52 © 2020 Adama Science & Technology University. All rights reserved Ethiopian Journal of Science and Sustainable Development e-ISSN 2663-3205 Volume 8 (1), 2021 Journal Home Page: www.ejssd.astu.edu.et ASTU Research Paper Morphometric Analysis and Prioritization of Sub-watersheds for Soil Erosion using Geomatics Technologies in Megech River Catchment, Lake Tana Basin, North Western Ethiopia Muralitharan Jothimani1,, Francis Lawrence2, Zerihun Dawit3 1Department of Geology, College of Natural Sciences, Arba Minch University, Arba Minch, Ethiopia 2Department of Applied Geology, Adama Science & Technology University, Adama, Ethiopia 3Department of Geology, College of Natural and Computational Sciences, University of Gondar, Gondar, Ethiopia Article Info Abstract Article History: Received 27 July 2020 Received in revised form 29 September 2020 Accepted 10 October 2020 Soil erosion is one of the most critical environmental problems in the sustainable development of agriculture and natural resources. Ethiopia is facing severe soil erosion problems. The present study was carried out in the Megech River catchment, Lake Tana Basin, North Western Ethiopia. The present study aims to identify the sensitive soil erosion-prone sub-watersheds in the Megech River catchment. ASTER-DEM (Advanced Space-borne Thermal Emission and Reflection), a 30 m spatial resolution digital elevation model (DEM), was used to delineate the sub-watersheds and drainage networks through spatial Analyst and ArcHydro extension of ESRI ArcGIS v10.6.1 software. The cloud-free optical satellite data got from Landsat-8 Operational Land Imager (OLI) has been used to update the drainage network of the present study area. The study area was divided into four sub-watersheds: WS-1, WS-2, WS-3, and WS-4. The primary, linear, and areal drainage morphometric parameters were calculated by applying the standard formula. Furthermore, the ranks were allocated to each drainage morphometric parameter of the four sub- watersheds based on their soil erosion proneness. The compound factor value was calculated for the sub-watersheds. The lower value of the compound factor has a high possibility of soil erosion and vice versa. The compound factor of the present study area's sub-watersheds is 2.33 (WS-1), 2.88 (WS-2), 2.11(WS-3), and 2.67 (WS-4). Based on the compound factor value, the present study area's sub-watersheds 3,1,4 and 4 were classified into very high, high, medium, and low priority sub-watersheds, respectively. Through morphometric drainage analysis, the sub- watershed-3 has been identified as a very high-priority ranked watershed in the present study. It needs immediate soil conservation measures for efficient watershed planning and management. Further, the present study shows the effectiveness of the drainage morphometric analysis using the satellite image and GIS techniques in prioritizing the sub-watersheds for soil resource conservation and management in the Megech River catchment, Lake Tana Basin, North Western Ethiopia. Keywords: Morphometric analysis Soil erosion Sub-watershed prioritization Geomatics Megech River Ethiopia 1. Introduction In Ethiopia, agricultural productivity and food security are facing problems due to land degradation resulting from soil erosion (Hurni 1993; Hengsdijk et al., 2005; Erkossa et al., 2015; Taguas et al., 2015;  Corresponding author, e-mail: muralitharangeo@gmail.com https://doi.org/10.20372/ejssdastu:v8.i1.2021.225 Fazzini et al., 2015; Keesstra et al., 2016; Nigussie et al., 2017; Mekuriaw et al., 2018). At present, the northwestern part of Ethiopia faces the highest soil erosion problems (Hurni et al., 2015). According to (Woldeamlak and http://www.ejssd.astu.edu/ https://doi.org/10.20372/ejssdastu:v8.i1.2021................ Jothimani et al. Ethiop.J.Sci.Sustain.Dev., Vol. 8 (1), 2021 53 Stroosnijder, 2003; Belay et al., 2014; Halefom and Teshome, 2019), soil erosion in Ethiopia is caused by deforestation and the growth of the urban area and rangeland. This continued soil erosion has led to soil loss, exposure of rock outcrops, soil nutrient depletion, agricultural productivity, and environmental degradation. By organizing the community for agricultural production, food security, population livelihood improvement, and alleviating environmental damage, the Ethiopian government facilitates soil conservation techniques and methods. (Tesfaye et al., 2014a, 2014b; Haregeweyn et al., 2015; Kebede, 2014; Teshome et al., 2016; Kawo and Shankar, 2018; Athick and Shankar, 2019; Shankar and Kawo, 2019). According to Amare et al. (2014) and Teshome et al. (2016), the following soil conservation structures, such as stone bunds, soil bunds, and percolation ditches, have been constructed in different parts of Ethiopia through community mobilization. Poitras et al. (2011) stated that deprived and inadequate data on soil erosion and stream flow lead to unreliable planning and inadequate project operation of soil conservation measures. There is a need for a scientific study to identify the soil erosion-prone area and further identify suitable soil erosion conservation structures. Hence, detailed hydrological and soil erosion proneness information is needed for sustainable development in soil conservation management practices of the region of interest. Watershed prioritization is a well-known scientific method for identifying soil erosion-prone areas, flood- prone areas, and suitable areas for groundwater exploration (Vittala et al., 2008; Magesh et al., 2011; Thomas et al., 2012). It is essential for comprehensive watershed development and improved soil management in arid and semi-arid regions to know the local drainage morphometry and their environmental implications (Sreedevi et al., 2009; Shankar et al. 2009; Gulavani et al., 2017; Everard et al., 2018). A drainage basin is an essential landscape of geomorphic and hydrologic structure. It is an elementary unit concerned with collecting the supply of water and sediments. It requires a drainage morphometric analysis for the watershed prioritization process and covers the mathematical quantification of the basin's diverse aspects (Clarke, 1966). Linear, shape, and relief features comprise numerous parameters like stream number, stream length, drainage density, circularity ratio, form factor, and relief ratio (Magesh and Chandrasekar, 