id	sid	tid	token	lemma	pos
cana-729	1	1	communications	communication	NOUN
cana-729	1	2	on	on	ADP
cana-729	1	3	applied	apply	VERB
cana-729	1	4	nonlinear	nonlinear	ADJ
cana-729	1	5	analysis	analysis	NOUN
cana-729	1	6	issn	issn	NOUN
cana-729	1	7	:	:	PUNCT
cana-729	1	8	1074	1074	NUM
cana-729	1	9	-	-	PUNCT
cana-729	1	10	133x	133x	NUM
cana-729	1	11	vol	vol	NOUN
cana-729	1	12	31	31	NUM
cana-729	1	13	no	no	NOUN
cana-729	1	14	.	.	PUNCT
cana-729	2	1	3s	3s	NUM
cana-729	2	2	(	(	PUNCT
cana-729	2	3	2024	2024	NUM
cana-729	2	4	)	)	PUNCT
cana-729	2	5	29	29	NUM
cana-729	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-729	2	7	drought	drought	NOUN
cana-729	2	8	analysis	analysis	NOUN
cana-729	2	9	and	and	CCONJ
cana-729	2	10	forecasting	forecasting	NOUN
cana-729	2	11	in	in	ADP
cana-729	2	12	odisha	odisha	PROPN
cana-729	2	13	using	use	VERB
cana-729	2	14	machine	machine	NOUN
cana-729	2	15	learning	learn	VERB
cana-729	2	16	techniques	technique	NOUN
cana-729	2	17	neena	neena	PROPN
cana-729	2	18	uthaman1	uthaman1	PROPN
cana-729	2	19	,	,	PUNCT
cana-729	2	20	saroj	saroj	PROPN
cana-729	2	21	kumar	kumar	PROPN
cana-729	2	22	das2	das2	PROPN
cana-729	2	23	,	,	PUNCT
cana-729	2	24	kaibalya	kaibalya	ADV
cana-729	2	25	pattnaik2	pattnaik2	NOUN
cana-729	2	26	,	,	PUNCT
cana-729	2	27	s.dhanasekar2	s.dhanasekar2	PROPN
cana-729	2	28	*	*	PROPN
cana-729	2	29	1arab	1arab	NUM
cana-729	2	30	open	open	ADJ
cana-729	2	31	university	university	NOUN
cana-729	2	32	,	,	PUNCT
cana-729	2	33	oman	oman	PROPN
cana-729	2	34	school	school	NOUN
cana-729	2	35	of	of	ADP
cana-729	2	36	advanced	advanced	ADJ
cana-729	2	37	sciences	science	NOUN
cana-729	2	38	,	,	PUNCT
cana-729	2	39	vellore	vellore	PROPN
cana-729	2	40	institute	institute	PROPN
cana-729	2	41	of	of	ADP
cana-729	2	42	technology	technology	PROPN
cana-729	2	43	,	,	PUNCT
cana-729	2	44	chennai	chennai	PROPN
cana-729	2	45	neena.u@aou.edu.om	neena.u@aou.edu.om	PROPN
cana-729	2	46	sarojkumar.dash@vit.ac.in	sarojkumar.dash@vit.ac.in	NOUN
cana-729	2	47	dhanasekar.sundaram@vit.ac.in	dhanasekar.sundaram@vit.ac.in	NOUN
cana-729	2	48	article	article	NOUN
cana-729	2	49	history	history	NOUN
cana-729	2	50	:	:	PUNCT
cana-729	2	51	received	receive	VERB
cana-729	2	52	:	:	PUNCT
cana-729	2	53	05	05	NUM
cana-729	2	54	-	-	PUNCT
cana-729	2	55	04	04	NUM
cana-729	2	56	-	-	PUNCT
cana-729	2	57	2024	2024	NUM
cana-729	2	58	revised	revise	VERB
cana-729	2	59	:	:	PUNCT
cana-729	2	60	21	21	NUM
cana-729	2	61	-	-	SYM
cana-729	2	62	05	05	NUM
cana-729	2	63	-	-	PUNCT
cana-729	2	64	2024	2024	NUM
cana-729	2	65	accepted	accept	VERB
cana-729	2	66	:	:	PUNCT
cana-729	2	67	02	02	NUM
cana-729	2	68	-	-	PUNCT
cana-729	2	69	06	06	NUM
cana-729	2	70	-	-	PUNCT
cana-729	2	71	2024	2024	NUM
cana-729	2	72	abstract	abstract	NOUN
cana-729	2	73	:	:	PUNCT
cana-729	2	74	drought	drought	NOUN
cana-729	2	75	is	be	AUX
cana-729	2	76	a	a	DET
cana-729	2	77	natural	natural	ADJ
cana-729	2	78	phenomenon	phenomenon	NOUN
cana-729	2	79	that	that	PRON
cana-729	2	80	damages	damage	VERB
cana-729	2	81	agricultural	agricultural	ADJ
cana-729	2	82	land	land	NOUN
cana-729	2	83	severely	severely	ADV
cana-729	2	84	.	.	PUNCT
cana-729	3	1	the	the	DET
cana-729	3	2	severity	severity	NOUN
cana-729	3	3	of	of	ADP
cana-729	3	4	drought	drought	NOUN
cana-729	3	5	must	must	AUX
cana-729	3	6	be	be	AUX
cana-729	3	7	reduced	reduce	VERB
cana-729	3	8	to	to	PART
cana-729	3	9	decrease	decrease	VERB
cana-729	3	10	its	its	PRON
cana-729	3	11	impact	impact	NOUN
cana-729	3	12	on	on	ADP
cana-729	3	13	agricultural	agricultural	ADJ
cana-729	3	14	productivity	productivity	NOUN
cana-729	3	15	.	.	PUNCT
cana-729	4	1	the	the	DET
cana-729	4	2	study	study	NOUN
cana-729	4	3	of	of	ADP
cana-729	4	4	drought	drought	NOUN
cana-729	4	5	was	be	AUX
cana-729	4	6	carried	carry	VERB
cana-729	4	7	out	out	ADP
cana-729	4	8	for	for	ADP
cana-729	4	9	the	the	DET
cana-729	4	10	state	state	NOUN
cana-729	4	11	odisha	odisha	PROPN
cana-729	4	12	which	which	PRON
cana-729	4	13	experienced	experience	VERB
cana-729	4	14	drought	drought	NOUN
cana-729	4	15	8	8	NUM
cana-729	4	16	times	time	NOUN
cana-729	4	17	during	during	ADP
cana-729	4	18	the	the	DET
cana-729	4	19	last	last	ADJ
cana-729	4	20	20	20	NUM
cana-729	4	21	years	year	NOUN
cana-729	4	22	due	due	ADP
cana-729	4	23	to	to	ADP
cana-729	4	24	failure	failure	NOUN
cana-729	4	25	of	of	ADP
cana-729	4	26	monsoon	monsoon	NOUN
cana-729	4	27	.	.	PUNCT
cana-729	5	1	analysis	analysis	NOUN
cana-729	5	2	for	for	ADP
cana-729	5	3	the	the	DET
cana-729	5	4	data	datum	NOUN
cana-729	5	5	was	be	AUX
cana-729	5	6	explored	explore	VERB
cana-729	5	7	by	by	ADP
cana-729	5	8	explorative	explorative	ADJ
cana-729	5	9	analysis.the	analysis.the	DET
cana-729	5	10	drought	drought	NOUN
cana-729	5	11	forecasting	forecasting	NOUN
cana-729	5	12	was	be	AUX
cana-729	5	13	carried	carry	VERB
cana-729	5	14	out	out	ADP
cana-729	5	15	using	use	VERB
cana-729	5	16	machine	machine	NOUN
cana-729	5	17	learning	learning	NOUN
cana-729	5	18	techniques	technique	NOUN
cana-729	5	19	like	like	ADP
cana-729	5	20	the	the	DET
cana-729	5	21	auto	auto	NOUN
cana-729	5	22	-	-	PUNCT
cana-729	5	23	regressive	regressive	ADJ
cana-729	5	24	model	model	NOUN
cana-729	5	25	(	(	PUNCT
cana-729	5	26	ar	ar	NOUN
cana-729	5	27	)	)	PUNCT
cana-729	5	28	,	,	PUNCT
cana-729	6	1	long	long	ADJ
cana-729	6	2	short	short	ADJ
cana-729	6	3	-	-	PUNCT
cana-729	6	4	term	term	NOUN
cana-729	6	5	memory	memory	NOUN
cana-729	6	6	(	(	PUNCT
cana-729	6	7	lstm	lstm	NOUN
cana-729	6	8	)	)	PUNCT
cana-729	6	9	,	,	PUNCT
cana-729	6	10	and	and	CCONJ
cana-729	6	11	auto	auto	NOUN
cana-729	6	12	-	-	PUNCT
cana-729	6	13	regressive	regressive	ADJ
cana-729	6	14	integrated	integrated	ADJ
cana-729	6	15	moving	move	VERB
cana-729	6	16	average	average	ADJ
cana-729	6	17	(	(	PUNCT
cana-729	6	18	arima	arima	NOUN
cana-729	6	19	)	)	PUNCT
cana-729	6	20	using	use	VERB
cana-729	6	21	daily	daily	ADJ
cana-729	6	22	rainfall	rainfall	NOUN
cana-729	6	23	data	datum	NOUN
cana-729	6	24	collected	collect	VERB
cana-729	6	25	for	for	ADP
cana-729	6	26	28	28	NUM
cana-729	6	27	years	year	NOUN
cana-729	6	28	(	(	PUNCT
cana-729	6	29	19932020	19932020	NUM
cana-729	6	30	)	)	PUNCT
cana-729	6	31	.	.	PUNCT
cana-729	7	1	further	far	ADV
cana-729	7	2	using	use	VERB
cana-729	7	3	this	this	DET
cana-729	7	4	data	datum	NOUN
cana-729	7	5	each	each	DET
cana-729	7	6	district	district	NOUN
cana-729	7	7	was	be	AUX
cana-729	7	8	categorised	categorise	VERB
cana-729	7	9	into	into	ADP
cana-729	7	10	four	four	NUM
cana-729	7	11	different	different	ADJ
cana-729	7	12	categories	category	NOUN
cana-729	7	13	namely	namely	ADV
cana-729	7	14	flood	flood	NOUN
cana-729	7	15	(	(	PUNCT
cana-729	7	16	fl	fl	NOUN
cana-729	7	17	)	)	PUNCT
cana-729	7	18	,	,	PUNCT
cana-729	7	19	no	no	DET
cana-729	7	20	drought	drought	NOUN
cana-729	7	21	(	(	PUNCT
cana-729	7	22	nd	nd	NOUN
cana-729	7	23	)	)	PUNCT
cana-729	7	24	,	,	PUNCT
cana-729	7	25	moderate	moderate	ADJ
cana-729	7	26	drought	drought	NOUN
cana-729	7	27	(	(	PUNCT
cana-729	7	28	md	md	PROPN
cana-729	7	29	)	)	PUNCT
cana-729	7	30	,	,	PUNCT
cana-729	7	31	and	and	CCONJ
cana-729	7	32	severe	severe	ADJ
cana-729	7	33	drought	drought	NOUN
cana-729	7	34	(	(	PUNCT
cana-729	7	35	sd	sd	NOUN
cana-729	7	36	)	)	PUNCT
cana-729	7	37	.	.	PUNCT
cana-729	8	1	to	to	PART
cana-729	8	2	classify	classify	VERB
cana-729	8	3	the	the	DET
cana-729	8	4	districts	district	NOUN
cana-729	8	5	after	after	ADP
cana-729	8	6	forecasting	forecasting	NOUN
cana-729	8	7	,	,	PUNCT
cana-729	8	8	classification	classification	NOUN
cana-729	8	9	models	model	NOUN
cana-729	8	10	were	be	AUX
cana-729	8	11	used	use	VERB
cana-729	8	12	like	like	ADP
cana-729	8	13	support	support	NOUN
cana-729	8	14	vector	vector	NOUN
cana-729	8	15	classifier	classifier	NOUN
cana-729	8	16	(	(	PUNCT
cana-729	8	17	svc	svc	PROPN
cana-729	8	18	)	)	PUNCT
cana-729	8	19	and	and	CCONJ
cana-729	8	20	naïve	naïve	ADJ
cana-729	8	21	bayes	bayes	NOUN
cana-729	8	22	.	.	PUNCT
cana-729	9	1	the	the	DET
cana-729	9	2	results	result	NOUN
cana-729	9	3	of	of	ADP
cana-729	9	4	the	the	DET
cana-729	9	5	forecasting	forecasting	NOUN
cana-729	9	6	model	model	NOUN
cana-729	9	7	as	as	ADV
cana-729	9	8	well	well	ADV
cana-729	9	9	as	as	ADP
cana-729	9	10	the	the	DET
cana-729	9	11	classification	classification	NOUN
cana-729	9	12	model	model	NOUN
cana-729	9	13	were	be	AUX
cana-729	9	14	compared	compare	VERB
cana-729	9	15	.	.	PUNCT
cana-729	10	1	it	it	PRON
cana-729	10	2	becomes	become	VERB
cana-729	10	3	important	important	ADJ
cana-729	10	4	to	to	PART
cana-729	10	5	forecast	forecast	VERB
cana-729	10	6	drought	drought	NOUN
cana-729	10	7	for	for	ADP
cana-729	10	8	proper	proper	ADJ
cana-729	10	9	planning	planning	NOUN
cana-729	10	10	and	and	CCONJ
cana-729	10	11	management	management	NOUN
cana-729	10	12	of	of	ADP
cana-729	10	13	the	the	DET
cana-729	10	14	water	water	NOUN
cana-729	10	15	resource	resource	NOUN
cana-729	10	16	system	system	NOUN
cana-729	10	17	to	to	PART
cana-729	10	18	decrease	decrease	VERB
cana-729	10	19	the	the	DET
cana-729	10	20	damage	damage	NOUN
cana-729	10	21	due	due	ADP
cana-729	10	22	to	to	ADP
cana-729	10	23	such	such	ADJ
cana-729	10	24	calamities	calamity	NOUN
cana-729	10	25	.	.	PUNCT
cana-729	11	1	this	this	DET
cana-729	11	2	study	study	NOUN
cana-729	11	3	is	be	AUX
cana-729	11	4	valuable	valuable	ADJ
cana-729	11	5	for	for	SCONJ
cana-729	11	6	the	the	DET
cana-729	11	7	government	government	NOUN
cana-729	11	8	,	,	PUNCT
cana-729	11	9	farmers	farmer	NOUN
cana-729	11	10	,	,	PUNCT
cana-729	11	11	and	and	CCONJ
cana-729	11	12	other	other	ADJ
cana-729	11	13	stakeholders	stakeholder	NOUN
cana-729	11	14	to	to	PART
cana-729	11	15	understand	understand	VERB
cana-729	11	16	the	the	DET
cana-729	11	17	pattern	pattern	NOUN
cana-729	11	18	and	and	CCONJ
cana-729	11	19	reason	reason	NOUN
cana-729	11	20	behind	behind	ADP
cana-729	11	21	the	the	DET
cana-729	11	22	severity	severity	NOUN
cana-729	11	23	of	of	ADP
cana-729	11	24	drought	drought	NOUN
cana-729	11	25	to	to	PART
cana-729	11	26	take	take	VERB
cana-729	11	27	relevant	relevant	ADJ
cana-729	11	28	precautionary	precautionary	ADJ
cana-729	11	29	measures	measure	NOUN
cana-729	11	30	and	and	CCONJ
cana-729	11	31	improve	improve	VERB
cana-729	11	32	decisions	decision	NOUN
cana-729	11	33	and	and	CCONJ
cana-729	11	34	facilities	facility	NOUN
cana-729	11	35	to	to	PART
cana-729	11	36	tackle	tackle	VERB
cana-729	11	37	such	such	ADJ
cana-729	11	38	natural	natural	ADJ
cana-729	11	39	calamities	calamity	NOUN
cana-729	11	40	.	.	PUNCT
cana-729	12	1	keywords	keyword	NOUN
cana-729	12	2	:	:	PUNCT
cana-729	13	1	drought	drought	NOUN
cana-729	13	2	,	,	PUNCT
cana-729	13	3	long	long	ADJ
cana-729	13	4	short	short	ADJ
cana-729	13	5	-	-	PUNCT
cana-729	13	6	term	term	NOUN
cana-729	13	7	memory	memory	NOUN
cana-729	13	8	(	(	PUNCT
cana-729	13	9	lstm	lstm	NOUN
cana-729	13	10	)	)	PUNCT
cana-729	13	11	,	,	PUNCT
cana-729	13	12	auto	auto	NOUN
cana-729	13	13	-	-	PUNCT
cana-729	13	14	regressive	regressive	ADJ
cana-729	13	15	model	model	NOUN
cana-729	13	16	(	(	PUNCT
cana-729	13	17	ar	ar	NOUN
cana-729	13	18	)	)	PUNCT
cana-729	13	19	,	,	PUNCT
cana-729	13	20	autoregressive	autoregressive	ADJ
cana-729	13	21	integrated	integrated	ADJ
cana-729	13	22	moving	move	VERB
cana-729	13	23	average	average	ADJ
cana-729	13	24	(	(	PUNCT
cana-729	13	25	arima	arima	NOUN
cana-729	13	26	)	)	PUNCT
cana-729	13	27	and	and	CCONJ
cana-729	13	28	support	support	VERB
cana-729	13	29	vector	vector	NOUN
cana-729	13	30	classifier	classifier	NOUN
cana-729	13	31	(	(	PUNCT
cana-729	13	32	svc	svc	PROPN
cana-729	13	33	)	)	PUNCT
cana-729	13	34	,	,	PUNCT
cana-729	13	35	naïve	naïve	ADJ
cana-729	13	36	bayes	bayes	NOUN
cana-729	13	37	1	1	NUM
cana-729	13	38	.	.	PUNCT
cana-729	14	1	introduction	introduction	NOUN
cana-729	14	2	drought	drought	NOUN
cana-729	14	3	is	be	AUX
cana-729	14	4	a	a	DET
cana-729	14	5	type	type	NOUN
cana-729	14	6	of	of	ADP
cana-729	14	7	natural	natural	ADJ
cana-729	14	8	calamity	calamity	NOUN
cana-729	14	9	that	that	PRON
cana-729	14	10	occurs	occur	VERB
cana-729	14	11	due	due	ADJ
cana-729	14	12	to	to	ADP
cana-729	14	13	a	a	DET
cana-729	14	14	shortage	shortage	NOUN
cana-729	14	15	of	of	ADP
cana-729	14	16	water	water	NOUN
cana-729	14	17	supply	supply	NOUN
cana-729	14	18	,	,	PUNCT
cana-729	14	19	whether	whether	SCONJ
cana-729	14	20	it	it	PRON
cana-729	14	21	is	be	AUX
cana-729	14	22	due	due	ADJ
cana-729	14	23	to	to	ADP
cana-729	14	24	precipitation	precipitation	NOUN
cana-729	14	25	below	below	ADP
cana-729	14	26	average	average	ADJ
cana-729	14	27	,	,	PUNCT
cana-729	14	28	low	low	ADJ
cana-729	14	29	surface	surface	NOUN
cana-729	14	30	water	water	NOUN
cana-729	14	31	,	,	PUNCT
cana-729	14	32	or	or	CCONJ
cana-729	14	33	groundwater	groundwater	NOUN
cana-729	14	34	.	.	PUNCT
cana-729	15	1	drought	drought	NOUN
cana-729	15	2	can	can	AUX
cana-729	15	3	be	be	AUX
cana-729	15	4	long	long	ADJ
cana-729	15	5	-	-	PUNCT
cana-729	15	6	term	term	NOUN
cana-729	15	7	and	and	CCONJ
cana-729	15	8	lasts	last	VERB
cana-729	15	9	for	for	ADP
cana-729	15	10	months	month	NOUN
cana-729	15	11	and	and	CCONJ
cana-729	15	12	years	year	NOUN
cana-729	15	13	or	or	CCONJ
cana-729	15	14	it	it	PRON
cana-729	15	15	can	can	AUX
cana-729	15	16	be	be	AUX
cana-729	15	17	short	short	ADJ
cana-729	15	18	-	-	PUNCT
cana-729	15	19	term	term	NOUN
cana-729	15	20	that	that	PRON
cana-729	15	21	lasts	last	VERB
cana-729	15	22	even	even	ADV
cana-729	15	23	for	for	ADP
cana-729	15	24	15	15	NUM
cana-729	15	25	days	day	NOUN
cana-729	15	26	.	.	PUNCT
cana-729	16	1	droughts	drought	NOUN
cana-729	16	2	are	be	AUX
cana-729	16	3	divided	divide	VERB
cana-729	16	4	into	into	ADP
cana-729	16	5	three	three	NUM
cana-729	16	6	categories	category	NOUN
cana-729	16	7	:	:	PUNCT
cana-729	16	8	meteorological	meteorological	ADJ
cana-729	16	9	droughts	drought	NOUN
cana-729	16	10	,	,	PUNCT
cana-729	16	11	hydrological	hydrological	ADJ
cana-729	16	12	droughts	drought	NOUN
cana-729	16	13	,	,	PUNCT
cana-729	16	14	and	and	CCONJ
cana-729	16	15	agricultural	agricultural	ADJ
cana-729	16	16	droughts	drought	NOUN
cana-729	16	17	.	.	PUNCT
cana-729	17	1	meteorological	meteorological	ADJ
cana-729	17	2	droughts	drought	NOUN
cana-729	17	3	are	be	AUX
cana-729	17	4	based	base	VERB
cana-729	17	5	on	on	ADP
cana-729	17	6	the	the	DET
cana-729	17	7	precipitation	precipitation	NOUN
cana-729	17	8	or	or	CCONJ
cana-729	17	9	the	the	DET
cana-729	17	10	degree	degree	NOUN
cana-729	17	11	of	of	ADP
cana-729	17	12	dryness	dryness	NOUN
cana-729	17	13	.	.	PUNCT
cana-729	18	1	it	it	PRON
cana-729	18	2	is	be	AUX
cana-729	18	3	considered	consider	VERB
cana-729	18	4	as	as	SCONJ
cana-729	18	5	region	region	NOUN
cana-729	18	6	-	-	PUNCT
cana-729	18	7	specific	specific	NOUN
cana-729	18	8	as	as	ADP
cana-729	18	9	the	the	DET
cana-729	18	10	precipitation	precipitation	NOUN
cana-729	18	11	that	that	PRON
cana-729	18	12	depends	depend	VERB
cana-729	18	13	on	on	ADP
cana-729	18	14	the	the	DET
cana-729	18	15	atmospheric	atmospheric	ADJ
cana-729	18	16	condition	condition	NOUN
cana-729	18	17	varies	vary	VERB
cana-729	18	18	from	from	ADP
cana-729	18	19	region	region	NOUN
cana-729	18	20	to	to	ADP
cana-729	18	21	region	region	NOUN
cana-729	18	22	.	.	PUNCT
cana-729	19	1	whereas	whereas	SCONJ
cana-729	19	2	hydrological	hydrological	ADJ
cana-729	19	3	droughts	drought	NOUN
cana-729	19	4	are	be	AUX
cana-729	19	5	based	base	VERB
cana-729	19	6	on	on	ADP
cana-729	19	7	the	the	DET
cana-729	19	8	water	water	NOUN
cana-729	19	9	supply	supply	NOUN
cana-729	19	10	like	like	ADP
cana-729	19	11	groundwater	groundwater	NOUN
cana-729	19	12	table	table	NOUN
cana-729	19	13	decline	decline	NOUN
cana-729	19	14	,	,	PUNCT
cana-729	19	15	stream	stream	NOUN
cana-729	19	16	flow	flow	NOUN
cana-729	19	17	,	,	PUNCT
cana-729	19	18	and	and	CCONJ
cana-729	19	19	reservoir	reservoir	NOUN
cana-729	19	20	.	.	PUNCT
cana-729	20	1	agricultural	agricultural	ADJ
cana-729	20	2	droughts	drought	NOUN
cana-729	20	3	are	be	AUX
cana-729	20	4	related	relate	VERB
cana-729	20	5	to	to	ADP
cana-729	20	6	both	both	CCONJ
cana-729	20	7	meteorological	meteorological	ADJ
cana-729	20	8	and	and	CCONJ
cana-729	20	9	hydrological	hydrological	ADJ
cana-729	20	10	droughts	drought	NOUN
cana-729	20	11	to	to	ADP
cana-729	20	12	the	the	DET
cana-729	20	13	agricultural	agricultural	ADJ
cana-729	20	14	impact	impact	NOUN
cana-729	20	15	.	.	PUNCT
cana-729	21	1	drought	drought	NOUN
cana-729	21	2	has	have	VERB
cana-729	21	3	a	a	DET
cana-729	21	4	great	great	ADJ
cana-729	21	5	impact	impact	NOUN
cana-729	21	6	on	on	ADP
cana-729	21	7	agricultural	agricultural	ADJ
cana-729	21	8	production	production	NOUN
cana-729	21	9	,	,	PUNCT
cana-729	21	10	which	which	PRON
cana-729	21	11	further	far	ADV
cana-729	21	12	brings	bring	VERB
cana-729	21	13	down	down	ADP
cana-729	21	14	the	the	DET
cana-729	21	15	economy	economy	NOUN
cana-729	21	16	of	of	ADP
cana-729	21	17	that	that	DET
cana-729	21	18	area	area	NOUN
cana-729	21	19	.	.	PUNCT
cana-729	22	1	as	as	SCONJ
cana-729	22	2	drought	drought	NOUN
cana-729	22	3	causes	cause	VERB
cana-729	22	4	water	water	NOUN
cana-729	22	5	and	and	CCONJ
cana-729	22	6	food	food	NOUN
cana-729	22	7	shortages	shortage	NOUN
cana-729	22	8	,	,	PUNCT
cana-729	22	9	it	it	PRON
cana-729	22	10	has	have	VERB
cana-729	22	11	a	a	DET
cana-729	22	12	direct	direct	ADJ
cana-729	22	13	impact	impact	NOUN
cana-729	22	14	on	on	ADP
cana-729	22	15	the	the	DET
cana-729	22	16	affected	affected	ADJ
cana-729	22	17	population	population	NOUN
cana-729	22	18	's	's	PART
cana-729	22	19	health	health	NOUN
cana-729	22	20	,	,	PUNCT
cana-729	22	21	increasing	increase	VERB
cana-729	22	22	the	the	DET
cana-729	22	23	risk	risk	NOUN
cana-729	22	24	of	of	ADP
cana-729	22	25	acute	acute	ADJ
cana-729	22	26	and	and	CCONJ
cana-729	22	27	chronic	chronic	ADJ
cana-729	22	28	illness	illness	NOUN
cana-729	22	29	,	,	PUNCT
cana-729	22	30	as	as	ADV
cana-729	22	31	well	well	ADV
cana-729	22	32	as	as	ADP
cana-729	22	33	mortality	mortality	NOUN
cana-729	22	34	.	.	PUNCT
cana-729	23	1	diseases	disease	NOUN
cana-729	23	2	like	like	ADP
cana-729	23	3	anaemia	anaemia	NOUN
cana-729	23	4	(	(	PUNCT
cana-729	23	5	iron	iron	NOUN
cana-729	23	6	deficiency	deficiency	NOUN
cana-729	23	7	disease	disease	NOUN
cana-729	23	8	)	)	PUNCT
cana-729	23	9	are	be	AUX
cana-729	23	10	seen	see	VERB
cana-729	23	11	in	in	ADP
cana-729	23	12	drought	drought	NOUN
cana-729	23	13	-	-	PUNCT
cana-729	23	14	affected	affect	VERB
cana-729	23	15	areas	area	NOUN
cana-729	23	16	due	due	ADJ
cana-729	23	17	to	to	ADP
cana-729	23	18	malnutrition	malnutrition	NOUN
cana-729	23	19	as	as	SCONJ
cana-729	23	20	the	the	DET
cana-729	23	21	availability	availability	NOUN
cana-729	23	22	of	of	ADP
cana-729	23	23	food	food	NOUN
cana-729	23	24	decreases	decrease	NOUN
cana-729	23	25	in	in	ADP
cana-729	23	26	such	such	ADJ
cana-729	23	27	areas	area	NOUN
cana-729	23	28	.	.	PUNCT
cana-729	24	1	even	even	ADV
cana-729	24	2	there	there	PRON
cana-729	24	3	’s	’	VERB
cana-729	24	4	a	a	DET
cana-729	24	5	risk	risk	NOUN
cana-729	24	6	of	of	ADP
cana-729	24	7	infectious	infectious	ADJ
cana-729	24	8	diseases	disease	NOUN
cana-729	24	9	like	like	ADP
cana-729	24	10	diarrhoea	diarrhoea	NOUN
cana-729	24	11	,	,	PUNCT
cana-729	24	12	pneumonia	pneumonia	NOUN
cana-729	24	13	due	due	ADP
cana-729	24	14	to	to	ADP
cana-729	24	15	communications	communication	NOUN
cana-729	24	16	on	on	ADP
cana-729	24	17	applied	apply	VERB
cana-729	24	18	nonlinear	nonlinear	ADJ
cana-729	24	19	analysis	analysis	NOUN
cana-729	24	20	issn	issn	NOUN
cana-729	24	21	:	:	PUNCT
cana-729	24	22	1074	1074	NUM
cana-729	24	23	-	-	PUNCT
cana-729	24	24	133x	133x	NUM
cana-729	24	25	vol	vol	NOUN
cana-729	24	26	31	31	NUM
cana-729	24	27	no	no	NOUN
cana-729	24	28	.	.	PUNCT
cana-729	25	1	3s	3s	NUM
cana-729	25	2	(	(	PUNCT
cana-729	25	3	2024	2024	NUM
cana-729	25	4	)	)	PUNCT
cana-729	25	5	30	30	NUM
cana-729	25	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-729	25	7	displacement	displacement	NOUN
cana-729	25	8	,	,	PUNCT
cana-729	25	9	acute	acute	ADJ
cana-729	25	10	malnutrition	malnutrition	NOUN
cana-729	25	11	and	and	CCONJ
cana-729	25	12	lack	lack	NOUN
cana-729	25	13	of	of	ADP
cana-729	25	14	water	water	NOUN
cana-729	25	15	and	and	CCONJ
cana-729	25	16	sanitation	sanitation	NOUN
cana-729	25	17	.	.	PUNCT
cana-729	26	1	people	people	NOUN
cana-729	26	2	also	also	ADV
cana-729	26	3	suffer	suffer	VERB
cana-729	26	4	from	from	ADP
cana-729	26	5	mental	mental	ADJ
cana-729	26	6	health	health	NOUN
cana-729	26	7	and	and	CCONJ
cana-729	26	8	psychological	psychological	ADJ
cana-729	26	9	social	social	ADJ
cana-729	26	10	stress	stress	NOUN
cana-729	26	11	.	.	PUNCT
cana-729	27	1	drought	drought	NOUN
cana-729	27	2	may	may	AUX
cana-729	27	3	trigger	trigger	VERB
cana-729	27	4	wildfires	wildfire	NOUN
cana-729	27	5	and	and	CCONJ
cana-729	27	6	dust	dust	NOUN
cana-729	27	7	storms	storm	NOUN
cana-729	27	8	,	,	PUNCT
cana-729	27	9	lowering	lower	VERB
cana-729	27	10	air	air	NOUN
cana-729	27	11	quality	quality	NOUN
cana-729	27	12	and	and	CCONJ
cana-729	27	13	increasing	increase	VERB
cana-729	27	14	the	the	DET
cana-729	27	15	risk	risk	NOUN
cana-729	27	16	of	of	ADP
cana-729	27	17	lung	lung	NOUN
cana-729	27	18	disorders	disorder	NOUN
cana-729	27	19	such	such	ADJ
cana-729	27	20	as	as	ADP
cana-729	27	21	asthma	asthma	NOUN
cana-729	27	22	as	as	ADV
cana-729	27	23	well	well	ADV
cana-729	27	24	as	as	ADP
cana-729	27	25	heart	heart	NOUN
cana-729	27	26	disease	disease	NOUN
cana-729	27	27	.	.	PUNCT
cana-729	28	1	every	every	DET
cana-729	28	2	year	year	NOUN
cana-729	28	3	,	,	PUNCT
cana-729	28	4	drought	drought	NOUN
cana-729	28	5	affects	affect	VERB
cana-729	28	6	55	55	NUM
cana-729	28	7	million	million	NUM
cana-729	28	8	people	people	NOUN
cana-729	28	9	throughout	throughout	ADP
cana-729	28	10	the	the	DET
cana-729	28	11	world	world	NOUN
cana-729	28	12	.	.	PUNCT
cana-729	29	1	it	it	PRON
cana-729	29	2	poses	pose	VERB
cana-729	29	3	a	a	DET
cana-729	29	4	significant	significant	ADJ
cana-729	29	5	threat	threat	NOUN
cana-729	29	6	to	to	ADP
cana-729	29	7	crops	crop	NOUN
cana-729	29	8	and	and	CCONJ
cana-729	29	9	cattle	cattle	NOUN
cana-729	29	10	across	across	ADP
cana-729	29	11	the	the	DET
cana-729	29	12	world	world	NOUN
cana-729	29	13	.	.	PUNCT
cana-729	30	1	drought	drought	NOUN
cana-729	30	2	raises	raise	VERB
cana-729	30	3	the	the	DET
cana-729	30	4	risk	risk	NOUN
cana-729	30	5	of	of	ADP
cana-729	30	6	infections	infection	NOUN
cana-729	30	7	,	,	PUNCT
cana-729	30	8	shortages	shortage	NOUN
cana-729	30	9	of	of	ADP
cana-729	30	10	fuel	fuel	NOUN
cana-729	30	11	,	,	PUNCT
cana-729	30	12	and	and	CCONJ
cana-729	30	13	mass	mass	NOUN
cana-729	30	14	migration	migration	NOUN
cana-729	30	15	.	.	PUNCT
cana-729	31	1	water	water	NOUN
cana-729	31	2	scarcity	scarcity	NOUN
cana-729	31	3	affects	affect	VERB
cana-729	31	4	40	40	NUM
cana-729	31	5	per	per	ADP
cana-729	31	6	cent	cent	NOUN
cana-729	31	7	of	of	ADP
cana-729	31	8	the	the	DET
cana-729	31	9	world	world	NOUN
cana-729	31	10	's	's	PART
cana-729	31	11	population	population	NOUN
cana-729	31	12	and	and	CCONJ
cana-729	31	13	an	an	DET
cana-729	31	14	estimated	estimate	VERB
cana-729	31	15	700	700	NUM
cana-729	31	16	million	million	NUM
cana-729	31	17	people	people	NOUN
cana-729	31	18	are	be	AUX
cana-729	31	19	at	at	ADP
cana-729	31	20	risk	risk	NOUN
cana-729	31	21	of	of	ADP
cana-729	31	22	displacing	displace	VERB
cana-729	31	23	by	by	ADP
cana-729	31	24	drought	drought	NOUN
cana-729	31	25	by	by	ADP
cana-729	31	26	2030	2030	NUM
cana-729	31	27	.	.	PUNCT
cana-729	32	1	due	due	ADP
cana-729	32	2	to	to	ADP
cana-729	32	3	rising	rise	VERB
cana-729	32	4	temperatures	temperature	NOUN
cana-729	32	5	,	,	PUNCT
cana-729	32	6	water	water	NOUN
cana-729	32	7	evaporates	evaporates	AUX
cana-729	32	8	more	more	ADV
cana-729	32	9	quickly	quickly	ADV
cana-729	32	10	making	make	VERB
cana-729	32	11	dry	dry	ADJ
cana-729	32	12	regions	region	NOUN
cana-729	32	13	drier	dry	ADJ
cana-729	32	14	and	and	CCONJ
cana-729	32	15	wet	wet	ADJ
cana-729	32	16	regions	region	NOUN
cana-729	32	17	wetter	wetter	ADV
cana-729	32	18	,	,	PUNCT
cana-729	32	19	so	so	SCONJ
cana-729	32	20	it	it	PRON
cana-729	32	21	increases	increase	VERB
cana-729	32	22	the	the	DET
cana-729	32	23	risk	risk	NOUN
cana-729	32	24	of	of	ADP
cana-729	32	25	droughts	drought	NOUN
cana-729	32	26	in	in	ADP
cana-729	32	27	dry	dry	ADJ
cana-729	32	28	areas	area	NOUN
cana-729	32	29	and	and	CCONJ
cana-729	32	30	floods	flood	NOUN
cana-729	32	31	in	in	ADP
cana-729	32	32	wet	wet	ADJ
cana-729	32	33	areas	area	NOUN
cana-729	32	34	.	.	PUNCT
cana-729	33	1	most	most	ADJ
cana-729	33	2	of	of	ADP
cana-729	33	3	the	the	DET
cana-729	33	4	disasters	disaster	NOUN
cana-729	33	5	that	that	PRON
cana-729	33	6	have	have	AUX
cana-729	33	7	been	be	AUX
cana-729	33	8	recorded	record	VERB
cana-729	33	9	in	in	ADP
cana-729	33	10	the	the	DET
cana-729	33	11	past	past	ADJ
cana-729	33	12	10	10	NUM
cana-729	33	13	years	year	NOUN
cana-729	33	14	are	be	AUX
cana-729	33	15	from	from	ADP
cana-729	33	16	floods	flood	NOUN
cana-729	33	17	,	,	PUNCT
cana-729	33	18	droughts	drought	NOUN
cana-729	33	19	,	,	PUNCT
cana-729	33	20	heat	heat	NOUN
cana-729	33	21	waves	wave	NOUN
cana-729	33	22	and	and	CCONJ
cana-729	33	23	severe	severe	ADJ
cana-729	33	24	storms	storm	NOUN
cana-729	33	25	.	.	PUNCT
cana-729	34	1	numerous	numerous	ADJ
cana-729	34	2	investigators	investigator	NOUN
cana-729	34	3	have	have	AUX
cana-729	34	4	demonstrated	demonstrate	VERB
cana-729	34	5	that	that	SCONJ
cana-729	34	6	anthropogenic	anthropogenic	ADJ
cana-729	34	7	influence	influence	NOUN
cana-729	34	8	produces	produce	VERB
cana-729	34	9	major	major	ADJ
cana-729	34	10	changes	change	NOUN
cana-729	34	11	in	in	ADP
cana-729	34	12	the	the	DET
cana-729	34	13	trends	trend	NOUN
cana-729	34	14	and	and	CCONJ
cana-729	34	15	variability	variability	NOUN
cana-729	34	16	of	of	ADP
cana-729	34	17	climate	climate	NOUN
cana-729	34	18	indicators	indicator	NOUN
cana-729	34	19	[	[	X
cana-729	34	20	32	32	NUM
cana-729	34	21	]	]	PUNCT
cana-729	34	22	.	.	PUNCT
cana-729	35	1	according	accord	VERB
cana-729	35	2	to	to	ADP
cana-729	35	3	their	their	PRON
cana-729	35	4	research	research	NOUN
cana-729	35	5	,	,	PUNCT
cana-729	35	6	the	the	DET
cana-729	35	7	countries	country	NOUN
cana-729	35	8	in	in	ADP
cana-729	35	9	southern	southern	ADJ
cana-729	35	10	asia	asia	PROPN
cana-729	35	11	are	be	AUX
cana-729	35	12	the	the	DET
cana-729	35	13	most	most	ADV
cana-729	35	14	susceptible	susceptible	ADJ
cana-729	35	15	to	to	ADP
cana-729	35	16	the	the	DET
cana-729	35	17	current	current	ADJ
cana-729	35	18	global	global	ADJ
cana-729	35	19	warming	warming	NOUN
cana-729	35	20	,	,	PUNCT
cana-729	35	21	and	and	CCONJ
cana-729	35	22	the	the	DET
cana-729	35	23	effects	effect	NOUN
cana-729	35	24	of	of	ADP
cana-729	35	25	major	major	ADJ
cana-729	35	26	hazard	hazard	NOUN
cana-729	35	27	occurrences	occurrence	NOUN
cana-729	35	28	like	like	ADP
cana-729	35	29	droughts	drought	NOUN
cana-729	35	30	pose	pose	VERB
cana-729	35	31	a	a	DET
cana-729	35	32	growing	grow	VERB
cana-729	35	33	threat	threat	NOUN
cana-729	35	34	to	to	ADP
cana-729	35	35	india	india	PROPN
cana-729	35	36	.	.	PUNCT
cana-729	36	1	thus	thus	ADV
cana-729	36	2	,	,	PUNCT
cana-729	36	3	odisha	odisha	PROPN
cana-729	36	4	,	,	PUNCT
cana-729	36	5	which	which	PRON
cana-729	36	6	is	be	AUX
cana-729	36	7	situated	situate	VERB
cana-729	36	8	on	on	ADP
cana-729	36	9	india	india	PROPN
cana-729	36	10	's	's	PART
cana-729	36	11	eastern	eastern	ADJ
cana-729	36	12	coast	coast	NOUN
cana-729	36	13	,	,	PUNCT
cana-729	36	14	is	be	AUX
cana-729	36	15	susceptible	susceptible	ADJ
cana-729	36	16	to	to	ADP
cana-729	36	17	frequent	frequent	ADJ
cana-729	36	18	extreme	extreme	ADJ
cana-729	36	19	weather	weather	NOUN
cana-729	36	20	occurrences	occurrence	NOUN
cana-729	36	21	like	like	ADP
cana-729	36	22	cyclones	cyclone	NOUN
cana-729	36	23	,	,	PUNCT
cana-729	36	24	floods	flood	NOUN
cana-729	36	25	,	,	PUNCT
cana-729	36	26	and	and	CCONJ
