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This paper describes the benefits of using more reliable local climate scenarios to analyse hydrological responses. It assumes that Regional Climate Model (RCM) simulations are more reliable when they provide better approximations to the historical basic and drought statistics after applying a bias correction to them. We have investigated whether the best solutions in terms of their approximation to the local meteorology may also provide the best hydrological assessments. We have carried out a classification of the corrected RCM simulations used for both approximations. This has been applied in the Cenajo basin (south-eastern Spain), where we show that the best approximations of the historical meteorological statistics also provide the best approximations for the hydrological statistics. The selected RCMs were used to generate future (2071–2100) local scenarios under the RCP8.5 emission scenario. The two selected RCMs predict significant changes in mean precipitation (−31.6 % and −44.0 %) and mean temperature (+26.0 % and +32.2 %). They also predict higher frequency (from 5 events in the historical period to 20 and 22 in the future), length (4.8 to 7.4 and 10.5 months), magnitude (2.53 to 6.56 and 9.62 SPI) and intensity (0.48 to 1.00 and 0.94 SPI) of extreme meteorological droughts. These two RCMs also predict higher changes in mean streamflow (−43.5 % and −57.2 %) and hydrological droughts. The two RCMs also predict worrying changes in streamflow (−43.5 % and −57.2 %) and hydrologically extreme droughts: frequency (from 3 to 11 for the first model and 8 events for the second model), length (8.3 to 15.4 and 29.6 months), magnitude (from 3.98 to 11.84 and 31.72 SSI), and intensity (0.63 to 0.90 and 1.52 SSI).

Groundwater recharge quantification is essential for sustainable groundwater resources management, but typically limited to local and regional scale estimates. A high-resolution (1 km x 1 km) dataset consisting of long-term average actual evapotranspiration, effective precipitation, a groundwater recharge coefficient, and the resulting groundwater recharge map has been created for all of Europe using a variety of pan-European datasets and seven national gridded recharge estimates. As an initial step, the approach developed for continental scale mapping consists of a merged estimate of actual evapotranspiration originating from satellite data and the vegetation controlled Budyko approach to subsequently estimate effective precipitation. Secondly, a machine learning model based on the Random Forest regressor was developed for mapping groundwater recharge coefficients, using a range of covariates related to geology, soil, topography and climate. A common feature of the approach is the validation and training against effective precipitation, recharge coefficients and groundwater recharge from seven national gridded datasets covering the UK, Ireland, Finland, Denmark, the Netherlands, France and Spain, representing a wide range of climatic and hydrogeological conditions across Europe. The groundwater recharge map provides harmonised high-resolution estimates across Europe and locally relevant estimates for areas where this information is otherwise not available, while being consistent with the existing national gridded estimates. The Pan-European groundwater recharge pattern compares well with results from the global hydrological model PCR-GLOBWB 2. At country scale, the results were compared to a German recharge map showing great similarity. The full dataset of long-term average actual evapotranspiration, effective precipitation, recharge coefficients and groundwater recharge is available through the EuroGeoSurveys’ open access European Geological Data Infrastructure (EGDI).

