State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin, 300350, China.
Environ Sci Pollut Res Int. 2018 Aug;25(23):23328-23341. doi: 10.1007/s11356-018-2408-1. Epub 2018 Jun 5.
The risk of water shortage caused by uncertainties, such as frequent drought, varied precipitation, multiple water resources, and different water demands, brings new challenges to the water transfer projects. Uncertainties exist for transferring water and local surface water; therefore, the relationship between them should be thoroughly studied to prevent water shortage. For more effective water management, an uncertainty-based water shortage risk assessment model (UWSRAM) is developed to study the combined effect of multiple water resources and analyze the shortage degree under uncertainty. The UWSRAM combines copula-based Monte Carlo stochastic simulation and the chance-constrained programming-stochastic multiobjective optimization model, using the Lunan water-receiving area in China as an example. Statistical copula functions are employed to estimate the joint probability of available transferring water and local surface water and sampling from the multivariate probability distribution, which are used as inputs for the optimization model. The approach reveals the distribution of water shortage and is able to emphasize the importance of improving and updating transferring water and local surface water management, and examine their combined influence on water shortage risk assessment. The possible available water and shortages can be calculated applying the UWSRAM, also with the corresponding allocation measures under different water availability levels and violating probabilities. The UWSRAM is valuable for mastering the overall multi-water resource and water shortage degree, adapting to the uncertainty surrounding water resources, establishing effective water resource planning policies for managers and achieving sustainable development.
由频繁干旱、多变降水、多种水资源和不同用水需求等不确定性引起的水资源短缺风险给调水工程带来了新的挑战。调水和当地地表水都存在不确定性，因此应深入研究它们之间的关系，以防止水资源短缺。为了更有效地进行水资源管理，开发了基于不确定性的水资源短缺风险评估模型 (UWSRAM)，以研究多种水资源的综合影响，并分析不确定性下的短缺程度。UWSRAM 结合了基于 copula 的蒙特卡罗随机模拟和机会约束规划-随机多目标优化模型，以中国鲁南受水区为例。统计 copula 函数用于估计可利用调水量和当地地表水的联合概率，并从多元概率分布中进行抽样，作为优化模型的输入。该方法揭示了水资源短缺的分布情况，能够强调改进和更新调水和当地地表水管理的重要性，并检验它们对水资源短缺风险评估的综合影响。可以应用 UWSRAM 计算可能的可用水量和短缺量，并在不同的可用水量水平和违反概率下计算相应的分配措施。UWSRAM 对于掌握整体多水资源和水资源短缺程度、适应水资源的不确定性、为管理者制定有效的水资源规划政策以及实现可持续发展具有重要价值。
