The Mediterranean Basin is a region naturally prone to drought due to its climatic variability. These variations are being exacerbated by the current climate change situation, with projections agree that the frequency and severity of these extreme events will increase. Paradigmatically, this region has based its socioeconomic development on activities directly related to water resources, such as agriculture and tourism. In addition, the Mediterranean basin is delimited by mountain ranges close to the sea that draw different-sized catchments where water resources availability is directly linked to snow presence. Therefore, snow dynamics need to be considered when analyzing droughts. Cold and warm winter droughts over these mountains have special characteristics since winter temperatures are around zero and conditions both snow accumulation and ablation directly.However, the general drought indices, SPI (Standardized Precipitation Index) or SPEI (Standardized Precipitation-Evapotranspiration Index), which are the most widely used tools to characterize droughts, do not explicitly account for snow. New snow drought indices have been proposed, for instance, the Standardized Snow Water Equivalent Index (SSWEI). They are, on the one hand, based on snow variables typically derived from modelling and are subject to large uncertainties over Mediterranean mountain catchments; and, on the other hand, focus mainly on the ablation process. This work proposes to define a new drought index, introducing the concept of snowfall drought in Mediterranean mountain regions. Then, snowfall is the target variable used to define the drought index, the Standardized Snowfall Index (SSNI). The index definition is based on the methodology already proposed when defining other drought indices, evaluating, in this case, eight different candidate distributions, and standardizing their probability using a Normal distribution. The aggregation time selected for the snowfall series was 12 months. HydroGFD3 bias-adjusted reanalysis data (daily time-step and 25 km spatial resolution) for precipitation and temperature during the period 1980-2024 are used in the study. Snowfall is determined using a variable temperature thresholding over the whole Mediterranean Basin (2266 catchments). The SSNI was evaluated against the SPI index to assess the differences in detecting drought between the two indices.The results show that the candidate distribution selected differed depending on the location of the catchment. That is, the Gamma distribution was the best at capturing the snowfall drought dynamics in high elevation catchments, Log-Logistic in the eastern Mediterranean catchments, and Weibull in the western ones. The number of drought periods also differed spatially, ranging from 0 to 22 episodes with a duration between 0 and 20 months, and a clear relationship between both: the longer the duration, the smaller its frequency. In addition, this new index helps better quantify the effect of a snow deficit in the meteorological drought definition - from all months identified with a drought, 38% of them would not have been classified as drought months, only accounting for precipitation and not for snowfall - and consequently to better understand the drought propagation cascade over the region.Acknowledgments: This work is part of the project CNS2023-145125, funded by MCIN/AEI/10.13039/501100011033 and European Union “NextGenerationEU”/PRTR.

Snow cover shapes climate, ecosystems, water resources, and socio-economic activities, yet its long-term European variability remains poorly known due to short and fragmented observational records. Here, we present a continent-wide, 600-year reconstruction of monthly European snow cover extent at 2° spatial resolution, derived by combining reanalysis data through a machine learning technique. The record reveals an unprecedented seasonal reorganization at monthly scale since around 1850: December–January snow cover extent shrinks by up to 20%, while April–May snow cover extent declines by up to 30%, especially at latitudes higher than 50°N. February and March are comparatively stable. While snow cover exhibits the strongest sensitivity to rising temperatures, reduced precipitation still leaves a noticeable imprint, particularly in the Mediterranean basins and Scandinavia. These changes place recent loss of snow cover in a multi-centennial context and underline the urgent need to assess impacts on sensitive ecosystems, water resources, and socio-economic sectors. Our dataset provides a crucial baseline for adaptation planning and benchmarking climate model simulations. European snow-cover extent has undergone an unprecedented seasonal reorganization since around 1850, with monthly declines of up to 30%, according to a 600-year reconstruction combining reanalysis data and machine learning method.

