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Groundwater is a strategic water resource in water-stressed regions such as the Mediterranean region. It used to meet the increasing domestic water demand and food production, maintaining ecosystem integrity and buffering climate change impacts. However, groundwater information that relies mainly on in-situ data observations remains fragmented and lacking standardization in the Mediterranean region due to the lack of systematic monitoring and data-sharing policy. PRIMA Foundation, launched in 2018 as a European Commission funding program, has targeted groundwater as a priority topic in its two first calls of 2018 and 2019. Sustain-COAST and InTheMED are two PRIMA-funded projects aiming for sustainable groundwater management in the Mediterranean region, adopting innovative but complementary approaches. Among their specific goals, Sustain-COAST and InTheMED projects have jointly developed a joint effort to collect groundwater-level data from around the Mediterranean. Over 14,000 time series of historical groundwater level data have been collected from different countries and have been harmonized into a common format. The resulting groundwater database has opened new horizons and perspectives for groundwater assessment that were previously invisible. In this contribution, we present and explore five new directions that have resulted from the groundwater database of the Mediterranean region: 1. Trend analysis and groundwater patterns clustering and their controlling drivers, 2. Regional groundwater level estimates combining different global groundwater models and regional in-situ data, 3. A methodological framework using Gravity Recovery and Climate Experiment (GRACE) satellite data to retrieve groundwater storage changes, 4. Water policy timeline, harmonization and pathways for innovative governance, and 5. Lesson learned from “success stories” of groundwater trend reversal and their transfer capabilities. This contribution will shed light on the power of data-sharing and will call for future systemic groundwater data collection in the Mediterranean region and beyond.

This deliverable presents the results of implementing the High-Resolution Monitoring Approach (HRMA) strategy for the Greek and Tunisian case studies throughout the project period. This deliverable illustrates the importance of HRMA, especially in areas experiencing rapid changes where when the traditional monitoring strategies are failed to offer insightful knowledge that can guide effective groundwater management. The Greek case studies focuses on the continuity of groundwatermonitoring using different parameters as proxies for groundwater sources and mixing during the declining and recovering phases. However, the HRMA strategy used in the Tunisian case study aimed to identify the surface water-groundwater hotspots and their interacting processes. The two HRMA monitoring strategies implemented in the Greek and Tunisian case studies can serve as two typical examples of implementing the same approaches in other demo sites experiencing the same features.

Improving river monitoring techniques is critical given the concomitant impact of climate change, population growth, and pollution over the last years. Turbidity is one of the most significant metrics for water quality characteristics. In river basins, high turbidity values can be indicative of both organic and inorganic materials. Turbidity is often used as a proxy for transport of suspended particles and associated fluxes of hydrophobic pollutants in a wide range of hydrological conditions. However, it is demanding to estimate suspended sediment yields in rivers because of the high variability along stream of suspended sediment concentrations. Traditional methods, such as gravimetric analysis, are time-consuming, expensive, often discontinuous in space and time and influenced by human errors or instrumental limitations.Remote sensing techniques are a suitable alternative to point measurements. Satellite remote sensing allows to study the spatial and temporal variations of water status parameters, but it is limited by the spatial and temporal resolution of the satellites considered. Low range systems can help increase the resolution of the imagery used for this purpose. In particular, the use of optical cameras can significantly reduce the monitoring cost and exponentially increase the information on water bodies health and hydrological dynamics, offering a large amount of data distributed in time and space. Nonetheless, all optical sensing methods are strongly affected by many environmental constraints (light, good optical transmission, visibility, etc.), which make them currently not always suitable for regular long-term monitoring of turbidity in rivers. The main goal of the monitoring procedure identified in this work is to avoid all these constraints, by processing the camera image to use it as a real measurement data. In this work, an image processing procedure has been identified by exploiting the water surface reflectance properties to estimate water turbidity spectral indices related to red and green bands of the light visible spectrum (Miglino et al., 2022). This river monitoring system is under development in different cross sections of the Bode River, one of the best-instrumented catchments in Central Germany.managed by UFZ Helmholtz Centre for Environmental Research. They gather a wide range of environmental data including a long-term time series on water quantity and quality. Preliminary results highlighted interesting similarities between the chromatic variation of the water surface captured by the RGB camera and the real data. Keywords: turbidity, sediment transport, image processing, spectral indices, remote sensing, camera, water quality assessment. References:Miglino, D., Jomaa, S., Rode, M., Isgro, F., & Manfreda, S. (2022). Monitoring Water Turbidity Using Remote Sensing Techniques. Environmental Sciences Proceedings, 21(1), 63.

Forest status in natural catchment is substantially important for hydrology and water quality, but it has been increasingly altered by human activities and climatic factors. Due to recent rapid changes in forest cover, there is an urgent need for hydrological water quality models which can adapt to these changing environmental conditions. The objective of this study was to analyse the impact of rapid continuous forest decline on nitrogen losses in a temperate mountain range catchment using a dynamic setting of the HYPE (HYdrological Predictions for the Environment) model. The modified model was applied to the Große Ohe catchment, Germany, which has experienced severe forest dieback (caused by bark beetle infestations) and its recovery over the last three decades. The model was validated by using also additional 25 years data from an internal gauge station (Forellenbach) and two soil measurement sites. Three scenarios, namely, no forest change, deforestation with subsequent regeneration, and deforestation without regeneration, were compared to identify key factors influencing catchment discharge and nitrogen export due to deforestation and regeneration. Results showed that the model performed well at the Große Ohe catchment scale, with Nash-Sutcliffe Efficiency values of 0.77 and 0.57 for discharge and IN concentration, respectively, and percentage BIAS values of -11.6% and 0.5%, respectively, during the validation period. Similar good performances were also observed at other scales. The simulation results proved that the improved model was able to (1) well capture the timing of peak flows and the seasonal dynamics of inorganic nitrogen (IN) concentration, and more importantly, (2) reflect the first increasing and then decreasing trend of discharge and IN concentration, in accordance with the deforestation and forest regeneration, respectively. By comparing scenarios, after experienced forest dieback without regeneration, the discharge and IN concentration exports were 24.9% and 160%, respectively, greater than those of scenario without forest change. However, the discharge and IN concentration exports were only 3.63% and 39.6% greater, respectively, with the help of continuous regeneration, indicating that forest regeneration is important for restoring hydrological and water quality status in the catchment. Compared to non-change scenario, the deforestation scenario exhibited decreased annual plant uptake of 34.7%, and strong increase in annual denitrification and N mineralization suggesting that the increased nitrogen export was likely induced by the reduction in vegetation uptake and the increased availability of soil nitrogen from tree residues. Overall, the adapted mechanistic modelling under the changing catchment forest conditions can strongly support forest management in terms of water quality.