cana-729	36	27	droughts	drought	NOUN
cana-729	36	28	[	[	X
cana-729	36	29	33,34	33,34	NOUN
cana-729	36	30	]	]	PUNCT
cana-729	36	31	.	.	PUNCT
cana-729	37	1	odisha	odisha	PROPN
cana-729	37	2	was	be	AUX
cana-729	37	3	the	the	DET
cana-729	37	4	most	most	ADV
cana-729	37	5	vulnerable	vulnerable	ADJ
cana-729	37	6	state	state	NOUN
cana-729	37	7	in	in	ADP
cana-729	37	8	india	india	PROPN
cana-729	37	9	in	in	ADP
cana-729	37	10	terms	term	NOUN
cana-729	37	11	of	of	ADP
cana-729	37	12	climate	climate	NOUN
cana-729	37	13	extremes	extreme	NOUN
cana-729	37	14	,	,	PUNCT
cana-729	37	15	as	as	SCONJ
cana-729	37	16	demonstrated	demonstrate	VERB
cana-729	37	17	by	by	ADP
cana-729	37	18	[	[	X
cana-729	37	19	35	35	NUM
cana-729	37	20	]	]	PUNCT
cana-729	37	21	from	from	ADP
cana-729	37	22	1951	1951	NUM
cana-729	37	23	to	to	ADP
cana-729	37	24	2010	2010	NUM
cana-729	37	25	,	,	PUNCT
cana-729	37	26	the	the	DET
cana-729	37	27	state	state	NOUN
cana-729	37	28	experienced	experience	VERB
cana-729	37	29	35	35	NUM
cana-729	37	30	years	year	NOUN
cana-729	37	31	of	of	ADP
cana-729	37	32	floods	flood	NOUN
cana-729	37	33	,	,	PUNCT
cana-729	37	34	22	22	NUM
cana-729	37	35	years	year	NOUN
cana-729	37	36	of	of	ADP
cana-729	37	37	droughts	drought	NOUN
cana-729	37	38	,	,	PUNCT
cana-729	37	39	and	and	CCONJ
cana-729	37	40	8	8	NUM
cana-729	37	41	years	year	NOUN
cana-729	37	42	of	of	ADP
cana-729	37	43	cyclones	cyclone	NOUN
cana-729	37	44	.	.	PUNCT
cana-729	38	1	consequently	consequently	ADV
cana-729	38	2	,	,	PUNCT
cana-729	38	3	it	it	PRON
cana-729	38	4	is	be	AUX
cana-729	38	5	necessary	necessary	ADJ
cana-729	38	6	and	and	CCONJ
cana-729	38	7	relevant	relevant	ADJ
cana-729	38	8	to	to	PART
cana-729	38	9	develop	develop	VERB
cana-729	38	10	studies	study	NOUN
cana-729	38	11	and	and	CCONJ
cana-729	38	12	monitoring	monitoring	NOUN
cana-729	38	13	in	in	ADP
cana-729	38	14	this	this	DET
cana-729	38	15	agroeconomic	agroeconomic	ADJ
cana-729	38	16	state	state	NOUN
cana-729	38	17	,	,	PUNCT
cana-729	38	18	such	such	ADJ
cana-729	38	19	as	as	ADP
cana-729	38	20	those	those	PRON
cana-729	38	21	of	of	ADP
cana-729	38	22	[	[	X
cana-729	38	23	36	36	NUM
cana-729	38	24	]	]	PUNCT
cana-729	38	25	,	,	PUNCT
cana-729	38	26	[	[	X
cana-729	38	27	37],[38	37],[38	NOUN
cana-729	38	28	]	]	PUNCT
cana-729	38	29	,	,	PUNCT
cana-729	39	1	[	[	X
cana-729	39	2	39	39	NUM
cana-729	39	3	]	]	PUNCT
cana-729	39	4	and	and	CCONJ
cana-729	39	5	[	[	X
cana-729	39	6	40	40	NUM
cana-729	39	7	]	]	PUNCT
cana-729	39	8	.	.	PUNCT
cana-729	40	1	odisha	odisha	PROPN
cana-729	40	2	has	have	VERB
cana-729	40	3	61,80,000	61,80,000	NUM
cana-729	40	4	hectares	hectare	NOUN
cana-729	40	5	of	of	ADP
cana-729	40	6	cultivated	cultivate	VERB
cana-729	40	7	land	land	NOUN
cana-729	40	8	out	out	ADP
cana-729	40	9	of	of	ADP
cana-729	40	10	1,55,707	1,55,707	NOUN
cana-729	40	11	square	square	ADJ
cana-729	40	12	kilometres	kilometre	NOUN
cana-729	40	13	of	of	ADP
cana-729	40	14	geographical	geographical	ADJ
cana-729	40	15	area	area	NOUN
cana-729	40	16	.	.	PUNCT
cana-729	41	1	natural	natural	ADJ
cana-729	41	2	disasters	disaster	NOUN
cana-729	41	3	like	like	ADP
cana-729	41	4	drought	drought	NOUN
cana-729	41	5	,	,	PUNCT
cana-729	41	6	flood	flood	NOUN
cana-729	41	7	,	,	PUNCT
cana-729	41	8	and	and	CCONJ
cana-729	41	9	storms	storm	NOUN
cana-729	41	10	have	have	AUX
cana-729	41	11	significantly	significantly	ADV
cana-729	41	12	impacted	impact	VERB
cana-729	41	13	the	the	DET
cana-729	41	14	state	state	NOUN
cana-729	41	15	's	's	PART
cana-729	41	16	economy	economy	NOUN
cana-729	41	17	over	over	ADP
cana-729	41	18	the	the	DET
cana-729	41	19	ages	age	NOUN
cana-729	41	20	.	.	PUNCT
cana-729	42	1	for	for	ADP
cana-729	42	2	41	41	NUM
cana-729	42	3	years	year	NOUN
cana-729	42	4	in	in	ADP
cana-729	42	5	the	the	DET
cana-729	42	6	last	last	ADJ
cana-729	42	7	50	50	NUM
cana-729	42	8	years	year	NOUN
cana-729	42	9	,	,	PUNCT
cana-729	42	10	the	the	DET
cana-729	42	11	state	state	NOUN
cana-729	42	12	has	have	AUX
cana-729	42	13	been	be	AUX
cana-729	42	14	plagued	plague	VERB
cana-729	42	15	by	by	ADP
cana-729	42	16	natural	natural	ADJ
cana-729	42	17	disasters	disaster	NOUN
cana-729	42	18	,	,	PUNCT
cana-729	42	19	for	for	ADP
cana-729	42	20	19	19	NUM
cana-729	42	21	years	year	NOUN
cana-729	42	22	,	,	PUNCT
cana-729	42	23	it	it	PRON
cana-729	42	24	has	have	AUX
cana-729	42	25	been	be	AUX
cana-729	42	26	hit	hit	VERB
cana-729	42	27	by	by	ADP
cana-729	42	28	drought	drought	NOUN
cana-729	42	29	.	.	PUNCT
cana-729	43	1	droughts	drought	NOUN
cana-729	43	2	cause	cause	VERB
cana-729	43	3	a	a	DET
cana-729	43	4	severe	severe	ADJ
cana-729	43	5	decline	decline	NOUN
cana-729	43	6	in	in	ADP
cana-729	43	7	agricultural	agricultural	ADJ
cana-729	43	8	productivity	productivity	NOUN
cana-729	43	9	,	,	PUNCT
cana-729	43	10	thus	thus	ADV
cana-729	43	11	reducing	reduce	VERB
cana-729	43	12	a	a	DET
cana-729	43	13	farmer	farmer	NOUN
cana-729	43	14	's	's	PART
cana-729	43	15	revenue	revenue	NOUN
cana-729	43	16	.	.	PUNCT
cana-729	44	1	even	even	ADV
cana-729	44	2	rural	rural	ADJ
cana-729	44	3	job	job	NOUN
cana-729	44	4	options	option	NOUN
cana-729	44	5	,	,	PUNCT
cana-729	44	6	such	such	ADJ
cana-729	44	7	as	as	ADP
cana-729	44	8	agricultural	agricultural	ADJ
cana-729	44	9	labour	labour	NOUN
cana-729	44	10	,	,	PUNCT
cana-729	44	11	rural	rural	ADJ
cana-729	44	12	craftsmen	craftsman	NOUN
cana-729	44	13	,	,	PUNCT
cana-729	44	14	and	and	CCONJ
cana-729	44	15	small	small	ADJ
cana-729	44	16	rural	rural	ADJ
cana-729	44	17	companies	company	NOUN
cana-729	44	18	,	,	PUNCT
cana-729	44	19	are	be	AUX
cana-729	44	20	substantially	substantially	ADV
cana-729	44	21	impacted	impact	VERB
cana-729	44	22	.	.	PUNCT
cana-729	45	1	drought	drought	NOUN
cana-729	45	2	in	in	ADP
cana-729	45	3	odisha	odisha	PROPN
cana-729	45	4	generally	generally	ADV
cana-729	45	5	occurs	occur	VERB
cana-729	45	6	during	during	ADP
cana-729	45	7	the	the	DET
cana-729	45	8	month	month	NOUN
cana-729	45	9	of	of	ADP
cana-729	45	10	june	june	PROPN
cana-729	45	11	to	to	ADP
cana-729	45	12	october	october	PROPN
cana-729	45	13	that	that	PRON
cana-729	45	14	is	be	AUX
cana-729	45	15	during	during	ADP
cana-729	45	16	the	the	DET
cana-729	45	17	kharif	kharif	NOUN
cana-729	45	18	season	season	NOUN
cana-729	45	19	and	and	CCONJ
cana-729	45	20	greatly	greatly	ADV
cana-729	45	21	affects	affect	VERB
cana-729	45	22	the	the	DET
cana-729	45	23	paddy	paddy	NOUN
cana-729	45	24	crops	crop	NOUN
cana-729	45	25	.	.	PUNCT
cana-729	46	1	districts	district	NOUN
cana-729	46	2	like	like	ADP
cana-729	46	3	bolangir	bolangir	NOUN
cana-729	46	4	,	,	PUNCT
cana-729	46	5	rayagada	rayagada	PROPN
cana-729	46	6	,	,	PUNCT
cana-729	46	7	kalahandi	kalahandi	PROPN
cana-729	46	8	,	,	PUNCT
cana-729	46	9	malkangiri	malkangiri	NOUN
cana-729	46	10	,	,	PUNCT
cana-729	46	11	nuapada	nuapada	PROPN
cana-729	46	12	,	,	PUNCT
cana-729	46	13	sonepur	sonepur	NOUN
cana-729	46	14	,	,	PUNCT
cana-729	46	15	nabarangpur	nabarangpur	PROPN
cana-729	46	16	and	and	CCONJ
cana-729	46	17	koraput	koraput	NOUN
cana-729	46	18	which	which	PRON
cana-729	46	19	include	include	VERB
cana-729	46	20	47	47	NUM
cana-729	46	21	blocks	block	NOUN
cana-729	46	22	are	be	AUX
cana-729	46	23	drought	drought	NOUN
cana-729	46	24	-	-	PUNCT
cana-729	46	25	prone	prone	ADJ
cana-729	46	26	districts	district	NOUN
cana-729	46	27	in	in	ADP
cana-729	46	28	odisha	odisha	PROPN
cana-729	46	29	.	.	PUNCT
cana-729	47	1	2	2	X
cana-729	47	2	.	.	X
cana-729	47	3	objectives	objective	NOUN
cana-729	47	4	antenesh	antenesh	ADJ
cana-729	47	5	belayneh	belayneh	NOUN
cana-729	47	6	and	and	CCONJ
cana-729	47	7	jan	jan	PROPN
cana-729	47	8	adamowski	adamowski	PROPN
cana-729	47	9	investigated	investigate	VERB
cana-729	47	10	machine	machine	NOUN
cana-729	47	11	learning	learn	VERB
cana-729	47	12	techniques	technique	NOUN
cana-729	47	13	in	in	ADP
cana-729	47	14	the	the	DET
cana-729	47	15	awash	awash	NOUN
cana-729	47	16	river	river	NOUN
cana-729	47	17	basin	basin	NOUN
cana-729	47	18	of	of	ADP
cana-729	47	19	ethiopia	ethiopia	PROPN
cana-729	47	20	in	in	ADP
cana-729	47	21	2013	2013	NUM
cana-729	47	22	,	,	PUNCT
cana-729	47	23	like	like	ADP
cana-729	47	24	artificial	artificial	ADJ
cana-729	47	25	neural	neural	ADJ
cana-729	47	26	network	network	NOUN
cana-729	47	27	,	,	PUNCT
cana-729	47	28	coupled	couple	VERB
cana-729	47	29	wavelet	wavelet	NOUN
cana-729	47	30	,	,	PUNCT
cana-729	47	31	and	and	CCONJ
cana-729	47	32	support	support	VERB
cana-729	47	33	vector	vector	NOUN
cana-729	47	34	regressor	regressor	NOUN
cana-729	47	35	in	in	ADP
cana-729	47	36	which	which	PRON
cana-729	47	37	the	the	DET
cana-729	47	38	input	input	NOUN
cana-729	47	39	data	datum	NOUN
cana-729	47	40	was	be	AUX
cana-729	47	41	pre	pre	ADJ
cana-729	47	42	-	-	VERB
cana-729	47	43	processed	processed	ADJ
cana-729	47	44	using	use	VERB
cana-729	47	45	wavelet	wavelet	NOUN
cana-729	47	46	analysis	analysis	NOUN
cana-729	47	47	for	for	ADP
cana-729	47	48	forecasting	forecast	VERB
cana-729	47	49	short	short	ADJ
cana-729	47	50	-	-	PUNCT
cana-729	47	51	term	term	NOUN
cana-729	47	52	drought	drought	NOUN
cana-729	47	53	.	.	PUNCT
cana-729	48	1	to	to	PART
cana-729	48	2	illustrate	illustrate	VERB
cana-729	48	3	drought	drought	NOUN
cana-729	48	4	in	in	ADP
cana-729	48	5	the	the	DET
cana-729	48	6	river	river	NOUN
cana-729	48	7	basin	basin	NOUN
cana-729	48	8	,	,	PUNCT
cana-729	48	9	they	they	PRON
cana-729	48	10	employed	employ	VERB
cana-729	48	11	the	the	DET
cana-729	48	12	standard	standard	ADJ
cana-729	48	13	precipitation	precipitation	NOUN
cana-729	48	14	index	index	NOUN
cana-729	48	15	as	as	ADP
cana-729	48	16	a	a	DET
cana-729	48	17	drought	drought	NOUN
cana-729	48	18	index	index	NOUN
cana-729	48	19	.	.	PUNCT
cana-729	49	1	the	the	DET
cana-729	49	2	study	study	NOUN
cana-729	49	3	found	find	VERB
cana-729	49	4	that	that	SCONJ
cana-729	49	5	coupled	couple	VERB
cana-729	49	6	wavelet	wavelet	NOUN
cana-729	49	7	neural	neural	ADJ
cana-729	49	8	networks	network	NOUN
cana-729	49	9	are	be	AUX
cana-729	49	10	a	a	DET
cana-729	49	11	superior	superior	ADJ
cana-729	49	12	model	model	NOUN
cana-729	49	13	to	to	PART
cana-729	49	14	forecast	forecast	VERB
cana-729	49	15	drought	drought	NOUN
cana-729	49	16	in	in	ADP
cana-729	49	17	the	the	DET
cana-729	49	18	awash	awash	NOUN
cana-729	49	19	river	river	NOUN
cana-729	49	20	basin	basin	NOUN
cana-729	49	21	than	than	ADP
cana-729	49	22	the	the	DET
cana-729	49	23	other	other	ADJ
cana-729	49	24	two	two	NUM
cana-729	49	25	machine	machine	NOUN
cana-729	49	26	learning	learn	VERB
cana-729	49	27	approaches[1	approaches[1	X
cana-729	49	28	]	]	PUNCT
cana-729	49	29	.	.	PUNCT
cana-729	50	1	other	other	ADJ
cana-729	50	2	machine	machine	NOUN
cana-729	50	3	learning	learning	NOUN
cana-729	50	4	models	model	NOUN
cana-729	50	5	for	for	ADP
cana-729	50	6	drought	drought	NOUN
cana-729	50	7	forecasting	forecasting	NOUN
cana-729	50	8	,	,	PUNCT
cana-729	50	9	such	such	ADJ
cana-729	50	10	as	as	ADP
cana-729	50	11	self	self	NOUN
cana-729	50	12	-	-	PUNCT
cana-729	50	13	adaptive	adaptive	ADJ
cana-729	50	14	scalable	scalable	ADJ
cana-729	50	15	extreme	extreme	ADJ
cana-729	50	16	machine	machine	NOUN
cana-729	50	17	(	(	PUNCT
cana-729	50	18	sadeelm	sadeelm	PROPN
cana-729	50	19	)	)	PUNCT
cana-729	50	20	,	,	PUNCT
cana-729	50	21	online	online	ADJ
cana-729	50	22	sequential	sequential	ADJ
cana-729	50	23	polar	polar	ADJ
cana-729	50	24	machine	machine	NOUN
cana-729	50	25	(	(	PUNCT
cana-729	50	26	oselm	oselm	NOUN
cana-729	50	27	)	)	PUNCT
cana-729	50	28	,	,	PUNCT
cana-729	50	29	and	and	CCONJ
cana-729	50	30	extreme	extreme	ADJ
cana-729	50	31	machine	machine	NOUN
cana-729	50	32	learning	learning	NOUN
cana-729	50	33	(	(	PUNCT
cana-729	50	34	elm	elm	PROPN
cana-729	50	35	)	)	PUNCT
cana-729	50	36	were	be	AUX
cana-729	50	37	compared	compare	VERB
cana-729	50	38	using	use	VERB
cana-729	50	39	sea	sea	NOUN
cana-729	50	40	surface	surface	NOUN
cana-729	50	41	temperature	temperature	NOUN
cana-729	50	42	anomaly	anomaly	NOUN
cana-729	50	43	(	(	PUNCT
cana-729	50	44	ssta	ssta	NOUN
cana-729	50	45	)	)	PUNCT
cana-729	50	46	as	as	ADP
cana-729	50	47	input	input	NOUN
cana-729	50	48	variables	variable	NOUN
cana-729	50	49	in	in	ADP
cana-729	50	50	the	the	DET
cana-729	50	51	nino4	nino4	ADJ
cana-729	50	52	and	and	CCONJ
cana-729	50	53	ninow	ninow	ADJ
cana-729	50	54	zones	zone	NOUN
cana-729	50	55	.	.	PUNCT
cana-729	51	1	the	the	DET
cana-729	51	2	main	main	ADJ
cana-729	51	3	objective	objective	NOUN
cana-729	51	4	of	of	ADP
cana-729	51	5	the	the	DET
cana-729	51	6	project	project	NOUN
cana-729	51	7	was	be	AUX
cana-729	51	8	to	to	PART
cana-729	51	9	predict	predict	VERB
cana-729	51	10	drought	drought	NOUN
cana-729	51	11	using	use	VERB
cana-729	51	12	drought	drought	NOUN
cana-729	51	13	indices	index	NOUN
cana-729	51	14	like	like	ADP
cana-729	51	15	the	the	DET
cana-729	51	16	precipitation	precipitation	NOUN
cana-729	51	17	standardized	standardize	VERB
cana-729	51	18	evaporation	evaporation	NOUN
cana-729	51	19	index	index	NOUN
cana-729	51	20	(	(	PUNCT
cana-729	51	21	spei	spei	PROPN
cana-729	51	22	)	)	PUNCT
cana-729	51	23	and	and	CCONJ
cana-729	51	24	the	the	DET
cana-729	51	25	standardized	standardized	ADJ
cana-729	51	26	communications	communication	NOUN
cana-729	51	27	on	on	ADP
cana-729	51	28	applied	apply	VERB
cana-729	51	29	nonlinear	nonlinear	ADJ
cana-729	51	30	analysis	analysis	NOUN
cana-729	51	31	issn	issn	NOUN
cana-729	51	32	:	:	PUNCT
cana-729	51	33	1074	1074	NUM
cana-729	51	34	-	-	PUNCT
cana-729	51	35	133x	133x	NUM
cana-729	51	36	vol	vol	NOUN
cana-729	51	37	31	31	NUM
cana-729	51	38	no	no	NOUN
cana-729	51	39	.	.	PUNCT
cana-729	52	1	3s	3s	NUM
cana-729	52	2	(	(	PUNCT
cana-729	52	3	2024	2024	NUM
cana-729	52	4	)	)	PUNCT
cana-729	52	5	31	31	NUM
cana-729	52	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-729	52	7	precipitation	precipitation	NOUN
cana-729	52	8	index	index	NOUN
cana-729	52	9	(	(	PUNCT
cana-729	52	10	spi	spi	PROPN
cana-729	52	11	)	)	PUNCT
cana-729	52	12	.	.	PUNCT
cana-729	53	1	using	use	VERB
cana-729	53	2	rmse	rmse	NOUN
cana-729	53	3	and	and	CCONJ
cana-729	53	4	corr	corr	NOUN
cana-729	53	5	as	as	ADP
cana-729	53	6	statistical	statistical	ADJ
cana-729	53	7	indices	index	NOUN
cana-729	53	8	to	to	PART
cana-729	53	9	quantify	quantify	VERB
cana-729	53	10	accuracy	accuracy	NOUN
cana-729	53	11	,	,	PUNCT
cana-729	53	12	this	this	DET
cana-729	53	13	study	study	NOUN
cana-729	53	14	found	find	VERB
cana-729	53	15	that	that	SCONJ
cana-729	53	16	the	the	DET
cana-729	53	17	self	self	NOUN
cana-729	53	18	-	-	PUNCT
cana-729	53	19	adaptive	adaptive	ADJ
cana-729	53	20	evolutionary	evolutionary	ADJ
cana-729	53	21	extreme	extreme	ADJ
cana-729	53	22	learning	learn	VERB
cana-729	53	23	machine	machine	NOUN
cana-729	53	24	model	model	NOUN
cana-729	53	25	outperformed	outperform	VERB
cana-729	53	26	the	the	DET
cana-729	53	27	other	other	ADJ
cana-729	53	28	two	two	NUM
cana-729	53	29	models	model	NOUN
cana-729	54	1	[	[	X
cana-729	54	2	2	2	X
cana-729	54	3	]	]	PUNCT
cana-729	54	4	the	the	DET
cana-729	54	5	possibility	possibility	NOUN
cana-729	54	6	of	of	ADP
cana-729	54	7	deep	deep	ADJ
cana-729	54	8	learning	learning	NOUN
cana-729	54	9	models	model	NOUN
cana-729	54	10	for	for	ADP
cana-729	54	11	drought	drought	NOUN
cana-729	54	12	assessment	assessment	NOUN
cana-729	54	13	as	as	ADV
cana-729	54	14	well	well	ADV
cana-729	54	15	as	as	ADP
cana-729	54	16	machine	machine	NOUN
cana-729	54	17	learning	learning	NOUN
cana-729	54	18	approaches	approach	NOUN
cana-729	54	19	were	be	AUX
cana-729	54	20	looked	look	VERB
cana-729	54	21	into	into	ADP
cana-729	54	22	in	in	ADP
cana-729	54	23	[	[	X
cana-729	54	24	3	3	NUM
cana-729	54	25	]	]	PUNCT
cana-729	54	26	.	.	PUNCT
cana-729	55	1	they	they	PRON
cana-729	55	2	employed	employ	VERB
cana-729	55	3	soil	soil	NOUN
cana-729	55	4	moisture	moisture	NOUN
cana-729	55	5	,	,	PUNCT
cana-729	55	6	air	air	NOUN
cana-729	55	7	temperature	temperature	NOUN
cana-729	55	8	,	,	PUNCT
cana-729	55	9	wind	wind	NOUN
cana-729	55	10	speed	speed	NOUN
cana-729	55	11	,	,	PUNCT
cana-729	55	12	surface	surface	NOUN
cana-729	55	13	pressure	pressure	NOUN
cana-729	55	14	,	,	PUNCT
cana-729	55	15	geopotential	geopotential	ADJ
cana-729	55	16	height	height	NOUN
cana-729	55	17	,	,	PUNCT
cana-729	55	18	and	and	CCONJ
cana-729	55	19	relative	relative	ADJ
cana-729	55	20	humidity	humidity	NOUN
cana-729	55	21	as	as	ADP
cana-729	55	22	major	major	ADJ
cana-729	55	23	hydrometeorological	hydrometeorological	ADJ
cana-729	55	24	antecedents	antecedent	NOUN
cana-729	55	25	for	for	ADP
cana-729	55	26	the	the	DET
cana-729	55	27	investigation	investigation	NOUN
cana-729	55	28	.	.	PUNCT
cana-729	56	1	they	they	PRON
cana-729	56	2	used	use	VERB
cana-729	56	3	a	a	DET
cana-729	56	4	deep	deep	ADJ
cana-729	56	5	learning	learning	NOUN
cana-729	56	6	method	method	NOUN
cana-729	56	7	which	which	PRON
cana-729	56	8	is	be	AUX
cana-729	56	9	based	base	VERB
cana-729	56	10	on	on	ADP
cana-729	56	11	a	a	DET
cana-729	56	12	one	one	NUM
cana-729	56	13	-	-	PUNCT
cana-729	56	14	way	way	NOUN
cana-729	56	15	agglomeration	agglomeration	NOUN
cana-729	56	16	neural	neural	ADJ
cana-729	56	17	network	network	NOUN
cana-729	56	18	to	to	PART
cana-729	56	19	capture	capture	VERB
cana-729	56	20	the	the	DET
cana-729	56	21	fundamental	fundamental	ADJ
cana-729	56	22	relationship	relationship	NOUN
cana-729	56	23	between	between	ADP
cana-729	56	24	hydrometeorological	hydrometeorological	ADJ
cana-729	56	25	factors	factor	NOUN
cana-729	56	26	and	and	CCONJ
cana-729	56	27	precipitation	precipitation	NOUN
cana-729	56	28	.	.	PUNCT
cana-729	57	1	in	in	ADP
cana-729	57	2	2019	2019	NUM
cana-729	57	3	,	,	PUNCT
cana-729	57	4	amandeep	amandeep	ADJ
cana-729	57	5	kaur	kaur	PROPN
cana-729	57	6	and	and	CCONJ
cana-729	57	7	sandeep	sandeep	PROPN
cana-729	57	8	k.	k.	PROPN
cana-729	57	9	sod	sod	PROPN
cana-729	57	10	developed	develop	VERB
cana-729	57	11	a	a	DET
cana-729	57	12	novel	novel	ADJ
cana-729	57	13	method	method	NOUN
cana-729	57	14	for	for	ADP
cana-729	57	15	assessing	assess	VERB
cana-729	57	16	drought	drought	NOUN
cana-729	57	17	.	.	PUNCT
cana-729	58	1	they	they	PRON
cana-729	58	2	developed	develop	VERB
cana-729	58	3	a	a	DET
cana-729	58	4	system	system	NOUN
cana-729	58	5	for	for	ADP
cana-729	58	6	drought	drought	NOUN
cana-729	58	7	evaluation	evaluation	NOUN
cana-729	58	8	and	and	CCONJ
cana-729	58	9	prediction	prediction	NOUN
cana-729	58	10	that	that	PRON
cana-729	58	11	incorporates	incorporate	VERB
cana-729	58	12	dimensionality	dimensionality	NOUN
cana-729	58	13	reduction	reduction	NOUN
cana-729	58	14	for	for	ADP
cana-729	58	15	determining	determine	VERB
cana-729	58	16	drought	drought	NOUN
cana-729	58	17	severity	severity	NOUN
cana-729	58	18	levels	level	NOUN
cana-729	58	19	using	use	VERB
cana-729	58	20	artificial	artificial	ADJ
cana-729	58	21	neural	neural	ADJ
cana-729	58	22	networks	network	NOUN
cana-729	58	23	(	(	PUNCT
cana-729	58	24	ann	ann	PROPN
cana-729	58	25	)	)	PUNCT
cana-729	58	26	that	that	PRON
cana-729	58	27	were	be	AUX
cana-729	58	28	optimised	optimise	VERB
cana-729	58	29	with	with	ADP
cana-729	58	30	genetic	genetic	ADJ
cana-729	58	31	algorithm	algorithm	NOUN
cana-729	58	32	(	(	PUNCT
cana-729	58	33	ann	ann	PROPN
cana-729	58	34	-	-	PUNCT
cana-729	58	35	ga	ga	PROPN
cana-729	58	36	)	)	PUNCT
cana-729	58	37	,	,	PUNCT
cana-729	58	38	and	and	CCONJ
cana-729	58	39	deep	deep	ADJ
cana-729	58	40	neural	neural	ADJ
cana-729	58	41	networks	network	NOUN
cana-729	58	42	(	(	PUNCT
cana-729	58	43	dnn	dnn	PROPN
cana-729	58	44	)	)	PUNCT
cana-729	58	45	.	.	PUNCT
cana-729	59	1	drought	drought	NOUN
cana-729	59	2	conditions	condition	NOUN
cana-729	59	3	were	be	AUX
cana-729	59	4	predicted	predict	VERB
cana-729	59	5	using	use	VERB
cana-729	59	6	support	support	NOUN
cana-729	59	7	vector	vector	NOUN
cana-729	59	8	regression	regression	NOUN
cana-729	59	9	(	(	PUNCT
cana-729	59	10	svr	svr	PROPN
cana-729	59	11	)	)	PUNCT
cana-729	59	12	for	for	ADP
cana-729	59	13	several	several	ADJ
cana-729	59	14	climatic	climatic	ADJ
cana-729	59	15	blocks	block	NOUN
cana-729	59	16	and	and	CCONJ
cana-729	59	17	time	time	NOUN
cana-729	59	18	periods	period	NOUN
cana-729	59	19	.	.	PUNCT
cana-729	60	1	drought	drought	NOUN
cana-729	60	2	conditions	condition	NOUN
cana-729	60	3	were	be	AUX
cana-729	60	4	predicted	predict	VERB
cana-729	60	5	using	use	VERB
cana-729	60	6	support	support	NOUN
cana-729	60	7	vector	vector	NOUN
cana-729	60	8	regression	regression	NOUN
cana-729	60	9	(	(	PUNCT
cana-729	60	10	svr	svr	PROPN
cana-729	60	11	)	)	PUNCT
cana-729	60	12	for	for	ADP
cana-729	60	13	several	several	ADJ
cana-729	60	14	climatic	climatic	ADJ
cana-729	60	15	blocks	block	NOUN
cana-729	60	16	and	and	CCONJ
cana-729	60	17	time	time	NOUN
cana-729	60	18	periods	period	NOUN
cana-729	60	19	.	.	PUNCT
cana-729	61	1	the	the	DET
cana-729	61	2	paper	paper	NOUN
cana-729	61	3	's	's	PART
cana-729	61	4	findings	finding	NOUN
cana-729	61	5	demonstrate	demonstrate	VERB
cana-729	61	6	that	that	SCONJ
cana-729	61	7	deep	deep	ADJ
cana-729	61	8	neural	neural	ADJ
cana-729	61	9	networks	network	NOUN
cana-729	61	10	(	(	PUNCT
cana-729	61	11	dnn	dnn	PROPN
cana-729	61	12	)	)	PUNCT
cana-729	61	13	performed	perform	VERB
cana-729	61	14	with	with	ADP
cana-729	61	15	95.36	95.36	NUM
cana-729	61	16	per	per	ADP
cana-729	61	17	cent	cent	NOUN
cana-729	61	18	accuracy	accuracy	NOUN
cana-729	61	19	[	[	X
cana-729	61	20	4	4	NUM
cana-729	61	21	]	]	PUNCT
cana-729	61	22	.	.	PUNCT
cana-729	62	1	the	the	DET
cana-729	62	2	drought	drought	NOUN
cana-729	62	3	prediction	prediction	NOUN
cana-729	62	4	model	model	NOUN
cana-729	62	5	was	be	AUX
cana-729	62	6	established	establish	VERB
cana-729	62	7	for	for	ADP
cana-729	62	8	pakistan	pakistan	PROPN
cana-729	62	9	for	for	ADP
cana-729	62	10	the	the	DET
cana-729	62	11	first	first	ADJ
cana-729	62	12	time	time	NOUN
cana-729	62	13	,	,	PUNCT
cana-729	62	14	utilising	utilise	VERB
cana-729	62	15	the	the	DET
cana-729	62	16	standardised	standardised	ADJ
cana-729	62	17	precipitation	precipitation	NOUN
cana-729	62	18	evapotranspiration	evapotranspiration	NOUN
cana-729	62	19	index	index	NOUN
cana-729	62	20	as	as	ADP
cana-729	62	21	a	a	DET
cana-729	62	22	drought	drought	NOUN
cana-729	62	23	index	index	NOUN
cana-729	62	24	,	,	PUNCT
cana-729	62	25	for	for	ADP
cana-729	62	26	two	two	NUM
cana-729	62	27	crop	crop	NOUN
cana-729	62	28	seasons	season	NOUN
cana-729	62	29	rabi	rabi	NOUN
cana-729	62	30	and	and	CCONJ
cana-729	62	31	kharif	kharif	NOUN
cana-729	62	32	.	.	PUNCT
cana-729	63	1	they	they	PRON
cana-729	63	2	employed	employ	VERB
cana-729	63	3	recursive	recursive	ADJ
cana-729	63	4	feature	feature	NOUN
cana-729	63	5	elimination	elimination	NOUN
cana-729	63	6	(	(	PUNCT
cana-729	63	7	rfe	rfe	NOUN
cana-729	63	8	)	)	PUNCT
cana-729	63	9	as	as	ADP
cana-729	63	10	a	a	DET
cana-729	63	11	feature	feature	NOUN
cana-729	63	12	selection	selection	NOUN
cana-729	63	13	strategy	strategy	NOUN
cana-729	63	14	for	for	ADP
cana-729	63	15	finding	find	VERB
cana-729	63	16	sets	set	NOUN
cana-729	63	17	of	of	ADP
cana-729	63	18	predictors	predictor	NOUN
cana-729	63	19	and	and	CCONJ
cana-729	63	20	created	create	VERB
cana-729	63	21	a	a	DET
cana-729	63	22	prediction	prediction	NOUN
cana-729	63	23	model	model	NOUN
cana-729	63	24	utilising	utilise	VERB
cana-729	63	25	three	three	NUM
cana-729	63	26	machine	machine	NOUN
cana-729	63	27	learning	learn	VERB
cana-729	63	28	techniques	technique	VERB
cana-729	63	29	artificial	artificial	ADJ
cana-729	63	30	neural	neural	ADJ
cana-729	63	31	network	network	NOUN
cana-729	63	32	,	,	PUNCT
cana-729	63	33	support	support	NOUN
cana-729	63	34	vector	vector	NOUN
cana-729	63	35	regressor	regressor	NOUN
cana-729	63	36	and	and	CCONJ
cana-729	63	37	k	k	NOUN
cana-729	63	38	-	-	PUNCT
cana-729	63	39	nearest	near	ADJ
cana-729	63	40	neighbour	neighbour	NOUN
cana-729	63	41	.	.	PUNCT
cana-729	64	1	the	the	DET
cana-729	64	2	paper	paper	NOUN
cana-729	64	3	concludes	conclude	VERB
cana-729	64	4	that	that	SCONJ
cana-729	64	5	the	the	DET
cana-729	64	6	svmbased	svmbase	VERB
cana-729	64	7	model	model	NOUN
cana-729	64	8	outperformed	outperform	VERB
cana-729	64	9	the	the	DET
cana-729	64	10	ann	ann	PROPN
cana-729	64	11	and	and	CCONJ
cana-729	64	12	knn	knn	PROPN
cana-729	64	13	models	model	NOUN
cana-729	64	14	[	[	X
cana-729	64	15	5	5	NUM
cana-729	64	16	]	]	PUNCT
cana-729	64	17	.	.	PUNCT
cana-729	65	1	the	the	DET
cana-729	65	2	sea	sea	NOUN
cana-729	65	3	surface	surface	NOUN
cana-729	65	4	temperature	temperature	NOUN
cana-729	65	5	(	(	PUNCT
cana-729	65	6	sst	sst	NOUN
cana-729	65	7	)	)	PUNCT
cana-729	65	8	was	be	AUX
cana-729	65	9	used	use	VERB
cana-729	65	10	as	as	ADP
cana-729	65	11	a	a	DET
cana-729	65	12	primary	primary	ADJ
cana-729	65	13	predictor	predictor	NOUN
cana-729	65	14	in	in	ADP
cana-729	65	15	the	the	DET
cana-729	65	16	development	development	NOUN
cana-729	65	17	of	of	ADP
cana-729	65	18	a	a	DET
cana-729	65	19	drought	drought	NOUN
cana-729	65	20	prediction	prediction	NOUN
cana-729	65	21	model	model	NOUN
cana-729	65	22	in	in	ADP
cana-729	65	23	2021	2021	NUM
cana-729	65	24	.	.	PUNCT
cana-729	66	1	they	they	PRON
cana-729	66	2	constructed	construct	VERB
cana-729	66	3	three	three	NUM
cana-729	66	4	models	model	NOUN
cana-729	66	5	that	that	PRON
cana-729	66	6	are	be	AUX
cana-729	66	7	asfp	asfp	NOUN
cana-729	66	8	-	-	PUNCT
cana-729	66	9	svr	svr	PROPN
cana-729	66	10	,	,	PUNCT
cana-729	66	11	asfp	asfp	NOUN
cana-729	66	12	-	-	PUNCT
cana-729	66	13	elm	elm	PROPN
cana-729	66	14	,	,	PUNCT
cana-729	66	15	and	and	CCONJ
cana-729	66	16	asfprf	asfprf	NOUN
cana-729	66	17	employing	employ	VERB
cana-729	66	18	the	the	DET
cana-729	66	19	antecedent	antecedent	NOUN
cana-729	66	20	sst	sst	NOUN
cana-729	66	21	fluctuating	fluctuate	VERB
cana-729	66	22	pattern	pattern	NOUN
cana-729	66	23	and	and	CCONJ
cana-729	66	24	machine	machine	NOUN
cana-729	66	25	learning	learn	VERB
cana-729	66	26	techniques	technique	NOUN
cana-729	66	27	like	like	ADP
cana-729	66	28	support	support	NOUN
cana-729	66	29	vector	vector	NOUN
cana-729	66	30	regressor	regressor	NOUN
cana-729	66	31	,	,	PUNCT
cana-729	66	32	extreme	extreme	ADJ
cana-729	66	33	learning	learning	NOUN
cana-729	66	34	machine	machine	NOUN
cana-729	66	35	,	,	PUNCT
cana-729	66	36	and	and	CCONJ
cana-729	66	37	random	random	ADJ
cana-729	66	38	forest	forest	NOUN
cana-729	66	39	.	.	PUNCT
cana-729	67	1	the	the	DET
cana-729	67	2	orange	orange	ADJ
cana-729	67	3	,	,	PUNCT
cana-729	67	4	pearl	pearl	NOUN
cana-729	67	5	,	,	PUNCT
cana-729	67	6	colorado	colorado	NOUN
cana-729	67	7	,	,	PUNCT
cana-729	67	8	and	and	CCONJ
cana-729	67	9	danube	danube	PROPN
cana-729	67	10	river	river	NOUN
cana-729	67	11	basins	basin	NOUN
cana-729	67	12	were	be	AUX
cana-729	67	13	studied	study	VERB
cana-729	67	14	.	.	PUNCT
cana-729	68	1	as	as	ADP
cana-729	68	2	a	a	DET
cana-729	68	3	drought	drought	NOUN
cana-729	68	4	index	index	NOUN
cana-729	68	5	,	,	PUNCT
cana-729	68	6	the	the	DET
cana-729	68	7	standardised	standardised	ADJ
cana-729	68	8	precipitation	precipitation	NOUN
cana-729	68	9	evapotranspiration	evapotranspiration	NOUN
cana-729	68	10	index	index	NOUN
cana-729	68	11	(	(	PUNCT
cana-729	68	12	spei	spei	PROPN
cana-729	68	13	)	)	PUNCT
cana-729	68	14	was	be	AUX
cana-729	68	15	utilised	utilise	VERB
cana-729	68	16	.	.	PUNCT
cana-729	69	1	asfp	asfp	PROPN
cana-729	69	2	-	-	PUNCT
cana-729	69	3	elm	elm	PROPN
cana-729	69	4	outperformed	outperform	VERB
cana-729	69	5	the	the	DET
cana-729	69	6	other	other	ADJ
cana-729	69	7	two	two	NUM
cana-729	69	8	models	model	NOUN
cana-729	69	9	,	,	PUNCT
cana-729	69	10	according	accord	VERB
cana-729	69	11	to	to	ADP
cana-729	69	12	the	the	DET
cana-729	69	13	findings	finding	NOUN
cana-729	69	14	[	[	X
cana-729	69	15	6	6	NUM
cana-729	69	16	]	]	PUNCT
cana-729	69	17	multilayer	multilayer	ADJ
cana-729	69	18	perceptron	perceptron	PROPN
cana-729	69	19	(	(	PUNCT
cana-729	69	20	mlp	mlp	PROPN
cana-729	69	21	)	)	PUNCT
cana-729	69	22	,	,	PUNCT
cana-729	69	23	adaptive	adaptive	ADJ