2014). Horton (1945) introduced morphometric quantification first and explained the fundamental relation of drainage arrangements with the basin's hydrology. Later, several researchers have contributed to the development of methods of drainage morphometric analysis (Strahler 1957; Shreve 1966; Gregory and Walling, 1968; Ziemer, 1973; Breyer and Scott Snow, 1992; Al-sulaimi et al., 1997; Agarwal, 1998; Nag and Chakraborty, 2003; Reddy et al., 2004; Das and Mukherjee, 2005). In the past, watershed management studies needed the data associated elevation, slope, geology, soil data through topographic maps, and collection of the datasets mentioned above wanted extensive and tedious field surveys (Sreedevi et al., 2013). Nowadays, advanced remote sensing and GIS (geomatics) technologies made watershed management studies relatively easy with high precision. Geomatics technologies became a vital component in watershed management research (Subyani et al., 2010; Sangle and Yannawar, 2014; Kumar et al., 2018). Remote sensing provides high accurate terrain information and GIS technologies contributing advanced tools for analyzing the satellite data for the drainage morphometric investigations. Remote sensing and GIS method-based morphometric studies have been conducted in different parts of the world by the following researchers (Al-sulaimi et al., 1997; Subyani et al., 2010; Sehgal and Babar, 2013; Aouragh and Essahlaoui, 2014; Biswas et al., 2014; Pophare and Balpande, 2014; Martins and Gadiga, 2015; Osano, 2015; Kumar and Kshitij, 2017; Rawat et al., 2017; Yanina et al., 2017; Kumar et al., 2018; Jothimani et al., 2019 & 2020). Drainage morphometric studies are critical in hydrological investigations of the watersheds (Sreedevi et al., 2009), and it is also essential for the subsequent studies at the watershed level such as estimation of soil erosion proneness and flood susceptibility mapping (Bagyaraj and Gurugnanam, 2011; Altaf et al., 2014; Farhan and Anaba, 2016; Gopinath et al., 2016; Masoud 2016; Yogesh et al., 2016; Kandpal et al., 2017; Meshram and Sharma, 2017; Satheesh kumar and Venkateswaran 2018 Prabhakar et al., 2019; Prakash, 2019), estimation of groundwater potentialities (Jasmin and Mallikarjuna, 2013), estimation of surface water potential (Suresh and Jothimani et al. Ethiop.J.Sci.Sustain.Dev., Vol. 8 (1), 2021 54 Sudhakar 2004), to determine plant growth potential (Kadam et al., 2017), sediment yield (Altaf and Meraj, 2014), and site selection for groundwater recharge structure and soil protection in the basin (Rekha et al., 2011; Wani and Javed, 2013; Choudhari et al., 2018). With this background, the present study was conducted with the following specific objectives: (i) ASTER DEM coupled with GIS techniques were used to extract the drainage network, and the cloud-free optical satellite data such as: Landsat-8 Operational Land Imager (OLI) has been used to update the present's drainage network area. (ii) Calculation of the various drainage morphometric parameters using the standard formula of the Megech River's sub-watersheds, and (iii) To prioritize sub-watersheds using the compound factor method and rank the sub-watershed for protection, preparation, and administration of the soil resource in the present study area. There have been no such studies using this current method in the present study area, and hence, the current study is the leading of its kind in the present study area. 2. Materials and Methods 2.1. Study area In the present study, drainage morphometric analysis and prioritization has been carried out in the Megech River catchment, Lake Tana Basin. The Megech River catchment lies between latitudes 12°15′48′′ to 12°45′17′′ N and longitudes 37°21′31′′ to 37°36′56′′ E in northwestern Ethiopia is shown in Figure 1. The elevation ranges from 1781 to 2896 m above mean sea level. The Megech River catchment has a rough terrain with a slope ranging from 0° to 74° (Figure 2). It has an area of 560 km2 and forms a part of the Lake Tana Basin, and establishes one of the Blue Nile River source basins. According to EMS (2019), the average maximum temperature ranges between 18.4°C and 29.2°C, and the average minimum temperature is between 8.3°C and 13.1°C. As per the Ethiopian standard Agro-climate classification system, the Megech River catchment falls between Dega (cold and humid) and Woinedega (cool sub-humid) agro-climatic regions. The land use of the catchment is mostly agricultural, followed by woody and shrub lands. The Megech River instigates from the Semen Mountains and then flows to a southern course and ends into Lake Tana. It is one of the major rivers flowing into Lake Tana from the northern part of Ethiopia. The upper northern part of the Megech River catchment is characterized by a rugged mountainous, whereas the lower part, around Lake Tana, is characterized by flat low-lying land (WWDSE and TAHAL GROUP, 2008). The study area’s elevation and slope maps were prepared from the ASTER-DEM. Figure. 2 show the elevation map of the Megech watershed. The Megech watershed has a gentle slope to extremely steep slopes and the slope values ranging from 0° to 74°. According to the Ethiopian Geological Survey (GSE, 2011), the catchment area comprises upper basaltic lava flows, trachytes with different weathering natures, and lacustrine sediments. According to FAO (2006), the main soil types in the present study area are luvisols, regosols, vertisols, fluvisols, and cambisols. 