Traditional water quality monitoring in River Systems is both labor intensive and expensive. However, in order to better understand the different phenomena occurring in river systems, it is vital to have robust data available. Satellite observations have been successful in monitoring different environmental systems, but generally, current available spatial resolutions and cloud cover in inland waters limit the monitoring of rivers. Recent developments in the use of Unmanned Aerial Systems (UAS) highlighted the potential to address this gap in environmental monitoring. In this study, UAS and image processing techniques were utilized to gather an overview of the water quality variability, specific to turbidity level and pollutant transport, along the Sarno River, which is the most polluted river in Europe, and the river pollution has long been subject to disputes between many sectors. Preliminary findings highlighted the potential of image processing and allowed to identify the variability in river water quality along the main river by adopting a sampling protocol in several points of the Sarno River. While there were few observations of plastic in river banks, organic transport was mostly observed and interestingly, there is a water quality spatial mixing in the river mouth, which is difficult to observe using traditional in situ point measurements. This study only covers the initial phase of the river monitoring activities. Keywords: UAS river monitoring, sediment transport, image processing, spectral indices, remote sensing, drones, water quality assessment References: Miglino, D., Jomaa, S., Rode, M., Isgro, F., & Manfreda, S. (2022). Monitoring Water Turbidity Using Remote Sensing Techniques. Environmental Sciences Proceedings, 21(1), 63.

Turbidity is one of the most critical metrics in water quality monitoring. High turbidity in river basins can be an indicator of both organic and inorganic material presence. Improving existing river monitoring techniques is essential, given the growing presence of critical factors, such as climate change, population growth, and pollution in recent years. In this study, a real scale experiment has been conducted in Selke River within the Bode catchment in Germany. The Bode basin is one of the best-instrumented catchments in Central Germany, managed by UFZ Helmholtz Centre for Environmental Research. In this experiment, the level of turbidity has been artificially increased by adding kaolin clay into the river, upstream enough from the monitored river cross-section to ensure the complete mixing between clay and water. Kaolin is usually exploited to prepare turbidity standard solutions. In addition, it is a harmless, easy to handle, and low-cost clay mineral, which is also an abundant silicate in soils and sediments. The monitoring field campaign has been conducted using different instruments, such as an optical camera, a multispectral camera mounted on fixed positions and a drone, which have been used to describe, from different points of view, the synthetic turbidity event generated. Different types of camera and installation settings have been investigated to understand the full potential of this technology for water quality monitoring. The gathered optical data was compared to the recorded turbidity of the UFZ sensors, which has been currently installed in the Selke river cross-section. The final goal of this work is to build a reliable image processing procedure for the development of a camera system that could support existing monitoring techniques and increase the temporal and spatial resolution in river monitoring. Keywords: camera, UAS, river monitoring, sediment transport, image processing, spectral indices, remote sensing, drones, water quality assessment

Successful modelling of the groundwater level variations in hydrogeological systems in complex formations considerably depends on spatial and temporal data availability and knowledge of the boundary conditions. Geostatistics plays an important role in model-related data analysis and preparation, but has specific limitations when the aquifer system is inhomogeneous. This study combines geostatistics with machine learning approaches to solve problems in complex aquifer systems. Herein, the emphasis is given to cases where the available dataset is large and randomly distributed in the different aquifer types of the hydrogeological system. Self-Organizing Maps can be applied to identify locally similar input data, to substitute the usually uncertain correlation length of the variogram model that estimates the correlated neighborhood, and then by means of Transgaussian Kriging to estimate the bias corrected spatial distribution of groundwater level. The proposed methodology was tested on a large dataset of groundwater level data in a complex hydrogeological area. The obtained results have shown a significant improvement compared to the ones obtained by classical geostatistical approaches.

Milestone 2.3 is the first draft of groundwater trend analyses performed. Showing the analysis results for groundwater level trends with a regional perspective using the longest available time series., This project is part of the PRIMA Programme supported by the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No 1923.

Successful modelling of the groundwater level variations in hydrogeological systems in complex formations considerably depends on spatial and temporal data availability and knowledge of the boundary conditions. Geostatistics plays an important role in model-related data analysis and preparation, but has specific limitations when the aquifer system is inhomogeneous. This study combines geostatistics with machine learning approaches to solve problems in complex aquifer systems. Herein, the emphasis is given to cases where the available dataset is large and randomly distributed in the different aquifer types of the hydrogeological system. Self-Organizing Maps can be applied to identify locally similar input data, to substitute the usually uncertain correlation length of the variogram model that estimates the correlated neighborhood, and then by means of Transgaussian Kriging to estimate the bias corrected spatial distribution of groundwater level. The proposed methodology was tested on a large dataset of groundwater level data in a complex hydrogeological area. The obtained results have shown a significant improvement compared to the ones obtained by classical geostatistical approaches.

The Mediterranean region is characterised by growing anthropogenic and climate pressures, resulting in increased water demand. Even though groundwater represents a strategic freshwater reserve in the Mediterranean, its status is becoming increasingly uncertain. The uneven distribution of data availability and scant data-sharing policies and systematic monitoring are significant constraints for management and vulnerability assessments. The objectives of this work are: i) characterization of significant changes in groundwater level time series in the region, ii) comparison of groundwater level models with in-situ data, iii) determine the influence of drivers in the temporal changes as well as the spatial distribution of groundwater levels. A database has been developed with over 8,000 time series of groundwater levels collected from national monitoring systems of Spain, Portugal and France, concentrating most measurements after 1980. At first, a search for long term trends and temporal patterns is performed on the most complete time series in the 1985-2014 period. Correlations between significant trends and environmental and anthropogenic drivers are assessed. Furthermore, the outputs of three steady-state global groundwater models (Reinecke et al. (2019), de Graaf et al. (2015) and Fan et al. (2013)) are compared to both interpolated grid-based and piezometer observations. And the relationship between the spatial distribution of groundwater level with explanatory variables is characterized.Significant groundwater level changes can be found in at least one third of the assessed piezometers. The simulated steady-state hydraulic head obtained from the three models showed a good agreement with the in-situ data in the Iberian Peninsula. A combined analysis of the temporal and spatial drivers for groundwater dynamics at a regional scale will ameliorate groundwater process understanding in the Mediterranean region. This study also makes a case about the importance of consistent and reliable monitoring as a necessary step for management of the resource. Acknowledgement: This work was supported by Sustain-COAST and InTheMED projects. Sustain-COAST - funded by the German Federal Ministry of Education and Research (Grant 01DH19015) under the EU PRIMA 2018 programme. InTheMED - funed by the PRIMA 2019 programme supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 1923.