Abstract. Aerodynamic roughness lengths are a key source of uncertainty in modeling turbulent heat fluxes over snow-covered surfaces, particularly in complex terrain. We investigate the influence of instrumental and measurement uncertainties and terrain complexity on roughness length estimates and MOST-based turbulent flux calculations using data from twelve eddy-covariance (EC) stations across the European Alps, covering slopes from 0.5° to 27°. Two stations with multiple measurement levels allow for a detailed analysis of vertical wind profiles. Several bulk aerodynamic methods and roughness length parameterizations are evaluated. Roughness lengths derived from logarithmic wind profiles under near-neutral conditions vary by up to an order of magnitude between measurement heights, indicating a strong sensitivity to sensor height and potential violations of the law of the wall. Instrumental and measurement uncertainties, especially under predominantly near-neutral or stable conditions with weak vertical gradients, lead to large relative errors in scalar roughness lengths and propagate into modeled turbulent fluxes, resulting in relative errors of up to 38.9% for turbulent sensible heat flux and up to 56.5% for turbulent latent heat flux. Roughness lengths for momentum and scalars vary substantially among sites, and commonly assumed fixed ratios between them do not hold. No systematic degradation in bulk aerodynamic method performance with increasing slope is observed, suggesting that limitations arise from the general application of MOST in complex terrain. When EC-derived roughness lengths are unavailable, prescribing a constant roughness length (0.61 mm) for momentum and scalars provides the most robust EC-independent results.

La teledetección puede ser una herramienta de apoyo eficaz para evaluar el estado ecológico de las masas de agua, especialmente en sistemas regulados donde los umbrales hidrológicos fijos no siempre reflejan la respuesta ecológica real. Este estudio examina el régimen hidrológico en la cuenca del río Giribaile (Andalucía) y cómo se ajusta a los umbrales definidos por el Plan Hidrológico vigente, analizando su grado de cumplimiento, y explora cómo la dinámica de la vegetación de ribera, evaluada mediante series de imágenes del satélite Landsat, puede integrarse para ajustar los umbrales de caudal ecológico según las condiciones locales. El régimen de caudal incumple con frecuencia los umbrales establecidos en el plan, lo que evidencia la necesidad de estrategias de gestión específicas para incorporar las dinámicas de distintas masas de agua. El NDVI captura la fenología ribereña, pero su relación con el caudal no es directa ni lineal y depende de múltiples factores ambientales. Sin embargo, su monitoreo ayuda a detectar situaciones de desequilibrio ecológico y puede servir para adaptar y actualizar los umbrales de caudal.

Mediterranean agrosilvopastoral ecosystems (MAEs), such as the Dehesa/Montado in Spain (SP)/Portugal (PT), Meriagos in Italy (IT) and valonia oak forests in Greece (GR), provide essential environmental services and play a significant role in supporting local communities, their economies, and well-being. However, the MAEs are highly vulnerable to the impacts of climate change effects, including rapid warming and heat waves, prolonged droughts with intermittent and sudden heavy rainfall and mediterranean hurricanes (medicanes) and wildfires. Water table decline, groundwater flow depletion, tree mortality, poor tree natural regeneration, soil degradation, decrease of biodiversity, and drastic modification of habitat pattern are the major direct consequences of the above-mentioned changes. Addressing these issues requires tailored sustainable solutions and transformative actions to support local communities and authorities in building climate resilience. The DRYAD project supports the EU Mission Adaptation to Climate Change by demonstrating climate-resilient nature-based solutions (NbS) tailored to MAEs. DRYAD aims to enhance MAE resilience to climate change through locally adapted NbS designed in collaboration with farmers and other stakeholders. The DRYAD project is centered around the development, testing and demonstration of NbS in five Demonstration Regions (DRs). The most promising NbS will be transferred to the three Replication Regions (RR). Furthermore, DRYAD supports a multi-level and cross-sectoral integrated and adaptive management governance by developing a Decision Support System (DSS). DRYAD mobilizes regional and local authorities and stakeholders, research entities, private/public foundations, companies and citizens and involves them in co-creation, co-implementation, and co-validation processes through Living Labs. This will lead to the creation of widely re-applicable NbS with long-lasting impacts. The project envisages the development of tools and implementation guidelines to promote sustainable and climate-resilient practices and facilitate regional adaptation plans, contributing to the Nature Restoration Law regarding resilient nature and climate adaptations. DRYAD will address a range of NbS across different spatial scales and under various management and climate scenarios. The proposed approaches consider the complex interactions within natural systems, the diverse land uses and practices in MAEs, the intricate governance structures, and the diverse interests of stakeholders. The objectives and expected outcomes of DRYAD are presented with special emphasis on its novel technological developments which include: 1) Real-time and cost-effective monitoring solutions using in-situ LoRaWan and remote sensing (RS) data for NbS implementation in pilot demonstration areas (PDAs); 2) Development of a web-based geospatial database management system (GDMS) for managing space/time field and RS data; 3) Performing integrated ecohydrological models by coupling SCOPE, STEMMUS and MODFLOW6 codes to assess drought-related plant-soil-surface water-groundwater interactions; 4) Using models to support the novel NbS implementations; 5) Upscaling of NbS from local (PDA) to regional (DR) scales; 6) Replication of NbS in RR; 7) Development of a DSS and its embedding in GDMS; and 8) Dissemination of DRYAD results via a DSS, operational on computers and mobile phone apps.Acknowledgments: This research was performed within DRYAD Project, which has received funding from the European Union’s Horizon Europe research and innovation program under grant agreement 101156076.

