Comprehensive evaluation of water resources security in the Yellow River basin based on a fuzzy multi-attribute decision analysis approach

Abstract

Abstract. In this paper, a fuzzy multi-attribute decision analysis approach (FMADAA) was developed for supporting the evaluation of water resources security in nine provinces within the Yellow River basin. A numerical approximation system and a modified left-right scoring approach were adopted to cope with the uncertainties in the acquired information. Also, four conventional multi-attribute decision analysis (MADA) methods were implemented in the evaluation model for impact evaluation, including simple weighted addition (SWA), weighted product (WP), cooperative game theory (CGT) and technique for order preference by similarity to ideal solution (TOPSIS). Moreover, several aggregation methods including average ranking procedure, Borda and Copeland methods were used to integrate the ranking results, helping rank the water resources security in those nine provinces as well as improving reliability of evaluation results. The ranking results showed that the water resources security of the entire basin was in critical condition, including the insecurity and absolute insecurity states, especially in Shanxi, Inner Mongolia and Ningxia provinces in which water resources were lower than the average quantity in China. Hence, the improvement of water eco-environment statuses in the above-mentioned provinces should be prioritized in the future planning of the Yellow River basin.

Evaluating Water Resource Security in Karst Areas Using DPSIRM Modeling, Gray Correlation, and Matter–Element Analysis

“…We used the gray correlation method to calculate the weight of each rating index listed in Table 1. Using Equations (11) and (12), we then incorporated the matter-element R 2005 -R 2012 into the matter-element analysis model to evaluate index correlation degrees, factor layer correlation degrees, and comprehensive correlation degrees for the Guizhou region (Tables 2-4). For 2005, for example, the correlation degrees (k j (x 1 )) of the five corresponding grades are N o1 = −0.021, N o2 = 0.013, N o3 = 0.001, N o4 = 0.000, and N o5 = −0.014.…”

“…Consequently, water resource security has become a principal factor limiting economic and social development in China. To date, water security evaluations have focused on regions traditionally associated with water scarcity [9], such as the populous areas of Central and Eastern China [10,11], the arid northwest, and the Yellow River Basin [12]. In contrast, little attention has been paid to water availability in the country's humid, economically deprived southwestern areas, which includes China's famous karst region.…”

Impact of Social Factors in Agricultural Production on the Crop Water Footprint in Xinjiang, China

“…Therefore, improving the efficiency of water resource use in agricultural production is an important way to relieve the pressure on China's overall water resources. Reasonable assessments of the demand by crops for water resources and the utilization of water resources in the production of crops can provide a theoretical basis for improving the management and regulation of agricultural water resources [2]. Compared to the traditional water use evaluation approach, the relatively new concept of the "water footprint" provides a framework to assess the impact of human production and consumption activities on water resources from the aspects of amounts, types, and utilization efficiency [3][4][5][6].…”

A nonlinear modelling-based high-order response surface method for predicting monthly pan evaporations

“…In the last decades, data-driven methods such as fuzzy genetic (FG), artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) have been applied for modelling Epan (Sudheer et al, 2002;Kisi, 2009;Dogan et al, 2010;Kim et al, 2013;Kisi and Tombul, 2013;Malik and Kumar, 2015) and have been successfully applied in water resources (Moghaddamnia et al, 2009;Amini et al, 2010;Sanikhani et al, 2012;Kisi and Tombul, 2013;Liu et al 2014;Li et al 2015;Khan and Valeo, 2015;Xu et al, 2016). Sudheer et al (2002) used ANN in modelling Epan and compared with Stephens-Stewart (SS) method.…”