The Mediterranean region is experiencing rapid population growth, increasing water demand, and faster climate warming. Groundwater plays a central role in the development of the Mediterranean by ensuring food security, buffering climate changes impacts and maintaining socio-economic stability and ecosystems integrity. However, despite groundwater being recognised as a powerful catalyser against climate- and human-induced effects, its status remains unknown, and its budget is uncertain. Moreover, the lack of appropriate groundwater monitoring programs at a regional scale, data sharing policy, and fragmented water policy and governance have complicated this vital resource's sustainable utilisation and protection.To this end, an international and multidisciplinary team of scientists with complementary skills have joined efforts through two PRIMA-funded projects (Sustain-COAST and InTheMED) towards better groundwater management and governance in the Mediterranean. In this respect, the Sustain-COAST Living Labs provide the setting to explore innovative governance approaches that could be scaled to increase resilience and adaptation capacity across the Mediterranean. At a regional scale, efforts target detailed water policy examination, pathways exploration towards the reinforcement of in-situ data collection, and groundwater modelling. Examination of water policy of the Mediterranean revealed an unbalanced situation between South Europe, characterised by complete, harmonised and straightforward water policy. Conversely, in North Africa and Middle East, water policy was found complex, not regionalised and fragmented in various initiatives. Results also showed the Mediterranean has become increasingly dependent on cereal importation over local food production, which poses a severe threat to its best diet overall and food security. Results suggested that combining in-situ data and regional groundwater modelling can offer further insights into this data-scarce region. Believing “that no one size fits all”, lessons learned from success stories, and tailored solutions to typical demonstration sites from both shores of the Mediterranean region are of extreme importance.Acknowledgement: This work was supported by Sustain-COAST and InTheMED projects. Sustain-COAST was funded by the German Federal Ministry of Education and Research (BMBF, Germany, Grant 01DH19015) under the EU PRIMA 2018 programme. InTheMED is part of the PRIMA 2019 programme supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 1923.

European Water Framework Directive (WFD) reported that river morphological alteration and diffuse pollution are two dominant pressures of European water bodies at the catchment scale. To achieve good status targeted by WFD, river restoration has received increasing attention. However, less is known about the spatial and temporal effects of stream morphologic characteristics (i.e., meandering, stream order) on instream nitrate retention at the river network scale. The objective of this study is to explore the relationship between in-stream nitrate retention and stream geomorphologic characteristics (sinuosity, width and order) and to assess the effect of natural river conditions on in-stream nitrate retention. Therefore, we implemented a grid-based nitrate catchment model (mHM-Nitrate, Yang et al. 2018) in the Bode catchment (3200 km2) in central Germany, which offers comprehensive long-term and high-frequency data at several water quality gauge stations for model calibration and validation. We evaluated two alternative empirical approaches to quantify in-stream denitrification (based on denitrification velocity and denitrification rate constant, respectively) and conducted scenario analysis on more natural morphological stream conditions by increasing the river sinuosity according to its relationship with stream power. Results showed that the model well captured the dynamics of daily discharge and nitrate concentration, with Nash-Sutcliffe Efficiency ≥ 0.87 for discharge and Kling-Gupta Efficiency ≥ 0.59 for nitrate concentration from 2015-2018. In-stream retention (including assimilatory uptake and denitrification) by the whole river network accounted for 3.5% and 35.9% of total nitrate loadings in winter and summer, respectively. The summer in-stream denitrification rate was two times higher in the lowland arable area than in the mountain forest area (225.1 and 68.8 mg N m-2 d-1, respectively). Similarly, summer in-stream assimilatory uptake was five times higher in the lowland arable area than the mountain forest area (167.9 and 27.2 mg N m-2 d-1, respectively). The model scenario representing more natural river network conditions by restoring the river sinuosity can lead to an additional nitrate loading reduction of 20% in 6th order stream network in summer. Our results show that the renaturation of streams can increase nitrate retention in flowing water, with efficiency increasing significantly with decreasing runoff. However, a significant reduction in the nitrate concentration remains limited to the growing season, especially in summer.Yang, X., Jomaa, S., Zink, M., Fleckenstein, J. H., Borchardt, D., Rode, M. (2018): A New Fully Distributed Model of Nitrate Transport and Removal at Catchment Scale. Water Resources Research, 54 (8) 5856.

The Mediterranean region is undergoing increasing climatic and anthropogenic pressures that challenge water security. Groundwater is a strategic resource for agriculture and water supply in the region, buffering climate change impacts. While previous studies have focused on specific aquifers' water budgets and trends at plot scales, regional dynamics remain unclear. One of the challenges for assessment is the uneven distribution of access to groundwater level monitoring data, as it's not centralized and publicly accessible in most Mediterranean countries. Here we present results that focused on analyzing the groundwater level trends in the countries with the most available groundwater level information: France, Portugal, and Spain. This study contributes to our understanding of groundwater dynamics under varying drivers and groundwater-depletion mitigation options.As a system with 'memory,' analyzing decades of time series is essential to understand the changes, vulnerability, and resilience. For 1985-1994, 1995-2004, and 2005-2014, a trend analysis was performed on the groundwater levels for piezometers (n=844) covering these periods with considerable completeness. We identified clusters of similar groundwater level developments and categorized them into nine aquifer archetypes, for example: stable water table depth, continued depletion, groundwater level recovery, and local gaining or depleting water levels occurring in each of the three decades. Furthermore, the influence of climate and geological variables on these temporal evolutions were analyzed. Overall, about a third of the studied piezometers showed trends in at least one of the periods. Increasing depths were observed more abundantly in the first period (1985-1994), while decreasing depths were more abundant in the last period.This work was developed in the scope of the InTheMED project. InTheMED is part of the PRIMA programme supported by the European Union's Horizon 2020 research and innovation programme under grant agreement No 1923.

Growing water demands in the Mediterranean region have increased groundwater exploitation, imposing urgent and efficient groundwater management. Sustainable management requires a proper understanding of groundwater status and accurate estimates of groundwater levels with less uncertainty. In this context, large-scale modelling has been shown to assess groundwater resources under changing conditions, especially in regions known for data scarcity. This study aims to quantify the steady-state groundwater levels at continental scales using a model ensemble and in-situ groundwater observations. To test the models' applicability and validity, we utilize one of the most monitored groundwater systems in the Mediterranean region, the Iberian Peninsula. Outputs of three global gradient-based groundwater models (Reinecke et al. (2019), de Graaf et al. (2017), and Fan et al. (2013)) were compared to observations from long-term groundwater monitoring network. The model ensemble showed reasonable performance in replicating the groundwater levels for shallow groundwater, but performance deteriorated with increased elevation.In this study, we argue that we can develop continental scale groundwater maps for groundwater assessment by combining model results with in-situ data. Historical groundwater levels were used to test, train and validate the different combination methods. Here we present the outcomes and discuss the accuracy of the final product. We see this study as a benchmark approach of using multi-model ensemble and observations to deliver better groundwater steady-state conditions as a baseline for groundwater users and managers in the Mediterranean region.This work was supported by the German Federal Ministry of Education and Research (BMBF, Germany, Grant 01DH19015) under the Project Sustain-COAST, co-funded by EU PRIMA 2018 programmes.

