Water provision planning on the basis of human population growth forecasts: A case study of the City of uMhlathuze, KwaZulu-Natal Province, South Africa
Access to adequate water is a battle the City of uMhlathuze faces daily, with the disadvantaged and impoverished areas being most affected as a result of a rapidly increasing growth in human population. The future water condition will be impossible to manage unless the municipality is able to addres...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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IWA Publishing
2022-09-01
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| Series: | Water Supply |
| Subjects: | |
| Online Access: | http://ws.iwaponline.com/content/22/9/7172 |
| _version_ | 1811332291542122496 |
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| author | Thato Julius Mokoma Surafel Luleseged Tilahun |
| author_facet | Thato Julius Mokoma Surafel Luleseged Tilahun |
| author_sort | Thato Julius Mokoma |
| collection | DOAJ |
| description | Access to adequate water is a battle the City of uMhlathuze faces daily, with the disadvantaged and impoverished areas being most affected as a result of a rapidly increasing growth in human population. The future water condition will be impossible to manage unless the municipality is able to address the increased demand for water which often leads to illegal water connections. The goal of this study is twofold: first to predict human population growth over a 50-year period and secondly, to formulate a linear programming model to determine the number of additional reservoir tanks which need to be built, in order to satisfy the human water demand for the next half century. This study compares the application of automated time series forecasting models like ARIMA, ETS, and BATS model to predict the growth in human population. The best model to forecast human population growth was then selected using the forecasting assessment criterion of RMSE, MAE, MASE and MAPE. Based on the forecast results obtained in this study, ARIMA(1,1,0) with drift model has shown a better prediction accuracy in terms of the RMSE = 3.725, MAE = 2.265, MASE = 0.211, and MAPE = 0.757, than the ETS(A,Ad,N), and BATS(1, {0,0}, 1,-) model to explain the observed values of a time series. The forecast results derived from ARIMA(1,1,0) with drift model have indicated that the human population growth will triple by 2067, albeit at a higher pace than at any period since 1996. On the basis of human population growth forecasts, it is suggested that 687 additional reservoir tanks with a capacity of 47,500 kilolitres are built within the next 50 years in order to supplement the increased demand for water that comes with an increase in human population. An implication of these findings is the possibility that, should anticipated human population growth materialise, the current reservoir tanks are likely to come under stress due to the increased demand for water.
HIGHLIGHTS
Water provision planning.;
Application of automated time series forecasting models to predict the growth in human population.;
Formulation of a new linear programming model along with its solution to determine the number of additional reservoir tanks to be built for half a century in advance.; |
| first_indexed | 2024-04-13T16:34:36Z |
| format | Article |
| id | doaj.art-d2c8f6bc96504fe2abd5c70e90bcbf69 |
| institution | Directory Open Access Journal |
| issn | 1606-9749 1607-0798 |
| language | English |
| last_indexed | 2024-04-13T16:34:36Z |
| publishDate | 2022-09-01 |
| publisher | IWA Publishing |
| record_format | Article |
| series | Water Supply |
| spelling | doaj.art-d2c8f6bc96504fe2abd5c70e90bcbf692022-12-22T02:39:28ZengIWA PublishingWater Supply1606-97491607-07982022-09-012297172718810.2166/ws.2022.290290Water provision planning on the basis of human population growth forecasts: A case study of the City of uMhlathuze, KwaZulu-Natal Province, South AfricaThato Julius Mokoma0Surafel Luleseged Tilahun1 Department of Economics, Faculty of Commerce, Administration, and Law, University of Zululand, Richards Bay, KwaZulu-Natal Province, South Africa Department of Mathematics, Addis Ababa Science and Technology University, Addis Ababa, Ethiopia Access to adequate water is a battle the City of uMhlathuze faces daily, with the disadvantaged and impoverished areas being most affected as a result of a rapidly increasing growth in human population. The future water condition will be impossible to manage unless the municipality is able to address the increased demand for water which often leads to illegal water connections. The goal of this study is twofold: first to predict human population growth over a 50-year period and secondly, to formulate a linear programming model to determine the number of additional reservoir tanks which need to be built, in order to satisfy the human water demand for the next half century. This study compares the application of automated time series forecasting models like ARIMA, ETS, and BATS model to predict the growth in human population. The best model to forecast human population growth was then selected using the forecasting assessment criterion of RMSE, MAE, MASE and MAPE. Based on the forecast results obtained in this study, ARIMA(1,1,0) with drift model has shown a better prediction accuracy in terms of the RMSE = 3.725, MAE = 2.265, MASE = 0.211, and MAPE = 0.757, than the ETS(A,Ad,N), and BATS(1, {0,0}, 1,-) model to explain the observed values of a time series. The forecast results derived from ARIMA(1,1,0) with drift model have indicated that the human population growth will triple by 2067, albeit at a higher pace than at any period since 1996. On the basis of human population growth forecasts, it is suggested that 687 additional reservoir tanks with a capacity of 47,500 kilolitres are built within the next 50 years in order to supplement the increased demand for water that comes with an increase in human population. An implication of these findings is the possibility that, should anticipated human population growth materialise, the current reservoir tanks are likely to come under stress due to the increased demand for water. HIGHLIGHTS Water provision planning.; Application of automated time series forecasting models to predict the growth in human population.; Formulation of a new linear programming model along with its solution to determine the number of additional reservoir tanks to be built for half a century in advance.;http://ws.iwaponline.com/content/22/9/7172automated time series forecasting modelshuman population growthlinear programming modelreservoir tankswater supply and distribution |
| spellingShingle | Thato Julius Mokoma Surafel Luleseged Tilahun Water provision planning on the basis of human population growth forecasts: A case study of the City of uMhlathuze, KwaZulu-Natal Province, South Africa Water Supply automated time series forecasting models human population growth linear programming model reservoir tanks water supply and distribution |
| title | Water provision planning on the basis of human population growth forecasts: A case study of the City of uMhlathuze, KwaZulu-Natal Province, South Africa |
| title_full | Water provision planning on the basis of human population growth forecasts: A case study of the City of uMhlathuze, KwaZulu-Natal Province, South Africa |
| title_fullStr | Water provision planning on the basis of human population growth forecasts: A case study of the City of uMhlathuze, KwaZulu-Natal Province, South Africa |
| title_full_unstemmed | Water provision planning on the basis of human population growth forecasts: A case study of the City of uMhlathuze, KwaZulu-Natal Province, South Africa |
| title_short | Water provision planning on the basis of human population growth forecasts: A case study of the City of uMhlathuze, KwaZulu-Natal Province, South Africa |
| title_sort | water provision planning on the basis of human population growth forecasts a case study of the city of umhlathuze kwazulu natal province south africa |
| topic | automated time series forecasting models human population growth linear programming model reservoir tanks water supply and distribution |
| url | http://ws.iwaponline.com/content/22/9/7172 |
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