cana-729	69	24	neuro	neuro	NOUN
cana-729	69	25	-	-	PUNCT
cana-729	69	26	fuzzy	fuzzy	ADJ
cana-729	69	27	interface	interface	NOUN
cana-729	69	28	system	system	NOUN
cana-729	69	29	(	(	PUNCT
cana-729	69	30	anfis	anfis	PROPN
cana-729	69	31	)	)	PUNCT
cana-729	69	32	,	,	PUNCT
cana-729	69	33	support	support	VERB
cana-729	69	34	vector	vector	NOUN
cana-729	69	35	machine	machine	NOUN
cana-729	69	36	(	(	PUNCT
cana-729	69	37	svm	svm	PROPN
cana-729	69	38	)	)	PUNCT
cana-729	69	39	,	,	PUNCT
cana-729	69	40	and	and	CCONJ
cana-729	69	41	radial	radial	ADJ
cana-729	69	42	basis	basis	NOUN
cana-729	69	43	function	function	NOUN
cana-729	69	44	neural	neural	ADJ
cana-729	69	45	network	network	NOUN
cana-729	69	46	were	be	AUX
cana-729	69	47	used	use	VERB
cana-729	69	48	to	to	PART
cana-729	69	49	forecast	forecast	VERB
cana-729	69	50	drought	drought	NOUN
cana-729	69	51	in	in	ADP
cana-729	69	52	iran	iran	PROPN
cana-729	69	53	in	in	ADP
cana-729	69	54	2020	2020	NUM
cana-729	69	55	.	.	PUNCT
cana-729	70	1	(	(	PUNCT
cana-729	70	2	rbfnn	rbfnn	PROPN
cana-729	70	3	)	)	PUNCT
cana-729	70	4	.	.	PUNCT
cana-729	71	1	mlp	mlp	PROPN
cana-729	71	2	,	,	PUNCT
cana-729	71	3	anfis	anfis	PROPN
cana-729	71	4	,	,	PUNCT
cana-729	71	5	rbfnn	rbfnn	NOUN
cana-729	71	6	and	and	CCONJ
cana-729	71	7	svm	svm	PROPN
cana-729	71	8	were	be	AUX
cana-729	71	9	also	also	ADV
cana-729	71	10	trained	train	VERB
cana-729	71	11	using	use	VERB
cana-729	71	12	the	the	DET
cana-729	71	13	nomadic	nomadic	ADJ
cana-729	71	14	people	people	NOUN
cana-729	71	15	algorithm	algorithm	NOUN
cana-729	71	16	(	(	PUNCT
cana-729	71	17	npa	npa	NOUN
cana-729	71	18	)	)	PUNCT
cana-729	71	19	.	.	PUNCT
cana-729	72	1	these	these	DET
cana-729	72	2	models	model	NOUN
cana-729	72	3	were	be	AUX
cana-729	72	4	used	use	VERB
cana-729	72	5	to	to	PART
cana-729	72	6	anticipate	anticipate	VERB
cana-729	72	7	the	the	DET
cana-729	72	8	standardised	standardised	ADJ
cana-729	72	9	precipitation	precipitation	NOUN
cana-729	72	10	index	index	NOUN
cana-729	72	11	for	for	ADP
cana-729	72	12	the	the	DET
cana-729	72	13	next	next	ADJ
cana-729	72	14	three	three	NUM
cana-729	72	15	months	month	NOUN
cana-729	72	16	(	(	PUNCT
cana-729	72	17	3	3	NUM
cana-729	72	18	-	-	PUNCT
cana-729	72	19	months	month	NOUN
cana-729	72	20	spi	spi	NOUN
cana-729	72	21	)	)	PUNCT
cana-729	72	22	.	.	PUNCT
cana-729	73	1	the	the	DET
cana-729	73	2	results	result	NOUN
cana-729	73	3	reveal	reveal	VERB
cana-729	73	4	that	that	SCONJ
cana-729	73	5	the	the	DET
cana-729	73	6	anfis	anfis	PROPN
cana-729	73	7	-	-	PUNCT
cana-729	73	8	npa	npa	NOUN
cana-729	73	9	model	model	NOUN
cana-729	73	10	was	be	AUX
cana-729	73	11	better	well	ADJ
cana-729	73	12	than	than	ADP
cana-729	73	13	rbfnn	rbfnn	NOUN
cana-729	73	14	-	-	PUNCT
cana-729	73	15	npa	npa	NOUN
cana-729	73	16	,	,	PUNCT
cana-729	73	17	svm	svm	ADJ
cana-729	73	18	-	-	ADJ
cana-729	73	19	npa	npa	NOUN
cana-729	73	20	and	and	CCONJ
cana-729	73	21	mpl	mpl	PROPN
cana-729	73	22	-	-	PUNCT
cana-729	73	23	npa	npa	NOUN
cana-729	73	24	models	model	NOUN
cana-729	73	25	,	,	PUNCT
cana-729	73	26	as	as	ADV
cana-729	73	27	well	well	ADV
cana-729	73	28	as	as	ADP
cana-729	73	29	demonstrating	demonstrate	VERB
cana-729	73	30	that	that	SCONJ
cana-729	73	31	hybrid	hybrid	NOUN
cana-729	73	32	models	model	NOUN
cana-729	73	33	outperform	outperform	VERB
cana-729	73	34	solo	solo	NOUN
cana-729	73	35	models	model	NOUN
cana-729	73	36	[	[	X
cana-729	73	37	7	7	X
cana-729	73	38	]	]	PUNCT
cana-729	73	39	for	for	ADP
cana-729	73	40	agricultural	agricultural	ADJ
cana-729	73	41	drought	drought	NOUN
cana-729	73	42	prediction	prediction	NOUN
cana-729	73	43	in	in	ADP
cana-729	73	44	2019	2019	NUM
cana-729	73	45	,	,	PUNCT
cana-729	73	46	an	an	DET
cana-729	73	47	enhanced	enhanced	ADJ
cana-729	73	48	support	support	NOUN
cana-729	73	49	vector	vector	NOUN
cana-729	73	50	regression	regression	NOUN
cana-729	73	51	model	model	NOUN
cana-729	73	52	was	be	AUX
cana-729	73	53	applied	apply	VERB
cana-729	73	54	.	.	PUNCT
cana-729	74	1	they	they	PRON
cana-729	74	2	employed	employ	VERB
cana-729	74	3	the	the	DET
cana-729	74	4	boosted	boosted	ADJ
cana-729	74	5	support	support	NOUN
cana-729	74	6	vector	vector	NOUN
cana-729	74	7	regression	regression	NOUN
cana-729	74	8	(	(	PUNCT
cana-729	74	9	bs	bs	NOUN
cana-729	74	10	-	-	PUNCT
cana-729	74	11	svr	svr	NOUN
cana-729	74	12	)	)	PUNCT
cana-729	74	13	model	model	NOUN
cana-729	74	14	and	and	CCONJ
cana-729	74	15	the	the	DET
cana-729	74	16	fuzzy	fuzzy	ADJ
cana-729	74	17	support	support	NOUN
cana-729	74	18	vector	vector	NOUN
cana-729	74	19	regression	regression	NOUN
cana-729	74	20	(	(	PUNCT
cana-729	74	21	f	f	X
cana-729	74	22	-	-	PUNCT
cana-729	74	23	svr	svr	NOUN
cana-729	74	24	)	)	PUNCT
cana-729	74	25	model	model	NOUN
cana-729	74	26	as	as	ADP
cana-729	74	27	upgraded	upgrade	VERB
cana-729	74	28	svr	svr	NOUN
cana-729	74	29	models	model	NOUN
cana-729	74	30	,	,	PUNCT
cana-729	74	31	using	use	VERB
cana-729	74	32	the	the	DET
cana-729	74	33	standardise	standardise	ADJ
cana-729	74	34	precipitation	precipitation	NOUN
cana-729	74	35	communications	communication	NOUN
cana-729	74	36	on	on	ADP
cana-729	74	37	applied	apply	VERB
cana-729	74	38	nonlinear	nonlinear	ADJ
cana-729	74	39	analysis	analysis	NOUN
cana-729	74	40	issn	issn	NOUN
cana-729	74	41	:	:	PUNCT
cana-729	74	42	1074	1074	NUM
cana-729	74	43	-	-	PUNCT
cana-729	74	44	133x	133x	NUM
cana-729	74	45	vol	vol	NOUN
cana-729	74	46	31	31	NUM
cana-729	74	47	no	no	NOUN
cana-729	74	48	.	.	PUNCT
cana-729	75	1	3s	3s	NUM
cana-729	75	2	(	(	PUNCT
cana-729	75	3	2024	2024	NUM
cana-729	75	4	)	)	PUNCT
cana-729	75	5	32	32	NUM
cana-729	75	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-729	75	7	evapotranspiration	evapotranspiration	NOUN
cana-729	75	8	index	index	NOUN
cana-729	75	9	(	(	PUNCT
cana-729	75	10	spei	spei	PROPN
cana-729	75	11	)	)	PUNCT
cana-729	75	12	as	as	ADP
cana-729	75	13	a	a	DET
cana-729	75	14	drought	drought	NOUN
cana-729	75	15	index	index	NOUN
cana-729	75	16	.	.	PUNCT
cana-729	76	1	the	the	DET
cana-729	76	2	paper	paper	NOUN
cana-729	76	3	's	's	PART
cana-729	76	4	main	main	ADJ
cana-729	76	5	goal	goal	NOUN
cana-729	76	6	was	be	AUX
cana-729	76	7	to	to	PART
cana-729	76	8	reduce	reduce	VERB
cana-729	76	9	drought	drought	NOUN
cana-729	76	10	in	in	ADP
cana-729	76	11	the	the	DET
cana-729	76	12	langat	langat	ADJ
cana-729	76	13	river	river	NOUN
cana-729	76	14	basin	basin	NOUN
cana-729	76	15	's	's	PART
cana-729	76	16	downstream	downstream	ADJ
cana-729	76	17	end	end	NOUN
cana-729	76	18	.	.	PUNCT
cana-729	77	1	model	model	NOUN
cana-729	77	2	accuracy	accuracy	NOUN
cana-729	77	3	was	be	AUX
cana-729	77	4	determined	determine	VERB
cana-729	77	5	using	use	VERB
cana-729	77	6	mbe	mbe	PROPN
cana-729	77	7	,	,	PUNCT
cana-729	77	8	mae	mae	PROPN
cana-729	77	9	,	,	PUNCT
cana-729	77	10	rsquare	rsquare	NOUN
cana-729	77	11	and	and	CCONJ
cana-729	77	12	rmse	rmse	NOUN
cana-729	77	13	and	and	CCONJ
cana-729	77	14	it	it	PRON
cana-729	77	15	was	be	AUX
cana-729	77	16	determined	determine	VERB
cana-729	77	17	that	that	SCONJ
cana-729	77	18	the	the	DET
cana-729	77	19	f	f	PROPN
cana-729	77	20	-	-	PUNCT
cana-729	77	21	svr	svr	PROPN
cana-729	77	22	model	model	NOUN
cana-729	77	23	is	be	AUX
cana-729	77	24	more	more	ADV
cana-729	77	25	accurate	accurate	ADJ
cana-729	77	26	than	than	ADP
cana-729	77	27	the	the	DET
cana-729	77	28	bs	bs	NOUN
cana-729	77	29	-	-	PUNCT
cana-729	77	30	svr	svr	PROPN
cana-729	77	31	model	model	NOUN
cana-729	78	1	[	[	X
cana-729	78	2	8	8	NUM
cana-729	78	3	]	]	PUNCT
cana-729	78	4	.	.	PUNCT
cana-729	79	1	drought	drought	NOUN
cana-729	79	2	analysis	analysis	NOUN
cana-729	79	3	and	and	CCONJ
cana-729	79	4	estimation	estimation	NOUN
cana-729	79	5	for	for	ADP
cana-729	79	6	the	the	DET
cana-729	79	7	period	period	NOUN
cana-729	79	8	1980	1980	NUM
cana-729	79	9	-	-	SYM
cana-729	79	10	2019	2019	NUM
cana-729	79	11	were	be	AUX
cana-729	79	12	carried	carry	VERB
cana-729	79	13	out	out	ADP
cana-729	79	14	in	in	ADP
cana-729	79	15	2021	2021	NUM
cana-729	79	16	utilising	utilise	VERB
cana-729	79	17	the	the	DET
cana-729	79	18	standardised	standardised	ADJ
cana-729	79	19	precipitation	precipitation	NOUN
cana-729	79	20	evapotranspiration	evapotranspiration	NOUN
cana-729	79	21	index	index	NOUN
cana-729	79	22	as	as	ADP
cana-729	79	23	a	a	DET
cana-729	79	24	drought	drought	NOUN
cana-729	79	25	index	index	NOUN
cana-729	79	26	,	,	PUNCT
cana-729	79	27	with	with	ADP
cana-729	79	28	the	the	DET
cana-729	79	29	tibetan	tibetan	PROPN
cana-729	79	30	plateau	plateau	PROPN
cana-729	79	31	,	,	PUNCT
cana-729	79	32	china	china	PROPN
cana-729	79	33	as	as	ADP
cana-729	79	34	a	a	DET
cana-729	79	35	case	case	NOUN
cana-729	79	36	study	study	NOUN
cana-729	79	37	.	.	PUNCT
cana-729	80	1	random	random	ADJ
cana-729	80	2	forest	forest	NOUN
cana-729	80	3	,	,	PUNCT
cana-729	80	4	long	long	ADJ
cana-729	80	5	term	term	NOUN
cana-729	80	6	short	short	ADJ
cana-729	80	7	memory	memory	NOUN
cana-729	80	8	(	(	PUNCT
cana-729	80	9	lstm	lstm	NOUN
cana-729	80	10	)	)	PUNCT
cana-729	80	11	,	,	PUNCT
cana-729	80	12	convolutional	convolutional	ADJ
cana-729	80	13	neural	neural	ADJ
cana-729	80	14	network	network	NOUN
cana-729	80	15	and	and	CCONJ
cana-729	80	16	extreme	extreme	ADJ
cana-729	80	17	gradient	gradient	NOUN
cana-729	80	18	boost	boost	NOUN
cana-729	80	19	were	be	AUX
cana-729	80	20	the	the	DET
cana-729	80	21	machine	machine	NOUN
cana-729	80	22	learning	learn	VERB
cana-729	80	23	approaches	approach	NOUN
cana-729	80	24	investigated	investigate	VERB
cana-729	80	25	(	(	PUNCT
cana-729	80	26	xgb	xgb	NUM
cana-729	80	27	)	)	PUNCT
cana-729	80	28	.	.	PUNCT
cana-729	81	1	in	in	ADP
cana-729	81	2	this	this	DET
cana-729	81	3	work	work	NOUN
cana-729	81	4	,	,	PUNCT
cana-729	81	5	seven	seven	NUM
cana-729	81	6	scenarios	scenario	NOUN
cana-729	81	7	were	be	AUX
cana-729	81	8	investigated	investigate	VERB
cana-729	81	9	,	,	PUNCT
cana-729	81	10	each	each	PRON
cana-729	81	11	of	of	ADP
cana-729	81	12	which	which	PRON
cana-729	81	13	was	be	AUX
cana-729	81	14	based	base	VERB
cana-729	81	15	on	on	ADP
cana-729	81	16	a	a	DET
cana-729	81	17	mix	mix	NOUN
cana-729	81	18	of	of	ADP
cana-729	81	19	diverse	diverse	ADJ
cana-729	81	20	climatic	climatic	ADJ
cana-729	81	21	conditions	condition	NOUN
cana-729	81	22	.	.	PUNCT
cana-729	82	1	the	the	DET
cana-729	82	2	findings	finding	NOUN
cana-729	82	3	reveal	reveal	VERB
cana-729	82	4	that	that	SCONJ
cana-729	82	5	the	the	DET
cana-729	82	6	xgb	xgb	PROPN
cana-729	82	7	model	model	NOUN
cana-729	82	8	was	be	AUX
cana-729	82	9	used	use	VERB
cana-729	82	10	as	as	ADP
cana-729	82	11	an	an	DET
cana-729	82	12	input	input	NOUN
cana-729	82	13	,	,	PUNCT
cana-729	82	14	which	which	PRON
cana-729	82	15	included	include	VERB
cana-729	82	16	precipitation	precipitation	NOUN
cana-729	82	17	,	,	PUNCT
cana-729	82	18	wind	wind	NOUN
cana-729	82	19	speed	speed	NOUN
cana-729	82	20	,	,	PUNCT
cana-729	82	21	lowest	low	ADJ
cana-729	82	22	temperature	temperature	NOUN
cana-729	82	23	,	,	PUNCT
cana-729	82	24	maximum	maximum	ADJ
cana-729	82	25	temperature	temperature	NOUN
cana-729	82	26	,	,	PUNCT
cana-729	82	27	average	average	ADJ
cana-729	82	28	temperature	temperature	NOUN
cana-729	82	29	,	,	PUNCT
cana-729	82	30	and	and	CCONJ
cana-729	82	31	relative	relative	ADJ
cana-729	82	32	humidity[9	humidity[9	NOUN
cana-729	82	33	]	]	PUNCT
cana-729	82	34	.	.	PUNCT
cana-729	83	1	many	many	ADJ
cana-729	83	2	studies	study	NOUN
cana-729	83	3	have	have	AUX
cana-729	83	4	been	be	AUX
cana-729	83	5	conducted	conduct	VERB
cana-729	83	6	to	to	PART
cana-729	83	7	anticipate	anticipate	VERB
cana-729	83	8	and	and	CCONJ
cana-729	83	9	forecast	forecast	VERB
cana-729	83	10	drought	drought	NOUN
cana-729	83	11	conditions	condition	NOUN
cana-729	83	12	in	in	ADP
cana-729	83	13	different	different	ADJ
cana-729	83	14	parts	part	NOUN
cana-729	83	15	of	of	ADP
cana-729	83	16	the	the	DET
cana-729	83	17	world	world	NOUN
cana-729	84	1	[	[	X
cana-729	84	2	11	11	NUM
cana-729	84	3	,	,	PUNCT
cana-729	84	4	12	12	NUM
cana-729	84	5	,	,	PUNCT
cana-729	84	6	13,19,20	13,19,20	NUM
cana-729	84	7	]	]	X
cana-729	84	8	,	,	PUNCT
cana-729	84	9	but	but	CCONJ
cana-729	84	10	comparatively	comparatively	ADV
cana-729	84	11	few	few	ADJ
cana-729	84	12	have	have	AUX
cana-729	84	13	looked	look	VERB
cana-729	84	14	at	at	ADP
cana-729	84	15	the	the	DET
cana-729	84	16	larger	large	ADJ
cana-729	84	17	picture	picture	NOUN
cana-729	84	18	of	of	ADP
cana-729	84	19	overall	overall	ADJ
cana-729	84	20	drought	drought	NOUN
cana-729	84	21	vulnerability	vulnerability	NOUN
cana-729	84	22	.	.	PUNCT
cana-729	85	1	only	only	ADV
cana-729	85	2	a	a	DET
cana-729	85	3	few	few	ADJ
cana-729	85	4	studies	study	NOUN
cana-729	85	5	have	have	AUX
cana-729	85	6	examined	examine	VERB
cana-729	85	7	drought	drought	NOUN
cana-729	85	8	prediction	prediction	NOUN
cana-729	85	9	in	in	ADP
cana-729	85	10	particular	particular	ADJ
cana-729	85	11	states	state	NOUN
cana-729	85	12	[	[	X
cana-729	85	13	14	14	NUM
cana-729	85	14	,	,	PUNCT
cana-729	85	15	15	15	NUM
cana-729	85	16	]	]	PUNCT
cana-729	85	17	.	.	PUNCT
cana-729	86	1	various	various	ADJ
cana-729	86	2	factors	factor	NOUN
cana-729	86	3	influencing	influence	VERB
cana-729	86	4	the	the	DET
cana-729	86	5	drought	drought	NOUN
cana-729	86	6	was	be	AUX
cana-729	86	7	analysed	analyse	VERB
cana-729	86	8	in	in	ADP
cana-729	86	9	[	[	X
cana-729	86	10	16,17	16,17	NUM
cana-729	86	11	]	]	PUNCT
cana-729	86	12	.	.	PUNCT
cana-729	87	1	assessing	assess	VERB
cana-729	87	2	drought	drought	NOUN
cana-729	87	3	risk	risk	NOUN
cana-729	87	4	is	be	AUX
cana-729	87	5	essential	essential	ADJ
cana-729	87	6	for	for	ADP
cana-729	87	7	efficient	efficient	ADJ
cana-729	87	8	livelihood	livelihood	NOUN
cana-729	87	9	management	management	NOUN
cana-729	87	10	given	give	VERB
cana-729	87	11	this	this	DET
cana-729	87	12	sensitivity	sensitivity	NOUN
cana-729	87	13	and	and	CCONJ
cana-729	87	14	the	the	DET
cana-729	87	15	region	region	NOUN
cana-729	87	16	's	's	PART
cana-729	87	17	dense	dense	ADJ
cana-729	87	18	population	population	NOUN
cana-729	87	19	and	and	CCONJ
cana-729	87	20	heavy	heavy	ADJ
cana-729	87	21	reliance	reliance	NOUN
cana-729	87	22	on	on	ADP
cana-729	87	23	agriculture	agriculture	NOUN
cana-729	87	24	.	.	PUNCT
cana-729	88	1	notably	notably	ADV
cana-729	88	2	,	,	PUNCT
cana-729	88	3	research	research	NOUN
cana-729	88	4	by	by	ADP
cana-729	88	5	[	[	X
cana-729	88	6	17	17	NUM
cana-729	88	7	,	,	PUNCT
cana-729	88	8	18,13	18,13	NUM
cana-729	88	9	]	]	PUNCT
cana-729	88	10	produced	produce	VERB
cana-729	88	11	drought	drought	NOUN
cana-729	88	12	risk	risk	NOUN
cana-729	88	13	maps	map	NOUN
cana-729	88	14	by	by	ADP
cana-729	88	15	applying	apply	VERB
cana-729	88	16	the	the	DET
cana-729	88	17	analytical	analytical	ADJ
cana-729	88	18	hierarchical	hierarchical	ADJ
cana-729	88	19	process	process	NOUN
cana-729	88	20	(	(	PUNCT
cana-729	88	21	ahp	ahp	NOUN
cana-729	88	22	)	)	PUNCT
cana-729	88	23	,	,	PUNCT
cana-729	88	24	with	with	ADP
cana-729	88	25	positive	positive	ADJ
cana-729	88	26	results	result	NOUN
cana-729	88	27	.	.	PUNCT
cana-729	89	1	a	a	DET
cana-729	89	2	wide	wide	ADJ
cana-729	89	3	variety	variety	NOUN
cana-729	89	4	of	of	ADP
cana-729	89	5	metrics	metric	NOUN
cana-729	89	6	have	have	AUX
cana-729	89	7	been	be	AUX
cana-729	89	8	used	use	VERB
cana-729	89	9	over	over	ADP
cana-729	89	10	time	time	NOUN
cana-729	89	11	to	to	PART
cana-729	89	12	analyze	analyze	VERB
cana-729	89	13	drought	drought	NOUN
cana-729	89	14	conditions	condition	NOUN
cana-729	89	15	,	,	PUNCT
cana-729	89	16	with	with	ADP
cana-729	89	17	regional	regional	ADJ
cana-729	89	18	variations	variation	NOUN
cana-729	89	19	in	in	ADP
cana-729	89	20	their	their	PRON
cana-729	89	21	applicability	applicability	NOUN
cana-729	89	22	.	.	PUNCT
cana-729	90	1	several	several	ADJ
cana-729	90	2	techniques	technique	NOUN
cana-729	90	3	,	,	PUNCT
cana-729	90	4	such	such	ADJ
cana-729	90	5	as	as	ADP
cana-729	90	6	temperature	temperature	NOUN
cana-729	90	7	,	,	PUNCT
cana-729	90	8	rainfall	rainfall	NOUN
cana-729	90	9	,	,	PUNCT
cana-729	90	10	vegetation	vegetation	NOUN
cana-729	90	11	index	index	NOUN
cana-729	90	12	,	,	PUNCT
cana-729	90	13	and	and	CCONJ
cana-729	90	14	soil	soil	NOUN
cana-729	90	15	moisture	moisture	NOUN
cana-729	90	16	,	,	PUNCT
cana-729	90	17	have	have	AUX
cana-729	90	18	been	be	AUX
cana-729	90	19	applied	apply	VERB
cana-729	90	20	to	to	PART
cana-729	90	21	simulate	simulate	VERB
cana-729	90	22	drought	drought	NOUN
cana-729	90	23	conditions	condition	NOUN
cana-729	90	24	in	in	ADP
cana-729	90	25	different	different	ADJ
cana-729	90	26	regions	region	NOUN
cana-729	90	27	of	of	ADP
cana-729	90	28	the	the	DET
cana-729	90	29	world	world	NOUN
cana-729	90	30	[	[	X
cana-729	90	31	21	21	NUM
cana-729	90	32	,	,	PUNCT
cana-729	90	33	22	22	NUM
cana-729	90	34	]	]	PUNCT
cana-729	90	35	.	.	PUNCT
cana-729	91	1	measurement	measurement	NOUN
cana-729	91	2	methods	method	NOUN
cana-729	91	3	vary	vary	VERB
cana-729	91	4	as	as	ADV
cana-729	91	5	well	well	ADV
cana-729	91	6	since	since	SCONJ
cana-729	91	7	the	the	DET
cana-729	91	8	nature	nature	NOUN
cana-729	91	9	of	of	ADP
cana-729	91	10	drought	drought	NOUN
cana-729	91	11	varies	vary	VERB
cana-729	91	12	depending	depend	VERB
cana-729	91	13	on	on	ADP
cana-729	91	14	local	local	ADJ
cana-729	91	15	climate	climate	NOUN
cana-729	91	16	conditions	condition	NOUN
cana-729	91	17	[	[	PUNCT
cana-729	91	18	23	23	NUM
cana-729	91	19	]	]	PUNCT
cana-729	91	20	.	.	PUNCT
cana-729	92	1	there	there	PRON
cana-729	92	2	are	be	VERB
cana-729	92	3	two	two	NUM
cana-729	92	4	types	type	NOUN
cana-729	92	5	of	of	ADP
cana-729	92	6	connections	connection	NOUN
cana-729	92	7	that	that	PRON
cana-729	92	8	drought	drought	NOUN
cana-729	92	9	parameters	parameter	NOUN
cana-729	92	10	can	can	AUX
cana-729	92	11	show	show	VERB
cana-729	92	12	:	:	PUNCT
cana-729	92	13	linear	linear	ADJ
cana-729	92	14	and	and	CCONJ
cana-729	92	15	nonlinear	nonlinear	ADJ
cana-729	92	16	[	[	X
cana-729	92	17	24	24	NUM
cana-729	92	18	,	,	PUNCT
cana-729	92	19	25	25	NUM
cana-729	92	20	]	]	PUNCT
cana-729	92	21	.	.	PUNCT
cana-729	93	1	drought	drought	NOUN
cana-729	93	2	frequency	frequency	NOUN
cana-729	93	3	and	and	CCONJ
cana-729	93	4	intensity	intensity	NOUN
cana-729	93	5	have	have	AUX
cana-729	93	6	been	be	AUX
cana-729	93	7	effectively	effectively	ADV
cana-729	93	8	proved	prove	VERB
cana-729	93	9	by	by	ADP
cana-729	93	10	the	the	DET
cana-729	93	11	probability	probability	NOUN
cana-729	93	12	density	density	NOUN
cana-729	93	13	functions	function	NOUN
cana-729	93	14	(	(	PUNCT
cana-729	93	15	pdfs	pdfs	NOUN
cana-729	93	16	)	)	PUNCT
cana-729	93	17	of	of	ADP
cana-729	93	18	drought	drought	NOUN
cana-729	93	19	indices	index	NOUN
cana-729	93	20	[	[	X
cana-729	93	21	26,27,28	26,27,28	NUM
cana-729	93	22	]	]	X
cana-729	93	23	.	.	PUNCT
cana-729	94	1	a	a	DET
cana-729	94	2	combination	combination	NOUN
cana-729	94	3	of	of	ADP
cana-729	94	4	topographical	topographical	ADJ
cana-729	94	5	,	,	PUNCT
cana-729	94	6	meteorological	meteorological	ADJ
cana-729	94	7	,	,	PUNCT
cana-729	94	8	and	and	CCONJ
cana-729	94	9	socioeconomic	socioeconomic	ADJ
cana-729	94	10	variables	variable	NOUN
cana-729	94	11	make	make	VERB
cana-729	94	12	odisha	odisha	PROPN
cana-729	94	13	vulnerable	vulnerable	ADJ
cana-729	94	14	to	to	ADP
cana-729	94	15	drought	drought	NOUN
cana-729	94	16	[	[	X
cana-729	94	17	29	29	NUM
cana-729	94	18	]	]	PUNCT
cana-729	94	19	.	.	PUNCT
cana-729	95	1	the	the	DET
cana-729	95	2	climate	climate	NOUN
cana-729	95	3	is	be	AUX
cana-729	95	4	primarily	primarily	ADV
cana-729	95	5	tropical	tropical	ADJ
cana-729	95	6	,	,	PUNCT
cana-729	95	7	with	with	ADP
cana-729	95	8	irregular	irregular	ADJ
cana-729	95	9	and	and	CCONJ
cana-729	95	10	seasonal	seasonal	ADJ
cana-729	95	11	monsoons	monsoon	NOUN
cana-729	95	12	that	that	PRON
cana-729	95	13	provide	provide	VERB
cana-729	95	14	an	an	DET
cana-729	95	15	uneven	uneven	ADJ
cana-729	95	16	dispersion	dispersion	NOUN
cana-729	95	17	of	of	ADP
cana-729	95	18	rainfall	rainfall	NOUN
cana-729	95	19	throughout	throughout	ADP
cana-729	95	20	the	the	DET
cana-729	95	21	area	area	NOUN
cana-729	95	22	.	.	PUNCT
cana-729	96	1	due	due	ADP
cana-729	96	2	to	to	ADP
cana-729	96	3	the	the	DET
cana-729	96	4	state	state	NOUN
cana-729	96	5	's	's	PART
cana-729	96	6	undulating	undulate	VERB
cana-729	96	7	topography	topography	NOUN
cana-729	96	8	and	and	CCONJ
cana-729	96	9	low	low	ADJ
cana-729	96	10	soil	soil	NOUN
cana-729	96	11	moisture	moisture	NOUN
cana-729	96	12	retention	retention	NOUN
cana-729	96	13	,	,	PUNCT
cana-729	96	14	dry	dry	ADJ
cana-729	96	15	spells	spell	NOUN
cana-729	96	16	make	make	VERB
cana-729	96	17	water	water	NOUN
cana-729	96	18	scarcity	scarcity	NOUN
cana-729	96	19	worse	worse	ADV
cana-729	97	1	[	[	X
cana-729	97	2	30	30	NUM
cana-729	97	3	]	]	PUNCT
cana-729	97	4	.	.	PUNCT
cana-729	98	1	the	the	DET
cana-729	98	2	region	region	NOUN
cana-729	98	3	's	's	PART
cana-729	98	4	vulnerability	vulnerability	NOUN
cana-729	98	5	is	be	AUX
cana-729	98	6	further	far	ADV
cana-729	98	7	increased	increase	VERB
cana-729	98	8	by	by	ADP
cana-729	98	9	high	high	ADJ
cana-729	98	10	evaporation	evaporation	NOUN
cana-729	98	11	rates	rate	NOUN
cana-729	98	12	,	,	PUNCT
cana-729	98	13	excessive	excessive	ADJ
cana-729	98	14	groundwater	groundwater	NOUN
cana-729	98	15	resource	resource	NOUN
cana-729	98	16	use	use	NOUN
cana-729	98	17	,	,	PUNCT
cana-729	98	18	and	and	CCONJ
cana-729	98	19	insufficient	insufficient	ADJ
cana-729	98	20	water	water	NOUN
cana-729	98	21	management	management	NOUN
cana-729	98	22	techniques	technique	NOUN
cana-729	98	23	[	[	X
cana-729	98	24	30	30	NUM
cana-729	98	25	,	,	PUNCT
cana-729	98	26	31	31	NUM
cana-729	98	27	]	]	PUNCT
cana-729	98	28	.	.	PUNCT
cana-729	99	1	deep	deep	ADJ
cana-729	99	2	learning	learn	VERB
cana-729	99	3	algorithms	algorithm	NOUN
cana-729	99	4	were	be	AUX
cana-729	99	5	looked	look	VERB
cana-729	99	6	into	into	ADP
cana-729	99	7	for	for	ADP
cana-729	99	8	drought	drought	NOUN
cana-729	99	9	prediction	prediction	NOUN
cana-729	99	10	[	[	X
cana-729	99	11	10	10	NUM
cana-729	99	12	]	]	PUNCT
cana-729	99	13	.	.	PUNCT
cana-729	100	1	taking	take	VERB
cana-729	100	2	lagged	lag	VERB
cana-729	100	3	values	value	NOUN
cana-729	100	4	of	of	ADP
cana-729	100	5	standardise	standardise	ADJ
cana-729	100	6	streamflow	streamflow	PROPN
cana-729	100	7	index	index	NOUN
cana-729	100	8	(	(	PUNCT
cana-729	100	9	ssi	ssi	PROPN
cana-729	100	10	)	)	PUNCT
cana-729	100	11	as	as	ADP
cana-729	100	12	input	input	NOUN
cana-729	100	13	,	,	PUNCT
cana-729	100	14	long	long	ADJ
cana-729	100	15	-	-	PUNCT
cana-729	100	16	term	term	NOUN
cana-729	100	17	drought	drought	NOUN
cana-729	100	18	was	be	AUX
cana-729	100	19	predicted	predict	VERB
cana-729	100	20	.	.	PUNCT
cana-729	101	1	this	this	DET
cana-729	101	2	approach	approach	NOUN
cana-729	101	3	was	be	AUX
cana-729	101	4	carried	carry	VERB
cana-729	101	5	out	out	ADP
cana-729	101	6	using	use	VERB
cana-729	101	7	support	support	NOUN
cana-729	101	8	vector	vector	NOUN
cana-729	101	9	regressor	regressor	NOUN
cana-729	101	10	(	(	PUNCT
cana-729	101	11	svr	svr	PROPN
cana-729	101	12	)	)	PUNCT
cana-729	101	13	and	and	CCONJ
cana-729	101	14	multilayer	multilayer	ADJ
cana-729	101	15	perceptron	perceptron	PROPN
cana-729	101	16	(	(	PUNCT
cana-729	101	17	mlp	mlp	PROPN
cana-729	101	18	)	)	PUNCT
cana-729	101	19	.	.	PUNCT
cana-729	102	1	3	3	X
cana-729	102	2	.	.	X
cana-729	102	3	methods	method	NOUN
cana-729	102	4	in	in	ADP
cana-729	102	5	this	this	DET
cana-729	102	6	paper	paper	NOUN
cana-729	102	7	,	,	PUNCT
cana-729	102	8	the	the	DET
cana-729	102	9	methodology	methodology	NOUN
cana-729	102	10	comprises	comprise	VERB
cana-729	102	11	four	four	NUM
cana-729	102	12	stages	stage	NOUN
cana-729	102	13	.	.	PUNCT
cana-729	103	1	in	in	ADP
cana-729	103	2	the	the	DET
cana-729	103	3	first	first	ADJ
cana-729	103	4	stage	stage	NOUN
cana-729	103	5	data	data	NOUN
cana-729	103	6	collection	collection	NOUN
cana-729	103	7	was	be	AUX
cana-729	103	8	done	do	VERB
cana-729	103	9	.	.	PUNCT
cana-729	104	1	the	the	DET
cana-729	104	2	second	second	ADJ
cana-729	104	3	stage	stage	NOUN
cana-729	104	4	consists	consist	VERB
cana-729	104	5	of	of	ADP
cana-729	104	6	data	datum	NOUN
cana-729	104	7	pre	pre	ADJ
cana-729	104	8	-	-	NOUN
cana-729	104	9	processing	processing	ADJ
cana-729	104	10	.	.	PUNCT
cana-729	105	1	in	in	ADP
cana-729	105	2	the	the	DET
cana-729	105	3	third	third	ADJ
cana-729	105	4	stage	stage	NOUN
cana-729	105	5	,	,	PUNCT
cana-729	105	6	the	the	DET
cana-729	105	7	forecasting	forecasting	NOUN
cana-729	105	8	model	model	NOUN
cana-729	105	9	was	be	AUX
cana-729	105	10	implemented	implement	VERB
cana-729	105	11	using	use	VERB
cana-729	105	12	the	the	DET
cana-729	105	13	long	long	ADJ
cana-729	105	14	short	short	ADJ
cana-729	105	15	-	-	PUNCT
cana-729	105	16	term	term	NOUN
cana-729	105	17	memory	memory	NOUN
cana-729	105	18	model	model	NOUN
cana-729	105	19	(	(	PUNCT
cana-729	105	20	lstm	lstm	PROPN
cana-729	105	21	)	)	PUNCT
cana-729	105	22	,	,	PUNCT
cana-729	105	23	the	the	DET
cana-729	105	24	auto	auto	NOUN
cana-729	105	25	-	-	PUNCT
cana-729	105	26	regressive	regressive	ADJ
cana-729	105	27	model	model	NOUN
cana-729	105	28	(	(	PUNCT
cana-729	105	29	ar	ar	NOUN
cana-729	105	30	)	)	PUNCT
cana-729	105	31	and	and	CCONJ
cana-729	105	32	the	the	DET
cana-729	105	33	autocommunications	autocommunication	NOUN
cana-729	105	34	on	on	ADP
cana-729	105	35	applied	apply	VERB
cana-729	105	36	nonlinear	nonlinear	ADJ
cana-729	105	37	analysis	analysis	NOUN
cana-729	105	38	issn	issn	NOUN
cana-729	105	39	:	:	PUNCT
cana-729	105	40	1074	1074	NUM
cana-729	105	41	-	-	PUNCT
cana-729	105	42	133x	133x	NUM
cana-729	105	43	vol	vol	NOUN
cana-729	105	44	31	31	NUM
cana-729	105	45	no	no	NOUN
cana-729	105	46	.	.	PUNCT
cana-729	106	1	3s	3s	NUM
cana-729	106	2	(	(	PUNCT
cana-729	106	3	2024	2024	NUM
cana-729	106	4	)	)	PUNCT
cana-729	106	5	33	33	NUM
cana-729	106	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-729	106	7	regressive	regressive	ADJ
cana-729	106	8	integrated	integrated	ADJ
cana-729	106	9	moving	move	VERB
cana-729	106	10	average	average	ADJ
cana-729	106	11	model	model	NOUN
cana-729	106	12	(	(	PUNCT
cana-729	106	13	arima	arima	PROPN
cana-729	106	14	)	)	PUNCT
cana-729	106	15	.	.	PUNCT
cana-729	107	1	in	in	ADP
cana-729	107	2	the	the	DET
cana-729	107	3	fourth	fourth	ADJ
cana-729	107	4	stage	stage	NOUN
cana-729	107	5	classification	classification	NOUN
cana-729	107	6	of	of	ADP
cana-729	107	7	the	the	DET
cana-729	107	8	forecasted	forecast	VERB
cana-729	107	9	precipitation	precipitation	NOUN
cana-729	107	10	was	be	AUX
cana-729	107	11	done	do	VERB
cana-729	107	12	using	use	VERB
cana-729	107	13	naïve	naïve	ADJ
cana-729	107	14	bayes	baye	NOUN
cana-729	107	15	and	and	CCONJ
cana-729	107	16	support	support	VERB
cana-729	107	17	vector	vector	NOUN
cana-729	107	18	classifier	classifier	NOUN
cana-729	107	19	(	(	PUNCT
cana-729	107	20	svc	svc	PROPN
cana-729	107	21	)	)	PUNCT
cana-729	107	22	.	.	PUNCT
cana-729	108	1	3.1	3.1	NUM
cana-729	108	2	data	datum	NOUN
cana-729	108	3	collection	collection	NOUN
cana-729	108	4	the	the	DET
cana-729	108	5	dataset	dataset	NOUN
cana-729	108	6	was	be	AUX
cana-729	108	7	collected	collect	VERB
cana-729	108	8	from	from	ADP
cana-729	108	9	the	the	DET
cana-729	108	10	official	official	ADJ
cana-729	108	11	website	website	NOUN
cana-729	108	12	of	of	ADP
cana-729	108	13	the	the	DET
cana-729	108	14	special	special	ADJ
cana-729	108	15	relief	relief	NOUN
cana-729	108	16	organisation	organisation	NOUN
cana-729	108	17	,	,	PUNCT
cana-729	108	18	government	government	NOUN
cana-729	108	19	of	of	ADP
cana-729	108	20	odisha	odisha	PROPN
cana-729	108	21	.	.	PUNCT
cana-729	109	1	this	this	DET
cana-729	109	2	organisation	organisation	NOUN
cana-729	109	3	was	be	AUX
cana-729	109	4	created	create	VERB
cana-729	109	5	for	for	ADP
cana-729	109	6	relief	relief	NOUN
cana-729	109	7	and	and	CCONJ
cana-729	109	8	rescue	rescue	NOUN
cana-729	109	9	operations	operation	NOUN