Long-term monitoring shows evidence of persistent changes in the magnitude and timing of the seasonal pattern and C-Q relations of nitrate concentrations in rivers, with possibly grave effects on aquatic ecosystems. Seasonal patterns of riverine nutrient concentrations are driven by a complex interplay of inputs, transport, and in-stream processing. Over multi-decadal periods, each of these factors may change due to socio-economic factors such as consumption patterns, governance regimes, or technological control measures. Here we test the hypothesis that observed multi-decadal changes in stream nitrate seasonality could be explained by changes in the relative importance of catchment nutrient sources over time. We analyze 66 years of shifting nitrate seasonality in a large, central-European river (Elbe) during a period of significant socio-political changes (1954 to 2019), with correspondingly significant changes in the sources of anthropogenic nitrate emissions. We show that the in-stream nitrate seasonality of the River Elbe changed significantly from a weak seasonal pattern (chemostatic) with peak concentrations during summer in the 1950s to a strong seasonal pattern (chemodynamic) with peak concentrations during winter in the 1990s. We link these shifts to a succession of technical/ political developments which influence the contribution of point and diffuse sources over time. Such shifts in seasonal concentration patterns can significantly impact the macronutrient (carbon, nitrogen, phosphorus) ratios in rivers, which in turn highly affect the health of aquatic ecosystems.

Data organization: Input: The experimental data. The experimental setup are described at: Cheraghi, M., A. Rinaldo, G. Sander, P. Perona, and D.A. Barry. (2018), Catchment drainage network scaling laws found experimentally in overland flow morphologies,Geophys. Res. Lett., 45.https://doi.org/10.1029/2018GL078351 model: The C++ code to numerically solve the landscape evolution model Results: The model results at different time-steps are saved in this folder &nbsp

Bayesian decision analysis is usually employed to make decisions in the presence of uncertainty. A common cost-benefit analysis approach, which is novel in the risk analysis of hydrologic/hydraulic applications, and a Bayesian decision analysis are applied to aid the decision making of implementing mitigation measures for groundwater resources management. The alternative option examined is a variation in terms of groundwater use only and possible over-pumping violations. The methodological steps are analytically presented and are associated with the original developed code. The results indicate that the probability of the uncertainty is the driving variable that determines the optimal decision, and depending on the unknown probability handling, the methodology may lead to a different optimal decision. Thus, the proposed tool can help the decision makers to examine and compare different scenarios using different approaches before making a decision considering the cost of a hydrologic/hydraulic project and the varied economic charges that water table limit violations can cause inside an audit interval. In contrast to practices that assess the effect of each proposed action separately considering only current knowledge of the examined issue. This tool aids decision making by considering prior information and the sampling distribution of future successful audits.

High-frequency water quality monitoring is increasingly used in examining the nutrient fluxes within catchments. Despite this, no studies have assessed the impact of monitoring frequency on the uncertainty of nitrate estimates obtained from distributed or semi-distributed catchment models. This study aims to evaluate the impacts of two different frequencies of nitrate sampling on the performance of a catchment hydrology model, including the uncertainty in both predictions and calibrated parameters. The investigation uses the HYPE model to simulate streamflow and nitrate concentrations (2010–2015) in the Selke catchment, a heterogeneous mesoscale catchment in central Germany. The Bayesian inference scheme of the DREAM code was employed for calibration and uncertainty analysis, and to explore differences between fortnightly and daily nitrate sampling strategies. The results indicate that: (a) the posterior uncertainty intervals of nitrogen-export process parameters were narrower when the model was calibrated to daily nitrate measurements, while similar maximum likelihood parameter values were obtained regardless of the sampling frequency; (b) the model calibrated using daily nitrate data better represented both daily and fortnightly nitrate measurements relative to that obtained using fortnightly sampling; (c) the daily nitrate dataset produced significantly smaller parametric prediction uncertainty, but only modest reduction in total prediction uncertainty, relative to the fortnightly nitrate dataset; (d) model structural error and measurement errors are the primary sources of total prediction uncertainty, and these combine to inhibit the benefits of high-frequency monitoring. We conclude that the adequacy of sampling frequency is dependent on model structure and measurement errors, such that higher-frequency nitrate monitoring may not markedly reduce the uncertainty of nutrient predictions, depending on other levels and sources of uncertainty.

This report summaries the main activities of the WP3 team on the project Sustain-COAST during the first half second year. Efforts were spent in making progress on the second task of WP3 (Task 3.2), which aimed to identify the cost structures for groundwater depletion and pollution preventing measures groundwater use for each case study of the four Sustain-COAST demonstration sites. The second task 3.2 aimed to analyze the cost structures for groundwater depletion and pollution preventing measures groundwater use in each case study. Variables under investigation including mitigation option should be considered in the analysis. The choice of the appropriate technique in each case study mainly depends on the issue site. This task considered at an early stage the potential common "Issue", which can be shared and agreed by all stakeholders in each case study. To this end, first, the mitigation options description, literature review and close interaction with the case studies partners were conducted. Second, the mapping of those options was performed as part of Task 3.2 for each case study. It is worth to be noted here, that the mapping exercise of the different mitigation options will be a dynamical process during and will be adjusted over the course of the project, where key stakeholders can be added at a different stage to enrich the multi-stakeholder partnership process. The provided information will give insights into assessing the sustainability of the current and future groundwater management strategies. This analysis will identify for each real site the areas of agricultural, domestic, and industrial water demand, the adequate mitigation option tackling the groundwater problems in the most vulnerable zones in terms of water resources availability, management and pollution risks.