The compliance of environmental flows following the recommendations of the Water Framework Directive (WFD) is a crucial aspect in the management of reservoir water allocation. This issue is especially challenging in catchments with long and recurrent drought periods, such as those affected by the Mediterranean climate. There are still some gaps to be addressed by managers and water authorities. For instance, the correct definition of minimum environmental flow (MEF) to be fulfilled. These MEF values, which are set in the River Basin Management Plan (RBMP), commonly vary slightly throughout the year. Sometimes, this assumption is not accomplished because these values are above those that would have been observed under natural conditions. Therefore, in these regions it is decisive to adapt the MEF requirements to the local hydrometeorological seasonally. This work proposes the combination of historical streamflow and precipitation data to assess the viability of using seasonal hydrometeorological patterns in the definition of the MEF rates. For that, several monitored water bodies were analysed. Streamflow information from gauging stations and precipitation data were selected in the two main river basin districts in the South of Spain: the Guadalquivir River Basin, and the Andalusian Mediterranean Watersheds River Basin. First, for each case, we reviewed the compliance of the MEF rates analysing when these threshold values were or not achieved at the monthly scale. In addition, we analysed the seasonal variability in terms of both precipitation and streamflow and compared these outcomes with the seasonal variations of the MEF. This analysis was carried out during 10 hydrological years, from September 2010 to August 2020.According to our results, most of the locations were below 28% of accomplishment during the summer months. This percentage increased when the period analysed was the winter. However, this percentage was below 50% in some locations. On the contrary, only in those locations which are fed by mountain catchments, the accomplishment was fulfilled in 73-100% during the whole year. The joint seasonal analysis of precipitation and streamflow highlights that the MEF established in the RBMP were oversized in most of the cases, overlooking the precipitation patterns.This work showed that a revision of the MEF values set by the RBMP is required. That is especially significant in locations where seasonal variations of the MEF are null or imperceptible. Our outcomes will help to set the basis for the design of a new methodology when defining MEF. Hence, this new approach will consider not only water quantity but also hydrometeorological seasonal variability as the main step to truly address water management from the perspective of the WFD. Acknowledgments: This work has been funded by the project TED2021-130937A-I00, ENFLOW-MED “Incorporating climate variability and water quality aspects in the implementation of environmental flows in Mediterranean catchments” with the economic collaboration of MCIN/AEI/10.13039/501100011033 and European Union “NextGenerationEU”/Plan de Recuperación, Transformación y Resiliencia.

Globalization, population growth and climate changes are directly impacting the global water cycle with consequences at the local scale. For instance, water extremes, scarcity and flooding, have overpassed the natural cycles to which water managers were used to. These breaking boundary conditions are particularly present in Mediterranean semiarid areas such as the Andalucia region, southern of Spain. These new scenarios require updated management strategies and skills in the water management field, Civil engineers have a crucial role, not only in the designing of new infrastructure but also in the planification and participation at the political debate from different perspectives. Therefore, these new skills and competences have to be developed during the undergraduate period. In fact, the use of new teaching methodologies and strategies has become a very common tool in the higher education system. Specifically, subjects such as Hydrology can create the right environment where students can be trained to propose solutions and resolve water management conflicts in which numerous interests are present. Therefore, the use of teaching strategies such as role play debates for the resolution of water conflicts appear as a fundamental methodology in the civil engineering field. This work presents the results of the implementation of role play in the subject of Hydrology in the Civil Engineering program at the University of Cordoba during the last 5 academic years. The role-play fronts students into a real water conflict scenario: A generalized drought and 10 months without rainfall make it impossible to meet the needs of both society and irrigation communities in two towns. One of the municipalities wants to build a small dam for water management and leisure activities; however, the vicinity municipality, which is located within the catchment, is not in favor of the construction of this infrastructure. All the agents involved in the water conflict are represented by students. The roles were assigned randomly to the students.The experiment has two periods, the first one was a pilot case during the 2019-2020 to enable us the definition of the best assignment. The second period from 2020-2021 until 2023-2024 represents the 4 years study case, where students have faced the same hydrological scenario, in two phases, one face-to-face with oral debate, and another online and written in which the role of the first face-to-face part was changed.The student performance results are complemented with three kinds of surveys, i) an quality improvement survey, ii) self-analysis of acquired competences and iii) a pre debate and post event survey that analyzes the student perspective on water management. The results obtained were very satisfactory. The competencies that the students consider to have improved the most are i) ability to argue and defend ideas, ii) ability to research information and iii) ability to develop a critical spirit. Moreover, overall satisfaction with the activity has been very high in all years.

