Increasing knowledge of the transmissivity field of a detrital aquifer by geostatistical merging of different sources of information

Acknowledgements The work reported here was supported by research project PID2019-106435GB-I00 of the Ministerio de Ciencia e Innovación of Spain. We thank Philippe Renard and the two anonymous reviewers who provided constructive comments that have allowed us to improve the final version of this paper.Transmissivity is a significant hydrogeological parameter that affects the reliability of groundwater flow and transport models. This study demonstrates the improvement in the estimated transmissivity field of an unconfined detritic aquifer that can be obtained by using geostatistical methods to combine three types of data: hard transmissivity data obtained from pumping tests, soft transmissivity data obtained from lithological information from boreholes, and water head data. The piezometric data can be related to transmissivity by solving the hydrogeology inverse problem, i.e., including the observed water head to determine the unknown model parameters (log transmissivities). The geostatistical combination of all the available information is achieved by using three different geostatistical methodologies: ordinary kriging, ordinary co-kriging and inverse problem universal co-kriging. In addition, there are eight methodological cases to be compared according to which log-transmissivity data are considered as the primary variable in co-kriging and whether two or three variables are used in inverse-problem universal co-kriging. The results are validated by using the performance statistics of the direct modelling of the unconfined groundwater flow and comparing observed water heads with the modelled ones. Although the results show that the two sets of log-transmissivity data are incompatible, the set of log-transmissivity data from the lithofacies provides a good log-transmissivity image that can be improved by inverse modelling. The map provided by inverse-problem universal co-kriging provides the best results. Using three variables, rather than two in the inverse problem, gives worse results because of the incompatibility of the log-transmissivity data sets.Project PID2019-106435GB-I00 of the Ministerio de Ciencia e Innovación of SpainOpen Access funding provided thanks to the CRUE-CSIC agreement with Springer Natur

Predictive modelling benchmark of nitrate Vulnerable Zones at a regional scale based on Machine learning and remote sensing

Nitrate leaching losses from arable lands into groundwater were a main driver in designating Nitrate Vulnerable Zones (NVZs) according to the Nitrates Directive, with a view to enhancing their water quality. Despite this, developing common strategies for effective water quality control in these areas remains a challenge in the European Union. This paper evaluates the performance of the Random Forest (RF) machine learning algorithm combined with Feature Selection (FS) techniques in predicting nitrate pollution in NVZs groundwater bodies in different periods and using updated environmental features in Andalusia, Spain. A set of forty-four features extrinsic to groundwater bodies were used as environmental predictors, with an aim to make this methodology exportable to other regions. Phenological features obtained through remote-sensing techniques were included to measure the dynamics of agricultural activity. In addition, other dynamic features derived from weather and livestock effluents were included to analyse seasonal and interannual changes in nitrate pollution. Three feature stacks and two nitrate databases were used in the predictive modelling: Period 1 (2009), with 321 nitrate samples for training; Period 2 (2010), with 282 nitrate samples for validation and initial spatial prediction; and Period 3 (2017), to assess the changes in the probability of groundwater nitrate content exceeding 50 mg/L. Random Forest as a wrapper with four sequential search methods was considered: sequential backward selection (SBS), sequential forward selection (SFS), sequential forward floating selection (SFFS) and sequential backward floating selection (SBFS). From among all the Feature Selection methods applied, Random Forest with SFS had the best performance (overall accuracy = 0.891 and six predictor features) and linked the highest probability of nitrate pollution with three dynamic features: the Normalized Difference Vegetation Index (NDVI) base level, NDVI value for the end of the growing season and accumulated manure production of livestock farms; and three static features: slope, sediment depositional areas and valley depth

Analysis of drought conditions and their effects on Lake Trasimeno (Central Italy) levels

An analysis of drought conditions on the Lake Trasimeno area (Umbria, Central Italy) and of their influence on the lake levels is presented. Lake Trasimeno is one of the largest Italian lakes, and its economic and environmental importance is very high. The analysis of temperature data (1963-2014) shows that annual temperature is increasing – in accordance with what is known for Central Italy and the Mediterranean area – with a significant gradient of about 0.023°C/ year. No significant annual and seasonal rainfall trends were observed over the Lake Trasimeno catchment. The power spectrum analysis of rainfall and lake level fluctuations shows that both periodograms have high statistical confidence levels (>99%) for annual and semi-annual cycles. The annual cycles of the periodogram of lake level fluctuations show a higher statistical confidence level than semi-annual cycles. Some other cycles such as the El-Niño Southern oscillation, North Atlantic oscillation, and solar activity are highlighted, with significance levels lower than that of annual and semi-annual cycles. The standardized precipitation (SPI) and standardized reconnaissance drought indices, at different time scales, show that frequency and duration of extreme and severe droughts have increased in the last 25 years. A significant relationship between 12-month SPI and 12-month standardized lake levels fluctuations was obtained for the 1989-2014 period, indicating that SPI12 can be a useful indicator to represent drought severity for systems such as the Lake Trasimeno by considering lake level fluctuations rather than lake levels

