Abstract
The present investigation intends to prioritize the sub-watersheds of the Urmodi River watershed (Maharashtra State, India) for Soil Conservation, which is based on the integrated approach consisting of geomorphometric and Land Use Land Cover (LULC) factors. Prioritization based on Geographic Information Science (GIS) platform, allows us to take informed decisions for managing and safeguarding resources from degradation. Quantitative morphometric analysis of three aspects, namely linearity, shape and relief, were carried out for sub-watersheds encompassing the entire study area. In addition, Remote Sensing (RS) based on high-resolution multispectral data with 10 m spatial resolution captured by Sentinel 2 satellite was analysed to infer the land cover condition. In water-induced soil erosion, morphometric parameters have crucial role in understanding the geo-environmental characteristics of the terrain. Moreover, rainfall effects depend on the pattern of LULC change and each land cover responds differently to the raindrop energy it receives. Therefore, it requires integration of the geomorphological and hydrological characteristics of the sub-watersheds derived from their morphometric parameters with the LULC to generate compounded ranking-based prioritization of the sub-watersheds. During the prioritization analysis, the lower compound value is considered with higher priority for appropriate soil conservation measures. It was found that the integration of morphometric and LULC factors changed the prioritization ranking considerably. Incidentally, Sub-watershed 4 which was having moderate raking based on morphomertic analysis, got highest rank and compound value of 2.38 due to integrated approach. It was evident that the use of an integrated prioritization approach helps us to arrive at better decision-making related to soil conservation.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
1 Introduction
Watershed is a geographical unit and natural boundary where it is a logical choice to practice morphometric analysis to understand the hydrological cycle (Ahmed et al. 2018). Watershed deterioration is one of the common issues in India and it also influences at global scale (Prabhakar et al. 2019). Therefore, prioritization of the watershed is necessary for comprehensive watershed management and planning to reduce soil loss (Ahirwar et al. 2019). In watershed management, its prioritization has attracted scientific attention, which helps for the better and protective measures for the natural resource management (Sarma and Saikia 2012). Soil erosion is one of the detrimental processes for land resource and it leads to uncertainty related to water availability in the watershed area. Erosion (soil loss) not only destroys the land but also creates the other environmental issues like reservoir sedimentation, channel siltation, deposition of unfertile material on agricultural land and posing infertility due to erosion (Vemu and Udayabhaskar 2010). Drainage basin refers to the whole area providing runoff and sustaining parts or all stream-flow including main channels with its tributaries (Prabhakaran and Jawahar Raj 2018). Analysis of morphometric parameters of a drainage basin and its associated stream network show its hydrological behaviour (Pophare and Balpande 2014). Quantitative parameters of drainage network of the basin have a very helpful function in the hydrological model, watershed prioritization, natural resource management and its rehabilitation (Choudhari et al. 2018). Remote Sensing (RS) and Geographical Information System (GIS) is a widely used tool in prioritization of watershed, which also helps in planning and development (Sarma and Saikia 2012). In the watershed development plan, it is essential to understand the terrain conditions, erosion status and drainage pattern of an area (Sreedevi et al. 2005). Rainfall and wind are the main factors that cause erosion and soil degradation, which cause changes in river morphology and problems related to the water reservoir and other environmental issues. Integration of RS and GIS methods can be successfully used in soil erosion assessment and sub-watershed prioritization (Thakkar and Dhiman 2007; Javed et al. 2011; Chandniha and Kansal 2017).
The joint application of the RS and GIS methodology has been found to be a promising and powerful tool in the morphometric analysis of drainage network in recent years (Pandey and Das 2016). It is essential for prioritizing sub-basins as part of the integrated assessment of river basin degradation. Many researchers have used the GIS and RS approach in studies related to the watershed management including its prioritization for better management of natural resources (Nooka Ratnam et al. 2005; Malik and Bhat 2014; Khadse et al. 2015; Meshram and Sharma 2017).
A study was carried out in 2020 by the National Institute of Soil Bureau and Land Use Planning (NBSS and LUP 2002) employing the Universal Soil Loss Equation (USLE) to show soil erosion risk zones in the Maharashtra state (India). This study showed that soil degradation triggered by soil erosion is quite prominent in this area. Other recent study, performed by Bagwan and Gavali (2020a) revealed that very severe erosion zone (> 80 ton/ha−1 year−1) was expanding with the annual incremental rate of 14.87% in the study area. In addition to this aspect, it was also found that the rainfall erosivity is high in Urmodi River watershed having values around 1014.7 MJ mm ha−1 h−1 year−1 in the plateau region (Bagwan and Gavali 2020b). Therefore, due to soil erosion susceptibility, there is a pertinent need to prioritize regions for soil conservation and to protect the land from deterioration. As a part of watershed management and better resource utilization, factors, such as basin drainage characteristics, soil condition and land cover, play a crucial role (Bhattacharya et al. 2019). In the current study, an attempt is made to derive ranking based on morphometric parameters and Land Use Land Cover (LULC) using RS and GIS tools for prioritization of soil erosion measures in the Urmodi River watershed (Satara district, Maharashtra State, India) as a part of sustainable development plan for this region.
2 Study area
The Urmodi River watershed (Satara district, Maharashtra, India; Fig. 1) is located between: longitudes 73° 47′ 38.432′′ E–74° 6′ 58.267′′ E and latitudes 17° 28′ 36.893′′ N–17° 44′ 35.072′′ N. The Urmodi river basin covers 414.27 km2. It is spread in three toposheets viz. 47 K/2, 47K3 and 47 G/14. From the toposheets, with the elevation difference of 685 m. Urmodi River originates at the Kaas Lake located in Jaoli block (administrative boundaries) and meets with the Krishna River at Kashil village, in Satara block. The study region is situated on the right bank of the Krishna River. The world heritage site Kaas plateau (IUCN 2012) is located in the upper catchment of the River Urmodi, which is a source of attraction for tourists during the monsoon season. During the field observation, it has been observed that, in the upper catchment, most of the lateritic soil area was under the paddy cultivation. And the lower catchment area used for the sugarcane, wheat, jowar, etc. The entire watershed is underline by the Deccan trap basaltic lava flow, from the upper cretaceous to lower Eocene age. The physiographic features of the watershed can be divided into hills and ghats, plateaus, foothills and plains. From the field survey, it has been observed that, black soil and lateritic soils is present in the study area. It has been reported that, the Deccan trap is basically composed by hard rock and soft rock, i.e., alluvium. In this region, the mean temperature ranges from 14.4 to 36.8 °C The annual rainfall in Jaoli and Satara district varies between 1730.1 and 1048.4 mm, as estimated from 2001 to 2010 (CGWB 2013). The main source of rainfall in the study area is observed during the monsoon, i.e. from June to September (Praveen et al. 2020). The Urmodi River carries heavy sediment load during the monsoon. This river is not perennial after the rainy season due to the construction of a dam. Overall, the drainage pattern of the river is parallel to semi-dendritic. In the Urmodi river watershed, we find the agriculture, rural settlement, roadways, open forest and dense forest and water bodies as a main land cover.