The presentation will summarize the main findings of the chapter “Water”[1] of the report “Climate and Environmental Change in the Mediterranean Basin – Current Situation and Risks for the Future”. This report was published in November 2020 and prepared by 190 scientists from 25 countries, who belong to the scientific network “Mediterranean Experts on Climate and Environmental Change”.Water resources in the Mediterranean are scarce, unevenly distributed and often mismatching human and environmental needs. Approx. 180 million people in the southern and eastern Mediterranean countries suffer from water scarcity (3 capita-1 yr-1). The main water use is for agriculture, and more specifically on the southern and eastern rim. Water demand for both tourism and agriculture peak in summer, potentially enhancing conflicts in the future. Municipal water use is particularly constrained in the south and will likely be exacerbated in the future by demographic and migration phenomena. Northern countries face additional risks in flood prone areas where urban settlements are rapidly increasing.Climate change, in combination with demographic and socio-economic developments, has mainly negative consequences for the water cycle in the Mediterranean Basin, including reduced runoff and groundwater recharge, increased crop water requirements, increased conflicts among users, and increased risk of overexploitation and degradation. These impacts will be particularly severe for global warming higher than 2°C.Adequate water supply and demand management offers some options to cope with risks. Technical solutions are available for improving water use efficiency and productivity, and increasing reuse. Seawater desalination is increasingly used as adaptation measure to reduce (potable) water scarcity in dry Mediterranean countries, despite known drawbacks in terms of environmental impacts and energy requirements. Promising solar technologies are under development, potentially reducing emissions and costs. Reuse of wastewater is a solution for agriculture and industrial activities but also recharge of aquifers. Inter-basin transfers may lead to controversies and conflicts. Construction of dams contributes to the reduction of water and energy scarcities, but with trade-offs in terms of social and environmental impacts.Overall, water demand management, which increases water use efficiency and reduces water losses, is crucial for water governance for a sustainable development. Maintaining Mediterranean diet or coming back to it on the basis of locally produced foods and reducing food wastes may save water but also carbon emissions while having nutritional and health benefits. [1] Fader M., Giupponi C., Burak S., Dakhlaoui H., Koutroulis A., Lange M.A., Llasat M.C., Pulido-Velazquez D., Sanz-Cobeña A. (2020): Water. In: Climate and Environmental Change in the Mediterranean Basin – Current Situation and Risks for the Future. First Mediterranean Assessment Report [Cramer W, Guiot J, Marini K (eds.)] Union for the Mediterranean, Plan Bleu, UNEP/MAP, Marseille, France, 57pp, in press. Download

In order to assess the anthropogenic impacts on groundwater quality we generally need to identify the natural conditions or Natural background levels (NBLs) within groundwater systems, which are used as references to assess the evolution of the contamination status. This information, in addition to the threshold values (TVs), which are derived from NBLs and based on specific criteria values for legitimate water uses and the environment (terrestrial and aquatic ecosystems), is required to appropriately assess of the chemical status of groundwater in accordance with the European Water Framework Directive and to analyse and propose potential measures where they are required.In literature, different methodologies are available to assess NBLs and reference TVs for different geochemical substances based on the available measurements of groundwater salinity (e.g. based on probability plots). In this work we analyze and compare three previously proposed methods for derivation of chloride NBLs, which is a conservation solute and is closely related to salt water intrusion in inland and coastal aquifers. We discuss and compare their applicability in pilots located in different settings (southern /northern European / Mediteranean/ North Sea /Baltic Sea) covering different typologies (detrital, karstic, fissured aquifers) and management issues (overexploitation, land use and land cover changes, etc). We perform sensitivity analysis to different constraints applied to remove samples affected by human activity (Nitrate and the brackish saline constraints) in the assessment of NBLs. Finally, based on this analysis, we propose a general approach for derivation of NBLs that could be applied to any of the tested pilots as well as other similar settings in Europe. This research has been partially supported by the SIGLO-AN project (RTI2018-101397-B-I00) from the Spanish Ministry of Science, Innovation and Universities (Programa Estatal de I+D+I orientada a los Retos de la Sociedad).This work has been partially supported by the GeoE.171.008-TACTIC and GeoE.171.008-HOVER projects from GeoERA organization funded by European Union’s Horizon 2020 research and innovation program.

