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American Journal of  
Environment and Climate (AJEC)

Assessing the Climatic Influence on River in Bangladesh: in Perspective of  
Morphology and Discharge of  Surma River

Shetu Akter1, M. Farhad Howladar2*, Zia Ahmed1, Tayabur Rashid Chowdhury1, Shah Md. Shahnewaz Sayem1

Volume 1 Issue 1, Year 2022
ISSN: 2832-403X (Online)

DOI: https://doi.org/10.54536/ajec.v1i1.181
https://journals.e-palli.com/home/index.php/ajec

Article Information ABSTRACT

Received: March 11, 2022

Accepted: May 09, 2022

Published: May 11, 2022

Bangladesh is a region that is vulnerable to climate change. In this study, the influence of  
rainfall on river morphology and river discharges was investigated. The morphological 
analysis of  the Surma River was carried out using GIS. Rainfall of  Sylhet over 44 years 
(1972–2016) was analyzed. Annually 434.099 mm rainfall precipitated in Sylhet. The mean 
annual rainfall from 1972-to 2016 shows a little decreasing trend. 845.99 M3/s of  water 
was discharged on average from the Surma river annually. Over these 44 years, erosion and 
deposition show a very decreasing rate with a very steep slope. The sinuosity index of  the 
Surma River varies from 1.32 to 2.29. The total erosion is strongly related to annual mean 
rainfall (r=0.939), which greatly affects the total river erosion. 88% of  erosion depends on 
the annual mean rainfall (r2=0.88). The r between mean annual rainfall and total deposition 
is 0.919, which presents a very strong positive relationship. More than 80% of  the erosion 
can be explained by rainfall. According to the percentage of  r2, about 89.8% of  variables of  
deposition can be explained by rainfall if  other factors remain constant. The river deposition 
and erosion are very highly dependent on river discharge. The Surma river’s annual mean 
discharge and rainfall are strongly correlated (r = 0.69), which indicates that the discharge 
of  the Surma river is highly dependent on the surrounding area’s rainfall. To conclude, it can 
be noted that the Sylhet rainfall decreased from 1972 to 2016, which had affected the Surma 
river’s morphology directly due to climate change.

Keywords
Surma River, River morphology, 
Climate change, Discharge pattern, 
GIS, and RS.

1 Dept of  Geography and Environment, Shahjalal University of  Science and Technology, Sylhet-3114, Bangladesh.
2 Department of  Petroleum & Mining Engineering, Shahjalal University of  Science and Technology, Sylhet-3114, Bangladesh.
* Corresponding author’s e-mail: farhad-pme@sust.edu ; farhadpme@gmail.com

INTRODUCTION
The magnitude of  erosion and sediment yield is highly 
controlled by Climate (e.g., Hicks et al. ¬1996, Glade 
1998, 2011; Crozier 1997). In response to global warming, 
soil erosion rates are commonly expected to rise (e.g., 
Ministry of  the Environment (MfE),2008) through a 
number of  mechanisms, including improvements in 
(1) rainfall erosion, (2) slope stability of  soil water, (3) 
plant biomass, (4) wind and drought frequency, and (5) 
land use required to adapt to climate change. (Nearing 
et al. 2004; Crozier 2010). Due to climate change, the 
frequency and severity of  natural calamities (droughts, 
floods, storms, and cyclones) have been changed. (Fowler 
& Hennessey 1995;MfE,2008).Over the past centuries, 
human beings have had a multitude of  impacts on fluvial 
structures, either directly (such as dam and embankment 
construction) or indirectly (such as changes in the land 
cove) (Goudie, 2006). Climate change impact studies 
concentrate on changes in river discharge and aspects of  
its temporal variability and season for individual drainage 
basins (Howlader, 2021, Kundzewicz et al., 2007). There 
are still few global reports on the impact of  climate 
change on river flow regimes (e.g., Milly et al. 2002, Döll 
and Zhang 2010, Hirabayashi et al. 2008). The strength 
of  rainfall is a major factor in regulating phenomena such 
as floods, soil erosion levels, and mass movements (Sidle 
and Dhakal 2002). 
In their third Assessment Report, South Asia is declared 
the most significantly affected climate change area by 
IPCC (Chowdhury, 2021, McCarthy et al., 2001). Due 
to several socio-economic and hydro-geological factors, 

