Abstract
To further quantitatively assess the water resources carrying capacity (WRCC) system and analyze and identify the regional water resources carrying state and the physical mechanism of the state change, WRCC and obstacle factor diagnosis were carried out. In this paper, we proposed the mobility matrix to determine the connection number components, considered the dynamic attributes of the difference degree coefficient, and calculated it using the semi-partial subtraction set pair potential and triangular fuzzy number, so as to construct the quantitative diagnosis method of regional WRCC obstacle factors based on the connection number and TOPSIS. The results applied to six cities in the Huaibei Plain showed that the WRCC fluctuated around grade 2 and was in a poor state, which was mainly due to the insufficient support force; the water resources carrying state of the six cities gradually improved from 2011 to 2018, but the state became worse in 2019, which was related to the low precipitation in that year, the reduction in water resources, and the high degree of water resource utilization. The WRCC of Fuyang and Huainan was worse than that of the other four cities; over the 9 years, the average grades of Fuyang and Huainan were 2.26 and 2.43, while those of Huainan, Bozhou, Suzhou, and Bengbu were 2.19, 2.12, 2.05, and 2.05, respectively. The key obstacles limiting the improvement in the WRCC of the Huaibei Plain were per capita water resources, annual water production modulus, per capita water supply, vegetation coverage ratio, utilization ratio of water resources, water consumption per 104 yuan value-added by industry, and population density. In time, the key obstacle factors in neighboring years generally tended to have similarity, and conversely appeared as a difference; in space, neighboring regions showed similarity and conversely presented as a difference. The results of this study can offer technical support and a decision-making basis for water resources management in the Huaibei Plain. The method constructed in this paper is extremely interpretive, easy to calculate, highly sensitive, and reliable in application results, which opens up a new perspective for the rational determination of the connection number and the difference degree coefficient and provides a new intelligent way to determine the state of a complex set pair system and its causal mechanism analysis and diagnosis of obstacle factors.
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