StRaWHAT: A stochastic rainwater harvesting assessment tool for direct quantification of rainwater harvesting system performance

Abstract

Rainwater harvesting (RWH) contributes to reduced flooding and relief of demand on water supply systems and is instrumental in sustainable development. The conventional analytical probabilistic approach for RWH has a limitation of requiring an assumption of the initial storage condition which may cause overestimation or underestimation of the system's performance. By deriving the average storage volume of the RWH tank to get rid of such an assumption, a stochastic rainwater harvesting assessment tool (StRaWHAT) which is comprised of a set of closed-form analytical equations was developed and proposed for use in directly quantifying the hydrological performance statistics of RWH systems. The accuracy of StRaWHAT was verified by comparing its results with those obtained from continuous simulations based on mass balance principles for a large number of design scenarios with different climate conditions (6 cities in China and the US), storage capacities (1–20 m3) and water use rates (0.5, 1, 1.5 or 2 m3/day). Close agreements (NSE = 0.984, RMSE = 0.022, and CORR = 0.995) between StRaWHAT and continuous simulation results illustrated that StRaWHAT can provide accurate results for all types of system configurations. Extensive example case studies were carried out for RWH systems located in six cities in China and the U.S. Different types of applications were also illustrated. Overall, the proposed StRaWHAT was proved to be a computationally efficient and ease-to-use tool for directly assessing the hydrological performance of RWH systems.