Assessing Water Resources Vulnerability by Using a Rough Set Cloud Model: A Case Study of the Huai River Basin, China

Abstract

Assessing water resources vulnerability is the foundation of local water resources management. However, as one of the major water systems in China, there is no existing evaluation index system that can effectively assess water resource vulnerability for the Huai River basin. To address this issue, we identified key vulnerability factors, constructed an evaluation index system, and applied such system to evaluate water resources vulnerability for the Huai River basin empirically in this paper. Specifically, our evaluation index system consists of 18 indexes selected from three different aspects: water shortage, water pollution, and water-related natural disaster. Then, the improved blind deletion rough set method was used to reduce the size of the evaluation index while keep the evaluation power. In addition, the improved conditional information entropy rough set method was employed to calculate the weights of evaluation indexes. Based on the reduced index system and calculated weights, a rough set cloud model was applied to carry out the vulnerability evaluation. The empirical results show that the Huai River basin water resources were under severe vulnerability conditions for most of the time between 2000 and 2016, and the Most Stringent Water Resources Management System (MS-WRMS) established in 2012 did not work effectively as expected.

Assessing and Predicting the Water Resources Vulnerability under Various Climate-Change Scenarios: A Case Study of Huang-Huai-Hai River Basin, China

“…In this paper, the index system method is used to evaluate and forecast the river basin water resources vulnerability. On the basis of the causes and manifestations of the water resources vulnerability, we divide the water resource vulnerability index (WVI) into three secondary indexes, which are water shortage vulnerability (WSVI), water pollution vulnerability (WPVI), and water-related natural disaster vulnerability (WDVI) [ 39 ]. Then, we divide each secondary indicator into four three level indexes, namely, the pressure, state, impact, and response.…”

“…After adding an indicator, the equivalence relationship between the subset before adding and the subset after adding will be verified according to the concept of rough set. The detailed principles and procedures of this method can refer to the work by Pawlak [ 40 ], and the detailed calculation steps of this method are shown in reference [ 39 ].…”

Evaluation and Scenario Prediction of the Water-Energy-Food System Security in the Yangtze River Economic Belt Based on the RF-Haken Model

“…For the negative indicators, (0, µ-σ] is level 5, (µ-σ, µ] is level 4, (µ, µ+σ] is level 3, (µ+σ, µ+2σ] is level 2, (µ +2σ,∞] is level 1, and the opposite is true for the positive indicators. Other indicators refer to existing studies [34][35][36] and are combined with the situation of the Yangtze River Economic Belt itself. The classification criteria applicable to the Yangtze River Economic Belt region are shown in Table 2, below.…”

Assessment and Prediction of Water Resources Vulnerability Based on a NRS-RF Model: A Case Study of the Song-Liao River Basin, China

“…In the application of evaluation methods, weight evaluation methods, such as entropy weight method [28], projection pursuit method [29], analytic hierarchy process (AHP) method [30] are used more frequently. In addition, principal component analysis (PCA) [31,32], technique for order preference by similarity to an ideal solution (TOPSIS) [33], rough set cloud [34], connection entropy approach [35], expert-based model [36] and other quantitative methods are also used in the assessment of water resources vulnerability. What's more, Geographical Information System (GIS) is often used in the study of water resources vulnerability [37].…”