3 Materials and methods
3.1 Datasets used
Toposheets of Survey of India (SoI) have been used for the demarcation of the stream network. We have used this toposheet maps numbered: E43O2(47 K/2), E43O3(47 K/3), and E43N14(47 G/14). The scale of toposheet is 1:50,000. The toposheets are scanned with 300 dots per inch in JPG format. The toposheet comes with WGS84 as a native datum. The three toposheets were georeferenced, and then cropped according to the area of interest. In the second step, they were processed with mosaic operation. Later, the sub-watershed boundary was demarcated and cropped. Finally, it was re-projected with WGS84 and UTM North zone 43.
3.2 Satellite data
The Sentinel 2 is the program which is a result of the joint initiative of the European Commission (EC) and European Space Agency (ESA). The Global Monitoring of Environment and Security (GMES) Sentinel 2 is able to provide the multispectral high-resolution imagery over world terrestrial surfaces (Drusch et al. 2012). The satellite imagery was downloaded from https://scihub.copernicus.eu; it was acquired on 11 November 2016 and used to derive the land use land cover thematic layer. The main advantage of the image is that the level of the product is Sentinel-2 level 1C, which is ortho-rectified in nature. The present imagery was cloud-free with JPEG2000 as file format. The location identifier of the acquired data is orbit 105 and tile number isT43QCV.
3.3 Digitization and sub-watershed generation
Ordering of streams including temporary and permanent flow is the basic of stream order. Strahler (1964) method was used for demarcation of streams which produces the drainage network. The study region was divided into seven sub-watersheds based on drainage flow and mean sea level values. Figure 2 portrays the flowchart of the executed methodology.
3.4 Morphometric analysis
Various morphometric aspect performed on watershed is helpful in its characterization. Study of drainage network plays a significant role in land and water resources management (Fenta et al. 2017). For the present study, three aspects were considered for the morphometric analysis of Urmodi river watershed. The linear, shape and relief aspects were calculated using GIS technique. The drainage pattern of Urmodi River watershed and its sub-basins are depicted in Fig. 3. Linear aspect consists of a section of the morphometric analysis, linked with the channel pattern of the drainage network (Pandey and Das 2016). Linear parameters are directly linked with erodibility, which includes bifurcation ratio (Rb), drainage density (Dd), texture ratio (Rt), stream frequency (Fs), length of overland flow (Lo) (Chandniha and Kansal 2017; Nooka Ratnam et al. 2005). Rho coefficient (ρ) indicates hydric storage and attenuates the erosion effect during discharge. The shape factors, included in this category, indicate the geomorphology and also provide an insight into infiltration and runoff (Sujatha et al. 2015). Watersheds have different shapes and its shape reflects the runoff actions at the outlet. For the given study basin shape (Bs), circularity ratio (Rc), compactness coefficient (Cc), elongation ratio (Re) and form factor (Ff) were used. Relief characteristics of watershed morphometry deal with three-dimensional features, which include area, volume, the elevation of landforms to analyze various geological and hydrological characteristics (Sahu et al. 2017). Basin relief (Bh), Relief ratio (Rh), Ruggedness number (Rn), Melton ruggedness number (MRn), Dissection index (Dis) were computed for sub-basins and whole Urmodi river watershed. Table 1 shows the formulae used for the computation of linear, shape and relief aspects and their description.
3.5 Land Use Land Cover (LULC)
To achieve integrated analysis, RS data were employed to depict the land surface cover using multispectral bands. For the classification purpose, we need the spectral band combination to prepare the False Colour Composition (FCC) of imagery. Sentinel 2 remotely sensed Band 2—Blue (490 nm), Band 3—Green (560 nm), Band 4—Red (665 nm) and Band 8—NIR (842 nm) with a spatial resolution of 10 m has been used. Land Use Land Cover (LULC) was carried out with visual interpretation from FCC. Based on spectral characteristics of imagery, signature file is created, which is very helpful in investigating and demarcation of particular land cover. Various features on terrain show their own unique spectral reflectance and can be identified by visual analysis. Supervised classification was done using ERDAS 2011 software package. We have applied maximum likelihood technique for the classification. For the present study area, six LULC classes were created, such as Agriculture, Waterbody, Barren land, Settlement, Dense forest, and Open forest. Out of these classes, water body and settlement were excluded as they do not have topsoil cover susceptible to water-induced and topography based on soil erosion. With the help classification technique, we can monitor the changes in LULC (Khanday and Javed 2016).
3.6 Priority assignment and integration
The major goal behind the prioritization is to conduct management action with best suited for its sub-watersheds (Malik and Bhat 2014). The linear morphometric aspects and relief are directly proportional to soil risk, whereas shape aspects are inversely related (Nooka Ratnam et al. 2005; Javed et al. 2011; Meshram and Sharma 2017). Morphometric parameters, like stream frequency, mean bifurcation ratio, drainage density, length of overland flow, circularity ratio, elongation ratio, basin shape, and compactness coefficient, have been used as erosion parameters for watershed prioritization (Biswas et al. 1999). As reported by Javed et al. (2011), the study shows that in case of linear parameters, high value is to be ranked as 1, the next low value has to be given as 2 and so on. Whereas, the shape aspect of sub-watersheds are inversely proportional with soil erosion, the lowest value has been given as 1, the next low value considered as 2 and so on. After all rating completion, compound value has been calculated by simply taking mean of rating. The lowest compound value has to be rated as 1 and next lowest value as 2 and so on. LULC has been considered as a parameter in which, each class has a role as priority criteria for watershed prioritization. High-priority ranking has been given to areas with less vegetation cover, low agriculture land, and high barren land (Malik and Bhat 2014).