This work carries the social learning process out via Living Labs in order to construct a common vision on sustainable groundwater management. In this process, the scientific and local knowledge are integrated. This study is part of Sustain-COAST project co-funded by PRIMA programme. Stakeholders’ active engagement is realized via Living Labs, which are participatory actions that encourage the dialogue among private and public actors, create institutionalized space for discussion and vision sharing, and analyze the stakeholder-suggested mitigation options. A stakeholder mapping took place, that is the list of all the key groups, organizations, and people involved to water management in the study area. Further analysis was carried out to better understand stakeholders’ roles and perspectives, within the first Living Lab, organized in Malia. 55 stakeholders interacted gathered, including water users, policy makers, local and regional authorities, water management and supply associations, socio-ecological and cultural associations, NGOs, citizens, technicians, external experts, scientists. Stakeholders got involved in social learning actions, knowing each other, expressed their motivations and expectations to participate in the first Living Lab and the project. Afterwards, a participatory session followed by implementing digital ICT tools (Mentimeter App.), which is an opinion survey technique that might improve societal awareness and stakeholders’ active engagement in water management. Afterwards, an interactive participatory map activity took place, which enabled the study site’s characterization according to key-stakeholders’ perception, knowledge, and expertise on water management issues in the area. Stakeholders collaborated in groups and filled maps of the study area with significant spatial data and information. Participants were asked to express their common vision on Malia in an entertaining puzzle activity.The aforementioned interactive sessions enabled the extraction of the raised water issues in Malia as well as the suggestion of possible options . The need for sustainable and balanced development taking into account principles of law and equal accessibility for all was specifically noted by stakeholders. Stakeholders evaluated the Living Labs as an innovative interactive and interesting way of exchanging views among institutions and citizens, through participation and technological means. Living Labs are expected to provide significant information exchange among institutions and actors and provide realistic and socially acceptable suggestions for the local community. Stakeholders are directly involved and motivated to maintain their active engagement in a longlasting process via future Living Labs in Malia. Such actions increase governance capacity by addressing people’s skills in jointly decision-making and engaging stakeholders in a social learning process through participation. Actions that encourage dialogue among different actors and use innovative mediation techniques form the best options to improve and integrate water governance.

Groundwater resources in Mediterranean coastal aquifers are under threat due to overexploitation and climate change impacts, resulting in saltwater intrusion. This situation is deteriorated by the absence of sustainable groundwater resources management plans. Efficient management and monitoring of groundwater systems requires interpreting all sources of available data. This work aims at the development of a set of plausible 3D geological models combining 2D geophysical profiles, spatial data analytics and geostatistical simulation techniques. The resulting set of models represents possible scenarios of the structure of the coastal aquifer system under investigation. Inverted resistivity profiles, along with borehole data, are explored using spatial data science techniques to identify regions associated with higher uncertainty. Relevant parts of the profiles will be used to generate 3D models after detailed Anisotropy and variogram analysis. Multidimensional statistical techniques are then used to select representative models of the true subsurface while exploring the uncertainty space. The resulting models will help to identify primary gaps in existing knowledge about the groundwater system and to optimize the groundwater monitoring network. A comparison with a numerical groundwater flow model will identify similarities and differences and it will be used to develop a typical hydrogeological model, which will aid the management and monitoring of the area's groundwater resources. This work will help the development of a reliable groundwater flow model to investigate future groundwater level fluctuations at the study area under climate change scenarios.

The Mediterranean region faces water security challenges with increasing water demand and climate change effects. Groundwater has become a key resource for water supply and economic development in the last decades, however, its budget remains poorly understood. The distribution of piezometric data in the Mediterranean has a very contrasting distribution. A large portion of them is not centralized and openly accessible, resulting in lack of detailed assessment of groundwater trends and their controlling factors at the regional Mediterranean scale. The objectives of this work are: i) the creation of a long-term and, possibly, the most comprehensive database for groundwater dynamics in the Mediterranean region, ii) the identification of trends and clusters on groundwater levels, and iii) the identification of the relationship between trends and climatic and hydrogeological drivers.Over 10,000 time series of groundwater level have been collected from national and regional authorities and the literature. The data come from eight countries in the Mediterranean region and have been post-processed into a common format. A search for seasonal patterns and long-term trends is performed then clustered accordingly. Furthermore, the influence of controlling factors such as precipitation and hydrogeology on the groundwater dynamics and trends are assessed. Significant groundwater level changes have been identified at a regional scale and used to provide insight into groundwater level change drivers’ in the Mediterranean region. The database is the result of a unique joint effort between regional groundwater experts to collect groundwater status information in the Mediterranean region and will serve as the foundation for future research on the influence of anthropogenic drivers and the prediction of groundwater depletion hotspots.This work was developed under the scope of the InTheMED project. InTheMED is part of the PRIMA programme supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 1923.

This work carries the social learning process out via Living Labs in order to construct a common vision on sustainable groundwater management. In this process, the scientific and local knowledge are integrated. This study is part of Sustain-COAST project co-funded by PRIMA programme. Stakeholders’ active engagement is realized via Living Labs, which are participatory actions that encourage the dialogue among private and public actors, create institutionalized space for discussion and vision sharing, and analyze the stakeholder-suggested mitigation options.A stakeholder mapping took place, that is the list of all the key groups, organizations, and people involved to water management in the study area. Further analysis was carried out to better understand stakeholders’ roles and perspectives, within the first Living Lab, organized in Malia. 55 stakeholders interacted gathered, including water users, policy makers, local and regional authorities, water management and supply associations, socio-ecological and cultural associations, NGOs, citizens, technicians, external experts, scientists.Stakeholders got involved in social learning actions, knowing each other, expressed their motivations and expectations to participate in the first Living Lab and the project. Afterwards, a participatory session followed by implementing digital ICT tools (Mentimeter App.), which is an opinion survey technique that might improve societal awareness and stakeholders’ active engagement in water management. Afterwards, an interactive participatory map activity took place, which enabled the study site’s characterization according to key-stakeholders’ perception, knowledge, and expertise on water management issues in the area. Stakeholders collaborated in groups and filled maps of the study area with significant spatial data and information. Participants were asked to express their common vision on Malia in an entertaining puzzle activity.The aforementioned interactive sessions enabled the extraction of the raised water issues in Malia as well as the suggestion of possible options . The need for sustainable and balanced development taking into account principles of law and equal accessibility for all was specifically noted by stakeholders. Stakeholders evaluated the Living Labs as an innovative interactive and interesting way of exchanging views among institutions and citizens, through participation and technological means. Living Labs are expected to provide significant information exchange among institutions and actors and provide realistic and socially acceptable suggestions for the local community.Stakeholders are directly involved and motivated to maintain their active engagement in a long-lasting process via future Living Labs in Malia. Such actions increase governance capacity by addressing people’s skills in jointly decision-making and engaging stakeholders in a social learning process through participation. Actions that encourage dialogue among different actors and use innovative mediation techniques form the best options to improve and integrate water governance. Keywords: Living Labs; Innovative governance; Water resources management; Stakeholder mapping; Social learning processes; Stakeholders’ engagement The PRIMA programme is an Art.185 initiative supported and funded under Horizon 2020, the European Union’s Programme for Research and Innovation.The project is funded by the General Secretariat for Research and Technology of the Ministry of Development and Investments under the PRIMA Programme. PRIMA is an Art.185 initiative supported and co-funded under Horizon 2020, the European Union’s Programme for Research and Innovation.

