当前位置: X-MOL 学术J. Clean. Prod. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Stochastic Mathematical Models to Balance Human and Environmental Water Needs and Select the Best Conservation Policy for Drought-Prone River Basins
Journal of Cleaner Production ( IF 11.1 ) Pub Date : 2020-11-23 , DOI: 10.1016/j.jclepro.2020.125230
Mohammad Amin Farzaneh , Shabnam Rezapour , Rachel Fovargue , Thomas M. Neeson

In this paper, a multi-objective, multi-period, and stochastic mathematical model is developed to identify drought-resilient strategies for balancing human and environmental water needs given uncertainty about future water availability. The model makes sustainable water withdrawal/distribution decisions for the interconnected water reservoirs of a river network through balancing societal and environmental water needs. These decisions are restricted by the storage capacities of reservoirs and fluctuations of water availability over the planning horizon. The model relies on interval estimation of stochastic hydrological factors, which may be drawn from historical data or future climate projections. The model finds a compromise between drought resilience and satisfaction of water needs through a reliability level that represents the risk attitude of water decision-makers. Finally, the model is extended to include water conservation options. The extended model determines the spatial and temporal prioritization of water reservoirs for water conservation. The proposed models are tested on the Red River of the south-central United States. We quantify tradeoffs between human and environmental water needs and identify water sustainability strategies that are resilient to stochastic drought events. Our model is applicable to drought-prone river basins around the world where water managers seek to balance environmental and human water needs while remaining resilient to unexpected fluctuations in water availability.



中文翻译:

随机数学模型来平衡人类和环境的水需求,并为干旱-普罗涅河流域选择最佳保护策略

在本文中,建立了一个多目标,多周期和随机的数学模型,以在给定未来水可利用性的不确定性的情况下,确定用于平衡人类和环境水需求的抗旱策略。该模型通过平衡社会和环境用水需求,为河流网络的互连水库做出可持续的取水/取水决策。这些决定受到水库的存储容量和整个规划阶段的水量波动的限制。该模型依赖于随机水文因子的区间估计,这可以从历史数据或未来的气候预测中得出。该模型通过代表水决策者风险态度的可靠性水平,在干旱适应力和水需求满足之间找到了折衷方案。最后,该模型被扩展为包括节水方案。扩展模型确定了用于节约用水的水库的空间和时间优先顺序。建议的模型在美国中南部的红河上进行了测试。我们量化人类和环境用水需求之间的权衡,并确定对随机干旱事件具有弹性的水可持续性策略。我们的模型适用于世界各地干旱多发的流域,那里的水管理人员寻求平衡环境和人类用水需求,同时保持对可用水量意外波动的抵御能力。该模型已扩展为包括节水选项。扩展模型确定了用于节约用水的水库的空间和时间优先顺序。建议的模型在美国中南部的红河上进行了测试。我们量化人类和环境用水需求之间的权衡,并确定对随机干旱事件具有弹性的水可持续性策略。我们的模型适用于世界各地干旱多发的流域,那里的水管理人员寻求平衡环境和人类用水需求,同时保持对可用水量意外波动的抵御能力。该模型已扩展为包括节水选项。扩展模型确定了用于节约用水的水库的空间和时间优先顺序。建议的模型在美国中南部的红河上进行了测试。我们量化人类和环境用水需求之间的权衡,并确定对随机干旱事件具有弹性的水可持续性策略。我们的模型适用于世界各地干旱多发的流域,那里的水管理人员寻求平衡环境和人类用水需求,同时保持对可用水量意外波动的抵御能力。建议的模型在美国中南部的红河上进行了测试。我们量化人类与环境用水需求之间的折衷,并确定对随机干旱事件具有弹性的水可持续性策略。我们的模型适用于世界各地干旱多发的流域,那里的水管理人员寻求平衡环境和人类用水需求,同时保持对可用水量意外波动的抵御能力。建议的模型在美国中南部的红河上进行了测试。我们量化人类和环境用水需求之间的权衡,并确定对随机干旱事件具有弹性的水可持续性策略。我们的模型适用于世界各地干旱多发的流域,那里的水管理人员寻求平衡环境和人类用水需求,同时保持对可用水量意外波动的抵御能力。

更新日期:2020-11-25
down
wechat
bug