Generalized storage–reliability–yield relationships for rainwater harvesting systems

Sizing storage for rainwater harvesting (RWH) systems is often a difficult design consideration, as the system must be designed specifically for the local rainfall pattern. We introduce a generally applicable method for estimating the required storage by using regional regression equations to account for climatic differences in the behavior of RWH systems across the entire continental United States. A series of simulations for 231 locations with continuous daily precipitation records enable the development of storage–reliability–yield (SRY) relations at four useful reliabilities, 0.8, 0.9, 0.95, and 0.98. Multivariate, log-linear regression results in storage equations that include demand, collection area and local precipitation statistics. The continental regression equations demonstrated excellent goodness-of-fit (R² 0.96–0.99) using only two precipitation parameters, and fits improved when three geographic regions with more homogeneous rainfall characteristics were considered. The SRY models can be used to obtain a preliminary estimate of how large to build a storage tank almost anywhere in the United States based on desired yield and reliability, collection area, and local rainfall statistics. Our methodology could be extended to other regions of world, and the equations presented herein could be used to investigate how RWH systems would respond to changes in climatic variability. The resulting model may also prove useful in regional planning studies to evaluate the net benefits which result from the broad use of RWH to meet water supply requirements. We outline numerous other possible extensions to our work, which when taken together, illustrate the value of our initial generalized SRY model for RWH systems.