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 m³, with a total of 67,233,578 m³ 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 m³ and a total of 63,520,284 m³. The mean extraction volume for raw water wells was determined to be 20,629 ± 19,767 m³, with a total extraction volume of 3,713,294 m³. 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.

The rainwater chemistry within the Metropolitan Area of Monterrey (MAM) was studied during a one-year period (January 2019–January 2020) in seven sampling sites. The metal concentration of Zn, Fe, Cd, Cu, Ni, and Mn was analyzed in bulk samples and the toxicity potential (TP) was calculated for each metal. A canonical correspondence analysis (CCA) was applied to identify the relationship between environmental variables and metals concentrations. An average of 26.6 ± 10 mm of rainfall was obtained. A mean pH of 7.2 ± 0.3 and a mean electrical conductivity of 177.8 ± 8.7 µS cm⁻¹ were observed. The average concentration of metals in all sites follows a descending order of Fe> Zn > Mn > Cu > Ni > Cd. The university site shows the highest averages of Fe, Zn, Cu, and Mn, which is attributed to its proximity to the metallurgical industry. The TP value of Cd reflects a risk in all sites and Fe only for the Universidad, Obispado, Pastora, and Santa Catarina sites, using as a reference value the Environmental Protection Agency (EPA) Drinking Water Regulations and Mexican norm NOM-127-SSA1-1994. The CCA analysis showed that only Ni and Cd had a strong correlation with the environmental variable of relative humidity of air.

A variety of statistical techniques were assessed for their usefulness for analysing the pattern of geographical and temporal changes in groundwater levels in order to diagnose the water supply in Meoqui, Chihuahua, which is situated in dry North-Central Mexico. These included Facebook Prophet, Lasso, generalized linear regularized models (GLMNET), autoregressive-integrated moving average (ARIMA), and a hybrid approach that merged Prophet and XGBoost. This was conducted on the assumption that the levels varied during the year and that it was possible to perform statistical analyses that derived a model explaining the changes and allowing for spatiotemporal prediction. The data set encompassed the period between 2020 and 2025 and was obtained from the Junta Municipal de Aguas y Saneamiento (JMAS) in Meoqui. The data set consisted of eight wells from which water was extracted for human consumption. The ARIMA model was identified as the optimal method for generating predictions on a monthly and annual basis. Furthermore, an inverse distance weighted (IDW) interpolation approach was utilised to conduct a spatial analysis. This enabled the visualisation of the predicted spatiotemporal changes in groundwater levels. The mean overall level was determined to be 26 m ± 16, with a minimum of 3 m and a lower level of 64 m. Models were estimated, comprising a general model and models specific to each well type. The best model for general level was Facebook Prophet (MAE 6.31, MAPE 16.28, MASE 1.23, SMAPE 16.79, RMSE 7.25, R-sq 0.29). The Sen’s slope of the historic level was found to be 0.38 (p < 0.001), thus indicating a decline in the groundwater level. The spatiotemporal analysis indicated a monthly decline in water levels from February to August, followed by an improvement in levels until November, which were then maintained until January. The lowest levels were observed in the area associated with Well 5. The findings of this study offer valuable insights into the spatiotemporal patterns of groundwater in the region, which could inform the development of sustainable groundwater management policies.

Bulk deposition was studied along an urbanization gradient in the state of Nuevo Leon, Mexico. During a yearlong period seven sites within the Metropolitan Area of Monterrey (MAM) and two rural sites (Allende and Linares) were monitored, with the purpose of characterizing deposition and identifying possible patterns between sites. A total of 32 rainfall events were collected. An average pH of 7.15 ?? 0.02 was found, which indicates the presence of neutralizing substances in rainwater, as well as an average Electrical Conductivity of 153.96 ?? 6.83 ??S/cm. The annual accumulated deposition follows the descending order Ca> K> Mg> Fe> Zn> Mn> Cu> Cd> Ni and does not show significant differences between urban and rural areas, with the exception of Ca (p = 0.017). The Principal Component Analysis shows that metals (Cu, Zn, Ni, Mn, and Cd) represent an important pathway in the deposition phenomena and this behavior is maintained through the urbanization gradient, which denotes that the rural areas could be connected to the air basin of the MAM. Seasonal deposition showed that Zn, Fe, Cd, Cu, Ni, Mn Ca, and Mg are higher during autumn and K during winter. Enrichment Factors shows that Zn and Cd were highly enriched, Cu and Ni were moderately enriched, and Ca, K, and Mn were not enriched. Finally, backward trajectories for rural sites showed that only for Allende site a possible carry-over of pollutants is observed during the summer, since the wind currents come preferably from the northern part of the MAM.