45 Geological Survey Organisations (GSOs) from 32 European countries developed an ERA-NET Co-Fund Action: Establishing the European Geological Surveys Research Area to deliver a Geological Service for Europe (GeoERA). The GeoEra project HOVER (Hydrogeological processes and Geological settings over Europe controlling dissolved geogenic and anthropogenic elements in groundwater of relevance to human health and the status of dependent ecosystems) aims to gain understanding of the controls on groundwater quality across Europe using the combined expertise and data held by member states. Objectives of the HOVER work package 7 (WP7) are i) review of existing index methods for assessing the vulnerability of the upper aquifer to pollution and selection of the methods to be applied at the pilot and pan-EU scale, ii) compilation and harmonization of input data sets required for assessing vulnerability, and iii) assessment of aquifer vulnerability to pollution (both in maps and 2-d schematic cross sections).The selected methodology adopted in this project is DRASTIC, which will be applied in ten pilot areas and at the pan-European scale. In karst regions, however, the COP method will be applied in the pilots. This is accompanied with comparisons with the outcomes of existing national vulnerability assessments. It is anticipated to validate the resulting vulnerability maps at the pilot level using available groundwater nitrate contamination information.

Climate change (CC) already have widespread and significant impacts in Europe, which is expected to increase in the future. Groundwater plays a vital role for the land phase of the freshwater cycle and have the capability of buffering or enhancing the impact from extreme climate events causing droughts or floods, depending on the subsurface properties and the status of the system (dry/wet) prior to the climate event. Understanding and taking the hydrogeology into account is therefore essential in the assessment of climate change impacts.The Geological Survey Organisations (GSOs) in Europe compile the necessary data and knowledge of the groundwater systems across Europe. The overall vision of the project “Tools for Assessment of ClimaTe change ImpacT on Groundwater and Adaptation Strategies – TACTIC” is to enhance the utilisation of these data and knowledge of the subsurface system in CC impact assessments, and the identification and analyses of potential adaptation strategies. To reach this vision, the objective of TACTIC is to contribute to the development of coherent and transparent assessments of CC impacts on groundwater and surface water, supporting improved EU policy making, and providing decision support for stakeholders and decision makers. To accomplish this, an infra-structure among European Geological Survey Organisations are developed in TACTIC to foster advancement and harmonisation of CC assessments, made up by: 1) The TACTIC Toolbox, consisting of relevant tools and methods for CC impact assessments, 2) TACTIC guidelines that will guide GSOs and other relevant stakeholders on the selection of appropriate tools and their use for producing comparable results, 3) The European Geological Data Infrastructure (EGDI) where data, reports and open-access papers will be stored and made freely available The project is centred around 40 pilot studies covering a variety of CC challenges as well as different hydrogeological settings and different management systems found in Europe. The pilot activities are coordinated centrally in the project, to ensure that assessments, to the extent possible, are harmonised and can be compared across pilots. Synthesizing the experiences and results from the pilots will enable the development of a guideline and future roadmap, with the aim of 1) encouraging more GSOs to contribute in CC impact assessments 2) providing guidance to make the learning curve less steep and 3)ensuring that new assessments are comparable with assessments conducted in TACTIC.TACTIC is part of the Horizon 2020 ERA-NET on Applied Geoscience (GeoERA) and together with the three other GeoERA groundwater projects, TACTIC will provide new and important data for further development of the European Geological Data Infrastructure (EGDI) with publicly available data enabling the development of EU-wide decision support systems for sustainable management of subsurface resources in a changing climate.This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 731166.

Each experimental data measured by an instrument has an associated spatial (and temporal) support to which the measurement is assigned. In this sense a logger provides the temperature at a particular spatial location and has a point-support while satellite derived temperatures have an areal support equal to the size of the pixel of the satellite image (i.e. the spatial resolution of the image). Thus, when combining or merging both types of measurement, their support must be taken into account. In fact, in nature there is a continuous temperature field that is only accessible from empirical data with its associated support. In this work three sources of data have been considered to model the variability of temperature at two scales in the Southern Rocky Mountains across the northern Front Range of Colorado (NFRC). The coarse scale uses the NRCS SNOTEL stations across the NFRC and the fine scale uses iButton sensors at the Colorado State University Mountain Campus (CSUMC) located within the NFRC. The MODIS-based land surface temperature (LST), which has a spatial resolution of about 1 km, has been considered for both scales. The SNOTEL stations and the iButton sensors have a point support while satellite LST has an areal support. The main goal of this work is to assess the variability of the temperature field at both scales, taking into account the support effect of each set of experimental data, by using a geostatistical approach.This research has been partially supported by the SIGLO-AN project from the Spanish Ministry of Science, Innovation and Universities (Programa Estatal de I+D+I orientada a los Retos de la Sociedad).

