GIS integrated RUSLE model-based soil loss estimation and watershed prioritization for land and water conservation aspects

Abstract

Land degradation has become one of the major threats throughout the globe, affecting about 2.6 billion people in more than 100 countries. The highest rate of land degradation is in Asia, followed by Africa and Europe. Climate change coupled with anthropogenic activities have accelerated the rate of land degradation in developing nations. In India, land degradation has affected about 105.48 million hectares. Thus, modeling and mapping soil loss, and assessing the vulnerability threat of the active erosional processes in a region are the major challenges from the land and water conservation aspects. The present study attempted rigorous modeling to estimate soil loss from the Banas Basin of Rajasthan state, India, using GIS-integrated Revised Universal Soil Loss Equation (RUSLE) equation. Priority ranking was computed for different watersheds in terms of the degree of soil loss from their catchments, so that appropriate conservation measures can be implemented. The total area of Banas basin (68,207.82 km2) was systematically separated into 25 watersheds ranging in area from 113.0 to 7626.8 km2. Rainfall dataset of Indian Meteorological Department for 30 years (1990–2020), FAO based Soil map for soil characterization, ALOS PALSAR digital elevation model for topographic assessment, and Sentinal-2 based land use and land cover map were integrated for modeling and mapping soil erosion/loss risk assessment. The total annual soil loss in the Banas basin was recorded as 21,766,048.8 tons. The areas under very low (0–1 t ha-1 year-1), low (1–5 t ha-1 year-1), medium (5–10 t ha-1 year-1), high (10–50 t ha-1 year-1) and extreme (>50 t ha-1 year-1) soil loss categories were recorded as 24.2, 66.8, 7.3, 0.9, and 0.7%, respectively, whereas the respective average annual soil loss values were obtained as 0.8, 3.0, 6.0, 23.1, and 52.0 t ha-1 year-1. The average annual soil loss among different watersheds was recorded in the range of 1.1–84.9 t ha-1 year-1, being highest (84.9 t ha-1 year-1) in WS18, followed by WS10 (38.4 t ha-1 year-1), SW25 (34.7 t ha-1 year-1) and WS23 (17.9 t ha-1 year-1), whereas it was lowest for WS8 (1.1 t ha-1 year-1). Thus, WS18 obtained the highest/top priority rank in terms of the average annual soil loss (84.9 t ha-1 year-1) to be considered as the first priority for land and water conservation planning and implementation. The quantitative results of this study would be useful for implementation of land and water conservation measures in the problematic areas of the Banas basin for controlling soil loss through water erosion.

Soil Erosion Hazard Zonation in Bandu Sub-Watershed, India

“…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). Hence, Bandu sub-watershed prioritization and its soil loss estimation can be a reference work for the researcher in similar physical environment.…”

Assessing Soil Erosion Susceptibility Using Revised Morgan-Morgan-Finney Model: A Case Study from Kulekhani Watershed, Makawanpur, Nepal

“…The study determined that 66.48% of the area posed very low and low soil erosion risk, 30.55% presented moderate and moderately high erosion risk, 2.86% exhibited high erosion risk, and 0.08% showcased very high erosion risk, aligning with the current study′s findings. Another study conducted by Singh et al (2023) evaluated the total annual soil loss in the Banas basin (encompassing an area of 6.82 million hectares) as 21.766 million tons. Maximum soil loss occurred in the extreme soil loss category (>50 t ha –1 yr –1 ) at 52 t ha –1 yr –1 , while the minimum was in the low soil loss category (0–1 t ha –1 yr –1 ) at 0.8 t ha –1 yr –1 .…”

Fluvial Geomorphological Changes in the Moribund Deltaic Region of Eastern India using remote sensing and GIS techniques

“…The sinuosity index (P) compares straight and meandering channels. It's the channel length divided by the valley length or slope ratio (Singh et al 2023). Leopold et al (1964) used sinuosity index for distinguishing the river in sinuous and meandering.…”