2.2. Materials The following datasets/materials have been used in the present study, and the description of the data and its sources have been discussed in the following section. ASTER (Advanced Space-borne Thermal Emission and Reflection), 30 m resolution, and tile number (N12°E37o) were downloaded from the following website (https://search.earthdata.nasa.gov/search/). Moreover, it is used to delineate the sub-watersheds and drainage networks have done by using Spatial Analyst and Arc Hydro extension of ESRI ArcGIS v10.6.1. The cloud- free Landsat-8, Operational Land Imager (OLI) optical satellite data with path-row numbers 170-051, dated 22- February-2018, were downloaded from the United States Geological Survey (USGS) Global Visualization Viewer (GLOVIS) portal (http://earthexplorer.usgs.gov/). Furthermore, the same has been used to update the drainage network of the study area. 2.3. Extraction of drainage networks and demarcation of sub-watersheds boundaries The extraction of drainage networks and demarcation of the four sub-watersheds boundary were completed with ArcMap 10.6.1 coupled with ArcHydro tools using ASTER (DEM). The following DEM processing methods (fill sinks, flow direction, flow accumulation, stream definition, stream segmentation, and catchment https://search.earthdata.nasa.gov/ Jothimani et al. Ethiop.J.Sci.Sustain.Dev., Vol. 8 (1), 2021 55 grid delineation) were carried out to extract the drainage network and demarcate the sub-watershed’s boundary. The Megech River basin is divided into four sub- watersheds (WS-1, WS-2, WS-3, and WS-4). The Megech River catchment’s drainage network and sub- watershed boundaries are shown in Figure 3. Figure 1: Study area map Figure 2: Elevation and Slope map Jothimani et al. Ethiop.J.Sci.Sustain.Dev., Vol. 8 (1), 2021 56 Figure 3: Drainage network and sub-watershed boundary map 3. Results and Discussions The standard formula was used to calculate the following drainage morphometric parameters viz; area, perimeter, stream order, number of streams, and perimeter. These parameters were grouped into basic drainage morphometric parameters. Linear drainage morphometric parameters calculated include stream order (u), stream number (Nu), stream length (Lu), bifurcation ratio (Rb), mean stream length (Lsm), and stream length ratio (Rl). Areal drainage morphometric parameters calculated include drainage density (Dd), drainage frequency (Fs), circulatory ratio (Rc), form factor (Ff), elongation ratio (Re), and length of overland flow (Lg). Morphometric parameters and their corresponding standard formulae are shown in Table 1. 3.1. Linear morphometric parameters The first step in the drainage morphometric characterization of a river catchment is the description of stream order and stream order, as suggested by Strahler (1964) used for the present study area. Stream order always increases from upstream to downstream, Horton (1945). In the present study, fifth-order drainage order (Figure 3) attained for morphometric characterization. WS-1 and WS- 3 exhibit the Vth order drainage pattern; WS-2 and WS-4 exhibit IVth order. The study area exhibits the dendric drainage pattern and it is exhibiting the presence of the hard rock in the major part of the study area. The order-wise drainage numbers are shown in Table 2. A total of 5076 streams were recognized in the entire Megech River catchment. Of these, 49.37% (2506) are first-order, 21.45% (1089), second-order, 14.58% (740), third-order, 9.93% (504) fourth-order, and 4.67% (237) contain fifth-order streams. The total length of streams calculated in WS-1 is 247 km, 188 km in WS-2, 232 km in WS-3, and 104 km in WS-4. We give the results of stream orders in (Table 2). The mean stream length is a typical property connected to the drainage network and its related surface. The mean stream length (Lsm) was calculated by dividing the total stream length (Lu) of order ‘u’ by the total number of streams (Nu) of order ‘u’. The mean stream length (Lsm) calculated is 0.11 for WS-1, 0.15 for WS-2, 0.18 for WS-3, and 0.2 for WS-4. The stream length ratio (RL) was measured as the ratio of the mean stream length of one order to the next lower order of the stream segment. Stream length sections of individual of the successive orders of a basin tend to be a direct symmetrical series with stream length increasing towards higher streams (Horton, 1945). We give the stream length ratio calculated for each sub-watershed in Table 3. The bifurcation ratio (Rb) is the ratio of the number of streams of the given order “Nu” to the number of streams of higher-order “u+1”. The bifurcation ratio reveals the shape of the basin. An elongated basin is likely to have a high Rb, whereas a circular basin is likely to have a low Rb (Schumm, 1956). Thus, from the values of the bifurcation ratio, WS-4 exhibits an elongated shape, whereas SW- 2 is nearly circular. In the study, each sub-watershed bifurcation ratio was calculated, which varies from 1.83 in WS-1, 1.57 in WS- 2, 1.98 in WS-3, and 2.65 in WS-4 (Table 4). The mean bifurcation ratio (Rbm) is defined as the average of the bifurcation ratio of all orders. The basin length is an essential morphometric parameter of the drainage basin. The basin length is maximum in WS-3 and minimum in WS-2. The basin length varies from 24 km in WS-1, 21 km in WS-2, 25 km in WS-3, and 16 km in WS-4 (Table 4). Jothimani et al. Ethiop.J.Sci.Sustain.Dev., Vol. 8 (1), 2021 57 Table 1: Morphometric parameters with formulae S.No Morphometric parameters Formulae/definition References Linear morphometric parameters 1 Stream order (u) Hierarchical rank Strahler (1964) 2 Stream number (Nu) Total number of stream segments of the order ‘u’ Horton (1945) 3 Stream length (Lu) The total length of the stream segments of that particular order Horton (1945) 4 Bifurcation ratio (Rb) Rb = Nu/N(u+1) where Nu = total number of stream segments of the order ‘u’ and N(u+1) = number of stream segments of the next higher order Schumm (1956) 5 Mean bifurcation ratio (Rbm) Rbm=average of bifurcation ratios of all orders Strahler (1957) 6 Mean stream length (Lsm) Lsm = ΣLu/Nu where Lu = total length of the stream segments of the particular order Nu = total number of stream segments of the same order ‘u’ Horton (1932) 7 Stream length ratio (Rl) Rl = Lu/L(u−1) where Lu = the mean length of all stream segments of a given order (u) and L(u−1) = the mean length of all stream segments of one order less to given order (u) Horton (1945) 8 Basin length (Lb) 1.312*A 0:568 where, L=basin length (km), A=area of the basin (km2) Nooka et al. (2005) Areal morphometric parameters 9 Basin Perimeter (P) (km) GIS analysis Schumm (1956) 10 Drainage frequency (Df) Fs = ΣNu/A where Nu = total number of stream segments of the order ‘u’ and A = area of the watershed (km2) Horton (1932) 11 Drainage density (Dd) Dd = ΣL/A where L = the total length of streams; A = area of the watershed Horton (1932) 12 Form factor (Ff) Rf = A/Lb 2, where A = area of the basin and Lb = (maximum) basin length Horton (1932) 13 Circulatory ratio (Cr) Cr = 4πA/P 2 where A = area of the basin (km2) and P = perimeter of basin (km) Miller (1953) 14 Drainage texture (Dt) Dt = N1/P where N1 = the total number of first-order