Bangladesh is the most vulnerable to climate-prone areas. 
The main reasons for its vulnerability are its geographical 
location in South Asia, its low-lying floodplain topography, 
and its intense climate is driven by monsoons resulting 
in severe water distribution. The population density of  
Bangladesh is also very high, leading to the occurrence 
of  poverty. The Bangladesh government has taken many 
steps to obtain sustainable development goals, but they 
face significant challenges in sustaining its development 
due to climate change (Ahmed and Haque, 2002). 
Bangladesh is on the list of  the world’s prominent climate 
change vulnerable countries (IPCC, 2007). 
In Asia, the impact of  global climate change is seen mostly 
in the hydrologic sector (Organization for Economic 
Co-operation and Development, 2003). Bangladesh’s 
rainfall pattern will change along with a steady increase 
in temperature due to climate change (IPCC, 2007). The 
overall objective of  this study is to analyze the impacts 
of  climatic change on the Surma River, analyzing its 
morphology and discharge with respect to rainfall.
The specific elements of  the objectives of  this research 
have been set as follows:

I. To identify the Morphological (Historical course, 
quantity of  accretion and deposition, the sinuosity index, 
width, length) change of  Surma river.

II. To analyze the impact of  climate change on river 
morphology and discharge of  Surma River.
Materials and methods
“Research methodology is a way to systematically solve 
the research problem” (Kothari, 2004). It comprises the 
steps and methods of  research that have been done and 

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applied. In short, a methodology is a study or description 
of  methods (Baskerville, 1991). Surma River in Sylhet 
District was the study area of  this research work. Surma 
River is the longest river in Bangladesh; it runs through 
the northeastern part of  Bangladesh (Rahman,2018). 
This is the cloudiest part of  Bangladesh (Rashid, 1991). 
The highest precipitation falls in this area; for this reason, 
this river is chosen to determine rainfall’s impact on its 
morphology and discharge (Akter, 2019). Two types of  
numeric data (mean discharge and rainfall) have been 

analyzed. To determine the relationship between the 
variables, the linear regression method is applied.
Description of  Study area
The Surma Basin, which covers the eastern parts of  
Bangladesh, is home to at least 8 million people, making 
it a populated geographical region of  Bangladesh. Surma 
Basin depends on these peoples for its household, 
industrial, and other purposes. Sylhet is a major 
metropolis located on the banks of  the Surma River in 
northeastern Surma River ascends like the Barak on the 

Khasi and Tripura
Naga-Manipur watershed’s southern slopes. The Barak 
splits up branches within the Assam district of  Cachhar 
in India. The northern department of  Surma flows west, 
after which to Sylhet town in the southwest. It flows 
beyond Sylhet to Sunamganj town northwest and west; 
from there southwest to Madna, where it meets the 

kushiyara, the Barak’s alternative branch. 
Climatic variable (rainfall) and River Discharge data 
collection
In this study, to find out the climatic trend, one variable 
of  climate, which is rainfall, was considered. But a fact is 
that from origin to meet up Kushiyara river in Ajmiriganj, 

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Surma river travel between Sylhet and Sunamganj, But in 
Sunamganj do not have any meteorological observation 
post, for this purpose only from Sylhet Station the 
climatic variables (rainfall) records accumulated. Daily 
discharge data at Sylhet station were collected from the 
Water Resources Planning Organization of  Bangladesh 

from 1972 to 2006, and observed discharge data in a 
certain interval from 2007 to 2016 have been analyzed 
here
Satellite images collection
This study is based on secondary data (river discharge, 
rainfall), and Landsat image was used as secondary data. 

