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El principal objetivo de este estudio es el análisis de la movilización de sedimento durante la avenida controlada del 5 de mayo de 2022 en el curso bajo del río Ebro desde la presa de Ribarroja. Durante este evento, se realizó una campaña de ensayos incluyendo aforo de caudales y medidas de turbidez y concentración de sedimentos en suspensión. Esta información ha permitido simular numéricamente el curso bajo del río Ebro desde la presa de Flix hasta su desembocadura con el modelo Iber, modelo euleriano 2D basado en el esquema de los volúmenes finitos de primer orden. Para ello se ha empleado el módulo de transporte de sedimentos en suspensión que resuelve la ecuación de advección – difusión, que emplea el modelo de erosión y sedimentación de Van-Rijn y resuelve la conservación de masa de Exner para estudiar la evolución del lecho. Los resultados de la modelización numérica son coherentes con la campaña de ensayos y validan el modelo Iber para analizar el transporte de sólidos en suspensión en la zona de estudio.

Abstract Water availability is of paramount importance for sustainable development and environmental planning, specifically in regions such as the Iberian Peninsula, renowned for diverse landscapes and varying climatic conditions. Due to climate change, understanding the potential impacts on water resources becomes essential for effective water management strategies. This research effort aims to assess future potential water availability for the Iberian Peninsula in different climate scenarios, employing cutting-edge water resource modelling techniques integrated within a geographic information system (GIS) framework. In this study, potential water availability is defined as the annual demand for water that can be satisfied at a specific point in the fluvial network with certain reliability. An ensemble of state-of-the-art climate models is utilised to project runoff for the Iberian Peninsula during the mid- and late-twenty-first century periods. These climate projections were subsequently processed using the GIS-based water resource management model, WAAPA, to derive potential water availability under a range of realistic hypotheses. The results indicate that anticipated shifts in precipitation patterns will lead to alterations in hydrological regimes across the region, significantly impacting future water availability. By using GIS-based methodologies, we can facilitate the identification of vulnerable areas susceptible to changes in water availability, offering spatially explicit information along the main rivers of the Iberian Peninsula for decision-makers and stakeholders. High-resolution spatial outputs from this research and detailed water availability estimates serve as valuable input for integrated water resource management and climate change adaptation planning. By combining advanced GIS-based hydrological modelling with climate scenarios, this research presents a robust framework for assessing water resources amidst a changing climate, applicable to other regions struggling with analogous challenges. Ultimately, our study provides vital insights for policymakers and stakeholders, empowering them to make informed decisions and devise adaptive measures to ensure sustainable use of water resources despite uncertain future climatic conditions.

Riverbank filtration (RBF) consists of green drinking water production in many regions and is used as a pre-treatment phase. This study investigates the performance of the RBF in the Nile delta, Egypt, for climate change and population growth scenarios of 2030, 2040, and 2050. This study presents a new method for predicting the sharing of riverbanks considering three cases: i) the river stage controlling the water levels in the river, ii) increasing RBF pumping, and iii) changing the groundwater levels. This last scenario is achieved by changing the general head in the MODFLOW model. The results showed that RBF sharing (RBFS) is a proportion of the river leakage inflow, in which the decrease of the river stage due to the influence of climate change reduced the river leakage inflow and RBFS. In addition, increasing RBF pumping, decreasing RBF pumping, and lowering the groundwater levels due to the increase in the future drinking water pumping for the population growth increased the river leakage inflow and RBFS. Finally, combining the three cases decreased RBFS in the coming years of 2030, 2040, and 2050, respectively, due to more groundwater sharing than the river inflow. The results show that the water budget is a good tool to investigate RBFS compared with MT3D results. This technique can reduce the cost of water quality collection and analysis; moreover, it will help with the estimation of RBF and save time compared with solute transport modeling.