streams; P = the perimeter of the watershed) Horton (1945) 15 Elongation ratio (Er) Er = 2√(A/π)/Lb where A = the area of watershed, π = 3.14, Lb = the basin length Schumn (1956) 16 Compact coefficient (Cc) Cc = P/2√πA where P = perimeter of basin (km) and A = area of the basin ( km2) Horton (1945) 17 Length of overland flow (Lg) Lg = 1/2Dd where Dd = drainage density of basin or Lg = (1/Dd)/2 Horton (1945) Table 2: Results of the morphometric analysis of the sub-watersheds Sub-WS Number of Streams of each Order (Nu) Stream Length of each Order (Lu) in km 1st 2nd 3rd 4th 5th 6th Total 1st 2nd 3rd 4th 5th 6th Total WS-1 896 373 370 121 139 ---- 1899 114 47 32 12 42 ---- 247 WS-2 579 273 149 193 ----- ---- 1194 103 36 28 21 ---- ---- 188 WS-3 704 310 196 56 98 ---- 1364 112 52 35 10 23 ---- 232 WS-4 327 133 25 134 ----- ---- 619 54 25 8 17 ---- ---- 104 Jothimani et al. Ethiop.J.Sci.Sustain.Dev., Vol. 8 (1), 2021 58 Table 3: Results of the morphometric analysis of the sub-watersheds Sub-WS Stream length ratio (Rl) Mean Mean stream length (Lsm) Mean 2/1 3/2 4/3 5/4 6/5 WS-1 0.41 0.68 0.38 3.5 ---- 1.24 0.13 0.13 0.09 0.10 0.13 0.30 0.11 WS-2 0.35 0.78 0.75 1.0 ---- 0.72 0.18 0.13 0.19 0.11 0.18 ----- 0.15 WS-3 0.46 0.67 0.29 2.3 --- 3.72 0.16 0.17 0.18 0.18 0.16 0.23 0.18 WS-4 0.46 0.32 2.13 ---- ---- 2.91 0.17 0.19 0.32 0.13 0.17 ----- 0.20 Table 4: Results of the morphometric analysis of the sub-watersheds Bifurcation ratio Rbm Lb Sub-watersheds 1/2 2/3 3/4 4/5 5/6 WS-1 2.40 1.01 3.06 0.87 ----- 1.83 24 WS-2 2.12 1.83 0.77 ----- ----- 1.57 21 WS-3 2.27 1.58 3.50 0.57 ----- 1.98 25 WS-4 2.46 5.32 0.19 ----- ----- 2.65 16 Where Rbm = mean bifurcation ratio, and Lb =length of basin kms 3.2. Areal morphometric parameters The calculated basin perimeter varied from 115 km in WS-1, 57 km in WS-2, 109 km in WS-3, and 58 in WS-4 (Table 5). The area of the sub-watershed is an additional significant morphometric parameter. In the present study, each sub-watershed area was calculated, which varies from 168 km2 in WS-1, 134 km2 in WS-2, 177 km2 in WS-3, and 80km2 WS-4 given in (Table 5). The compactness coefficient calculated for the study area varies from 2.50 in WS-1, 0.72 in WS-2, 0.43 in WS-3, and 0.55 in WS-4 (Table 5). The compactness of the coefficient has a direct relationship to the soil erosion proneness. Lower values of compactness coefficient signify lesser soil erosion vulnerability risk, while higher values show great soil erosion proneness and represent the need to implement soil conservation measures. High form factor values usually form the watershed's circular shape and have high peak flows over a short period. In contrast, elongated basins with low form factors have low peak flows over long durations. The calculated form factor value varies from 0.16 to 0.22, which shows an elongated circular shape and suggests a flatter peak flow with a longer duration. Form factor values are shown in Table 5. An elongation ratio calculated varied from 0.61 in WS-1, 0.62 in WS-2, 0.60 in WS-3, and 0.63 in WS-4. An elongation ratio close to 1.0 is typically a region of shallow relief, whereas that of 0.6–0.8 is associated with high relief and steep ground slope (Strahler, 1964). The elongation values can be grouped into three categories: >0.9 circular, 0.9–0.8 oval, and <0.7 elongated (Strahler, 1964). The elongation ratio values of the study area sub-watershed are <0.7, representing the basin's elongated shape. The elongation ratio values of each sub-watershed are shown in Table 8. Each sub- watershed circulatory ratio was calculated and varied from 0.16 in WS-1, 0.52in WS-2, 0.19 in WS-3, and 0.30 in WS-4 (Table 5). A maximum circulatory ratio of 0.52 was observed in WS-2 and represented the circular shape of sub-watershed. Table 5: Results of the morphometric analysis of the sub-watersheds Sub-watersheds A P Df Dd Ff Cr Dt Er Cc Lg WS-1 168 115 11.30 1.47 0.29 0.16 7.79 0.61 2.50 0.340 WS-2 134 57 8.91 1.40 0.30 0.52 10.16 0.62 1.39 0.357 WS-3 177 109 7.71 1.31 0.28 0.19 6.46 0.60 2.31 0.382 WS-4 80 58 7.74 1.30 0.31 0.30 5.64 0.63 1.83 0.385 A= area, P=perimeter, Df = drainage frequency, Dd= drainage density, Ff= form factor, Cr= circulatory ratio, Dt= drainage texture, Er= elongation ratio, Cc= compact coefficient, and Lg= length of overland. Jothimani et al. Ethiop.J.Sci.Sustain.Dev., Vol. 8 (1), 2021 59 Drainage density shows the underlying rock's physical properties of the area. Drainage density in the present study area varies from 1.47 km/ km2 in (WS-1) 1.40 km/ km2, in (WS-2) 1.31 km/ km2 in (WS-3) and 1.30 km/ km2 in (WS-4) (Table 5). The study area's overall drainage density ranges from 0 km/ km2 to 3.30 km/ km2. Permeable subsoil material, thick vegetation, low elevation, and coarse drainage texture indicate low drainage density (Nag, 1998). High drainage density is the subsequent impermeable subsurface material, thin vegetation, mountainous relief, and fine drainage texture. In this study, each sub-watershed shows a different stream of frequency value. Higher stream frequency values have observed in WS-1 and WS-2, representing impervious sub-surface media, whereas less stream frequency resulted in WS-3 and WS-4 and represented the porous sub-surface media with low elevation. Table 5 shows the stream frequency values. 3.3. Priority ranking of sub-watersheds The present study emphasizes prioritizing the four sub-watersheds of the Megech River based on a drainage morphometric parameter analysis. The following morphometric parameters like drainage density (Dd), drainage frequency (Df), circulatory ratio (Cr), bifurcation ratio (Br), elongation ratio (Er), drainage texture (Dt), form factor (Ff), compactness coefficient (Cc), and length of overland (Lg) were measured and ranked accordingly. Morphometric parameters like Rb, Dd, Lg, and Df have a direct relationship with soil erosion proneness (Biswas et al. 1999; Nooka et al. 2005; Javed et al. 2011). Rank1 was assigned to the highest value of the above-mentioned morphometric parameters, rank 2 to the second-highest value of the morphometric parameters, and rank 3 given the lowest value of the above-mentioned drainage morphometric parameters. The following drainage morphometric parameters, circulatory ratio (Rc), form factor (Ff), Drainage texture (Dt), and Compactness co- efficient (Cc) have a reverse relationship