Accurate streamflow forecasting is crucial for effective water resources management, particularly in semi-arid regions increasingly impacted by climate change. This study evaluated the performance of deep learning models for streamflow forecasting in two catchments in eastern Spain. The models were trained on historical data using a one-step-ahead forecasting approach and evaluated through temporal cross-validation. A recursive multi-step forecasting strategy was subsequently used to assess predictive performance across different forecasting horizons. The long short-term memory (LSTM) models generally outperformed the multilayer perceptron (MLP) models due to their ability to capture temporal dependencies, although they exhibited high sensitivity to the length of training data and model calibration. The MLP models performed better with simple preprocessing, whereas the LSTM models benefited from combining temporal features with deseasonalization techniques. The optimal configuration for each catchment consistently delivered robust performance and reasonable predictions across various forecasting horizons. This study highlights the potential of neural network models for streamflow forecasting and provides practical guidance for implementing deep learning models in semi-arid basins, thereby contributing to improved drought risk assessment and water resources management.

Study Region The study is conducted in the Júcar River basin, located in eastern Spain. As a highly regulated Mediterranean river basin, its hydrological and environmental stability faces significant challenges driven by climate change. Study Focus This paper analyzes the impact of climate change on river hydrology, water quality, and environmental flows. Hydrological and water quality models were jointly used to compare historical baseline simulations with CMIP6 climate projections under the SSP2–4.5 and SSP5–8.5 scenarios. New Hydrological Insights for the Region Projections reveal a severe reduction in future water resources, marked by an average 47.8% decrease in total annual inflow across the basin. This decline leads to a deterioration of hydrological status, where an average of 68.5% of water bodies register increased hydrological alteration, and the number of water bodies classified as very altered more than double compared to historical conditions. The analysis shows that reduced dilution capacity and temperature-driven metabolic acceleration (specifically impacting BOD5 and Ammonium) increase the risk of water quality failures by an average of 117%. Furthermore, the findings highlight a critical trend in environmental flow performance with average deficits increasing by up to 17.7%. A significant drop in the coefficient of variation for these deficits confirms a regime shift from episodic drought events to a state of chronic water stress and loss of ecological resilience.

This study presents an integrated modelling framework designed to support water quality assessment and regulatory compliance analysis in river basins. The proposed approach combines deep learning-based streamflow prediction, stochastic uncertainty propagation, hydrological spatial disaggregation, and process-based water quality modelling at the basin scale. The framework is applied to the J & uacute;car River Basin (eastern Spain), a highly regulated Mediterranean system characterized by strong hydrological variability and significant water quality pressures. Streamflow is predicted using a Long Short-Term Memory (LSTM) network, and uncertainty is propagated through Monte Carlo simulations to generate ensemble inflow predictions. These inflows are spatially disaggregated using variation factors derived from an HBV hydrological model, providing distributed inputs to a water quality model that simulates concentrations of biochemical oxygen demand (BOD), phosphorus, and ammonium. The framework successfully reproduces the main spatial and temporal patterns of pollutant concentrations while explicitly quantifying the uncertainty associated with hydrological predictions. Water chemical status classifications show high agreements with observations, achieving accuracies of 90% for BOD, 84.4% for phosphorus, and 85.3% for ammonium. By providing probabilistic estimates of pollutant concentrations, the framework also enables identification of periods with elevated risk of regulatory threshold exceedance. Overall, the proposed approach offers a robust and transferable methodology for integrating probabilistic hydrological forecasting with water quality assessment, supporting risk-informed river basin management under uncertainty.

