La gestión del agua potable en zonas urbanas representa en la actualidad uno de los mayores desafíos. Por lo tanto, el suministro de agua potable y el saneamiento ha llevado a los expertos a explorar nuevos enfoques y estrategias para su gestión. Ubicándose en esta línea de trabajo, el presente documento explora los indicadores de evaluación de desempeño para la gestión del recurso hídrico aplicados a los servicios de abastecimiento de agua a nivel nacional e internacional. El objetivo consiste en proponer indicadores relacionados con los enfoques de gestión del agua orientados al derecho humano al agua y a un medio ambiente sano, y armonizando con el ODS-6 se plantea evaluar tanto los indicadores cualitativos como cuantitativos a través de una revisión de la literatura y criterios de selección, como aplicabilidad, relevancia, datos existentes y características locales de manejo que le dan al recurso hídrico. Aplicando al estudio de caso el Sistema de Agua Potable y Alcantarillado de León, Guanajuato (SAPAL), la investigación aplicó la metodología análisis jerárquico de procesos (AHP), indicando aquellos indicadores relevantes para la gestión del recurso hídrico bajo la perspectiva de soluciones multidisciplinares, integrales y sostenibles para el servicio de abastecimiento de agua, con lo cual pudo verificarse la disponibilidad de datos para la aplicación de los indicadores propuestos. Se concluye que a partir de este planteamiento se cuenta con indicadores que consideren los enfoques en materia socioambiental que impacten en la gestión sostenible del agua de manera que coadyuve al diseño, seguimiento, evaluación y toma de decisiones de políticas públicas enfocadas a los organismos operadores de manera integral.

This study examines the spatio-temporal evolution of precipitation in the State of Guanajuato, Mexico, from 1981 to 2016 by analyzing monthly series from 65 meteorological stations. A rigorous data quality protocol was implemented, selecting stations with more than 30 years of continuous data and less than 10% missing values. Multiple Imputation by Chained Equations (MICE) with Predictive Mean Matching was applied to handle missing data, preserving the statistical properties of the time series as validated by Kolmogorov–Smirnov tests ($p=1.000$ for all stations). Homogeneity was assessed using Pettitt, SNHT, Buishand, and von Neumann tests, classifying 60 stations (93.8%) as useful, 3 (4.7%) as doubtful, and 2 (3.1%) as suspicious for monthly analysis. Breakpoints were predominantly clustered around periods of instrumental changes (2000–2003 and 2011–2014), underscoring the necessity of homogenization prior to trend analysis. The Trend-Free Pre-Whitening Mann–Kendall (TFPW-MK) test was applied to account for significant first-order autocorrelation (${\rho }_1 > 0.3$) present in all series. The analysis revealed no statistically significant monotonic trends in monthly precipitation at any of the 65 stations ($\alpha =0.05$). While 75.4% of the stations showed slight non-significant increasing tendencies (Kendall’s $\tau$ range: 0.0016 to 0.0520) and 24.6% showed non-significant decreasing tendencies ($\tau$ range: −0.0377 to −0.0008), Sen’s slope estimates were negligible (range: −0.0029 to 0.0111 mm/year) and statistically indistinguishable from zero. No discernible spatial patterns or correlation between trend magnitude and altitude ($\rho =-0.022$, $p>0.05$) were found, indicating region-wide precipitation stability during the study period. The integration of advanced imputation, multi-test homogenization, and robust trend detection provides a comprehensive framework for hydroclimatic analysis in semi-arid regions. These findings suggest that Guanajuato’s severe water crisis cannot be attributed to declining precipitation but rather to anthropogenic factors, primarily unsustainable groundwater extraction for agriculture.

Pollution in ecosystems has increased, especially in water, due to the pollutant agents that alter their chemical, physical and biological characteristics. This requires actions to resolve or at least reduce the harmful effects generated on the environment and people’s health. Many of the contaminants present in water come from the industrial sector, with the textile industry being one of the most impactful as it uses mostly synthetic dyes, which are characterized as being recalcitrant and toxic, so they cannot be degraded by conventional water treatment methods. Advanced oxidation processes have a great potential for application, especially those that use heterogeneous photocatalysis. The present research evaluates the efficiency in the adsorption and degradation of the triazoic Direct Blue 71 dye in aqueous mediums at concentrations of 600 ppm by the heterogeneous photocatalysis method. The photocatalysts used are layered double hydroxides (LDHs) with a Mg/Al = 3 ratio and are thermally activated and doped with Fe at 1, 3 and 5% w/w. The most efficient materials achieved removal percentages greater than 80% by means of a second-order kinetic model with a DB71 half-life decolorization of less than one hour; as shown by an HPLC study, the absence of intermediate products would confirm the mineralization of the dye.

Synthetic plastic impacts the environment due to its slow degradation and the generation of microplastics, driving the development of bioplastics. This study evaluated the use of bagasse fiber combined with corn and potato starch to improve the physical and mechanical properties of bioplastics. Five bioplastic mixtures (Am1 to Am5) were prepared with corn starch, glycerin, acetic acid, maleic anhydride, and agave bagasse. Am1 was prepared without bagasse, and the others were prepared with different amounts of bagasse (0, 10, 30, 50, and 70 g). Bioplastics made from potato starch (Ap1 to Ap5) were also produced under the same conditions and were assessed using the thermogravimetric (TGA) and scanning electron microscopy (SEM) tests. Analysis of variance showed significant differences (p < 0.001) in the moisture, Young’s modulus, and stress of the bioplastics. The corn-based bioplastics exhibited lower moisture values (7.26% and 5.51%) compared to the potato-based ones (9.68% to 8.89%). Young’s modulus and stress increased in the corn-based (Am5 = 4.59 MPa) and potato-based (Ap5 = 3.53 MPa) bioplastics with higher amounts of bagasse. Furthermore, TGA and SEM revealed the surface morphology and the effects of processing, and based on their results, it was found that agave bagasse improved the mechanical and thermal properties of bioplastics, especially corn-based ones, suggesting its potential as a material with a lower environmental impact.

La concentración de cloro como desinfectante suministrado a la red de distribución de agua decae con el paso del tiempo debido a su interacción con microorganismos, metales y otras sustancias presentes en el agua. Los programas de computadora, como Epanet, se utilizan para simular el comportamiento hidráulico y la calidad del agua en las redes de distribución; con su ayuda se pueden representar modificaciones físicas y operativas en un modelo numérico para conocer el nuevo comportamiento sin comprometer la calidad del servicio. La calibración del modelo de cloro como desinfectante consiste en tomar como referencia la concentración en varios puntos de la red y ajustar los coeficientes de decaimiento en el modelo hasta lograr que las concentraciones simuladas coincidan con las medidas. En el presente artículo se muestra la automatización de este proceso haciendo uso de la técnica heurística algoritmos genéticos y la Toolkit de EPANET con MATLAB (2016). El proceso de calibración se realiza en un sector de la red de distribución de la ciudad de Guanajuato, obteniendo una correlación de 0.816 con un error promedio absoluto de 0.08 mg/l entre las concentraciones modeladas y medidas; y que como resultado permitirá conocer la concentración del cloro en diversos puntos de la red, asegurándose de brindar un servicio de calidad durante el abastecimiento.