Erosion susceptibility mapping of sub-watersheds for management prioritization using MCDM-based ensemble approach

Ghosh, Biman; Mukhopadhyay, Sutapa

doi:10.1007/s12517-020-06297-4

Cited by 26 publications

(10 citation statements)

References 54 publications

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“…However, Lo (0.036) and Di (0.034) have relatively similar impact on erosion in the Anambra Basin. These results align with recent studies conducted in tropical areas of the world (Bhattacharya et al 2020;Ghosh & Mukhopadhyay 2021). The results of the MCDM models are presented in Tables 7 and 8.…”

Section: Sub-watershed Prioritization Using Mcdm-based Ensemblesupporting

confidence: 90%

“…In order to effectively manage erosion risks in the Anambra Basin, there is a need for a uniform ranking method that considers all rankings from the MCDM models. While previous studies, such as Ameri et al (2018) and Ghosh and Mukhopadhyay (2021), have employed methods such as percentage-change and average rank system, these methods need to take into account the relative strengths of each model in their final ranking. In this study, a Spearman's rank correlation coefficient was used to analyze the rank relationships between the pairs of MCDM models.…”

Section: Mcdm-based Ensemble Sub-watershed Rankingmentioning

confidence: 99%

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Coupling MCDM-Based ensemble and AHP for the sustainable management of erosion risk in a tropical Sub-Saharan basin

Raji

Akintuyi

Wunude

et al. 2023

Preprint

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One of the most pressing environmental issues of the 21st century is land degradation in fragile watersheds where acute sediment aggradation, erosion, and flooding have become everyday occurrences. Previous attempts to prioritise sub-watersheds have been plagued with uncertainty. Addressing this problem therefore requires identifying erosion-prone areas, specifically at the sub-watersheds level, and reducing the uncertainty of outcomes to a minimum. In this study, an ensemble of seven multi-criteria decision-making (MCDM) models was developed to prioritise the sub-watersheds of the Anambra Basin against erosion risk. These MCDM models, namely MOORA (multi-objective optimisation based on ratio analysis), GRA (grey relational analysis), CoCoSo (combined compromise solution), CODAS (combinative distance-based assessment), TOPSIS (a technique for order preference by similarity to ideal solution), COPRAS (complex proportional assessment), and VIKOR (VieKriterijumsko KOmpromisno Rangiranje), were coupled with the Analytical Hierarchical Process (AHP) and Geographic Information System (GIS) with 23 geomorphometric parameters to provide an integrated sub-watershed ranking. The accuracy of the models was tested using Spearman's rank correlation and geometric mean to compute a uniform sub-watershed ranking. The results indicate that sub-watershed H has the highest aggregate ranking across the MCDM models, making it the top priority for erosion mitigation projects. Furthermore, the model validation assessment shows that the MOORA and COPRAS models returned similar results with the aggregated ranks and possess the most significant rank correlation coefficients, indicating the highest predictive accuracy. This study can be utilised by decision-makers in data-sparse regions for sustainable watershed management in the face of erosion risks.

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Section: Sub-watershed Prioritization Using Mcdm-based Ensemblesupporting

confidence: 90%

Section: Mcdm-based Ensemble Sub-watershed Rankingmentioning

confidence: 99%

Coupling MCDM-Based ensemble and AHP for the sustainable management of erosion risk in a tropical Sub-Saharan basin

Raji

Akintuyi

Wunude

et al. 2023

Preprint

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“…Ranking using the average COPRAS-CODAS ranking. This ranking uses as a research [6], which carried out the final ranking based on the average ranking of the 4 MCDM methods. 4.…”

Section: Figure 1 Research Stagementioning

confidence: 99%

“…According to Zavadskas, et al in [4] the COPRAS method is a Multi-Criteria Decision Making (MCDM) method that is used to evaluate alternatives where the ratio based on two measures, the sum of the performance of the favorable criteria and the sum of the unfavorable criteria. The COPRAS method is used for the assessment of ICT development in G7 countries [5], vulnerability mapping of subwatershed erosion [6], green logistics and green supply chain management [7], Decision Making for New Student Admissions at MTsN Bangkalan [8], motorcycle selection Electricity [9], multi-criteria decision making for hybrid wind power plants [10], Supplier Selection at ABC Mining Companies in Indonesia [11], and Determination of Potential Zones for the Pasir Batu Mine [12].…”