with soil erosion proneness as stated by (Biswas et al. 1999; Nooka et al. 2005; Javed et al. 2011). Subsequently, rank 1, assigned to the lowest value of the above-mentioned morphometric parameters, the following lower value has been assigned a rank of 2, and rank 3 is assigned to the highest value of the above-mentioned drainage morphometric parameter. Thus, the ranks were allocated to each drainage morphometric parameter of the four sub- watersheds based on their flood proneness is shown in Table 6. The compound factor was calculated by summing the assigned ranks of the various drainage morphometric parameters and dividing them by the number of parameters used to prioritize the sub-watersheds (Patel et al., 2012). In the present study, sub-watershed-3 got very highly prioritized with the lowest compound factor value of 2.11. The sub-watershed with the highest compound factor value of 2.88 (WS- 2) has a low priority rank. The sub-watershed, which has the lowest value of the compound factor, is highly vulnerable to soil erosion. Sub-watershed-wise compound factor values and their prioritization rankings are shown in Table 7 and Figure 4. In this present study, sub-watershed-3 has identified sub- watershed-3 as a high-priority ranked watershed, and it needs immediate soil conservation measures for efficient watershed planning and management. Table 6: Estimation of compound factor values Morphometric parameters Sub-watersheds WS-1 WS-2 WS-3 WS-4 Bifurcation ratio 3 4 2 1 Drainage frequency 1 2 3 4 Drainage density 1 2 3 4 Length of overland flow 4 3 2 1 Circulatory ratio 1 4 2 3 Form factor 2 3 1 4 Elongation ratio 2 3 1 4 Drainage Texture 3 4 2 1 Compactness coefficient 4 1 3 2 Compound factor value 2.33 2.88 2.11 2.67 Jothimani et al. Ethiop.J.Sci.Sustain.Dev., Vol. 8 (1), 2021 60 Table 7: Compound factor value and priority ranking of sub-watersheds Sub-watersheds Compound factor Priority ranking WS-1 2.33 High WS-2 2.88 Low WS-3 2.11 Very high WS-4 2.67 Medium Figure 4: Sub-watersheds wise prioritization for soil erosion map 4. Conclusion The present study shows the effectiveness of the ASTER DEM, Landsat-8 OLI image, and GIS techniques in the quantitative drainage morphometric analysis. Therefore, remote sensing data and GIS techniques are more efficient for understanding individual sub- watershed morphological characteristics. The linear, areal, and relief morphometric aspects established the watershed's hydrologic performance, and it is the same. It is beneficial for the sub-watershed wise prioritization. In the present study, four sub-watersheds were considered for the drainage morphometric analysis. The selected drainage morphometric parameters were calculated using the standard formula. The morphometric parameters such as bifurcation ratio, drainage density, length of overland flow, and drainage frequency are directly connected with soil erosion proneness. Hence, rank 1 is assigned to the highest values of the parameters mentioned above, followed by second-rank to second-highest value, and rank third given the above parameters' lowest value. The morphometric parameters such as circulatory ratio, form factor, elongation ratio, and drainage texture and compactness coefficient have a reverse relation with soil erosion proneness. Hence, rank 1 is assigned to the lowest values of those parameters, followed by rank two to the second-lowest value, and ranks three, given the above parameters' highest value. Thus, the ranks are allocated to each drainage morphometric parameter of the four sub- watersheds; then, the compound factor is computed by aggregating the assigned ranks of the criteria mentioned above and then dividing by the number of morphometric criteria used for sub-watersheds prioritization. Through the present analysis, sub-watershed-3 has been identified as the very-high soil erosion-prone watershed. Furthermore, it needs immediate soil conservation remedial measures for efficient soil resource management planning. The present study results are useful for resource planners, decision-makers, or government-private agencies who attempt to take up soil resources, conservation measures, or fixation of soil conservation structures in the present study area. Reference Agarwal, C.S. (1998). Study of drainage pattern through aerial data in Naugarh area of Varanasi District, U.P. J Indian Soc Remote Sens., 26:169–175 Al-Sulaimi, J., Khalaf, F.J., Mukhopadhyay (1997). Geomorphological analysis of paleo drainage systems and their environmental implications in the desert of Kuwait. Environ Geol. 29:94–111 Altaf F, Meraj G, Romshoo SA. (2013). Morphometric analysis to infer hydrological behavior of Lidder watershed, Western Himalaya, India. Geogr J., 2013. doi:10.1155/2013/178021 Altaf, F Meraj G, Romshoo S. (2014). Morphometric analysis to infer hydrological behaviour of Lidder watershed, western Himalaya, India. Geogr J., 2013:1–14. https://doi.org/10.1155/2013/178021 https://doi.org/10.1155/2013/178021 Jothimani et al. Ethiop.J.Sci.Sustain.Dev., Vol. 8 (1), 2021 61 Amare, T., Zegeye, A.D., Yitaferu, B., Steenhuis, T.S., Hurni, H., Zeleke, G. (2014). Combined effect of soil bund with biological soil and water conservation measures in the northwestern Ethiopian highlands. Ecohydrol. Hydrobiol. 14 (2014), 192– 199. Aouragh, M.H. and Essahlaoui, A. (2014). Morphometric analysis of a Guigou Sub-watershed, Sebou basin, Middle Atlas, Morocco using GIS based ASTER (DEM) image. Int J Innov Res Sci Eng Technol., 3(4), 11503-11512 Athick, A.A.S.M., & Shankar, K. (2019). Data on Land Use and Land Cover Changes in Adama Wereda, Ethiopia, on ETM+, TM and OLI- TIRS landsat sensor using PCC and CDM techniques, Data in Brief, 24. https://doi.org/10.1016/j.dib.2019.103880. Bagyaraj, M. and Gurugnanam, B. (2011). Significance of morphometric studies, soil characteristics, erosion phenomena and landform processes using remote sensing and GIS for Kodaikanal Hills. Res J Environ Earth Sci., 3(2011):221–233 Belay, K.T., Van Rompaey, A., Poesen, J., Van Bruyssel, S., Deckers, J, and Amare, K. (2014). Spatial analysis of land cover changes in eastern Tigray (Ethiopia) from 1965 to 2007: are there signs of a forest transition? Land Degrad. Dev. 25, 130–142. http://dx.doi. org/10.1002/ldr.1153. Biswas, A., Majumdar, D, and Banerjee, S. (2014). Morphometry governs the dynamics of a