Empirical Bayesian Kriging method to evaluate inter-annual water-table evolution in the Cuenca Alta del Río Laja aquifer, Guanajuato, México

Abstract The evolution of the water-table in the Cuenca Alta del Rio Laja aquifer (CARL aquifer) was investigated using Empirical Bayesian Kriging (EBK) utilizing ArcGIS ® and the Curve-Fit tool developed by the United States Geological Survey (USGS). We created a new methodology to identify areas of the aquifer that can host unregistered wells, or users that overdraft the permitted extraction volume, and forecast water-table change based on historical annual water levels. Short-term climate variability, specifically the El Nino and La Nina phenomena, had an indirect influence on groundwater availability driven by less or more groundwater demand for irrigation, respectively. La Nina phenomena (2011-2012) caused severe drought driving a mean water-table velocity (WTV) of -1.57 m/year (drawdown). This contrasted to a wet El Nino period (2014-2015) driving a mean WTV of +1.12 m/year (recovery). Across the period 2008-2015, the WTV and water-table acceleration maps revealed mean values of -0.43 m/year and 0.93 m/year2, respectively. These numbers suggest that the problem of dewatering of the CARL aquifer continued, but that the rate of drawdown has slowed. If the observed drawdown rate continues, by the year 2035, 45% of the surface area of the CARL aquifer will have a water-table greater than 120 m below surface, 24 % of the area will exceed 150 m and 5% of the area will exceed 180 m. Whereas deeper water tables increase the cost of lifting water to the surface, there is also a risk of worsening groundwater quality as deeper parts of the aquifer are sourced. Furthermore, the demand for irrigation is likely to increase under the most likely near-term climate change scenarios published by the Intergovernmental Panel on Climate Change. A 5-10% reduction in rainfall is predicted by 2040. Given these potential negative future consequences of over-exploiting aquifers, this original approach will help water managers make more informed decisions for the development of groundwater resources.