Household water demand estimation and its implications for water accessibility: a case study

Document Type : Research Paper

Authors

1 Assistant Professor, Environmental Management and Crop Production Unit, College of Agriculture, Engineering and Science, Bowen University, Iwo, Nigeria

2 Associate Professor, Mathematics Programme, College of Agriculture, Engineering and Science, Bowen University, Iwo, Nigeria

3 Department of Geography, Obafemi Awolowo University, Ile-Ife, Nigeria

4 Professor, Environmental Management and Crop Production Unit, College of Agriculture, Engineering and Science, Bowen University, Iwo, Nigeria

Abstract

Spatio-temporal accessibility to water, especially, for household use is expedient to a healthy living. This work attempted the development of predictive models using multiple regression to forecast household water use and also assess the significance of water demand forecasting to water use efficiency and its accessibility in homes. Data used for the study were generated through questionnaire administration and these were analyzed using descriptive and inferential statistics. Domestic water uses consist of 10 defined components (Drinking, Cooking, Bathing, Washing, Cleaning, Car wash, Lawn watering, Coolant/Chiller, Incidental and Livestock) proportionately distributed within Coolant/Chiller and Washing regime and ranged from 0.12% to 38.53% respectively among the regime components. Results of the regression analyses revealed that two home water use components namely Washing and Car wash predict home water use at 95% level of confidence with R2 of 0.872 and the Standard Error of 28.91. With this result, Model 3 showed better accuracy than Models 1 and 2 comparatively. The Incidental use component was not significant and may be ignored in the computation. Two predictive components namely Washing and Car wash generally explain excessive use of water in homes and must be considered to enhance the efficient use and unrestricted accessibility of this vital resource.

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References

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Environmental Resources Research
Volume 11, Issue 1
July 2023
Pages 131-140

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