ARIMA and TFARIMA Analysis of the Main Water Quality Parameters in the Initial Components of a Megacity’s Drinking Water Supply System
The objective of this paper is to use autoregressive, integrated, and moving average (ARIMA) and transfer function ARIMA (TFARIMA) models to analyze the behavior of the main water quality parameters in the initial components of a drinking water supply system (DWSS) of a megacity (Bogota, Colombia)....
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Hydrology |
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| Online Access: | https://www.mdpi.com/2306-5338/11/1/10 |
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| author | Carlos Alfonso Zafra-Mejía Hugo Alexander Rondón-Quintana Carlos Felipe Urazán-Bonells |
| author_facet | Carlos Alfonso Zafra-Mejía Hugo Alexander Rondón-Quintana Carlos Felipe Urazán-Bonells |
| author_sort | Carlos Alfonso Zafra-Mejía |
| collection | DOAJ |
| description | The objective of this paper is to use autoregressive, integrated, and moving average (ARIMA) and transfer function ARIMA (TFARIMA) models to analyze the behavior of the main water quality parameters in the initial components of a drinking water supply system (DWSS) of a megacity (Bogota, Colombia). The DWSS considered in this study consisted of the following components: a river, a reservoir, and a drinking water treatment plant (WTP). Water quality information was collected daily and over a period of 8 years. A comparative analysis was made between the components of the DWSS based on the structure of the ARIMA and TFARIMA models developed. The results show that the best water quality indicators are the following: turbidity > color > total iron. Increasing the time window of the ARIMA analysis (daily/weekly/monthly) suggests an increase in the magnitude of the AR term for each DWSS component (WTP > river > reservoir). This trend suggests that the turbidity behavior in the WTP is more influenced by past observations compared to the turbidity behavior in the river and reservoir, respectively. Smoothing of the data series (moving average) as the time window of the ARIMA analysis increases leads to a greater sensitivity of the model for outlier detection. TFARIMA models suggest that there is no significant influence of past river turbidity events on turbidity in the reservoir, and of reservoir turbidity on turbidity at the WTP outlet. Turbidity outlier events between the river and reservoir occur mainly in a single observation (additive outliers), and between the reservoir and WTP also have a permanent effect over time (level shift outliers). The AR term of the models is useful for studying the transfer of effects between DWSS components, and the MA term is useful for studying the influence of external factors on water quality in each DWSS component. |
| first_indexed | 2024-03-08T10:48:54Z |
| format | Article |
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| institution | Directory Open Access Journal |
| issn | 2306-5338 |
| language | English |
| last_indexed | 2024-03-08T10:48:54Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Hydrology |
| spelling | doaj.art-08ffdaff7f4242d3aafa9ed44f9ee66a2024-01-26T16:50:04ZengMDPI AGHydrology2306-53382024-01-011111010.3390/hydrology11010010ARIMA and TFARIMA Analysis of the Main Water Quality Parameters in the Initial Components of a Megacity’s Drinking Water Supply SystemCarlos Alfonso Zafra-Mejía0Hugo Alexander Rondón-Quintana1Carlos Felipe Urazán-Bonells2Grupo de Investigación en Ingeniería Ambiental-GIIAUD, Facultad del Medio Ambiente y Recursos Naturales, Universidad Distrital Francisco José de Caldas, Bogotá E-110321, ColombiaFacultad del Medio Ambiente y Recursos Naturales, Universidad Distrital Francisco José de Caldas, Bogotá E-110321, ColombiaFacultad de Ingeniería, Programa de Ingeniería Civil, Universidad Militar Nueva Granada, Campus Cajicá E-250247, ColombiaThe objective of this paper is to use autoregressive, integrated, and moving average (ARIMA) and transfer function ARIMA (TFARIMA) models to analyze the behavior of the main water quality parameters in the initial components of a drinking water supply system (DWSS) of a megacity (Bogota, Colombia). The DWSS considered in this study consisted of the following components: a river, a reservoir, and a drinking water treatment plant (WTP). Water quality information was collected daily and over a period of 8 years. A comparative analysis was made between the components of the DWSS based on the structure of the ARIMA and TFARIMA models developed. The results show that the best water quality indicators are the following: turbidity > color > total iron. Increasing the time window of the ARIMA analysis (daily/weekly/monthly) suggests an increase in the magnitude of the AR term for each DWSS component (WTP > river > reservoir). This trend suggests that the turbidity behavior in the WTP is more influenced by past observations compared to the turbidity behavior in the river and reservoir, respectively. Smoothing of the data series (moving average) as the time window of the ARIMA analysis increases leads to a greater sensitivity of the model for outlier detection. TFARIMA models suggest that there is no significant influence of past river turbidity events on turbidity in the reservoir, and of reservoir turbidity on turbidity at the WTP outlet. Turbidity outlier events between the river and reservoir occur mainly in a single observation (additive outliers), and between the reservoir and WTP also have a permanent effect over time (level shift outliers). The AR term of the models is useful for studying the transfer of effects between DWSS components, and the MA term is useful for studying the influence of external factors on water quality in each DWSS component.https://www.mdpi.com/2306-5338/11/1/10ARIMA modelARIMA transfer function modeldrinking water supply systemforecasttime series analysiswater quality |
| spellingShingle | Carlos Alfonso Zafra-Mejía Hugo Alexander Rondón-Quintana Carlos Felipe Urazán-Bonells ARIMA and TFARIMA Analysis of the Main Water Quality Parameters in the Initial Components of a Megacity’s Drinking Water Supply System Hydrology ARIMA model ARIMA transfer function model drinking water supply system forecast time series analysis water quality |
| title | ARIMA and TFARIMA Analysis of the Main Water Quality Parameters in the Initial Components of a Megacity’s Drinking Water Supply System |
| title_full | ARIMA and TFARIMA Analysis of the Main Water Quality Parameters in the Initial Components of a Megacity’s Drinking Water Supply System |
| title_fullStr | ARIMA and TFARIMA Analysis of the Main Water Quality Parameters in the Initial Components of a Megacity’s Drinking Water Supply System |
| title_full_unstemmed | ARIMA and TFARIMA Analysis of the Main Water Quality Parameters in the Initial Components of a Megacity’s Drinking Water Supply System |
| title_short | ARIMA and TFARIMA Analysis of the Main Water Quality Parameters in the Initial Components of a Megacity’s Drinking Water Supply System |
| title_sort | arima and tfarima analysis of the main water quality parameters in the initial components of a megacity s drinking water supply system |
| topic | ARIMA model ARIMA transfer function model drinking water supply system forecast time series analysis water quality |
| url | https://www.mdpi.com/2306-5338/11/1/10 |
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