Dual Benefit of Rainwater Harvesting—High Temporal-Resolution Stochastic Modelling

Ofer Snir,Eran Friedler

doi:10.3390/w13172415

Abstract

The objective of the presented study was to develop a high-temporal-resolution stochastic rainwater harvesting (RWH) model for assessing the dual benefits of RWH: potable water savings and runoff reduction. Model inputs of rainfall and water demand are used in a stochastic manner, maintaining their natural pattern, while generating realistic noise and temporal variability. The dynamic model solves a mass-balance equation for the rainwater tank, while logging all inflows and outflows from it for post-simulation analysis. The developed model can simulate various building sizes, roof areas, rainwater tank volumes, controlled release policies, and time periods, providing a platform for assessing short- and long-term benefits. Standard passive rainwater harvesting operation and real-time control policies (controlled release) are demonstrated for a 40-apartment building with rainfall data typical for a Mediterranean climate, showing the system’s ability to supply water for non-potable uses, while reducing runoff volumes and flows, with the latter significantly improved when water is intentionally released from the tank prior to an expected overflow. The model could be used to further investigate the effects of rainwater harvesting on the urban water cycle, by coupling it with an urban drainage model and simulating the operation of a distributed network of micro-reservoirs that supply water and mitigate floods.

Highlights

Rainwater harvesting (RWH) has gained interest in recent years, as researchers and engineers find that it has positive effects on urban water infrastructure even in developed countries with functioning water supply systems [1]
A high-temporal resolution stochastic RWH model aimed at assessing potable water savings and runoff reduction was developed using real-life water demand and rainfall data
The presented model does not include tank size optimization, as such process requires a cost–benefit analysis which was beyond the scope of this study

Summary

Introduction

Rainwater harvesting (RWH) has gained interest in recent years, as researchers and engineers find that it has positive effects on urban water infrastructure even in developed countries with functioning water supply systems [1]. Water demands and stormwater management systems vary greatly between different climatic, socioeconomic and geographic regions, the field of RWH modeling has developed in order to assess the expected gains from such systems prior to installation [1]. Owing to these variations, different RWH models have been set up by many research groups in a variety of locations around the world [4]

Objectives

Methods

Results

Conclusion