Climate change will modify the availability of snow resources in the future. Thus developing methodologies to assess impacts of potential future climate change scenarios on snow variables is a key subject. In this work we combine several previous developed methodologies (downscaling climate change scenarios to local scale, cellular automata models, and stochastic weather generators) to assess impacts of future climate change scenarios and its uncertainty on snow cover area through a Montecarlo simulation. The cellular automata model uses climatic indices (precipitation and temperature) as driving variables to estimate snow cover area. Future scenarios of these variables can be generated using bias correction and delta change approaches and different regional climate models. The stochastic weather generators allow us to produce multiple series of precipitation and temperature based on the statistical characteristics of the future local scenarios generated. These multiple series can be used as inputs of the cellular automata model in order to assess the future snow cover area and its uncertainty. The main advantages of the proposed methodology are its applicability in cases with limited information and in mountain ranges scales. The methodology has been applied to the Sierra Nevada mountain range in southern Spain. This area has a Mediterranean climate very sensitive to climate change. Using the future precipitation and temperature scenarios generated considering the Representative Concentration Pathways 8.5 (RCP8.5) for the period 2071–2100, we obtain a significant reduction in snow cover area, with mean values of 59.0% for the local scenarios generated with a delta change approach, and 61.7% for those one generated with the bias correction approach.This research has been partially supported by the SIGLO-AN project (RTI2018-101397-B-I00) from the Spanish Ministry of Science, Innovation and Universities (Programa Estatal de I+D+I orientada a los Retos de la Sociedad).

The spatial distribution of snow thickness in extensive alpine regions can be estimated with high spatial resolution from LIDAR data capture. However, due to the significant economic cost of these activities, its application is limited, especially to cover large areas. Traditionally, snow thickness has been estimated by applying interpolation methods and/or hydrological models that approximate the distribution of snow from fieldwork data. In some places there is permanent infrastructure that facilitates the collection of data. In Spain, within the framework of the national snow depth monitoring program (ERHIN, initiated in 1981), an infrastructure consisting of a network of poles distributed over various mountain ranges was generated to obtain measurements by direct observation from helicopter flights (1-3 per year). This monitoring activity has been drastically reduced and even cancelled in some mountain ranges in recent years as a result of budget cuts. In order to maintain the observation of snow, we propose a novel approach to involve groups of volunteers to take advantage of the existing (or optimally increased) infrastructure that are underutilized or in disuse, to gather photos of poles as a means of monitoring snow thickness. The proposal is being applied in the Sierra Nevada (Southern Spain), and may be extended in the future across the whole Spain. The tasks performed to achieve the objective are: 1) Inventory of infrastructures and potential volunteer: The 23 poles installed by the ERHIN program in Sierra Nevada are being marked to facilitate their identification in photos sent in by volunteers. An inventory of potential volunteer and user groups has been compiled; 2) Optimum design of snowpole network for monitoring snow depth: The aim is to identify the optimal location of new poles in order to minimize uncertainty in estimates of snow depth. To solve this problem, we have employed a regression model that estimates the spatial distribution of snow depth and its uncertainty 3) Generation of tools to supply and display information: Mobile application and web platform. For the success of the activity, we need user-friendly applications that include relevant local information (e.g., location of the poles) and an adequate link to the project web for supplying and storing information; 4) Maximization of participation. Program of incentives. We have involved key institutions, such as Sierra Nevada Natural Park and Andalusian Mountaineering Federation (FAM), which predict a high participation rate by its members. To encourage collaboration, participation by volunteers will be published, including ranking and honorary awards to the most active. As stated by the Andalusian Federation of Mountaineers, this ‘competition’ will be an additional incentive to increase participation by mountaineers. The task will have a significant impact with a low economic cost; 5) Dissemination and communication of relevant: It includes the design and distribution of posters and brochures to the main potential groups of volunteers.This research has been partially supported by the SIGLO-AN project (RTI2018-101397-B-I00) from the Spanish Ministry of Science, Innovation and Universities (Programa Estatal de I+D+I orientada a los Retos de la Sociedad).