4 Results and discussion
The digital morphometric analysis and land use land cover analysis were carried out in a GIS environment using ArcGIS 10. The morphometric parameters were pivotal in understanding the hydraulic role of the watershed. The development of drainage network is related with geology, while precipitation shapes the stream pattern. The investigation of various linear, shape and relief parameters is discussed as follows:
4.1 Linear Morphometric parameters
The linear parameters like stream frequency, drainage density, mean bifurcation ratio, length of overland flow, drainage texture has direct linkages to erodibility. Therefore, it can be used for erosion risk assessment (Chauhan et al. 2016). The linear parameter based on compound value was computed for each sub-watershed.
4.1.1 Area (A) and perimeter (P)
Based on SoI toposheet, the Urmodi River watershed occupies 414.27 km2 (Fig. 3). Using the ‘calculate geometry’ tool in the polygon operation in ArcGIS platform, the area and perimeter were computed. The area range of sub-watershed is between 22.95 and 111.22 km2. The boundary of the watershed is 106.20 km. The whole Urmodi River watershed is divided into seven sub-watersheds and their dimensions are given in Table 2. The 7th sub-watershed has highest area and perimeter, whereas, the 5th sub-watershed has the lowest size.
4.1.2 Stream order
Categorization of streams based on its number and types of the tributary junction is called stream ordering (Sujatha et al. 2015). Strahler (1964) method was followed for stream ordering, where the origination of first channel formation is ordered as ‘first-order’ stream and when two ‘first-order’ streams meet, it further runs as ‘second order’ and so on. Stream number is simply the computing of channel’s number representing a particular order.
4.1.3 Stream number (Nu)
As we come downward across the watershed, the stream order decreases and also the stream number (Nu) is now directly related to the stream order. The Nu was calculated using the polyline demarcation of each individual stream by ‘digitized’ format in a shapefile. The number of streams of each order was described with respect to their sub-watershed in Table 2.
4.1.4 Stream length (L u) and mean stream length
It is derived by simply calculating the length of stream of all orders expressed in kilometres. The digitized polylines of shapefile were examined using ‘calculate geometry’ tool. The length of all stream orders according to sub-watershed is presented in Table 2; it also includes the mean stream length. For the whole watershed, its value is 0.78 km and the other sub-watersheds show values ranging from 0.65 to 0.89 km.
4.1.5 Stream length ratio (Rl)
Stream flow ratio has a direct relationship with surface runoff, erosion and discharge of the basin (Pandey and Das 2016). Table 3, illustrates the ratios of the sub-watershed wise and main watershed stream length. The Urmodi River watershed shows the Rl value 0.67 and its sub-watershed ranges between 0.39 and 2.91. This parameter revealed that the sub-watersheds 1 and 3 have higher surface runoff, based on erosion and in comparison to other sub-watersheds.
4.1.6 Stream frequency (Fs)
Stream frequency (Fs) and drainage density (Dd) have a close association with the sub-watersheds. Fs is also dependent on the basin geology, which reflects the drainage texture. Moreover, it is also related to permeability, infiltration capacity and relief of the sub-watersheds (Avinash et al. 2014). Table 4 shows Fs values of the sub-watersheds. The minimum value of Fs was 3.48 km/km2 in subwatershed 7 and maximum value was 5.98 km/km2 in subwatershed 3. Stream frequency of Urmodi river watershed was 4.66 km/km2. There exists a positive correlation between drainage density and stream frequency (R2 = 0.64).
4.1.7 Bifurcation ratio (R b) and mean R b
This is a dimensionless parameter that expresses the geometric similarity of catchment along with ramification of drainage network (Strahler 1964). Generally, Rb values have a range from 3.0 to 5.0, on homogenous rocky terrain (Thomas et al. 2010). For Urmodi River watershed, Rb value was found to be 5.45. As described in Table 2, the minimum Rb value was 4.04 and the maximum mean Rb value was 5.08 for the subwatersheds of Urmodi River. As reported by (Horton 1945), the Rb value ranged between 2 (on the flat regions) and 4 (hilly or mountainous zones). This parameter is clearly indicating that the whole watershed has a hilly topographic condition.
4.1.8 Length of overland flow (L o)
It is the length of water flow over the ground before accumulating into the stream channel. Greater the values of Lo, lesser the surface runoff (Horton 1932). This has a significant relationship with physiographic and hydrological development of drainage basin (Javed et al. 2011). The range of Lo varies from 0.126 to 0.161 for the subwatersheds of Urmodi catchment. For whole Urmodi river watershed, it showed 0.138. From Table 4, it is clear that the subwatershed 7 has the highest value and therefore, the lowest runoff.
4.1.9 Rho coefficient (ρ)
It is a dimensionless linear parameter of morphometric analysis. This factor relates to the drainage composition and physiographic development of the drainage basin (Horton 1945). Rho coefficient (ρ) varies according to natural conditions of climate, geological, biological, geomorphic and anthropogenic activities (Thomas et al. 2010). Rho coefficients of respective subwatersheds are shown in Table 4. Minimum and maximum values of the rho coefficient for the subwatersheds of Urmodi River were 0.47 and 0.92, respectively. For the whole watershed, it has been found that the ρ value 0.75.
4.1.9.1 Constant of channel flow (C)
This factor is measured in km2/km, as it is inverse of Dd. Geology, relative relief and climate of the watershed shape the constant of channel flow (C) (Schumm 1956). Value of C factor gives the number of km2 of surface area, which needed to maintain one linear kilometre of the stream channel. As the value of C increases, the rock permeability also increases (Prabu and Baskaran 2013). Table 4 describes the C values of sub-basins and Urmodi basin. Under less vegetation condition, low C values minimize the Lo and thus water discharge is more rapid (Samal et al. 2015). For the present study, C value ranged from 0.252 to 0.323 km2/km. For the whole watershed, the C value was 0.276 km2/km.
4.1.9.2 Drainage density (Dd)
It is a linear morphometric parameter which is expressed in km/km2. Drainage density (Dd) is a sensitive indicator for the calculation of erosion by streams and the effect of characteristics at the outlet (Chandniha and Kansal 2017). This parameter also indicates the closeness of the channel spacing; hence, it provides the quantitative measurement of the average stream length for the whole watershed (Dikpal et al. 2017). In the present study, Dd for subwatersheds ranged from 3.10 to 3.97 km/km2. Dd for the Urmodi River watershed was 3.26 km/km2. Higher Dd shows more effective operations of stream incision; moreover, high incision is associated with steep slopes (Langbein 1947).
