Prioritization of soil erosion-prone sub-watersheds using fuzzy-based multi-criteria decision-making methods in Narmada basin watershed, India

Meshram, Sarita Gajbhiye; Tirivarombo, Sithabile; Meshram, Chandrashekhar; Alvandi, Ehsan

doi:10.1007/s13762-022-04044-8

Cited by 17 publications

(5 citation statements)

References 36 publications

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“…Land use and land cover (LULC) and NDVI data were acquired using Sentinel-2 satellite imagery and supervised image classification, six classes -glaciers, water bodies, agricultural land, vegetation cover, and built-up areas -were identified (Belazreg et al 2023;Bandyopadhyay et al 2023;Meshram et al 2023). Lithology layer ws created using the geological survey data in ArcGIS (Farhat et al 2023;Mushtaq et al 2023), while soil type layer was generated from the Food and Agriculture Organization (FAO) shape files.…”

Section: Data Collection and Preprocessingmentioning

confidence: 99%

Hazards profile of the Shigar Valley, Central Karakoram, Pakistan: Multicriteria hazard susceptibility assessment

Afreen,

Haq,

Mark

2024

Auc Geographica

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The rapid deglaciation in the Upper Indus Basin (UIB) significantly impacts local landscapes, watersheds, and basin-wide hydrology. While creating new opportunities, such as emerging landscapes and hydrological changes, deglaciation simultaneously heightens the risk of glacio-hydrological hazards in adjacent and downstream regions. With limited available land for agriculture and settlements, communities around glaciers expand human activities toward newly formed floodplains and deglaciating valleys, necessitating a comprehensive understanding of associated risks and vulnerabilities. This study employs Geographical Information System (GIS) and Remote Sensing products for a multicriteria hazards susceptibility assessment in the Shigar Valley, located in the downstream of major Himalayan glaciers – the Baltoro (63 km) and Biafo (67 km) glaciers. The research reveals that 28.3% of the valley is highly susceptible to multiple hazards, emphasizing the urgency of informed decision-making in the region. Only 0.03% area lies in the very low susceptible category, 9.7% in the low susceptible, 60.6% in the moderately susceptible, and 1.04% in the very highly susceptible categories. These findings highlight the need for proactive measures, adaptive strategies, and sustainable development in the Shigar Valley to mitigate the escalating risks posed by deglaciation and changing hydrological patterns.

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Section: Data Collection and Preprocessingmentioning

confidence: 99%

Hazards profile of the Shigar Valley, Central Karakoram, Pakistan: Multicriteria hazard susceptibility assessment

Afreen,

Haq,

Mark

2024

Auc Geographica

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“…Stream network is a basic requirement of any morphometric study and the prioritization of watersheds (Meshram et al 2022a). Digital Elevation Model (DEM) generated by Shutter Radar Topography Mission (SRTM) data is a common tool to define a stream network and sub-watershed map (Meshram et al 2022b). Different drainage network parameters i.e., numbers and lengths and watershed area, perimeter, width and length were determined in GIS environment (Benzougagh et al 2022;Meshram et al 2022c).…”

Section: Morphometric Parametersmentioning

confidence: 99%

Assessing vulnerability to soil erosion based on fuzzy best worse multi-criteria decision-making method

Meshram

Hasan

Meshram³

et al. 2022

Appl Water Sci

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Soil wearing away or erosion is a chief agent of land loss in agricultural land and is regarded worldwide as a serious environmental hazard. This study performed watershed prioritization using morphometric parameters based on fuzzy best worse method (F-BWM) and GIS integration for Gusru Watershed, India. This study prioritizes sub-watersheds of the study area from viewpoint of soil erosion using five major parameters i.e., stream frequency (Fs), relative relief (Rr), length of overland flow (Lo), relief ratio (Rh) and drainage density (Dd). Fuzzy based Best Worse Multi-Criteria Decision-Making (F-BWM) Method was used to assigning weights to used criteria and combining them to achieve erosion susceptibility for each sub-watershed. Results showed that sub-watersheds 9, 14, and 5 were most susceptible to soil erosion and sub-watershed 3 was the least from the viewpoint of soil erosion ranking.

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“…Moreover, it helps in planning degradation neutrality strategies through sub-watersheds prioritization [12,33]. Recently, researchers have successfully implemented morphometric parameters as criteria in the prioritization of sub-watersheds by applying Multi Criteria Decision Analysis (MCDA) techniques [19,[34][35][36][37]. MCDA techniques were used for complex decision making while considering a set of criteria to improve decision accuracy [8,[38][39][40][41].…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of MCDA Techniques for Identifying Erosion-Prone Areas in the Burhanpur Watershed in Central India for the Purposes of Sustainable Watershed Management

Patel,

Ramana Rao,

Rajwade

et al. 2023

Water

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The degradation of land and increasing water scarcity are existing challenges for agricultural sustainability, necessitating the implementation of improved soil-conservation practices at the watershed scale. The identification and selection of critical/prone areas based on erosion-governing criteria is essential and helps in the execution of the management process for determining priority. This study prioritizes erosion-prone sub-watersheds (alternatives) based on morphometric parameters (multiple criteria) via five Multi-Criteria Decision Analysis (MCDA) approaches, i.e., AHP: Analytical Hierarchy Process; TOPSIS: Technique for Order of Preference by Similarity to Ideal Solution; VIKOR: VIseKriterijumska Optimizacija I Kompromisno Resenje; SAW: Simple Additive Weighting; and CF: Compound Factor. Based on their priority score, 19 sub-watersheds were classified into four priority classes: low priority (0–0.25), moderate priority (0.25–0.50), high priority (0.50–0.75), and very high priority (0.75–1). The results revealed that about 8.34–30.15% area of the Burhanpur watershed is critically prone to erosion, followed by 23.38–52.05% area classed as high priority, 7.47–49.99% area classed as moderate priority, and 10.33–18.28% area classed as low priority. Additionally, four indices—percentage of changes (∆P), intensity of changes (∆I), the Spearman rank correlation coefficient test (SCCT), and the Kendall tau correlation coefficient test (KTCCT)—were employed to compare the models. This study confirms the efficacy of morphometric parameters for prioritizing sub-watersheds to preserve soil and the environment, particularly in areas for which limited information is available.

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Prioritization of soil erosion-prone sub-watersheds using fuzzy-based multi-criteria decision-making methods in Narmada basin watershed, India

Cited by 17 publications

References 36 publications

Hazards profile of the Shigar Valley, Central Karakoram, Pakistan: Multicriteria hazard susceptibility assessment

Hazards profile of the Shigar Valley, Central Karakoram, Pakistan: Multicriteria hazard susceptibility assessment

Assessing vulnerability to soil erosion based on fuzzy best worse multi-criteria decision-making method

Comparative Analysis of MCDA Techniques for Identifying Erosion-Prone Areas in the Burhanpur Watershed in Central India for the Purposes of Sustainable Watershed Management

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