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

IF 3.2 3区 地球科学 Q1 Environmental Science
Debarati Bera, Dipanwita Dutta
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引用次数: 0

摘要

随着极端天气事件、地下水危机和人口膨胀的加剧,作物胁迫和歉收已成为严峻的挑战。地方和区域范围内的农业干旱脆弱性(ADV)已成为全球关注的问题,因为它与粮食安全、饥饿问题和贫困直接相关。Kangsabati 河流域是印度东部主要的易旱流域之一,由于季风降雨量的波动、灌溉系统不完善以及恶劣的自然环境因素,该流域经常受到作物减产或歉收的影响。在这种情况下,本研究侧重于利用多传感器数据集和地理空间技术评估 Kangsabati 流域的农业脆弱性。通过涵盖气象、农业、土壤和社会经济等方面的多源数据集,利用强大、系统和灵活的决策模糊层次分析法(fuzzy-AHP)技术评估了农业脆弱性指数。ADV 指数是两个综合指数的函数乘积:敏感性指数(SI)和适应性指数。敏感度指数由农业干旱指数强度、地下水压力、土壤侵蚀、耕种者比例、边缘工人和农业用地等成分得出。适应能力取决于人力、财力、物力、基础设施和自然资本。每个指数都是在考虑了各种因素后,采用模糊-AHP 方法计算权重得出的。综合指数准确揭示了各地理区域资源分布的差异。研究表明,近 60% 的高敏感区位于以起伏地形为特征的盆地上游地区。整个盆地的大部分(48%)为中度干旱敏感区。研究结果还显示,盆地中上部的大部分地区(35%)极易受到农业干旱的影响。与此相反,下游盆地对干旱的脆弱程度较低至非常低。结果表明,尽管一些地区的敏感度处于中等或较低水平,但由于其适应能力有限,农业干旱的脆弱性已变得很高。为评估 ADV 而制定的综合框架具有针对具体地区实施政策和实现可持续增长的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Comprehensive Evaluation of Agricultural Drought Vulnerability Using Fuzzy-AHP-Based Composite Index Integrating Sensitivity and Adaptive Capacity

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.

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来源期刊
Hydrological Processes
Hydrological Processes 环境科学-水资源
CiteScore
6.00
自引率
12.50%
发文量
313
审稿时长
2-4 weeks
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.
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