When the water supply capacity of the reservoir is small, hedge rule (HR) can be applied to reduce the risk of unacceptably large damage from water shortage during drought. Moreover, in water-receiving areas of water diversion project, it is important to reduce transfer based on HR when the water-receiving area is in a wet period so as to reduce the water transfer cost. This paper improved the traditional HR and proposed a new kind of hedging rule named joint hedging rule (JHR). JHR was applied to Yuqiao Reservoir of Tianjin in China and was compared with HR and standard operation policy (SOP) as two control groups. The result indicates that JHR performs better than HR and SOP, which cannot only mitigate the risk of unacceptably large damage from water shortage by one hedge process but also reduce the transferred water by another hedge process. In addition, the number of days of different water shortage, the storage ratio at the end of the year, and transferred water result indicates that JHR is of high reliability and practicability.
Water shortages and the deterioration of water quality in the natural environment have a negative effect on social development of many countries. Therefore, optimizing the allocation of water resources has become an important research topic in water resources planning and management. An essential step in improving the utilization efficiency of water resources is the prediction of water supply and demand. Because it has a great number of merits, the grey prediction method has been widely used in population prediction and temperature prediction. However, it also has limitations such as low prediction precision since original data seriously fluctuates. This paper aims to handle the sample values by an innovative method utilizing moving-average technique (MA) model and optimizing the background values to make them more typical. Results proved that the prediction accuracy of the traditional model was effectively improved by the proposed method. The proposed model was then applied in the multi-objective planning to establish an optimal water resources allocation model for Beijing in the short-term (2020) planning timeframe, including local water resources, transfer water volumes, and other water supplies. The results indicated that industrial and agricultural water use could be well met, while domestic and environmental water resources may face a shortage.
Abstract:Rainfall is an essential index to measure drought, and it is dependent upon various parameters including geographical environment, air temperature and pressure. The nonlinear nature of climatic variables leads to problems such as poor accuracy and instability in traditional forecasting methods. In this paper, the combined forecasting method based on data mining technology and cross entropy is proposed to forecast the rainfall with full consideration of the time-effectiveness of historical data. In view of the flaws of the fuzzy clustering method which is easy to fall into local optimal solution and low speed of operation, the ant colony algorithm is adopted to overcome these shortcomings and, as a result, refine the model. The method for determining weights is also improved by using the cross entropy. Besides, the forecast is conducted by analyzing the weighted average rainfall based on Thiessen polygon in the Beijing-Tianjin-Hebei region. Since the predictive errors are calculated, the results show that improved ant colony fuzzy clustering can effectively select historical data and enhance the accuracy of prediction so that the damage caused by extreme weather events like droughts and floods can be greatly lessened and even kept at bay.
When a city’s water demand cannot be fully satisfied, the hedging rule can reduce water loss by limiting water supply in advance. Based on water supply priority and benefit loss of water shortage for different users, this paper improved the objective function of hedging rules considering the benefit loss of water shortage. At the same time, according to the idea of restricting water supply by water users in turn, improved hedging rules (IHR) are applied to the urban water supply in Tianjin. The conclusions achieved from this study are as follows: (1) IHR increased water supply assurance rates for domestic water with high-priority and avoided destructive water shortages in agricultural water with low-priority. (2) IHR can better reduce the destructive loss caused by a large number of water shortages and the loss of production caused by a small numbers of water shortages than traditional hedging rules, which ensures high efficiency of water supply during the dry period. The results show that the IHR can improve the operational performance of the urban water supply.
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