With the intensification of global water scarcity issues, Managed Aquifer Recharge (MAR) has become an approach to improve groundwater resilience and promote long-term water sustainability. This study develops a general governance framework for MAR agreements that emphasizes the need for adaptability, public engagement and comprehensive regulations to effectively manage MAR systems. This framework takes into consideration different contexts and their impact on the design and feasibility of MAR agreements in four Mediterranean case studies in Spain, Portugal, Tunisia, and Cyprus. The framework demonstrates that successful MAR governance depends on the alignment between technical feasibility, stakeholder participation, regulatory integration and financial sustainability. It guides managers from initial feasibility stages to the formalization of locally adapted MAR agreements highlighting common governance principles despite contrasting legal and institutional settings. The findings show the capacity of the framework to translate technical feasibility into functional governance roadmaps tailored to regional legal climates. Technical validation justifies these interventions by revealing localized potential benefits, including a projected 38% reduction in groundwater pumping in Spain, a lower-cost treatment in Portugal, groundwater level recovery of up to 23.6 m in Tunisia, and a 7.4 m ground-water rise in Cyprus. Furthermore, the framework identifies stakeholder engagement, adaptive monitoring, and flexible agreement structures as critical factors for long-term MAR implementation. Based on these findings, the proposed MAR governance framework has been able to adapt to different levels of institutional maturities leading to concrete outputs tailored to the local context, ranging from signed letters of intent for future man-agement planning to formal institutional charter adapted to local governance maturity. This work provides decision-makers with a scalable, actionable model to overcome non-technical barriers a co-create accountable, socially accepted MAR implementation strategies. It also offers transferable lessons for the development of resilient MAR governance models in other regions facing similar governance challenges.

This study assesses the chemical state of surface water bodies (SWBs) in the Júcar River Basin District (Spain), specifically focusing on contaminants such as nickel, lead, imazalil, and thiabendazole. To identify risky zones, the RREA model was combined with a Python-based subroutine to estimate the minimum non-compliance load (MNCL). The results show that many SWBs fail to meet water quality criteria due to point source pollution. The RREA (Rapid Response to Environmental status) model improves monitoring capacities by confirming SWB chemical statuses and detecting locations that have not been monitored or assessed thoroughly. The study also analyzes confidence levels by comparing MNCL to the current accumulated load (CAL), allowing for the identification and prioritization of important non-compliant SWBs and locations that require additional examination. This methodology not only enhances the accuracy of compliance evaluations but also serves as a useful tool for targeted water quality management initiatives. The results of this paper highlight the potential of the proposed pressure-impact approach to assess the chemical state of SWBs. This approach is useful to support sustainable management measures that mitigate water quality issues and preserve the environmental status of SWBs.

Water governance involves the political, social, economic and administrative systems set up to develop and manage water resources, and the supply of water-related services, at different levels of society (Rogers, 2003). Integrating Managed Aquifer Recharge (MAR) into water governance requires a multi-faceted approach. It must consider hydrogeological conditions, land use patterns and socio-economic factors (Ghannem et al., 2024a). “Within the AGREEMAR project”, an adaptive governance framework for MAR is proposed to address the pressing challenges of groundwater depletion and water scarcity in the mediterranean region. It is designed to guide the co-creation of sustainable, inclusive and adaptive MAR agreements. However, the success of this framework depends on collaboration among various stakeholders for effective governance leading to better water management.The approach combines technical, social, economic, and regulatory aspects that are essential for MAR implementation (Figure 1). From a technical perspective, it focuses on identifying suitable MAR sites using feasibility maps and numerical models to assess hydrological and environmental impacts and to analyze the effects of MAR on the rest of water uses in the basin and on the quantitative evolution of the aquifers. From a social point of view, it stresses the importance of including local, regional and general stakeholders in decision-making processes. Economically, it considers cost-effectiveness, resource allocation and compensation mechanisms to equitably distribute benefits among stakeholders. Regulatory aspects focus on fulfilling existing legislation and aligning with local and international policies. This framework incorporates tools such as decision support systems “AQUATOOL” and numerical groundwater modeling “INOWAS platform” to simulate scenarios and guide informed decision-making. The approach is applied to specific case studies in Spain (Ghannem et al., 2024b). Guidelines for regional MAR agreements are proposed, which provide practical insights for implementing MAR agreements within different socio-economic, environmental, and regulatory contexts of each region.This approach shows a participatory and systematic process to address the complexities of MAR. By integrating technical assessments, stakeholder-driven methodologies and a solid policy framework, it provides a replicable model for improving sustainable groundwater management in the mediterranean region and beyond. Details of the adaptive governance framework, that can be applicable to the Mediterranean basin, will be presented during the congress.Fig. 1. Elements to be considered when drafting MAR agreements ReferencesGhannem, S., Bergillos, R.J., Andreu, J., Paredes-Arquiola, J., Solera, A. 2024a. AGREEMAR Deliverable D3.2: General governance framework for MAR agreements. Available online at https://www.agreemar.inowas.com/deliverables.Ghannem, S., Bergillos, R.J., Andreu, J., Solera, A., Leitão, T.E., Martins, T.N., Alpes K.G., Oliveira M.M., Horovitz M., Chkirbene A., Khemiri K., Panagiotou C.F. 2024b. AGREEMAR D3.3: Set of Regional Draft Agreements tailored to the project case studies. Available online at https://www.agreemar.inowas.com/deliverables.Rogers, P. (2003). Effective Water Governance. Global Water Partnership Technical Committee (TEC).