drainage basin: analysis and implications. Geogr. J., 2014:1–14. https://doi.org/10.1155/2014/927176 Biswas, S., Sudhakar S, and Desai VR. (1999). Prioritization of sub-watersheds based on morphometric analysis of drainage basin: A remote sensing and GIS approach. Jour. Indian Soc. Remote Sensing. .27: 155-166. https://doi.org/10.1007/BF02991569 Breyer, SP., and Scott Snow R. (1992). Drainage basin perimeters: a fractal significance. Geomorphology, 5:143–157. https://doi.org/10.1016/ 0169-555X(92)90062-S Choudhari, PP, Nigam GK, Singh SK, and Thakur S. (2018). Morphometric based prioritization of watershed for groundwater potential of Mula river basin, Maharashtra, India. Geol Ecol Landscapes., 9508:1–12. https://doi.org/10.1080/24749508.2018.1452482 Clarke JI. (1966). Morphometry from maps, essays in geomorphology. Elsevier Publication Co., New York, pp 235–274 Das AK, and Mukherjee S. (2005). Drainage morphometry using satellite data and GIS in Raigad district, Maharashtra. J Geol Soc India, 65:577– 586 EMS (Ethiopian Meteorological Service) (2019). Ethiopian meteorological service data base (1973–2019). Ethiopian Meteorological Service, Addis Ababa Erkossa, T., Wudneh, A., Desalegn, B, and Taye, G. (2015). Linking soil erosion to on-site financial cost: lessons from watersheds in the Blue Nile basin. Solid Earth, 6: 765–774. http://dx.doi.org/10.5194/se-6-765-2015. Everard M, Sharma OP, Vishwakarma VK, Khandal D, Sahu YK, Bhatnagar R, Singh JK, Kumar R, Nawab A, Kumar A, Kumar V, Kashyap A, Pandey DN, and Pinder AC. (2018). Assessing the feasibility of integrating ecosystem-based with engineered water resource governance and management for water security in semi-arid landscapes: a case study in the Banas catchment, Rajasthan, India. Sci Total Environ, 612:1249–1265. https://doi.org/10.1016/j.scitotenv.2017. 08.308 Farhan, Y., and Anaba, O. (2016). A remote sensing and GIS approach for prioritization of Wadi Shueib mini-watersheds (Central Jordan) based on morphometric and soil erosion susceptibility analysis. J Geogr Inf Syst., 8(01):1–19 Fazzini M, Bisci C, and Billi P. (2015). The climate of Ethiopia. In: Billi P (ed) Landscapes and Landforms of Ethiopia. World geomorphologic landscapes. Springer, Dordrecht Food and Agriculture Organization of the United Nations (FAO) (2006). World reference base for soil resources, 2006: a framework for international classification, correlation, and communication, 2006th edn. Food and Agriculture Organization of the United Nations, Rome Gopinath, G., Nair, A.G, and Ambili, G.K. (2016). Watershed prioritization based on morphometric analysis coupled with multi criteria decision making. Arab J Geosci. 9, 129 https://doi.org/10.1007/s12517-015-2238-0 Gregory, K.J., and Walling, D.E. (1968). The variation of drainage density within a catchment. Hydrol Sci J., 13(2):61–68 GSE. (2011). Geology, Geochemistry and Gravity Survey of West Gonder and Gonder Map. Addis Ababa, Ethiopa. Gulavani VS, Deshmukh PSS, and Zende M. (2017). Geomorphological analysis of upper Karha watershed in semi-arid area, Maharastra, India. Int Educ Sci Res. J., 3:52–56 Halefom, A, and Teshome, A. (2019). Modelling and mapping of erosion potentiality watersheds using AHP and GIS technique: a case study of Alamata Watershed, South Tigray, Ethiopia. Modeling Earth Systems and Environment, 5:1-13 Haregeweyn, N., Tsunekawa, A., Nyssen, J., Poesen, J., Tsubo, M., Meshesha, D.T., Schütt, B., Adgo, E., and Tegegne, F. (2015). Soil erosion and conservation in Ethiopia: a review. Prog. Phys. Geogr., 39: 750–774. http://dx.doi.org/10.1177/0309133315598725. Hengsdijk, H., Meijerink, G.W., and Mosugu, M.E. (2005). Modeling the effect of three soil and water conservation practices in Tigray, Ethiopia. Agric. Ecosyst. Environ. 105, 29–40. http://dx.doi.org/10.1016/j.agee.2004.06.002. Horton, R. E. (1932). Drainage-basin characteristics transactions, Am Geophys Union., 13:350-361 https://doi.org/10.1029/TR013i001p00350 Horton, R. E. (1945). Erosional development of streams and their drainage basin; hydrophysical approach to quantitative morphology. Geol Soc Am Bull, 56:151–180. https://doi.org/10.1130/0016- 7606(1945)56 Hurni, H. (1993). Land degradation, famine and resources scenarios in Ethiopia. In: Pimental D (ed) World soil erosion and conservation. Cambridge University Press, Cambridge Hurni, K., Zeleke, G., Kassie, M., Tegegne, B., Kassawmar, T., Teferi, E., Moges, A., Tadesse, D., Ahmed, M., Degu, Y., Kebebew, Z. (2015). Soil degradation and sustainable land management in the rainfed agricultural areas of Ethiopia: an assessment of the economic implications. Report for the economics of land degradation initiative http://dx.doi/ https://doi.org/10.1155/2014/927176 https://doi.org/10.1007/BF02991569 https://doi.org/10.1016/ https://doi.org/10.1080/24749508.2018.1452482 http://dx.doi.org/10.5194/se-6-765-2015 https://doi.org/10.1016/j.scitotenv.2017.%2008.308 https://doi.org/10.1007/s12517-015-2238-0 http://dx.doi.org/10.1177/0309133315598725 http://dx.doi.org/10.1016/j.agee.2004.06.002 https://doi.org/10.1029/TR013i001p00350 https://doi.org/10.1130/0016- Jothimani et al. Ethiop.J.Sci.Sustain.Dev., Vol. 8 (1), 2021 62 Jasmin, I., and Mallikarjuna, P. (2013). Morphometric analysis of Araniar river basin using remote sensing and geographical information system in the assessment of groundwater potential. Arab J Geosci., 6:3683– 3692. https://doi.org/10.1007/s12517-012-0627-1 Javed, A., Khanday, M.Y., and Rais, S. (2011). Watershed prioritization using morphometric and land use/land cover parameters: a remote sensing and GIS based approach. Jour. Geol. Soc. India, 78:63-75. https://doi.org/10.1007/s12594-011-0068-6 Kadam, A.K., Jaweed, T.H., Umrikar, B.N., Hussain, K., and Sankhua, R.N. (2017). Morphometric prioritization of semi-arid watershed for plant growth potential using GIS technique. Model. Earth Syst. Environ., 3:1663-1673. https://doi.org/10.1007/s40808-017- 0386-9 Kandpal, H., Kumar, A., Reddy, C.P., and Malik, A. (2017). Watershed prioritization based on morphometric parameters using remote sensing and geographical information system watershed prioritization based on morphometric parameters using remote sensing and geographical information system. Indian J Eco., 4(3):433-437 Kawo, N.S., Shankar, K. (2018). Groundwater quality assessment using water quality index and GIS technique in Modjo River Basin, Central Ethiopia. Journal of African Earth Sciences, 147:300-311. https://doi.org/10.1016/j.jafrearsci.2018.06.034 Kebede, W. (2014). Effect of soil and water conservation measures and challenges for its adoption: Ethiopia in focus. J. Environ. Sci. Technol., 7: 185–199. Keesstra, S., Pereira, P., Novara, A., Brevik, E.C., Azorin-Molina, C., Parras-Alcántara, L., Jordán, A., and Cerdà, A. (2016). Effects of soil management techniques on soil water erosion in apricot orchards. Sci. Total Environ. 