Table 1: Details of  acquired Satellite Images
Spacecraft ID Sensor Id Acquisition Data Path/Row Resolution Cloud cover Image Quality
LANDSAT 1 MSS 1972-12-27 146/43 60 0.00 0
LANDSAT 2 MSS 1976-12-15 146/43 60 0.00 0
LANDSAT 3 MSS 1980-02-01 146/43 60 1.00 0
LANDSAT 5 TM 1988-11-10 136/43 30 1.00 9
LANDSAT 5 TM 1992-12-7 136/43 30 7.00 9
LANDSAT 5 TM 1996-01-30 136/43 30 0.00 9
LANDSAT 7 ETM 2000-11-17 136/43 30 0.00 9
LANDSAT 5 TM 2004-02-26 136/43 30 3.00 7
LANDSAT 5 TM 2008-11-17 136/43 30 0.00 9
LANDSAT 7 ETM 2012-02-22 136/43 30 1.00 9
LANDSAT 8 OLI-TIRS 2016-12-09 136/43 30 0.00 9

In order to assess the effect of  climate change on river 
morphology, eleven satellite images of  1972, 1976, 1980, 
1988, 1992, 1996, 2000, 2004, 2008, 2012, and 2016 were 
downloaded from the United States Geological Survey 
(USGS). The total time span was divided by a 4-year 
time interval. Satellite data of  the same time interval is 
quite impossible to acquire, so there is some lapse in 
the interval. Examples of  the Satellite images obtained 
are shown in table 1. A list of  steps is made to get an 
appropriate output. To correct the errors, Radiometric 
and Geometric corrections were done in many steps. The 
radiometric correction and atmospheric correction were 
performed for all the bands of  each image.
The correction procedure of  the Landsat 8 image is 
different from the correction procedure of  other Landsat 
images. The image was processed using the formula 
provided in the Landsat 8 handbook. 
Dark object Subtraction is a very simple image-based 
method of  atmospheric correction. ENVI 5 was used to 
do Dark object Subtraction.
The Normalized Difference Water Index (NDWI) 
method is a common approach to detecting water bodies. 
The following formula was used for the NDWI index. 
But the formula varies with Landsat sensor. For Landsat 
4 TM, the following formula was used for the NDWI 
index.

MNDWI means Modified Normalized Difference Water 
Index, where MIR is a middle infrared band, and Green 
presents the pixel value of  the green band.
The collected satellite images from USGS were subset 
using the shapefile of  the study area in ERDAS Imagine.

RESULT AND DISCUSSION
A sequence of  Landsat images of  four years intervals, 
including 1972, 1976, 1980, 1988, 1992, 1996, 2000, 
2004, 2008, 2012, and 2016 reveal the yearly erosion and 

deposition rate.
Erosion and deposition have occurred at different places 
in different periods. Table 2 represents the erosion and 
deposition scenario of  the Surma River. Over the period 
of  these 44 years in Surma, River deposition was higher 
than erosion. The highest deposition and erosion took 
place in the time interval 1980 to 1988. During these time 
intervals, the rainfall and river discharge were also very 
high (Table 2). 
In the period 1972 to 1976, total accretion was 828.813 
acres, and the accretion rate was 207.20 acres/year (table 
2). The total erosion was 681.1 acres, and the erosion rate 
was 170.27 acres/year (table 2). Land deposited more 
than the eroded, a total of  147.713 acres of  land added to 
the bank of  Surma River (table 2).
In the period 1976 to 1980, total accretion was 1276.87 
acres, and the accretion rate was 319.27 acres/year (table 
2). The total erosion was 680.56 acres, and the erosion rate 
was 170.14 acres/year. Land deposited quite worn, a total 
of  596.31 acres of  land superimposed within the bank 
of  Surma stream (table 2). This period of  the deposition 
was from 1972 to 1976 (table 2). The deposition rate was 
conjointly beyond erosion.
Due to the unavailable Landsat image from 1981 to 1987, 
1984 image could not get to go with a sequence of  4 years 
time interval. The image had taken in 1988 for analysis. 
In the period 1980 to 1988, total accretion was 2634.29 
acres, and the accretion rate was 329.28 acres/year (table 
2). The total erosion was 1873.61 acres, and the erosion 
rate was 234.2 acres/year (table 2). Land deposited more 
than eroded land; a total of  760.68 acres of  land was 
added to the bank of  the Surma River (table 2). A very 
high amount of  land was eroded and deposited in these 
eight years time intervals (table 2). 
Total accretion was 1084.23 acres, and the accretion rate 
was 271.05 acres/year from 1988 to 1992 (table 2). The 
total erosion was 774.29 acres, and the erosion rate was 

