Prioritization of Watershed Using Remote Sensing and Geographic Information System

• Published in: Sustainability Vol. 13; no. 16; p. 9456
• Main Authors: Kumar, Devendra, Dhaloiya, Arvind, Nain, Ajeet Singh, Sharma, Mahendra Paal, Singh, Amandeep
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.08.2021
• Subjects: Agricultural land; Best management practices; Control; Digital Elevation Models; Drainage patterns; Environmental aspects; Erosion control; Geographic information systems; India; Land cover; Land use; Landslides; Management; Natural resource management; Natural resources; Organic matter; Organic soils; Rainfall; Rainfall-runoff relationships; Remote sensing; Resource conservation; Resource management; Risk factors; Slopes; Soil conservation; Soil erosion; Soil properties; Soil texture; Texture; Water; Watersheds; India
• ISSN: 2071-1050; 2071-1050
• DOI: 10.3390/su13169456

Soil erosion is becoming a major concern at the watershed scale for the environment, natural resources, and sustainable resource management. Therefore, the estimation of soil loss through this phenomenon and the identification of critical soil erosion-prone areas are considered to be key tasks in the soil conservation programme for the design and implementation of best management practices for specific regions or areas. In the present study, revised universal soil loss equation (RUSLE) modelling is combined with remote sensing (RS) and geographical information system (GIS) techniques and used to predict soil erosion and the prioritization of watersheds in Nainital district Uttarakhand, India. For the estimation of soil loss, different factors, namely, rainfall-runoff erosivity (R) factor, soil erodability (K) factor, slope length steepness (LS) factor, cover management (C) factor, and the erosion control practices (P) factor were computed. The data on various other aspects such as land use/land cover (LU/LC), the digital elevation model (DEM), slope, contours, drainage network, soil texture, organic matter, and rainfall were integrated to prepare a database for the RUSLE equation by employing ENVI & QGIS software. The results showed that a major portion (70.26%) of Nainital district is covered with forest, followed by area under fallow and agricultural land. Annual average soil loss ranged between 20 to 80 t ha−1 yr−1 in the study area. Out of 50 watersheds in the study area, 7 watersheds were given top priority for conserving natural resources, while 11 watersheds, mostly in the east-central part of Nainital, were kept under the next priority category. Only 4 watersheds of the total were given lowest priority. Moreover, it was concluded that major portions of Nainital district were in a severely prone category of soil erosion, and therefore required immediate action plans to check soil erosion and evade the possibility of landslides.