Drinking Water Security in Times of Drought and Beyond: Improved Prediction, Management, and Decision-Making Tools for Water Distribution in Southern CaliforniaEPA Grant Number: FP917781
Title: Drinking Water Security in Times of Drought and Beyond: Improved Prediction, Management, and Decision-Making Tools for Water Distribution in Southern California
Investigators: Quesnel, Kimberly
Institution: Stanford University
EPA Project Officer: Lee, Sonja
Project Period: September 1, 2015 through August 31, 2018
Project Amount: $132,000
RFA: STAR Graduate Fellowships (2015) RFA Text | Recipients Lists
Research Category: Academic Fellowships
The goal of this research is to increase knowledge of local and regional factors driving urban water use and to then incorporate those factors into an innovative and accurate demand-forecasting tool. This research will investigate traditional factors affecting water use in addition to uncovering new drivers, such as the uptake of new technologies and management techniques, increased urbanization, and a changing climate. Exploring all potential drivers of urban water use will enable the fellow to construct a better, more comprehensive demand forecasting model than currently exists. Understanding demand enables better supply management and the uptake of creative solutions such as installing green infrastructure to recharge groundwater, utilizing recycled water to meet non-potable needs, and increasing conservation and efficiency measures for source protection.
Using the case study of water districts and municipalities in Orange County, California, the fellow will first investigate the socio-environmental factors influencing potable water demand across geographical regions, water-use sectors, and temporal scales using statistical techniques to analyze customer-level consumption data. As part of this investigation, the fellow will examine changes in water use due to demand management strategies, regulations, and media outreach while also uncovering novel drivers of water use. The fellow will use these findings to develop an urban water-use demand forecasting model that can ultimately lead to more accurate prediction of urban water needs and can help water managers plan when, where, and for purpose water is needed.
Exploring fine resolution data will enable this research to move beyond current knowledge of what impacts demand and allow the fellow to uncover drivers of urban water use not currently accounted for in traditional demand forecasting models, for example, the interrelationship between end-use electricity and water. After first uncovering the complex factors affecting urban water use, the fellow will then be able to create a complete demand-forecasting tool. By helping water managers understand their present and future needs, this tool will allow decision makers to expand their supply options and allocate resources in the most environmentally and economically efficient way.