This paper analyses the effects of environmental flows on water quality within a highly regulated basin, focusing on the Turia River basin in the eastern Iberian Peninsula. Through water management and water quality models, a series of simulations were conducted, introducing variations in the outflows of the Loriguilla reservoir to evaluate the effects of different environmental flow scenarios on water quality, particularly at the location of the intake for the water supply to Valencia. Three environmental flow scenarios were analyzed, alongside an alternative management scenario, considering their implications on water quality and reliability of water demand. The findings of this paper, particularly the nitrate (NO3−) concentration evolution, highlight the influence of minimum e-flow and e-flow regimes on water quality within the basin. These results suggest that while modifying the current flow regime can lead to some improvements in nitrate concentrations at the Valencia supply intake point, the primary cause of high nitrate concentrations is attributed to irrigation return flow and the pre-existing contamination of the aquifer. This analysis offers valuable insights into the complexities of water quality management in regulated basins, emphasizing the need for a multi-faceted approach to address the diverse factors influencing water quality and demand supply reliability.

This work presents a novel methodology to assess the effects of regulated flow regimes on the hydrological alteration of the downstream river stretches. The methodology is mainly based on applying a water allocation model and the quantification, normalization, and aggregation of indicators of hydrological alteration, which relate to the hydrological regimes under regulated and natural conditions. The final output is a global indicator of the hydrological alteration of each river stretch. The methodology was applied to a case study in eastern Spain: the Jucar River basin. The values of the global indicator of hydrological alteration obtained indicate a less pronounced alteration in the river stretches located in the upper part of the basin and a higher alteration in the downstream stretches. Thus, they represent accurately the real hydrologic conditions of the basin and demonstrate the goodness of the methodology proposed in this work.

Appears in: ICERI2023 Proceedings Publication year: 2023Page: 1832 (abstract only)ISBN: 978-84-09-55942-8ISSN: 2340-1095doi: 10.21125/iceri.2023.0531Conference name: 16th annual International Conference of Education, Research and InnovationDates: 13-15 November, 2023Location: Seville, Spain

Highly regulated basins have traditionally required management practices to mitigate the negative environmental impacts and ensure human well-being. This paper proposes and assesses environmental and water supply deficit indicators to assist in the management of environmental flows (e-flows). For that, a water allocation model is applied, and hydrological alteration, habitat alteration and water supply indicators are quantified, normalized and integrated into a general basin management indicator. This basin management indicator is analyzed for four management approaches and seven e-flow scenarios in the Júcar River Basin (eastern Spain). Hydrological alteration indicators show a less pronounced alteration in the river sections located upstream of the basin while a higher alteration in the downstream sections. As for the habitat indicators, they experience an improvement compared to the natural regime. Based on the values of the basin management indicator, the best e-flow scenario to adopt in the Júcar River Basin is selected. The indicators proposed in this work are useful for supporting decision-making regarding the planning and management of e-flows in regulated river basins worldwide.

R.J. Bergillos, J. Paredes-Arquiola, A. Sanchis-Plasencia, J. AndreuTechnical University of Valencia (SPAIN)