Information on the share of river bank erosion to the total sediment load at catchment scale by using the fingerprinting approach is important to address our knowledge of erosion processes to better target soil erosion control measures. In particular, river bank erosion is affected by many factors such as spatial and temporal variables and is difficult to quantify the relationship of the share of bank erosion to catchment size and upland erosion rate without extensive fieldwork and data analysis. Potential tracers including geochemical, fallout radionuclides, bulk and compound-specific stable isotopes, and magnetic properties have been used, often in combination with sediment source apportionment. In this worldwide review, the global dataset for percent share of river bank and surface erosion using fingerprinting approach was collected to establish the significance of catchment size and other physical controls on river bank erosion. Google Scholar and Web of Science were used to review research articles that included river bank/subsurface as one of the sediment sources in the study areas. This database showed that the UK (n = 84), USA (n = 14) and Brazil (n = 10) had the highest number of catchments, followed by Iran (n = 4), Southern Zambia (n = 1), Australia (n = 1), Spain (n = 1), Mongolia (n = 1) and Burkina Faso (n = 1) ranging in size from 0.31 to 15000 km2, predominately agriculture. Based on published studies, there is a clear shift of sediment sources from surface erosion to river bank erosion with increasing catchment size. The results show the wide range of relative contributions of surface and river bank sources to the catchment sediment yield around the globe. There are a number of catchments with river bank contribution exceeding 25% and surface contribution exceeding 90% of total sediment loss. This diversity highlights the many factors that influence river bank erosion. In addition to the wide range, sediment source contribution in the range 1-25% from river bank is generally representative around the World. We recommend that long term monitoring of sediment load and surface and river bank sources at nested sites within a catchment are indispensable. Furthermore, limited information on the share of sources often makes it difficult to target mitigation measures reducing sediment loads at the catchment scale.Keywords: Sediment load, catchment size, fingerprinting approach, river bank share

Groundwater is a valuable resource throughout the world. It supplies the needs of many sectors everywhere. Providing high spatial resolution groundwater data is important for climatic, hydrological and agricultural applications, to ensure sustainable groundwater management. The scarcity of high-resolution groundwater data over large scales at the required accuracy is a significant limitation for such applications. This study was undertaken in the Mediterranean region, which is recognized as one of the world's most sensitive regions to water scarcity due to both climate change and consistently increasing anthropogenic pressures. Groundwater is considered a strategic freshwater reserve in the Mediterranean region; however, its status remains poorly characterized. This study investigates the feasibility of downscaling outputs of three global groundwater models (Reinecke et al. (2019), de Graaf et al. (2017) and Fan et al. (2013)) to higher resolution.Steady-state results of the three models were compared with in-situ groundwater level observations, and an aggregation method was developed for downscaling. Observations from a long-term groundwater monitoring network over different regional studies around the Mediterranean were employed. Results showed that there is a significant discrepancy between the three compared model outputs. More specifically, the de Graaf et al. (2017) model presents a deeper water table than Reinecke et al. (2019) and Fan et al. (2013), while de Graaf et al. (2017) generally shows more significant variability in simulated water table depth. A detailed comparison between simulated and measured water table depth of different Mediterranean aquifers having different climatic, geologic and anthropogenic conditions will be presented.The results of this work will contribute to advance the understanding of how to combine large-scale groundwater modelling with local in-situ data as a crucial tool to improve groundwater management in data-scarce regions.This work was supported by the German Federal Ministry of Education and Research (BMBF, Germany, Grant 01DH19015) under the Project Sustain-COAST, co-funded by EU PRIMA 2018 programme. References­ Reinecke, R. et al. Challenges in developing a global gradient-based groundwater model (G3M v1.0) for the integration into a global hydrological model. Model Dev 12, 2401-2418 (2019). ­ de Graaf, I. et al. A global-scale two-layer transient groundwater model: Development and application to groundwater depletion. Water Resour 102, 53-67 (2017). ­ Fan, Y. et al. Global patterns of groundwater table depth. Science 339, 940-943 (2013).

Groundwater resources in Mediterranean coastal aquifers are under threat due to overexploitation and climate change impacts, resulting in saltwater intrusion. This situation is deteriorated by the absence of sustainable groundwater resources management plans. Efficient management and monitoring of groundwater systems requires interpreting all sources of available data. This work aims at the development of a set of plausible 3D geological models combining 2D geophysical profiles, spatial data analytics and geostatistical simulation techniques. The resulting set of models represents possible scenarios of the structure of the coastal aquifer system under investigation. Inverted resistivity profiles, along with borehole data, are explored using spatial data science techniques to identify regions associated with higher uncertainty. Relevant parts of the profiles will be used to generate 3D models after detailed Anisotropy and variogram analysis. Multidimensional statistical techniques are then used to select representative models of the true subsurface while exploring the uncertainty space. The resulting models will help to identify primary gaps in existing knowledge about the groundwater system and to optimize the groundwater monitoring network. A comparison with a numerical groundwater flow model will identify similarities and differences and it will be used to develop a typical hydrogeological model, which will aid the management and monitoring of the area's groundwater resources. This work will help the development of a reliable groundwater flow model to investigate future groundwater level fluctuations at the study area under climate change scenarios. This work was developed under the scope of the InTheMED project. InTheMED is part of the PRIMA programme supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 1923.

This study investigates the impacts of climate change on the hydrological response of a Mediterranean mesoscale catchment using a hydrological model. The effect of climate change on the discharge of the Alata River Basin in Mersin province (Turkey) was assessed under the worst-case climate change scenario (i.e., RCP8.5), using the semi-distributed, process-based hydrological model Hydrological Predictions for the Environment (HYPE). First, the model was evaluated temporally and spatially and has been shown to reproduce the measured discharge consistently. Second, the discharge was predicted under climate projections in three distinct future periods (i.e., 2021–2040, 2046–2065 and 2081–2100, reflecting the beginning, middle and end of the century, respectively). Climate change projections showed that the annual mean temperature in the Alata River Basin rises for the beginning, middle and end of the century, with about 1.35, 2.13 and 4.11 °C, respectively. Besides, the highest discharge timing seems to occur one month earlier (February instead of March) compared to the baseline period (2000–2011) in the beginning and middle of the century. The results show a decrease in precipitation and an increase in temperature in all future projections, resulting in more snowmelt and higher discharge generation in the beginning and middle of the century scenarios. However, at the end of the century, the discharge significantly decreased due to increased evapotranspiration and reduced snow depth in the upstream area. The findings of this study can help develop efficient climate change adaptation options in the Levant’s coastal areas.

