The rational allocation of water resources in the basin/region can be better assisted and performed using a suitable water resources allocation model. Rule-based and optimization-based simulation methods are utilized to solve medium- and long-term water resources allocation problems. Since rule-based allocation methods requires more experience from expert practice than optimization-based allocation methods, it may not be utilized by users that lack experience. Although the optimal solution can be obtained via the optimization-based allocation method, the highly skilled expert experience is not taken into account. To overcome this deficiency and employ the advantages of both rule-based and optimization-based simulation methods, this paper proposes the optimal allocation model of water resources where the highly skilled expert experience has been considered therein. The “prospect theory” is employed to analyze highly skilled expert behavior when decision-making events occur. The cumulative prospect theory value is employed to express the highly skilled expert experience. Then, the various elements of the cumulative prospect theory value can be taken as the variables or parameters in the allocation model. Moreover, the optimal water allocation model developed by the general algebraic modeling system (GAMS) has been improved by adding the decision reversal control point and defining the inverse objective function and other constraints. The case study was carried out in the Wuyur River Basin, northeast of China, and shows that the expert experience considered as the decision maker’s preference can be expressed in the improved optimal allocation model. Accordingly, the improved allocation model will contribute to improving the rationality of decision-making results and helping decision-makers better address the problem of water shortage.

In order to mitigate environmental and ecological impacts resulting from groundwater overexploitation, we developed a multiple-iterated dual control model consisting of four modules for groundwater exploitation and water level. First, a water resources allocation model integrating calculation module of groundwater allowable withdrawal was built to predict future groundwater recharge and discharge. Then, the results were input into groundwater numerical model to simulate water levels. Groundwater exploitation was continuously optimized using the critical groundwater level as the feedback, and a groundwater multiple-iterated technique was applied to the feedback process. The proposed model was successfully applied to a typical region in Shenyang in northeast China. Results showed the groundwater numerical model was verified in simulating water levels, with a mean absolute error of 0.44 m, an average relative error of 1.33%, and a root-mean-square error of 0.46 m. The groundwater exploitation reduced from 290.33 million m³ to 116.76 million m³ and the average water level recovered from 34.27 m to 34.72 m in planning year. Finally, we proposed the strategies for water resources management in which the water levels should be controlled within the critical groundwater level. The developed model provides a promising approach for water resources allocation and sustainable groundwater management, especially for those regions with overexploited groundwater.

In this paper, a multi-dimensional equilibrium allocation model of water resources was developed based on the groundwater multiple loop iteration technique. The proposed model is an integrated framework of three modules respectively corresponding to the input layer, operation layer, and feedback layer in the allocation process. Firstly, a prediction model integrating the genetic algorithm-back propagation (GA-BP) model, the general regression neural network (GRNN) model, and the support vector machine (SVM) model was built to predict the future reservoir runoff, and the results were entered into the database of an optimal allocation model. Furthermore, taking exploitable groundwater as the feedback factor, the water resource optimal allocation model was continuously optimized. Also, the groundwater multiple loop iteration technique was applied to the feedback process. The proposed model was successfully applied to a typical region in Jinan, Eastern China. The uncertainties of future reservoir runoff and exploitable groundwater were taken into account. The results revealed that groundwater represented 36.6% of water supply in the base year, indicating that it is the main water source in Jinan. However, the amount of groundwater mining was decreased after considering the exploitable groundwater. The developed framework provides a comprehensive approach towards optimal future allocation of water resources, especially for the regions with overexploited groundwater.

Gao, Y.; Lai, L.; Yao, M., and Ma, Z., 2019. Water environment quality assessment based on normal cloud-fuzzy variable set evaluation model. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 39–46. Coconut Creek (Florida), ISSN 0749-0208.Water environmental quality assessment is an important groundwork for river planning, governance, and management. A normal cloud-fuzzy variable evaluation model which incorporated the minimum relative entropy weights was proposed to evaluate the water quality of 13 monitoring points in the Qinhuai River in 2016. The evaluation results proved to be more reasonable and effective in comparison with the results of the single-factor index evaluation method, fuzzy comprehensive evaluation method and cloud model. The analysis of model-level eigenvalue (H) showed that most of the water quality of the Upper Qinhuai River and Qinhuai New River is better in flood season than in non-flood season, which also showed the pollution characteristics of urban industry and domestic sewage. However, the water quality of the Outer Qinhuai River and inner Qinhuai River is worse in the flood season than in non-flood season, which showed the typical pollution characteristics of urban sewage and catering. The study results can be helpful for future evaluation and research of water environment in regions and river basins.

To explore the evolution in patterns of urban water consumption (UWC) accompanying socio-economic development, historical data on socio-economic conditions and water consumption in developed cities worldwide were collected. stages of evolution and patterns in UWC were identified through Pettitt tests. Through correlation analysis, the main socio-economic indicators influencing UWC were identified, and their threshold values for different trends in the evolution of UWC were statistically analyzed. The use of these patterns of evolution for UWC prediction was explored taking Changsha, China as a case study. Results indicate the following: (1) UWC typically increases in the early stage of development and then stabilizes or decreases later; (2) when UWC stabilizes or decreases, socio-economic indicators, namely per capita GDP, tertiary industry’s contribution to GDP, and urbanization rate, range from [USD 10,000, 60,000], [60%, 80%], and [85%, 95%], respectively, entering or approaching the developed economy stage. (3) Using patterns in this evolution, Changsha’s UWC is predicted to increase until the turning point, which will occur between 2027 and 2035 (earlier than that predicted using genetic programming) and then decrease earlier than that of Hunan Province or the entirety of China. Predicted values are lower than those obtained using the quota method. This study provides a new perspective on relationships between UWC and socio-economic conditions, supporting water resources planning.