The physically-based, spatially-distributed hydrometeorological model SASER, which is based on the SURFEX LSM, is used to model the hydrological cycle in several domains in Spain and southern France. In this study, the modeled streamflows are validated in a domain centered on the Pyrenees mountain range and which includes all the surrounding river basins, including the Ebro and the Adour-Garonne, with a spatial resolution of 2.5 km. Low flows were found to be poorly simulated by the model. We present an improvement of the SASER modeling chain, which introduces a conceptual reservoir, to enhance the representation of the slow component (drainage) in the hydrological response. The reservoir introduces two new empirical parameters. First, the parameters of the conceptual reservoir model were determined on a catchment-by-catchment basis, calibrating against daily observed data from 53 hydrological stations representing near-natural conditions (local calibration). The results show, on the median value, an improvement (ΔKGE of 0.11) with respect to the reference simulation. Furthermore, the relative bias of two low-flow indices were calculated and reported a clear improvement. Secondly, a regionalization approach was used, which links physiographic information with reservoir parameters through linear equations. A genetic algorithm was used to optimize the equation coefficients through the median daily KGE. Cross-validation was used to test the regionalization approach. The median KGE improved from 0.60 (default simulation) to 0.67 (ΔKGE = 0.07) after regionalization and execution of the routing scheme, and 79 % of independent catchments showed improvement. The model with regionalized parameters had a performance, in KGE terms, very close to that of the model with locally calibrated parameters. The key benefit if the regionalization is that allow us to determine the new empirical parameter of the conceptual reservoir in basins where calibration is not possible (ungauged or human-influenced basins).

A smart, flexible, fuzzy-based regression is proposed in order to describe non-constant behavior of runoff as a function of precipitation. Hence, for high precipitation, beyond a fuzzy threshold, a conventional linear (precise) relation between precipitation and runoff is established, while for low precipitation, a curve with different behavior is activated. Between these curves and for a runoff range, each curve holds to some degree. Hence, a simplified Sugeno architecture scheme is established on few logical rules. Alternatively, the model can be enhanced by using a combination between the fuzzy linear regression of Tanaka and the aforementioned simplified Sugeno architecture. The training process is achieved based on the Particle Swarm Optimization (PSO) method.

Human-Machine Interfaces employing biosignal-based inputs are hard to translate to real-life applications, in part because of the difficulty of developing generalized models to classify physiological events representing a user’s actions. In the proposed framework, an Electrooculography (EOG)-based game is operated through a pipeline of decision methods. These include a user-independent classification model of eye movements using a Convolutional Neural Network (CNN), which is fed with images created from signal windows, and an Ensemble of Utility Decision Networks (EUDN), which moderates the impact of oftentimes conflicting ocular events while enabling a more natural level of control over the interface. The CNN and the EUDN replace the normally used feature-based ocular event detection methods for EOG. Finally, a Reinforcement Learning-based game actuation approach simultaneously updates multiple $(State, Action)$ pairs for each rewarded outcome, intervenes to mitigate the consequences of wrongful game Commands, and can be used as part of a “shared-control” paradigm based on EOG. Results show a positive impact of Reinforcement Learning both in improving participants’ game performance as well as in reducing some of their subjective workload indicators.

Drought is a natural phenomenon that is controlled by different factors such as natural climate and catchment controls, and in many worldwide regions, it is now driven by human activities (i.e., reservoirs, irrigation, groundwater abstractions). Reservoirs initially ensure water availability and help cope with drought, especially in semi-arid regions; however, this human modification of the environment may lead to both positive and negative effects on the hydrological cycle, which need to be understood. This involves a better understanding of hydrological processes and incorporating human interactions within coupled human–natural systems to improve drought management. We focused on a strongly irrigated area located in the northeast of the Iberian Peninsula, the northern part of the Canal of Aragon and Catalonia district supplied by the Barasona reservoir. We implemented a simple water management model to simulate the reservoir operation (human-influenced scenario) and examined the contribution of human activities, associated with irrigation, on the water budget and drought propagation. For this purpose, we used simulations performed by the hydrometeorological model SASER (SAFRAN-SURFEX-EauDyssée-RAPID), which provided a natural scenario (without human influence) to contrast with the human-influenced scenario. The model performance was evaluated through the Kling Gupta Efficiency (KGE) metric. The first results demonstrated satisfactory performance to simulate reservoir storage and outflows against observed data, with KGE values of 0.4 and 0.82, respectively. Then we explored the linkages between agricultural drought, associated with evapotranspiration, and hydrological drought. We applied standardized indices to identify different kinds of drought, compared them, and assessed changes induced by human activities. Human modifications modulate the hydrological response of the catchment, and alter the intensity of hydrological drought, while human activities reduce the intensity of agricultural droughts.

