Groundwater depletion is an important problem driven by population growth, land use and land cover (LULC) change, climate change, and other factors. Groundwater depletion generates water stress and encourages unstainable resource use. The aim of this study is to determine how population growth, LULC change, and climate change relate to groundwater depletion in the Alto Atoyac sub-basin, Oaxaca, Mexico. Twenty-five years of dry season water table data from 1984 to 2009 are analyzed to examine annual groundwater depletion. Kriging is used to interpolate the region’s groundwater levels in a geographic information system (GIS) from mapped point measurements. An analysis of remotely sensed data revealed patterns of LULC change during a 34-year (1986–2018) period, using a supervised, machine-learning classification algorithm to calculate the changes in LULC. This analysis is shown to have an 85% accuracy. A global circulation model (GFDL-CM3) and the RCP4.5 and RCP8.5 scenarios were used to estimate the effects of climate change on the region’s groundwater. Estimates of evapotranspiration (using HELP3.5 code) and runoff (USDA-SCS-CN), were calculated. Since 1984, the region’s mean annual temperature has increased 1.79 °C and urban areas have increased at a rate of 2.3 km²/year. Population growth has increased water consumption by 97.93 × 10⁶ m³/year. The volume of groundwater is shrinking at a rate of 284.34 × 10⁶ m³/year, reflecting the extreme pressure on groundwater supply in the region. This research reveals the nature of the direct impacts that climate change, changing LULCs, and population growth have in the process of groundwater depletion.

Soils in arid or semi-arid areas often have salinity problems, so the quality of irrigation water plays an important role in agricultural production. Groundwater quality analysis includes the determination of chloride ions, which are toxic to plants in high concentrations. A total of 1358 groundwater samples were collected and analyzed in the period 1980-2008. Water electrical conductivity [EC] and chloride ion concentration values were related by the linear equation [Cl-] = 4.928 EC (R> 0.94), to estimate the concentration of chloride ions as a function of the electrical conductivity of water in the study area. A geophysical survey was conducted through 34 Vertical Electrical Soundings (VESs) to calculate the water electrical conductivity from the interpretation of the apparent resistivity data. Twenty-nine VESs were used to relate the resistivity of the saturated formation (Ro) with that for the groundwater (Rw) by the linear equation Rw = 0.427 Ro + 1.987. Then, EC was estimated as the inverse of Rw. Finally, the chloride ion concentration was determined by the equation mentioned above. Following the same procedure for the five remaining VESs, which were acquired in places where there are no wells, the chloride ion concentration and the electrical resistivity of the saturated formation (Ro) and groundwater (Rw and its inverse EC) were obtained without requiring a destructive technique.

Rural communities in Mexico and other countries with limited economic resources require a low-cost measurement system for the piezometric level and temperature of groundwater for their sustainable management, since anthropogenic action (pumping extractions), natural recharge and climate change phenomena affect the behavior of piezometric levels in the aquifer and its sustainability is at risk. Decrease in the piezometric level under a balanced level promotes salt intrusion from ocean water to the aquifer, salinizing and deteriorating the water quality for agriculture and other activities; and a decrease in water level under the pumps or well drilling depth could deprive communities of water. Water temperature monitoring is essential to determine electric conductivity and dissolved salt content in groundwater. Using IoT technology, a device was developed that monitors both variables inside the well, and the ambient temperature and atmospheric pressure outside the well. The measurements are made in real time, with sampling every second and sending data to a dedicated server every 15 min so that the visualization can be accessed through a device with Internet access. The time series of the variables measured inside and outside the well were obtained over a period of three months in the rural community of Agua Blanca, Guasave, Sinaloa, Mexico. Through these records, a progressive temporary drawdown of the piezometric level is observed, as well as the frequency of pumping. This low-cost IoT system shows potential use in hydrological processes of interest such as the separation of regional and local flow, drawdown rates and recognition of geohydrological parameters.