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193.57 acres/year (table 2). The land deposition was 
higher than erosion, with a total of  309.94 acres of  land 
added to the bank of  the Surma River (table 2).
In the period 1992 to 1996, total accretion was 964.35 
acres, and the accretion rate was 241.08 acres/year (table 
2). The total erosion was 486.29 acres, and the erosion 
rate was 121.57 acres/year. Land deposited more than 
eroded land; a total of  478.06 acres of  land was added to 
the bank of  the Surma River.
In the period 1996 to 2000, total accretion was 645.85 
acres, and the accretion rate was 161.46 acres/year (table 
2). The total erosion was 482.896 acres, and the erosion 

rate was 120.724 acres/year (table 2). Land deposited 
more than eroded land; a total of  162.95 acres of  land 
was added to the bank of  the Surma River (table 2).
In the period 2000 to 2004, total accretion was 304.062 
acres, and the accretion rate was 76.01 acres/year (table 
2). The total erosion was 292.8 acres, and the erosion rate 
was 73.2 acres/year (table 2). Land deposited more than 
eroded land; a total of  89.37 acres of  land was added to 
the bank of  the Surma River (table 2).
Twelve bends from the selected reach of  the Surma 
river were shown in the following figure 1, which are 
selected These river bends were selected on the basis 

Table 2: Erosion and deposition scenario of  Surma River from 1972 to 2016.
Period Accretion

rate
(Acres/year)

Total Accretion
(Acres

Erosion
Rate

(Acres/year)

Total
Erosion
(Acres)

Difference
(Acres)

1972-1976 207.20 828.813 170.27 681.1 147.713
1976-1980 319.27 1276.87 170.14 680.56 596.31
1980-1988 329.28 2634.29 234.2 1873.61 760.68
1988-1992 271.05 1084.23 193.57 774.29 309.94
1992-1996 241.08 964.35 121.57 486.29 478.06
1996-2000 161.46 645.85 120.724 482.896 162.95
2000-2004 76.01 304.062 73.2 292.8 11.26
2004-2008 66.98 267.934 44.64 178.56 89.37
2008-2012 38.17 152.7 25.76 103.05 49.65
2012-2016 26.89 107.98 19.07 76.287 31.69

Total 173.739 8267.079 117.3144 5629.443 2637.623
1972-2016 75.51 6457.34 24.4 4930.93 1526.41

Figure 1: Selected reach of  Surma River.

Figure 2: Erosion and Deposition inbend 1-12 from 1972-2016

of  the historical imagery of  Google Earth Pro and the 
reconnaissance survey. Surma River is the longest river in 
Bangladesh. From upstream to downstream, 12 bends are 
selected for the analysis. Significant changes took place 
along with these 12 selected reaches.
In the period 2004 to 2008, total accretion was 267.934 
acres, and the accretion rate was 66.98 acres/year (table 
2). The total erosion was 178.56 acres, and the erosion 
rate was 44.64 acres/year (table 2). Land deposited more 
than eroded land; a total of  89.37 acres of  land was added 
to the bank of  the Surma River (table 2).