To better understand the increasing human impact on the water cycle and the feedbacks between hydrology and society, the International Association of Hydrological Sciences (IAHS) organized the scientific decade "Panta Rhei - Everything Flows: Change in hydrology and society" (2013-2022). A key finding is the need to use integrated approaches to assess the co-evolution of human-water systems in order to avoid unintended consequences of human interventions over long periods of time. Additionally, substantial progress has been made in leveraging new data sources on human behaviour, e.g. through text mining of social media posts. Much has been learned about detecting hydrological changes and attributing them to their drivers, e.g. quantifying climate effects on floods. To achieve further progress, we recommend broadening the understanding, the discipline and training activities, while at the same time pursuing synthesis by focusing on key themes, developing innovative approaches and finding sustainable solutions to the world's water problems.

Dehesas, a biodiversity-rich Mediterranean agro-silvopastoral ecosystem with seasonal water availability, are highly sensitive to changes in both climatic conditions and management practices. While droughts naturally occur, climate change exacerbates water scarcity, leading to i) low and unpredictable pasture and tree production, ii) decreased pasture quality and shrub encroachment, iii) oak tree decline, mortality, and lack of natural regeneration, and iv) increased soil exposure to degradation and nutrient losses. These impacts jeopardize the long-term ecological and economic sustainability of dehesas, creating significant profitability challenges for rural communities.Given the high degree of human intervention in dehesa, management practices are closely linked to the water fluxes, influencing the vulnerability to stressors. Integrating water availability projections into management planning and promoting sustainable water use are critical strategies to enhance the resilience of these systems. Under the umbrella of the European project DRYAD (“Demonstration and modelling of Nature-based solutions to enhance the resilience of Mediterranean agro-silvo-pastoral ecosystems and landscapes”), we are developing process-based Nature-Based Solutions (NBS) aimed at improving ecosystem management to mitigate vulnerability to drought. These NBS focus on monitoring pasture productivity and tree mortality in relation to water stress to include these linkages in management strategies. Key outputs include composite risk and recurrence indexes integrating Earth Observation and forecasting alongside a human intervention factor represented as a coefficient of change to assess the impacts of management strategies.The NBSs are being tested in two pilot areas in Andalusia, Spain, with a view to replication and upscaling in other Mediterranean regions. Different scales will be assessed, ranging from on-farm to watershed levels, to determine the optimal management depending on the water stress conditions. Close collaboration with stakeholders is needed to ensure the effective implementation of these solutions, addressing practical needs and facilitating adoption. This approach contributes to the long-term resilience of dehesas by supporting sustainable practices, enhancing ecosystem services, and bolstering rural livelihoods. Acknowledgments: This research was performed within DRYAD Project, which has received funding from the European Union’s Horizon Europe research and innovation program under grant agreement 101156076. This work is part of the grant RYC2022-035320-I, funded by MCIN/AEI/10.13039/501100011033 and FSE+