4.1.9.3 Drainage texture (T)
It is used to show the spacing of drainage lines (Smith 1950). This factor has a relationship with rock type and vegetation; massive and hard rock produces the coarse drainage texture whereas soft and weak rocks produce the fine texture. The value of T is for: coarse texture < 4; intermediate 4–10; fine 10–15 and; ultrafine/badland topography > 15 (Sreedevi et al. 2005). By considering the given categories, all the subwatersheds showed ultra-fine drainage texture, even though the Urmodi river watershed itself possesses the ultrafine texture.
4.1.9.4 Texture ratio (R t)
The Texture ratio (Rt) has been of a great importance in understanding the lithological infiltration capacity. The Rt values of subwatersheds of Urmodi River catchment range between 5.74 and 9.20. Hydrologically, the subwatershed 5 has longest basin lag time while, the subwatershed 6 has the shortest basin lag time. The Rt value of Urmodi River watershed is found to be 18.18.
4.2 Shape aspect
Five shape parameters, namely Basin shape (Bs), Circularity ratio (Rc), Compactness coefficient (Cc), Elongation ratio (Re), Form factor (Rf) and Relief aspect, were analysed for the subwatersheds and entire Urmodi River watershed. Shape parameters have an inverse relationship with soil loss.
4.2.1 Basin shape (B s)
Parameter Bs is related to the flood discharge (Javed et al. 2011). The Urmodi River watershed had a Bs value of 3.91. Sub-basins of Urmodi River watershed had Bs values between 2.70, for subwatershed 2, and 3.27, for the subwatershed 7. The subwatershed 2 is the one that produces more discharge, based on its shape, thus, having more proneness to erosion as compared to subwatershed 7, which has negative relationship to runoff, as the high Bs value is inversely proportional to low risk of erosion. So, the shape of subwatershed matters, as it relates both the runoff and the susceptibility to the erodibility.
4.2.2 Circularity ratio (R c)
The Rc is a dimensionless parameter. The maximum value attained by Rc is 1.0, when the watershed boundary approaches to near circle (Miller 1953). This parameter is influenced by stream frequency, LULC and geological structures, climate, slope and relief factors of the basin (Singh et al. 2013). The Urmodi river watershed has a value of 0.46, whereas all subwatersheds have a value between 0.49 and 0.73 (Table 5). Low circularity ratio shows elongated shape whereas higher values shows approaches near to circularity. Values of Rc > 0.60 were found in subwatershed 2 and subwatershed 6, which indicates predisposition to flood risk during the peak period of concentrated flood flow. The values of Rc reflect the stages of evolution of watersheds, the lower values indicate young phases and the higher values are related to the mature stages of watershed development (Thomas et al. 2010).
4.2.3 Compactness coefficient (C c)
The compactness coefficient (Cc) is used to investigate the relationship between hydrologic basins with exact circular basin having the same area (Javed et al. 2011). From point of view for the circular shaped basin, when we consider the drainage standpoint, it will produce the shortest time of concentration before peak flow takes place in the catchment (Javed et al. 2009). The highest value of Cc was found for the subwatershed 7 (1.426), and the lowest Cc value was found for the subwatershed 6 (1.167). The Cc value for the whole watershed was found to be 1.472. Table 5 shows the values for the other subwatersheds.
4.2.4 Elongation ratio (R e)
The elongation ratio (Re) is used to indicate the shape of the watershed. The Re varies from 0.6 to 1.0 over diverse geological and climatic conditions (Meshram and Sharma 2017). Re values of all subwatersheds has been shown in Table 5, in which values of: Re > 0.9 indicate the circular shape; Re > 0.9–0.8 are related to oval shape and; Re < 0.7 are less elongated shapes (Javed et al. 2009). The variations in values of Re are caused by the guiding effect of thrusting and faulting in the watershed. Higher the values of Re, higher the infiltration and thus lower the surface runoff. Low Re reflects the high soil erosion susceptibility and sedimentation load (Sreedevi et al. 2013). This means that, subwatershed 7 with Re value 0.62 carries more sediment load and the subwatershed 5 with Re value 0.70 carries less sediment load. For the entire Urmodi River watershed, the average Re values was found to be 0.57.
4.2.5 Form factor (R f)
Form factor and elongation ratio has a close and inverse relationship. As the value of Rf decreases, the elongativity of the basin will be increased. The value of Rf for the perfect circle is 0.7854. For circular basins, Rf values are higher and high peak flow rates for a shorter period; for the elongated basin, Rf has lower value, thus low peak flow for longer period of time (Javed et al. 2011). For the present study area, the Rf range remained between 0.31 and 0.38. Smaller value of Rf, more elongated the shape of the basin. The subwatershed 5 is more elongated as compared to all other subwatersheds. For the whole watershed, the Rf value was 0.26.
4.3 Relief aspect
The relief parameters, including Basin relief (Rh), Relief ratio (Rr), Ruggedness number (Rn), Melton Ruggedness number (MRn), Dissection index (Dis), are having a direct impact on soil erosion. For Urmodi River watershed, five relief components were computed for the whole basin and its sub-basins. The relief parameters have implications in summarizing the landforms, as well as the erosional and sedimentation properties of the watershed.
4.3.1 Basin relief (R h)
Basin relief (Rh) is the controlling factor of stream gradient and thus shapes the sediment transport and flood patterns (Hadley and Schumm 1961). Denudation attributes of the basin can be well understood by analysing this relief parameter (Sujatha et al. 2015). This relief aspect has a crucial role in assessing drainage development, surface, and sub-surface water flow, landform development, permeability, terrain erosional characteristics (Vincy et al. 2012). Urmodi river watershed showed the Rh value of 685 m. Table 6 shows the Rh values of the subwatersheds ranging from 467 to 602 m.
4.3.2 Relief ratio (R r)
The relief ratio (Rr) is a dimensionless parameter, which is a ratio of height to length. Rr factor describes the overall steepness of relief in the study region; this is an indicator to show erosion intensity taking place on a slope of the sub-basin (Kaliraj et al. 2015). Rr represents the high energy basin with strong erosion and high sedimentation yield (Sujatha et al. 2015). For the whole Urmodi watershed, the Rr value was 0.017. Table 6 describes the Rr values of the subwatersheds and the whole Urmodi River watershed. The range of Rr was between 0.029 and 0.060. High Rr values also reflect hilly region and low represent pediplain and valley region (Kadam et al.2017). The subwatershed 7 shows mainly the pediplain region and the upper Urmodi catchment indicates hilly region; it includes subwatershed 1 and subwatershed 3. Subwatersheds 2 and 5 had the same value that is 0.060, thus, generating nearly the same sediment load.