Section: Introductionmentioning

confidence: 99%

BPNT Program Beneficiaries Based on Copras and Codas

Midyanti

Bahri

Midyanti

2023

jitk

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Determination of recipients of the Non-Cash Food Assistance Program (BPNT) is a matter that causes problems if it is not carried out in an objective, transparent, and targeted manner. Previous studies on BPNT were based on a specific method, which did not use a negative trend in the criteria. In this study, the Multi-Criteria Decision Making (MCDM) approach was used to recommend the recipients of the BPNT program. Two MCDM models were used in this study, COPRAS and CODAS methods. Spearman's rank correlation method was used to determine the best model and measure the degree of similarity between the results obtained from different models. Spearman rank correlation shows that COPRAS and CODAS have a strong positive correlation of 0.89899. The combined COPRAS-CODAS ranking model produces a very strong positive correlation value of 0.9744 for both methods, so the model is used for recommendations for BPNT program recipients.

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“… Compute the maximum and minimum indices for alternatives: In this step, Equations (20) and (21) are used to separately compute the sum of beneficial (i.e., higher values are more preferable) and non‐beneficial (i.e., lower values are preferable) criteria.

S_{j}^{+} = \sum_{j = 1}^{n} y_{+ ij} j = 1, 2, \dots . n;

S_{j}^{-} = \sum_{j = 1}^{n} y_{- ij} j = k + 1, k + 2, \dots n;

where

S_{j}^{+}

and

S_{j}^{-}

are sums of the weighted normalized values of beneficial and non‐beneficial criteria, respectively;

y_{+ ij}

and

y_{- ij}

are the weighted normalized score of beneficial and non‐beneficial criteria, respectively (Ghosh & Mukhopadhyay, 2021). Compute each alternative's relative importance: The formula below is utilized to estimate the relative significance score for each alternative (pixel).

\begin{matrix} Q_{i} goodbreak= S_{j}^{+} goodbreak+ \frac{S_{- italicmin} \sum_{i = 1}^{m} S_{j}^{-}}{S_{j}^{-} \sum_{i = 1}^{m} \frac{S_{- \min}}{S_{j}^{-}}} \\ U_{i} goodbreak= \frac{Q_{i}}{\max ((), Q_{i})} \end{matrix}

where

…”

Section: Susceptibility Analysismentioning

confidence: 99%

A novel hybrid GIS‐based multi‐criteria decision‐making approach for flood susceptibility analysis in large ungauged watersheds

Sahraei

Kanani‐Sadat

Homayouni

et al. 2022

J Flood Risk Management

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Characterizing and identification of flood-susceptible areas can be a solution to mitigate the damages and fatality rate. This study proposes a novel hybrid MCDM framework to assess flood susceptibility in large ungauged watersheds dealing with data scarcity issues. The proposed method examines the interdependencies and causal relationships between various criteria affecting the flooding procedure using the DEcision-MAking Trial and Evaluation Laboratory (DEMATEL). Moreover, since experts' opinions contain uncertainty, the fuzzy logic is integrated with DEMATEL to overcome this shortcoming. Then, the local weights of criteria were estimated using the Best-Worst Method (BWM) to enhance the pairwise comparisons process. Final criteria weights were obtained using Fuzzy DEMATEL and BWM results in Analytical Network Process (ANP) super-matrix. Finally, the criteria were distributed spatially using the Complex Proportional Assessment of Alternatives (COPRAS) method based on obtained weights. The proposed method was compared with different approaches such as Fuzzy-DEMATEL ANP, BWM, and AHP using several statistical measures. We concluded that the novel hybrid proposed method outperformed other approaches based on our results. Moreover, by overlaying classified maps with the historical flood events locations, it was concluded that 85.96% of flooded areas were classified as "high" and "very high.

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Erosion susceptibility mapping of sub-watersheds for management prioritization using MCDM-based ensemble approach

Cited by 26 publications

References 54 publications

Coupling MCDM-Based ensemble and AHP for the sustainable management of erosion risk in a tropical Sub-Saharan basin

Coupling MCDM-Based ensemble and AHP for the sustainable management of erosion risk in a tropical Sub-Saharan basin

BPNT Program Beneficiaries Based on Copras and Codas

A novel hybrid GIS‐based multi‐criteria decision‐making approach for flood susceptibility analysis in large ungauged watersheds

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