The headwaters catchments of the Sierra Nevada mountain range in Southern Spain are a clear example of Mediterranean mountain catchments where climate variability enhances the spatiotemporal complexity of snow dynamics. The changeable patterns of snowfall combined with the usually mild and sunny winters result in shallow snowpacks that favor various accumulation and melting cycles and, consequently, the appearance of a characteristic snow patchy distribution. Remote sensing techniques has proven to be the most effective solution to monitor this characteristic snow distribution. Among the different satellite constellations, Landsat still provides the most extended time series with an adequate spatial resolution for capturing the long-term snow spatial variability over these areas. Applying a spectral mixture analysis to the long-term Landsat dataset over the area has allowed us to not only improve the spatial representation of snow that binary classification gave but also to define and idetenfigy the presence of pixels that are not fully covered by snow: mixed pixels. This work proposes using these mixed pixels as an indicator of snow cover occurrence and persistence and linking its frequency and evolution with snow dynamics, from snowfall to snow ablation patterns. Twenty years of Landsat imagery has been analyzed over an area composed of the five main headwaters in the Sierra Nevada mountain range. A spectral mixture analysis, considering the three main land cover over the region: snow, shallow vegetation, and rocks, was performed to define the land cover partitioning in each pixel in the area. The distributed snow-mixed pixels' spatiotemporal persistence and evolution over the region were statistically analyzed. The analysis of the occurrence of these pixels shows that their presence can reach up to 40% of the mountain range during some specific years, such as wet and cold years. The clustering of mixed pixels has also allowed us to identify common areas where patchy conditions prevail. A clear differential pattern has been observed between catchments in the southern face, which is highly influenced by the presence of the sea, and in the southern face, which has a more continental climate. Finally, analyzing the temporal evolution of these pixels has allowed for the spatial assessment of areas where snowfalls can be significant and/or frequent. Still, persistence is not enhanced by the local conditions. In general, this work highlights that accounting for subgrid variability is key in this area for understanding snow spatiotemporal patterns, determining the more vulnerable regions facing potential changes in the snow regime due to global warming and climate variability, and further assessing water resources planning through the improvement of hydrological models predictions.Acknowledgment: This research was funded by the Spanish Ministry of Science and Innovation through the research project PID2021-12323SNB-I00, HYPOMED—“Incorporating hydrological uncertainty and risk analysis to the operation of hydropower facilities in Mediterranean mountain watersheds.”

Over the past 20 years, the Hydrological Ensemble Prediction Experiment (HEPEX) international community of practice has advanced the science and practice of hydrological ensemble prediction and its application in impact- and risk-based decision-making, fostering innovations through cutting-edge techniques and data that enhance water-related sectors. Here, we present insights from those 20 years on the key priorities for (co)creating broadly applicable hydrological forecasting systems that add value across spatial scales and time horizons. We highlight the advancement of hydrological forecasting chains through rigorous data management that incorporates diverse, high-quality data sources, data assimilation techniques, and the application of artificial intelligence (AI) to improve predictive accuracy. HEPEX has played a critical role in enhancing the reliability of water resources and water-related risk management globally by standardizing ensemble forecasting. This effort complements HEPEX's broader initiative to strengthen research to operations, making innovative forecasting solutions both practical and accessible. Additionally, efforts have been made toward supporting the United Nations Early Warnings for All initiative through developing robust and reliable early warning systems by means of global training, education and capacity development, and the sharing of technology. Finally, we note that the integration of advanced science, user-centric methods, and global collaboration can provide a solid framework for improving the prediction and management of hydrological extremes, aligning forecasting systems with the dynamic needs of water resource and risk management in a changing climate. To effectively meet future demands, it is crucial to accelerate the integration of innovative science within operational frameworks, fostering adaptable and resilient hydrological forecasting systems globally. SIGNIFICANCE STATEMENT: We present transformative advancements in hydrological forecast- ing that integrate diverse, high-quality data sources , advanced modeling techniques, including artificial intelligence (AI)/machine learning (ML) to enhance predictive accuracy across different time scales and spatial dimensions. Through Hydrological Ensemble Prediction Experiment (HEPEX)'s contributions in standardizing ensemble predictions, we have significantly improved forecast reli- ability and support across various water-related sectors. The efforts of the HEPEX community of practice also underpin robust early warning systems through extensive global capacity develop- ment and technology sharing, in alignment with the United Nations Early Warnings for All initia- tive. By fostering strategic collaborations, we bridge the research-to-operations gap, promoting forecasting solutions that are both practical and accessible. HEPEX body of work enhances global disaster resilience, making substantial contributions toward sophisticated, actionable hydrological forecasting and management worldwide.