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In the period 2004 to 2008, total accretion was 267.934 
acres, and the accretion rate was 66.98 acres/year (table 
2). The total erosion was 178.56 acres, and the erosion 
rate was 44.64 acres/year (table 2). Land deposited more 
than eroded land; a total of  89.37 acres of  land was added 
to the bank of  the Surma River (table 2).
In the period 2008 to 2012, total accretion was 152.7 
acres, and the accretion rate was 38.17 acres/year (table 
2). The total erosion was 103.05 acres, and the erosion 
rate was 25.76 acres/year (table 2). Land deposited more 
than eroded land; a total of  49.65 acres of  land was added 
to the bank of  the Surma River (table 2).
Total accretion was 107.98 acres, and the accretion rate 
was 26.89 acres/year in the time of  2012 to 2016 (table 
2). The total erosion was 76.287 acres, and the erosion 
rate was 19.07 acres/year (table 2). Land deposited more 
than an eroded total of  31.69 acres of  land added to the 
bank of  the Surma River (table 2).

Figure 3: Total Erosion and Deposition in Surma River 
from 1972-2016.

Figure 4: River width at a different location from 1972-
to 2016.

Figure 3 exhibits total Erosion and Deposition in the 
Surma River from 1972-to 2016. The erosion and 
deposition were higher from 1980-to 1988 (figure 3). 
Over these 44 years, erosion and deposition show a very 
decreasing rate with a very steep slope. The rainfall in 
Sylhet also shows a decreasing trend. The discharge of  
Surma River is showing a decreasing rate. The relationship 
of  river morphology with river discharge and rainfall will 
be discussed later in this paper.
Analysis of  channel widening in Surma River
The width of  each bend is the average width of  this 
corresponding bend. Figure 4 represents the width of  the 
Surma River at a different point from 1972 to 2016. The 
width of  the Surma River shows a decreasing trend over 
the period of  time. From 1972 to 1980, the river width 
was the highest (figure 4). After 1980 the river width 
started decreasing because of  the deposition of  sediment 
on the bank. The deposition of  the Surma River was 
much higher than erosion, which is caused by a decrease 
in the river width (table 2).
The maximum width of  the river was in 1972, and 
after that, the width fluctuated with increasing time. On 
average, the river width is higher in the middle stream 
than upstream, 130.71 m (figure 4). The average width 
downstream is 122.34 m. The lowest width found in 
Upstream is 116.75 m. Day by the Surma River width 
decreases.
Analysis of  sinuosity index of  Surma River
The river channel is straight when the sinuosity is less 

than 1.05; the river pattern is seen as sinuous when it is 
between 1.05 and 1.50and if  it is greater than 1.5, the 
river meander (Brice, 1984).
Surma River is a meandering river. The sinuosity of  the 
Surma River changes over time. The highest sinuosity 
found in 1976 which 2.29 (table 3). The sinuosity index 
of  the Surma River varies from 1.32 to 2.29. The highest 
sinuosity was found in bend eleven in 1976, which was 
2.3. the lowest sinuosity was found in bend two, which 
was 1.33.
After 1980 the sinuosity of  the Surma River started 
to decrease due to the cut off  in bend eleven and the 
straightening of  the river channel (figure  2). The river 
meander Surma River ups and down with time. In 1988, 
1996, and 2000 the river characteristics were sinuous 
(table 2). In the years 1976 and 1980, the river was 
meandering (table 3).
Table 3: Sinuosity Index of  Surma River from 1972 
and 2016.

Year Curvilinear 
length (m)

Linear 
length (m)

SI Characteristics

1972 142486.79 73,763.36 1.93 Meandering

1976 169607.01 73,820.26 2.29 Meandering

1980 152598.22 73,807.38 2.06 Meandering

1988 109227.30 73,320.26 1.49 Sinuous

1992 116288.03 73,057.34 1.59 Meandering

1996 100595 73,222.65 1.37 Sinuous

2000 96718.97 73,210.26 1.32 Sinuous

2004 114767.87 73,407.38 1.56 Meandering

2008 109227.30 73,232.65 1.5 Meandering

2012 121652.12 73,216.26 1.62 Meandering

2016 117767.87 73,817.38 1.59 Meandering

Patterns of  average Rainfall in Sylhet
Figure 5 shows the average rainfall from 1972-to 2016. 
Average rainfall in Sylhet decreased throughout the study 
period (figure 5). The rainfall pattern fluctuated over this 
period. More than 450 mm of  rainfall was precipitated 
at the beginning of  1972. Suddenly, the amount of  
rainfall increased with a moderate margin in the following 

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two years, above 550 mm. In the middle of  the study 
period (1975-1981), the amount of  rain fell moderately, 
and it continued. In Sylhet, the total rainfall increased 
moderately in the following four years (1988-1992) at a 
moderate rate.