The management of environmental flows is of paramount importance in regulated water resources systems to preserve river ecosystems. This work proposes a methodology to assess habitat alteration in river basins altered by management activities. The methodology is based on the joint application of a basin management model (SIMGES, AQUATOOL) and a model to estimate habitat time series (CAUDECO). CAUDECO is based on the weighted useable areas of the species in their different vital stages that, in turn, depend on the flows in each river stretch and the biological periods of the species. The final output is an indicator of habitat alteration, which is defined ad hoc for this work to relate the habitat suitability under regulated and natural regimes. The methodology was applied to a case study in north-western Spain: the Órbigo River basin. The results in the current management scenario highlight that the ecological flows improve the habitat suitability of several species with respect to natural regime conditions. For instance, the mean values of the habitat time series in the Órbigo River for the brown trout and bermejuela under regulated conditions are 69.6% and 88%; whereas in natural regime they are equal to 55.1% and 72.9%, respectively. Based on these results, eight additional scenarios of ecological flows were tested and their effects on both habitat alteration and water demand reliability were quantified and discussed. It was found that increases in the ecological flows up to 30% do not affect the reliability of water demands and reduce habitat alteration (i.e., lead to values of the habitat alteration indicator closer to 1) for all species present in the river basin. These results highlight that the methodology and indicator of habitat alteration proposed in this paper are useful to support the management of regulated river basins, since they allow assessing the implications of ecological flows on both habitat suitability and reliability of water demands.

Over recent decades major advances have been made in global hydrological modelling underpinned by progress in high-resolution data availability, as well as in computational and data storage capabilities. These advances have provided hydrologists with opportunities to develop high-resolution large-scale hydrological models (LHMs) designed to represent and study the global hydrological cycle. However, with the aim of answering relevant questions for water resources policy and management, LHMs have recently been used in a number of regional applications. This has been enabled by their increasing spatial resolution which makes it possible to zoom-in on specific regions, essentially removing the barriers between global and regional models. Notwithstanding their growing sophistication, the current generation of LHMs still fall short in their ability to represent dynamic trade-offs in the water-food-energy-environment nexus, and water competition between upstream and downstream users. These limitations hinder the ability of LHMs to provide reliable insights at any scale other than the global, leaving the task of incorporating human water management activities within these models as one of the grand challenges for the hydrologic research community. Catchment-scale water management models (CWMMs) adopt a holistic systems approach to comprehensively address water availability, use, infrastructure, and policy aspects within multi-sectoral water allocation. The coupling of these models with LHMs can enhance their representation of human interventions in the natural water cycle (e.g., management of reservoirs, intra- and inter-basin water transfers) and improve the accuracy of water demand estimations such as irrigation requirements by including irrigation schemes. The inclusion of this local knowledge into LHMs’ modelling process can, therefore, increase their capacity to support rigorous nexus analyses to inform water policy and management decisions. This work represents the preliminary outcome of a project with the overall research objective of developing and providing a “proof-of-concept” to explore and design an approach for integrating CWMMs with LHMs, and to assess its potential and limitations to enhance the quality of information LHMs provide at regional scale. This work will present the initial efforts to compare the outcomes of LHMs from the Inter-Sectoral Impact Model Intercomparison Project and the CWMM AQUATOOL in the Ebro River basin, a heavily managed catchment in Spain with multiple competing water uses. This comparison will provide an estimate of the capacity of LHMs to provide useful information for decision making, as well as to identify knowledge gaps to be filled with management models.

Aquifers are ubiquitous, and their water is easy to obtain with low extraction costs. On many occasions, these characteristics lead to overexploitation due to important water level declines, reduction of river base flows, enhanced seawater intrusion, and wetland affection. The forecasted increase in water demands and global warming will impact the future availability of water resources. Conjunctive use of surface and subsurface waters can help in mitigating these impacts. There are two main conjunctive use strategies: artificial recharge (AR) and alternate conjunctive use (ACU). AR stores waters that are not to be used directly in aquifers. ACU utilizes groundwater in dry periods, while surface waters are preferred in wet ones; this allows the increase of water supply with lower dam storage, economic gains, and environmental advantages. Efficient conjunctive use can prevent soil salinization and waterlogging problems in semiarid countries due to excessive recharge from irrigation return flows or other origins. Groundwater is a neglected and generally misused resource to maintain environmental conditions. When considering the solution to a water resources problem, groundwater should always be part of the design as an alternative or a complementary resource. Aquifers have large inertia, and changes in their volumes are only noticeable after years of observations. Unfortunately, groundwater observation networks are much poorer than surface ones, something that should be changed if groundwater is to come to the rescue in these times of climate change. Human and material resources should be made available to monitor, control, analyze, and forecast groundwater.