cana-729	109	10	during	during	ADP
cana-729	109	11	various	various	ADJ
cana-729	109	12	natural	natural	ADJ
cana-729	109	13	calamities	calamity	NOUN
cana-729	109	14	.	.	PUNCT
cana-729	110	1	the	the	DET
cana-729	110	2	data	data	NOUN
cana-729	110	3	collection	collection	NOUN
cana-729	110	4	and	and	CCONJ
cana-729	110	5	analysis	analysis	NOUN
cana-729	110	6	was	be	AUX
cana-729	110	7	done	do	VERB
cana-729	110	8	on	on	ADP
cana-729	110	9	windows	window	NOUN
cana-729	110	10	10	10	NUM
cana-729	110	11	(	(	PUNCT
cana-729	110	12	64	64	NUM
cana-729	110	13	-	-	PUNCT
cana-729	110	14	bit	bit	NOUN
cana-729	110	15	)	)	PUNCT
cana-729	110	16	,	,	PUNCT
cana-729	110	17	and	and	CCONJ
cana-729	110	18	microsoft	microsoft	PROPN
cana-729	110	19	excel	excel	VERB
cana-729	110	20	(	(	PUNCT
cana-729	110	21	2016	2016	NUM
cana-729	110	22	version	version	NOUN
cana-729	110	23	)	)	PUNCT
cana-729	110	24	was	be	AUX
cana-729	110	25	used	use	VERB
cana-729	110	26	for	for	ADP
cana-729	110	27	consolidating	consolidate	VERB
cana-729	110	28	and	and	CCONJ
cana-729	110	29	grouping	group	VERB
cana-729	110	30	the	the	DET
cana-729	110	31	data	datum	NOUN
cana-729	110	32	.	.	PUNCT
cana-729	111	1	python	python	PROPN
cana-729	111	2	(	(	PUNCT
cana-729	111	3	3.8.8	3.8.8	NUM
cana-729	111	4	version	version	NOUN
cana-729	111	5	)	)	PUNCT
cana-729	111	6	was	be	AUX
cana-729	111	7	used	use	VERB
cana-729	111	8	for	for	ADP
cana-729	111	9	forecasting	forecasting	NOUN
cana-729	111	10	and	and	CCONJ
cana-729	111	11	performing	perform	VERB
cana-729	111	12	classification	classification	NOUN
cana-729	111	13	algorithms	algorithm	NOUN
cana-729	111	14	.	.	PUNCT
cana-729	112	1	the	the	DET
cana-729	112	2	dataset	dataset	NOUN
cana-729	112	3	contains	contain	VERB
cana-729	112	4	daily	daily	ADJ
cana-729	112	5	rainfall	rainfall	NOUN
cana-729	112	6	that	that	PRON
cana-729	112	7	was	be	AUX
cana-729	112	8	recorded	record	VERB
cana-729	112	9	from	from	ADP
cana-729	112	10	the	the	DET
cana-729	112	11	year	year	NOUN
cana-729	112	12	1998	1998	NUM
cana-729	112	13	to	to	ADP
cana-729	112	14	2021	2021	NUM
cana-729	112	15	for	for	ADP
cana-729	112	16	all	all	DET
cana-729	112	17	the	the	DET
cana-729	112	18	blocks	block	NOUN
cana-729	112	19	under	under	ADP
cana-729	112	20	all	all	DET
cana-729	112	21	30	30	NUM
cana-729	112	22	districts	district	NOUN
cana-729	112	23	in	in	ADP
cana-729	112	24	odisha	odisha	PROPN
cana-729	112	25	.	.	PUNCT
cana-729	113	1	there	there	PRON
cana-729	113	2	are	be	VERB
cana-729	113	3	30	30	NUM
cana-729	113	4	districts	district	NOUN
cana-729	113	5	in	in	ADP
cana-729	113	6	odisha	odisha	PROPN
cana-729	113	7	namely	namely	ADV
cana-729	113	8	–	–	PUNCT
cana-729	113	9	angul	angul	NOUN
cana-729	113	10	,	,	PUNCT
cana-729	113	11	balangir	balangir	NOUN
cana-729	113	12	,	,	PUNCT
cana-729	113	13	bargarh	bargarh	ADJ
cana-729	113	14	,	,	PUNCT
cana-729	113	15	dhenkanal	dhenkanal	ADJ
cana-729	113	16	,	,	PUNCT
cana-729	113	17	rayagada	rayagada	PROPN
cana-729	113	18	,	,	PUNCT
cana-729	113	19	koraput	koraput	PROPN
cana-729	113	20	,	,	PUNCT
cana-729	113	21	debagarh	debagarh	PROPN
cana-729	113	22	,	,	PUNCT
cana-729	113	23	kendujhar	kendujhar	NOUN
cana-729	113	24	,	,	PUNCT
cana-729	113	25	sambalpur	sambalpur	NOUN
cana-729	113	26	,	,	PUNCT
cana-729	113	27	subarnapur	subarnapur	PROPN
cana-729	113	28	sundargarh	sundargarh	PROPN
cana-729	113	29	,	,	PUNCT
cana-729	113	30	bhadrak	bhadrak	NOUN
cana-729	113	31	,	,	PUNCT
cana-729	113	32	cuttack	cuttack	NOUN
cana-729	113	33	,	,	PUNCT
cana-729	113	34	jagatsinghpur	jagatsinghpur	NOUN
cana-729	113	35	,	,	PUNCT
cana-729	113	36	kendrapara	kendrapara	PROPN
cana-729	113	37	,	,	PUNCT
cana-729	113	38	khordha	khordha	PROPN
cana-729	113	39	mayurbhanj	mayurbhanj	NOUN
cana-729	113	40	,	,	PUNCT
cana-729	113	41	puri	puri	PROPN
cana-729	113	42	,	,	PUNCT
cana-729	113	43	boudh	boudh	PROPN
cana-729	113	44	,	,	PUNCT
cana-729	113	45	gajapati	gajapati	PROPN
cana-729	113	46	,	,	PUNCT
cana-729	113	47	ganjam	ganjam	PROPN
cana-729	113	48	,	,	PUNCT
cana-729	113	49	kalahandi	kalahandi	NOUN
cana-729	113	50	,	,	PUNCT
cana-729	113	51	nuapada	nuapada	PROPN
cana-729	113	52	,	,	PUNCT
cana-729	113	53	jajpur	jajpur	NOUN
cana-729	113	54	,	,	PUNCT
cana-729	113	55	kandhamal	kandhamal	ADJ
cana-729	113	56	,	,	PUNCT
cana-729	113	57	malkangiri	malkangiri	NOUN
cana-729	113	58	,	,	PUNCT
cana-729	113	59	nabrangpur	nabrangpur	PROPN
cana-729	113	60	,	,	PUNCT
cana-729	113	61	balasore	balasore	NOUN
cana-729	113	62	,	,	PUNCT
cana-729	113	63	nayagarh	nayagarh	PROPN
cana-729	113	64	,	,	PUNCT
cana-729	113	65	jharsuguda	jharsuguda	NOUN
cana-729	113	66	and	and	CCONJ
cana-729	113	67	there	there	PRON
cana-729	113	68	are	be	VERB
cana-729	113	69	315	315	NUM
cana-729	113	70	blocks	block	NOUN
cana-729	113	71	that	that	PRON
cana-729	113	72	comes	come	VERB
cana-729	113	73	under	under	ADP
cana-729	113	74	these	these	DET
cana-729	113	75	30	30	NUM
cana-729	113	76	districts	district	NOUN
cana-729	113	77	.	.	PUNCT
cana-729	114	1	3.2	3.2	NUM
cana-729	114	2	pre	pre	NOUN
cana-729	114	3	processing	processing	NOUN
cana-729	114	4	of	of	ADP
cana-729	114	5	data	datum	NOUN
cana-729	114	6	the	the	DET
cana-729	114	7	raw	raw	ADJ
cana-729	114	8	data	datum	NOUN
cana-729	114	9	that	that	PRON
cana-729	114	10	consists	consist	VERB
cana-729	114	11	of	of	ADP
cana-729	114	12	the	the	DET
cana-729	114	13	daily	daily	ADJ
cana-729	114	14	rainfall	rainfall	NOUN
cana-729	114	15	data	datum	NOUN
cana-729	114	16	for	for	ADP
cana-729	114	17	each	each	DET
cana-729	114	18	block	block	NOUN
cana-729	114	19	of	of	ADP
cana-729	114	20	odisha	odisha	PROPN
cana-729	114	21	was	be	AUX
cana-729	114	22	aggregated	aggregate	VERB
cana-729	114	23	to	to	PART
cana-729	114	24	districtwise	districtwise	VERB
cana-729	114	25	.	.	PUNCT
cana-729	115	1	instead	instead	ADV
cana-729	115	2	of	of	ADP
cana-729	115	3	considering	consider	VERB
cana-729	115	4	the	the	DET
cana-729	115	5	whole	whole	ADJ
cana-729	115	6	dataset	dataset	NOUN
cana-729	115	7	only	only	ADV
cana-729	115	8	28	28	NUM
cana-729	115	9	years	year	NOUN
cana-729	115	10	of	of	ADP
cana-729	115	11	data	datum	NOUN
cana-729	115	12	was	be	AUX
cana-729	115	13	considered	consider	VERB
cana-729	115	14	because	because	SCONJ
cana-729	115	15	before	before	ADP
cana-729	115	16	1993	1993	NUM
cana-729	115	17	there	there	PRON
cana-729	115	18	were	be	VERB
cana-729	115	19	only	only	ADV
cana-729	115	20	13	13	NUM
cana-729	115	21	districts	district	NOUN
cana-729	115	22	in	in	ADP
cana-729	115	23	odisha	odisha	PROPN
cana-729	115	24	namely	namely	ADV
cana-729	115	25	–	–	PUNCT
cana-729	115	26	keonjhar	keonjhar	PROPN
cana-729	115	27	,	,	PUNCT
cana-729	115	28	bolangir	bolangir	ADJ
cana-729	115	29	,	,	PUNCT
cana-729	115	30	cuttack	cuttack	NOUN
cana-729	115	31	,	,	PUNCT
cana-729	115	32	dhenkanal	dhenkanal	ADJ
cana-729	115	33	,	,	PUNCT
cana-729	115	34	kalahandi	kalahandi	NOUN
cana-729	115	35	,	,	PUNCT
cana-729	115	36	koraput	koraput	NOUN
cana-729	115	37	,	,	PUNCT
cana-729	115	38	mayurbhanj	mayurbhanj	ADJ
cana-729	115	39	,	,	PUNCT
cana-729	115	40	phulbani	phulbani	PROPN
cana-729	115	41	,	,	PUNCT
cana-729	115	42	puri	puri	PROPN
cana-729	115	43	,	,	PUNCT
cana-729	115	44	balasore	balasore	NOUN
cana-729	115	45	,	,	PUNCT
cana-729	115	46	sambalpur	sambalpur	NOUN
cana-729	115	47	,	,	PUNCT
cana-729	115	48	ganjam	ganjam	NOUN
cana-729	115	49	,	,	PUNCT
cana-729	115	50	and	and	CCONJ
cana-729	115	51	sundargarh	sundargarh	NOUN
cana-729	115	52	.	.	PUNCT
cana-729	116	1	but	but	CCONJ
cana-729	116	2	from	from	ADP
cana-729	116	3	1993	1993	NUM
cana-729	116	4	these	these	DET
cana-729	116	5	13	13	NUM
cana-729	116	6	districts	district	NOUN
cana-729	116	7	were	be	AUX
cana-729	116	8	further	far	ADV
cana-729	116	9	divided	divide	VERB
cana-729	116	10	into	into	ADP
cana-729	116	11	30	30	NUM
cana-729	116	12	districts	district	NOUN
cana-729	116	13	.	.	PUNCT
cana-729	117	1	after	after	ADP
cana-729	117	2	getting	get	VERB
cana-729	117	3	it	it	PRON
cana-729	117	4	aggregated	aggregate	VERB
cana-729	117	5	average	average	ADJ
cana-729	117	6	rainfall	rainfall	NOUN
cana-729	117	7	and	and	CCONJ
cana-729	117	8	standard	standard	ADJ
cana-729	117	9	deviation	deviation	NOUN
cana-729	117	10	for	for	ADP
cana-729	117	11	28	28	NUM
cana-729	117	12	years	year	NOUN
cana-729	117	13	were	be	AUX
cana-729	117	14	calculated	calculate	VERB
cana-729	117	15	for	for	ADP
cana-729	117	16	each	each	DET
cana-729	117	17	district	district	NOUN
cana-729	117	18	.	.	PUNCT
cana-729	118	1	here	here	ADV
cana-729	118	2	simple	simple	ADJ
cana-729	118	3	statistical	statistical	ADJ
cana-729	118	4	measures	measure	NOUN
cana-729	118	5	like	like	ADP
cana-729	118	6	average	average	ADJ
cana-729	118	7	and	and	CCONJ
cana-729	118	8	standard	standard	ADJ
cana-729	118	9	deviation	deviation	NOUN
cana-729	118	10	were	be	AUX
cana-729	118	11	used	use	VERB
cana-729	118	12	for	for	ADP
cana-729	118	13	the	the	DET
cana-729	118	14	classification	classification	NOUN
cana-729	118	15	of	of	ADP
cana-729	118	16	different	different	ADJ
cana-729	118	17	districts	district	NOUN
cana-729	118	18	into	into	ADP
cana-729	118	19	different	different	ADJ
cana-729	118	20	drought	drought	NOUN
cana-729	118	21	severity	severity	NOUN
cana-729	118	22	.	.	PUNCT
cana-729	119	1	using	use	VERB
cana-729	119	2	the	the	DET
cana-729	119	3	average	average	ADJ
cana-729	119	4	and	and	CCONJ
cana-729	119	5	standard	standard	ADJ
cana-729	119	6	deviation	deviation	NOUN
cana-729	119	7	of	of	ADP
cana-729	119	8	28	28	NUM
cana-729	119	9	years	year	NOUN
cana-729	119	10	of	of	ADP
cana-729	119	11	rainfall	rainfall	NOUN
cana-729	119	12	(	(	PUNCT
cana-729	119	13	where	where	SCONJ
cana-729	119	14	standard	standard	ADJ
cana-729	119	15	deviation	deviation	NOUN
cana-729	119	16	was	be	AUX
cana-729	119	17	calculated	calculate	VERB
cana-729	119	18	for	for	ADP
cana-729	119	19	28	28	NUM
cana-729	119	20	years	year	NOUN
cana-729	119	21	of	of	ADP
cana-729	119	22	yearly	yearly	ADJ
cana-729	119	23	rainfall	rainfall	NOUN
cana-729	119	24	record	record	NOUN
cana-729	119	25	)	)	PUNCT
cana-729	119	26	each	each	DET
cana-729	119	27	district	district	NOUN
cana-729	119	28	was	be	AUX
cana-729	119	29	categorised	categorise	VERB
cana-729	119	30	into	into	ADP
cana-729	119	31	four	four	NUM
cana-729	119	32	different	different	ADJ
cana-729	119	33	categories	category	NOUN
cana-729	119	34	according	accord	VERB
cana-729	119	35	to	to	ADP
cana-729	119	36	the	the	DET
cana-729	119	37	severity	severity	NOUN
cana-729	119	38	level	level	NOUN
cana-729	119	39	namely	namely	ADV
cana-729	119	40	severe	severe	ADJ
cana-729	119	41	drought	drought	NOUN
cana-729	119	42	(	(	PUNCT
cana-729	119	43	sd	sd	NOUN
cana-729	119	44	)	)	PUNCT
cana-729	119	45	,	,	PUNCT
cana-729	119	46	moderate	moderate	ADJ
cana-729	119	47	drought	drought	NOUN
cana-729	119	48	(	(	PUNCT
cana-729	119	49	md	md	PROPN
cana-729	119	50	)	)	PUNCT
cana-729	119	51	,	,	PUNCT
cana-729	119	52	no	no	DET
cana-729	119	53	drought	drought	NOUN
cana-729	119	54	(	(	PUNCT
cana-729	119	55	nd	nd	NOUN
cana-729	119	56	)	)	PUNCT
cana-729	119	57	and	and	CCONJ
cana-729	119	58	flood	flood	NOUN
cana-729	119	59	(	(	PUNCT
cana-729	119	60	fl	fl	NOUN
cana-729	119	61	)	)	PUNCT
cana-729	119	62	.	.	PUNCT
cana-729	120	1	the	the	DET
cana-729	120	2	categorisation	categorisation	NOUN
cana-729	120	3	was	be	AUX
cana-729	120	4	done	do	VERB
cana-729	120	5	in	in	ADP
cana-729	120	6	such	such	DET
cana-729	120	7	a	a	DET
cana-729	120	8	way	way	NOUN
cana-729	120	9	that	that	PRON
cana-729	120	10	–	–	PUNCT
cana-729	120	11	•	•	NOUN
cana-729	120	12	if	if	SCONJ
cana-729	120	13	the	the	DET
cana-729	120	14	average	average	ADJ
cana-729	120	15	rainfall	rainfall	NOUN
cana-729	120	16	for	for	ADP
cana-729	120	17	a	a	DET
cana-729	120	18	particular	particular	ADJ
cana-729	120	19	district	district	NOUN
cana-729	120	20	for	for	ADP
cana-729	120	21	a	a	DET
cana-729	120	22	given	give	VERB
cana-729	120	23	year	year	NOUN
cana-729	120	24	falls	fall	VERB
cana-729	120	25	below	below	ADP
cana-729	120	26	the	the	DET
cana-729	120	27	difference	difference	NOUN
cana-729	120	28	in	in	ADP
cana-729	120	29	average	average	ADJ
cana-729	120	30	rainfall	rainfall	NOUN
cana-729	120	31	of	of	ADP
cana-729	120	32	28	28	NUM
cana-729	120	33	years	year	NOUN
cana-729	120	34	and	and	CCONJ
cana-729	120	35	0.5	0.5	NUM
cana-729	120	36	times	time	NOUN
cana-729	120	37	its	its	PRON
cana-729	120	38	standard	standard	ADJ
cana-729	120	39	deviation	deviation	NOUN
cana-729	120	40	,	,	PUNCT
cana-729	120	41	then	then	ADV
cana-729	120	42	it	it	PRON
cana-729	120	43	comes	come	VERB
cana-729	120	44	under	under	ADP
cana-729	120	45	severe	severe	ADJ
cana-729	120	46	drought	drought	NOUN
cana-729	120	47	(	(	PUNCT
cana-729	120	48	sd	sd	NOUN
cana-729	120	49	)	)	PUNCT
cana-729	120	50	situation	situation	NOUN
cana-729	120	51	.	.	PUNCT
cana-729	121	1	•	•	INTJ
cana-729	121	2	if	if	SCONJ
cana-729	121	3	the	the	DET
cana-729	121	4	average	average	ADJ
cana-729	121	5	rainfall	rainfall	NOUN
cana-729	121	6	for	for	ADP
cana-729	121	7	a	a	DET
cana-729	121	8	particular	particular	ADJ
cana-729	121	9	district	district	NOUN
cana-729	121	10	for	for	ADP
cana-729	121	11	a	a	DET
cana-729	121	12	given	give	VERB
cana-729	121	13	year	year	NOUN
cana-729	121	14	falls	fall	VERB
cana-729	121	15	in	in	ADP
cana-729	121	16	between	between	ADP
cana-729	121	17	its	its	PRON
cana-729	121	18	average	average	ADJ
cana-729	121	19	rainfall	rainfall	NOUN
cana-729	121	20	of	of	ADP
cana-729	121	21	28	28	NUM
cana-729	121	22	years	year	NOUN
cana-729	121	23	and	and	CCONJ
cana-729	121	24	the	the	DET
cana-729	121	25	difference	difference	NOUN
cana-729	121	26	of	of	ADP
cana-729	121	27	average	average	ADJ
cana-729	121	28	rainfall	rainfall	NOUN
cana-729	121	29	of	of	ADP
cana-729	121	30	28	28	NUM
cana-729	121	31	years	year	NOUN
cana-729	121	32	and	and	CCONJ
cana-729	121	33	0.5	0.5	NUM
cana-729	121	34	times	time	NOUN
cana-729	121	35	its	its	PRON
cana-729	121	36	standard	standard	ADJ
cana-729	121	37	deviation	deviation	NOUN
cana-729	121	38	,	,	PUNCT
cana-729	121	39	then	then	ADV
cana-729	121	40	it	it	PRON
cana-729	121	41	comes	come	VERB
cana-729	121	42	under	under	ADP
cana-729	121	43	a	a	DET
cana-729	121	44	moderate	moderate	ADJ
cana-729	121	45	drought	drought	NOUN
cana-729	121	46	(	(	PUNCT
cana-729	121	47	md	md	PROPN
cana-729	121	48	)	)	PUNCT
cana-729	121	49	situation	situation	NOUN
cana-729	121	50	.	.	PUNCT
cana-729	122	1	•	•	INTJ
cana-729	122	2	if	if	SCONJ
cana-729	122	3	the	the	DET
cana-729	122	4	average	average	ADJ
cana-729	122	5	rainfall	rainfall	NOUN
cana-729	122	6	for	for	ADP
cana-729	122	7	a	a	DET
cana-729	122	8	particular	particular	ADJ
cana-729	122	9	district	district	NOUN
cana-729	122	10	for	for	ADP
cana-729	122	11	a	a	DET
cana-729	122	12	given	give	VERB
cana-729	122	13	year	year	NOUN
cana-729	122	14	falls	fall	VERB
cana-729	122	15	in	in	ADP
cana-729	122	16	between	between	ADP
cana-729	122	17	its	its	PRON
cana-729	122	18	average	average	ADJ
cana-729	122	19	rainfall	rainfall	NOUN
cana-729	122	20	of	of	ADP
cana-729	122	21	28	28	NUM
cana-729	122	22	years	year	NOUN
cana-729	122	23	and	and	CCONJ
cana-729	122	24	the	the	DET
cana-729	122	25	sum	sum	NOUN
cana-729	122	26	of	of	ADP
cana-729	122	27	the	the	DET
cana-729	122	28	average	average	ADJ
cana-729	122	29	rainfall	rainfall	NOUN
cana-729	122	30	of	of	ADP
cana-729	122	31	28	28	NUM
cana-729	122	32	years	year	NOUN
cana-729	122	33	and	and	CCONJ
cana-729	122	34	0.5	0.5	NUM
cana-729	122	35	times	time	NOUN
cana-729	122	36	its	its	PRON
cana-729	122	37	standard	standard	ADJ
cana-729	122	38	deviation	deviation	NOUN
cana-729	122	39	,	,	PUNCT
cana-729	122	40	then	then	ADV
cana-729	122	41	it	it	PRON
cana-729	122	42	comes	come	VERB
cana-729	122	43	under	under	ADP
cana-729	122	44	the	the	DET
cana-729	122	45	no	no	DET
cana-729	122	46	drought	drought	NOUN
cana-729	122	47	(	(	PUNCT
cana-729	122	48	nd	nd	NOUN
cana-729	122	49	)	)	PUNCT
cana-729	122	50	situation	situation	NOUN
cana-729	122	51	.	.	PUNCT
cana-729	123	1	•	•	INTJ
cana-729	123	2	if	if	SCONJ
cana-729	123	3	the	the	DET
cana-729	123	4	average	average	ADJ
cana-729	123	5	rainfall	rainfall	NOUN
cana-729	123	6	for	for	ADP
cana-729	123	7	a	a	DET
cana-729	123	8	particular	particular	ADJ
cana-729	123	9	district	district	NOUN
cana-729	123	10	for	for	ADP
cana-729	123	11	a	a	DET
cana-729	123	12	given	give	VERB
cana-729	123	13	year	year	NOUN
cana-729	123	14	falls	fall	VERB
cana-729	123	15	above	above	ADP
cana-729	123	16	the	the	DET
cana-729	123	17	sum	sum	NOUN
cana-729	123	18	average	average	ADJ
cana-729	123	19	rainfall	rainfall	NOUN
cana-729	123	20	of	of	ADP
cana-729	123	21	28	28	NUM
cana-729	123	22	years	year	NOUN
cana-729	123	23	and	and	CCONJ
cana-729	123	24	0.5	0.5	NUM
cana-729	123	25	times	time	NOUN
cana-729	123	26	its	its	PRON
cana-729	123	27	standard	standard	ADJ
cana-729	123	28	deviation	deviation	NOUN
cana-729	123	29	,	,	PUNCT
cana-729	123	30	then	then	ADV
cana-729	123	31	it	it	PRON
cana-729	123	32	comes	come	VERB
cana-729	123	33	under	under	ADP
cana-729	123	34	the	the	DET
cana-729	123	35	flood	flood	NOUN
cana-729	123	36	(	(	PUNCT
cana-729	123	37	fl	fl	NOUN
cana-729	123	38	)	)	PUNCT
cana-729	123	39	situation	situation	NOUN
cana-729	123	40	.	.	PUNCT
cana-729	124	1	communications	communication	NOUN
cana-729	124	2	on	on	ADP
cana-729	124	3	applied	apply	VERB
cana-729	124	4	nonlinear	nonlinear	ADJ
cana-729	124	5	analysis	analysis	NOUN
cana-729	124	6	issn	issn	NOUN
cana-729	124	7	:	:	PUNCT
cana-729	124	8	1074	1074	NUM
cana-729	124	9	-	-	PUNCT
cana-729	124	10	133x	133x	NUM
cana-729	124	11	vol	vol	NOUN
cana-729	124	12	31	31	NUM
cana-729	124	13	no	no	NOUN
cana-729	124	14	.	.	PUNCT
cana-729	125	1	3s	3s	NUM
cana-729	125	2	(	(	PUNCT
cana-729	125	3	2024	2024	NUM
cana-729	125	4	)	)	PUNCT
cana-729	125	5	34	34	NUM
cana-729	125	6	https://internationalpubls.com	https://internationalpubls.com	SYM
cana-729	125	7	3.3	3.3	NUM
cana-729	125	8	forecasting	forecasting	NOUN
cana-729	125	9	model	model	NOUN
cana-729	125	10	for	for	ADP
cana-729	125	11	forecasting	forecast	VERB
cana-729	125	12	three	three	NUM
cana-729	125	13	models	model	NOUN
cana-729	125	14	have	have	AUX
cana-729	125	15	been	be	AUX
cana-729	125	16	used	use	VERB
cana-729	125	17	i.e.	i.e.	ADV
cana-729	125	18	,	,	PUNCT
cana-729	125	19	the	the	DET
cana-729	125	20	auto	auto	NOUN
cana-729	125	21	-	-	PUNCT
cana-729	125	22	regressive	regressive	ADJ
cana-729	125	23	model	model	NOUN
cana-729	125	24	(	(	PUNCT
cana-729	125	25	ar	ar	NOUN
cana-729	125	26	)	)	PUNCT
cana-729	125	27	,	,	PUNCT
cana-729	125	28	long	long	ADJ
cana-729	125	29	short	short	ADJ
cana-729	125	30	-	-	PUNCT
cana-729	125	31	term	term	NOUN
cana-729	125	32	memory	memory	NOUN
cana-729	125	33	model	model	NOUN
cana-729	125	34	(	(	PUNCT
cana-729	125	35	lstm	lstm	NOUN
cana-729	125	36	)	)	PUNCT
cana-729	125	37	and	and	CCONJ
cana-729	125	38	auto	auto	NOUN
cana-729	125	39	-	-	PUNCT
cana-729	125	40	regressive	regressive	ADJ
cana-729	125	41	integrated	integrated	ADJ
cana-729	125	42	moving	move	VERB
cana-729	125	43	average	average	NOUN
cana-729	125	44	(	(	PUNCT
cana-729	125	45	arima	arima	PROPN
cana-729	125	46	)	)	PUNCT
cana-729	125	47	.	.	PUNCT
cana-729	126	1	for	for	ADP
cana-729	126	2	these	these	DET
cana-729	126	3	models	model	NOUN
cana-729	126	4	,	,	PUNCT
cana-729	126	5	the	the	DET
cana-729	126	6	dataset	dataset	NOUN
cana-729	126	7	was	be	AUX
cana-729	126	8	split	split	VERB
cana-729	126	9	into	into	ADP
cana-729	126	10	a	a	DET
cana-729	126	11	train	train	NOUN
cana-729	126	12	set	set	NOUN
cana-729	126	13	and	and	CCONJ
cana-729	126	14	a	a	DET
cana-729	126	15	test	test	NOUN
cana-729	126	16	set	set	VERB
cana-729	126	17	in	in	ADP
cana-729	126	18	the	the	DET
cana-729	126	19	ratio	ratio	NOUN
cana-729	126	20	90:10	90:10	NUM
cana-729	126	21	.	.	PUNCT
cana-729	127	1	3.3.1	3.3.1	NUM
cana-729	127	2	ar	ar	NOUN
cana-729	127	3	model	model	NOUN
cana-729	127	4	when	when	SCONJ
cana-729	127	5	there	there	PRON
cana-729	127	6	is	be	VERB
cana-729	127	7	any	any	DET
cana-729	127	8	association	association	NOUN
cana-729	127	9	between	between	ADP
cana-729	127	10	the	the	DET
cana-729	127	11	values	value	NOUN
cana-729	127	12	in	in	ADP
cana-729	127	13	a	a	DET
cana-729	127	14	time	time	NOUN
cana-729	127	15	series	series	NOUN
cana-729	127	16	and	and	CCONJ
cana-729	127	17	the	the	DET
cana-729	127	18	values	value	NOUN
cana-729	127	19	that	that	PRON
cana-729	127	20	succeed	succeed	VERB
cana-729	127	21	and	and	CCONJ
cana-729	127	22	precede	precede	VERB
cana-729	127	23	them	they	PRON
cana-729	127	24	,	,	PUNCT
cana-729	127	25	an	an	DET
cana-729	127	26	auto	auto	NOUN
cana-729	127	27	-	-	PUNCT
cana-729	127	28	regressive	regressive	ADJ
cana-729	127	29	(	(	PUNCT
cana-729	127	30	ar	ar	NOUN
cana-729	127	31	)	)	PUNCT
cana-729	127	32	model	model	NOUN
cana-729	127	33	is	be	AUX
cana-729	127	34	used	use	VERB
cana-729	127	35	to	to	PART
cana-729	127	36	anticipate	anticipate	VERB
cana-729	127	37	future	future	ADJ
cana-729	127	38	behaviour	behaviour	NOUN
cana-729	127	39	based	base	VERB
cana-729	127	40	on	on	ADP
cana-729	127	41	previous	previous	ADJ
cana-729	127	42	behaviour	behaviour	NOUN
cana-729	127	43	.	.	PUNCT
cana-729	128	1	it	it	PRON
cana-729	128	2	is	be	AUX
cana-729	128	3	a	a	DET
cana-729	128	4	linear	linear	ADJ
cana-729	128	5	regression	regression	NOUN
cana-729	128	6	of	of	ADP
cana-729	128	7	the	the	DET
cana-729	128	8	data	datum	NOUN
cana-729	128	9	in	in	ADP
cana-729	128	10	the	the	DET
cana-729	128	11	time	time	NOUN
cana-729	128	12	series	series	NOUN
cana-729	128	13	against	against	ADP
cana-729	128	14	one	one	NUM
cana-729	128	15	or	or	CCONJ
cana-729	128	16	more	more	ADJ
cana-729	128	17	previous	previous	ADJ
cana-729	128	18	values	value	NOUN
cana-729	128	19	in	in	ADP
cana-729	128	20	the	the	DET
cana-729	128	21	same	same	ADJ
cana-729	128	22	time	time	NOUN
cana-729	128	23	series	series	NOUN
cana-729	128	24	,	,	PUNCT
cana-729	128	25	i.e.	i.e.	X
cana-729	128	26	,	,	PUNCT
cana-729	128	27	the	the	DET
cana-729	128	28	value	value	NOUN
cana-729	128	29	of	of	ADP
cana-729	128	30	the	the	DET
cana-729	128	31	outcome	outcome	NOUN
cana-729	128	32	variable	variable	NOUN
cana-729	128	33	(	(	PUNCT
cana-729	128	34	y	y	NOUN
cana-729	128	35	)	)	PUNCT
cana-729	128	36	at	at	ADP
cana-729	128	37	time	time	NOUN
cana-729	128	38	t	t	PROPN
cana-729	128	39	is	be	AUX
cana-729	128	40	similar	similar	ADJ
cana-729	128	41	to	to	ADP
cana-729	128	42	simple	simple	ADJ
cana-729	128	43	linear	linear	ADJ
cana-729	128	44	regression	regression	NOUN
cana-729	128	45	where	where	SCONJ
cana-729	128	46	the	the	DET
cana-729	128	47	predictor	predictor	NOUN
cana-729	128	48	variable	variable	NOUN
cana-729	128	49	is	be	AUX
cana-729	128	50	directly	directly	ADV
cana-729	128	51	associated	associate	VERB
cana-729	128	52	(	(	PUNCT
cana-729	128	53	x	x	NOUN
cana-729	128	54	)	)	PUNCT
cana-729	128	55	.	.	PUNCT
cana-729	129	1	however	however	ADV
cana-729	129	2	,	,	PUNCT
cana-729	129	3	the	the	DET
cana-729	129	4	ar	ar	PROPN
cana-729	129	5	model	model	PROPN
cana-729	129	6	differs	differ	VERB
cana-729	129	7	from	from	ADP
cana-729	129	8	a	a	DET
cana-729	129	9	basic	basic	ADJ
cana-729	129	10	linear	linear	ADJ
cana-729	129	11	regression	regression	NOUN
cana-729	129	12	in	in	ADP
cana-729	129	13	that	that	PRON
cana-729	129	14	y	y	PROPN
cana-729	129	15	is	be	AUX
cana-729	129	16	dependent	dependent	ADJ
cana-729	129	17	on	on	ADP
cana-729	129	18	x	x	X
cana-729	129	19	and	and	CCONJ
cana-729	129	20	prior	prior	ADJ
cana-729	129	21	y	y	PROPN
cana-729	129	22	values	value	NOUN
cana-729	129	23	.	.	PUNCT
cana-729	130	1	3.3.2	3.3.2	NUM
cana-729	130	2	arima	arima	NOUN
cana-729	130	3	model	model	NOUN
cana-729	130	4	the	the	DET
cana-729	130	5	strength	strength	NOUN
cana-729	130	6	of	of	ADP
cana-729	130	7	a	a	DET
cana-729	130	8	dependent	dependent	ADJ
cana-729	130	9	variable	variable	NOUN
cana-729	130	10	relative	relative	NOUN
cana-729	130	11	to	to	ADP
cana-729	130	12	other	other	ADJ
cana-729	130	13	variables	variable	NOUN
cana-729	130	14	is	be	AUX
cana-729	130	15	used	use	VERB
cana-729	130	16	in	in	ADP
cana-729	130	17	the	the	DET
cana-729	130	18	autoregressive	autoregressive	ADJ
cana-729	130	19	integrated	integrated	ADJ
cana-729	130	20	moving	move	VERB
cana-729	130	21	average	average	ADJ
cana-729	130	22	(	(	PUNCT
cana-729	130	23	arima	arima	PROPN
cana-729	130	24	)	)	PUNCT
cana-729	130	25	model	model	NOUN
cana-729	130	26	,	,	PUNCT
cana-729	130	27	which	which	PRON
cana-729	130	28	is	be	AUX
cana-729	130	29	a	a	DET
cana-729	130	30	type	type	NOUN
cana-729	130	31	of	of	ADP
cana-729	130	32	regression	regression	NOUN
cana-729	130	33	analysis	analysis	NOUN
cana-729	130	34	.	.	PUNCT
cana-729	131	1	arima	arima	PROPN
cana-729	131	2	forecasts	forecast	VERB
cana-729	131	3	the	the	DET
cana-729	131	4	future	future	NOUN
cana-729	131	5	by	by	ADP
cana-729	131	6	looking	look	VERB
cana-729	131	7	at	at	ADP
cana-729	131	8	the	the	DET
cana-729	131	9	difference	difference	NOUN
cana-729	131	10	between	between	ADP
cana-729	131	11	values	value	NOUN
cana-729	131	12	in	in	ADP
cana-729	131	13	a	a	DET
cana-729	131	14	string	string	NOUN
cana-729	131	15	rather	rather	ADV
cana-729	131	16	than	than	ADP
cana-729	131	17	the	the	DET
cana-729	131	18	actual	actual	ADJ
cana-729	131	19	values	value	NOUN
cana-729	131	20	.	.	PUNCT
cana-729	132	1	"	"	PUNCT
cana-729	132	2	ar	ar	NOUN
cana-729	132	3	"	"	PUNCT
cana-729	132	4	stands	stand	VERB
cana-729	132	5	for	for	ADP
cana-729	132	6	auto	auto	NOUN
cana-729	132	7	regression	regression	NOUN
cana-729	132	8	,	,	PUNCT
cana-729	132	9	which	which	PRON
cana-729	132	10	depicts	depict	VERB
cana-729	132	11	a	a	DET
cana-729	132	12	converting	convert	VERB
cana-729	132	13	variable	variable	NOUN
cana-729	132	14	that	that	PRON
cana-729	132	15	regresses	regress	VERB
cana-729	132	16	on	on	ADP
cana-729	132	17	its	its	PRON
cana-729	132	18	very	very	ADV
cana-729	132	19	own	own	ADJ
cana-729	132	20	lagged	lag	VERB
cana-729	132	21	,	,	PUNCT
cana-729	132	22	or	or	CCONJ
cana-729	132	23	previous	previous	ADJ
cana-729	132	24	values	value	NOUN
cana-729	132	25	,	,	PUNCT
cana-729	132	26	"	"	PUNCT
cana-729	132	27	i	i	PRON
cana-729	132	28	"	"	PUNCT
cana-729	132	29	stands	stand	VERB
cana-729	132	30	for	for	ADP
cana-729	132	31	integrated	integrate	VERB
cana-729	132	32	,	,	PUNCT
cana-729	132	33	which	which	PRON
cana-729	132	34	depicts	depict	VERB
cana-729	132	35	the	the	DET
cana-729	132	36	differencing	differencing	NOUN
cana-729	132	37	of	of	ADP
cana-729	132	38	raw	raw	ADJ
cana-729	132	39	observations	observation	NOUN
cana-729	132	40	in	in	ADP
cana-729	132	41	the	the	DET
cana-729	132	42	dataset	dataset	NOUN
cana-729	132	43	in	in	ADP
cana-729	132	44	order	order	NOUN
cana-729	132	45	for	for	SCONJ
cana-729	132	46	the	the	DET
cana-729	132	47	time	time	NOUN
cana-729	132	48	series	series	NOUN
cana-729	132	49	to	to	PART
cana-729	132	50	become	become	VERB
cana-729	132	51	,	,	PUNCT
cana-729	132	52	and	and	CCONJ
cana-729	132	53	"	"	PUNCT
cana-729	132	54	ma	ma	PROPN
cana-729	132	55	"	"	PUNCT
cana-729	132	56	stands	stand	VERB
cana-729	132	57	for	for	ADP
cana-729	132	58	moving	move	VERB
cana-729	132	59	average	average	ADJ
cana-729	132	60	,	,	PUNCT
cana-729	132	61	which	which	PRON
cana-729	132	62	illustrates	illustrate	VERB
cana-729	132	63	how	how	SCONJ
cana-729	132	64	an	an	DET
cana-729	132	65	observation	observation	NOUN
cana-729	132	66	and	and	CCONJ
cana-729	132	67	how	how	SCONJ
cana-729	132	68	the	the	DET
cana-729	132	69	residual	residual	ADJ
cana-729	132	70	error	error	NOUN
cana-729	132	71	of	of	ADP
cana-729	132	72	a	a	DET
cana-729	132	73	moving	move	VERB
cana-729	132	74	average	average	ADJ
cana-729	132	75	model	model	NOUN
cana-729	132	76	depends	depend	VERB
cana-729	132	77	when	when	SCONJ
cana-729	132	78	applied	apply	VERB
cana-729	132	79	to	to	ADP
cana-729	132	80	lagged	lag	VERB
cana-729	132	81	observations	observation	NOUN
cana-729	132	82	.	.	PUNCT
cana-729	133	1	3.3.3	3.3.3	NUM