The Mediterranean region is increasingly recognized as a climate change hotspot but is highly underrepresented in hydrological climate change studies. This study aims to investigate the climate change effects on the hydrology of Lakhmass catchment in Tunisia. Lakhmass catchment is a part of the Medium Valley of Medjerda in northwestern Tunisia that drains an area of 126 km². First, the Hydrologiska Byråns Vattenbalansavdelning light (HBV-light) model was calibrated and validated successfully at a daily time step to simulate discharge during the 1981–1986 period. The Nash Sutcliffe Efficiency and Percent bias (NSE, PBIAS) were (0.80, +2.0%) and (0.53, −9.5%) for calibration (September 1982–August 1984) and validation (September 1984–August 1986) periods, respectively. Second, HBV-light model was considered as a predictive tool to simulate discharge in a baseline period (1981–2009) and future projections using data (precipitation and temperature) from thirteen combinations of General Circulation Models (GCMs) and Regional Climatic Models (RCMs). We used two trajectories of Representative Concentration Pathways, RCP4.5 and RCP8.5, suggested by the Intergovernmental Panel on Climate Change (IPCC). Each RCP is divided into three projection periods: near-term (2010–2039), mid-term (2040–2069) and long-term (2070–2099). For both scenarios, a decrease in precipitation and discharge will be expected with an increase in air temperature and a reduction in precipitation with almost 5% for every +1 °C of global warming. By long-term (2070–2099) projection period, results suggested an increase in temperature with about 2.7 °C and 4 °C, and a decrease in precipitation of approximately 7.5% and 15% under RCP4.5 and RCP8.5, respectively. This will likely result in a reduction of discharge of 12.5% and 36.6% under RCP4.5 and RCP8.5, respectively. This situation calls for early climate change adaptation measures under a participatory approach, including multiple stakeholders and water users.

The Mediterranean region is recognized as a climate change and anthropogenic pressures hotspot, especially with the high seasonality of precipitation and increased water demands. The coastal areas, in particular, are significantly vulnerable to the effect of this critical situation. In such conditions, groundwater plays a fundamental role in water security in the Mediterranean region. Groundwater is considered as a strategic freshwater reserve. However, its status remains poorly characterized, and its total budget uncertain. In this study, we argue that large-scale groundwater modelling has shown great potential for improvement of our physical understanding of groundwater systems functioning and to the guidance of implementing science-based adaptation and sustainable mitigation measures in the Mediterranean. In recent years, groundwater modelling has moved from local to regional/global scale, offering insights into the status of data-scarce regions. However, it remains unclear to what extent those models can be used to support management decisions. This study aims to evaluate the performance of three global gradient-based groundwater models to represent the groundwater levels at steady-state and transient regimes in different Mediterranean aquifers. In this investigation, the groundwater models of Fan et al. (2013), de Graaf et al. (2017), and Reinecke et al. (2019) are used. Comparison between the groundwater level predictions of the three models was conducted. Then, comparison between the water table depths simulated by each model with the corresponding in-situ data in three case studies: La Mancha aquifer in Spain, an island aquifer in Crete, Greece and the Cap Bon Peninsula in Tunisia, were performed. Preliminary results showed that there is a large discrepancy between the three compared model outputs. More specifically, the de Graaf et al. (2017) model presents a deeper water table than Reinecke et al. (2019) and Fan et al. (2013), while de Graaf et al. (2017) generally shows greater variability in simulated water table depth. This study contributes in enhancing the role of regional-scale groundwater modeling as an important tool in assessing and predicting changes in groundwater levels in data-scarce regions, under considerable climate variability and increasing anthropogenic pressures.

This report summaries the progress and activities of the Task 2.2a entitled “Use of integrated highresolution monitoring approach (HRMA)” in the first year of the project period. To this end, a detailed case studies investigation was carried out with a close interaction with Task 2.1 “Case studies characterisation”. A first impression on the specific groundwater problems in the four case studies was developed. Then, the alignment between the main problems of each groundwater system, stakeholder objectives and existing monitoring network was conducted. Finally, different innovative monitoring strategies using the high resolution monitoring approach were listed and discussed.

This report summaries the main activities of the WP3 team on the project Sustain-COAST during the first year. Efforts were spent in making progress on the first Task of WP3 (Task 3.1), which aimed to identify the relevant social and economic impact factors of today's groundwater use for each case study of the four Sustain-COAST demonstration sites. The first Task 3.1 aimed to analyze the socio-economic determinants of water users in each case study. Variables under investigation including cultural, social and technological aspects as well as existing mechanisms implemented by governments, water supply companies and other factors, such as market prices, government subsidies, socially responsible behavior, and green farming should be considered in the analysis. The delineation of the system boundary in each case study mainly depends on the nature of the issue emerging from the interaction between researchers and stakeholders. This task considered at an early stage the potential common "Issue", which can be shared and agreed by all stakeholders in each case study. To this end, first, the site description, literature review and close interaction with the case studies partners were conducted. Second, the mapping of stakeholders was performed as part of Task 3.1 for each case study. The mapping exercise of the different stakeholders' groups will be a dynamical process and will be adjusted throughout the Living Labs organization, where key stakeholders can be added at a different stage to enrich the multi-stakeholder partnership process. The socio-economic data will give insights into the spatial distribution of current sectoral water demand and supply. Moreover, the water withdrawals, procurements and use will be mapped and will provide the basis for assessing the sustainability of the current and future groundwater management strategies. This analysis will identify for each case study site the areas of agricultural, domestic, and industrial water demand, the proportions of groundwater covering the demand and the identification of (seasonal) deficits in supply as well as the most vulnerable zones in terms of water resources availability, management and pollution risks.

Excessive dissolved inorganic nitrogen (DIN) added to urban river systems by point-source (PS) inputs, including raw sewage and wastewater treatment plant (WWTP) effluent, constitutes a water-quality problem of growing concern worldwide. However, the quantification of their impacts on DIN retention capacity and pathways in receiving water still remains partial. In this study, a spatially intensive water quality monitoring campaign was conducted to support the application of a water quality model to a PS-impacted urban river in Hefei City, China. The DIN retention capacities and pathway of a reference upstream Reach A, a raw-sewage-impacted Reach B and a WWTP-effluent-dominated Reach C were quantified using the model results after a Bayesian approach for parameter estimation and uncertainty analysis. The results showed that the raw sewage discharge elevated the assimilatory uptake rate but lowered its efficiency in Reach B, while the WWTP effluent discharge elevated both the denitrification rate and efficiency and made Reach C a denitrification hotspot with an increased nitrate concentration and hypoxic environment. The effects of the PS inputs on the DIN retention pathways (assimilatory uptake vs. denitrification) were regulated by their impacts on river metabolism. Despite different pathways, the total DIN retention ratios of Reaches A, B and C under low-flow conditions were 30.3% km-1, 14.3% km-1 and 6.5% km-1, respectively, which indicated that the instream DIN retention capacities were significantly impaired by the PS inputs. This result suggests that the DIN discharged from PS inputs to urban rivers will be transported with the potential to create long-term ecological implications not only locally but also more distant downstream.

