Selecting a Time-Series Model to Predict Drinking Water Extraction in a Semi-Arid Region in Chihuahua, Mexico

Martín Alfredo Legarreta-González, César A. Meza-Herrera, Rafael Rodríguez-Martínez (), Darithsa Loya-González, Carlos Servando Chávez-Tiznado, Viridiana Contreras-Villarreal and Francisco Gerardo Véliz-Deras ()
Additional contact information
Martín Alfredo Legarreta-González: Universidad Tecnológica de la Tarahumara, Carr. Guachochi-Yoquivo km 1.5, Chihuahua 33180, Mexico
César A. Meza-Herrera: Unidad Regional Universitaria de Zonas Áridas, Universidad Autónoma Chapingo, Km. 40 Carr. Gómez Palacio Chihuahua, Bermejillo 35230, Mexico
Rafael Rodríguez-Martínez: Unidad Laguna Periférico Raúl López Sánchez S/N, Universidad Autónoma Agraria Antonio Narro, Torreón 27054, Mexico
Darithsa Loya-González: Universidad Tecnológica de la Tarahumara, Carr. Guachochi-Yoquivo km 1.5, Chihuahua 33180, Mexico
Carlos Servando Chávez-Tiznado: Universidad Tecnológica de la Tarahumara, Carr. Guachochi-Yoquivo km 1.5, Chihuahua 33180, Mexico
Viridiana Contreras-Villarreal: Unidad Laguna Periférico Raúl López Sánchez S/N, Universidad Autónoma Agraria Antonio Narro, Torreón 27054, Mexico
Francisco Gerardo Véliz-Deras: Unidad Laguna Periférico Raúl López Sánchez S/N, Universidad Autónoma Agraria Antonio Narro, Torreón 27054, Mexico

Sustainability, 2024, vol. 16, issue 22, 1-22

Abstract: As the effects of global climate change intensify, it is increasingly important to implement more effective water management practices, particularly in arid and semi-arid regions such as Meoqui, Chihuahua, situated in the arid northern center of Mexico. The objective of this study was to identify the optimal time-series model for analyzing the pattern of water extraction volumes and predicting a one-year forecast. It was hypothesized that the volume of water extracted over time could be explained by a statistical time-series model, with the objective of predicting future trends. To achieve this objective, three time-series models were evaluated. To assess the pattern of groundwater extraction, three time-series models were employed: the seasonal autoregressive integrated moving average (SARIMA), Prophet, and Prophet with extreme gradient boosting (XGBoost). The mean extraction volume for the entire period was 50,935 ± 47,540 m 3 , with a total of 67,233,578 m 3 extracted from all wells. The greatest volume of water extracted has historically been from urban wells, with an average extraction of 55,720 ± 48,865 m 3 and a total of 63,520,284 m 3 . The mean extraction volume for raw water wells was determined to be 20,629 ± 19,767 m 3 , with a total extraction volume of 3,713,294 m 3 . The SARIMA(1,1,1)(1,0,0) 12 model was identified as the optimal time-series model for general extraction, while a “white noise” model, an ARIMA(0,1,0) for raw water, and an SARIMA(2,1,1)(2,0,0) 12 model were identified as optimal for urban wells. These findings serve to reinforce the efficacy of the SARIMA model in forecasting and provide a basis for water resource managers in the region to develop policies that promote sustainable water management.

Keywords: Facebook Prophet; Prophet Boost model; hybrid models; SARIMA; model calibration (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/16/22/9722/pdf (application/pdf)
https://www.mdpi.com/2071-1050/16/22/9722/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2024:i:22:p:9722-:d:1516354

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().