cana-729	133	2	lstm	lstm	NOUN
cana-729	133	3	model	model	NOUN
cana-729	133	4	lstm	lstm	NOUN
cana-729	133	5	networks	network	NOUN
cana-729	133	6	are	be	AUX
cana-729	133	7	a	a	DET
cana-729	133	8	form	form	NOUN
cana-729	133	9	of	of	ADP
cana-729	133	10	recurrent	recurrent	ADJ
cana-729	133	11	neural	neural	ADJ
cana-729	133	12	network	network	NOUN
cana-729	133	13	that	that	PRON
cana-729	133	14	learns	learn	VERB
cana-729	133	15	order	order	NOUN
cana-729	133	16	dependency	dependency	NOUN
cana-729	133	17	in	in	ADP
cana-729	133	18	sequence	sequence	NOUN
cana-729	133	19	prediction	prediction	NOUN
cana-729	133	20	challenges	challenge	NOUN
cana-729	133	21	.	.	PUNCT
cana-729	134	1	because	because	SCONJ
cana-729	134	2	there	there	PRON
cana-729	134	3	might	might	AUX
cana-729	134	4	be	be	AUX
cana-729	134	5	gaps	gap	NOUN
cana-729	134	6	of	of	ADP
cana-729	134	7	undetermined	undetermined	ADJ
cana-729	134	8	duration	duration	NOUN
cana-729	134	9	between	between	ADP
cana-729	134	10	critical	critical	ADJ
cana-729	134	11	events	event	NOUN
cana-729	134	12	in	in	ADP
cana-729	134	13	a	a	DET
cana-729	134	14	time	time	NOUN
cana-729	134	15	series	series	NOUN
cana-729	134	16	,	,	PUNCT
cana-729	134	17	lstm	lstm	ADJ
cana-729	134	18	networks	network	NOUN
cana-729	134	19	are	be	AUX
cana-729	134	20	optimal	optimal	ADJ
cana-729	134	21	for	for	ADP
cana-729	134	22	classification	classification	NOUN
cana-729	134	23	and	and	CCONJ
cana-729	134	24	prediction	prediction	NOUN
cana-729	134	25	.	.	PUNCT
cana-729	135	1	in	in	ADP
cana-729	135	2	simple	simple	ADJ
cana-729	135	3	language	language	NOUN
cana-729	135	4	,	,	PUNCT
cana-729	135	5	for	for	ADP
cana-729	135	6	example	example	NOUN
cana-729	135	7	,	,	PUNCT
cana-729	135	8	we	we	PRON
cana-729	135	9	have	have	VERB
cana-729	135	10	a	a	DET
cana-729	135	11	dataset	dataset	NOUN
cana-729	135	12	that	that	PRON
cana-729	135	13	consists	consist	VERB
cana-729	135	14	of	of	ADP
cana-729	135	15	the	the	DET
cana-729	135	16	temperature	temperature	NOUN
cana-729	135	17	for	for	ADP
cana-729	135	18	five	five	NUM
cana-729	135	19	months	month	NOUN
cana-729	135	20	say	say	VERB
cana-729	135	21	from	from	ADP
cana-729	135	22	january	january	PROPN
cana-729	135	23	to	to	ADP
cana-729	135	24	may	may	AUX
cana-729	135	25	and	and	CCONJ
cana-729	135	26	we	we	PRON
cana-729	135	27	want	want	VERB
cana-729	135	28	a	a	DET
cana-729	135	29	prediction	prediction	NOUN
cana-729	135	30	to	to	PART
cana-729	135	31	be	be	AUX
cana-729	135	32	done	do	VERB
cana-729	135	33	for	for	ADP
cana-729	135	34	the	the	DET
cana-729	135	35	next	next	ADJ
cana-729	135	36	3	3	NUM
cana-729	135	37	months	month	NOUN
cana-729	135	38	say	say	VERB
cana-729	135	39	june	june	PROPN
cana-729	135	40	,	,	PUNCT
cana-729	135	41	july	july	PROPN
cana-729	135	42	and	and	CCONJ
cana-729	135	43	august	august	PROPN
cana-729	135	44	.	.	PUNCT
cana-729	136	1	so	so	ADV
cana-729	136	2	,	,	PUNCT
cana-729	136	3	this	this	DET
cana-729	136	4	algorithm	algorithm	NOUN
cana-729	136	5	will	will	AUX
cana-729	136	6	first	first	ADV
cana-729	136	7	use	use	VERB
cana-729	136	8	the	the	DET
cana-729	136	9	inputs	input	NOUN
cana-729	136	10	i.e	i.e	X
cana-729	136	11	,	,	PUNCT
cana-729	136	12	the	the	DET
cana-729	136	13	temperature	temperature	NOUN
cana-729	136	14	of	of	ADP
cana-729	136	15	january	january	PROPN
cana-729	136	16	,	,	PUNCT
cana-729	136	17	february	february	PROPN
cana-729	136	18	,	,	PUNCT
cana-729	136	19	march	march	PROPN
cana-729	136	20	,	,	PUNCT
cana-729	136	21	april	april	PROPN
cana-729	136	22	and	and	CCONJ
cana-729	136	23	may	may	AUX
cana-729	136	24	and	and	CCONJ
cana-729	136	25	use	use	VERB
cana-729	136	26	it	it	PRON
cana-729	136	27	to	to	PART
cana-729	136	28	predict	predict	VERB
cana-729	136	29	the	the	DET
cana-729	136	30	temperature	temperature	NOUN
cana-729	136	31	of	of	ADP
cana-729	136	32	june	june	PROPN
cana-729	136	33	.	.	PUNCT
cana-729	137	1	then	then	ADV
cana-729	137	2	in	in	ADP
cana-729	137	3	the	the	DET
cana-729	137	4	next	next	ADJ
cana-729	137	5	case	case	NOUN
cana-729	137	6	,	,	PUNCT
cana-729	137	7	it	it	PRON
cana-729	137	8	will	will	AUX
cana-729	137	9	drop	drop	VERB
cana-729	137	10	the	the	DET
cana-729	137	11	temperature	temperature	NOUN
cana-729	137	12	of	of	ADP
cana-729	137	13	january	january	PROPN
cana-729	137	14	and	and	CCONJ
cana-729	137	15	take	take	VERB
cana-729	137	16	the	the	DET
cana-729	137	17	temperature	temperature	NOUN
cana-729	137	18	from	from	ADP
cana-729	137	19	february	february	PROPN
cana-729	137	20	,	,	PUNCT
cana-729	137	21	march	march	PROPN
cana-729	137	22	,	,	PUNCT
cana-729	137	23	april	april	PROPN
cana-729	137	24	,	,	PUNCT
cana-729	137	25	may	may	AUX
cana-729	137	26	and	and	CCONJ
cana-729	137	27	june	june	PROPN
cana-729	137	28	to	to	PART
cana-729	137	29	predict	predict	VERB
cana-729	137	30	the	the	DET
cana-729	137	31	temperature	temperature	NOUN
cana-729	137	32	of	of	ADP
cana-729	137	33	july	july	PROPN
cana-729	137	34	.	.	PUNCT
cana-729	138	1	again	again	ADV
cana-729	138	2	,	,	PUNCT
cana-729	138	3	in	in	ADP
cana-729	138	4	the	the	DET
cana-729	138	5	second	second	ADJ
cana-729	138	6	case	case	NOUN
cana-729	138	7	,	,	PUNCT
cana-729	138	8	it	it	PRON
cana-729	138	9	will	will	AUX
cana-729	138	10	drop	drop	VERB
cana-729	138	11	the	the	DET
cana-729	138	12	temperature	temperature	NOUN
cana-729	138	13	of	of	ADP
cana-729	138	14	february	february	PROPN
cana-729	138	15	and	and	CCONJ
cana-729	138	16	take	take	VERB
cana-729	138	17	the	the	DET
cana-729	138	18	temperature	temperature	NOUN
cana-729	138	19	from	from	ADP
cana-729	138	20	march	march	PROPN
cana-729	138	21	,	,	PUNCT
cana-729	138	22	april	april	PROPN
cana-729	138	23	,	,	PUNCT
cana-729	138	24	may	may	AUX
cana-729	138	25	,	,	PUNCT
cana-729	138	26	june	june	PROPN
cana-729	138	27	and	and	CCONJ
cana-729	138	28	july	july	PROPN
cana-729	138	29	to	to	PART
cana-729	138	30	predict	predict	VERB
cana-729	138	31	the	the	DET
cana-729	138	32	temperature	temperature	NOUN
cana-729	138	33	of	of	ADP
cana-729	138	34	august	august	PROPN
cana-729	138	35	.	.	PUNCT
cana-729	139	1	3.4	3.4	NUM
cana-729	139	2	classification	classification	NOUN
cana-729	139	3	model	model	NOUN
cana-729	139	4	for	for	ADP
cana-729	139	5	classifying	classify	VERB
cana-729	139	6	the	the	DET
cana-729	139	7	severity	severity	NOUN
cana-729	139	8	of	of	ADP
cana-729	139	9	drought	drought	NOUN
cana-729	139	10	according	accord	VERB
cana-729	139	11	to	to	ADP
cana-729	139	12	the	the	DET
cana-729	139	13	precipitation	precipitation	NOUN
cana-729	139	14	forecasted	forecast	VERB
cana-729	139	15	,	,	PUNCT
cana-729	139	16	two	two	NUM
cana-729	139	17	forecasting	forecasting	NOUN
cana-729	139	18	models	model	NOUN
cana-729	139	19	have	have	AUX
cana-729	139	20	been	be	AUX
cana-729	139	21	used	use	VERB
cana-729	139	22	i.e.	i.e.	ADV
cana-729	139	23	,	,	PUNCT
cana-729	139	24	support	support	VERB
cana-729	139	25	vector	vector	NOUN
cana-729	139	26	classifier	classifier	NOUN
cana-729	139	27	and	and	CCONJ
cana-729	139	28	naive	naive	ADJ
cana-729	139	29	bayes	baye	NOUN
cana-729	139	30	.	.	PUNCT
cana-729	140	1	similarly	similarly	ADV
cana-729	140	2	for	for	ADP
cana-729	140	3	these	these	DET
cana-729	140	4	models	model	NOUN
cana-729	140	5	also	also	ADV
cana-729	140	6	dataset	dataset	VERB
cana-729	140	7	was	be	AUX
cana-729	140	8	split	split	VERB
cana-729	140	9	into	into	ADP
cana-729	140	10	a	a	DET
cana-729	140	11	train	train	NOUN
cana-729	140	12	set	set	NOUN
cana-729	140	13	and	and	CCONJ
cana-729	140	14	a	a	DET
cana-729	140	15	test	test	NOUN
cana-729	140	16	set	set	VERB
cana-729	140	17	in	in	ADP
cana-729	140	18	the	the	DET
cana-729	140	19	ratio	ratio	NOUN
cana-729	140	20	90:10	90:10	NUM
cana-729	140	21	.	.	PUNCT
cana-729	141	1	3.4.1	3.4.1	NUM
cana-729	141	2	naive	naive	ADJ
cana-729	141	3	bayes	bayes	NOUN
cana-729	141	4	classifier	classifier	AUX
cana-729	141	5	a	a	DET
cana-729	141	6	bayesian	bayesian	NOUN
cana-729	141	7	classifier	classifier	NOUN
cana-729	141	8	is	be	AUX
cana-729	141	9	a	a	DET
cana-729	141	10	probabilistic	probabilistic	ADJ
cana-729	141	11	classification	classification	NOUN
cana-729	141	12	model	model	NOUN
cana-729	141	13	.	.	PUNCT
cana-729	142	1	naive	naive	ADJ
cana-729	142	2	bayes	bayes	PROPN
cana-729	142	3	uses	use	VERB
cana-729	142	4	machine	machine	NOUN
cana-729	142	5	learning	learn	VERB
cana-729	142	6	to	to	PART
cana-729	142	7	distinguish	distinguish	VERB
cana-729	142	8	between	between	ADP
cana-729	142	9	various	various	ADJ
cana-729	142	10	objects	object	NOUN
cana-729	142	11	based	base	VERB
cana-729	142	12	on	on	ADP
cana-729	142	13	particular	particular	ADJ
cana-729	142	14	attributes	attribute	NOUN
cana-729	142	15	.	.	PUNCT
cana-729	143	1	the	the	DET
cana-729	143	2	bayes	bayes	PROPN
cana-729	143	3	theorem	theorem	VERB
cana-729	143	4	is	be	AUX
cana-729	143	5	used	use	VERB
cana-729	143	6	in	in	ADP
cana-729	143	7	this	this	DET
cana-729	143	8	communications	communication	NOUN
cana-729	143	9	on	on	ADP
cana-729	143	10	applied	apply	VERB
cana-729	143	11	nonlinear	nonlinear	ADJ
cana-729	143	12	analysis	analysis	NOUN
cana-729	143	13	issn	issn	NOUN
cana-729	143	14	:	:	PUNCT
cana-729	143	15	1074	1074	NUM
cana-729	143	16	-	-	PUNCT
cana-729	143	17	133x	133x	NUM
cana-729	143	18	vol	vol	NOUN
cana-729	143	19	31	31	NUM
cana-729	143	20	no	no	NOUN
cana-729	143	21	.	.	PUNCT
cana-729	144	1	3s	3s	NUM
cana-729	144	2	(	(	PUNCT
cana-729	144	3	2024	2024	NUM
cana-729	144	4	)	)	PUNCT
cana-729	144	5	35	35	NUM
cana-729	144	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-729	144	7	model	model	NOUN
cana-729	144	8	.	.	PUNCT
cana-729	145	1	the	the	DET
cana-729	145	2	bayes	bayes	PROPN
cana-729	145	3	theorem	theorem	NOUN
cana-729	145	4	may	may	AUX
cana-729	145	5	be	be	AUX
cana-729	145	6	used	use	VERB
cana-729	145	7	to	to	PART
cana-729	145	8	calculate	calculate	VERB
cana-729	145	9	the	the	DET
cana-729	145	10	likelihood	likelihood	NOUN
cana-729	145	11	of	of	ADP
cana-729	145	12	a	a	DET
cana-729	145	13	occurring	occur	VERB
cana-729	145	14	given	give	VERB
cana-729	145	15	b	b	NOUN
cana-729	145	16	,	,	PUNCT
cana-729	145	17	where	where	SCONJ
cana-729	145	18	b	b	NOUN
cana-729	145	19	is	be	AUX
cana-729	145	20	the	the	DET
cana-729	145	21	evidence	evidence	NOUN
cana-729	145	22	and	and	CCONJ
cana-729	145	23	a	a	PRON
cana-729	145	24	is	be	AUX
cana-729	145	25	the	the	DET
cana-729	145	26	hypothesis	hypothesis	NOUN
cana-729	145	27	.	.	PUNCT
cana-729	146	1	the	the	DET
cana-729	146	2	underlying	underlying	ADJ
cana-729	146	3	assumption	assumption	NOUN
cana-729	146	4	is	be	AUX
cana-729	146	5	that	that	SCONJ
cana-729	146	6	all	all	DET
cana-729	146	7	characteristics	characteristic	NOUN
cana-729	146	8	are	be	AUX
cana-729	146	9	independent	independent	ADJ
cana-729	146	10	of	of	ADP
cana-729	146	11	one	one	NUM
cana-729	146	12	another	another	DET
cana-729	146	13	.	.	PUNCT
cana-729	147	1	these	these	DET
cana-729	147	2	algorithms	algorithm	NOUN
cana-729	147	3	are	be	AUX
cana-729	147	4	commonly	commonly	ADV
cana-729	147	5	used	use	VERB
cana-729	147	6	in	in	ADP
cana-729	147	7	sentiment	sentiment	NOUN
cana-729	147	8	analysis	analysis	NOUN
cana-729	147	9	,	,	PUNCT
cana-729	147	10	spam	spam	NOUN
cana-729	147	11	filtering	filtering	NOUN
cana-729	147	12	,	,	PUNCT
cana-729	147	13	recommendation	recommendation	NOUN
cana-729	147	14	systems	system	NOUN
cana-729	147	15	,	,	PUNCT
cana-729	147	16	and	and	CCONJ
cana-729	147	17	other	other	ADJ
cana-729	147	18	applications	application	NOUN
cana-729	147	19	since	since	SCONJ
cana-729	147	20	they	they	PRON
cana-729	147	21	are	be	AUX
cana-729	147	22	quick	quick	ADJ
cana-729	147	23	and	and	CCONJ
cana-729	147	24	simple	simple	ADJ
cana-729	147	25	to	to	PART
cana-729	147	26	construct	construct	VERB
cana-729	147	27	.	.	PUNCT
cana-729	148	1	3.4.2	3.4.2	NUM
cana-729	148	2	support	support	NOUN
cana-729	148	3	vector	vector	NOUN
cana-729	148	4	classifier	classifier	NOUN
cana-729	148	5	svm	svm	PROPN
cana-729	148	6	is	be	AUX
cana-729	148	7	a	a	DET
cana-729	148	8	supervised	supervised	ADJ
cana-729	148	9	machine	machine	NOUN
cana-729	148	10	learning	learning	NOUN
cana-729	148	11	technique	technique	NOUN
cana-729	148	12	that	that	PRON
cana-729	148	13	may	may	AUX
cana-729	148	14	be	be	AUX
cana-729	148	15	used	use	VERB
cana-729	148	16	to	to	PART
cana-729	148	17	solve	solve	VERB
cana-729	148	18	both	both	DET
cana-729	148	19	regression	regression	NOUN
cana-729	148	20	issues	issue	NOUN
cana-729	148	21	and	and	CCONJ
cana-729	148	22	classification	classification	NOUN
cana-729	148	23	problems	problem	NOUN
cana-729	148	24	.	.	PUNCT
cana-729	149	1	each	each	DET
cana-729	149	2	data	datum	NOUN
cana-729	149	3	point	point	NOUN
cana-729	149	4	in	in	ADP
cana-729	149	5	this	this	DET
cana-729	149	6	algorithm	algorithm	NOUN
cana-729	149	7	is	be	AUX
cana-729	149	8	plotted	plot	VERB
cana-729	149	9	in	in	ADP
cana-729	149	10	an	an	DET
cana-729	149	11	n	n	ADV
cana-729	149	12	-	-	PUNCT
cana-729	149	13	dimensional	dimensional	ADJ
cana-729	149	14	space	space	NOUN
cana-729	149	15	,	,	PUNCT
cana-729	149	16	with	with	ADP
cana-729	149	17	the	the	DET
cana-729	149	18	value	value	NOUN
cana-729	149	19	of	of	ADP
cana-729	149	20	each	each	DET
cana-729	149	21	characteristic	characteristic	NOUN
cana-729	149	22	assigned	assign	VERB
cana-729	149	23	to	to	ADP
cana-729	149	24	a	a	DET
cana-729	149	25	specific	specific	ADJ
cana-729	149	26	coordinate	coordinate	NOUN
cana-729	149	27	.	.	PUNCT
cana-729	150	1	then	then	ADV
cana-729	150	2	classification	classification	NOUN
cana-729	150	3	is	be	AUX
cana-729	150	4	carried	carry	VERB
cana-729	150	5	out	out	ADP
cana-729	150	6	by	by	ADP
cana-729	150	7	locating	locate	VERB
cana-729	150	8	the	the	DET
cana-729	150	9	hyper	hyper	NOUN
cana-729	150	10	-	-	NOUN
cana-729	150	11	plane	plane	NOUN
cana-729	150	12	that	that	PRON
cana-729	150	13	best	well	ADV
cana-729	150	14	distinguishes	distinguish	VERB
cana-729	150	15	the	the	DET
cana-729	150	16	classes	class	NOUN
cana-729	150	17	.	.	PUNCT
cana-729	151	1	3.5	3.5	NUM
cana-729	151	2	accuracy	accuracy	NOUN
cana-729	151	3	measure	measure	NOUN
cana-729	151	4	root	root	NOUN
cana-729	151	5	mean	mean	VERB
cana-729	151	6	square	square	ADJ
cana-729	151	7	error	error	NOUN
cana-729	151	8	is	be	AUX
cana-729	151	9	the	the	DET
cana-729	151	10	standard	standard	ADJ
cana-729	151	11	deviation	deviation	NOUN
cana-729	151	12	of	of	ADP
cana-729	151	13	the	the	DET
cana-729	151	14	residuals	residual	NOUN
cana-729	151	15	.	.	PUNCT
cana-729	152	1	residuals	residual	NOUN
cana-729	152	2	are	be	AUX
cana-729	152	3	the	the	DET
cana-729	152	4	distance	distance	NOUN
cana-729	152	5	between	between	ADP
cana-729	152	6	the	the	DET
cana-729	152	7	regression	regression	NOUN
cana-729	152	8	line	line	NOUN
cana-729	152	9	and	and	CCONJ
cana-729	152	10	the	the	DET
cana-729	152	11	data	data	NOUN
cana-729	152	12	points	point	NOUN
cana-729	152	13	.	.	PUNCT
cana-729	153	1	it	it	PRON
cana-729	153	2	is	be	AUX
cana-729	153	3	a	a	DET
cana-729	153	4	measure	measure	NOUN
cana-729	153	5	of	of	ADP
cana-729	153	6	the	the	DET
cana-729	153	7	uniform	uniform	ADJ
cana-729	153	8	distribution	distribution	NOUN
cana-729	153	9	of	of	ADP
cana-729	153	10	residuals	residual	NOUN
cana-729	153	11	.	.	PUNCT
cana-729	154	1	it	it	PRON
cana-729	154	2	shows	show	VERB
cana-729	154	3	how	how	SCONJ
cana-729	154	4	closely	closely	ADV
cana-729	154	5	the	the	DET
cana-729	154	6	data	data	NOUN
cana-729	154	7	points	point	NOUN
cana-729	154	8	are	be	AUX
cana-729	154	9	grouped	group	VERB
cana-729	154	10	around	around	ADP
cana-729	154	11	the	the	DET
cana-729	154	12	best	good	ADJ
cana-729	154	13	-	-	PUNCT
cana-729	154	14	fit	fit	ADJ
cana-729	154	15	line	line	NOUN
cana-729	154	16	.	.	PUNCT
cana-729	155	1	the	the	DET
cana-729	155	2	percentage	percentage	NOUN
cana-729	155	3	mean	mean	VERB
cana-729	155	4	absolute	absolute	ADJ
cana-729	155	5	error	error	NOUN
cana-729	155	6	(	(	PUNCT
cana-729	155	7	mape	mape	NOUN
cana-729	155	8	)	)	PUNCT
cana-729	155	9	measures	measure	VERB
cana-729	155	10	the	the	DET
cana-729	155	11	prediction	prediction	NOUN
cana-729	155	12	accuracy	accuracy	NOUN
cana-729	155	13	of	of	ADP
cana-729	155	14	the	the	DET
cana-729	155	15	system	system	NOUN
cana-729	155	16	.	.	PUNCT
cana-729	156	1	it	it	PRON
cana-729	156	2	is	be	AUX
cana-729	156	3	determined	determine	VERB
cana-729	156	4	as	as	ADP
cana-729	156	5	the	the	DET
cana-729	156	6	difference	difference	NOUN
cana-729	156	7	between	between	ADP
cana-729	156	8	the	the	DET
cana-729	156	9	mean	mean	ADJ
cana-729	156	10	absolute	absolute	ADJ
cana-729	156	11	percent	percent	NOUN
cana-729	156	12	error	error	NOUN
cana-729	156	13	for	for	ADP
cana-729	156	14	each	each	DET
cana-729	156	15	time	time	NOUN
cana-729	156	16	period	period	NOUN
cana-729	156	17	and	and	CCONJ
cana-729	156	18	the	the	DET
cana-729	156	19	actual	actual	ADJ
cana-729	156	20	value	value	NOUN
cana-729	156	21	divided	divide	VERB
cana-729	156	22	by	by	ADP
cana-729	156	23	the	the	DET
cana-729	156	24	actual	actual	ADJ
cana-729	156	25	value	value	NOUN
cana-729	156	26	and	and	CCONJ
cana-729	156	27	expressed	express	VERB
cana-729	156	28	as	as	ADP
cana-729	156	29	a	a	DET
cana-729	156	30	percentage	percentage	NOUN
cana-729	156	31	.	.	PUNCT
cana-729	157	1	4	4	X
cana-729	157	2	.	.	X
cana-729	157	3	analysis	analysis	VERB
cana-729	157	4	the	the	DET
cana-729	157	5	analysis	analysis	NOUN
cana-729	157	6	of	of	ADP
cana-729	157	7	the	the	DET
cana-729	157	8	rainfall	rainfall	NOUN
cana-729	157	9	in	in	ADP
cana-729	157	10	odisha	odisha	PROPN
cana-729	157	11	using	use	VERB
cana-729	157	12	visualization	visualization	NOUN
cana-729	157	13	in	in	ADP
cana-729	157	14	matlab	matlab	PROPN
cana-729	157	15	.	.	PUNCT
cana-729	158	1	the	the	DET
cana-729	158	2	following	follow	VERB
cana-729	158	3	are	be	AUX
cana-729	158	4	the	the	DET
cana-729	158	5	visualiztions	visualiztion	NOUN
cana-729	158	6	of	of	ADP
cana-729	158	7	the	the	DET
cana-729	158	8	data	data	NOUN
cana-729	158	9	communications	communication	NOUN
cana-729	158	10	on	on	ADP
cana-729	158	11	applied	apply	VERB
cana-729	158	12	nonlinear	nonlinear	ADJ
cana-729	158	13	analysis	analysis	NOUN
cana-729	158	14	issn	issn	NOUN
cana-729	158	15	:	:	PUNCT
cana-729	158	16	1074	1074	NUM
cana-729	158	17	-	-	PUNCT
cana-729	158	18	133x	133x	NUM
cana-729	158	19	vol	vol	NOUN
cana-729	158	20	31	31	NUM
cana-729	158	21	no	no	NOUN
cana-729	158	22	.	.	PUNCT
cana-729	159	1	3s	3s	NUM
cana-729	159	2	(	(	PUNCT
cana-729	159	3	2024	2024	NUM
cana-729	159	4	)	)	PUNCT
cana-729	159	5	36	36	NUM
cana-729	159	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-729	159	7	fig	fig	NOUN
cana-729	159	8	1	1	NUM
cana-729	159	9	districtwise	districtwise	NOUN
cana-729	159	10	visualiztion	visualiztion	NOUN
cana-729	159	11	of	of	ADP
cana-729	159	12	total	total	ADJ
cana-729	159	13	rainfall	rainfall	NOUN
cana-729	159	14	from	from	ADP
cana-729	159	15	2004	2004	NUM
cana-729	159	16	-	-	SYM
cana-729	159	17	2023	2023	NUM
cana-729	159	18	from	from	ADP
cana-729	159	19	fig	fig	NOUN
cana-729	159	20	1	1	NUM
cana-729	159	21	district	district	NOUN
cana-729	159	22	wise	wise	ADJ
cana-729	159	23	analysis	analysis	NOUN
cana-729	159	24	rain	rain	NOUN
cana-729	159	25	fall	fall	NOUN
cana-729	159	26	and	and	CCONJ
cana-729	159	27	drought	drought	NOUN
cana-729	159	28	can	can	AUX
cana-729	159	29	be	be	AUX
cana-729	159	30	done	do	VERB
cana-729	159	31	.	.	PUNCT
cana-729	160	1	fig	fig	NOUN
cana-729	160	2	2total	2total	NUM
cana-729	160	3	rainfall	rainfall	NOUN
cana-729	160	4	from	from	ADP
cana-729	160	5	the	the	DET
cana-729	160	6	year	year	NOUN
cana-729	160	7	2004	2004	NUM
cana-729	160	8	-	-	SYM
cana-729	160	9	2023	2023	NUM
cana-729	160	10	from	from	ADP
cana-729	160	11	the	the	DET
cana-729	160	12	fig	fig	NOUN
cana-729	160	13	2	2	NUM
cana-729	160	14	the	the	DET
cana-729	160	15	years	year	NOUN
cana-729	160	16	2005	2005	NUM
cana-729	160	17	,	,	PUNCT
cana-729	160	18	2006,2007,2008,20113,2014,2018,2019	2006,2007,2008,20113,2014,2018,2019	NUM
cana-729	160	19	2020	2020	NUM
cana-729	160	20	had	have	VERB
cana-729	160	21	rainfall	rainfall	NOUN
cana-729	160	22	more	more	ADJ
cana-729	160	23	than	than	ADP
cana-729	160	24	45,000	45,000	NUM
cana-729	160	25	mm	mm	NOUN
cana-729	160	26	.	.	PUNCT
cana-729	161	1	it	it	PRON
cana-729	161	2	can	can	AUX
cana-729	161	3	be	be	AUX
cana-729	161	4	considered	consider	VERB
cana-729	161	5	as	as	ADP
cana-729	161	6	flood	flood	NOUN
cana-729	161	7	scenorio	scenorio	NOUN
cana-729	161	8	.	.	PUNCT
cana-729	162	1	the	the	DET
cana-729	162	2	years	year	NOUN
cana-729	162	3	2004,2010,2015,2016	2004,2010,2015,2016	PROPN
cana-729	162	4	had	have	VERB
cana-729	162	5	rainfall	rainfall	NOUN
cana-729	162	6	below	below	ADP
cana-729	162	7	40,000	40,000	NUM
cana-729	162	8	mm	mm	NOUN
cana-729	162	9	.	.	PUNCT
cana-729	163	1	it	it	PRON
cana-729	163	2	can	can	AUX
cana-729	163	3	be	be	AUX
cana-729	163	4	considered	consider	VERB
cana-729	163	5	as	as	ADP
cana-729	163	6	drought	drought	NOUN
cana-729	163	7	scenorio	scenorio	NOUN
cana-729	163	8	.	.	PUNCT
cana-729	164	1	fig	fig	NOUN
cana-729	164	2	3	3	NUM
cana-729	164	3	average	average	ADJ
cana-729	164	4	rainfall	rainfall	NOUN
cana-729	164	5	communications	communication	NOUN
cana-729	164	6	on	on	ADP
cana-729	164	7	applied	apply	VERB
cana-729	164	8	nonlinear	nonlinear	ADJ
cana-729	164	9	analysis	analysis	NOUN
cana-729	164	10	issn	issn	NOUN
cana-729	164	11	:	:	PUNCT
cana-729	164	12	1074	1074	NUM
cana-729	164	13	-	-	PUNCT
cana-729	164	14	133x	133x	NUM
cana-729	164	15	vol	vol	NOUN
cana-729	164	16	31	31	NUM
cana-729	164	17	no	no	NOUN
cana-729	164	18	.	.	PUNCT
cana-729	165	1	3s	3s	NUM
cana-729	165	2	(	(	PUNCT
cana-729	165	3	2024	2024	NUM
cana-729	165	4	)	)	PUNCT
cana-729	165	5	37	37	NUM
cana-729	165	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-729	165	7	from	from	ADP
cana-729	165	8	the	the	DET
cana-729	165	9	fig	fig	NOUN
cana-729	165	10	3	3	NUM
cana-729	165	11	the	the	DET
cana-729	165	12	average	average	ADJ
cana-729	165	13	rainfall	rainfall	NOUN
cana-729	165	14	was	be	AUX
cana-729	165	15	lesser	less	ADJ
cana-729	165	16	than	than	SCONJ
cana-729	165	17	1400	1400	NUM
cana-729	165	18	mm	mm	NOUN
cana-729	165	19	were	be	AUX
cana-729	165	20	2004,2010,2015,2016,2017,2023	2004,2010,2015,2016,2017,2023	NUM
cana-729	165	21	.	.	PUNCT
cana-729	166	1	the	the	DET
cana-729	166	2	average	average	ADJ
cana-729	166	3	rainfall	rainfall	NOUN
cana-729	166	4	were	be	AUX
cana-729	166	5	higher	high	ADJ
cana-729	166	6	than	than	ADP
cana-729	166	7	1600	1600	NUM
cana-729	166	8	mm	mm	NOUN
cana-729	166	9	in	in	ADP
cana-729	166	10	the	the	DET
cana-729	166	11	years	year	NOUN
cana-729	166	12	2006,2007,2013,2014,2018,2019,2020	2006,2007,2013,2014,2018,2019,2020	NUM
cana-729	166	13	.	.	PUNCT
cana-729	167	1	this	this	DET
cana-729	167	2	inferes	infere	NOUN
cana-729	167	3	that	that	SCONJ
cana-729	167	4	more	more	ADJ
cana-729	167	5	reains	reain	NOUN
cana-729	167	6	occurs	occur	VERB
cana-729	167	7	in	in	ADP
cana-729	167	8	consecutive	consecutive	ADJ
cana-729	167	9	years	year	NOUN
cana-729	167	10	.	.	PUNCT
cana-729	168	1	fig	fig	NOUN
cana-729	168	2	4	4	NUM
cana-729	168	3	plot	plot	NOUN
cana-729	168	4	of	of	ADP
cana-729	168	5	total	total	ADJ
cana-729	168	6	rain	rain	NOUN
cana-729	168	7	fall	fall	VERB
cana-729	168	8	from	from	ADP
cana-729	168	9	2004	2004	NUM
cana-729	168	10	-	-	SYM
cana-729	168	11	2023	2023	NUM
cana-729	168	12	fig	fig	NOUN
cana-729	168	13	5	5	NUM
cana-729	168	14	plot	plot	NOUN
cana-729	168	15	of	of	ADP
cana-729	168	16	linear	linear	ADJ
cana-729	168	17	trend	trend	NOUN
cana-729	168	18	of	of	ADP
cana-729	168	19	total	total	ADJ
cana-729	168	20	rain	rain	NOUN
cana-729	168	21	fall	fall	VERB
cana-729	168	22	from	from	ADP
cana-729	168	23	2004	2004	NUM
cana-729	168	24	-	-	SYM
cana-729	168	25	2023	2023	NUM
cana-729	168	26	fig	fig	NOUN
cana-729	168	27	6	6	NUM
cana-729	168	28	plot	plot	NOUN
cana-729	168	29	of	of	ADP
cana-729	168	30	average	average	ADJ
cana-729	168	31	rain	rain	NOUN
cana-729	168	32	fall	fall	VERB
cana-729	168	33	from	from	ADP
cana-729	168	34	2004	2004	NUM
cana-729	168	35	-	-	SYM
cana-729	168	36	2023	2023	NUM
cana-729	168	37	y	y	NOUN
cana-729	168	38	=	=	PUNCT
cana-729	168	39	-527.16x	-527.16x	PROPN
cana-729	169	1	+	+	NUM
cana-729	169	2	1e+06	1e+06	X
cana-729	169	3	r²	r²	NOUN
cana-729	169	4	=	=	SYM
cana-729	169	5	0.1441	0.1441	NUM
cana-729	169	6	-5000	-5000	NOUN
cana-729	169	7	0	0	NUM
cana-729	169	8	5000	5000	NUM
cana-729	169	9	10000	10000	NUM
cana-729	169	10	15000	15000	NUM
cana-729	169	11	20000	20000	NUM
cana-729	169	12	25000	25000	NUM
cana-729	169	13	30000	30000	NUM
cana-729	169	14	35000	35000	NUM
cana-729	169	15	40000	40000	NUM
cana-729	169	16	45000	45000	NUM
cana-729	169	17	2000	2000	NUM
cana-729	169	18	2005	2005	NUM
cana-729	169	19	2010	2010	NUM
cana-729	169	20	2015	2015	NUM
cana-729	169	21	2020	2020	NUM
cana-729	169	22	2025	2025	NUM
cana-729	169	23	a	a	DET
cana-729	169	24	xi	xi	ADP
cana-729	169	25	s	s	PROPN
cana-729	169	26	ti	ti	X
cana-729	169	27	tl	tl	PROPN
cana-729	169	28	e	e	PROPN
cana-729	169	29	axis	axis	NOUN
cana-729	169	30	title	title	NOUN
cana-729	169	31	communications	communication	NOUN
cana-729	169	32	on	on	ADP
cana-729	169	33	applied	apply	VERB
cana-729	169	34	nonlinear	nonlinear	ADJ
cana-729	169	35	analysis	analysis	NOUN
cana-729	169	36	issn	issn	NOUN
cana-729	169	37	:	:	PUNCT
cana-729	169	38	1074	1074	NUM
cana-729	169	39	-	-	PUNCT
cana-729	169	40	133x	133x	NUM
cana-729	169	41	vol	vol	NOUN
cana-729	169	42	31	31	NUM
cana-729	169	43	no	no	NOUN
cana-729	169	44	.	.	PUNCT
cana-729	170	1	3s	3s	NUM
cana-729	170	2	(	(	PUNCT
cana-729	170	3	2024	2024	NUM
cana-729	170	4	)	)	PUNCT
cana-729	170	5	38	38	NUM
cana-729	170	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-729	170	7	from	from	ADP
cana-729	170	8	the	the	DET
cana-729	170	9	fig	fig	NOUN
cana-729	170	10	4	4	NUM
cana-729	170	11	,	,	PUNCT
cana-729	170	12	fig	fig	NOUN
cana-729	170	13	5	5	NUM
cana-729	170	14	,	,	PUNCT
cana-729	170	15	fig	fig	NOUN
cana-729	170	16	6	6	NUM
cana-729	170	17	it	it	PRON
cana-729	170	18	is	be	AUX
cana-729	170	19	noticed	notice	VERB
cana-729	170	20	that	that	SCONJ
cana-729	170	21	there	there	PRON
cana-729	170	22	exists	exist	VERB
cana-729	170	23	a	a	DET
cana-729	170	24	pattern	pattern	NOUN
cana-729	170	25	in	in	ADP
cana-729	170	26	the	the	DET
cana-729	170	27	rain	rain	NOUN
cana-729	170	28	fall	fall	NOUN
cana-729	170	29	of	of	ADP
cana-729	170	30	odisha	odisha	PROPN
cana-729	170	31	.	.	PUNCT
cana-729	171	1	fig	fig	PROPN
cana-729	171	2	7	7	NUM
cana-729	171	3	trend	trend	NOUN
cana-729	171	4	line	line	NOUN
cana-729	171	5	for	for	ADP
cana-729	171	6	the	the	DET
cana-729	171	7	district	district	NOUN
cana-729	171	8	malkangiri	malkangiri	NOUN
cana-729	171	9	in	in	ADP
cana-729	171	10	fig	fig	NOUN
cana-729	171	11	7	7	NUM
cana-729	171	12	,	,	PUNCT
cana-729	171	13	the	the	DET
cana-729	171	14	average	average	ADJ
cana-729	171	15	rainfall	rainfall	NOUN
cana-729	171	16	of	of	ADP
cana-729	171	17	malkangiri	malkangiri	NOUN
cana-729	171	18	distict	distict	NOUN
cana-729	171	19	which	which	PRON
cana-729	171	20	is	be	AUX
cana-729	171	21	on	on	ADP
cana-729	171	22	the	the	DET
cana-729	171	23	bank	bank	PROPN
cana-729	171	24	river	river	PROPN
cana-729	171	25	mahanadhi	mahanadhi	PROPN
cana-729	171	26	gives	give	VERB
cana-729	171	27	the	the	DET
cana-729	171	28	trend	trend	NOUN
cana-729	171	29	as	as	ADV
cana-729	171	30	same	same	ADJ
cana-729	171	31	as	as	ADP
cana-729	171	32	overall	overall	ADJ
cana-729	171	33	trend	trend	NOUN
cana-729	171	34	.	.	PUNCT
cana-729	172	1	*	*	PUNCT
cana-729	172	2	courtesy	courtesy	ADJ
cana-729	172	3	national	national	ADJ
cana-729	172	4	informatics	informatics	PROPN
cana-729	172	5	centre	centre	PROPN
cana-729	172	6	.	.	PUNCT
cana-729	173	1	fig	fig	NOUN
cana-729	173	2	8(a	8(a	NUM
cana-729	173	3	)	)	PUNCT
cana-729	173	4	geo	geo	PROPN
cana-729	173	5	map	map	NOUN
cana-729	173	6	of	of	ADP
cana-729	173	7	mayurbhanj	mayurbhanj	ADJ
cana-729	173	8	district	district	NOUN