4.3.3 Ruggedness number (R n)
The structural complexity of the terrain can be indicated using the ruggedness number (Rn) parameter. Higher the Rn values, greater the erosion proneness and more susceptible to an increase peak discharge (Sreedevi et al. 2013). High values of Rn generated when drainage density and basin relief values are high. Ruggedness values are also slope dependent, which means slope steepness and length (Strahler 1958). High Rn indicates the more complex terrain conditions to erosion susceptibility (Samal et al. 2015). Subwatershed 7 presented the lowest Rn value (1.69) and the subwatershed 1 shows the highest Rn value (2.25). (Table 6) depicts the values of subwatersheds for the Rn parameter.
4.3.4 Melton Ruggedness number (MRn)
The Melton ruggedness number (MRn) is a specialized slope index used to evidence the relief ruggedness within the watershed (Melton 1965). MRn values of Urmodi watershed and subwatersheds are shown in Table 6. Low values of MRn signify the normal flow to Main River without heavy debris load (Soni 2017).
4.3.5 Dissection index (D is)
Normally, the values of Dis range between 0 and 1, where ‘0’ represents the total absence of vertical erosion and reflects flat terrain surface. And, ‘1’ represents a vertical cliff, escarpment of hill slope (Thomas et al. 2010). Dissection index of Urmodi River subwatersheds lies between 0.42 and 0.49 (Table 6). High value of Dis indicates the long and steep slopes with high degree of dissection and related to more proneness of terrain to the erosion susceptibility. Here, subwatershed 7 shows more susceptibility and the subwatershed 5 shows less susceptibility. The whole watershed shows the value of 0.54 for this factor. Table 7 illustrates the ratings of linearity, shape and relief pertaining to morphometric parameters with their respective rankings.
4.4 Land Use Land Cover analysis
Figure 4 shows the final output of LULC map prepared from the Sentinel 2 band processing in the GIS environment. Moreover, accuracy assessment was carried out with Overall Classification Accuracy of 85.83% and Kappa Statistics 0.81. The description of LULC classes is described below. The areas acquired by different cover are shown in Table 8.
Area having land utilization with annual and perennial crops and scattered rural settlement nearby, it is included in this class (Hassen and Assen 2018). Urmodi watershed is mainly a paddy cultivation area, especially in its hilly laterite terrain. We can generally observe paddy fields behind the reservoir. And towards the downward region of the dam, we can find other croplands like sugarcane, maize, wheat, etc. Agriculture fields were the second most dominant cover type which acquired 25.33% of the whole watershed (Table 8). The maximum agriculture activities were found in subwatershed 7 which has low relative relief and it is also the largest covered area out of seven subwatersheds. Lowest percentage of agricultural land was observed in the subwatershed 1, which is located in the upper highlands of the Urmodi River watershed.
In the present study area, a large reservoir and small catchment ponds were prominently present. The permanent river channel is also marked as a water body. As we can observe from Fig. 4, subwatersheds 1, 2 and 3 constitute 8.16 km2, 0.90 km2 and 6.58 km2 of the whole basin. Other subwatersheds are also having water bodies including river channels and small catchment structures. But for soil conservation purpose, in ranking criteria (Table 9), this category is excluded because of the absence of topsoil layer.
The areas with no or less vegetation cover are directly exposed to soil erosion and rock outcrop (Miheretu and Yimer 2018). Barren land occupies 88.28 km2, which is the third rank category of land cover. Barren land is most susceptible to water led soil erosion as there are no obstacles to runoff, such as vegetation. So, the sub-basins with the higher barren surface have to be given a higher ranking. Subwatershed 4 shows maximum soil loss risk due to its 21.43 km2 area, which is exposed to erosion and form barren conditions. Whereas to subwatershed 1 was given the lowest priority, as it contains only 6.88 km2 of barren land.
Basically, the permanent settlement of concrete rooftops, roads, and villages is accounted for the settlement land cover. Subwatersheds 4, 6 and 7 have a dense settlement zone; one of the reasons is the passing of National Highway 4. From soil conservation point of view, this cover has not been included in ranking due to absence of topsoil.
High densities of naturally grown trees are taken into this class. From visual interpretation and ground truthing, the area has been classified. The upper sub-catchments show the higher area of dense forest as this is a part of reserved forests. As the area of dense forest cover gets lowered into sub-basins, more land is exposed to drain. While ranking, the percentage of the land with the less dense forest was given as rank 1. Subwatersheds 7, show less area that is 13.56 km2 (12.19% of its own area) under this land cover class; for this reason, it needs to be ranked 1. LULC in the catchment also acts as an indicator for the environmental conditions and vulnerability to soil erosion. Incompatible land cover causes aggravation in soil erosion behaviour, which is among the main causes of land degradation (Chauhan et al. 2016). LULC is also applied as one of the main indicators used for watershed prioritization (Malik and Bhat 2014). Areas with vegetation cover along with their intricate root system are less prone to the impact of rainfall, as they bind to the topsoil (Nooka Ratnam et al. 2005).
LULC is a good indicator of land degradation at the catchment scale and has great importance in understanding the erosional behaviour. When the land cover alters the impact of rainfall on each land cover class, it also changes the surface runoff characteristics at the subwatershed level (Bagwan and Gavali 2020b). Along with the dense forest, LULC class, low density of tree canopy also can be considered as a separate class. It includes the bare soil with sparsely distributed tree cover. This type of land patch also includes the shrubs (Mariwah et al. 2017). As we have done the ranking of dense forest, likewise different vegetation classes follow proportionate ratings. Low vegetated and open forest areas, within the subwatershed, are needed to be given as top ranking. Subwatershed 7 has shown poor vegetation cover and hence need to be ranked one. Subwatershed 5 shows 9.41 km2 of open forest which is 41.01% of its own area, therefore it is ranked 7.
4.5 Integration of morphometric parameters and LULC ranking
As mentioned earlier, morphometric parameters and land cover have a close relationship and goes hand in hand. Drainage density, constant of channel maintenance, drainage texture, etc. are the some of the parameters which influence the erosion process. On the same side, if a land cover pattern gets altered, it will also affect the drainage pattern. The geomorphometric parameters along with LULC have great potential to optimally prioritize the soil and water conservation structure (Chauhan et al. 2016; Ahirwar et al. 2019).The dynamics between the drainage characteristics and surface land cover depict collective reflection of the impact of stream channels and anthropogenic activities across the watershed. Hence, there was need to integrate these two components. The linear and relief morphometric components of the morphometry are directly proportional to the erosional activity and hence were arranged in descending order. Whereas, the shape parameters are inversely proportional and were arranged in ascending order (Table 7). In the same way, Table 9 depicting the land use and land cover based on ranking show the two subwatersheds with the same compound value, i.e. 5.0 for the subwatershed 1 and subwatershed 3. So, based on the LULC-based prioritization both comes under the same ranking.