Figure 5: Mean Annual Rainfall from 1972-2016

Figure 5: Scatter plotting of  mean annual rainfall and 
erosion.

Figure 6: Scatter plotting of  mean annual rainfall and 
deposition

In recent days, the rainfall in Sylhet decreased, causing 
many impacts on the environment and the economy. Due 
to this rainfall change, there must be some disorder in the 
discharge pattern of  the Surma River.
Effects of  Climate Change on river morphology
In the event of  climate change, when the quantity and 
seasonal distribution of  the water discharge increases, 
both sediment supply, and sediment transport are 
subject to change. Changes in the quantity of  water will 
induce changes in the discharge of  rivers; in particular, 
the likelihood of  serious hydrological events will 
increase. This may contribute to improvements in the 
river channels’ flooding, sedimentation, and sediment 
transport. It can be due to a lack of  physically grounded 
river channel structure and sediment transport models, 
leading to little faith in projections of  the effect of  climate 
change on river channels (IPCC, 2007). In addition, the 
estimation of  improvements in sediment transport shows 
a great reliance on the predicted greenhouse gas emission 
scenario. Below we analyzed the impact of  climate change 
on the Surma River.
Relation among annual mean rainfall, total erosion, 
and deposition in 1972-2016
Erosion is mainly caused due to the flowing water in the 
river. The fast river discharge erodes rocks and soil. When 
a vast amount of  rainfall drains in a certain area, the 
rainwater falls into the river, and the discharge increases. 
The water flow is highly dependent on the landslope, 
where the slope is very steep, and the water flows faster. 
The amount of  discharge in the river is another cause of  
river erosion; when the discharge is high, it flows very 
faster than when it is dry.
Table 4 represents the correlation of  mean rainfall, river 
erosion, and deposition from 1972-to 2016. The erosion 
of  the Surma river depends on annual mean rainfall 
(Table 4). The r between them is 0.939, indicating a very 
strong positive relationship and significance (table 4). It is 
shown from multiple r2 that 88% of  erosion is influenced 
by annual mean rainfall (Table 4). If  the rainfall increases, 
the erosion will increase; if  the rainfall decreases, the 
erosion will also decrease. 
The rainfall of  Sylhet highly influences the deposition in 
Surma River; the r between them is 0.919, which indicates 

a very strong positive relation (table 4). It is seen that r2 
square is 0.84, which means 84% of  deposition depends 
on the annual mean rainfall (Table 4). The river deposition 
is very highly dependent on river discharge. The higher 
amount of  rainfall increases the total river discharge. This 
leads to an increase in the erosion of  the river and the 
eroded sediments deposited in other parts of  the river.
Table 4: Correlation of  mean rainfall, river erosion and 
deposition in 1972-2016
Independent 

Variable
Dependent 

Variable
r-

value
P.E 
(r)

r2 r2 

in 
%

Signifi-
cance

Annual 
Mean 
Rainfall
(1972-2016)

Total 
Erosion
(1972-
2016)

0.939 0.025 0.88 88% Signifi-
cant

Annual 
Mean 
Rainfall
(1972-2016)

Total
Deposition
(1972-
2016)

0.919 0.035 0.84 84% Signifi-
cant

r= Coefficient of  correlation, P.E. = Probable Error, r2= 
Coefficient of  determination

Figure 5 exhibits a scatter plotting of  mean annual rainfall 
and erosion. The linear regression between rainfall and 
erosion shows a very meaningful result. Here, rainfall 
is considered a predictor or independent variable, while 
erosion is considered a dependent variable. The r2 value 
shows a very strong relationship between rainfall and 
erosion. More than 80% of  the erosion can be explained 
by rainfall. The regression coefficient reveals that a one-
unit change in rainfall may cause a change of  2.361unit 
of  erosion (figure 5). The intercept of  regression means 
that if  the change in rainfall remains constant, the erosion 
would be 216.7. The direction of  the trend line also shows 
a very strong positive relationship between these two 
variables. In short, it can be concluded that increasing (or 
decreasing) rainfall can cause increment (or decrement) 
in erosion.