Due to global climate change, the past decade has been the warmest for Germany since the beginning of climate records. Not only air temperature but also precipitation patterns are changing and therefore influencing the hydrologic cycle. This will certainly influence the chemical status of ground- and surface water bodies as mobilization, dilution and chemical reactions of contaminants are altered. However, it is uncertain if those alterations will impact water quality for better or worse and how they occur spatially. Since water management in Europe is handled at the regional scale, we suggest that an investigation is needed at the same scale to capture and quantify the different responses of the chemical status of water bodies to climate change and extreme weather conditions. In this study, we use open-access data to (1) quantify changes in temperature, precipitation, streamflow and groundwater levels for the past 40 - 60 years and (2) assess their impacts on nutrient concentrations in surface- and groundwater bodies. To disentangle management from climate effects we pay special attention to extreme weather conditions in the past decade. Referring to the Water Framework Directive, we chose the river basin district Elbe as our area of interest. Preliminary results indicate that especially the nitrate concentrations in surface water bodies of the Elbe catchment were positively affected in the last two years, while no significant impact on nitrate levels in shallow groundwater bodies was witnessed. However, many wells showed the first significant increase in water table depth in both years since 1985, raising the question of how fast groundwater-surface water interactions will change in the next years.

There is mounting evidence that the extreme weather conditions, either droughts or floods, could likely be more frequent than what was thought before, resulting in increased impacts on our ecosystems. This study aims to investigate the effect of the extreme drought events that occurred in the period 2015-2019 on the nitrate-N concentrations and loads in the Bode catchment (3300 km2) located in the transition areas of central uplands and northern lowlands of Germany. To this, a combination of high-frequency (15 min data in the period 2011-2019) and long-term (1993-2010) of continuous discharge and biweekly nitrate-N records in five typical gauging stations, representing different landscape features and dominant-runoff components of the catchment, were utilized. In the period 2015-2019, mean annual precipitation decreased by about 10%, and mean temperature increased by 1.46 °C compared to the period 1969-2014. Results suggested no evident changes in nitrate-N concentrations and loads in the upper mountainous areas of the Bode catchment (mainly forest) and groundwater-dominated gauging station, reflecting no impact of the droughts on these two archetypical sub-catchments. However, results showed that the nitrate-N concentrations and loads declined significantly in the lowland, agriculture dominated areas of the Bode catchment. This can be explained by the reduction of nitrate-N contribution from the lower part of the catchment during the spring and summer periods. It seems that the drought-induced increased evapotranspiration and decreased precipitation resulted in the reduced runoff from lowland areas of the catchment, affecting the nitrate-N mixing of different N source areas within the catchment. These findings suggest that recent changes of temperature and precipitation unlikely change considerably nitrate-N dynamics in terms of yearly load, but significantly reduce nitrate-N concentrations during low-flow periods in summer.

Strom event-scale analysis provides insights into nitrate transport dynamics at catchment scale. Investigating different hysteretic relationships between nitrate and discharge can disentangle catchment nitrate functioning both spatially and temporally. In this study, we explored seasonality and landscape gradiemt effects on nitrate concentration-discharge (C-Q) hysteresis patterns based on six-year (2012-2017), high-frequency (15 min) data in the Selke catchment (central Germany). The Selke catchment exhibits heterogeneous combinations of meteorological, hydrogeological, and anthropogenic conditions. Three nested gauging stations were built along the main Selke River, capturing discharge and nitrate concentration from the dominant uppermost mixed forest and arable land, middle catchment pure steep forest and lowland arable and urban land areas, respectively. Amongst the 227 storm events that have been detected, anticlockwise and accretion of C-Q relationships accounted for 76.6% and 75.3%, respectively, while the proportions decreased with the increasing areal share of arable land during summer season. Accretion pattern predominated forest areas (e.g., the middle catchment) throughout the whole year suggesting higher nitrate concentration in dominating interflow than baseflow. In contrast, dilution pattern was almost exclusively observed in lowland areas (dominated by arable and urban areas) in dry periods, indicating lower nitrate concentration in quick runoff components like surface runoff. We further investigated the consistency and variability of hysteresis patterns from upstream to downstream based on shared events. Results indicated hysteresis patterns seemed to be consistent at the three stations when discharge was high enough. Moreover, we found that nitrate load contributions from the upper and lower areas changed seasonally, albeit the dominant share of runoff volume from the upper area throughout the whole year. Such a comprehensive analysis (i.e., clockwise vs. anticlockwise, accretion vs. dilution) enables in-deep discussion of the plausible mechanisms of nitrate dynamics under different landscape conditions. We are also aware of limitations of such statistical data analysis, which can likely be tackled by mechanistic modelling at higher temporal resolutions.

This case study presents the fate of selected organic, priority and emerging pollutants along a 3.6km sector of a vegetated, agricultural ditch situated in Sinaloa (Mexico). The ditch receives runoff of agriculture and domestic wastewater from an adjacent community. During 2013, the occurrence of 38 organic pollutants (pesticides, polycyclic aromatic hydrocarbons (PAHs), artificial sweeteners and pharmaceutical residues) was monitored monthly at five selected points in the ditch water. Additionally, sediment and Typha domingensis (cattail) plants were collected in March, June, and September 2013 and investigated concerning their ability to absorb and accumulate pollutants. The concentrations of the selected pollutants in the ditch water ranged from sub ngL-1 (metolachlor, atrazine) to μgL-1 (metalaxyl, acesulfame). The metabolites endosulfan sulfate and endosulfan lactone exceeded mostly the concentration of the precursor insecticide endosulfan. Sorption on sediments was of minor relevance for accumulation of pollutants in the ditch system. Concentrations in the sediments varied seasonally and ranged from 0.2 to 12,432μgkg-1 dry weight (d.w.). T. domingensis accumulated ten of the studied pollutants mainly in roots (5-1065μgkg-1 d.w.). Overall, the monitoring results of the ditch compartments indicated that downstream the concentrations of the target pollutants decreased. Under no-flow conditions in the hot season, the ditch revealed a noticeable potential to mitigate pollutants. Among the high microbial activity in the water and the subtropical climate conditions, the ditch vegetation contributed to natural attenuation of the selected pollutants.