To avoid ambiguity, the compound value for ranking of subwatersheds with respective parameters of morphometry and LULC (Tables 7, 9) was integrated and averaged to come across a precise ranking arrangement as shown in Table 10. The area of barren land was highest in the subwatershed 4, which is also the most susceptible area to erosion. This because, its LULC priority highly influenced the ranking and thereby affected the integrated compound value. Lowest compound value is also an indication of alarming degradation.
We need focus on such area on priority basis to safeguard the soil from being washed out and implement the appropriate soil conservation measures. Moreover, if the morphometric parameters are showing the same compound value for subwatersheds, the confusion could be avoided by integrating other component like LULC to solve the priority issue between two subwatersheds. From the integration of compound values of morphometric and LULC, we got more accurate ranking as shown in Fig. 5 about the final ranking assignment of the subwatershed. The studies carried out in India to mitigate the soil erosion show that, there is need to opt for the geo-morphometric parameter-based prioritization and it is necessary to determine the appropriate soil conservation measures for the integrated watershed management and planning (Das 2014; Singh and Singh 2018).
5 Conclusion
The current study attempts to prioritize the subwatersheds of Urmodi River with the purpose of decision-taking and appropriation of soil conservation measures. The digital morphometric analysis of linearity, shape and relief aspects of Urmodi river watershed and its sub-basins helped to identify the geological, geomorphological and hydrological characteristics of the entire watershed. In case of soil erosion, not only one factor but the several prevailing conditions are responsible for contributing to the dynamics of the watershed. The high-resolution Sentinel 2 images have played a vital role in understanding LULC more accurately, along with its orthorectified nature. By analysing the geomorphological and land cover factors, we can control the degradation of soil resources. The compound values of each subwatershed for morphometric parameters and LULC can be used to solve the confusion in priority ranking when one of the parameters shows the same ranking. Therefore, for a better reflection of stream linked land surface cover conditions, we may use the compounded values, which are averages of the above mentioned two parameters to prioritize the subwatersheds. The compounded values also help to identify the vulnerability of each subwatershed. It has been revealed that the morphometric and LULC-based priorities are different but better and informed decisions can be arrived by integrating them. The subwatersheds in the upper catchment show the lowest ranking, while the lower catchment area indicated highest ranking priorities. Integrated rating also solved the confusion arising from equal ranking of subwatersheds, which may help us to prioritize soil conservation efforts. The present study will help the policymakers to develop a better and more scientific Catchment Area Treatment (CAT) plan. Land cover and morphometric analysis are also helpful in safeguarding the reservoir from siltation.
References
Ahirwar, R., Malik, M. S., & Shukla, J. P. (2019). Prioritization of sub-watersheds for soil and water conservation in parts of Narmada river through morphometric analysis using remote sensing and GIS. Journal of the Geological Society of India, 94(5), 515–524. https://doi.org/10.1007/s12594-019-1349-8.
Ahmed, R., Sajjad, H., & Husain, I. (2018). Morphometric parameters-based prioritization of sub-watersheds using fuzzy analytical hierarchy process: a case study of lower Barpani Watershed, India. Natural Resources Research, 27(1), 67–75. https://doi.org/10.1007/s11053-017-9337-4.
Avinash, K., Deepika, B., & Jayappa, K. S. (2014). Basin geomorphology and drainage morphometry parameters used as indicators for groundwater prospect: Insight from geographical information system (GIS) technique. Journal of Earth Science, 25(6), 1018–1032. https://doi.org/10.1007/s12583-014-0505-8.
Bagwan, W. A., & Gavali, R. S. (2020a). Correction to: An assessment of rainfall-induced land degradation condition using Erosivity Density (ED) and heatmap method for Urmodi River watershed of Maharashtra, India. Journal of Sedimentary Environments. https://doi.org/10.1007/s43217-020-00031-6.
Bagwan, W. A., & Gavali, R. S. (2020b). Delineating changes in soil erosion risk zones using RUSLE model based on confusion matrix for the Urmodi river watershed, Maharashtra, India. Modeling Earth Systems and Environment. https://doi.org/10.1007/s40808-020-00965-w.
Biswas, S., Sudhakar, S., & Desai, V. R. (1999). Prioritisation of subwatersheds based on morphometric analysis of drainage basin: A remote sensing and GIS approach. Journal of the Indian Society of Remote Sensing, 27(3), 155–166. https://doi.org/10.1007/BF02991569.
Bhattacharya, R. K., Das Chatterjee, N., & Das, K. (2019). Multi-criteria-based sub-basin prioritization and its risk assessment of erosion susceptibility in Kansai-Kumari catchment area, India. Applied Water Science, 9, 76. https://doi.org/10.1007/s13201-019-0954-4.
Central Ground Water Board (CGWB) (2013) Ground water information Satara District Maharashtra. Ministry of Water Resources, Govt. of India. Central Region, Nagpur 1798/DBR/2013
Chandniha, S. K., & Kansal, M. L. (2017). Prioritization of sub-watersheds based on morphometric analysis using geospatial technique in Piperiya watershed, India. Applied Water Science, 7(1), 329–338. https://doi.org/10.1007/s13201-014-0248-9.
Chauhan, P., Chauniyal, D. D., Singh, N., & Tiwari, R. K. (2016). Quantitative geo-morphometric and land cover-based micro-watershed prioritization in the Tons river basin of the lesser Himalaya. Environmental Earth Sciences, 75(6), 498. https://doi.org/10.1007/s12665-016-5342-x.
Choudhari, P. P., Nigam, G. K., Singh, S. K., & Thakur, S. (2018). Morphometric based prioritization of watershed for groundwater potential of Mula river basin, Maharashtra, India. Geology, Ecology, and Landscapes, 2(4), 256–267. https://doi.org/10.1080/24749508.2018.1452482.
Das, D. (2014). Identification of Erosion Prone areas by morphometric analysis using GIS. Journal of The Institution of Engineers India: Series A, 95, 61–74. https://doi.org/10.1007/s40030-014-0069-8.
