Water Research Centre, School of Civil and Environmental Engineering, University of New South Wales Sydney, NSW, 2052, Australia; Monash Infrastructure Research Institute, Department of Civil Engineering, Monash University, Clayton, 3800, VIC, Australia.
Monash Infrastructure Research Institute, Department of Civil Engineering, Monash University, Clayton, 3800, VIC, Australia; Swiss Federal Institute of Aquatic Science & Technology (Eawag), Überlandstrasse 133, Dübendorf, 8600, Switzerland; Institute of Environmental Engineering, ETH Zürich, 8093, Zürich, Switzerland.
Water Res. 2020 Mar 15;171:115372. doi: 10.1016/j.watres.2019.115372. Epub 2019 Dec 7.
It is well known that rainwater harvesting (RWH) can augment water supply and reduce stormwater pollutant discharges. Due to the lack of continuous 2D modelling of urban flood coverage and its associated damage, the ability of RWH to reduce urban flood risks has not been fully evaluated. Literature suggests that small distributed storage spaces using RWH tanks will reduce flood damage only during small to medium flooding events and therefore cumulative assessment of their benefits is needed. In this study we developed a new integrated modelling framework that implements a semi-continuous simulation approach to investigate flood prevention and water supply benefits of RWH tanks. The framework includes a continuous mass balance simulation model that considers antecedent rainfall conditions and water demand/usage of tanks and predicts the available storage prior to each storm event. To do so, this model couples a rainfall-runoff tank storage model with a detailed stochastic end-use water demand model. The available storage capacity of tanks is then used as a boundary condition for the novel rapid flood simulation model. This flood model was developed by coupling the U.S. EPA Storm Water Management Model (SWMM) to the Cellular-Automata Fast Flood Evaluation (CA-ffé) model to predict the inundation depth caused by surcharges over the capacity of the drainage network. The stage-depth damage curves method was used to calculate time series of flood damage, which are then directly used for flood risk and cost-benefit analysis. The model was tested through a case study in Melbourne, using a recorded rainfall time series of 85 years (after validating the flood model against 1D-2D MIKE-FLOOD). Results showed that extensive implementation of RWH tanks in the study area is economically feasible and can reduce expected annual damage in the catchment by up to approximately 30 percent. Availability of storage space and temporal distribution of rainfall within an event were important factors affecting tank performance for flood reduction.
众所周知，雨水收集（RWH）可以增加供水量并减少雨水污染物的排放。由于缺乏对城市洪水覆盖范围及其相关破坏的连续二维建模，因此尚未充分评估 RWH 减少城市洪水风险的能力。文献表明，使用 RWH 水箱的小型分布式存储空间仅在小到中等洪水事件中会减少洪水破坏，因此需要对其收益进行累积评估。在这项研究中，我们开发了一种新的集成建模框架，该框架采用半连续模拟方法来研究 RWH 水箱的防洪和供水效益。该框架包括一个连续的质量平衡模拟模型，该模型考虑了前期降雨条件和水箱的水需求/使用情况，并在每次风暴事件之前预测可用的存储量。为此，该模型将降雨径流水箱存储模型与详细的随机终端用水需求模型耦合在一起。然后，将水箱的可用存储容量用作新颖的快速洪水模拟模型的边界条件。该洪水模型是通过将美国环保署的雨水管理模型（SWMM）与单元自动快速洪水评估（CA-ffé）模型耦合而开发的，用于预测排水网络容量超过洪水时的淹没深度。使用水位深度破坏曲线方法计算洪水破坏的时间序列，然后直接用于洪水风险和成本效益分析。该模型通过在墨尔本进行的案例研究进行了测试，该案例研究使用了 85 年的记录降雨时间序列（在对洪水模型进行了 1D-2D MIKE-FLOOD 验证之后）。结果表明，在研究区域内广泛实施 RWH 水箱在经济上是可行的，可以将集水区的预期年损失减少约 30％。存储空间的可用性和事件内的降雨时间分布是影响水箱减少洪水性能的重要因素。