Use of statistical techniques to evaluate the potential environmental impact to the groundwater from the employment of agricultural chemicals: Application to Campo de Cartagena GWB

La Directiva Marco del Agua y la Directiva de Aguas Subterráneas, desarrollada a través del artículo 17 de la primera, establecen una serie de requerimientos a los Estados Miembros con objeto de prevenir y luchar contra la contaminación de las aguas subterráneas. Las redes de observación proporcionan dicha información, verificando si la concentración de una sustancia determinada supera los umbrales ambientales en los puntos de control. Los límites de evaluación representan la máxima concentración admisible en dichos puntos. Cuando se evalúa el impacto potencial en el agua subterránea asociado a las actividades agrícolas, los parámetros relevantes son nitratos y pesticidas. La aplicación de técnicas estadísticas permite obtener concentraciones representativas, que pueden ser comparadas con los estándares ambientales. Con objeto de evaluar los impactos potenciales sobre el medio ambiente en general y el agua subterránea en particular en relación con la utilización rutinaria de productos químicos en la agricultura, se proporciona una visión de conjunto de la aplicación de técnicas estadísticas básicas, incluyendo análisis espacial y temporal. Este último se realiza mediante el análisis exploratorio de datos y ensayos de Mann-Kendall, mientras que el krigeaje es la técnica de referencia en el análisis espacialUnder article 17 of Water Framework Directive and the Groundwater Daughter Directive the Member States are required to provide measures to prevent and control groundwater pollution. Information on the concentration of a substance should be obtained from groundwater monitoring data. Pollution will be prevented if groundwater quality does not exceed a relevant assessment limit at an assessment point. Assessment limits represent the maximum concentration of a substance that should be present at the assessment point. When assessing the potential environmental impact to groundwater associated with agricultural activities, nitrates and pesticides are the relevant parameters.A number of techniques can then be applied to statistically derive a representative concentration for comparison to environmental standards.An insight into the ways in which basic statistical tools can be applied to evaluate potential impacts to the state of the environment, and water in particular, from the routine application of agricultural chemicals is provided. These include temporal and spatial analysis. Temporal evaluation is accomplished by means of exploratory data analysis and Mann Kendall trend test, while spatial analysis is realized by using kriging technique

Presencia y distribución de contaminantes emergentes en cuatro cuencas antropizadas del Sur de la Península Ibérica

El objetivo del presente estudio fue estudiar la presencia y distribución de contaminantes emergentes, tanto en aguas superficiales como en aguas subterráneas de acuíferos de cuatro cuencas del Sur de la Península Ibérica (Cuenca del río Guadalhorce (Málaga), Cuenca de la Laguna de Fuente de Piedra (Málaga), Cuenca del río Guadiaro (Málaga-Cádiz) y el acuífero detrítico de la Vega de Granada (Granada)). Para ello se seleccionaron casi 110 puntos de muestreo (77 subterráneas y 32 superficiales) distribuidas en cuatro cuencas que componen la zona de estudio. Los resultados revelan la presencia de contaminantes emergentes en todas las muestras analizadas. En las aguas superficiales se detectaron 33 contaminantes emergentes diferentes, principalmente fármacos, mientras que en las aguas subterráneas se hallaron 37 contaminantes emergentes diferentes, mayoritariamente plaguicidas.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Geostatistic estimation of soil manganese concentration and its relationship with groundwater of Spain