cana-729	173	9	8(b)trend	8(b)trend	NUM
cana-729	173	10	line	line	NOUN
cana-729	173	11	for	for	ADP
cana-729	173	12	the	the	DET
cana-729	173	13	largest	large	ADJ
cana-729	173	14	district	district	NOUN
cana-729	173	15	mayurbhanj	mayurbhanj	NOUN
cana-729	173	16	of	of	ADP
cana-729	173	17	odisha	odisha	PROPN
cana-729	173	18	.	.	PUNCT
cana-729	174	1	y	y	PROPN
cana-729	174	2	=	=	SYM
cana-729	174	3	19.924x	19.924x	NUM
cana-729	174	4	38436	38436	NUM
cana-729	174	5	r²	r²	NOUN
cana-729	174	6	=	=	NOUN
cana-729	175	1	0.14250	0.14250	NUM
cana-729	175	2	500	500	NUM
cana-729	175	3	1000	1000	NUM
cana-729	175	4	1500	1500	NUM
cana-729	175	5	2000	2000	NUM
cana-729	175	6	2500	2500	NUM
cana-729	175	7	2000	2000	NUM
cana-729	175	8	2005	2005	NUM
cana-729	175	9	2010	2010	NUM
cana-729	175	10	2015	2015	NUM
cana-729	175	11	2020	2020	NUM
cana-729	175	12	2025	2025	NUM
cana-729	175	13	total	total	ADJ
cana-729	175	14	rainfall	rainfall	NOUN
cana-729	175	15	y	y	PROPN
cana-729	175	16	=	=	PUNCT
cana-729	175	17	-4.3216x	-4.3216x	PROPN
cana-729	176	1	+	+	NUM
cana-729	176	2	10260	10260	NUM
cana-729	176	3	r²	r²	NOUN
cana-729	176	4	=	=	SYM
cana-729	176	5	0.0074	0.0074	NUM
cana-729	176	6	0	0	NUM
cana-729	176	7	500	500	NUM
cana-729	176	8	1000	1000	NUM
cana-729	176	9	1500	1500	NUM
cana-729	176	10	2000	2000	NUM
cana-729	176	11	2500	2500	NUM
cana-729	176	12	2000	2000	NUM
cana-729	176	13	2005	2005	NUM
cana-729	176	14	2010	2010	NUM
cana-729	176	15	2015	2015	NUM
cana-729	176	16	2020	2020	NUM
cana-729	176	17	2025	2025	NUM
cana-729	176	18	total	total	ADJ
cana-729	176	19	rain	rain	NOUN
cana-729	176	20	fall	fall	NOUN
cana-729	176	21	communications	communication	NOUN
cana-729	176	22	on	on	ADP
cana-729	176	23	applied	apply	VERB
cana-729	176	24	nonlinear	nonlinear	ADJ
cana-729	176	25	analysis	analysis	NOUN
cana-729	176	26	issn	issn	NOUN
cana-729	176	27	:	:	PUNCT
cana-729	176	28	1074	1074	NUM
cana-729	176	29	-	-	PUNCT
cana-729	176	30	133x	133x	NUM
cana-729	176	31	vol	vol	NOUN
cana-729	176	32	31	31	NUM
cana-729	176	33	no	no	NOUN
cana-729	176	34	.	.	PUNCT
cana-729	177	1	3s	3s	NUM
cana-729	177	2	(	(	PUNCT
cana-729	177	3	2024	2024	NUM
cana-729	177	4	)	)	PUNCT
cana-729	177	5	39	39	NUM
cana-729	177	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-729	177	7	fig	fig	NOUN
cana-729	177	8	9(a	9(a	NUM
cana-729	177	9	)	)	PUNCT
cana-729	177	10	geo	geo	PROPN
cana-729	177	11	mapof	mapof	PROPN
cana-729	177	12	jagatsinghpur	jagatsinghpur	PROPN
cana-729	177	13	9(b	9(b	NUM
cana-729	177	14	)	)	PUNCT
cana-729	177	15	trend	trend	NOUN
cana-729	177	16	line	line	NOUN
cana-729	177	17	for	for	ADP
cana-729	177	18	the	the	DET
cana-729	177	19	smallest	small	ADJ
cana-729	177	20	district	district	NOUN
cana-729	177	21	jagatsinghpur	jagatsinghpur	NOUN
cana-729	177	22	districtin	districtin	PROPN
cana-729	177	23	odisha	odisha	PROPN
cana-729	177	24	5	5	NUM
cana-729	177	25	.	.	NOUN
cana-729	177	26	results	result	NOUN
cana-729	177	27	and	and	CCONJ
cana-729	177	28	discussions	discussion	NOUN
cana-729	177	29	in	in	ADP
cana-729	177	30	this	this	DET
cana-729	177	31	paper	paper	NOUN
cana-729	177	32	,	,	PUNCT
cana-729	177	33	the	the	DET
cana-729	177	34	rainfall	rainfall	NOUN
cana-729	177	35	records	record	NOUN
cana-729	177	36	of	of	ADP
cana-729	177	37	odisha	odisha	PROPN
cana-729	177	38	were	be	AUX
cana-729	177	39	used	use	VERB
cana-729	177	40	to	to	PART
cana-729	177	41	successfully	successfully	ADV
cana-729	177	42	identify	identify	VERB
cana-729	177	43	the	the	DET
cana-729	177	44	severity	severity	NOUN
cana-729	177	45	level	level	NOUN
cana-729	177	46	of	of	ADP
cana-729	177	47	drought	drought	NOUN
cana-729	177	48	from	from	ADP
cana-729	177	49	the	the	DET
cana-729	177	50	year	year	NOUN
cana-729	177	51	1993	1993	NUM
cana-729	177	52	to	to	ADP
cana-729	177	53	2021	2021	NUM
cana-729	177	54	for	for	ADP
cana-729	177	55	all	all	DET
cana-729	177	56	the	the	DET
cana-729	177	57	districts	district	NOUN
cana-729	177	58	of	of	ADP
cana-729	177	59	the	the	DET
cana-729	177	60	state	state	NOUN
cana-729	177	61	.	.	PUNCT
cana-729	178	1	5.1	5.1	NUM
cana-729	178	2	drought	drought	NOUN
cana-729	178	3	and	and	CCONJ
cana-729	178	4	flood	flood	NOUN
cana-729	178	5	scenario	scenario	NOUN
cana-729	178	6	it	it	PRON
cana-729	178	7	was	be	AUX
cana-729	178	8	found	find	VERB
cana-729	178	9	that	that	SCONJ
cana-729	178	10	in	in	ADP
cana-729	178	11	1996	1996	NUM
cana-729	178	12	drought	drought	NOUN
cana-729	178	13	was	be	AUX
cana-729	178	14	recorded	record	VERB
cana-729	178	15	and	and	CCONJ
cana-729	178	16	in	in	ADP
cana-729	178	17	1994	1994	NUM
cana-729	178	18	flood	flood	NOUN
cana-729	178	19	situation	situation	NOUN
cana-729	178	20	was	be	AUX
cana-729	178	21	recorded	record	VERB
cana-729	178	22	in	in	ADP
cana-729	178	23	subarnapur	subarnapur	PROPN
cana-729	178	24	district	district	PROPN
cana-729	178	25	.	.	PUNCT
cana-729	179	1	the	the	DET
cana-729	179	2	rainfall	rainfall	NOUN
cana-729	179	3	pattern	pattern	NOUN
cana-729	179	4	of	of	ADP
cana-729	179	5	both	both	DET
cana-729	179	6	scenarios	scenario	NOUN
cana-729	179	7	,	,	PUNCT
cana-729	179	8	where	where	SCONJ
cana-729	179	9	the	the	DET
cana-729	179	10	blue	blue	ADJ
cana-729	179	11	bars	bar	NOUN
cana-729	179	12	show	show	VERB
cana-729	179	13	the	the	DET
cana-729	179	14	rainfall	rainfall	NOUN
cana-729	179	15	recorded	record	VERB
cana-729	179	16	in	in	ADP
cana-729	179	17	the	the	DET
cana-729	179	18	given	give	VERB
cana-729	179	19	month	month	NOUN
cana-729	179	20	and	and	CCONJ
cana-729	179	21	the	the	DET
cana-729	179	22	red	red	ADJ
cana-729	179	23	line	line	NOUN
cana-729	179	24	shows	show	VERB
cana-729	179	25	28	28	NUM
cana-729	179	26	years	year	NOUN
cana-729	179	27	of	of	ADP
cana-729	179	28	average	average	ADJ
cana-729	179	29	rainfall	rainfall	NOUN
cana-729	179	30	in	in	ADP
cana-729	179	31	subarnapur	subarnapur	PROPN
cana-729	179	32	district	district	PROPN
cana-729	179	33	and	and	CCONJ
cana-729	179	34	the	the	DET
cana-729	179	35	green	green	ADJ
cana-729	179	36	line	line	NOUN
cana-729	179	37	shows	show	VERB
cana-729	179	38	the	the	DET
cana-729	179	39	average	average	ADJ
cana-729	179	40	monsoon	monsoon	NOUN
cana-729	179	41	rainfall	rainfall	NOUN
cana-729	179	42	recorded	record	VERB
cana-729	179	43	in	in	ADP
cana-729	179	44	that	that	DET
cana-729	179	45	year	year	NOUN
cana-729	179	46	was	be	AUX
cana-729	179	47	compared	compare	VERB
cana-729	179	48	.	.	PUNCT
cana-729	180	1	the	the	DET
cana-729	180	2	first	first	ADJ
cana-729	180	3	half	half	NOUN
cana-729	180	4	of	of	ADP
cana-729	180	5	the	the	DET
cana-729	180	6	1996	1996	NUM
cana-729	180	7	graph	graph	NOUN
cana-729	180	8	shows	show	VERB
cana-729	180	9	the	the	DET
cana-729	180	10	moderate	moderate	ADJ
cana-729	180	11	drought	drought	NOUN
cana-729	180	12	scenario	scenario	NOUN
cana-729	180	13	(	(	PUNCT
cana-729	180	14	1995	1995	NUM
cana-729	180	15	)	)	PUNCT
cana-729	180	16	and	and	CCONJ
cana-729	180	17	the	the	DET
cana-729	180	18	second	second	ADJ
cana-729	180	19	half	half	NOUN
cana-729	180	20	shows	show	VERB
cana-729	180	21	the	the	DET
cana-729	180	22	drought	drought	NOUN
cana-729	180	23	scenario	scenario	NOUN
cana-729	180	24	(	(	PUNCT
cana-729	180	25	1996	1996	NUM
cana-729	180	26	)	)	PUNCT
cana-729	180	27	.	.	PUNCT
cana-729	181	1	there	there	PRON
cana-729	181	2	was	be	VERB
cana-729	181	3	a	a	DET
cana-729	181	4	sudden	sudden	ADJ
cana-729	181	5	fall	fall	NOUN
cana-729	181	6	in	in	ADP
cana-729	181	7	the	the	DET
cana-729	181	8	average	average	ADJ
cana-729	181	9	monsoon	monsoon	NOUN
cana-729	181	10	rainfall	rainfall	NOUN
cana-729	181	11	in	in	ADP
cana-729	181	12	the	the	DET
cana-729	181	13	year	year	NOUN
cana-729	181	14	1996	1996	NUM
cana-729	181	15	and	and	CCONJ
cana-729	181	16	the	the	DET
cana-729	181	17	rainfall	rainfall	NOUN
cana-729	181	18	that	that	PRON
cana-729	181	19	was	be	AUX
cana-729	181	20	recorded	record	VERB
cana-729	181	21	for	for	ADP
cana-729	181	22	each	each	DET
cana-729	181	23	month	month	NOUN
cana-729	181	24	did	do	AUX
cana-729	181	25	n't	not	PART
cana-729	181	26	cross	cross	VERB
cana-729	181	27	the	the	DET
cana-729	181	28	average	average	ADJ
cana-729	181	29	rainfall	rainfall	NOUN
cana-729	181	30	for	for	ADP
cana-729	181	31	that	that	DET
cana-729	181	32	year	year	NOUN
cana-729	181	33	and	and	CCONJ
cana-729	181	34	during	during	ADP
cana-729	181	35	monsoon	monsoon	NOUN
cana-729	181	36	season	season	NOUN
cana-729	181	37	it	it	PRON
cana-729	181	38	was	be	AUX
cana-729	181	39	just	just	ADV
cana-729	181	40	touching	touch	VERB
cana-729	181	41	the	the	DET
cana-729	181	42	average	average	ADJ
cana-729	181	43	monsoon	monsoon	NOUN
cana-729	181	44	rainfall	rainfall	NOUN
cana-729	181	45	line	line	NOUN
cana-729	181	46	.	.	PUNCT
cana-729	182	1	y	y	NOUN
cana-729	182	2	=	=	SYM
cana-729	182	3	11.679x	11.679x	NUM
cana-729	182	4	22026	22026	NUM
cana-729	182	5	r²	r²	NOUN
cana-729	182	6	=	=	SYM
cana-729	183	1	0.0626	0.0626	NUM
cana-729	183	2	0	0	NUM
cana-729	183	3	500	500	NUM
cana-729	183	4	1000	1000	NUM
cana-729	183	5	1500	1500	NUM
cana-729	183	6	2000	2000	NUM
cana-729	183	7	2500	2500	NUM
cana-729	183	8	2000	2000	NUM
cana-729	183	9	2005	2005	NUM
cana-729	183	10	2010	2010	NUM
cana-729	183	11	2015	2015	NUM
cana-729	183	12	2020	2020	NUM
cana-729	183	13	2025	2025	NUM
cana-729	183	14	total	total	ADJ
cana-729	183	15	rainfall	rainfall	NOUN
cana-729	183	16	communications	communication	NOUN
cana-729	183	17	on	on	ADP
cana-729	183	18	applied	apply	VERB
cana-729	183	19	nonlinear	nonlinear	ADJ
cana-729	183	20	analysis	analysis	NOUN
cana-729	183	21	issn	issn	NOUN
cana-729	183	22	:	:	PUNCT
cana-729	183	23	1074	1074	NUM
cana-729	183	24	-	-	PUNCT
cana-729	183	25	133x	133x	NUM
cana-729	183	26	vol	vol	NOUN
cana-729	183	27	31	31	NUM
cana-729	183	28	no	no	NOUN
cana-729	183	29	.	.	PUNCT
cana-729	184	1	3s	3s	NUM
cana-729	184	2	(	(	PUNCT
cana-729	184	3	2024	2024	NUM
cana-729	184	4	)	)	PUNCT
cana-729	184	5	40	40	NUM
cana-729	184	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-729	184	7	fig	fig	NOUN
cana-729	184	8	10	10	NUM
cana-729	184	9	average	average	ADJ
cana-729	184	10	rainfall	rainfall	NOUN
cana-729	184	11	unlike	unlike	ADP
cana-729	184	12	1996	1996	NUM
cana-729	184	13	,	,	PUNCT
cana-729	184	14	the	the	DET
cana-729	184	15	first	first	ADJ
cana-729	184	16	half	half	NOUN
cana-729	184	17	of	of	ADP
cana-729	184	18	1994	1994	NUM
cana-729	184	19	graph	graph	NOUN
cana-729	184	20	shows	show	VERB
cana-729	184	21	the	the	DET
cana-729	184	22	no	no	DET
cana-729	184	23	drought	drought	NOUN
cana-729	184	24	scenario	scenario	NOUN
cana-729	184	25	(	(	PUNCT
cana-729	184	26	1993	1993	NUM
cana-729	184	27	)	)	PUNCT
cana-729	184	28	and	and	CCONJ
cana-729	184	29	second	second	ADJ
cana-729	184	30	half	half	NOUN
cana-729	184	31	shows	show	VERB
cana-729	184	32	a	a	DET
cana-729	184	33	flood	flood	NOUN
cana-729	184	34	scenario	scenario	NOUN
cana-729	184	35	(	(	PUNCT
cana-729	184	36	1994	1994	NUM
cana-729	184	37	)	)	PUNCT
cana-729	184	38	.	.	PUNCT
cana-729	185	1	there	there	PRON
cana-729	185	2	's	be	VERB
cana-729	185	3	a	a	DET
cana-729	185	4	sudden	sudden	ADJ
cana-729	185	5	rise	rise	NOUN
cana-729	185	6	in	in	ADP
cana-729	185	7	the	the	DET
cana-729	185	8	average	average	ADJ
cana-729	185	9	monsoon	monsoon	NOUN
cana-729	185	10	rainfall	rainfall	NOUN
cana-729	185	11	in	in	ADP
cana-729	185	12	the	the	DET
cana-729	185	13	year	year	NOUN
cana-729	185	14	1994	1994	NUM
cana-729	185	15	and	and	CCONJ
cana-729	185	16	the	the	DET
cana-729	185	17	rainfall	rainfall	NOUN
cana-729	185	18	that	that	PRON
cana-729	185	19	was	be	AUX
cana-729	185	20	recorded	record	VERB
cana-729	185	21	for	for	ADP
cana-729	185	22	each	each	DET
cana-729	185	23	month	month	NOUN
cana-729	185	24	were	be	AUX
cana-729	185	25	much	much	ADV
cana-729	185	26	higher	high	ADJ
cana-729	185	27	than	than	ADP
cana-729	185	28	the	the	DET
cana-729	185	29	average	average	ADJ
cana-729	185	30	monsoon	monsoon	NOUN
cana-729	185	31	rainfall	rainfall	NOUN
cana-729	185	32	line	line	NOUN
cana-729	185	33	.	.	PUNCT
cana-729	186	1	fig	fig	NOUN
cana-729	186	2	11	11	NUM
cana-729	186	3	flood	flood	NOUN
cana-729	186	4	scenario	scenario	NOUN
cana-729	186	5	5.2	5.2	NUM
cana-729	186	6	model	model	NOUN
cana-729	186	7	accuracy	accuracy	NOUN
cana-729	186	8	the	the	DET
cana-729	186	9	accuracy	accuracy	NOUN
cana-729	186	10	of	of	ADP
cana-729	186	11	the	the	DET
cana-729	186	12	forecasting	forecasting	NOUN
cana-729	186	13	model	model	NOUN
cana-729	186	14	was	be	AUX
cana-729	186	15	determined	determine	VERB
cana-729	186	16	using	use	VERB
cana-729	186	17	rmse	rmse	NOUN
cana-729	186	18	and	and	CCONJ
cana-729	186	19	mape	mape	NOUN
cana-729	186	20	.	.	PUNCT
cana-729	187	1	the	the	DET
cana-729	187	2	average	average	ADJ
cana-729	187	3	rmse	rmse	NOUN
cana-729	187	4	of	of	ADP
cana-729	187	5	arima	arima	PROPN
cana-729	187	6	,	,	PUNCT
cana-729	187	7	ar	ar	PROPN
cana-729	187	8	and	and	CCONJ
cana-729	187	9	lstm	lstm	NOUN
cana-729	187	10	is	be	AUX
cana-729	187	11	13.8061	13.8061	NUM
cana-729	187	12	,	,	PUNCT
cana-729	187	13	29.5594	29.5594	NUM
cana-729	187	14	and	and	CCONJ
cana-729	187	15	25.5067	25.5067	NUM
cana-729	187	16	respectively	respectively	ADV
cana-729	187	17	.	.	PUNCT
cana-729	188	1	the	the	DET
cana-729	188	2	average	average	ADJ
cana-729	188	3	mape	mape	NOUN
cana-729	188	4	of	of	ADP
cana-729	188	5	arima	arima	PROPN
cana-729	188	6	,	,	PUNCT
cana-729	188	7	ar	ar	PROPN
cana-729	188	8	and	and	CCONJ
cana-729	188	9	lstm	lstm	NOUN
cana-729	188	10	is	be	AUX
cana-729	188	11	0.0846	0.0846	NUM
cana-729	188	12	,	,	PUNCT
cana-729	188	13	0.1779	0.1779	NUM
cana-729	188	14	and	and	CCONJ
cana-729	188	15	0.1589	0.1589	NUM
cana-729	188	16	respectively	respectively	ADV
cana-729	188	17	.	.	PUNCT
cana-729	189	1	communications	communication	NOUN
cana-729	189	2	on	on	ADP
cana-729	189	3	applied	apply	VERB
cana-729	189	4	nonlinear	nonlinear	ADJ
cana-729	189	5	analysis	analysis	NOUN
cana-729	189	6	issn	issn	NOUN
cana-729	189	7	:	:	PUNCT
cana-729	189	8	1074	1074	NUM
cana-729	189	9	-	-	PUNCT
cana-729	189	10	133x	133x	NUM
cana-729	189	11	vol	vol	NOUN
cana-729	189	12	31	31	NUM
cana-729	189	13	no	no	NOUN
cana-729	189	14	.	.	PUNCT
cana-729	190	1	3s	3s	NUM
cana-729	190	2	(	(	PUNCT
cana-729	190	3	2024	2024	NUM
cana-729	190	4	)	)	PUNCT
cana-729	190	5	41	41	NUM
cana-729	190	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-729	190	7	for	for	ADP
cana-729	190	8	the	the	DET
cana-729	190	9	classification	classification	NOUN
cana-729	190	10	model	model	NOUN
cana-729	190	11	,	,	PUNCT
cana-729	190	12	f1	f1	ADJ
cana-729	190	13	score	score	NOUN
cana-729	190	14	and	and	CCONJ
cana-729	190	15	precision	precision	NOUN
cana-729	190	16	score	score	NOUN
cana-729	190	17	were	be	AUX
cana-729	190	18	used	use	VERB
cana-729	190	19	as	as	ADP
cana-729	190	20	the	the	DET
cana-729	190	21	accuracy	accuracy	NOUN
cana-729	190	22	measure	measure	NOUN
cana-729	190	23	.	.	PUNCT
cana-729	191	1	the	the	DET
cana-729	191	2	f1	f1	PROPN
cana-729	191	3	score	score	NOUN
cana-729	191	4	of	of	ADP
cana-729	191	5	naive	naive	ADJ
cana-729	191	6	bayes	bayes	NOUN
cana-729	191	7	and	and	CCONJ
cana-729	191	8	svm	svm	PROPN
cana-729	191	9	is	be	AUX
cana-729	191	10	0.9393	0.9393	NUM
cana-729	191	11	and	and	CCONJ
cana-729	191	12	0.8956	0.8956	NUM
cana-729	191	13	respectively	respectively	ADV
cana-729	191	14	.	.	PUNCT
cana-729	192	1	the	the	DET
cana-729	192	2	precision	precision	NOUN
cana-729	192	3	scores	score	NOUN
cana-729	192	4	of	of	ADP
cana-729	192	5	naive	naive	ADJ
cana-729	192	6	bayes	baye	NOUN
cana-729	192	7	and	and	CCONJ
cana-729	192	8	svm	svm	PROPN
cana-729	192	9	are	be	AUX
cana-729	192	10	0.9778	0.9778	NUM
cana-729	192	11	and	and	CCONJ
cana-729	192	12	0.9407	0.9407	NUM
cana-729	192	13	respectively	respectively	ADV
cana-729	192	14	.	.	PUNCT
cana-729	193	1	6	6	X
cana-729	193	2	.	.	PUNCT
cana-729	193	3	conclusions	conclusion	NOUN
cana-729	193	4	comparing	compare	VERB
cana-729	193	5	the	the	DET
cana-729	193	6	average	average	ADJ
cana-729	193	7	rmse	rmse	NOUN
cana-729	193	8	and	and	CCONJ
cana-729	193	9	mape	mape	NOUN
cana-729	193	10	value	value	NOUN
cana-729	193	11	for	for	ADP
cana-729	193	12	the	the	DET
cana-729	193	13	forecasting	forecasting	NOUN
cana-729	193	14	model	model	NOUN
cana-729	193	15	,	,	PUNCT
cana-729	193	16	arima	arima	PROPN
cana-729	193	17	outperforms	outperform	VERB
cana-729	193	18	lstm	lstm	PROPN
cana-729	193	19	and	and	CCONJ
cana-729	193	20	ar	ar	NOUN
cana-729	193	21	in	in	ADP
cana-729	193	22	predicting	predict	VERB
cana-729	193	23	rainfall	rainfall	NOUN
cana-729	193	24	using	use	VERB
cana-729	193	25	the	the	DET
cana-729	193	26	last	last	ADJ
cana-729	193	27	28	28	NUM
cana-729	193	28	years	year	NOUN
cana-729	193	29	of	of	ADP
cana-729	193	30	data	datum	NOUN
cana-729	193	31	.	.	PUNCT
cana-729	194	1	for	for	ADP
cana-729	194	2	classification	classification	NOUN
cana-729	194	3	,	,	PUNCT
cana-729	194	4	naive	naive	ADJ
cana-729	194	5	baye	baye	NOUN
cana-729	194	6	's	's	PART
cana-729	194	7	accuracy	accuracy	NOUN
cana-729	194	8	is	be	AUX
cana-729	194	9	much	much	ADV
cana-729	194	10	better	well	ADJ
cana-729	194	11	than	than	ADP
cana-729	194	12	svm	svm	VERB
cana-729	194	13	for	for	ADP
cana-729	194	14	classifying	classify	VERB
cana-729	194	15	the	the	DET
cana-729	194	16	predicted	predict	VERB
cana-729	194	17	rainfall	rainfall	NOUN
cana-729	194	18	into	into	ADP
cana-729	194	19	severity	severity	NOUN
cana-729	194	20	levels	level	NOUN
cana-729	194	21	.	.	PUNCT
cana-729	195	1	7	7	X
cana-729	195	2	.	.	NUM
cana-729	195	3	limitations	limitation	NOUN
cana-729	195	4	and	and	CCONJ
cana-729	195	5	future	future	ADJ
cana-729	195	6	scope	scope	NOUN
cana-729	195	7	there	there	PRON
cana-729	195	8	are	be	VERB
cana-729	195	9	some	some	DET
cana-729	195	10	limitations	limitation	NOUN
cana-729	195	11	to	to	ADP
cana-729	195	12	the	the	DET
cana-729	195	13	model	model	NOUN
cana-729	195	14	used	use	VERB
cana-729	195	15	in	in	ADP
cana-729	195	16	this	this	DET
cana-729	195	17	paper	paper	NOUN
cana-729	195	18	.	.	PUNCT
cana-729	196	1	firstly	firstly	ADV
cana-729	196	2	,	,	PUNCT
cana-729	196	3	precipitation	precipitation	NOUN
cana-729	196	4	is	be	AUX
cana-729	196	5	not	not	PART
cana-729	196	6	the	the	DET
cana-729	196	7	only	only	ADJ
cana-729	196	8	factor	factor	NOUN
cana-729	196	9	that	that	PRON
cana-729	196	10	affects	affect	VERB
cana-729	196	11	drought	drought	NOUN
cana-729	196	12	.	.	PUNCT
cana-729	197	1	there	there	PRON
cana-729	197	2	are	be	VERB
cana-729	197	3	various	various	ADJ
cana-729	197	4	other	other	ADJ
cana-729	197	5	factors	factor	NOUN
cana-729	197	6	like	like	ADP
cana-729	197	7	soil	soil	NOUN
cana-729	197	8	moisture	moisture	NOUN
cana-729	197	9	,	,	PUNCT
cana-729	197	10	air	air	NOUN
cana-729	197	11	temperature	temperature	NOUN
cana-729	197	12	,	,	PUNCT
cana-729	197	13	wind	wind	NOUN
cana-729	197	14	speed	speed	NOUN
cana-729	197	15	,	,	PUNCT
cana-729	197	16	surface	surface	NOUN
cana-729	197	17	pressure	pressure	NOUN
cana-729	197	18	,	,	PUNCT
cana-729	197	19	geo	geo	PROPN
cana-729	197	20	-	-	PUNCT
cana-729	197	21	potential	potential	ADJ
cana-729	197	22	height	height	NOUN
cana-729	197	23	,	,	PUNCT
cana-729	197	24	relative	relative	ADJ
cana-729	197	25	humidity	humidity	NOUN
cana-729	197	26	,	,	PUNCT
cana-729	197	27	etc	etc	X
cana-729	197	28	.	.	X
cana-729	197	29	however	however	ADV
cana-729	197	30	,	,	PUNCT
cana-729	197	31	rainfall	rainfall	NOUN
cana-729	197	32	might	might	AUX
cana-729	197	33	be	be	AUX
cana-729	197	34	the	the	DET
cana-729	197	35	primary	primary	ADJ
cana-729	197	36	factor	factor	NOUN
cana-729	197	37	that	that	PRON
cana-729	197	38	can	can	AUX
cana-729	197	39	be	be	AUX
cana-729	197	40	considered	consider	VERB
cana-729	197	41	for	for	ADP
cana-729	197	42	drought	drought	NOUN
cana-729	197	43	prediction	prediction	NOUN
cana-729	197	44	.	.	PUNCT
cana-729	198	1	secondly	secondly	ADV
cana-729	198	2	,	,	PUNCT
cana-729	198	3	here	here	ADV
cana-729	198	4	only	only	ADV
cana-729	198	5	simple	simple	ADJ
cana-729	198	6	statistical	statistical	ADJ
cana-729	198	7	measures	measure	NOUN
cana-729	198	8	were	be	AUX
cana-729	198	9	used	use	VERB
cana-729	198	10	to	to	PART
cana-729	198	11	identify	identify	VERB
cana-729	198	12	the	the	DET
cana-729	198	13	severity	severity	NOUN
cana-729	198	14	level	level	NOUN
cana-729	198	15	of	of	ADP
cana-729	198	16	drought	drought	NOUN
cana-729	198	17	and	and	CCONJ
cana-729	198	18	classify	classify	VERB
cana-729	198	19	the	the	DET
cana-729	198	20	districts	district	NOUN
cana-729	198	21	accordingly	accordingly	ADV
cana-729	198	22	.	.	PUNCT
cana-729	199	1	another	another	DET
cana-729	199	2	issue	issue	NOUN
cana-729	199	3	is	be	AUX
cana-729	199	4	that	that	SCONJ
cana-729	199	5	the	the	DET
cana-729	199	6	models	model	NOUN
cana-729	199	7	used	use	VERB
cana-729	199	8	here	here	ADV
cana-729	199	9	can	can	AUX
cana-729	199	10	have	have	VERB
cana-729	199	11	greater	great	ADJ
cana-729	199	12	accuracy	accuracy	NOUN
cana-729	199	13	only	only	ADV
cana-729	199	14	for	for	ADP
cana-729	199	15	predicting	predict	VERB
cana-729	199	16	one	one	NUM
cana-729	199	17	or	or	CCONJ
cana-729	199	18	at	at	ADP
cana-729	199	19	most	most	ADJ
cana-729	199	20	two	two	NUM
cana-729	199	21	years	year	NOUN
cana-729	199	22	of	of	ADP
cana-729	199	23	precipitation	precipitation	NOUN
cana-729	199	24	.	.	PUNCT
cana-729	200	1	future	future	ADJ
cana-729	200	2	scope	scope	NOUN
cana-729	200	3	includes	include	VERB
cana-729	200	4	overcoming	overcome	VERB
cana-729	200	5	the	the	DET
cana-729	200	6	above	above	ADV
cana-729	200	7	-	-	PUNCT
cana-729	200	8	mentioned	mention	VERB
cana-729	200	9	limitations	limitation	NOUN
cana-729	200	10	and	and	CCONJ
cana-729	200	11	building	build	VERB
cana-729	200	12	a	a	DET
cana-729	200	13	more	more	ADV
cana-729	200	14	robust	robust	ADJ
cana-729	200	15	model	model	NOUN
cana-729	200	16	.	.	PUNCT
cana-729	201	1	real	real	ADJ
cana-729	201	2	-	-	PUNCT
cana-729	201	3	time	time	NOUN
cana-729	201	4	drought	drought	NOUN
cana-729	201	5	prediction	prediction	NOUN
cana-729	201	6	that	that	PRON
cana-729	201	7	includes	include	VERB
cana-729	201	8	all	all	DET
cana-729	201	9	the	the	DET
cana-729	201	10	factors	factor	NOUN
cana-729	201	11	affecting	affect	VERB
cana-729	201	12	drought	drought	NOUN
cana-729	201	13	can	can	AUX
cana-729	201	14	be	be	AUX
cana-729	201	15	developed	develop	VERB
cana-729	201	16	,	,	PUNCT
cana-729	201	17	which	which	PRON
cana-729	201	18	can	can	AUX
cana-729	201	19	be	be	AUX
cana-729	201	20	made	make	VERB
cana-729	201	21	user	user	NOUN
cana-729	201	22	-	-	PUNCT
cana-729	201	23	friendly	friendly	ADJ
cana-729	201	24	by	by	ADP
cana-729	201	25	developing	develop	VERB
cana-729	201	26	a	a	DET
cana-729	201	27	mobile	mobile	ADJ
cana-729	201	28	application	application	NOUN
cana-729	201	29	.	.	PUNCT
cana-729	202	1	references	reference	NOUN
cana-729	202	2	[	[	X
cana-729	202	3	1	1	NUM
cana-729	202	4	]	]	PUNCT
cana-729	202	5	agana	agana	PROPN
cana-729	202	6	,	,	PUNCT
cana-729	202	7	n.	n.	PROPN
cana-729	202	8	a.	a.	PROPN
cana-729	202	9	,	,	PUNCT
cana-729	202	10	homifar	homifar	ADV
cana-729	202	11	,	,	PUNCT
cana-729	202	12	a.	a.	NOUN
cana-729	202	13	,	,	PUNCT
cana-729	202	14	(	(	PUNCT
cana-729	202	15	2017	2017	NUM
cana-729	202	16	)	)	PUNCT
cana-729	202	17	,	,	PUNCT
cana-729	202	18	a	a	DET
cana-729	202	19	deep	deep	ADJ
cana-729	202	20	learning	learning	NOUN
cana-729	202	21	based	base	VERB
cana-729	202	22	approach	approach	NOUN
cana-729	202	23	for	for	ADP
cana-729	202	24	long	long	ADJ
cana-729	202	25	-	-	PUNCT
cana-729	202	26	term	term	NOUN
cana-729	202	27	drought	drought	NOUN
cana-729	202	28	prediction	prediction	NOUN
cana-729	202	29	.	.	PUNCT
cana-729	203	1	,	,	PUNCT
cana-729	203	2	computer	computer	NOUN
cana-729	203	3	science	science	NOUN
cana-729	203	4	;	;	PUNCT
cana-729	203	5	southeastcon	southeastcon	PROPN
cana-729	203	6	[	[	X
cana-729	203	7	2	2	NUM
cana-729	203	8	]	]	PUNCT
cana-729	203	9	belayneh	belayneh	NOUN
cana-729	203	10	,	,	PUNCT
cana-729	203	11	a.	a.	NOUN
cana-729	203	12	m.	m.	NOUN
cana-729	203	13	,	,	PUNCT
cana-729	203	14	adamowski	adamowski	PROPN
cana-729	203	15	,	,	PUNCT
cana-729	203	16	j.	j.	PROPN
cana-729	203	17	,	,	PUNCT
cana-729	203	18	(	(	PUNCT
cana-729	203	19	2013	2013	NUM
cana-729	203	20	)	)	PUNCT
cana-729	203	21	,	,	PUNCT
cana-729	203	22	drought	drought	NOUN
cana-729	203	23	forecasting	forecasting	NOUN
cana-729	203	24	using	use	VERB
cana-729	203	25	new	new	ADJ
cana-729	203	26	machine	machine	NOUN
cana-729	203	27	learning	learning	NOUN
cana-729	203	28	methods	method	NOUN
cana-729	203	29	,	,	PUNCT
cana-729	203	30	journal	journal	NOUN
cana-729	203	31	of	of	ADP
cana-729	203	32	water	water	NOUN
cana-729	203	33	and	and	CCONJ
cana-729	203	34	land	land	NOUN
cana-729	203	35	development	development	NOUN
cana-729	203	36	,	,	PUNCT
cana-729	203	37	18	18	NUM
cana-729	203	38	,	,	PUNCT
cana-729	203	39	3	3	NUM
cana-729	203	40	-	-	SYM
cana-729	203	41	12	12	NUM
cana-729	203	42	.	.	PUNCT
cana-729	204	1	[	[	X
cana-729	204	2	3	3	X
cana-729	204	3	]	]	X
cana-729	204	4	fung	fung	PROPN
cana-729	204	5	k	k	PROPN
cana-729	204	6	f	f	PROPN
cana-729	204	7	,	,	PUNCT
cana-729	204	8	huang	huang	PROPN
cana-729	204	9	y	y	PROPN
cana-729	204	10	f	f	PROPN
cana-729	204	11	,	,	PUNCT
cana-729	204	12	koo	koo	PROPN
cana-729	204	13	c	c	PROPN
cana-729	204	14	h	h	PROPN
cana-729	204	15	,	,	PUNCT
cana-729	204	16	mirzaei	mirzaei	PROPN
cana-729	204	17	m	m	PROPN
cana-729	204	18	..	..	PUNCT
cana-729	204	19	,	,	PUNCT
cana-729	204	20	(	(	PUNCT
cana-729	204	21	2020	2020	NUM
cana-729	204	22	)	)	PUNCT
cana-729	204	23	.	.	PUNCT
cana-729	205	1	improved	improve	VERB
cana-729	205	2	svr	svr	PROPN
cana-729	205	3	machine	machine	NOUN
cana-729	205	4	learning	learning	NOUN
cana-729	205	5	models	model	NOUN
cana-729	205	6	for	for	ADP
cana-729	205	7	agricultural	agricultural	ADJ
cana-729	205	8	drought	drought	NOUN
cana-729	205	9	prediction	prediction	NOUN
cana-729	205	10	at	at	ADP
cana-729	205	11	downstream	downstream	NOUN
cana-729	205	12	of	of	ADP
cana-729	205	13	langat	langat	ADJ
cana-729	205	14	river	river	NOUN
cana-729	205	15	basin	basin	NOUN
cana-729	205	16	,	,	PUNCT
cana-729	205	17	malaysia	malaysia	PROPN
cana-729	205	18	.	.	PUNCT
cana-729	206	1	j	j	PROPN
cana-729	206	2	water	water	NOUN
cana-729	206	3	climate	climate	NOUN
cana-729	206	4	change	change	NOUN
cana-729	206	5	.	.	PUNCT
cana-729	207	1	11(4):1383–1398	11(4):1383–1398	NUM
cana-729	207	2	.	.	PUNCT
cana-729	208	1	[	[	X
cana-729	208	2	4	4	NUM
cana-729	208	3	]	]	X
cana-729	208	4	kaur	kaur	PROPN
cana-729	208	5	,	,	PUNCT
cana-729	208	6	a.	a.	PROPN
cana-729	208	7	,	,	PUNCT
cana-729	208	8	sandeep	sandeep	PROPN
cana-729	208	9	k.	k.	PROPN
cana-729	208	10	sood	sood	PROPN
cana-729	208	11	.	.	PUNCT
cana-729	209	1	,	,	PUNCT
cana-729	209	2	(	(	PUNCT
cana-729	209	3	2020	2020	NUM
cana-729	209	4	)	)	PUNCT
cana-729	209	5	,	,	PUNCT
cana-729	209	6	deep	deep	ADJ
cana-729	209	7	learning	learning	NOUN
cana-729	209	8	based	base	VERB
cana-729	209	9	drought	drought	NOUN
cana-729	209	10	assessment	assessment	NOUN
cana-729	209	11	and	and	CCONJ
cana-729	209	12	prediction	prediction	NOUN
cana-729	209	13	framework	framework	NOUN
cana-729	209	14	,	,	PUNCT
cana-729	209	15	ecological	ecological	ADJ
cana-729	209	16	informatics	informatic	NOUN
cana-729	209	17	,	,	PUNCT
cana-729	209	18	57	57	NUM
cana-729	209	19	.	.	PUNCT
cana-729	210	1	[	[	X
cana-729	210	2	5	5	NUM
cana-729	210	3	]	]	SYM
cana-729	210	4	li	li	PROPN
cana-729	210	5	,	,	PUNCT
cana-729	210	6	j.	j.	PROPN
cana-729	210	7	,	,	PUNCT
cana-729	210	8	wang	wang	PROPN
cana-729	210	9	z.	z.	PROPN
cana-729	210	10	,	,	PUNCT
cana-729	210	11	wu	wu	PROPN
cana-729	210	12	x.	x.	PROPN
cana-729	210	13	,	,	PUNCT
cana-729	210	14	xu	xu	PROPN
cana-729	210	15	c	c	PROPN
cana-729	210	16	y.	y.	PROPN
cana-729	210	17	,	,	PUNCT
cana-729	210	18	shengalian	shengalian	PROPN
cana-729	210	19	g.	g.	PROPN
cana-729	210	20	chen	chen	PROPN
cana-729	210	21	x	x	PUNCT
cana-729	211	1	x.	x.	PROPN
cana-729	211	2	,	,	PUNCT