Dikpal, R. L., Renuka Prasad, T. J., & Satish, K. (2017). Evaluation of morphometric parameters derived from Cartosat-1 DEM using remote sensing and GIS techniques for Budigere Amanikere watershed, Dakshina Pinakini Basin, Karnataka, India. Applied Water Science, 7(8), 4399–4414. https://doi.org/10.1007/s13201-017-0585-6.
Drusch, M., Del Bello, U., Carlier, S., Colin, O., Fernandez, V., Gascon, F., et al. (2012). Sentinel-2: ESA’s optical high-resolution mission for GMES operational services. Remote Sensing of Environment, 120, 25–36. https://doi.org/10.1016/j.rse.2011.11.026.
Fenta, A. A., Yasuda, H., Shimizu, K., Haregeweyn, N., & Woldearegay, K. (2017). Quantitative analysis and implications of drainage morphometry of the Agula watershed in the semi-arid northern Ethiopia. Applied Water Science, 7(7), 3825–3840. https://doi.org/10.1007/s13201-017-0534-4.
Hadley, R. F., & Schumm, S. A. (1961). Sediment sources and drainage basin characteristics in upper Cheyenne River basin. Water Supply. In Water Supply Paper: Series number: 1531. https://doi.org/10.3133/wsp1531
Hassen, E. E., & Assen, M. (2018). Land use/cover dynamics and its drivers in Gelda catchment, Lake Tana watershed, Ethiopia. Environmental Systems Research, 6(1), 4. https://doi.org/10.1186/s40068-017-0081-x.
Horton, R. E. (1932). Drainage-basin characteristics. Eos, Transactions American Geophysical Union. https://doi.org/10.1029/TR013i001p00350.
Horton, R. E. (1945). Erosional development of streams and their drainage basins; Hydrophysical approach to quantitative morphology. Bulletin of the Geological Society of America. https://doi.org/10.1130/0016-7606(1945)56[275:EDOSAT]2.0.CO;2.
IUCN. (2012). IUCN evaluation of nomination of natural and mixed properties to the world heritage list. WHC-12/36.COM/INF.8B2. https://whc.unesco.org/archive/2012/whc12-36com-8B2inf-en.pdf
Javed, A., Khanday, M. Y., & Ahmed, R. (2009). Prioritization of sub-watersheds based on morphometric and land use analysis using remote sensing and GIS techniques. Journal of the Indian Society of Remote Sensing, 37(2), 261–274. https://doi.org/10.1007/s12524-009-0016-8.
Javed, A., Khanday, M. Y., & Rais, S. (2011). Watershed prioritization using morphometric and land use/land cover parameters: A remote sensing and GIS based approach. Journal of the Geological Society of India, 78(1), 63–75. https://doi.org/10.1007/s12594-011-0068-6.
Kadam, A., Jaweed, T., Urmikar, B., Hussain, K., & Sankhua, R. (2017). Morphometric prioritization of semi-arid watershed for plant growth potential using GIS technique. Modeling Earth Systems and Environment. https://doi.org/10.1007/s40808-017-0386-9.
Kaliraj, S., Chandrasekar, N., & Magesh, N. S. (2015). Morphometric analysis of the River Thamirabarani sub-basin in Kanyakumari District, South west coast of Tamil Nadu, India, using remote sensing and GIS. Environmental Earth Sciences, 73(11), 7375–7401. https://doi.org/10.1007/s12665-014-3914-1.
Khadse, G. K., Vijay, R., & Labhasetwar, P. K. (2015). Prioritization of catchments based on soil erosion using remote sensing and GIS. Environmental Monitoring and Assessment, 187(6), 333. https://doi.org/10.1007/s10661-015-4545-z.
Khanday, M. Y., & Javed, A. (2016). Spatio-temporal land cover changes in a semi-arid watershed: Central India. Journal of the Geological Society of India, 88(5), 576–584. https://doi.org/10.1007/s12594-016-0523-5.
Langbein, W.B. (1947). Topographic Characteristics of Drainage Basins. US Geol Soc Water Supply Pap 968-C.
Malik, M. I., & Bhat, M. S. (2014). Integrated approach for prioritizing watersheds for management: A study of Lidder Catchment of Kashmir Himalayas. Environmental Management, 54(6), 1267–1287. https://doi.org/10.1007/s00267-014-0361-4.
Mariwah, S., Osei, K. N., & Amenyo-Xa, M. S. (2017). Urban land use/land cover changes in the Tema metropolitan area (1990–2010). GeoJournal, 82(2), 247–258. https://doi.org/10.1007/s10708-015-9672-0.
Melton, M. A. (1965). The geomorphic and paleoclimatic significance of alluvial deposits in Southern Arizona. The Journal of Geology. https://doi.org/10.1086/627044.
Meshram, S. G., & Sharma, S. K. (2017). Prioritization of watershed through morphometric parameters: A PCA-based approach. Applied Water Science, 7(3), 1505–1519. https://doi.org/10.1007/s13201-015-0332-9.
Miheretu, B. A., & Yimer, A. A. (2018). Land use/land cover changes and their environmental implications in the Gelana sub-watershed of Northern highlands of Ethiopia. Environmental Systems Research, 6(1), 7. https://doi.org/10.1186/s40068-017-0084-7.
Miller, V. (1953). A quantitative geomorphologic study of drainage basin characteristics in the clinch mountain area. In Technical Report. 3 Virginia and Tennessee. Department of Geology — Columbia University.
National Institute of Soil Bureau and Land Use Planning (NBSS & LUP). (2002). Soil erosion Maharashtra, Technical Bulletin, NBSS Publ. 82. NBSS & LUP, Nagpur
Nooka Ratnam, K., Srivastava, Y. K., Venkateswara Rao, V., Amminedu, E., & Murthy, K. S. R. (2005). Check Dam positioning by prioritization micro-watersheds using SYI model and morphometric analysis—remote sensing and GIS perspective. Journal of the Indian Society of Remote Sensing. https://doi.org/10.1007/BF02989988.
Pandey, P. K., & Das, S. S. (2016). Morphometric analysis of Usri River basin, Chhotanagpur Plateau, India, using remote sensing and GIS. Arabian Journal of Geosciences. https://doi.org/10.1007/s12517-015-2287-4.
Pophare, A. M., & Balpande, U. S. (2014). Morphometric analysis of Suketi river basin, Himachal Himalaya, India. Journal of Earth System Science, 123(7), 1501–1515. https://doi.org/10.1007/s12040-014-0487-z.