Metal content in groundwater is a problem intensely studied by different researchers worldwide. High concentrations of these elements are related to geogenic sources besides of anthropogenic activities. In this work, a geostatistical estimation of manganese content in the soils of Spain (peninsula), in order to define the source areas of this element, is displayed. This estimate has been compared to groundwater analysis from the quality monitoring network of Agriculture, Food and Environment Ministry (MAGRAMA) to determine the influence of soil concentration on groundwater bodies, particularly in areas where high levels of concentration are found. For geostatistical estimation over 13,000 soil analyses have been employed, while the groundwater quality database has provided more than 9,900 records since year 2000, when the Water Framework Directive (WFD) came into force. Results show the existence of broad sectors where Manganese concentration in groundwater is over 0.4 ppm, that is likely responsible for adverse health effects. In general, these values are linked to certain human activitiesEl contenido en metales en las aguas subterráneas es un problema muy estudiado por diferentes investigadores en todo el mundo. Concentraciones altas de estos elementos están relacionadas con fuentes geogénicas y con factores antropocéntricos. En este trabajo, se muestra una estimación geoestadística del contenido de manganeso en los suelos de España (península) con objeto de delimitar las zonas fuente de este elemento. Esta estimación ha sido comparada con los análisis de aguas subterráneas procedentes de la red de control de calidad del Ministerio de Agricultura, Alimentación y Medio Ambiente (MAGRAMA) con objeto de determinar la influencia, especialmente de los máximos existentes en los suelos, sobre las masas de aguas subterráneas. Para la estimación geoestadística se han empleado más de 13.000 análisis de suelos, mientras que la base de datos de calidad de las aguas subterráneas presenta más de 9.900 registros a partir del año 2000, cuando entró en vigor la Directiva Marco del Agua (DMA). Los resultados muestran la existencia de amplios sectores donde la concentración de Mn en aguas subterráneas está por encima de 0,4 ppm, que es perjudicial para la salud. En general, estos valores están vinculados a algún tipo de actividad human

The ground penetrating radar (GPR) as a tool for characterizing abandoned mining dams. The Linares district (Jaén, Spain)

En Linares (Jaén) existió una gran actividad minera asociada a un cortejo filoniano de sulfuros metálicos. Estas antiguas labores mineras generaron grandes volúmenes de residuos acumulados sin ningún tipo de actuación correctora previa. En este trabajo se han seleccionado dos presas mineras de finos de lavadero (La Cañada I y La Mejor 1ª-2ª). La caracterización interna de estas estructuras se ha realizado mediante técnicas de prospección electromagnética, en concreto, con georrádar (GPR), utilizando antenas de 100 y 250 MHz. Los perfiles realizados han permitido identificar la morfología interna de estas presas: se observan estratificaciones cruzadas que se asocian al crecimiento centrípeto de las mismas, así como distintos cuerpos en la vertical que corresponderían a distintas etapas históricas en su desarrollo. Además, en una de ellas que ofrece escasa potencia (2 m), en la parte inferior se detecta el contacto con el sustrato triásicoIn Linares (Jaen), there is a history of a large amount of mining activity associated to a vein network of metallic sulphurs. These ancient mining operations have generated large accumulations of mine wastes without any prior corrective action. In this work, two mining impoundments have been selected (La Cañada I y La Mejor 1ª-2ª). The internal characterization of these structures was performed with electromagnetic sensing techniques, specifically with Ground Penetrating Radar (GPR), using antennas of 100 and 250 MHz. The generated profiles have allowed the identification of the internal morphology of the mining dams: cross stratifications associated to the lateral growth of the dams have been observed, as well as several vertical sets corresponding to different stages in the historical development of the dam. In addition, the contact of the mining wastes with the substratum has been detected in the dam with lower thickness (2 m

Spatial variability of physico-chemical characteristics of groundwater in carbonate aquifers of Haouz (Tetouan, Northern Morocco)

La cadena montañosa del Haouz, situada entre las ciudades de Ceuta y Tetuán, con una superficie superior a los 90 km2, está constituida por una serie de acuíferos kársticos, fundamentalmente dolomíticos. Estos acuíferos se caracterizan por una fuerte compartimentación consecuencia de una estructura en escamas afectada, a su vez, por importantes fracturas trasversales. En este trabajo se presenta una primera evaluación de su funcionamiento hidrogeológico así como de la variabilidad espacial de las características fisico- químicas de sus aguas subterráneasThe Haouz mountain range, situated in the north of Morocco, between the cities of Ceuta and Tetouan, has a surface area greater than 90 km2 and consists of karst aquifers mainly dolomitic. These aquifers are characterized by a thrust nappes structure which gives rise to a marked partitioning of the aquifers. A first approach on its hydrogeological functioning and spatial variability of the physical-chemical characteristics of groundwater is presented in this pape

