Rainfall is the major contribution for groundwater recharge in arid and semiarid climates, therefore a key factor in water resources estimation. This work presents the results of an in-depth study in Don ˜ana National Park concerning groundwater recharge behavior over a long period . The spatio-temporal kriging algorithm was used as a supportive tool to improve the reconstruction of the spatio-temporal rainfall variability. One of the main findings was that monthly recharge estimations range between 21 and 91% of the maximum rainfall, being overestimated in areas that also demonstrate spatial heterogeneity in rainfall distribution. In the light of these results, for water management purposes in the Mediterranean area, rainfall spatio-temporal scale is a critical aspect and it must be taken into account in groundwater reservoir allocation. Moreover, it is highlighted that local studies of rainfall and recharge, in an area of high ecological fragility, are essential to developing management strategies that prevent climate change effects and guarantee optimal conditions for groundwater resources in the future.

Groundwater resources are regularly the principal water supply in semiarid and arid climate areas. However, groundwater levels (GWL) in semiarid aquifers are suffering a general decrease because of anthropic exploitation of aquifers and the repercussions of climate change. Effective groundwater management strategies require a deep characterization of GWL fluctuations, in order to identify individual behaviors and triggering factors. In September 2019, the Guadalquivir River Basin Authority (CHG) declared that there was over-exploitation in three of the five groundwater bodies of the Almonte-Marismas aquifer, Southwest Spain. For that reason, it is critical to understand GWL dynamics in this aquifer before the new Spanish Water Resources Management Plans (2021–2027) are developed. The application of GWL series clustering in hydrogeology has grown over the past few years, as it is an extraordinary tool that promptly provides a GWL classification; each group can be related to different responses of a complex aquifer under any external change. In this work, GWL time series from 160 piezometers were analyzed for the period 1975 to 2016 and, after data pre-processing, 24 piezometers were selected for clustering with k-means (static) and time series (dynamic) clustering techniques. Six and seven groups (k) were chosen to apply k-means. Six characterized types of hydrodynamic behaviors were obtained with time series clustering (TSC). Number of clusters were related to diverse affections of water exploitation depending on soil uses and hydrogeological spatial distribution parameters. TSC enabled us to distinguish local areas with high hydrodynamic disturbance and to highlight a quantitative drop of GWL during the studied period.

Mathematical groundwater modelling with homogeneous permeability zones has been used for decades to manage water resources in the Almonte-Marismas aquifer (southwest Spain). This is a highly heterogeneous detrital aquifer which supports valuable ecological systems in the Doñana National Park. The present study demonstrates that it is possible to better characterize this heterogeneity by numerical discretization of the geophysical and lithological data available. We identified six hydrofacies whose spatial characteristics were quantified with indicator variogram modelling. Sequential Indicator Simulation then made it possible to construct a 3D geological model. Finally, this detailed model was included in MODFLOW through the Model Muse interface. This final process is still a challenge due to the difficulty of downscaling to a handy numerical modelling scale. New piezometric surfaces and water budgets were obtained. The classical model with zones and the model with 3D simulation were compared to confirm that, for management purposes, the effort of improving the geological heterogeneities is worthwhile. This paper also highlights the relevance of including subsurface heterogeneities within a real groundwater management model in the present global change scenario.

<p>Nowadays, the application of time series clustering is increasing in hydrogeology works. Groundwater level long data series provides a useful record to identify different hydrological behaviors and to validate the conceptual model of groundwater flow in aquifer systems. Piezometers also register the response to any changes that directly affect the amount of available groundwater resources (recharge or exploitation).</p><p>What are the expected variations of groundwater levels in an aquifer under high exploitation pressure? In this work, groundwater level time series from 160 piezometers in the hydrological years from 1975 to 2016 were analyzed. Especially, 24 piezometers are deeply studied. Data were preprocessed and transformed: selection of points, missing data imputation and data standardization. Visual clustering, k-means clustering and time series clustering were applied to classify groundwater level hydrographs using the available database. Six and seven groups of piezometers were identified to be associated with the different hydrofacies and extraction rates. Time series clustering was found to be the best method to analyze the studied piezometric database. Moreover, it was possible to characterize actual hydrodynamics, which will be useful for groundwater managers to make sustainable decisions.</p>

<p>Groundwater is the main water source for irrigation in arid and semi-arid areas. Unfortunately, it has been proven very difficult to prevent unauthorized extractions. The present work studies the application of wavelet analysis to detect and quantify the unfavorable effects of these extractions on the piezometry.</p><p>Wavelets have been widely applied for hydrologic time series analysis since the 1990s, with increasing popularity in recent years. This method can be applied to hydrologic series to reveal complex hydrological processes and evaluate complex latent factors, such as seasonal crop irrigation, controlling groundwater level fluctuations.</p><p>Records of the piezometric level from more than 150 piezometers were studied from 1975 to 2016 in the Almonte-Marismas aquifer (SW Spain). The majority of these time series presented periodicities between 11-12 months, which corresponded to hydrological cycles of recharge and discharge. Nevertheless, in some areas close to crop fields, periodicities of 2-3 and 4-6 months have been detected. In these cases, wavelet analysis could be used as a tool to prevent damage in areas in need of deeper legal control.</p>