Estimating the impact of climate change on residential water use using panel data analysis: a case study of Lilongwe, Malawi

In this study, panel linear models were used to develop an empirical relationship between metered household water use and the independent variables plot size and theoretical irrigation requirement. The estimated statistical model provides a means of estimating the climate-sensitive component of resi...

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Vydáno v:Journal of water, sanitation, and hygiene for development Ročník 8; číslo 2; s. 217 - 226
Hlavní autoři: Makwiza, Chikondi, Fuamba, Musandji, Houssa, Fadoua, Jacobs, Heinz Erasmus
Médium: Journal Article
Jazyk:angličtina
Vydáno: London IWA Publishing 01.06.2018
Témata:
Case studies
Climate change
Data analysis
Data processing
Datasets
Economic models
Emissions
Empirical analysis
Environmental impact
Estimation
Independent variables
Mathematical models
Rain
Rainfall
Regression analysis
Statistical models
Water conservation
Water supply
Water use
Water utilities
South Africa
Malawi
United States > US
Southern Africa
ISSN:2043-9083, 2408-9362
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Shrnutí:In this study, panel linear models were used to develop an empirical relationship between metered household water use and the independent variables plot size and theoretical irrigation requirement. The estimated statistical model provides a means of estimating the climate-sensitive component of residential water use. Ensemble averages of temperature and rainfall projections were used to quantify potential changes in water use due to climate change by 2050. Annual water use per household was estimated to increase by approximately 1.5% under the low emissions scenario or 2.3% under the high emissions scenario. The model results provide information that can enhance water conservation initiatives relating particularly to outdoor water use. The model approach presented utilizes data that are readily available to water supply utilities and can therefore be easily replicated elsewhere.
Bibliografie:ObjectType-Case Study-2
SourceType-Scholarly Journals-1
content type line 14
ObjectType-Report-1
ISSN:2043-9083
2408-9362
DOI:10.2166/washdev.2017.056