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According to the European Council Directive 51/2013 EURATOM, the radionuclide content in human consumption waters must comply with the stated recommendations to ensure the protection of public health. The radiological characterisation assessed in Laboratorio de Radiaciones Ionizantes y Datación of Universidad de Salamanca, in more than 400 groundwater samples gathered from intakes intended for human consumption from the Castilla y León region (Spain), has provided worthwhile data for evaluating the spatial distribution of the radioactivity content in the Duero basin. For this purpose, geostatistical exploration and interpolation analysis, using the inverse distance weighting (IDW) method, was performed. The IDW prediction maps showed higher radioactivity occurrence in western and southern areas of the study region, mainly related to the mineralogical influence of the igneous and metamorphosed outcroppings in the Cenozoic sediments that formed the porous detritic aquifers of the Duero basin edges. The hydraulic characteristics promote the distribution of these radioactivity levels towards the centre of the basin as a consequence of the unconfined nature of the aquifers. Prediction maps provide a worthwhile tool that can be used for better planning and managing of groundwater monitoring programmes. [ABSTRACT FROM AUTHOR]

In the present work, we evaluate the prediction capability of six pedotransfer functions (PTFs), reported in the literature, for the saturated hydraulic conductivity estimations (KS). We used a database with 900 measured samples obtained from the Irrigation District 023, in San Juan del Rio, Queretaro, Mexico. Additionally, six new PTFs were constructed for KS from clay percentage, bulk density, and saturation water content data. The results show, for the evaluated models, that one model presents an overestimation for KS > 0.5 cm h−1 values, three models have an underestimation for KS > 1.0 cm h−1, and two models have a good correlation (R2 > 0.98) but more than three parameters are necessary. Nevertheless, the last two models require 3–4 parameters in order to obtain optimization. On the other hand, the models proposed in this work have a similar correlation with fewer parameters. The fit is seen to be much better than using the existing ones, achieving a correlation of R2 = 0.9822 with only one variable and R2 = 0.9901 when we use two. [ABSTRACT FROM AUTHOR]