551–552, 357–366. http://dx.doi.org/ 10.1016/j. scitotenv.2016.01.182. Kumar, P., Kshitij, R. (2017). A GIS-based approach in drainage morphometric analysis of Kanhar River basin, India. Appl Water Sci., 217– 232. https://doi.org/10.1007/s13201-014-0238-y Kumar, P., Rajeev, R., and Chandel, S. (2018). Hydrological inferences through morphometric analysis of lower Kosi river basin of India for water resource management based on remote sensing data. Appl Water Sci., 8:1–16. https://doi.org/10.1007/s13201-018-0660-7 Magesh, N., Chandrasekar, N., and Soundranayagam, J. (2011). Morphometric evaluation of Papanasam and Manimuthar watersheds, parts of Western Ghats, Tirunelveli district, Tamil Nadu, India: a GIS approach. Environ Earth Sci., 64(2):373–381 Magesh, N.S., and Chandrasekar, N. (2014). GIS model-based morphometric evaluation of Tamiraparani subbasin, Tirunelveli district, Tamil Nadu, India. Arab J Geosci., 7:131–141. https://doi.org/10.1007/ s12517-012-0742-z Martins, A.K., and Gadiga, B.L. (2015). Hydrological and morphometric analysis of upper Yedzaram catchment of Mubi in Adamawa state, Nigeria. Using geographic information system (GIS). World Environ., 5:63 – 69. https://doi.org/10.5923/j.env.20150502.03 Mekuriaw, A., Heinimann, A., Zeleke, G., and Hurni, H. (2018). Factors influencing the adoption of physical soil and water conservation practices in the Ethiopian highlands. Int Soil Water Conserv Res., 6:23–30. https ://doi. org/10.1016/j.iswcr .2017.12.006 Meshram, S.G., and Sharma, S.K. (2017). Prioritization of watershed through morphometric parameters: a PCA-based approach. Appl Water Sci. 7:1505–1519. https://doi.org/10.1007/s13201-015-0332-9 Miller, V.C. (1953). A quantitative geomorphic study of drainage basin characteristics in the Clinch Mountain area, Virginia and Tennessee. Project NR 389042, Technical report 3, Columbia University, Department of Geology, ONR, Geography Branch, New York Masoud, M.H. (2016). Geoinformatics application for assessing the morphometric characteristics’ effect on hydrological response at watershed (case study of Wadi Qanunah, Saudi Arabia). Arab J Geosci., 9:280. https ://doi.org/10.1007/s1251 7-015-2300-y Muralitharan, J., Abel, A., Zerihun, D. (2020a). Mapping of soil erosion prone sub-watersheds through drainage morphometric analysis and weighted sum approach: a case study of Kulfo River basin, Rift valley, Arba Minch, Southern Ethiopia. Model Earth Syst Environ. https ://doi.org/10.1007/s4080 8-020-00820 –y Muralitharan, J., Dawit, Z, .Mulualem, W. (2020b). Flood Susceptibility Modeling of Megech River Catchment, Lake Tana Basin, North Western Ethiopia, Using Morphometric Analysis. Earth Syst Environ. https://doi.org/10.1007/s41748-020- 00173-7 Nag, S. (1998). Morphometric analysis using remote sensing techniques in the chaka sub-basin, purulia district, West Bengal. J Indian Soc Remote Sens., 26(1–2):69–76. https ://doi.org/10.1007/BF030 07341 Nag, S.K., and Chakraborty, S. (2003). Influence of rock types and structures in the development of drainage network in hard rock area. J Indian Soc Remote Sens. 31:26–35. https://doi.org/10.1007/BF03030749 Nigussie, Z., Tsunekawa, A., Haregeweyn, N., Adgo, E., Nohmi, M., Tsubo, M., Aklog, D., Meshesha, D.T, and Abele, S. (2017). Farmers' perception about soil erosion in Ethiopia. Land Degrad. Dev., 28: 401–411. http://dx.doi.org/10.1002/ldr.2647. Nooka, K., Srivastava, Y.K., Venkateshwara Rao, V., Amminedu, E., and Murthy, K.S.R. (2005). Check dam positioning by prioritization of micro-watersheds using SYI model and morphometric analysis-remote sensing and GIS perspective. Jour. Indian Soc. Remote Sens., 33:.25-38. https://doi.org/10.1007/BF02989988 Osano, P.O. (2015). Morphometric characterization and hydrological assessments of river Njoro watershed using system for automated geoscientific analysis (SAGA) and shuttle radar topographic mission (SRTM) digital elevation model. Int J Adv Remote Sens GIS, 4:37–44 https://doi.org/10.1007/s12517-012-0627-1 https://doi.org/10.1007/s40808-017-0386-9 https://doi.org/10.1007/s40808-017-0386-9 http://dx.doi.org/ https://doi.org/10.1007/s13201-014-0238-y https://doi.org/10.1007/s13201-018-0660-7 https://doi.org/10.1007/ https://doi.org/10.5923/j.env.20150502.03 https://doi.org/10.1007/s13201-015-0332-9 https://doi.org/10.1007/BF03030749 http://dx.doi.org/10.1002/ldr.2647 https://doi.org/10.1007/BF02989988 Jothimani et al. Ethiop.J.Sci.Sustain.Dev., Vol. 8 (1), 2021 63 Patel, D.P., Dholakia, M.B., Naresh, N., Srivastava, P.K. (2012). Water harvesting structure positioning by using geo- visualization concept and prioritization of mini-watersheds through morphometric analysis in the lower Tapi basin. J Indian Soc Remote Sens., 40:299–312 Poitras, V., Sushama, L., Seglenieks, F., Khaliq, M.N, and Soulis, E. (2011). Projected changes to streamflow characteristics over western Canada as simulated by the Canadian RCM. J. Hydrometeorol., 12(6): 395-141. Pophare, A.M., and Balpande, U.S. (2014). Morphometric analysis of Suketi river basin, Himachal Himalaya, India. J Earth Syst Sci. 123:1501–1515. https://doi.org/10.1007/s12040-014-0487-z Prabhakar, A.K., Singh, K.K, and Lohani, A.K. (2019). Study of Champua watershed for management of resources by using morphometric analysis and satellite imagery. Appl Water Sci., 9. 127 https://doi.org/10.1007/s13201-019-1003 Prakash, K., Rawat, D., and Singh, S. (2019). Morphometric analysis using SRTM and GIS in synergy with depiction: a case study of the Karmanasa River basin, North central India. Appl Water Sci., 9. 