cana-729	211	3	(	(	PUNCT
cana-729	211	4	2021	2021	NUM
cana-729	211	5	)	)	PUNCT
cana-729	211	6	,	,	PUNCT
cana-729	211	7	robust	robust	ADJ
cana-729	211	8	meteorological	meteorological	ADJ
cana-729	211	9	drought	drought	NOUN
cana-729	211	10	prediction	prediction	NOUN
cana-729	211	11	using	use	VERB
cana-729	211	12	antecedent	antecedent	NOUN
cana-729	211	13	sst	sst	NOUN
cana-729	211	14	fluctuations	fluctuation	NOUN
cana-729	211	15	and	and	CCONJ
cana-729	211	16	machine	machine	NOUN
cana-729	211	17	learning	learning	NOUN
cana-729	211	18	,	,	PUNCT
cana-729	211	19	water	water	NOUN
cana-729	211	20	resources	resource	NOUN
cana-729	211	21	research	research	NOUN
cana-729	211	22	.	.	PUNCT
cana-729	211	23	,	,	PUNCT
cana-729	211	24	57	57	NUM
cana-729	211	25	,	,	PUNCT
cana-729	211	26	e2020wr029413	e2020wr029413	NOUN
cana-729	211	27	.	.	PUNCT
cana-729	212	1	[	[	X
cana-729	212	2	6	6	NUM
cana-729	212	3	]	]	X
cana-729	212	4	liu	liu	PROPN
cana-729	212	5	,	,	PUNCT
cana-729	212	6	z.	z.	PROPN
cana-729	212	7	n.	n.	PROPN
cana-729	212	8	,	,	PUNCT
cana-729	212	9	li	li	PROPN
cana-729	212	10	q	q	PROPN
cana-729	212	11	f.	f.	PROPN
cana-729	212	12	,	,	PUNCT
cana-729	212	13	nguyen	nguyen	PROPN
cana-729	212	14	l	l	PROPN
cana-729	212	15	b.	b.	PROPN
cana-729	212	16	,	,	PUNCT
cana-729	212	17	xu	xu	PROPN
cana-729	212	18	g	g	PROPN
cana-729	212	19	h.	h.	PROPN
cana-729	212	20	,	,	PUNCT
cana-729	212	21	(	(	PUNCT
cana-729	212	22	2018	2018	NUM
cana-729	212	23	)	)	PUNCT
cana-729	212	24	,	,	PUNCT
cana-729	212	25	comparing	compare	VERB
cana-729	212	26	machine	machine	NOUN
cana-729	212	27	-	-	PUNCT
cana-729	212	28	learning	learn	VERB
cana-729	212	29	models	model	NOUN
cana-729	212	30	for	for	ADP
cana-729	212	31	drought	drought	NOUN
cana-729	212	32	forecasting	forecasting	NOUN
cana-729	212	33	in	in	ADP
cana-729	212	34	vietnam	vietnam	PROPN
cana-729	212	35	’s	’s	PART
cana-729	212	36	cai	cai	PROPN
cana-729	212	37	river	river	PROPN
cana-729	212	38	basin	basin	PROPN
cana-729	212	39	,	,	PUNCT
cana-729	212	40	polish	polish	PROPN
cana-729	212	41	journal	journal	NOUN
cana-729	212	42	of	of	ADP
cana-729	212	43	environmental	environmental	ADJ
cana-729	212	44	studies	study	NOUN
cana-729	212	45	.	.	PUNCT
cana-729	213	1	27(6):2633–2646	27(6):2633–2646	X
cana-729	213	2	.	.	PUNCT
cana-729	214	1	[	[	X
cana-729	214	2	7	7	NUM
cana-729	214	3	]	]	X
cana-729	214	4	maity	maity	NOUN
cana-729	214	5	,	,	PUNCT
cana-729	214	6	r.	r.	PROPN
cana-729	214	7	,	,	PUNCT
cana-729	214	8	mohd	mohd	PROPN
cana-729	214	9	imran	imran	PROPN
cana-729	214	10	khan	khan	PROPN
cana-729	214	11	,	,	PUNCT
cana-729	214	12	subharthi	subharthi	PROPN
cana-729	214	13	sarkar	sarkar	PROPN
cana-729	214	14	,	,	PUNCT
cana-729	214	15	riya	riya	PROPN
cana-729	214	16	dutta	dutta	PROPN
cana-729	214	17	,	,	PUNCT
cana-729	214	18	subhra	subhra	PROPN
cana-729	214	19	sekhar	sekhar	PROPN
cana-729	214	20	maity	maity	PROPN
cana-729	214	21	,	,	PUNCT
cana-729	214	22	manali	manali	ADJ
cana-729	214	23	pal	pal	NOUN
cana-729	214	24	and	and	CCONJ
cana-729	214	25	kironmala	kironmala	PROPN
cana-729	214	26	chanda	chanda	PROPN
cana-729	214	27	(	(	PUNCT
cana-729	214	28	2021	2021	NUM
cana-729	214	29	)	)	PUNCT
cana-729	214	30	,	,	PUNCT
cana-729	214	31	potential	potential	NOUN
cana-729	214	32	of	of	ADP
cana-729	214	33	deep	deep	ADJ
cana-729	214	34	learning	learning	NOUN
cana-729	214	35	in	in	ADP
cana-729	214	36	drought	drought	NOUN
cana-729	214	37	assessment	assessment	NOUN
cana-729	214	38	by	by	ADP
cana-729	214	39	extracting	extract	VERB
cana-729	214	40	information	information	NOUN
cana-729	214	41	from	from	ADP
cana-729	214	42	hydrometeorological	hydrometeorological	ADJ
cana-729	214	43	precursors	precursor	NOUN
cana-729	214	44	,	,	PUNCT
cana-729	214	45	journal	journal	NOUN
cana-729	214	46	of	of	ADP
cana-729	214	47	water	water	NOUN
cana-729	214	48	and	and	CCONJ
cana-729	214	49	climate	climate	NOUN
cana-729	214	50	change	change	NOUN
cana-729	214	51	.	.	PUNCT
cana-729	215	1	12	12	NUM
cana-729	215	2	(	(	PUNCT
cana-729	215	3	6	6	NUM
cana-729	215	4	):	):	PUNCT
cana-729	215	5	2774–2796	2774–2796	NUM
cana-729	215	6	.	.	PUNCT
cana-729	216	1	[	[	X
cana-729	216	2	8	8	NUM
cana-729	216	3	]	]	X
cana-729	216	4	mohamadi	mohamadi	NOUN
cana-729	216	5	,	,	PUNCT
cana-729	216	6	s.	s.	PROPN
cana-729	216	7	,	,	PUNCT
cana-729	216	8	sammen	samman	NOUN
cana-729	216	9	,	,	PUNCT
cana-729	216	10	s.s	s.s	PROPN
cana-729	216	11	.	.	PROPN
cana-729	216	12	,	,	PUNCT
cana-729	216	13	panahi	panahi	PROPN
cana-729	216	14	,	,	PUNCT
cana-729	216	15	f.	f.	PROPN
cana-729	216	16	et	et	PROPN
cana-729	216	17	al	al	PROPN
cana-729	216	18	.	.	PROPN
cana-729	217	1	(	(	PUNCT
cana-729	217	2	2020	2020	NUM
cana-729	217	3	)	)	PUNCT
cana-729	217	4	zoning	zoning	NOUN
cana-729	217	5	map	map	NOUN
cana-729	217	6	for	for	ADP
cana-729	217	7	drought	drought	NOUN
cana-729	217	8	prediction	prediction	NOUN
cana-729	217	9	using	use	VERB
cana-729	217	10	integrated	integrated	ADJ
cana-729	217	11	machine	machine	NOUN
cana-729	217	12	learning	learning	NOUN
cana-729	217	13	models	model	NOUN
cana-729	217	14	with	with	ADP
cana-729	217	15	a	a	DET
cana-729	217	16	nomadic	nomadic	ADJ
cana-729	217	17	people	people	NOUN
cana-729	217	18	optimization	optimization	NOUN
cana-729	217	19	algorithm	algorithm	NOUN
cana-729	217	20	.	.	PUNCT
cana-729	218	1	nat	nat	PROPN
cana-729	218	2	hazards	hazard	VERB
cana-729	218	3	104	104	NUM
cana-729	218	4	,	,	PUNCT
cana-729	218	5	537–579	537–579	NUM
cana-729	218	6	.	.	PUNCT
cana-729	218	7	https://doi.org/10.1007/s11069-020-04180-9	https://doi.org/10.1007/s11069-020-04180-9	PUNCT
cana-729	219	1	[	[	X
cana-729	219	2	9	9	NUM
cana-729	219	3	]	]	SYM
cana-729	219	4	mokhtar	mokhtar	NOUN
cana-729	219	5	,	,	PUNCT
cana-729	219	6	a.et	a.et	PROPN
cana-729	219	7	al	al	PROPN
cana-729	219	8	.	.	PROPN
cana-729	219	9	(	(	PUNCT
cana-729	219	10	2021	2021	NUM
cana-729	219	11	)	)	PUNCT
cana-729	219	12	,	,	PUNCT
cana-729	219	13	estimation	estimation	NOUN
cana-729	219	14	of	of	ADP
cana-729	219	15	spei	spei	PROPN
cana-729	219	16	meteorological	meteorological	ADJ
cana-729	219	17	drought	drought	NOUN
cana-729	219	18	using	use	VERB
cana-729	219	19	machine	machine	NOUN
cana-729	219	20	learning	learning	NOUN
cana-729	219	21	algorithms	algorithm	NOUN
cana-729	219	22	,	,	PUNCT
cana-729	219	23	ieee	ieee	NOUN
cana-729	219	24	access	access	NOUN
cana-729	219	25	,	,	PUNCT
cana-729	219	26	9	9	NUM
cana-729	219	27	,	,	PUNCT
cana-729	219	28	65504	65504	NUM
cana-729	219	29	-	-	SYM
cana-729	219	30	65523	65523	NUM
cana-729	219	31	.	.	PUNCT
cana-729	220	1	[	[	X
cana-729	220	2	10	10	NUM
cana-729	220	3	]	]	X
cana-729	220	4	najeebullah	najeebullah	PROPN
cana-729	220	5	khan	khan	PROPN
cana-729	220	6	,	,	PUNCT
cana-729	220	7	d.a	d.a	PROPN
cana-729	220	8	.	.	PROPN
cana-729	220	9	sachindra	sachindra	PROPN
cana-729	220	10	,	,	PUNCT
cana-729	220	11	shamsuddin	shamsuddin	NOUN
cana-729	220	12	shahid	shahid	PROPN
cana-729	220	13	,	,	PUNCT
cana-729	220	14	kamal	kamal	PROPN
cana-729	220	15	ahmed	ahmed	PROPN
cana-729	220	16	,	,	PUNCT
cana-729	220	17	mohammed	mohammed	PROPN
cana-729	220	18	sanusi	sanusi	PROPN
cana-729	220	19	shiru	shiru	PROPN
cana-729	220	20	,	,	PUNCT
cana-729	220	21	nadeem	nadeem	PROPN
cana-729	220	22	nawaz,(2020	nawaz,(2020	PROPN
cana-729	220	23	)	)	PUNCT
cana-729	220	24	prediction	prediction	NOUN
cana-729	220	25	of	of	ADP
cana-729	220	26	droughts	drought	NOUN
cana-729	220	27	over	over	ADP
cana-729	220	28	pakistan	pakistan	PROPN
cana-729	220	29	using	use	VERB
cana-729	220	30	machine	machine	NOUN
cana-729	220	31	learning	learning	NOUN
cana-729	220	32	algorithms	algorithm	NOUN
cana-729	220	33	,	,	PUNCT
cana-729	220	34	advances	advance	NOUN
cana-729	220	35	in	in	ADP
cana-729	220	36	water	water	NOUN
cana-729	220	37	resources	resource	NOUN
cana-729	220	38	,	,	PUNCT
cana-729	220	39	139	139	NUM
cana-729	220	40	.	.	PUNCT
cana-729	220	41	communications	communication	NOUN
cana-729	220	42	on	on	ADP
cana-729	220	43	applied	apply	VERB
cana-729	220	44	nonlinear	nonlinear	ADJ
cana-729	220	45	analysis	analysis	NOUN
cana-729	220	46	issn	issn	NOUN
cana-729	220	47	:	:	PUNCT
cana-729	220	48	1074	1074	NUM
cana-729	220	49	-	-	PUNCT
cana-729	220	50	133x	133x	NUM
cana-729	220	51	vol	vol	NOUN
cana-729	220	52	31	31	NUM
cana-729	220	53	no	no	NOUN
cana-729	220	54	.	.	PUNCT
cana-729	221	1	3s	3s	NUM
cana-729	221	2	(	(	PUNCT
cana-729	221	3	2024	2024	NUM
cana-729	221	4	)	)	PUNCT
cana-729	221	5	42	42	NUM
cana-729	221	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-729	222	1	[	[	X
cana-729	222	2	11	11	NUM
cana-729	222	3	]	]	X
cana-729	222	4	barnard	barnard	PROPN
cana-729	222	5	,	,	PUNCT
cana-729	222	6	d.m	d.m	PROPN
cana-729	222	7	.	.	PROPN
cana-729	222	8	germino	germino	PROPN
cana-729	222	9	,	,	PUNCT
cana-729	222	10	m.j	m.j	PROPN
cana-729	222	11	.	.	PROPN
cana-729	222	12	bradford	bradford	PROPN
cana-729	222	13	,	,	PUNCT
cana-729	222	14	j.b	j.b	PROPN
cana-729	222	15	.	.	PROPN
cana-729	222	16	o’connor	o’connor	PROPN
cana-729	222	17	,	,	PUNCT
cana-729	222	18	r.c	r.c	PROPN
cana-729	222	19	.	.	PROPN
cana-729	222	20	andrews	andrews	PROPN
cana-729	222	21	,	,	PUNCT
cana-729	222	22	c.m	c.m	PROPN
cana-729	222	23	.	.	PROPN
cana-729	222	24	shriver	shriver	PROPN
cana-729	222	25	,	,	PUNCT
cana-729	222	26	r.k	r.k	PROPN
cana-729	222	27	.	.	PROPN
cana-729	222	28	,	,	PUNCT
cana-729	222	29	(	(	PUNCT
cana-729	222	30	2021	2021	NUM
cana-729	222	31	)	)	PUNCT
cana-729	222	32	are	be	AUX
cana-729	222	33	drought	drought	NOUN
cana-729	222	34	indices	index	NOUN
cana-729	222	35	and	and	CCONJ
cana-729	222	36	climate	climate	NOUN
cana-729	222	37	data	datum	NOUN
cana-729	222	38	good	good	ADJ
cana-729	222	39	indicators	indicator	NOUN
cana-729	222	40	of	of	ADP
cana-729	222	41	ecologically	ecologically	ADV
cana-729	222	42	relevant	relevant	ADJ
cana-729	222	43	soil	soil	NOUN
cana-729	222	44	moisture	moisture	NOUN
cana-729	222	45	dynamics	dynamic	NOUN
cana-729	222	46	in	in	ADP
cana-729	222	47	drylands	dryland	NOUN
cana-729	222	48	?	?	PUNCT
cana-729	223	1	ecol	ecol	NOUN
cana-729	223	2	.	.	PUNCT
cana-729	224	1	indic	indic	PROPN
cana-729	224	2	.	.	PUNCT
cana-729	224	3	,	,	PUNCT
cana-729	224	4	133	133	NUM
cana-729	224	5	,	,	PUNCT
cana-729	224	6	108379	108379	NUM
cana-729	224	7	.	.	PUNCT
cana-729	225	1	[	[	X
cana-729	225	2	12	12	NUM
cana-729	225	3	]	]	X
cana-729	225	4	shah	shah	NOUN
cana-729	225	5	,	,	PUNCT
cana-729	225	6	d.	d.	PROPN
cana-729	225	7	mishra	mishra	PROPN
cana-729	225	8	,	,	PUNCT
cana-729	225	9	v.	v.	PROPN
cana-729	225	10	,	,	PUNCT
cana-729	225	11	(	(	PUNCT
cana-729	225	12	2020	2020	NUM
cana-729	225	13	)	)	PUNCT
cana-729	225	14	integrated	integrate	VERB
cana-729	225	15	drought	drought	NOUN
cana-729	225	16	index	index	NOUN
cana-729	225	17	(	(	PUNCT
cana-729	225	18	idi	idi	PROPN
cana-729	225	19	)	)	PUNCT
cana-729	225	20	for	for	ADP
cana-729	225	21	drought	drought	NOUN
cana-729	225	22	monitoring	monitoring	NOUN
cana-729	225	23	and	and	CCONJ
cana-729	225	24	assessment	assessment	NOUN
cana-729	225	25	in	in	ADP
cana-729	225	26	india	india	PROPN
cana-729	225	27	.	.	PUNCT
cana-729	226	1	water	water	NOUN
cana-729	226	2	resour	resour	PROPN
cana-729	226	3	.	.	PUNCT
cana-729	227	1	res	re	NOUN
cana-729	227	2	.	.	PROPN
cana-729	227	3	,	,	PUNCT
cana-729	227	4	56	56	NUM
cana-729	227	5	,	,	PUNCT
cana-729	227	6	e2019wr026284	e2019wr026284	NUM
cana-729	227	7	.	.	PUNCT
cana-729	228	1	[	[	X
cana-729	228	2	13	13	NUM
cana-729	228	3	]	]	X
cana-729	228	4	dikshit	dikshit	PROPN
cana-729	228	5	,	,	PUNCT
cana-729	228	6	a.	a.	NOUN
cana-729	228	7	pradhan	pradhan	PROPN
cana-729	228	8	,	,	PUNCT
cana-729	228	9	b.	b.	PROPN
cana-729	228	10	santosh	santosh	PROPN
cana-729	228	11	,	,	PUNCT
cana-729	228	12	m.	m.	NOUN
cana-729	228	13	,	,	PUNCT
cana-729	228	14	(	(	PUNCT
cana-729	228	15	2022	2022	NUM
cana-729	228	16	)	)	PUNCT
cana-729	228	17	artificial	artificial	ADJ
cana-729	228	18	neural	neural	ADJ
cana-729	228	19	networks	network	NOUN
cana-729	228	20	in	in	ADP
cana-729	228	21	drought	drought	NOUN
cana-729	228	22	prediction	prediction	NOUN
cana-729	228	23	in	in	ADP
cana-729	228	24	the	the	DET
cana-729	228	25	21st	21st	ADJ
cana-729	228	26	century	century	NOUN
cana-729	228	27	—	—	PUNCT
cana-729	228	28	a	a	DET
cana-729	228	29	scientometric	scientometric	ADJ
cana-729	228	30	analysis	analysis	NOUN
cana-729	228	31	.	.	PUNCT
cana-729	229	1	appl	appl	PROPN
cana-729	229	2	.	.	PUNCT
cana-729	229	3	soft	soft	ADJ
cana-729	229	4	comput	comput	NOUN
cana-729	229	5	.	.	PUNCT
cana-729	229	6	,	,	PUNCT
cana-729	229	7	114	114	NUM
cana-729	229	8	,	,	PUNCT
cana-729	229	9	108080	108080	NUM
cana-729	229	10	.	.	PUNCT
cana-729	230	1	[	[	X
cana-729	230	2	14	14	NUM
cana-729	230	3	]	]	X
cana-729	230	4	sokhi	sokhi	PROPN
cana-729	230	5	,	,	PUNCT
cana-729	230	6	r.s	r.s	PROPN
cana-729	230	7	.	.	PROPN
cana-729	230	8	moussiopoulos	moussiopoulos	PROPN
cana-729	230	9	,	,	PUNCT
cana-729	230	10	n.	n.	PROPN
cana-729	230	11	baklanov	baklanov	PROPN
cana-729	230	12	,	,	PUNCT
cana-729	230	13	a.	a.	NOUN
cana-729	230	14	bartzis	bartzis	PROPN
cana-729	230	15	,	,	PUNCT
cana-729	230	16	j.	j.	PROPN
cana-729	230	17	,	,	PUNCT
cana-729	230	18	coll	coll	PROPN
cana-729	230	19	,	,	PUNCT
cana-729	230	20	i.	i.	PROPN
cana-729	230	21	finardi	finardi	PROPN
cana-729	230	22	,	,	PUNCT
cana-729	230	23	s.	s.	PROPN
cana-729	230	24	friedrich	friedrich	PROPN
cana-729	230	25	,	,	PUNCT
cana-729	230	26	r.	r.	PROPN
cana-729	230	27	geels	geels	PROPN
cana-729	230	28	,	,	PUNCT
cana-729	230	29	c.	c.	PROPN
cana-729	230	30	grönholm	grönholm	PROPN
cana-729	230	31	,	,	PUNCT
cana-729	230	32	t.	t.	PROPN
cana-729	230	33	halenka	halenka	NOUN
cana-729	230	34	,	,	PUNCT
cana-729	230	35	t.	t.	PROPN
cana-729	230	36	et	et	PROPN
cana-729	230	37	al	al	PROPN
cana-729	230	38	.	.	PROPN
cana-729	230	39	(	(	PUNCT
cana-729	230	40	2022	2022	NUM
cana-729	230	41	)	)	PUNCT
cana-729	230	42	advances	advance	NOUN
cana-729	230	43	in	in	ADP
cana-729	230	44	air	air	NOUN
cana-729	230	45	quality	quality	NOUN
cana-729	230	46	research	research	NOUN
cana-729	230	47	—	—	PUNCT
cana-729	230	48	current	current	ADJ
cana-729	230	49	and	and	CCONJ
cana-729	230	50	emerging	emerge	VERB
cana-729	230	51	challenges	challenge	NOUN
cana-729	230	52	.	.	PUNCT
cana-729	231	1	atmos	atmos	PROPN
cana-729	231	2	.	.	PUNCT
cana-729	231	3	chem	chem	PROPN
cana-729	231	4	.	.	PUNCT
cana-729	232	1	phys	phy	NOUN
cana-729	232	2	.	.	PUNCT
cana-729	232	3	,	,	PUNCT
cana-729	232	4	22	22	NUM
cana-729	232	5	,	,	PUNCT
cana-729	232	6	4615–4703	4615–4703	NUM
cana-729	232	7	.	.	PUNCT
cana-729	233	1	[	[	X
cana-729	233	2	15	15	NUM
cana-729	233	3	]	]	X
cana-729	233	4	haile	haile	NOUN
cana-729	233	5	,	,	PUNCT
cana-729	233	6	g.g	g.g	PROPN
cana-729	233	7	.	.	PROPN
cana-729	233	8	tang	tang	PROPN
cana-729	233	9	,	,	PUNCT
cana-729	233	10	q.	q.	PROPN
cana-729	233	11	li	li	PROPN
cana-729	233	12	,	,	PUNCT
cana-729	233	13	w.	w.	PROPN
cana-729	233	14	liu	liu	PROPN
cana-729	233	15	,	,	PUNCT
cana-729	233	16	x.	x.	PROPN
cana-729	233	17	zhang	zhang	PROPN
cana-729	233	18	,	,	PUNCT
cana-729	233	19	x.	x.	PROPN
cana-729	233	20	(	(	PUNCT
cana-729	233	21	2020	2020	NUM
cana-729	233	22	)	)	PUNCT
cana-729	233	23	drought	drought	NOUN
cana-729	233	24	:	:	PUNCT
cana-729	233	25	progress	progress	NOUN
cana-729	233	26	in	in	ADP
cana-729	233	27	broadening	broaden	VERB
cana-729	233	28	its	its	PRON
cana-729	233	29	understanding	understanding	NOUN
cana-729	233	30	.	.	PUNCT
cana-729	234	1	wiley	wiley	PROPN
cana-729	234	2	interdiscip	interdiscip	NOUN
cana-729	234	3	.	.	PUNCT
cana-729	235	1	rev	rev	PROPN
cana-729	235	2	.	.	PROPN
cana-729	235	3	water	water	NOUN
cana-729	235	4	,	,	PUNCT
cana-729	235	5	7	7	NUM
cana-729	235	6	,	,	PUNCT
cana-729	235	7	e1407	e1407	NOUN
cana-729	235	8	.	.	PUNCT
cana-729	236	1	[	[	X
cana-729	236	2	16	16	NUM
cana-729	236	3	]	]	X
cana-729	236	4	sivakumar	sivakumar	PROPN
cana-729	236	5	,	,	PUNCT
cana-729	236	6	v.l	v.l	PROPN
cana-729	236	7	.	.	PROPN
cana-729	236	8	krishnappa	krishnappa	PROPN
cana-729	236	9	,	,	PUNCT
cana-729	236	10	r.r	r.r	PROPN
cana-729	236	11	.	.	PROPN
cana-729	236	12	nallanathel	nallanathel	PROPN
cana-729	236	13	,	,	PUNCT
cana-729	236	14	m.	m.	NOUN
cana-729	236	15	(	(	PUNCT
cana-729	236	16	2021	2021	NUM
cana-729	236	17	)	)	PUNCT
cana-729	236	18	drought	drought	NOUN
cana-729	236	19	vulnerability	vulnerability	NOUN
cana-729	236	20	assessment	assessment	NOUN
cana-729	236	21	and	and	CCONJ
cana-729	236	22	mapping	mapping	NOUN
cana-729	236	23	using	use	VERB
cana-729	236	24	multi	multi	ADJ
cana-729	236	25	-	-	ADJ
cana-729	236	26	criteria	criterion	NOUN
cana-729	236	27	decision	decision	NOUN
cana-729	236	28	making	making	NOUN
cana-729	236	29	(	(	PUNCT
cana-729	236	30	mcdm	mcdm	ADJ
cana-729	236	31	)	)	PUNCT
cana-729	236	32	and	and	CCONJ
cana-729	236	33	application	application	NOUN
cana-729	236	34	of	of	ADP
cana-729	236	35	analytic	analytic	ADJ
cana-729	236	36	hierarchy	hierarchy	NOUN
cana-729	236	37	process	process	NOUN
cana-729	236	38	(	(	PUNCT
cana-729	236	39	ahp	ahp	NOUN
cana-729	236	40	)	)	PUNCT
cana-729	236	41	for	for	ADP
cana-729	236	42	namakkal	namakkal	ADJ
cana-729	236	43	district	district	NOUN
cana-729	236	44	,	,	PUNCT
cana-729	236	45	tamilnadu	tamilnadu	PROPN
cana-729	236	46	,	,	PUNCT
cana-729	236	47	india	india	PROPN
cana-729	236	48	.	.	PUNCT
cana-729	236	49	mater	mater	PROPN
cana-729	236	50	.	.	PUNCT
cana-729	236	51	today	today	NOUN
cana-729	236	52	proc	proc	PROPN
cana-729	236	53	.	.	PROPN
cana-729	236	54	,	,	PUNCT
cana-729	236	55	43	43	NUM
cana-729	236	56	,	,	PUNCT
cana-729	236	57	1592–1599	1592–1599	NUM
cana-729	236	58	.	.	PUNCT
cana-729	237	1	[	[	X
cana-729	237	2	17	17	NUM
cana-729	237	3	]	]	X
cana-729	237	4	alharbi	alharbi	PROPN
cana-729	237	5	,	,	PUNCT
cana-729	237	6	r.s	r.s	PROPN
cana-729	237	7	.	.	PROPN
cana-729	237	8	nath	nath	PROPN
cana-729	237	9	,	,	PUNCT
cana-729	237	10	s.	s.	PROPN
cana-729	237	11	faizan	faizan	PROPN
cana-729	237	12	,	,	PUNCT
cana-729	237	13	o.m	o.m	PROPN
cana-729	237	14	.	.	PUNCT
cana-729	237	15	hasan	hasan	PROPN
cana-729	237	16	,	,	PUNCT
cana-729	237	17	m.s.u	m.s.u	NOUN
cana-729	237	18	.	.	PUNCT
cana-729	237	19	alam	alam	PROPN
cana-729	237	20	,	,	PUNCT
cana-729	237	21	s.	s.	PROPN
cana-729	237	22	khan	khan	PROPN
cana-729	237	23	,	,	PUNCT
cana-729	237	24	m.a	m.a	PROPN
cana-729	237	25	.	.	PROPN
cana-729	237	26	bakshi	bakshi	PROPN
cana-729	237	27	,	,	PUNCT
cana-729	237	28	s.	s.	PROPN
cana-729	237	29	sahana	sahana	PROPN
cana-729	237	30	,	,	PUNCT
cana-729	237	31	m.	m.	NOUN
cana-729	237	32	saif	saif	PROPN
cana-729	237	33	,	,	PUNCT
cana-729	237	34	m.m	m.m	PROPN
cana-729	237	35	.	.	PROPN
cana-729	237	36	(	(	PUNCT
cana-729	237	37	2022	2022	NUM
cana-729	237	38	)	)	PUNCT
cana-729	237	39	assessment	assessment	NOUN
cana-729	237	40	of	of	ADP
cana-729	237	41	drought	drought	NOUN
cana-729	237	42	vulnerability	vulnerability	NOUN
cana-729	237	43	through	through	ADP
cana-729	237	44	an	an	DET
cana-729	237	45	integrated	integrated	ADJ
cana-729	237	46	approach	approach	NOUN
cana-729	237	47	using	use	VERB
cana-729	237	48	ahp	ahp	PROPN
cana-729	237	49	and	and	CCONJ
cana-729	237	50	geoinformatics	geoinformatic	NOUN
cana-729	237	51	in	in	ADP
cana-729	237	52	the	the	DET
cana-729	237	53	kangsabati	kangsabati	PROPN
cana-729	237	54	river	river	PROPN
cana-729	237	55	basin	basin	NOUN
cana-729	237	56	.	.	PUNCT
cana-729	238	1	j.	j.	PROPN
cana-729	238	2	king	king	PROPN
cana-729	238	3	saud	saud	VERB
cana-729	238	4	univ.-sci	univ.-sci	PRON
cana-729	238	5	.	.	PUNCT
cana-729	239	1	,	,	PUNCT
cana-729	239	2	34	34	NUM
cana-729	239	3	,	,	PUNCT
cana-729	239	4	102332	102332	NUM
cana-729	239	5	.	.	PUNCT
cana-729	240	1	[	[	X
cana-729	240	2	18	18	NUM
cana-729	240	3	]	]	PUNCT
cana-729	240	4	alkhalidi	alkhalidi	PROPN
cana-729	240	5	,	,	PUNCT
cana-729	240	6	a.	a.	PROPN
cana-729	240	7	assaf	assaf	PROPN
cana-729	240	8	,	,	PUNCT
cana-729	240	9	m.n	m.n	PROPN
cana-729	240	10	.	.	PROPN
cana-729	240	11	alkaylani	alkaylani	PROPN
cana-729	240	12	,	,	PUNCT
cana-729	240	13	h.	h.	PROPN
cana-729	240	14	halaweh	halaweh	PROPN
cana-729	240	15	,	,	PUNCT
cana-729	240	16	g.	g.	PROPN
cana-729	240	17	salcedo	salcedo	PROPN
cana-729	240	18	,	,	PUNCT
cana-729	240	19	f.p	f.p	PROPN
cana-729	240	20	.	.	PROPN
cana-729	240	21	(	(	PUNCT
cana-729	240	22	2023	2023	NUM
cana-729	240	23	)	)	PUNCT
cana-729	240	24	integrated	integrate	VERB
cana-729	240	25	innovative	innovative	ADJ
cana-729	240	26	technique	technique	NOUN
cana-729	240	27	to	to	PART
cana-729	240	28	assess	assess	VERB
cana-729	240	29	and	and	CCONJ
cana-729	240	30	priorities	prioritie	VERB
cana-729	240	31	risks	risk	NOUN
cana-729	240	32	associated	associate	VERB
cana-729	240	33	with	with	ADP
cana-729	240	34	drought	drought	NOUN
cana-729	240	35	:	:	PUNCT
cana-729	240	36	impacts	impact	NOUN
cana-729	240	37	,	,	PUNCT
cana-729	240	38	measures	measure	NOUN
cana-729	240	39	/	/	SYM
cana-729	240	40	strategies	strategy	NOUN
cana-729	240	41	,	,	PUNCT
cana-729	240	42	and	and	CCONJ
cana-729	240	43	actions	action	NOUN
cana-729	240	44	,	,	PUNCT
cana-729	240	45	global	global	ADJ
cana-729	240	46	study	study	NOUN
cana-729	240	47	.	.	PUNCT
cana-729	241	1	int	int	NOUN
cana-729	241	2	.	.	PUNCT
cana-729	242	1	j.	j.	PROPN
cana-729	242	2	disaster	disaster	PROPN
cana-729	242	3	risk	risk	NOUN
cana-729	242	4	reduct	reduct	PROPN
cana-729	242	5	.	.	PUNCT
cana-729	242	6	,	,	PUNCT
cana-729	242	7	94	94	NUM
cana-729	242	8	,	,	PUNCT
cana-729	242	9	103800	103800	NUM
cana-729	242	10	.	.	PUNCT
cana-729	243	1	[	[	X
cana-729	243	2	19	19	NUM
cana-729	243	3	]	]	X
cana-729	243	4	mujere	mujere	X
cana-729	243	5	,	,	PUNCT
cana-729	243	6	n.	n.	NOUN
cana-729	243	7	(	(	PUNCT
cana-729	243	8	2023	2023	NUM
cana-729	243	9	)	)	PUNCT
cana-729	243	10	assessing	assess	VERB
cana-729	243	11	risks	risk	NOUN
cana-729	243	12	and	and	CCONJ
cana-729	243	13	resilience	resilience	NOUN
cana-729	243	14	to	to	ADP
cana-729	243	15	hydro	hydro	NOUN
cana-729	243	16	-	-	PUNCT
cana-729	243	17	meteorological	meteorological	ADJ
cana-729	243	18	disasters	disaster	NOUN
cana-729	243	19	.	.	PUNCT
cana-729	244	1	in	in	ADP
cana-729	244	2	disaster	disaster	NOUN
cana-729	244	3	risk	risk	NOUN
cana-729	244	4	reduction	reduction	NOUN
cana-729	244	5	for	for	ADP
cana-729	244	6	resilience	resilience	NOUN
cana-729	244	7	:	:	PUNCT
cana-729	244	8	climate	climate	NOUN
cana-729	244	9	change	change	NOUN
cana-729	244	10	and	and	CCONJ
cana-729	244	11	disaster	disaster	NOUN
cana-729	244	12	risk	risk	NOUN
cana-729	244	13	adaptation	adaptation	NOUN
cana-729	244	14	;	;	PUNCT
cana-729	244	15	springer	springer	NOUN
cana-729	244	16	international	international	ADJ
cana-729	244	17	publishing	publishing	NOUN
cana-729	244	18	:	:	PUNCT
cana-729	244	19	cham	cham	PROPN
cana-729	244	20	,	,	PUNCT
cana-729	244	21	switzerland	switzerland	PROPN
cana-729	244	22	,	,	PUNCT
cana-729	244	23	143–159	143–159	NUM
cana-729	244	24	.	.	PUNCT
cana-729	245	1	[	[	X
cana-729	245	2	20	20	NUM
cana-729	245	3	]	]	SYM
cana-729	245	4	akturk	akturk	NOUN
cana-729	245	5	,	,	PUNCT
cana-729	245	6	g.	g.	PROPN
cana-729	245	7	zeybekoglu	zeybekoglu	PROPN
cana-729	245	8	,	,	PUNCT
cana-729	245	9	u.	u.	PROPN
cana-729	245	10	yildiz	yildiz	PROPN
cana-729	245	11	,	,	PUNCT
cana-729	245	12	o.(2022	o.(2022	PROPN
cana-729	245	13	)	)	PUNCT
cana-729	245	14	assessment	assessment	NOUN
cana-729	245	15	of	of	ADP
cana-729	245	16	meteorological	meteorological	ADJ
cana-729	245	17	drought	drought	NOUN
cana-729	245	18	analysis	analysis	NOUN
cana-729	245	19	in	in	ADP
cana-729	245	20	the	the	DET
cana-729	245	21	kizilirmak	kizilirmak	PROPN
cana-729	245	22	river	river	PROPN
cana-729	245	23	basin	basin	NOUN
cana-729	245	24	,	,	PUNCT
cana-729	245	25	turkey	turkey	PROPN
cana-729	245	26	.	.	PUNCT
cana-729	246	1	arab	arab	PROPN
cana-729	246	2	.	.	PUNCT
cana-729	247	1	j.	j.	PROPN
cana-729	247	2	geosci	geosci	PROPN
cana-729	247	3	.	.	PUNCT
cana-729	247	4	,	,	PUNCT
cana-729	247	5	15	15	NUM
cana-729	247	6	,	,	PUNCT
cana-729	247	7	850	850	NUM
cana-729	247	8	.	.	PUNCT
cana-729	248	1	[	[	X
cana-729	248	2	21	21	NUM
cana-729	248	3	]	]	X
cana-729	248	4	warter	warter	PROPN
cana-729	248	5	,	,	PUNCT
cana-729	248	6	m.m	m.m	PROPN
cana-729	248	7	.	.	PROPN
cana-729	248	8	singer	singer	PROPN
cana-729	248	9	,	,	PUNCT
cana-729	248	10	m.b	m.b	PROPN
cana-729	248	11	.	.	PROPN
cana-729	248	12	cuthbert	cuthbert	PROPN
cana-729	248	13	,	,	PUNCT
cana-729	248	14	m.o	m.o	PROPN
cana-729	248	15	.	.	PROPN
cana-729	248	16	roberts	roberts	PROPN
cana-729	248	17	,	,	PUNCT
cana-729	248	18	d.	d.	PROPN
cana-729	248	19	caylor	caylor	PROPN
cana-729	248	20	,	,	PUNCT
cana-729	248	21	k.k	k.k	PROPN
cana-729	248	22	.	.	PROPN
cana-729	248	23	sabathier	sabathier	PROPN
cana-729	248	24	,	,	PUNCT
cana-729	248	25	r.	r.	PROPN
cana-729	248	26	stella	stella	PROPN
cana-729	248	27	,	,	PUNCT
cana-729	248	28	j.(2021	j.(2021	NOUN
cana-729	248	29	)	)	PUNCT
cana-729	248	30	drought	drought	NOUN
cana-729	248	31	onset	onset	NOUN
cana-729	248	32	and	and	CCONJ
cana-729	248	33	propagation	propagation	NOUN
cana-729	248	34	into	into	ADP
cana-729	248	35	soil	soil	NOUN
cana-729	248	36	moisture	moisture	NOUN
cana-729	248	37	and	and	CCONJ
cana-729	248	38	grassland	grassland	NOUN
cana-729	248	39	vegetation	vegetation	NOUN
cana-729	248	40	responses	response	NOUN
cana-729	248	41	during	during	ADP
cana-729	248	42	the	the	DET
cana-729	248	43	2012–2019	2012–2019	NUM
cana-729	248	44	major	major	ADJ
cana-729	248	45	drought	drought	NOUN
cana-729	248	46	in	in	ADP
cana-729	248	47	southern	southern	PROPN
cana-729	248	48	california	california	PROPN
cana-729	248	49	.	.	PUNCT
cana-729	249	1	hydrol	hydrol	NOUN
cana-729	249	2	.	.	PUNCT
cana-729	250	1	earth	earth	PROPN
cana-729	250	2	syst	syst	PROPN
cana-729	250	3	.	.	PUNCT
cana-729	251	1	sci	sci	PROPN
cana-729	251	2	.	.	PROPN
cana-729	251	3	,	,	PUNCT
cana-729	251	4	25	25	NUM
cana-729	251	5	,	,	PUNCT
cana-729	251	6	3713–3729	3713–3729	NUM
cana-729	251	7	.	.	PUNCT
cana-729	252	1	[	[	X
cana-729	252	2	22	22	NUM
cana-729	252	3	]	]	SYM
cana-729	252	4	yao	yao	NOUN
cana-729	252	5	,	,	PUNCT
cana-729	252	6	y.	y.	PROPN
cana-729	252	7	liu	liu	PROPN
cana-729	252	8	,	,	PUNCT
cana-729	252	9	y.	y.	PROPN
cana-729	252	10	zhou	zhou	PROPN
cana-729	252	11	,	,	PUNCT
cana-729	252	12	s.	s.	PROPN
cana-729	252	13	song	song	PROPN
cana-729	252	14	,	,	PUNCT
cana-729	252	15	j.	j.	PROPN
cana-729	252	16	fu	fu	PROPN
cana-729	252	17	,	,	PUNCT
cana-729	252	18	b.	b.	PROPN
cana-729	252	19	(	(	PUNCT
cana-729	252	20	2023	2023	NUM
cana-729	252	21	)	)	PUNCT
cana-729	252	22	soil	soil	NOUN
cana-729	252	23	moisture	moisture	NOUN
cana-729	252	24	determines	determine	VERB
cana-729	252	25	the	the	DET
cana-729	252	26	recovery	recovery	NOUN
cana-729	252	27	time	time	NOUN
cana-729	252	28	of	of	ADP
cana-729	252	29	ecosystems	ecosystem	NOUN
cana-729	252	30	from	from	ADP
cana-729	252	31	drought	drought	NOUN
cana-729	252	32	.	.	PUNCT
cana-729	253	1	glob	glob	PROPN
cana-729	253	2	.	.	PUNCT
cana-729	254	1	chang	chang	PROPN
cana-729	254	2	.	.	PUNCT
cana-729	255	1	biol	biol	PROPN
cana-729	255	2	.	.	PUNCT
cana-729	255	3	,	,	PUNCT
cana-729	255	4	29	29	NUM
cana-729	255	5	,	,	PUNCT
cana-729	255	6	3562–3574	3562–3574	NUM
cana-729	255	7	.	.	PUNCT
cana-729	256	1	[	[	X
cana-729	256	2	23	23	NUM
cana-729	256	3	]	]	X
cana-729	256	4	satoh	satoh	NOUN
cana-729	256	5	,	,	PUNCT
cana-729	256	6	y.	y.	PROPN
cana-729	256	7	;	;	PUNCT
cana-729	256	8	yoshimura	yoshimura	NOUN
cana-729	256	9	,	,	PUNCT
cana-729	256	10	k.	k.	PROPN
cana-729	256	11	;	;	PUNCT
cana-729	256	12	pokhrel	pokhrel	NOUN
cana-729	256	13	,	,	PUNCT
cana-729	256	14	y.	y.	PROPN
cana-729	256	15	;	;	PUNCT
cana-729	256	16	kim	kim	PROPN
cana-729	256	17	,	,	PUNCT
cana-729	256	18	h.	h.	PROPN
cana-729	256	19	;	;	PUNCT
cana-729	256	20	shiogama	shiogama	PROPN
cana-729	256	21	,	,	PUNCT
cana-729	256	22	h.	h.	PROPN
cana-729	256	23	;	;	PUNCT
cana-729	256	24	yokohata	yokohata	PROPN
cana-729	256	25	,	,	PUNCT
cana-729	256	26	t.	t.	PROPN
cana-729	256	27	;	;	PUNCT
