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A novel system of indicators for evaluating system resilience of regional agricultural water resources
Author(s) -
Dong Liu,
Yang Ding,
Qiang Fu,
Dan Zhao,
Muhammad Imran Khan,
Tianxiao Li,
Muhammad Abrar Faiz
Publication year - 2017
Publication title -
water science and technology water supply
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 39
eISSN - 1607-0798
pISSN - 1606-9749
DOI - 10.2166/ws.2017.084
Subject(s) - index (typography) , analytic hierarchy process , resilience (materials science) , computer science , land reclamation , agriculture , key (lock) , environmental resource management , resource (disambiguation) , principal component analysis , environmental science , operations research , mathematics , geography , artificial intelligence , computer network , physics , computer security , archaeology , world wide web , thermodynamics
Constructing a reasonable evaluation index system is important for characterizing water and land resources and for ecological restoration. To solve random and incomplete problems using a traditional evaluation index system, a novel model for evaluating regional agricultural water resources using a resilience index system was proposed. In addition, an new method for an evaluation index system and the filtering of key indicators were investigated. Based on the structural characteristics of a regional agricultural water resource system (AWRS), the model for an evaluation index system was built by constructing a hierarchical indicator architecture using a hierarchical framework model. The index weight was calculated using the importance of the criteria based on the inter criteria correlation (CRITIC). Then, index completeness was ensured using principal component analysis, and the reliability of the results was tested using the analytic hierarchy process. The model was applied to the Jiansanjiang Administration of Agricultural Reclamation in Heilongjiang, China. The main results included the following: (1) the index was optimized from 46 to 32, which identified the key indicators that affect the resilience of the Jiansanjiang Administration AWRS, and (2) an evaluation index system was constructed with a completeness of 85.6%. The results of this study provide an important and practical model for studying the resilience of related resources and environmental fields.

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