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The combined weight method (CWM) for comprehensive water resources carrying capacity evaluation is proposed in this paper to evaluate the regional water resources carrying capacity. Firstly, the accelerating genetic algorithm based on analytic hierarchy process (AGA-AHP) method is improved to optimize the expert evaluation matrix and determine the subjective weight, in which entropy weight method is used to determine objective weight, and the combined weight formula is put forward to get the combined weight of evaluation index. Secondly, the certainty degree is calculated by using the multi-dimensional normal cloud model. The obstacle factors of evaluation index are diagnosed. Finally, taking Henan Province as an example, the regional water resources carrying capacity is evaluated by using CWM method. The comparison between single cloud model, AHP-TOPSIS and CWM is made. It is proved that CWM method takes the fuzziness and randomness into account in the evaluation process, and the efficient and intuitive results can be obtained through evaluation. The obstacle degree and the time changing pattern of the index can be clearly diagnosed, which can provide a new idea for the evaluation method of water resources carrying capacity. [ABSTRACT FROM AUTHOR]

Groundwater is an essential resource that meets all of humanity's daily water demands, supports industrial development, influences agricultural output, and maintains ecological equilibrium. The objective behind this research is to find groundwater prospective zones and their sustainable development in Henan Province, located in the North China Plain, with the help of analytical hierarchical process (AHP) and frequency ratio (FR) models. Consequently, a groundwater inventory map was created, utilizing 70% of the data for training and 30% for testing purposes. The resulting maps were overlaid with groundwater levels and the locations of wells within the study area. The performance and validation of the models were assessed using the Area Under Curve (AUC) curve, which indicated an accuracy of 70% for the AHP model and 69% for the FR model. The study indicates that areas with suitable gradients and rainfall patterns generally have high groundwater prospective zonation (GWPZ), i.e., Zhumadian and Nanyang (ZN). However, AHP demonstrated a higher predictive capability in comparison to FR the broader context. Whereas GIS-RS methodology aligns with existing wells and field data that validate it in range of good and excellent. In conclusion, this study provides valuable insights for effective groundwater exploration and sustainable water supply planning in Henan Province. [ABSTRACT FROM AUTHOR]

[Display omitted] • A Water-economy-ecology concept framework is established. • An evaluation index system of 3 aspects including 15 indicators is constructed. • EFAST-Cloud model is innovatively proposed and applied in regional WRCC evaluation. • The WRCC of Henan Province is evaluated at the watershed scale and municipal scale. Water is the basic need for human survival and the development of economy and ecology. Water resources carrying capacity (WRCC) modelling is a fundamental task to explore the interaction mechanism between economy-ecology development and water resources carrying system. To reasonably quantify the regional WRCC, an evaluation method based on Water-economy-ecology (WEE) concept framework and EFAST-Cloud model is proposed in this study, and Henan Province of China is selected as a typical study area. It can both identify the inter-feeding relationships between sub-systems and evaluate the proportion of each grade in detail by reflecting the randomness and fuzziness of the evaluation. A total of 15 indicators including water system, economy system, and ecology system are constructed. The study analyzes the sensitivity of indicators by using Simlab software and then calculates the weight of indicators by using EFAST method. Compared with other traditional methods, EFAST algorithm is a special method for model sensitivity analysis, which can fully consider the coupling effect between indicators. According to the statistical data of 2010, 2015, and 2020, the WRCC at the watershed scale and municipal scale in Henan Province are evaluated through the EFAST-Cloud model. At the watershed scale, the ecology system criterion layer performs best over the multiple years, the Huaihe and Yangtze River basin have better WRCC at the target layer. At the municipal scale, Xuchang, Luohe, and Zhumadian have better WRCC, Puyang, Zhoukou, and Jiaozuo are slightly worse. The results show that WRCC of the study area has shown an overall improvement, but there is still much space for its development. Therefore, targeted recommendations are made for the water, economy, and ecology system respectively. The conclusion of this paper can provide a reference for the government in making water resources management policies. [ABSTRACT FROM AUTHOR]