Droughts are one of the gravest natural threats currently existing in the world and their occurrence and intensity might be exacerbated due to Climate Change. Scarcity is defined as the period when demand does not accomplish the normal reliability levels due to poor water management. Water and drought management plans (DMP) prevent scarcity periods by anticipating to drought and adapting to limited water resources. DMP in Spain were updated in December 2018. Two types of indicators were included: The Prolonged Drought Indicator and the Scarcity State Indicator (SSI). This study presents a comparison of the SSI among seven river basins in Spain, with the aim of making a starting point for its optimization and computation. The scarcity indicator is based on the relationship between the availability of resources and demands, identifying situations of short-term deficit in each of the areas defined. Its computation consists of a seven-step iterative process. Results detect two different approaches when determining the threshold values for the SSI. One method bases the threshold estimation on the risk of supply of the demands while the other obtains the threshold values from direct statistics of historical variables. The authors thank the Spanish Research Agency (MINECO) for the financial support to ERAS project (CTM2016-77804-P, including EU-FEDER funds).

In future years, and due to climate change, the frequency and intensity of extreme droughts will increase in some areas of the planet with water scarcity problems, affecting the reliability and vulnerability of water resource systems (WRS). Therefore, several approaches for real-time drought management were proposed in this study to improve the predictive capacity of currently used methodologies. This study was conducted in the Júcar River Basin, a highly regulated Mediterranean WRS whose experience in drought management is currently based on the combination of a stochastic model for future inflow series generation (using previous historical inflows) and a risk assessment model. Here, the possibility of improving and updating this approach was analysed by proposing three different models that integrate seasonal meteorological forecasts into the series generation process: i) an auto-regressive moving-average model with exogenous variables (ARMAX); ii) a hydrological model (HBV); and iii) an Artificial Neural Network (ANN) model. These models were also combined (individually) with a risk assessment model to assist in the decision-making process through a very intuitive drought risk indicator for several months in advance. The main results confirmed the potential for improving the predictive capacity of the current method using seasonal forecasts, especially with the ARMAX and ANN models under drought scenarios. Their results were more robust, with lower variabilities and uncertainty even after seven months, which represents a good opportunity to improve the decision-making process of this basin in a changing near future.

This article presents a novel methodology to assess the spatial and temporal variations of water resources exploitation within regulated river basins. The methodology, which is based on the application of a basin management model to properly assess the consumed and available water, was applied to a case study in the Iberian Peninsula to analyze the effects of environmental flows in the water resources exploitation of all rivers in the basin. It was demonstrated that the river sections in the upper part of the Órbigo River are subjected to lower water stress levels, so that they would be more suitable alternatives to supply new possible water uses. In addition, it was found that, during the summer months, the available water resources in natural regime are more than 1.5, 1.8 and 2.4 times lower than the consumed water in the upper, lower and middle stretches of the Órbigo River, respectively. This reveals the necessity of regulating the water resource to fulfill the water demands of the basin throughout the year. Finally, it was found that increases (decreases) in environmental flows not only lead to reductions (rises) in water availability, but also can induce decreases (increases) in consumed water resources due to lower (greater) water availability. This effect is more significant as water stress levels are higher. The results of this paper highlight the importance and usefulness of basin management models to accurately estimate the spatial variability of the water exploitation index, and the effects of environmental flows on both water availability and consumed water resources. The proposed approach to reduce the spatial scale of the water exploitation index is also helpful to identify the best water sources in river basins to meet future demands and/or higher values of environmental flows.

En este estudio se analiza el efecto del cambio climático en la calidad del agua de la cuenca del Júcar a partir de estimaciones futuras de aportaciones hidrológicas y temperatura del agua (Ta). Para ello, se utilizó un modelo de calidad de aguas a escala de cuenca con el que se estimó el estado ecológico de todas las masas de agua, basándose en las concentraciones de DBO5, P, NH4+ y NO3- para los horizontes futuros 2020, 2050 y 2080. De este análisis se obtuvo un incremento del número de masas con altos niveles de contaminación (80-100% incumplimientos) en los horizontes 2050 y 2080, localizadas sobre todo en la parte media y baja de la cuenca. Además, la degradación de la DBO5 y el NH4+ es muy dependiente de la temperatura del agua, poniendo de manifiesto la importancia de considerar esta variable en el modelo.