Regional Water Resources Security Grading Evaluation Considering Both Visible and Virtual Water: A Case Study on Hubei Province, China

Abstract

The security of water resources is of great importance to long-term sustainability. In order to better ensure the security of water resources, a significant link is to conduct water resources security evaluation, which should be considered from many perspectives as it involves natural reserves, social production, the efficiency of use, and environmental protection. In this paper, a fuzzy Analytic Hierarchy Process Sort (AHPSort) II-entropy weight (EW) method for regional water resources security evaluation is proposed based on the security of visible water and virtual water. Firstly, this paper takes into account the criterion of efficiency of water use in addition to two other criteria of quantity of water resources, pressure on water resources to establish a comprehensive water resources security evaluation system. Secondly, a combination method of hesitant fuzzy language judgment and entropy weight is employed to obtain the weight of each indicator. Thirdly, AHPSort II is used to classify the security levels of the evaluated regions, in which the security levels of regional water resources are divided into five levels. Furthermore, a case study on the cities of Hubei Province, China is conducted to show the applicability of the proposed method, the effectiveness, and reliability of the method are then verified by being compared with a subjective method and an objective method as well as sensitivity analysis. Finally, according to the comprehensive evaluation results, specific management suggestions for improving the water resources security in the case are put forward.

ARASsort: A new sorting based multiple attribute decision‐making algorithm

“…All methods have their own assumption, characteristics, paradigm, and perspective. Outranking methods such as PROMSORT (Araz & Ozkarahan, 2005) and Flowsort (Nemery & Lamboray, 2008) which are based on PROMETHEE, require that the decision‐maker defines preference functions for each attribute and also indifference and preference thresholds. Distance‐based approaches which are extensions of compensatory methods such as TOPSISsort (de Lima Silva et al, 2020; De Lima Silva & de Almeida Filho, 2020; Ocampo et al, 2021; Sabokbar et al, 2016; Yamagishi & Ocampo, 2022) and VIKORsort (Demir et al, 2018; Ocampo & Yamagishi, 2021; Polat et al, 2021; Sabbagh et al, 2021) need to determine positive and negative ideal solutions and measure the distance between each alternative and these ideals. Pairwise comparison‐based approaches relying on subjective judgments of the decision‐makers, need to build a hierarchy showing the relations between attributes and/or alternatives and too many survey questions should be answered by the experts, such as AHPsort (Ishizaka et al, 2012; Toledo et al, 2019), AHPsort II (Labella et al, 2020; Miccoli & Ishizaka, 2017; Xie et al, 2019), some fuzzy AHP sorting methods (Du et al, 2021; Ishizaka et al, 2020; Krejci & Ishizaka, 2018; Xu et al, 2019), and group AHPsort (Assumma et al, 2021; Labella et al, 2021; Lopez & Ishizaka, 2017). …”