In the current context of global warming, droughts frequency and severity have increased in the Mediterranean Region. The past hydrological year, 2022-2023, was a clear example of water scarcity after some years with precipitation below the historical mean threshold. In mountain catchments, this reduction in precipitation has resulted in a significant decrease of the seasonal snow and a shift in the common snowfall patterns. The coastal-mountain catchments in the Sierra Nevada mountain range (southern Spain) exemplify this situation. The use of drought indices, which are defined using hydrometeorological information, has been the most used tool for the development of warning systems and the definition of adaptation strategies. Indexes like the Standardised Precipitation Index (SPI) or the Streamflow Drought Index (SSDI), have been widely used when characterising both meteorological and hydrological droughts. However, in high mountain areas, the role of snowfall should also be taken into account in this index definition. Snowfall patterns clearly modifies the precipitation-runoff response on a seasonal basis, changing the water balance at different time scales. Therefore, “snow drought” might result in scarcity conditions even though no warning stage has been reached regarding drought’s alerts yet, and it should also be taken into account in the defintion of these indexes. Furthermore, the intrinsic characteristics of the snow cover in these regions: seasonality, with snow generally present from mid-autumn to mid-spring; low thickness and high density; various accumulation-ablation cycles throughout the year; and, high losses due to evaposublimation, make the specific definition even more necessary.This work aims to characterise snowfall droughts in semiarid mountains, understanding its connection to precipitation and hydrological droughts, assessing the viability of using drought indexes as tools for a better water-management decision-making. The Guadalfeo Catchment in the Sierra Nevada Mountain Range has been chosen as a representative coastal-mountain catchment of the Mediterranean basin to carry out this analysis.Both SPI and a Standardised Snowfall Index (SSI, defined as SPI but using snowfall data) were calculated in the study area on different time scales for a reference period of 40 years (1960-2020), together with SSDI from the available streamflow time series. The joint analysis of SSI and SPI on each time scale has allowed us to classify the four potential situations in relation to the occurrence of hydrological drought in the study catchments. The results show the relevant seasonality of snowfall droughts in this area, and the importance of persistent precipitation drought as antecedent conditions for the impacts of low-snow years on the spring and summer streamflow. The validation performed points to an increase of the annual variability of the snowfall regime, very much related to a higher torrentiality of the precipitation regime on an annual basis than to changes in temperature.Acknowledgement: This research was funded by the Spanish Ministry of Science and Innovation through the research project PID2021-12323SNB-I00, HYPOMED—“Incorporating hydrological uncertainty and risk analysis to the operation of hydropower facilities in Mediterranean mountain watersheds”.

1. Study Region The Sierra Nevada mountain range in Spain. 2. Study focus We estimate time series of snow aerodynamic roughness length from daily terrestrial photographs, leveraging textural features to analyze its influence on evaposublimation estimates in our regional snow model under an isotropic fetch assumption. Over a long-term study (2010–2021), we compare our derived roughness length time series with a constant roughness length, examining their implications for model performance and evaposublimation trends. 3. New hydrological insights for the region Our comparison reveals that the estimated contribution of evaposublimation to total annual snow ablation using roughness length time series is significantly higher (up to (48.8±3.6)%) than previously reported values (30–35%) and improve performance of our regional snow model upon using roughness length time series. In our study period spanning twelve years, cumulative evaposublimation decline (-7.23mm/yr), likely linked to decreasing snow cover duration (-4.57d/yr) and decreasing annual solid precipitation (-24.81mm/yr), though no trend in evaposublimation rates is observed. The Sierra Nevada’s shallow snowpacks and multiple accumulation and ablation periods create mixed surface types with patchy snow, rocks, and vegetation influencing roughness lengths. Consequently, we identify a relationship between roughness length and snow cover fraction, with the potential to facilitate evaposublimation rate estimates on a spatio-temporal scale for this region in the future.

This study proposes to use the vegetation vigour, measured by the Normalized Difference Vegetation Index (NDVI), as a proxy of the soil water content in Mediterranean mountain traditional irrigation systems. The Sierra Nevada ditches network (southern Spain), has been used as a representative study case. Vegetation status in the influence area of the ditches has been analysed for the period 1984-2020 using TM, ETM+, and OLI Landsat imagery. In addition, the implications of the restoration, using traditional techniques, of one of the ditches in the area, the Barjas Ditch, was used to assess the changes in vegetation before and after its implementation. The results show that (i) NDVI values have, in the area of influence of the ditches, a strong seasonal pattern link to ditches functioning; (ii) the closer the vegetation to the ditch the higher its NDVI values, NDVI in the immediate ditch area averaged 0.36 compared to 0.29 at distances > 200 m; (iii) the restoration of the Barjas' ditch has a beneficial impact on the vegetation status, NDVI experiences an increase of 19 % after the restoration resulting from a 0.09 rise. These results highlight the role of ditches in the landscape beyond their use as water resources infrastructure, proving a function to the ecosystems.

