Abstract

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.

Highlights

  • In recent years, rainwater harvesting (RWH) has attracted increased attention for various reasons including its use as an alternative water supply and for urban water management, notably control of stormwater

  • Being unable to change the rainfall pattern in the location of the planned RWH system, designers focus on the system components and parameters they can control, namely, the collection area, storage volume, and demand level

  • The SY data were used in a regional regression approach to obtain generalized equations for estimating storage for RWH systems using system parameters and daily rainfall statistics

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Summary

Introduction

Rainwater harvesting (RWH) has attracted increased attention for various reasons including its use as an alternative water supply and for urban water management, notably control of stormwater. In the past few decades, RWH has become a popular supplemental (and generally nonpotable) water source in urban and suburban areas in a wide range of climatic and socio-economic environments. 9 (2014) 075007 suburban gardener may value the water saving efficiency, and a stormwater engineer may value capture efficiency. These disparate objectives and interests have led to the use of different metrics and constraints upon which to assess RWH system performance, though the physical components of the system-collection area, conveyance, and storage—remain largely consistent. Being unable to change the rainfall pattern in the location of the planned RWH system, designers focus on the system components and parameters they can control, namely, the collection area, storage volume, and demand level. While there is no substitute for a detailed engineering design study at a given project location, there would be great utility in a simpler and more generally applicable method of preliminary RWH storage capacity estimation

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