Gauges modify wind fields, producing important undercatch in solid precipitation. For this reason, solid precipitation measurements show significant bias with respect to real values, especially under windy conditions. In this work we propose a methodology that combines geostatistical and hydrological models to perform a preliminary assessment of global undercatch and precipitation patterns (distribution between solid and liquid phase and spatial gradient with elevation) in alpine regions. It is based on the available information about daily natural streamflow and daily climatic data (precipitation and temperature) in the catchment. We want to analyse long time periods in order to take into account the stochastic behaviour of natural streamflow and climatic variables. A preliminary assessment of temperature and precipitation fields is performed by applying various geostatistical approaches assuming some hypothesis about the relationship between climatic fields and altitude. The generated fields are then employed as inputs of conceptual hydrological models, which includes two parameters to correct the solid and liquid precipitation, respectively. We have considered different hydrological approaches (SRM, HBV and a Témez model with a simple degree-day approach). The parameters are calibrated by minimizing the difference between the simulated and historical natural streamflows and/or snow cover area. It allows us to identify the best combination of geostatistical and hydrological models to approximate streamflow, to perform a global preliminary assessment of the undercatch of solid and liquid precipitation and their precipitation patterns by analysing spatial gradients with elevation. The methodology was applied in the Canales Basin, an alpine catchment of the Sierra Nevada (Spain).This research has been partially supported by the SIGLO-AN project (RTI2018-101397-B-I00) from the Spanish Ministry of Science, Innovation and Universities (Programa Estatal de I+D+I orientada a los Retos de la Sociedad) and by the GeoE.171.008-TACTIC project from GeoERA organization funded by European Union’s Horizon 2020 research and innovation program

The snow dynamics in alpine systems governs the hydrological cycle in these regions. However, snow data are usually limited due to poor accessibility and limited funds. On the other hand, the majority of scientific studies about snow resources are carried out at mountain slope or basin scale. The main goal of this work is to propose a parsimonious methodology to estimate snow water equivalent (SWE) at mountain range scale. A regression model that includes non-steady explanatory variables is proposed to assess snow depth dynamic based on the information coming from snow depth point observations, a digital elevation model, snow cover area from satellite and a precipitation index representative of the area. The main advantages of the method are its applicability in cases with limited information and in mountain ranges scales. In the proposed methodology different regression model structures with different degrees of complexity are calibrated combining steady and non-steady explanatory variables (elevation, slope, longitude, latitude, eastness, northness, maximum upwind slope, radiation, curvature, accumulated snow cover area and precipitation in a temporal window) and four basic mathematical transformations of these variables (square, root square, inverse and logarithm). In the case of the temporal variables different time windows to define the accumulated values of the explanatory indices have been tested too. We have applied the methodology in a case study, the Sierra Nevada mountain range (Southern Spain), where the calibration has been performed by using the snow depth data observation provided by the ERHIN program which have a very low temporal frequency (2 or 3 measurement per year). When only non-steady explanatory variables are considered, the coefficient of determination of the global spatial estimation model is 0.55. When we also include non-steady variables we obtain an approach with a coefficient of determination of 0.62. We have also calibrated a new regression approach by using, in addition to the ERHIN program information, data coming from a detailed temporal series of snow depth in a new specific location, which has allow to obtain models with R² of 0.59 (for steady explanatory variables) and 0.64 (including also non-steady explanatory variables). The dynamic of the snow density in the mountain range has been estimated by means of a physically based simulation driven by WRF data. Combining the snow depth and the density approaches we have estimated the final SWE in Sierra Nevada. This research has been partially supported by the SIGLO-AN project (RTI2018-101397-B-I00) from the Spanish Ministry of Science, Innovation and Universities (Programa Estatal de I+D+I orientada a los Retos de la Sociedad).

