Prioritization of Watershed Using Remote Sensing and Geographic Information System

Abstract

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.

Soil Erosion Hazard Zonation in Bandu Sub-Watershed, India

“…Another study performed in lower Sutlej sub-basin of Punjab, India showed that about 94.4 % and 4.7 % of the total area suffered from very slight erosion (0-5 tonne/hectare/year) and slight erosion (5-10 tonne/hectare/year), respectively, whereas 0.11 % area experienced very severe soil loss (> 25 tonne/hectare/year) that is very similar to the present study (Sharma et al, 2022). A new study performed using a revised universal soil loss equation method in Nainital district, Uttarakhand, India revealed the annual average soil loss ranged between 20 to 80 tonne/hectare/year in the study area which has a similarity with the present result (Kumar et al, 2021). A study conducted in the Banas basin of Rajasthan of India reflects that 90 % area has under 0-10 tonne/hectare/year soil loss category (Singh et al, 2023).…”

Flood-based critical sub-watershed mapping: comparative application of multi-criteria decision making methods and hydrological modeling approach

“…Watersheds are one of the best spatial systems for managing water and soil resources (Gajbhiye et al 2013;Kumar et al 2021) which for better management of this system is divided into homogeneous hydrological units or SWs (Aher et al 2014;Lin et al 2020). The effects of SWs on each other can be more important in FGP (Avand et al 2021), which shows the importance of prioritizing SWs.…”

Land use / land cover change detection and forecasting using GEE and hybrid Markov-CA model in the Nainital, a district of Uttarakhand State, India

“…Previous research revealed a number of issues with data quality, classi er accuracy and data validation. Additionally, it appears from the literature that no research has been done to look into changes in LU/LC patterns and their prediction in the study area [20].Finally, machine learning Random Forest classi er is used to get high accuracy. The results of the study are used to identify the critical elements that affect LU/LC dynamics and improve land use policy for sustainable land use planning and development.…”