{"title":"利用基于模糊-AHP 的综合指数全面评估农业干旱脆弱性,将敏感性和适应能力融为一体","authors":"Debarati Bera, Dipanwita Dutta","doi":"10.1002/hyp.15331","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>With increasing extreme weather events, ground water crisis and population expansion, crop stress and production failure have emerged as critical challenges. Agricultural drought vulnerability (ADV) at local and regional scales has become a global concern as it is directly related to food security, hunger issues and poverty. The Kangsabati river basin is one of the major drought-prone river basin in the eastern India and frequently affected by the reduction of crop production or crop failure because of fluctuation of monsoonal rainfalls, poor irrigation system and harsh edaphic factors. In this context, this study focuses on assessing agricultural vulnerability in the Kangsabati basin using multi-sensor datasets and geospatial techniques. The ADV has been assessed through multi-source data sets covering meteorological, agricultural, soil and socio-economic aspects using a powerful, systematic, and flexible decision-making fuzzy-based analytic hierarchy process (fuzzy-AHP) technique. The ADV index is a functional product of two composite indices: the sensitivity index (SI) and the adaptivity index. The SI is derived from components like the intensity of agricultural drought index, groundwater stress, soil erosion, percentage of cultivators, marginal workers and agricultural land. Adaptive capacity depends upon human, financial, physical, infrastructural and natural capital. Each index was derived considering various factors using fuzzy-AHP methods for weightage calculation. The composite indices revealed the variation of resource distribution precisely in each geographically distinct zone. The study shows that almost 60% of the highly sensitive zone is situated in the upper basin region characterised by undulating lands. A large part of the entire basin (48%) is moderately drought-sensitive. The result also shows that a significant part (35%) of the upper and middle basin is highly vulnerable to agricultural drought. In contrast, the lower basin exhibits low to very low levels of vulnerability to drought. The results indicate that even though some areas are moderate to less sensitive, the vulnerability of agricultural drought has become high due to their limited adaptive capacity. The comprehensive framework developed for assessing ADV has the potential for region-specific policy implementation and sustainable growth.</p>\n </div>","PeriodicalId":13189,"journal":{"name":"Hydrological Processes","volume":"38 11","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Comprehensive Evaluation of Agricultural Drought Vulnerability Using Fuzzy-AHP-Based Composite Index Integrating Sensitivity and Adaptive Capacity\",\"authors\":\"Debarati Bera, Dipanwita Dutta\",\"doi\":\"10.1002/hyp.15331\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>With increasing extreme weather events, ground water crisis and population expansion, crop stress and production failure have emerged as critical challenges. Agricultural drought vulnerability (ADV) at local and regional scales has become a global concern as it is directly related to food security, hunger issues and poverty. The Kangsabati river basin is one of the major drought-prone river basin in the eastern India and frequently affected by the reduction of crop production or crop failure because of fluctuation of monsoonal rainfalls, poor irrigation system and harsh edaphic factors. In this context, this study focuses on assessing agricultural vulnerability in the Kangsabati basin using multi-sensor datasets and geospatial techniques. The ADV has been assessed through multi-source data sets covering meteorological, agricultural, soil and socio-economic aspects using a powerful, systematic, and flexible decision-making fuzzy-based analytic hierarchy process (fuzzy-AHP) technique. The ADV index is a functional product of two composite indices: the sensitivity index (SI) and the adaptivity index. The SI is derived from components like the intensity of agricultural drought index, groundwater stress, soil erosion, percentage of cultivators, marginal workers and agricultural land. Adaptive capacity depends upon human, financial, physical, infrastructural and natural capital. Each index was derived considering various factors using fuzzy-AHP methods for weightage calculation. The composite indices revealed the variation of resource distribution precisely in each geographically distinct zone. The study shows that almost 60% of the highly sensitive zone is situated in the upper basin region characterised by undulating lands. A large part of the entire basin (48%) is moderately drought-sensitive. The result also shows that a significant part (35%) of the upper and middle basin is highly vulnerable to agricultural drought. In contrast, the lower basin exhibits low to very low levels of vulnerability to drought. The results indicate that even though some areas are moderate to less sensitive, the vulnerability of agricultural drought has become high due to their limited adaptive capacity. The comprehensive framework developed for assessing ADV has the potential for region-specific policy implementation and sustainable growth.</p>\\n </div>\",\"PeriodicalId\":13189,\"journal\":{\"name\":\"Hydrological Processes\",\"volume\":\"38 11\",\"pages\":\"\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Hydrological Processes\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/hyp.15331\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Environmental Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hydrological Processes","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/hyp.15331","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Environmental Science","Score":null,"Total":0}
A Comprehensive Evaluation of Agricultural Drought Vulnerability Using Fuzzy-AHP-Based Composite Index Integrating Sensitivity and Adaptive Capacity
With increasing extreme weather events, ground water crisis and population expansion, crop stress and production failure have emerged as critical challenges. Agricultural drought vulnerability (ADV) at local and regional scales has become a global concern as it is directly related to food security, hunger issues and poverty. The Kangsabati river basin is one of the major drought-prone river basin in the eastern India and frequently affected by the reduction of crop production or crop failure because of fluctuation of monsoonal rainfalls, poor irrigation system and harsh edaphic factors. In this context, this study focuses on assessing agricultural vulnerability in the Kangsabati basin using multi-sensor datasets and geospatial techniques. The ADV has been assessed through multi-source data sets covering meteorological, agricultural, soil and socio-economic aspects using a powerful, systematic, and flexible decision-making fuzzy-based analytic hierarchy process (fuzzy-AHP) technique. The ADV index is a functional product of two composite indices: the sensitivity index (SI) and the adaptivity index. The SI is derived from components like the intensity of agricultural drought index, groundwater stress, soil erosion, percentage of cultivators, marginal workers and agricultural land. Adaptive capacity depends upon human, financial, physical, infrastructural and natural capital. Each index was derived considering various factors using fuzzy-AHP methods for weightage calculation. The composite indices revealed the variation of resource distribution precisely in each geographically distinct zone. The study shows that almost 60% of the highly sensitive zone is situated in the upper basin region characterised by undulating lands. A large part of the entire basin (48%) is moderately drought-sensitive. The result also shows that a significant part (35%) of the upper and middle basin is highly vulnerable to agricultural drought. In contrast, the lower basin exhibits low to very low levels of vulnerability to drought. The results indicate that even though some areas are moderate to less sensitive, the vulnerability of agricultural drought has become high due to their limited adaptive capacity. The comprehensive framework developed for assessing ADV has the potential for region-specific policy implementation and sustainable growth.
期刊介绍:
Hydrological Processes is an international journal that publishes original scientific papers advancing understanding of the mechanisms underlying the movement and storage of water in the environment, and the interaction of water with geological, biogeochemical, atmospheric and ecological systems. Not all papers related to water resources are appropriate for submission to this journal; rather we seek papers that clearly articulate the role(s) of hydrological processes.