13 https://doi.org/10.1007/s13201-018- 0887-3 Rawat, U., Awasthi, A., and Gupta, D.S. (2017). Morphometric analysis using remote sensing and GIS techniques in the Bagain River basin. Indian J Sci Technol., 10:1–9. https://doi.org/10.17485/ijst/2017/v10i10/ 107875 Reddy, G.P.O., Maji, A.K,. and Gajbhiye, K.S. (2004). Drainage morphometry and its influence on landform characteristics in a basaltic terrain, Central India—a remote sensing and GIS approach. Int J Appl Earth Obs Geoinf., 6:1–16. https://doi.org/10.1016/j.jag.2004.06.003 Rekha, V.B., George. A.V., and Rita, M. (2011). Morphometric analysis and micro watershed prioritization of Peruvanthanam sub-watershed, the Manimala River basin, Kerala, South India. Enviro Res Eng Manag., 3:6–14 Sangle, A.S., and Yannawar, P.L. (2014). Morphometric analysis of watershed using GIS and RS: a review. Int J Eng Res Technol., 3: 599–602 Satheesh, K.S., Venkateswaran, S. (2018). Predilection of sustainable recharge structures using morphometric parameters and decision making model in the Vaniyar sub basin, South India. Appl Water Sci., 8:213. https ://doi.org/10.1007/s1320 1- 018-0844-1 Schumn, S.A. (1956). Evolution of drainage systems and slopes in Badlands at Perth Amboy, New Jersey. Geol Soc Am Bull., 67:597-646 https://doi.org/10.1130/0016-7606(1956)67[597:EODSAS]2.0.CO;2 Sehgal, I.J., and Babar, M. (2013). Morphometric analysis with reference to hydrogeological repercussion on Domri River sub- basin of Sindphana River basin, Maharashtra, India. J Geosci Geomatics., 1: 29–35. https://doi.org/10.12691/jgg-1-1-5 Shankar, K. and Kawo, S.N. (2019). Groundwater Quality Assessment Using Geospatial Techniques and WQI in North East of Adama Town, Oromia Region, Ethiopia. Hydrospatial Analysis, 3(1), 22–36. https://doi.org/10.21523/gcj3.19030103 Shankar, K., Aravindan, S., Rajendran, S. (2009). Hydrogeomorphological mapping in Paravanar River Sub-basin, Cuddalore district, Tamil Nadu, India. Journal of Eco-chronicle, 4(3):161-170. Shreve, R.L. (1966). Statistical law of stream numbers. J Geol., 74:17–37 Sreedevi, P.D., Owais, S., Khan, H.H., and Ahmed, S. (2009). Morphometric analysis of a watershed of South India using SRTM data and GIS. J Geol Soc India, 73:543–552. https://doi.org/10.1007/s12594-009-0038-4 Sreedevi, P.D., Sreekanth, P.D., and Khan, H.H. (2013). Drainage morphometry and its influence on hydrology in an semi arid region: using SRTM data and GIS. Environ Earth Sci., 70:839–848. https://doi. org/10.1007/s12665-012-2172-3 Strahler, A.N. (1957). Quantitative analysis of watershed geomorphology. Trans Am Geophys Union., 38:913–920. https://doi.org/10.1130/ 0016-7606 Strahler, A.N. (1964). Quantitative geomorphology of drainage basin and channel networks. In: Chow VT (ed) Handbook of applied hydrology. McGraw Hill Book Company, New York section, pp 4–39 Subyani, A.M., Qari, M.H., and Matsah, M.I. (2010). Digital elevation model and multivariate statistical analysis of morphometric parameters of some wadis, western Saudi Arabia. Arab J Geosci., 5:1–11. https://doi.org/ Suresh, M., and Sudhakar, S. (2004). Prioritization of watersheds using morphometric parameters and assessment of surface water potential using remote sensing. Journal of the Indian Society of Remote Sensing., 32:249–259 Taguas, E.V., Guzmán, E., Guzmán, G., Vanwalleghem, T, and Gómez, J.A. (2015). Characteristics and importance of rill and gully erosion: a case study in a small catchment of a marginal olive grove. Cuad. Investig. Geogr., 41-20. http://dx.doi.org/ 10.18172/cig.2644. Tesfaye, A., Deneke, T.T, and Selassie, Y.G. (2014a). Determinants of maintenance decision of introduced soil and water conservation practices in Fagita Lekoma District, north west highlands of Ethiopia. Ethiop. J. Appl. Sci. Technol., 5: 1– 17. Tesfaye, A., Negatu, W., Brouwer, R., and Zaag, P. (2014b). Understanding soil conservation decision of farmers in the Gedeb watershed, Ethiopia. Land Degrad. Dev., 25: 71–79. Teshome, A., de Graaff, J., Ritsema, C, and Kassie, M. (2016). Farmers' perceptions about the influence of land quality, land fragmentation and tenure systems on sustainable land management in the north western Ethiopian highlands. Land Degrad. Dev., 27: 884–898. http://dx.doi.org/10.1002/ldr.2298. https://doi.org/10.1007/s12040-014-0487-z https://doi.org/10.1007/s13201-019-1003 https://doi.org/10.1007/s13201-018-0887-3 https://doi.org/10.1007/s13201-018-0887-3 https://doi.org/10.17485/ijst/2017/v10i10/ https://doi.org/10.1016/j.jag.2004.06.003 https://doi.org/10.1130/0016-7606(1956)67%5b597:EODSAS%5d2.0.CO;2 https://doi.org/10.12691/jgg-1-1-5 https://doi.org/10.21523/gcj3.19030103 https://doi.org/10.1007/s12594-009-0038-4 https://doi/ https://doi.org/10.1130/ https://doi.org/ http://dx.doi.org/ http://dx.doi.org/10.1002/ldr.2298 Jothimani et al. Ethiop.J.Sci.Sustain.Dev., Vol. 8 (1), 2021 64 Thomas, J., Joseph, S., Thrivikramji, K., Abe, G., and Kannan, N. (2012). Morphometrical analysis of two tropical mountain river basins of contrasting environmental settings, the southern Western Ghats, India. Environ Earth Sci., 66(8):2353– 2366. Vittala, S.S., Govindaiah, S., and Gowda, H.H. (2008). Prioritization of sub watersheds for sustainable development and management of natural resources: an integrated approach using remote sensing, GIS and socio-economic data. Curr Sci., 95:345–354 Wani, M.H., and Javed, A. (2013). Evaluation of natural resource potential in semi-arid micro-watershed, eastern Rajasthan, using remote sensing and geographic information system. Arab J Geosci., 6:1843–1854. https://doi.org/10.1007/s12517-011-0472-7 Woldeamlak, B., and Stroosnijder, L. (2003). Effects of agro-ecological land use succession on soil properties in the Chemoga watershed, Blue Nile basin, Ethiopia. Geoderma, 111, 85–98. WWDSE & TAHAL GROUP (2008). Megech Dam Final Fisibility Report, Volume 2. Addis Ababa, Ethiopia. Yanina, M., Angillieri, E., and Fernández, O.M. (2017). Morphometric analysis of river basins using GIS and remote sensing of an Andean section of route 150, Argentina. A comparison between manual and automated delineation of basins. Revista Mexicana de Ciencias Geológicas., 34: 150–156 Yogesh, D., Mahesh, S., Ravindra, J., and Sanjay, P. (2016). .Application of watershed Erosion response model in planning resource conservation of Dehrang catchment, district Raigad. Univers J Environ Res Technol., 6(1) Ziemer, G.L. (1973). Quantitative geomorphology of drainage basins related to fish production. Alaska Department of Fish and Game, Division of Commercial Fisheries. https://doi.org/10.1007/s12517-011-0472-7