Significant progress has been achieved since the 2013 implementation of ecological flow rates due to the Water Framework Directive in Spain (WFD). Nevertheless, certain shortcomings exist, such as adequately monitoring compliance and analyzing the ecological response post-implementation. This is especially evident in areas characterized by complex meteorology, with extended periods of drought, as observed in regions affected by the Mediterranean climate. Moreover, it is crucial to combine minimum flows with pollution issues, whether anthropogenic or natural, to attain the good ecological status of water bodies.Our study aims to address three distinct questions: 1) How does implementing various environmental flow regimes impact the levels of hydrological alteration in terms of water quality and riparian vegetation downstream of the reservoirs? 2) How can we use remotely sensed information to complement existing water monitoring networks to assess changes in water quality and riparian vegetation? 3) What is the required spatiotemporal resolution needed to monitor these alterations? The pilot reservoir to conduct this study is within the Guadalquivir River Basin (southern Spain). This basin has relevant problems of reservoir silting and water pollution arising from high erosion and human intervention rates. To assess the evolution of water quality, quantity, and vegetation state, we evaluate different indexes derived from high, medium, and low spatial resolution VIS/NIR satellite images, with temporal resolution ranging from daily to biweekly. The analysis spans the period from 2018 to 2023, and we correlate remotely sensed information with ground data series of reservoir inlet and outlet flows, volume, and water level, provided by the regional government's Automatic Hydrological Information System (SAIH), but also with water quality data provided by the regional government’s DMA network (WFD approach). This also allowed for evaluating the relationship between flow regimes and the estimated water and vegetation parameters.Higher spatiotemporal scales proved crucial in studying changes in riparian vegetation, capturing the natural characteristics of Mediterranean riversides, which are not very wide and exhibit marked seasonal patterns. Due to the homogeneous land use of the basin, coarse-resolution indexes accurately reflect nearby vegetation patterns, serving as a proxy for the basin's ecological status. For water quality indexes, a spatial resolution of meters becomes necessary because, in this reservoir, invasive species proliferation and clogging levels are low. The lower resolution water index aligns with water level fluctuations, allowing us to use this information for longer-term analysis. Our ultimate goal is to provide effective metrics based on observations and simulations, accessible in quasi-real time, to support operational decision-making processes. We will apply the methodology to different reservoirs of the Guadalquivir River's upper, middle, and lower areas.This work has been funded by the project TED2021-130937A-I00, ENFLOW-MED “Incorporating climate variability and water quality aspects in the implementation of environmental flows in Mediterranean catchments” with the economic collaboration of MCIN/AEI/10.13039/501100011033 and European Union “NextGenerationEU”/Plan de Recuperación

In this paper, the Global Surface Water Explorer (GSWE) was combined with bathymetric and historical meteorological data to quantify water balance during the period 1984–2020 in the Primera de Palos freshwater lagoon (Southwest Spain). This allowed us, through a water balance approach, to estimate all water inputs and outputs to analyse the hydrological changes in the lagoon. The results showed high fluctuations with seasonal changes marked by the climatic regime during the first two decades of the study period. After this initial period, water extension remained stable above 70 % of the maximum lagoon extent. Thus, the natural hydrological regime of the lagoon was modified by water inputs from irrigation return, which are difficult to quantify. Thanks to a water balance approach, these irrigation returns were quantified as the closure term of the water balance. Three scenarios of irrigation return inputs can be defined, 4500, 1700, and 500 m3 d−1, depending on the cropping season. The use of remote sensing combined with bathymetric and meteorological data can provide the knowledge to support better informed water-management decision-making, although it may have some limitations in dry periods related to image processing in border data.

Snowmelt dynamics in Mediterranean mountains differs from the ones found in higher latitudes. This work assesses wet snow dynamics in semiarid environments combining proxy and remote sensing databases over a pilot area in the Sierra Nevada Mountain Range (southern Spain). A linear relationship was found between the minimum backscattering signal and the maximum snow depth achieved within a melting cycle. The slope of this relationship depends on the maximum snow depth reached and is linked to the contribution of the ground to the backscattering signal. These results delve into the understanding of wet-snow dynamics in Mediterranean mountains and can constitute the basis for an easy tool to compute maximum snowpack depth from the Sentinel 1 backscattering signal in these environments.

The new scientific decade (2023-2032) of the International Association of Hydrological Sciences (IAHS) aims at searching for sustainable solutions to undesired water conditions - whether it be too little, too much or too polluted. Many of the current issues originate from global change, while solutions to problems must embrace local understanding and context. The decade will explore the current water crises by searching for actionable knowledge within three themes: global and local interactions, sustainable solutions and innovative cross-cutting methods. We capitalise on previous IAHS Scientific Decades shaping a trilogy; from Hydrological Predictions (PUB) to Change and Interdisciplinarity (Panta Rhei) to Solutions (HELPING). The vision is to solve fundamental water-related environmental and societal problems by engaging with other disciplines and local stakeholders. The decade endorses mutual learning and co-creation to progress towards UN sustainable development goals. Hence, HELPING is a vehicle for putting science in action, driven by scientists working on local hydrology in coordination with local, regional, and global processes.