Wetlands protect and improve water quality, store floods, maintain surface water during dry periods and provide valuable habitats for wildlife. However, wetlands may be very sensitive to climate change and appropriate monitoring works and modelling activities are needed in order to design sustainable management strategies. In this work we aim to analyze the dynamics of the Lagunas de Ruidera wetland (Spain) for the period 1984−2015. We applied the supervised classification method to LANDSAT satellite images (missions 5, 7 and 8) with a spatial resolution of 30 m and a temporal resolution of around 16 days. In this case study two different water bodies in terms of surface reflectance have been detected. Both zones have been considered for the calibration of the water detection algorithm through a non-steady threshold. We have also analysed daily surface reflectance data from MODIS (MOD09GQ) to complete the temporal dynamic of the wetland. We obtained some correlations between surface reflectance of LANDSAT and MODIS but the efficiency to detect water surfaces of the second is considerably lower due to its 250 m spatial resolution. The results show a minimum and a maximum wetland surface of around 2.7 and 6.3 km² for the considered period. We have also analysed the relationship of the wetland surface with precipitation and aquifer discharge (obtained from a groundwater flow model). For the mean year at monthly scale, the maximum correlation between the wetland surface and precipitation is obtained for a lag of one month. The wetland surface has a similar monthly trend to the aquifer discharge and the maximum correlation is obtained without lag.This research has been partially supported by the SIGLO-AN project (RTI2018-101397-B-I00) from the Spanish Ministry of Science, Innovation and Universities (Programa Estatal de I+D+I orientada a los Retos de la Sociedad) and by the GeoE.171.008-TACTIC project from GeoERA organization funded by European Union’s Horizon 2020 research and innovation program.

Any change in the components of the water balance in a coastal aquifer, whether natural or anthropogenic, can alter the fresh water-salt water equilibrium. In this sense Climate change (CC) and Land Use and Land Cover (LULC) change might significantly influence the availability of groundwater resources in the future. These coastal systems demand an integrated analysis of quantity and quality issues to obtain an appropriate assessment of hydrological impacts using density-dependent flow solutions. The aim of this work is to perform an integrated analysis of future potential global change scenarios and their hydrological impacts in a coastal aquifer, the Plana Oropesa-Torreblanca aquifer. It is a Mediterranean aquifer that extends over a 75 km2 in which important historical LULC changes have been produced and are planned for the future. Future CC scenarios will be defined by using equi-feasible and non-feasible ensemble of projections based on the results of a multi-criteria analysis of the series generated from several Regional Climatic Models with different downscaling approaches. The hydrological impacts of these CC scenarios combined with future LULC scenarios will be assessed with a chain of models defined by a sequential coupling of rainfall-recharge models, crop irrigations requirements and irrigation returns models (for the aquifer and its neighbours that feeds it), and a density dependent aquifer approach. This chain of models, calibrated using the available historical data, allow testing the conceptual approximation of the aquifer behaviour. They are also fed with series representatives of potential GC scenarios in order to perform a sensitivity analysis regarding future scenarios of rainfall recharge, lateral flows of the hydraulically-connected neighbouring aquifer, agricultural recharge (taking into account expected future LULC changes) and Sea Level Rise (SLR). The proposed analysis is valuable to improve our knowledge about the aquifer and so comprise a tool to design sustainable adaptation management strategies taking into account the uncertainty in future global change conditions and their impacts. The results show that CC and LULC scenarios produce significant increase in the variability of flow budget components and in the chloride salinity concentration. They also show a low sensitivity to the SLR scenarios, especially in terms of hydraulic head.