The development of comprehensive soil conservation strategies, based on the soil erosion risk, is one of the critical components of sustainable river basin management, especially in tropical mountainous regions. The present study computes the spatially distributed longtime average annual soil loss (A) and sediment yield (SY) and prioritizes the soil erosion risk in a tropical mountain river basin. The Revised Universal Soil Loss Equation (RUSLE) and the sediment delivery distributed model (SEDD) models were coupled in the GIS environment to predict the intra-basin variability of the A and SY of the Karimpuzha River Basin (KRB) of the southern Western Ghats (in Kerala, India). The results indicate that, on an average basis, 9.3 t of soil has been eroded per hectare per year, whereas the SY is 6.3 t ha-1 y-1 (i.e., approximately two-thirds of the gross soil erosion). The SY of the majority (74.2%) of the basin area is low (i.e., ≤ 5.0 t ha-1 y-1), whereas the soil erosion and transport processes are a major concern in some areas (ca. 6.3 km2). The results imply the significance of land use/ land cover, rainfall, and topography in controlling the soil erosion risk of the basin. The study demonstrates the advantages of the delineation of the critical erosion areas, based on the hydrologic response units (HRUs) of the basin, to implement appropriate soil erosion management options for conservation of the soil resources. 

Soil erosion and sediment yield modeling in a tropical mountain watershed of the southern Western Ghats, India using RUSLE and geospatial tools

Assessing soil erosion risk in Meghalaya, India: integrating geospatial data with RUSLE model

ABSTRACT Morphometric analysis of a drainage basin along with its stream network is indispensable for analysing a river basin’s prevailing geomorphology, geo-hydrology, and erosional susceptibility. In this study, an enhanced morphometric evaluation method using Google Earth Engine (GEE) and Principal Component Analysis (PCA) was used to assess and prioritize 12 sub-basins of the Godavari River basin (GRB), India, based on their erosional susceptibility. The findings of erosional susceptibility were validated using the Sediment Yield (SY) model. Our findings highlight that the sub-basins of Indravati, Pranhita, and Manjira, i.e. 42.42% (132707.4 km2) of the entire GRB are at high risk of erosional susceptibility, requiring immediate implementation of soil conservation measures. Our findings also highlight that 52.71% of the GRB is in the mature stage of geological evolution, wherein erosional landform-building processes are still ongoing. Overall, GRB has a relatively low drainage density with dendritic drainage patterns, permeable soils, and elongated sub-basins of enhanced erosional susceptibility. Moreover, the results of the SY model exhibited 90% agreement with the results of the enhanced morphometric analysis. This study presents an efficient framework for enhanced morphometric analysis that can assist policymakers in the demarcation of priority zones for erosional susceptibility.

Enhanced morphometric analysis for soil erosion susceptibility mapping in the Godavari river basin, India: leveraging Google Earth Engine and principal component analysis

Today, watersheds have changed under the influence of various environmental and human factors, and their expected performance has decreased in terms of meeting human needs, providing natural responses, and reducing environmental risks. However, evaluating health status and its impact on various factors has not been given enough attention. To this end, an attempt has been made to evaluate the health and ecological security of the sub‐watersheds of the Sharghonj Watershed using the pressure‐state‐response approach emphasizing flood‐related issues in the region. Towards that, 21 preliminary hydrological, anthropogenic, natural, and climatic criteria were selected. The preliminary variables were then finalized based on the results of the collinearity test and the data availability. The final variables were appropriately allocated to pressure, state, and response indices, and associated health and ecological security indices were determined at the sub‐watershed scale. The results showed that the pressure, state, and response ranged from 0.56 to 0.86, 0.46 to 0.84, and 0.35 to 0.96, respectively. Health and ecological security also varied from 0.53 to 0.83 and 0.27 to 1.01 in different sub‐watersheds. Eventually, the weighted mean pressure, state, and response indices for the Sharghonj Watershed were 0.72, 0.67, and 0.73, respectively. The weighted mean health and ecological security indices were 0.70 and 0.68, respectively. The research results indicated that the dynamic of various variables related to floods considerably affects the health of the Sharghonj Watershed. It could be concluded from the results that the Sharghonj Watershed is highly flood‐susceptible, whose health and ecological security status was mainly controlled by the damages due to the destruction of residences and orchards by floods in the past years. The results of the current study provide an appropriate roadmap to the decision makers and planners for the better management of the watershed resources in the region through allocating adequate financial support and implementation measures to priority sub‐watersheds.This article is protected by copyright. All rights reserved.

Flood‐Oriented Watershed Health and Ecological Security Conceptual Modeling using PSR Approach for the Sharghonj Watershed, South Khorasan Province, Iran

Groundwater quality assessment using machine learning models: a comprehensive study on the industrial corridor of a semi-arid region

Using algorithmic game theory to improve supervised machine learning: A novel applicability approach in flood susceptibility mapping.

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Using algorithmic game theory to improve supervised machine learning: A novel applicability approach in flood susceptibility mapping.