To measure the association between deposition and rainfall, 
a linear regression model has been applied, considering 
rainfall as an independent variable and deposition as 

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the dependent variable. The value of  r2 reveals a very 
strong relationship between these two variables (figure 
6). According to the percentage of  r2, about 89.8% of  
the variables of  deposition can be explained by rainfall 
if  other factors remain constant. 89.8% of  deposition 
depends on rainfall (Table 4). Changes in rainfall impact 
the change in deposition proportionally. For example, 
one-unit increment (or decrement) of  rainfall can cause a 
5.921-unit decrement (or increment) in deposition (Table 
4). In short, rainfall and deposition are strongly related to 
each other.
Relation among annual mean Discharge, total 
erosion, and deposition in 1972-2016
Table 5 represents the correlation between mean discharge, 
river erosion, and deposition from 1972-to 2016. The 
Coefficient of  correlation r of  annual mean discharge and 
total erosion is 0.786, indicating a strong positive relation 
(table 5). Multiple r square is 0.617which means 61.7% 
of  erosion depends on the annual mean discharge. The 
total amount of  erosion is highly dependent on discharge. 
If  the discharge increases, the deposition amount will 
increase; if  the discharge decreases, the deposition will 
also decrease.
Table 5: Correlation of  mean discharge, river erosion 
and deposition in 1972-2016.
Independent 
Variable

Dependent 
Variable

r-
value

P.E 
(r)

r2 r2 

in 
%

Signifi-
cance

Annual 
Mean 
Rainfall
(1972-2016)

Total 
Erosion
(1972-
2016)

0.786 0.081 0.617 61.7% Signifi-
cant

Annual 
Mean 
Rainfall
(1972-2016)

Total
Deposition
(1972-
2016)

0.749 0.093 0.561 56.1% Signifi-
cant

r= Coefficient of  correlation, P.E. = Probable Error, r2= 
Coefficient of  determination

The r between mean annual discharge and total deposition 
is 0.749, presenting a very strong positive relation (table 5). 
Multiple r square is 0.561, meaning 56.1% of  deposition 
depends on the annual mean discharge (table 5). The 
relationship between deposition and discharge is very 
high. The river deposition is very highly dependent on 
river discharge. The higher amount of  rainfall increases 
the total river discharge. This leads to an increase in 
the deposition of  the river and the eroded sediments 
deposited in other parts of  the river.

CONCLUSION
At present, global climate change has become a huge 
issue of  concern. In the setting of  global climate change, 
the regional and local climate is additionally evolving. The 
climate in Northeastern parts of  Bangladesh is likewise 
evolving with time. This climate change is affecting the 
rivers. Both the river morphology and river discharge 
are altered due to climate change. Climate change affects 
river hydrology. 

The rainfall in Sylhet shows a decreasing rate, which alters 
the morphology of  the Surma River. The rainfall of  the 
study area can explain more than 80% of  river erosion 
and deposition. Both river erosion and deposition are 
strongly positively correlated with rainfall. The change 
in rainfall alters river discharge, leading to the change in 
river width, erosion, and deposition. 
From 1972 to 2016, the rainfall in Sylhet decreased, 
which altered the river discharge. The river discharge 
also lessened with the decline of  rainfall. More than 
55% of  river erosion and deposition can be explained 
by discharge. River discharge has a strong positive 
impact on river erosion and deposition. The diminishing 
discharge changed the river morphology. Reducing 
discharge lessened the river flow, which affected the river 
morphology. The erosion and deposition shrank with the 
decline of  discharge. The river width and sinuosity were 
also reduced. The river morphology is more correlated 
with rainfall than discharge.

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