Simulation and prediction analysis of urban household water demand based on multi-agentChinese Full Text
JIN Juliang;CUI Yi;ZHANG Libing;ZHOU Yuliang;WU Chengguo;School of Civil Engineering,Hefei University of Technology;Institute of Water Resources and Environmental Systems Engineering,Hefei University of Technology;
Abstract: In this paper, a model named MA-UHWDS, which can analyze the variation trend and influ-ence factors of urban household water demand by constructing different development scenarios, is proposedfor the control objective of total water line and the urban household water shortage. The model is appliedin Qingdao City,first to calculate the marginal propensity to consume water,basic water demand,and percapita water consumption of different income households with statistics from 2003 to 2012, then simulationand prediction of the per capita water consumption and total urban household water demand from 2013 to2022 in different scenarios are analyzed quantitatively. The results indicate that average share of expendi-ture for water use in living expenditure from 2003 to 2012 is just 0.395%, and the shares are so smallthat the public awareness on water conservation is weak;the per capita water consumption of the lowest in-come household from 2003 to 2012 are all below the basic water demand except 2008, while the highest is 14.16 m3 higher than that,therefore both the payment ability of the low income household and the over-use of the high should be considered in the reform of water price; compared with the scenario of PlIhSlElin 2022, the per capita water demand of seven kinds of income households in that of PlIhSlEldecrease16.7%,18.4%,18.1%,16.1%,15.0%,17.8% and 13.8%,respectively,so water price and disposable in-come could obviously impact the household water demand. MA-UHWDS provides new research idea andtool for total water consumption control.
Keywords：
urban household water demand; total water consumption control; simulation and prediction; multi-agent based modelling; extended linear expenditure system model;
- DOI：
10.13243/j.cnki.slxb.20150189
- Series：
- Subject：
- Classification Code：
TV213.4
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