Forecasting urban water demand: A meta-regression analysis.

Abstract:

:Water managers and planners require accurate water demand forecasts over the short-, medium- and long-term for many purposes. These range from assessing water supply needs over spatial and temporal patterns to optimizing future investments and planning future allocations across competing sectors. This study surveys the empirical literature on the urban water demand forecasting using the meta-analytical approach. Specifically, using more than 600 estimates, a meta-regression analysis is conducted to identify explanations of cross-studies variation in accuracy of urban water demand forecasting. Our study finds that accuracy depends significantly on study characteristics, including demand periodicity, modeling method, forecasting horizon, model specification and sample size. The meta-regression results remain robust to different estimators employed as well as to a series of sensitivity checks performed. The importance of these findings lies in the conclusions and implications drawn out for regulators and policymakers and for academics alike.

journal_name

J Environ Manage

authors

Sebri M

doi

10.1016/j.jenvman.2016.09.032

subject

Has Abstract

pub_date

2016-12-01 00:00:00

pages

777-785

issue

Pt 3

eissn

0301-4797

issn

1095-8630

pii

S0301-4797(16)30690-9

journal_volume

183

pub_type

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