Prabhakaran, A., & Jawahar Raj, N. (2018). Drainage morphometric analysis for assessing form and processes of the watersheds of Pachamalai hills and its adjoinings, Central Tamil Nadu, India. Applied Water Science, 8(1), 31. https://doi.org/10.1007/s13201-018-0646-5.
Prabhakar, A. K., Singh, K. K., Lohani, A. K., et al. (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-z.
Prabu, P., & Baskaran, R. (2013). Drainage morphometry of upper Vaigai river sub-basin, Western Ghats, South India using remote sensing and GIS. Journal of the Geological Society of India, 82(5), 519–528. https://doi.org/10.1007/s12594-013-0183-7.
Praveen, B., Talukdar, S., Shahfahad, et al. (2020). Analyzing trend and forecasting of rainfall changes in India using non-parametrical and machine learning approaches. Scientific Reports, 10, 10342. https://doi.org/10.1038/s41598-020-67228-7.
Sahu, N., Obi Reddy, G. P., Kumar, N., Nagaraju, M. S. S., Srivastava, R., & Singh, S. K. (2017). Morphometric analysis in basaltic Terrain of Central India using GIS techniques: a case study. Applied Water Science, 7(5), 2493–2499. https://doi.org/10.1007/s13201-016-0442-z.
Samal, D. R., Gedam, S. S., & Nagarajan, R. (2015). GIS based drainage morphometry and its influence on hydrology in parts of Western Ghats region, Maharashtra, India. Geocarto International. https://doi.org/10.1080/10106049.2014.978903.
Sarma, S., & Saikia, T. (2012). Prioritization of sub-watersheds in Khanapara-Bornihat area of Assam-Meghalaya (India) based on land use and slope analysis using remote sensing and GIS. Journal of the Indian Society of Remote Sensing, 40(3), 435–446. https://doi.org/10.1007/s12524-011-0163-6.
Schumm, S. A. (1956). Evolution of drainage systems and slopes in badlands at Perth Amboy. New Jersey: Bulletin of the Geological Society of America. https://doi.org/10.1130/0016-7606(1956)67[597:EODSAS]2.0.CO;2.
Singh, P., Thakur, J. K., & Singh, U. C. (2013). Morphometric analysis of Morar River Basin, Madhya Pradesh, India, using remote sensing and GIS techniques. Environmental Earth Sciences, 68(7), 1967–1977. https://doi.org/10.1007/s12665-012-1884-8.
Singh, O., & Singh, J. (2018). Soil erosion susceptibility assessment of the lower Himachal Himalayan Watershed. Journal of the Geological Society of India, 92, 157–165. https://doi.org/10.1007/s12594-018-0975-x.
Smith, K. G. (1950). Standards for grading texture of erosional topography. American Journal of Science. https://doi.org/10.2475/ajs.248.9.655.
Soni, S. (2017). Assessment of morphometric characteristics of Chakrar watershed in Madhya Pradesh India using geospatial technique. Applied Water Science, 7(5), 2089–2102. https://doi.org/10.1007/s13201-016-0395-2.
Sreedevi, P. D., Sreekanth, P. D., Khan, H. H., & Ahmed, S. (2013). Drainage morphometry and its influence on hydrology in an semi arid region: using SRTM data and GIS. Environmental Earth Sciences, 70(2), 839–848. https://doi.org/10.1007/s12665-012-2172-3.
Sreedevi, P. D., Subrahmanyam, K., & Ahmed, S. (2005). The significance of morphometric analysis for obtaining groundwater potential zones in a structurally controlled terrain. Environmental Geology, 47(3), 412–420. https://doi.org/10.1007/s00254-004-1166-1.
Strahler, A. N. (1958). Dimensional analysis applied to fluvially eroded landforms. Bulletin of the Geological Society of America. https://doi.org/10.1130/0016-7606(1958)69[279:DAATFE]2.0.CO;2.
Strahler, A. N. (1957). Quantitative analysis of watershed geomorphology. Transactions, American Geophysical Union 38(6), 913. https://doi.org/10.1029/TR038i006p00913
Strahler, A. N. (1964). Quantitative geology of drainage basins and channel networks. In (Chow, V. T. editor). Handbook of Applied Hydrology, 4, 39–76, McGraw-Hill Book Co.
Sujatha, E. R., Selvakumar, R., Rajasimman, U. A. B., & Victor, R. G. (2015). Morphometric analysis of sub-watershed in parts of Western Ghats, South India using ASTER DEM. Geomatics, Natural Hazards and Risk. https://doi.org/10.1080/19475705.2013.845114.
Thakkar, A. K., & Dhiman, S. D. (2007). Morphometric analysis and prioritization of miniwatersheds in Mohr watershed, Gujarat using remote sensing and GIS techniques. Journal of the Indian Society of Remote Sensing, 35(4), 313–321. https://doi.org/10.1007/BF02990787.
Thomas, J., Joseph, S., & Thrivikramaji, K. P. (2010). Morphometric aspects of a small tropical mountain river system, the southern Western Ghats, India. International Journal of Digital Earth, 3(2), 135–156. https://doi.org/10.1080/17538940903464370.
Vemu, S., & Udayabhaskar, P. (2010). An integrated approach for prioritization of reservoir catchment using remote sensing and geographic information system techniques. Geocarto International, 25(2), 149–168. https://doi.org/10.1080/10106040903015798.
Vincy, M. V., Rajan, B., & Pradeepkumar, A. P. (2012). Geographic information system–based morphometric characterization of sub-watersheds of Meenachil river basin, Kottayam district, Kerala, India. Geocarto International, 27(8), 661–684. https://doi.org/10.1080/10106049.2012.657694.
Acknowledgements
The first author is thankful to the School of Earth Sciences, Punyashlok Ahilyadevi Holkar Solapur University, Solapur (Formerly Solapur University, Solapur) (Letter no. SUS/BCUD/PGBUTR/2014-15/12298 dated 10 Mar 2015) for their financial support in the form of Departmental Research Fellowship (DRF). The authors are thankful to the Survey of India (SOI) office at Pune for providing toposheets. We are also thankful to the European Space Agency’s Copernicus Hub portal for providing high-resolution Sentinel 2 imagery.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest or competing interest.
Additional information
Communicated by M. V. Alves Martins
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Bagwan, W.A., Gavali, R.S. An Integrated Approach for the Prioritization of Subwatersheds in the Urmodi River Catchment (India) for Soil Conservation using Morphometric and Land Use Land Cover (LULC) factors. J. Sediment. Environ. 6, 39–56 (2021). https://doi.org/10.1007/s43217-020-00041-4
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s43217-020-00041-4