Shiksha Bastola, Binay Shakya, Yeongjeong Seong, Beomgu Kim, Younghun Jung
{"title":"AHP and FAHP-based multi-criteria analysis for suitable dam location analysis: a case study of the Bagmati Basin, Nepal","authors":"Shiksha Bastola, Binay Shakya, Yeongjeong Seong, Beomgu Kim, Younghun Jung","doi":"10.1007/s00477-024-02799-9","DOIUrl":null,"url":null,"abstract":"<p>The Bagmati River Basin is experiencing significant water stress due to a reduction of surface and groundwater resources, especially during the dry season. The basin’s heavy reliance on monsoon-dominated precipitation, without the buffer of snow or glacier melt, exacerbates these issues. Dam construction is seen as a viable solution for maintaining river flow and regulating river ecosystems. Thus, this study leveraged multi-criteria decision-making tools, particularly the analytical hierarchy process (AHP) and fuzzy AHP (FAHP) in conjunction with the Geographic Information System(GIS), to identify suitable dam construction sites in the Bagmati River Basin. Through an extensive literature review, nine criteria were identified: stream density, rainfall, slope, land use, elevation, soil type, distance from faults, distance from settlements, and distance from roads. Pairwise comparison matrices, based on expert surveys, were used to assign weights to each criterion, with validation against existing and proposed dams. Results show that approximately 31% of the basin area is suitable for dam construction, with about 4.45% area being highly suitable. FAHP only slightly outperforms AHP in assessing existing dam locations, demonstrating the robustness of both methodologies. For the validation of suitability analysis, location of existing dams are compared. While Nepal is not generally water-stressed, inter-seasonal water availability is high. Dam construction for multiple uses is nascent in Nepal, and location analysis studies are rare. The methodology used here can be replicated in other regions, offering valuable insights for decision-makers.</p>","PeriodicalId":21987,"journal":{"name":"Stochastic Environmental Research and Risk Assessment","volume":"128 1","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Stochastic Environmental Research and Risk Assessment","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1007/s00477-024-02799-9","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 0
Abstract
The Bagmati River Basin is experiencing significant water stress due to a reduction of surface and groundwater resources, especially during the dry season. The basin’s heavy reliance on monsoon-dominated precipitation, without the buffer of snow or glacier melt, exacerbates these issues. Dam construction is seen as a viable solution for maintaining river flow and regulating river ecosystems. Thus, this study leveraged multi-criteria decision-making tools, particularly the analytical hierarchy process (AHP) and fuzzy AHP (FAHP) in conjunction with the Geographic Information System(GIS), to identify suitable dam construction sites in the Bagmati River Basin. Through an extensive literature review, nine criteria were identified: stream density, rainfall, slope, land use, elevation, soil type, distance from faults, distance from settlements, and distance from roads. Pairwise comparison matrices, based on expert surveys, were used to assign weights to each criterion, with validation against existing and proposed dams. Results show that approximately 31% of the basin area is suitable for dam construction, with about 4.45% area being highly suitable. FAHP only slightly outperforms AHP in assessing existing dam locations, demonstrating the robustness of both methodologies. For the validation of suitability analysis, location of existing dams are compared. While Nepal is not generally water-stressed, inter-seasonal water availability is high. Dam construction for multiple uses is nascent in Nepal, and location analysis studies are rare. The methodology used here can be replicated in other regions, offering valuable insights for decision-makers.
期刊介绍:
Stochastic Environmental Research and Risk Assessment (SERRA) will publish research papers, reviews and technical notes on stochastic and probabilistic approaches to environmental sciences and engineering, including interactions of earth and atmospheric environments with people and ecosystems. The basic idea is to bring together research papers on stochastic modelling in various fields of environmental sciences and to provide an interdisciplinary forum for the exchange of ideas, for communicating on issues that cut across disciplinary barriers, and for the dissemination of stochastic techniques used in different fields to the community of interested researchers. Original contributions will be considered dealing with modelling (theoretical and computational), measurements and instrumentation in one or more of the following topical areas:
- Spatiotemporal analysis and mapping of natural processes.
- Enviroinformatics.
- Environmental risk assessment, reliability analysis and decision making.
- Surface and subsurface hydrology and hydraulics.
- Multiphase porous media domains and contaminant transport modelling.
- Hazardous waste site characterization.
- Stochastic turbulence and random hydrodynamic fields.
- Chaotic and fractal systems.
- Random waves and seafloor morphology.
- Stochastic atmospheric and climate processes.
- Air pollution and quality assessment research.
- Modern geostatistics.
- Mechanisms of pollutant formation, emission, exposure and absorption.
- Physical, chemical and biological analysis of human exposure from single and multiple media and routes; control and protection.
- Bioinformatics.
- Probabilistic methods in ecology and population biology.
- Epidemiological investigations.
- Models using stochastic differential equations stochastic or partial differential equations.
- Hazardous waste site characterization.