Hydrogeological, hydrodynamic and anthropogenic factors affecting the spread of pharmaceuticals and pesticides in water resources of the Granada plain (Spain)

The anthropogenic organic contaminants contemplated in the environmental legislation, as well as those of emerging concern, threaten the quality of water resources to a degree that remains largely unknown. Contaminant exposure in the aquatic environment is a crucial element if a full understanding of the risk is pursued. There are still many uncertainties about the occurrence of organic pollutants and behavior in the hydro(geo)logical media in large scale areas. The case study of the unconfined aquifer of the Granada Plain (approximately 200 km2) is presented here. Two surface and groundwater monitoring campaigns were conducted (March 2017 and June 2018). In total, 41 out of 171 target organic pollutants were detected, at least once: 17 pharmaceuticals or drugs of abuse, 21 pesticides or their metabolites and three polyaromatic hydrocarbons. In addition, physico-chemical parameters were measured during the monitoring campaigns and hydrochemical parameters and stable isotopes (δ2H, δ18O, δ13C) were analyzed. Statistical tests confirmed the significance of seasonal changes for some of these parameters (e.g., EC, Cl-, F-, δ18O, δ13C), revealing the influence from snowmelt water input on streams and the intensification of irrigation. In March 2017, the group of pesticides (largely represented by triazines) predominated, whereas the frequency of detection of pharmaceuticals increased substantially in June 2018. Results suggest four main factors affecting the spatial and seasonal variation of organic pollutants in the aquifer: the anthropogenic factor determining the period of contaminant release throughout the year (pesticide application period and growth of tourism) along with irrigation practices that include reclaimed wastewater; unsaturated zone thickness; [...]This article is a contribution to the Research Groups RNM-308 and RNM 128 of the “Junta de Andalucía” and the project “Study, detection and behavior of emerging contaminants in anthropized watersheds in Andalusia-EMAN (P20_397)”. We are grateful to technical translation specialists GeoTranslations for proofreading the English version. We would also like to thank the Associate Editor, and the anonymous reviewers, who largely contributed to the improvement of the manuscript. Funding for open access charge: Universidad de Málaga / CBU

Multiband PSInSAR and long-period monitoring of land subsidence in a strategic detrital aquifer (Vega de Granada, SE Spain): An approach to support management decisions

This work integrates detailed geological and hydrogeological information with PSI data to obtain a better understanding of subsidence processes detected in the detrital aquifer of the Vega de Granada (SE Spain) during the past 13 years. Ground motion was monitored by exploiting SAR images from the ENVISAT (2003–2009), Cosmo-SkyMed (2011–2014) and Sentinel-1A (2015–2016) satellites. PSInSAR results show an inelastic deformation in the aquifer and small land surface displacements (up to −55 mm). The most widespread land subsidence is detected during the ENVISAT period (2003–2009), which coincided with a long, dry period in the region. The highest displacement rates recorded during this period (up to 10 mm/yr) were detected in the central part of the aquifer, where many villages are located. For this period, there is a good correlation between groundwater level depletion and the augmentation of the average subsidence velocity and slight hydraulic head changes (<2 m) have a rapid ground motion response. The Cosmo-SkyMed period (2011–2014) coincided with a rainy period, and the land subsidence is only concentrated in some points. Rates of average subsidence up to 11.5 mm/yr are obtained for this period and are anthropogenic in origin, being related to earthmoving works. During the Sentinel-1A monitoring period (2015–2016) most of the region showed no deformation, except for some points of unknown origin in the NE sector. A general conclusion is that there is a clear lithological control in the spatial distribution of ground subsidence; all the subsiding areas detected are located where a higher clay content was identified. Although the SE sector of the aquifer had more intense groundwater exploitation, no land subsidence processes were detected, as coarse-grained sediments predominate in the substratum. This research will contribute to the drawing-up of a management plan for the sustainable use of this strategic aquifer, taking into account critical levels of groundwater depletion to avoid land subsidence in the areas identified as vulnerable. The European Space Agency satellite Sentinel-1A could be an effective decision-making tool in the near future.Unidad de Granada, Instituto Geológico y Minero de España, EspañaGeohazards InSAR Laboratory and Modeling Group, Instituto Geológico y Minero de España, EspañaDepartamento de Geodinámica, Universidad de Granada, EspañaCentre Tecnològic de Telecomunicacions de Catalunya, Españ