cana-729	256	28	hanasaki	hanasaki	PROPN
cana-729	256	29	,	,	PUNCT
cana-729	256	30	n.	n.	PROPN
cana-729	256	31	;	;	PUNCT
cana-729	256	32	wada	wada	PROPN
cana-729	256	33	,	,	PUNCT
cana-729	256	34	y.	y.	PROPN
cana-729	256	35	;	;	PUNCT
cana-729	256	36	burek	burek	PROPN
cana-729	256	37	,	,	PUNCT
cana-729	256	38	p.	p.	NOUN
cana-729	256	39	;	;	PUNCT
cana-729	256	40	byers	byer	NOUN
cana-729	256	41	,	,	PUNCT
cana-729	256	42	e.	e.	PROPN
cana-729	256	43	;	;	PUNCT
cana-729	256	44	et	et	PROPN
cana-729	256	45	al	al	PROPN
cana-729	256	46	.	.	PUNCT
cana-729	257	1	the	the	DET
cana-729	257	2	timing	timing	NOUN
cana-729	257	3	of	of	ADP
cana-729	257	4	unprecedented	unprecedented	ADJ
cana-729	257	5	hydrological	hydrological	ADJ
cana-729	257	6	drought	drought	NOUN
cana-729	257	7	under	under	ADP
cana-729	257	8	climate	climate	NOUN
cana-729	257	9	change	change	NOUN
cana-729	257	10	.	.	PUNCT
cana-729	258	1	nat	nat	PROPN
cana-729	258	2	.	.	PUNCT
cana-729	259	1	commun	commun	PROPN
cana-729	259	2	.	.	PUNCT
cana-729	260	1	2022	2022	NUM
cana-729	260	2	,	,	PUNCT
cana-729	260	3	13	13	NUM
cana-729	260	4	,	,	PUNCT
cana-729	260	5	3287	3287	NUM
cana-729	260	6	.	.	PUNCT
cana-729	261	1	[	[	X
cana-729	261	2	24	24	NUM
cana-729	261	3	]	]	SYM
cana-729	261	4	kumar	kumar	PROPN
cana-729	261	5	,	,	PUNCT
cana-729	261	6	p.	p.	PROPN
cana-729	261	7	;	;	PUNCT
cana-729	261	8	debele	debele	PROPN
cana-729	261	9	,	,	PUNCT
cana-729	261	10	s.e	s.e	PROPN
cana-729	261	11	.	.	PROPN
cana-729	261	12	;	;	PUNCT
cana-729	261	13	sahani	sahani	PROPN
cana-729	261	14	,	,	PUNCT
cana-729	261	15	j.	j.	PROPN
cana-729	261	16	;	;	PUNCT
cana-729	261	17	rawat	rawat	PROPN
cana-729	261	18	,	,	PUNCT
cana-729	261	19	n.	n.	PROPN
cana-729	261	20	;	;	PUNCT
cana-729	261	21	marti	marti	PROPN
cana-729	261	22	-	-	PUNCT
cana-729	261	23	cardona	cardona	PROPN
cana-729	261	24	,	,	PUNCT
cana-729	261	25	b.	b.	PROPN
cana-729	261	26	;	;	PUNCT
cana-729	261	27	alfieri	alfieri	PROPN
cana-729	261	28	,	,	PUNCT
cana-729	261	29	s.m	s.m	PROPN
cana-729	261	30	.	.	PROPN
cana-729	261	31	;	;	PUNCT
cana-729	261	32	basu	basu	PROPN
cana-729	261	33	,	,	PUNCT
cana-729	261	34	b.	b.	PROPN
cana-729	261	35	;	;	PUNCT
cana-729	261	36	basu	basu	PROPN
cana-729	261	37	,	,	PUNCT
cana-729	261	38	a.s	a.s	PROPN
cana-729	261	39	.	.	PROPN
cana-729	261	40	;	;	PUNCT
cana-729	261	41	bowyer	bowyer	PROPN
cana-729	261	42	,	,	PUNCT
cana-729	261	43	p.	p.	PROPN
cana-729	261	44	;	;	PUNCT
cana-729	261	45	charizopoulos	charizopoulos	PROPN
cana-729	261	46	,	,	PUNCT
cana-729	261	47	n.	n.	NOUN
cana-729	261	48	;	;	PUNCT
cana-729	261	49	et	et	PROPN
cana-729	261	50	al	al	PROPN
cana-729	261	51	.	.	PUNCT
cana-729	262	1	an	an	DET
cana-729	262	2	overview	overview	NOUN
cana-729	262	3	of	of	ADP
cana-729	262	4	monitoring	monitor	VERB
cana-729	262	5	methods	method	NOUN
cana-729	262	6	for	for	ADP
cana-729	262	7	assessing	assess	VERB
cana-729	262	8	the	the	DET
cana-729	262	9	performance	performance	NOUN
cana-729	262	10	of	of	ADP
cana-729	262	11	nature	nature	NOUN
cana-729	262	12	-	-	PUNCT
cana-729	262	13	based	base	VERB
cana-729	262	14	solutions	solution	NOUN
cana-729	262	15	against	against	ADP
cana-729	262	16	natural	natural	ADJ
cana-729	262	17	hazards	hazard	NOUN
cana-729	262	18	.	.	PUNCT
cana-729	263	1	earth	earth	NOUN
cana-729	263	2	-	-	PUNCT
cana-729	263	3	sci	sci	PROPN
cana-729	263	4	.	.	PUNCT
cana-729	263	5	rev	rev	PROPN
cana-729	263	6	.	.	PROPN
cana-729	263	7	2021	2021	NUM
cana-729	263	8	,	,	PUNCT
cana-729	263	9	217	217	NUM
cana-729	263	10	,	,	PUNCT
cana-729	263	11	103603	103603	NUM
cana-729	263	12	[	[	X
cana-729	263	13	25	25	NUM
cana-729	263	14	]	]	SYM
cana-729	263	15	wu	wu	PROPN
cana-729	263	16	,	,	PUNCT
cana-729	263	17	b.	b.	PROPN
cana-729	263	18	ma	ma	PROPN
cana-729	263	19	,	,	PUNCT
cana-729	263	20	z.	z.	PROPN
cana-729	263	21	yan	yan	PROPN
cana-729	263	22	,	,	PUNCT
cana-729	263	23	n.(2020	n.(2020	PROPN
cana-729	263	24	)	)	PUNCT
cana-729	263	25	agricultural	agricultural	ADJ
cana-729	263	26	drought	drought	NOUN
cana-729	263	27	mitigating	mitigating	NOUN
cana-729	263	28	indices	index	NOUN
cana-729	263	29	derived	derive	VERB
cana-729	263	30	from	from	ADP
cana-729	263	31	the	the	DET
cana-729	263	32	changes	change	NOUN
cana-729	263	33	in	in	ADP
cana-729	263	34	drought	drought	NOUN
cana-729	263	35	characteristics	characteristic	NOUN
cana-729	263	36	.	.	PUNCT
cana-729	264	1	remote	remote	PROPN
cana-729	264	2	sens	sens	PROPN
cana-729	264	3	.	.	PROPN
cana-729	264	4	environ	environ	PROPN
cana-729	264	5	.	.	PROPN
cana-729	264	6	,	,	PUNCT
cana-729	264	7	244	244	NUM
cana-729	264	8	,	,	PUNCT
cana-729	264	9	111813	111813	NUM
cana-729	264	10	.	.	PUNCT
cana-729	265	1	[	[	X
cana-729	265	2	26	26	NUM
cana-729	265	3	]	]	X
cana-729	265	4	kassahun	kassahun	PROPN
cana-729	265	5	,	,	PUNCT
cana-729	265	6	z.	z.	PROPN
cana-729	265	7	renninger	renninger	PROPN
cana-729	265	8	,	,	PUNCT
cana-729	265	9	h.j	h.j	PROPN
cana-729	265	10	.	.	PROPN
cana-729	265	11	(	(	PUNCT
cana-729	265	12	2021	2021	NUM
cana-729	265	13	)	)	PUNCT
cana-729	265	14	effects	effect	NOUN
cana-729	265	15	of	of	ADP
cana-729	265	16	drought	drought	NOUN
cana-729	265	17	on	on	ADP
cana-729	265	18	water	water	NOUN
cana-729	265	19	use	use	NOUN
cana-729	265	20	of	of	ADP
cana-729	265	21	seven	seven	NUM
cana-729	265	22	tree	tree	NOUN
cana-729	265	23	species	specie	NOUN
cana-729	265	24	from	from	ADP
cana-729	265	25	four	four	NUM
cana-729	265	26	genera	genera	NOUN
cana-729	265	27	growing	grow	VERB
cana-729	265	28	in	in	ADP
cana-729	265	29	a	a	DET
cana-729	265	30	bottomland	bottomland	NOUN
cana-729	265	31	hardwood	hardwood	NOUN
cana-729	265	32	forest	forest	NOUN
cana-729	265	33	.	.	PUNCT
cana-729	266	1	agric	agric	PROPN
cana-729	266	2	.	.	PUNCT
cana-729	267	1	for	for	ADP
cana-729	267	2	.	.	PUNCT
cana-729	267	3	meteorol	meteorol	NOUN
cana-729	267	4	.	.	PUNCT
cana-729	267	5	,	,	PUNCT
cana-729	267	6	301	301	NUM
cana-729	267	7	,	,	PUNCT
cana-729	267	8	108353	108353	NUM
cana-729	267	9	.	.	PUNCT
cana-729	268	1	[	[	X
cana-729	268	2	27	27	NUM
cana-729	268	3	]	]	X
cana-729	268	4	konapala	konapala	NOUN
cana-729	268	5	,	,	PUNCT
cana-729	268	6	g.	g.	PROPN
cana-729	268	7	mishra	mishra	PROPN
cana-729	268	8	,	,	PUNCT
cana-729	268	9	a.	a.	PROPN
cana-729	268	10	(	(	PUNCT
cana-729	268	11	2020	2020	NUM
cana-729	268	12	)	)	PUNCT
cana-729	268	13	quantifying	quantify	VERB
cana-729	268	14	climate	climate	NOUN
cana-729	268	15	and	and	CCONJ
cana-729	268	16	catchment	catchment	NOUN
cana-729	268	17	control	control	NOUN
cana-729	268	18	on	on	ADP
cana-729	268	19	hydrological	hydrological	ADJ
cana-729	268	20	drought	drought	NOUN
cana-729	268	21	in	in	ADP
cana-729	268	22	the	the	DET
cana-729	268	23	continental	continental	PROPN
cana-729	268	24	united	united	PROPN
cana-729	268	25	states	states	PROPN
cana-729	268	26	.	.	PUNCT
cana-729	269	1	water	water	NOUN
cana-729	269	2	resour	resour	NOUN
cana-729	269	3	.	.	PUNCT
cana-729	270	1	res	re	NOUN
cana-729	270	2	.	.	PROPN
cana-729	271	1	56	56	NUM
cana-729	271	2	,	,	PUNCT
cana-729	271	3	e2018wr024620	e2018wr024620	PROPN
cana-729	271	4	.	.	PUNCT
cana-729	272	1	[	[	X
cana-729	272	2	28	28	NUM
cana-729	272	3	]	]	X
cana-729	272	4	mukhawana	mukhawana	PROPN
cana-729	272	5	,	,	PUNCT
cana-729	272	6	m.b	m.b	PROPN
cana-729	272	7	.	.	PROPN
cana-729	272	8	kanyerere	kanyerere	PROPN
cana-729	272	9	,	,	PUNCT
cana-729	272	10	t.	t.	NOUN
cana-729	272	11	kahler	kahler	PROPN
cana-729	272	12	,	,	PUNCT
cana-729	272	13	d.	d.	PROPN
cana-729	272	14	(	(	PUNCT
cana-729	272	15	2023	2023	NUM
cana-729	272	16	)	)	PUNCT
cana-729	272	17	review	review	NOUN
cana-729	272	18	of	of	ADP
cana-729	272	19	in	in	ADP
cana-729	272	20	-	-	PUNCT
cana-729	272	21	situ	situ	NOUN
cana-729	272	22	and	and	CCONJ
cana-729	272	23	remote	remote	ADJ
cana-729	272	24	sensing	sensing	NOUN
cana-729	272	25	-	-	PUNCT
cana-729	272	26	based	base	VERB
cana-729	272	27	indices	index	NOUN
cana-729	272	28	and	and	CCONJ
cana-729	272	29	their	their	PRON
cana-729	272	30	applicability	applicability	NOUN
cana-729	272	31	for	for	ADP
cana-729	272	32	integrated	integrated	ADJ
cana-729	272	33	drought	drought	NOUN
cana-729	272	34	monitoring	monitoring	NOUN
cana-729	272	35	in	in	ADP
cana-729	272	36	south	south	PROPN
cana-729	272	37	africa	africa	PROPN
cana-729	272	38	.	.	PUNCT
cana-729	273	1	water	water	NOUN
cana-729	273	2	,	,	PUNCT
cana-729	273	3	15	15	NUM
cana-729	273	4	,	,	PUNCT
cana-729	273	5	240	240	NUM
cana-729	273	6	.	.	PUNCT
cana-729	274	1	[	[	X
cana-729	274	2	29	29	NUM
cana-729	274	3	]	]	X
cana-729	274	4	nicholson	nicholson	PROPN
cana-729	274	5	,	,	PUNCT
cana-729	274	6	c.c	c.c	PROPN
cana-729	274	7	.	.	PROPN
cana-729	274	8	egan	egan	PROPN
cana-729	274	9	,	,	PUNCT
cana-729	274	10	p.a	p.a	PROPN
cana-729	274	11	.	.	PROPN
cana-729	274	12	(	(	PUNCT
cana-729	274	13	2020	2020	NUM
cana-729	274	14	)	)	PUNCT
cana-729	274	15	natural	natural	ADJ
cana-729	274	16	hazard	hazard	NOUN
cana-729	274	17	threats	threat	NOUN
cana-729	274	18	to	to	ADP
cana-729	274	19	pollinators	pollinator	NOUN
cana-729	274	20	and	and	CCONJ
cana-729	274	21	pollination	pollination	NOUN
cana-729	274	22	.	.	PUNCT
cana-729	275	1	glob	glob	NOUN
cana-729	275	2	.	.	PUNCT
cana-729	276	1	chang	chang	PROPN
cana-729	276	2	.	.	PUNCT
cana-729	277	1	biol	biol	PROPN
cana-729	277	2	.	.	PUNCT
cana-729	277	3	,	,	PUNCT
cana-729	277	4	26	26	NUM
cana-729	277	5	,	,	PUNCT
cana-729	277	6	380–391	380–391	NUM
cana-729	277	7	.	.	PUNCT
cana-729	278	1	communications	communication	NOUN
cana-729	278	2	on	on	ADP
cana-729	278	3	applied	apply	VERB
cana-729	278	4	nonlinear	nonlinear	ADJ
cana-729	278	5	analysis	analysis	NOUN
cana-729	278	6	issn	issn	NOUN
cana-729	278	7	:	:	PUNCT
cana-729	278	8	1074	1074	NUM
cana-729	278	9	-	-	PUNCT
cana-729	278	10	133x	133x	NUM
cana-729	278	11	vol	vol	NOUN
cana-729	278	12	31	31	NUM
cana-729	278	13	no	no	NOUN
cana-729	278	14	.	.	PUNCT
cana-729	279	1	3s	3s	NUM
cana-729	279	2	(	(	PUNCT
cana-729	279	3	2024	2024	NUM
cana-729	279	4	)	)	PUNCT
cana-729	279	5	43	43	NUM
cana-729	279	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-729	280	1	[	[	X
cana-729	280	2	30	30	NUM
cana-729	280	3	]	]	X
cana-729	280	4	roy	roy	PROPN
cana-729	280	5	,	,	PUNCT
cana-729	280	6	p.	p.	PROPN
cana-729	280	7	pal	pal	NOUN
cana-729	280	8	,	,	PUNCT
cana-729	280	9	s.c	s.c	PROPN
cana-729	280	10	.	.	PROPN
cana-729	280	11	chakrabortty	chakrabortty	PROPN
cana-729	280	12	,	,	PUNCT
cana-729	280	13	r.	r.	PROPN
cana-729	280	14	chowdhuri	chowdhuri	PROPN
cana-729	280	15	,	,	PUNCT
cana-729	280	16	i.	i.	PROPN
cana-729	280	17	saha	saha	PROPN
cana-729	280	18	,	,	PUNCT
cana-729	280	19	a.	a.	NOUN
cana-729	280	20	shit	shit	PROPN
cana-729	280	21	,	,	PUNCT
cana-729	280	22	m.	m.	NOUN
cana-729	280	23	(	(	PUNCT
cana-729	280	24	2022	2022	NUM
cana-729	280	25	)	)	PUNCT
cana-729	280	26	climate	climate	NOUN
cana-729	280	27	change	change	NOUN
cana-729	280	28	and	and	CCONJ
cana-729	280	29	groundwater	groundwater	NOUN
cana-729	280	30	overdraft	overdraft	NOUN
cana-729	280	31	impacts	impact	NOUN
cana-729	280	32	on	on	ADP
cana-729	280	33	agricultural	agricultural	ADJ
cana-729	280	34	drought	drought	NOUN
cana-729	280	35	in	in	ADP
cana-729	280	36	india	india	PROPN
cana-729	280	37	:	:	PUNCT
cana-729	280	38	vulnerability	vulnerability	NOUN
cana-729	280	39	assessment	assessment	NOUN
cana-729	280	40	,	,	PUNCT
cana-729	280	41	food	food	NOUN
cana-729	280	42	security	security	NOUN
cana-729	280	43	measures	measure	NOUN
cana-729	280	44	and	and	CCONJ
cana-729	280	45	policy	policy	NOUN
cana-729	280	46	recommendation	recommendation	NOUN
cana-729	280	47	.	.	PUNCT
cana-729	281	1	sci	sci	PROPN
cana-729	281	2	.	.	PUNCT
cana-729	281	3	total	total	PROPN
cana-729	281	4	environ	environ	PROPN
cana-729	281	5	.	.	PROPN
cana-729	281	6	,	,	PUNCT
cana-729	281	7	849	849	NUM
cana-729	281	8	,	,	PUNCT
cana-729	281	9	157850	157850	NUM
cana-729	281	10	.	.	PUNCT
cana-729	282	1	[	[	X
cana-729	282	2	31	31	NUM
cana-729	282	3	]	]	X
cana-729	282	4	pal	pal	NOUN
cana-729	282	5	,	,	PUNCT
cana-729	282	6	s.c	s.c	PROPN
cana-729	282	7	.	.	PROPN
cana-729	282	8	chowdhuri	chowdhuri	PROPN
cana-729	282	9	,	,	PUNCT
cana-729	282	10	i.	i.	PROPN
cana-729	282	11	das	das	PROPN
cana-729	282	12	,	,	PUNCT
cana-729	282	13	b.	b.	PROPN
cana-729	282	14	chakrabortty	chakrabortty	PROPN
cana-729	282	15	,	,	PUNCT
cana-729	282	16	r.	r.	PROPN
cana-729	282	17	roy	roy	PROPN
cana-729	282	18	,	,	PUNCT
cana-729	282	19	p.	p.	PROPN
cana-729	282	20	saha	saha	PROPN
cana-729	282	21	,	,	PUNCT
cana-729	282	22	a.	a.	NOUN
cana-729	282	23	shit	shit	PROPN
cana-729	282	24	,	,	PUNCT
cana-729	282	25	m.	m.	NOUN
cana-729	282	26	(	(	PUNCT
cana-729	282	27	2022	2022	NUM
cana-729	282	28	)	)	PUNCT
cana-729	282	29	threats	threat	NOUN
cana-729	282	30	of	of	ADP
cana-729	282	31	climate	climate	NOUN
cana-729	282	32	change	change	NOUN
cana-729	282	33	and	and	CCONJ
cana-729	282	34	land	land	NOUN
cana-729	282	35	use	use	NOUN
cana-729	282	36	patterns	pattern	NOUN
cana-729	282	37	enhance	enhance	VERB
cana-729	282	38	the	the	DET
cana-729	282	39	susceptibility	susceptibility	NOUN
cana-729	282	40	of	of	ADP
cana-729	282	41	future	future	ADJ
cana-729	282	42	floods	flood	NOUN
cana-729	282	43	in	in	ADP
cana-729	282	44	india	india	PROPN
cana-729	282	45	.	.	PUNCT
cana-729	283	1	j.	j.	PROPN
cana-729	283	2	environ	environ	PROPN
cana-729	283	3	.	.	PROPN
cana-729	284	1	manag	manag	PROPN
cana-729	284	2	.	.	PROPN
cana-729	284	3	,	,	PUNCT
cana-729	284	4	305	305	NUM
cana-729	284	5	,	,	PUNCT
cana-729	284	6	114317	114317	NUM
cana-729	284	7	.	.	PUNCT
cana-729	285	1	[	[	X
cana-729	285	2	32	32	NUM
cana-729	285	3	]	]	SYM
cana-729	285	4	nageswararao	nageswararao	PROPN
cana-729	285	5	,	,	PUNCT
cana-729	285	6	m.m	m.m	PROPN
cana-729	285	7	.	.	PROPN
cana-729	285	8	,	,	PUNCT
cana-729	285	9	sinha	sinha	PROPN
cana-729	285	10	,	,	PUNCT
cana-729	285	11	p.	p.	PROPN
cana-729	285	12	,	,	PUNCT
cana-729	285	13	mohanty	mohanty	PROPN
cana-729	285	14	,	,	PUNCT
cana-729	285	15	u.c	u.c	PROPN
cana-729	285	16	.	.	PROPN
cana-729	285	17	,	,	PUNCT
cana-729	285	18	panda	panda	NOUN
cana-729	285	19	,	,	PUNCT
cana-729	285	20	r.k	r.k	PROPN
cana-729	285	21	.	.	PROPN
cana-729	285	22	,	,	PUNCT
cana-729	285	23	dash	dash	NOUN
cana-729	285	24	,	,	PUNCT
cana-729	285	25	g.p	g.p	PROPN
cana-729	285	26	.	.	PROPN
cana-729	285	27	,	,	PUNCT
cana-729	285	28	(	(	PUNCT
cana-729	285	29	2019	2019	NUM
cana-729	285	30	)	)	PUNCT
cana-729	285	31	evaluation	evaluation	NOUN
cana-729	285	32	of	of	ADP
cana-729	285	33	district	district	NOUN
cana-729	285	34	-	-	PUNCT
cana-729	285	35	level	level	NOUN
cana-729	285	36	rainfall	rainfall	NOUN
cana-729	285	37	characteristics	characteristic	NOUN
cana-729	285	38	over	over	ADP
cana-729	285	39	odisha	odisha	PROPN
cana-729	285	40	using	use	VERB
cana-729	285	41	high	high	ADJ
cana-729	285	42	-	-	PUNCT
cana-729	285	43	resolution	resolution	NOUN
cana-729	285	44	gridded	gridde	VERB
cana-729	285	45	dataset	dataset	NOUN
cana-729	285	46	(	(	PUNCT
cana-729	285	47	1901	1901	NUM
cana-729	285	48	-	-	SYM
cana-729	285	49	2013	2013	NUM
cana-729	285	50	)	)	PUNCT
cana-729	285	51	.	.	PUNCT
cana-729	286	1	sn	sn	PROPN
cana-729	286	2	applied	apply	VERB
cana-729	286	3	sciences	science	NOUN
cana-729	286	4	1	1	NUM
cana-729	286	5	,	,	PUNCT
cana-729	286	6	1211	1211	NUM
cana-729	286	7	.	.	PUNCT
cana-729	287	1	https://doi.org/10.1007/s42452019-1234-5	https://doi.org/10.1007/s42452019-1234-5	NOUN
cana-729	287	2	.	.	PUNCT
cana-729	288	1	[	[	X
cana-729	288	2	33	33	NUM
cana-729	288	3	]	]	X
cana-729	288	4	mishra	mishra	PROPN
cana-729	288	5	,	,	PUNCT
cana-729	288	6	m.	m.	NOUN
cana-729	288	7	,	,	PUNCT
cana-729	288	8	(	(	PUNCT
cana-729	288	9	2010	2010	NUM
cana-729	288	10	)	)	PUNCT
cana-729	288	11	integrating	integrate	VERB
cana-729	288	12	sustainable	sustainable	ADJ
cana-729	288	13	security	security	NOUN
cana-729	288	14	to	to	ADP
cana-729	288	15	integrated	integrate	VERB
cana-729	288	16	coastal	coastal	ADJ
cana-729	288	17	zone	zone	NOUN
cana-729	288	18	management	management	NOUN
cana-729	288	19	:	:	PUNCT
cana-729	288	20	a	a	DET
cana-729	288	21	case	case	NOUN
cana-729	288	22	study	study	NOUN
cana-729	288	23	of	of	ADP
cana-729	288	24	coastal	coastal	PROPN
cana-729	288	25	orissa	orissa	PROPN
cana-729	288	26	,	,	PUNCT
cana-729	288	27	india	india	PROPN
cana-729	288	28	.	.	PUNCT
cana-729	289	1	asian	asian	PROPN
cana-729	289	2	journal	journal	PROPN
cana-729	289	3	of	of	ADP
cana-729	289	4	environment	environment	NOUN
cana-729	289	5	and	and	CCONJ
cana-729	289	6	disaster	disaster	NOUN
cana-729	289	7	management	management	NOUN
cana-729	289	8	2	2	NUM
cana-729	289	9	(	(	PUNCT
cana-729	289	10	2	2	NUM
cana-729	289	11	)	)	PUNCT
cana-729	289	12	,	,	PUNCT
cana-729	289	13	209	209	NUM
cana-729	289	14	.	.	PUNCT
cana-729	290	1	https://doi.org/10.3850/s179392402010000232	https://doi.org/10.3850/s179392402010000232	X
cana-729	290	2	.	.	PUNCT
cana-729	291	1	[	[	X
cana-729	291	2	34	34	NUM
cana-729	291	3	]	]	X
cana-729	291	4	mishra	mishra	PROPN
cana-729	291	5	,	,	PUNCT
cana-729	291	6	m.	m.	NOUN
cana-729	291	7	,	,	PUNCT
cana-729	291	8	(	(	PUNCT
cana-729	291	9	2015	2015	NUM
cana-729	291	10	)	)	PUNCT
cana-729	291	11	analyzing	analyze	VERB
cana-729	291	12	the	the	DET
cana-729	291	13	dynamics	dynamic	NOUN
cana-729	291	14	of	of	ADP
cana-729	291	15	social	social	ADJ
cana-729	291	16	vulnerability	vulnerability	NOUN
cana-729	291	17	to	to	PART
cana-729	291	18	climate	climate	VERB
cana-729	291	19	induced	induce	VERB
cana-729	291	20	natural	natural	ADJ
cana-729	291	21	disasters	disaster	NOUN
cana-729	291	22	in	in	ADP
cana-729	291	23	orissa	orissa	PROPN
cana-729	291	24	,	,	PUNCT
cana-729	291	25	india	india	PROPN
cana-729	291	26	.	.	PUNCT
cana-729	291	27	int	int	PROPN
cana-729	291	28	.	.	PUNCT
cana-729	292	1	j.	j.	PROPN
cana-729	292	2	soc	soc	PROPN
cana-729	292	3	.	.	PUNCT
cana-729	293	1	sci	sci	PROPN
cana-729	293	2	.	.	PROPN
cana-729	293	3	4	4	NUM
cana-729	293	4	(	(	PUNCT
cana-729	293	5	2–3	2–3	NUM
cana-729	293	6	)	)	PUNCT
cana-729	293	7	,	,	PUNCT
cana-729	293	8	217	217	NUM
cana-729	293	9	.	.	PUNCT
cana-729	294	1	https://doi.org/10.5958/23215771.2015.00015.0	https://doi.org/10.5958/23215771.2015.00015.0	NOUN
cana-729	294	2	.	.	PUNCT
cana-729	295	1	[	[	X
cana-729	295	2	35	35	NUM
cana-729	295	3	]	]	X
cana-729	295	4	swain	swain	PROPN
cana-729	295	5	,	,	PUNCT
cana-729	295	6	m.	m.	NOUN
cana-729	295	7	,	,	PUNCT
cana-729	295	8	pattanayak	pattanayak	NOUN
cana-729	295	9	,	,	PUNCT
cana-729	295	10	s.	s.	PROPN
cana-729	295	11	,	,	PUNCT
cana-729	295	12	mohanty	mohanty	PROPN
cana-729	295	13	,	,	PUNCT
cana-729	295	14	u.c	u.c	PROPN
cana-729	295	15	.	.	PROPN
cana-729	295	16	,	,	PUNCT
cana-729	295	17	(	(	PUNCT
cana-729	295	18	2018	2018	NUM
cana-729	295	19	)	)	PUNCT
cana-729	295	20	characteristics	characteristic	NOUN
cana-729	295	21	of	of	ADP
cana-729	295	22	occurrence	occurrence	NOUN
cana-729	295	23	of	of	ADP
cana-729	295	24	heavy	heavy	ADJ
cana-729	295	25	rainfall	rainfall	NOUN
cana-729	295	26	events	event	NOUN
cana-729	295	27	over	over	ADP
cana-729	295	28	odisha	odisha	PROPN
cana-729	295	29	during	during	ADP
cana-729	295	30	summer	summer	NOUN
cana-729	295	31	monsoon	monsoon	NOUN
cana-729	295	32	season	season	NOUN
cana-729	295	33	.	.	PUNCT
cana-729	296	1	dynamics	dynamic	NOUN
cana-729	296	2	of	of	ADP
cana-729	296	3	atmospheres	atmosphere	NOUN
cana-729	296	4	and	and	CCONJ
cana-729	296	5	oceans	ocean	NOUN
cana-729	296	6	82	82	NUM
cana-729	296	7	,	,	PUNCT
cana-729	296	8	107–118	107–118	NUM
cana-729	296	9	.	.	PUNCT
cana-729	297	1	https://doi.org/10.1016/j.dynat	https://doi.org/10.1016/j.dynat	NOUN
cana-729	297	2	moce.2018.05.004	moce.2018.05.004	X
cana-729	297	3	.	.	PUNCT
cana-729	298	1	[	[	X
cana-729	298	2	36	36	NUM
cana-729	298	3	]	]	PUNCT
cana-729	298	4	panda	panda	NOUN
cana-729	298	5	,	,	PUNCT
cana-729	298	6	a.	a.	NOUN
cana-729	298	7	,	,	PUNCT
cana-729	298	8	(	(	PUNCT
cana-729	298	9	2017	2017	NUM
cana-729	298	10	)	)	PUNCT
cana-729	298	11	.	.	PUNCT
cana-729	299	1	vulnerability	vulnerability	NOUN
cana-729	299	2	to	to	PART
cana-729	299	3	climate	climate	NOUN
cana-729	299	4	variability	variability	NOUN
cana-729	299	5	and	and	CCONJ
cana-729	299	6	drought	drought	NOUN
cana-729	299	7	among	among	ADP
cana-729	299	8	small	small	ADJ
cana-729	299	9	and	and	CCONJ
cana-729	299	10	marginal	marginal	ADJ
cana-729	299	11	farmers	farmer	NOUN
cana-729	299	12	:	:	PUNCT
cana-729	299	13	a	a	DET
cana-729	299	14	case	case	NOUN
cana-729	299	15	study	study	NOUN
cana-729	299	16	in	in	ADP
cana-729	299	17	odisha	odisha	PROPN
cana-729	299	18	,	,	PUNCT
cana-729	299	19	india	india	PROPN
cana-729	299	20	.	.	PUNCT
cana-729	300	1	clim	clim	PROPN
cana-729	300	2	.	.	PUNCT
cana-729	301	1	dev	dev	PROPN
cana-729	301	2	.	.	PROPN
cana-729	301	3	9	9	NUM
cana-729	301	4	(	(	PUNCT
cana-729	301	5	7	7	NUM
cana-729	301	6	)	)	PUNCT
cana-729	301	7	,	,	PUNCT
cana-729	301	8	605–617	605–617	NUM
cana-729	301	9	.	.	PUNCT
cana-729	302	1	https://doi	https://doi	X
cana-729	302	2	.	.	PUNCT
cana-729	302	3	org/10.1080/17565529.2016.1184606	org/10.1080/17565529.2016.1184606	ADJ
cana-729	302	4	.	.	PUNCT
cana-729	303	1	[	[	X
cana-729	303	2	37	37	NUM
cana-729	303	3	]	]	PUNCT
cana-729	303	4	adarsh	adarsh	NOUN
cana-729	303	5	,	,	PUNCT
cana-729	303	6	s.	s.	PROPN
cana-729	303	7	,	,	PUNCT
cana-729	303	8	reddy	reddy	PROPN
cana-729	303	9	,	,	PUNCT
cana-729	303	10	j.m	j.m	PROPN
cana-729	303	11	.	.	PROPN
cana-729	303	12	,	,	PUNCT
cana-729	303	13	(	(	PUNCT
cana-729	303	14	2019	2019	NUM
cana-729	303	15	.	.	PUNCT
cana-729	303	16	)	)	PUNCT
cana-729	304	1	evaluation	evaluation	NOUN
cana-729	304	2	of	of	ADP
cana-729	304	3	trends	trend	NOUN
cana-729	304	4	and	and	CCONJ
cana-729	304	5	predictability	predictability	NOUN
cana-729	304	6	of	of	ADP
cana-729	304	7	short	short	ADJ
cana-729	304	8	-	-	PUNCT
cana-729	304	9	term	term	NOUN
cana-729	304	10	droughts	drought	NOUN
cana-729	304	11	in	in	ADP
cana-729	304	12	three	three	NUM
cana-729	304	13	meteorological	meteorological	ADJ
cana-729	304	14	subdivisions	subdivision	NOUN
cana-729	304	15	of	of	ADP
cana-729	304	16	india	india	PROPN
cana-729	304	17	using	use	VERB
cana-729	304	18	multivariate	multivariate	NOUN
cana-729	304	19	emdbased	emdbase	VERB
cana-729	304	20	hybrid	hybrid	ADJ
cana-729	304	21	modelling	modelling	NOUN
cana-729	304	22	.	.	PUNCT
cana-729	305	1	hydrol	hydrol	NOUN
cana-729	305	2	.	.	PUNCT
cana-729	306	1	process	process	NOUN
cana-729	306	2	.	.	PUNCT
cana-729	307	1	33	33	NUM
cana-729	307	2	,	,	PUNCT
cana-729	307	3	130	130	NUM
cana-729	307	4	–	–	PUNCT
cana-729	307	5	143	143	NUM
cana-729	307	6	.	.	PUNCT
cana-729	308	1	https://doi.org/10.1002/	https://doi.org/10.1002/	PROPN
cana-729	308	2	hyp.13316	hyp.13316	VERB
cana-729	308	3	.	.	PUNCT
cana-729	309	1	[	[	X
cana-729	309	2	38	38	NUM
cana-729	309	3	]	]	PUNCT
cana-729	309	4	samantaray	samantaray	NOUN
cana-729	309	5	,	,	PUNCT
cana-729	309	6	a.k	a.k	PROPN
cana-729	309	7	.	.	PROPN
cana-729	309	8	,	,	PUNCT
cana-729	309	9	singh	singh	PROPN
cana-729	309	10	,	,	PUNCT
cana-729	309	11	g.	g.	PROPN
cana-729	309	12	,	,	PUNCT
cana-729	309	13	ramadas	ramadas	PROPN
cana-729	309	14	,	,	PUNCT
cana-729	309	15	m.	m.	NOUN
cana-729	309	16	,	,	PUNCT
cana-729	309	17	panda	panda	NOUN
cana-729	309	18	,	,	PUNCT
cana-729	309	19	r.k	r.k	PROPN
cana-729	309	20	.	.	PROPN
cana-729	309	21	,	,	PUNCT
cana-729	309	22	(	(	PUNCT
cana-729	309	23	2019	2019	NUM
cana-729	309	24	)	)	PUNCT
cana-729	309	25	drought	drought	NOUN
cana-729	309	26	hotspot	hotspot	NOUN
cana-729	309	27	analysis	analysis	NOUN
cana-729	309	28	and	and	CCONJ
cana-729	309	29	risk	risk	NOUN
cana-729	309	30	assessment	assessment	NOUN
cana-729	309	31	using	use	VERB
cana-729	309	32	probabilistic	probabilistic	ADJ
cana-729	309	33	drought	drought	NOUN
cana-729	309	34	monitoring	monitoring	NOUN
cana-729	309	35	and	and	CCONJ
cana-729	309	36	severity	severity	NOUN
cana-729	309	37	–	–	PUNCT
cana-729	309	38	duration	duration	NOUN
cana-729	309	39	–	–	PUNCT
cana-729	309	40	frequency	frequency	NOUN
cana-729	309	41	analysis	analysis	NOUN
cana-729	309	42	.	.	PUNCT
cana-729	310	1	hydrol	hydrol	NOUN
cana-729	310	2	.	.	PUNCT
cana-729	311	1	process	process	NOUN
cana-729	311	2	.	.	PUNCT
cana-729	312	1	33	33	NUM
cana-729	312	2	,	,	PUNCT
cana-729	312	3	432–449	432–449	NUM
cana-729	312	4	.	.	PUNCT
cana-729	313	1	https://doi.org/10.1002/hyp.13337	https://doi.org/10.1002/hyp.13337	PROPN
cana-729	313	2	.	.	PUNCT
cana-729	314	1	[	[	X
cana-729	314	2	39	39	NUM
cana-729	314	3	]	]	X
cana-729	314	4	patel	patel	PROPN
cana-729	314	5	,	,	PUNCT
cana-729	314	6	s.k	s.k	PROPN
cana-729	314	7	.	.	PROPN
cana-729	314	8	,	,	PUNCT
cana-729	314	9	mathew	mathew	PROPN
cana-729	314	10	,	,	PUNCT
cana-729	314	11	b.	b.	PROPN
cana-729	314	12	,	,	PUNCT
cana-729	314	13	nanda	nanda	PROPN
cana-729	314	14	,	,	PUNCT
cana-729	314	15	a.	a.	NOUN
cana-729	314	16	,	,	PUNCT
cana-729	314	17	pati	pati	PROPN
cana-729	314	18	,	,	PUNCT
cana-729	314	19	s.	s.	PROPN
cana-729	314	20	,	,	PUNCT
cana-729	314	21	nayak	nayak	PROPN
cana-729	314	22	,	,	PUNCT
cana-729	314	23	h.	h.	PROPN
cana-729	314	24	,	,	PUNCT
cana-729	314	25	(	(	PUNCT
cana-729	314	26	2019	2019	NUM
cana-729	314	27	.	.	PUNCT
cana-729	315	1	a	a	DET
cana-729	315	2	review	review	NOUN
cana-729	315	3	on	on	ADP
cana-729	315	4	extreme	extreme	ADJ
cana-729	315	5	weather	weather	NOUN
cana-729	315	6	events	event	NOUN
cana-729	315	7	and	and	CCONJ
cana-729	315	8	livelihood	livelihood	NOUN
cana-729	315	9	in	in	ADP
cana-729	315	10	odisha	odisha	PROPN
cana-729	315	11	,	,	PUNCT
cana-729	315	12	india	india	PROPN
cana-729	315	13	.	.	PUNCT
cana-729	316	1	mausam	mausam	PROPN
cana-729	316	2	70	70	NUM
cana-729	316	3	(	(	PUNCT
cana-729	316	4	3	3	NUM
cana-729	316	5	)	)	PUNCT
cana-729	316	6	,	,	PUNCT
cana-729	316	7	551–560	551–560	NUM
cana-729	316	8	.	.	PROPN
cana-729	316	9	https://doi.org/	https://doi.org/	VERB
cana-729	316	10	10.1016	10.1016	NUM
cana-729	316	11	/	/	SYM
cana-729	316	12	j.ijdrr.2019.101436	j.ijdrr.2019.101436	NOUN
cana-729	316	13	.	.	PUNCT
cana-729	317	1	[	[	X
cana-729	317	2	40	40	NUM
cana-729	317	3	]	]	X
cana-729	317	4	sam	sam	PROPN
cana-729	317	5	,	,	PUNCT
cana-729	317	6	a.s	a.s	PROPN
cana-729	317	7	.	.	PROPN
cana-729	317	8	,	,	PUNCT
cana-729	317	9	padmaja	padmaja	PROPN
cana-729	317	10	,	,	PUNCT
cana-729	317	11	s.s	s.s	PROPN
cana-729	317	12	.	.	PROPN
cana-729	317	13	,	,	PUNCT
cana-729	317	14	kachele	kachele	PROPN
cana-729	317	15	,	,	PUNCT
cana-729	317	16	h.	h.	PROPN
cana-729	317	17	,	,	PUNCT
cana-729	317	18	kumar	kumar	PROPN
cana-729	317	19	,	,	PUNCT
cana-729	317	20	r.	r.	PROPN
cana-729	317	21	,	,	PUNCT
cana-729	317	22	mueller	mueller	PROPN
cana-729	317	23	,	,	PUNCT
cana-729	317	24	k.	k.	PROPN
cana-729	317	25	,	,	PUNCT
cana-729	317	26	(	(	PUNCT
cana-729	317	27	2020	2020	NUM
cana-729	317	28	.	.	PUNCT
cana-729	318	1	climate	climate	NOUN
cana-729	318	2	change	change	NOUN
cana-729	318	3	,	,	PUNCT
cana-729	318	4	drought	drought	NOUN
cana-729	318	5	and	and	CCONJ
cana-729	318	6	rural	rural	ADJ
cana-729	318	7	communities	community	NOUN
cana-729	318	8	:	:	PUNCT
cana-729	318	9	understanding	understand	VERB
cana-729	318	10	people	people	NOUN
cana-729	318	11	’s	’s	PART
cana-729	318	12	perceptions	perception	NOUN
cana-729	318	13	and	and	CCONJ
cana-729	318	14	adaptations	adaptation	NOUN
cana-729	318	15	in	in	ADP
cana-729	318	16	rural	rural	ADJ
cana-729	318	17	eastern	eastern	ADJ
cana-729	318	18	india	india	PROPN
cana-729	318	19	.	.	PUNCT
cana-729	319	1	international	international	ADJ
cana-729	319	2	journal	journal	PROPN
cana-729	319	3	of	of	ADP
cana-729	319	4	disaster	disaster	NOUN
cana-729	319	5	risk	risk	NOUN
cana-729	319	6	reduction	reduction	NOUN
cana-729	319	7	44	44	NUM
cana-729	319	8	,	,	PUNCT
cana-729	319	9	101436	101436	NUM
cana-729	319	10	.	.	PUNCT
cana-729	320	1	https://doi	https://doi	X
cana-729	320	2	.	.	PUNCT
cana-729	321	1	org/10.1016	org/10.1016	PROPN
cana-729	321	2	/	/	SYM
cana-729	321	3	j.ijdrr.2019.101436	j.ijdrr.2019.101436	NOUN
cana-729	321	4	.	.	PUNCT