This study proposes a stochastic methodology for the allocation of seasonal dam maximum conservation levels optimizing regular operation and hydrological dam safety. Furthermore, this methodology accounts the influence of accounting initial reservoir level variability. The methodology was applied to an arch dam classified as of risk type A with irrigation as the main demand associated. In the case study, a set of maximum conservation levels has been determined maximizing the supplied demand with a reliability of 90%. When accounting for initial reservoir level variability, the studied dam does not require flood control levels to fulfill the regulations regarding to overtopping. However, if the initial reservoir level at the beginning of the flood event is assumed equal to the seasonal maximum conservation level, the reservoir needs a flood control volume of 70 hm3 in one of the seasons. The methodology exposed can be useful in the analysis and prioritization of investments in hydrological safety of existing dams.

Evaluamos impactos y medidas de adaptación potenciales de la agricultura frente al cambio climático. Se proyecta una gran intensificación de las presiones sobre los recursos hídricos y la capacidad productiva en regiones de latitudes bajas – por ejemplo los deltas del Sureste de Asia y en países Mediterráneos. Por otra parte se proyectan oportunidades en regiones de zonas templadas – por ejemplo el norte de Rusia y el norte de Europa. Analizamos un serie de medidas técnicas y de regulación como respuesta de adaptación a estos riesgos y oportunidades, que pueden ser útiles para que los grupos de interés desarrollen medidas para reducir la vulnerabilidad del sector agrario al cambio climático.

La disponibilidad de los recursos hídricos podría verse afectada por el cambio climático y con ella el nivel de atención de las demandas. Para valorar dicho nivel de atención es frecuente el uso de indicadores que permiten identificar problemas de escasez de agua. Estos indicadores generalmente han sido desarrollados para análisis de planificación hidrológica a corto y medio plazo donde los efectos del cambio climático no son relevantes. Este artículo analiza la capacidad de dos indicadores: Indicador de calidad de servicio (I1) e Indicador de confiabilidad del suministro (I2) (desarrollados para uso a corto plazo) para su uso en sistemas expuestos al cambio climático (largo plazo). Este análisis se realizó mediante la aplicación de estos indicadores en tres cuencas españolas (Guadalquivir, Duero y Ebro) y bajo diferentes niveles de reducción en las aportaciones debido al cambio climático. Se determinó que I2 no es capaz de capturar los efectos de la variabilidad de dichas aportaciones. Se identificó un nuevo indicador Ip3 que, manteniendo el mismo criterio para su determinación que I2, es capaz de valorar mejor el nivel de atención de las demandas teniendo en cuenta la variabilidad de las aportaciones. Este nuevo indicador se seleccionó de entre tres propuestas de indicadores.

Para evaluar el impacto del cambio climático sobre los recursos hídricos es importante conocer si las simulaciones de los modelos climáticos son representativas de las características hidrológicas observadas y determinar cómo son las variaciones de las distintas variables hidrometeorológicas bajo escenarios de cambio climático. El presente estudio analiza el comportamiento de las principales variables que intervienen en el ciclo hidrológico: precipitación, temperatura, evaporación y escorrentía, en situación actual o escenario de control (1961-1990) y en escenario de cambio climático A2 (2071-2100) según distintas proyecciones climáticas del proyecto europeo PRUDENCE. El análisis se realiza en el ámbito de las cuencas que cubren la totalidad del territorio de la España peninsular. Los resultados destacan un sesgo negativo en la escorrentía simulada por los modelos climáticos con respecto a los valores observados estimados por el modelo hidrológico SIMPA. Las proyecciones climáticas muestran un incremento en los valores medios de temperatura y una disminución en la precipitación, evaporación y escorrentía y, se proyecta además un incremento en el coeficiente de variación. Las variables temperatura y precipitación presentan resultados más homogéneos y similares. La variable evaporación presenta cierta heterogeneidad y la variable escorrentía muestra una mayor dispersión en los resultados.