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In order to guarantee the sustainability of the potable water supply service, a water utility must generate improvements in its performance in an integrated manner. The objective of this research is to analyze and provide information about the components and indicators used by the water utility of Leon, Guanajuato, Mexico, which directly impact water management. The Analytic Hierarchy Process (AHP) and Fuzzy Logic (FL) methodologies were applied. The study determined the trends and evolution over time from 2002 to 2017. From the combination of both methodologies, a Water Supply Management Index was obtained with an average value of 0.79, which shows positive progress for water resource management by the water utility. However, the traditional indicators are insufficient and require particular attention. The analysis helped to identify those indicators that do impact water management and their ability to measure the sustainability of the city’s water utility. This may make it possible to monitor the progress toward the accomplishment of Sustainable Development Goal 6 (SDG 6), by performing an evaluation and thorough analysis of the status of water resources.

Climatological data with unreliable or missing values is an important area of research, and multiple methods are available to fill in missing data and evaluate data quality. Our study aims to compare the performance of different methods for estimating missing values that are explicitly designed for precipitation and multipurpose hydrological data. The climate variable used for the analysis was daily precipitation. We considered two different climate and orographic regions to evaluate the effects of altitude, precipitation regime and percentage of missing data on the Mean Absolute Error of imputed values and using a homogeneity evaluation of meteorological stations. We excluded from the analysis meteorological stations with more than 25% missing data. In the semi-arid region, ReddPrec (optimal for 9 stations), and GCIDW (optimal for 8) were the best performing methods for the 23 stations, with average MAE values of 1.63 mm/day and 1.46 mm/day, respectively. In the humid region, GCIDW was optimal in ~59% of stations, EM in ~24%, and ReddPrec in ~17%, with average MAE values of ~6.0 mm/day, 6.5 mm/day and ~9.8 mm/day, respectively. This research makes an important contribution to identifying the most appropriate methods to impute daily precipitation in different climatic regions of Mexico based on efficiency indicators and homogeneity evaluation.

Five municipalities in El Bajío present the highest industrial investments: Celaya, Irapuato, León, Salamanca, and Silao. Public and private investments, further to the support received from the government, have been decisive to industrialize the zone. The official discourse to encourage these activities has emphasized the economic and social benefits for inhabitants, the decrease in the use of water volumes, and the consequent improvement of water sources in each region. The main objective of the present work is to present a global industrial impact index to evaluate the industrial impact on water management by analyzing the evolution of some parameters regarding the official data available, in order to determine whether the industry has a positive outcome on the environmental, social, economic and hydrological aspects. For this study, we use Fuzzy Logic (FL) to complete a previous study, which was conducted using the Analytic Hierarchy Process (AHP). A combination of both approaches is used to define the global impact of industrialization, and the results obtained show that the benefits claimed by governmental policies are not being achieved. The use of this proposed index may guide the decision-making processes to encourage water sustainability.