Spatial and temporal estimation of soil loss for the sustainable management of a wet semi-arid watershed cluster

Abstract

The ungauged wet semi-arid watershed cluster, Seethagondi, lies in the Adilabad district of Telangana in India and is prone to severe erosion and water scarcity. The runoff and soil loss data at watershed, catchment, and field level are necessary for planning soil and water conservation interventions. In this study, an attempt was made to develop a spatial soil loss estimation model for Seethagondi cluster using RUSLE coupled with ARCGIS and was used to estimate the soil loss spatially and temporally. The daily rainfall data of Aphrodite for the period from 1951 to 2007 was used, and the annual rainfall varied from 508 to 1351 mm with a mean annual rainfall of 950 mm and a mean erosivity of 6789 MJ mm ha(-1) h(-1) year(-1). Considerable variation in land use land cover especially in crop land and fallow land was observed during normal and drought years, and corresponding variation in the erosivity, C factor, and soil loss was also noted. The mean value of C factor derived from NDVI for crop land was 0.42 and 0.22 in normal year and drought years, respectively. The topography is undulating and major portion of the cluster has slope less than 10°, and 85.3% of the cluster has soil loss below 20 t ha(-1) year(-1). The soil loss from crop land varied from 2.9 to 3.6 t ha(-1) year(-1) in low rainfall years to 31.8 to 34.7 t ha(-1) year(-1) in high rainfall years with a mean annual soil loss of 12.2 t ha(-1) year(-1). The soil loss from crop land was higher in the month of August with an annual soil loss of 13.1 and 2.9 t ha(-1) year(-1) in normal and drought year, respectively. Based on the soil loss in a normal year, the interventions recommended for 85.3% of area of the watershed includes agronomic measures such as contour cultivation, graded bunds, strip cropping, mixed cropping, crop rotations, mulching, summer plowing, vegetative bunds, agri-horticultural system, and management practices such as broad bed furrow, raised sunken beds, and harvesting available water using farm ponds and percolation tanks. This methodology can be adopted for estimating the soil loss from similar ungauged watersheds with deficient data and for planning suitable soil and water conservation interventions for the sustainable management of the watersheds.

Integrated watershed management: evolution, development and emerging trends

“…Recently, there have been many studies of watershed decision-making support systems designed for various purposes, such as water supply (Koutsoyiannis et al 2003;Ghahraman and Sepaskhah 2004;Chung et al 2008), soil conservation (Rahman et al 2009;Markose and Jayappa 2016;Rejani et al 2016), pollution (Djodjic et al 2002;Santhi et al 2006;Ouyang et al 2007), sustainable resource development (Smith et al 2003;Prodanovic and Simonovic 2010;Weng et al 2010;Mocanu et al 2013), the impact of land-use change (Engel et al 2003;Mango et al 2011), and stakeholder analysis in integrated watershed management (Luyet et al 2012;Mutekanga et al 2013). User-friendly decision support systems (DSS) are needed to help watershed managers and planners develop, understand, and evaluate alternative watershed management strategies, while accounting for the interests and goals of several stakeholders (Loucks et al 2005).…”

Spatial and Temporal Variation of C– Factor and Soil Erosion in a Semi-Arid Watershed: A Case Study in Mahabubnagar District

“…Its value varies from 0 to 1, for good conservation practice to poor conservation practice. For the proposed study, the P factor was derived from the land use, land cover map and the support practices, followed in the selected area (Reddy et al, 2005;Rejani et al, 2016). In the selected semi-arid watershed area, contour cultivation has been followed as a soil conservation method and hence the value of P factor was considered as 0.39.…”

“…Earlier researchers have used various models for estimating soil loss at catchment, regional and global scales such as Universal Soil Loss Equation (USLE), Revised Universal Soil Loss Equation (RUSLE), Water Erosion Prediction Project (WEPP), Soil and Water Assessment tool (SWAT), Agricultural Non-Point Source Pollution Model (AGNPS).The RUSLE has been widely adopted for soil loss estimation at the watershed scale, because of its convenience in computation and application (Balasubramani et al, 2015).Although, it is an empirical model, the combined use of remote sensing, Geographical Information System (GIS) and RUSLE techniques makes soil erosion estimation and its spatial distribution feasible within reasonable costs and better accuracy, in larger areas (Rejani et al, 2016).RUSLE computes the average annual soil loss from the catchment using factors, such as rainfall runoff erosivity (R), soil erodibility (K), topography(LS), cover management(C) and conservation practice(P).The present study focuses on the estimation of spatial and temporal variation of C-factor and soil erosion in a semi-arid watershed of Mahabubnagar district, using RUSLE coupled with GIS and its application, for the sustainable management of the watershed.…”

Land Use Change Impact on Flooding Areas: The Case Study of Cervaro Basin (Italy)

“…In recent years, numerous researchers have shown interest in applying geographical information system (GIS) and remote sensing imagery to the extraction of land surface parameters [6], which, if applied to hydrological models, can be useful to obtain reasonable results-especially in ungauged basins [7]. Incorporating processed satellite data within hydrological models has become a promising approach for better and accurate quantifications of water resources in river basins [8,9].…”