Downward shortwave radiation (DSR) is critical to many surface processes, and many satellite-derived DSR products have been released. Few studies have validated DSR over mountains where it is highly heterogeneous, and so, the shortwave flux measured at ground stations does not match kilometer-scale DSR products. To tackle this challenge, we used a high spatial resolution (30 m) daily DSR over Sierra Nevada, Spain, for 2008-2015, and a mountainous radiative transfer model to explore how topographic effects impacted the performances of DSR products. Four widely used satellite products were selected as proxies for our evaluation: 1) MCD18A1 V6.1 (with a spatial resolution of 1 km); 2) Meteosat Second Generation (MSG) DSR ( similar to 3.3 km); 3) Global LAnd Surface Satellite (GLASS) DSR V42 (0.05 degrees); and 4) Breathing Earth System Simulator (BESS) DSR (0.05 degrees). There are three main findings under clear skies. First, the product accuracies were slope-dependent, decreasing by 59.8%-134.6% with a slope of >= 25 degrees compared with areas with a slope of <10 degrees . Second, the product accuracies were aspect-dependent, exhibiting a higher degree of overestimation (i.e., average of 27.6 W/ m2 ) on the north side and underestimation (i.e., an average of -1.3 W/ m2 ) on the south side. Third, and finally, the product accuracies were time-dependent, exhibiting seasonal variations and pronounced overestimation in summer (i.e., 8.8-18.2 W/ m2 ). Moreover, the impact of topography decreased with increasing cloud cover. Our findings can be applied to various mountainous areas due to the same mechanism of how topography influences the DSR estimation. This study corroborates the substantial uncertainties of the current DSR products in mountains and the necessity of incorporating topographic information into DSR estimations.

Catchment modelling of water balance components is nowadays done at high spatial resolution for continental and global scales, thanks to the increasing computational capacity and the growing trend towards open data. One of these process-based models is the World-Wide HYPE (WW-HYPE; Arheimer et al., 2020), which was set-up by a stepwise calibration strategy to avoid equifinality when using streamflow data for parameter estimation. In this presentation we suggest to further evaluate whether the model is right for the right reason by comparing internal variables against independent Earth Observations (EO). We then assume that the results are robust if the two different sources of data reveal the same results. This approach could become a new standard method today for evaluating continuous process-based global models as there are numerous EO products representing various hydrological variables, most of them covering at least the last decade.We propose to compare three aspects when evaluating robustness in global hydrological variables: i) long-term means, ii) seasonal variability through monthly means, and iii) equifinality by comparing model-streamflow performance versus internal variable performance.We applied this method by comparing six hydrological variables (potential and actual evapotranspiration, snow cover, snow water equivalent, soil moisture or changes in water storages) from EO-products (based on MODIS, GlobSnow, ESA-CCI Soil Moisture and GRACE) with WWH variables for the time-period 2000-2014 (Pimentel et al, 2023). We then found that the general patterns in the hydrological cycle show good agreement between catchment modelling and EO at the global scale, although some months in water-storage changes differed. These dissimilarities indicate that hydrological variables above the ground and earlier in the flow path are more robust than the sub-surface downstream processes, such as soil moisture distribution and water-storage changes, which reflect more complex processes that can be challenging to describe both by hydrological models and satellite sensors. Regarding geographical distribution, there is a larger spread in results from regions with extreme characteristics, such as cold regions (Canadian prairies), arid regions (western USA, deserts), highly forested areas (Amazonas), and transition zones (Sahel and Mediterranean Basin). This indicate that the particularity of these regions calls for specific regional modelling and monitoring approaches rather than continental or global approaches.On the contrary, in temperate regions at mid-latitudes, e.g., eastern USA and central Europe, almost all the hydrological variables were found robust. With respect to equifinality, overall, there were no indication on good discharge performance and bad internal model representation. The exercise shows the potential in using EO products for model evaluation beyond traditional river-discharge observations from gauges, to first assess the robustness of hydrological variables and second to determine which processes should be better represented in model parameterisation, without forgetting that EO products are not a ground truth and are also assigned with uncertainties. References:Arheimer et al., 2020: Global catchment modelling using World-Wide HYPE (WWH), open data and stepwise parameter estimation, HESS 24, 535–559, https://doi.org/10.5194/hess-24-535-2020Pimentel et al., 2023: Assessing Robustness in Global Hydrological Modelling through EO Comparisons, HSJ (in review)