Towards Sustainable Development: Ranking of Soil Erosion-Prone Areas Using Morphometric Analysis and Multi-Criteria Decision-Making Techniques

Sub-watershed prioritization using morphometric analysis and multi-criteria decision-making (MCDM) techniques is a systematic approach to identifying and ranking sub-watersheds based on their susceptibility to soil erosion. This helps in implementing targeted soil conservation measures. In this study, sub-watersheds in the Narangi basin are prioritized by employing morphometric analysis integrated with advanced MCDM techniques, including additive ratio assessment (ARAS), complicated proportional assessment (COPRAS), multi-objective optimization by ratio analysis (MOORA), and the technique for order preference by similarity to ideal solution (TOPSIS). Weights for various MCDM methods are determined using the criteria importance through an inter-criteria correlation approach (CRITIC: criteria importance through inter-criteria correlation method), while geospatial techniques ensure precise spatial analysis. The results provide a unified ranking of sub-watersheds, revealing that sub-watershed 3 (SW3) and SW9 are in the high-priority soil erosion category; SW1, SW2, SW5, and SW8 are medium-priority; and SW4, SW6, SW7, and SW10 are low-priority. This comprehensive and sustainability-oriented approach equips decision-makers with robust tools to identify and manage sub-watersheds at risk of soil erosion, ensuring the long-term sustainability of land and water resources. This study aligns with sustainable development goal 15 (life on land) and promotes sustainable land use practices to combat soil degradation.

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Publication Details

Journal
Sustainability
Published
2025-03-01
DOI
https://doi.org/10.3390/su17052124
Citations
17
Primary Topic
Soil and Land Suitability Analysis
Type
article
Field-Weighted Citation Impact
41.17
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article

Towards Sustainable Development: Ranking of Soil Erosion-Prone Areas Using Morphometric Analysis and Multi-Criteria Decision-Making Techniques

Kaleem Mehmood, Aneesh Mathew, Padala Raja Shekar, Mohamed Zhran et al.
17 citations
Sustainability
Soil and Land Suitability Analysis
41.17
article

Towards Sustainable Development: Ranking of Soil Erosion-Prone Areas Using Morphometric Analysis and Multi-Criteria Decision-Making Techniques

Kaleem Mehmood, Aneesh Mathew, Padala Raja Shekar, Mohamed Zhran, Fahdah Falah Ben Hasher
article en
17 citations

Abstract

Sub-watershed prioritization using morphometric analysis and multi-criteria decision-making (MCDM) techniques is a systematic approach to identifying and ranking sub-watersheds based on their susceptibility to soil erosion. This helps in implementing targeted soil conservation measures. In this study, sub-watersheds in the Narangi basin are prioritized by employing morphometric analysis integrated with advanced MCDM techniques, including additive ratio assessment (ARAS), complicated proportional assessment (COPRAS), multi-objective optimization by ratio analysis (MOORA), and the technique for order preference by similarity to ideal solution (TOPSIS). Weights for various MCDM methods are determined using the criteria importance through an inter-criteria correlation approach (CRITIC: criteria importance through inter-criteria correlation method), while geospatial techniques ensure precise spatial analysis. The results provide a unified ranking of sub-watersheds, revealing that sub-watershed 3 (SW3) and SW9 are in the high-priority soil erosion category; SW1, SW2, SW5, and SW8 are medium-priority; and SW4, SW6, SW7, and SW10 are low-priority. This comprehensive and sustainability-oriented approach equips decision-makers with robust tools to identify and manage sub-watersheds at risk of soil erosion, ensuring the long-term sustainability of land and water resources. This study aligns with sustainable development goal 15 (life on land) and promotes sustainable land use practices to combat soil degradation.

SustainabilityVol. 17(5)
Princess Nourah bint Abdulrahman University (SA), National Institute of Technology Tiruchirappalli (IN), Mansoura University (EG), University of Swat (PK)
Openalex Percentile: Top 0%
Soil and Land Suitability Analysis
41.17
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