| projects-551 |
1462 |
PRECIMED |
Precision Irrigation Management to Improve Water and Nutrient Use Efficiency in theMediterranean Region |
PRIMA |
PRIMA-2018 |
Water Management |
2019-10-01 |
2023-03-31 |
Completed |
€ 001 550 779.00 |
PRECIMED project will research, develop and validate a Standards-based Decision Support System (DSS) including Irrigation/Fertirrigation Models for a massive analysis of real-time crop and meteorological status data to improve the efficient use of water, nutrients and energy. For this, the consortium will integrate the knowledge on fertilizers and irrigation of Mediterranean crops with innovative information and communication technologies (ICT) to develop a solution that will be respectful with the environment and economically profitable. The DSS will be developed for the end user that can easily access and manage through web interfaces from anywhere with the Internet and using their mobile phones, tablets or PC. The DSS platform will be able to collect a large amount of crop data, which will be processed and analyzed in order to provide notices to the user about crop needs and real-time recommendations to farmers regarding the best irrigation and fertilization practices. The DSS will offer management services and remote actuations to improve the lives of Mediterranean farmers and also save water and fertilizers in a region with significant problems of water stress and soil pollution. The challenge is to create stronger bridges between the two areas of the Mediterranean basin, which is made up of EU and non-EU countries: Tunisia, Algeria, Spain and Greece. In this sense, the consortium is made up of SMEs, research centers and end users that will collaborate to validate the solution for subsequent commercialization. This project will allow the consortium to achieve an irrigation and fertilization DSS that is designed, evaluated and validated by supporting farmers in the different participating countries, to reduce the gap between the platform's developers and farmers' users in order to reach a successful solution for the agricultural sector. |
https://mel.cgiar.org/projects/precimed |
Urban water' |
| projects-552 |
1455 |
INWAT |
Quality and management of intermittent rivers and associated groundwaters in the Mediterranean basins |
PRIMA |
PRIMA-2018 |
Water Management |
2019-07-01 |
2023-06-30 |
Completed |
€ 001 519 000.00 |
The Mediterranean region is increasingly affected by water scarcity because of rising demand (population growth and land-use changes) and decreasing availability (cimate change led rainfall decreases). This situation leads to more temporary waterways. INWAT will develop and improve tools to analyze, understand and predict hydrology, chemical and ecological status, and services in the Mediterranean area characterized by temporary waterways, and will integrate all these pieces in a decision-support system. |
https://mel.cgiar.org/projects/inwat |
Rivers and estuaries' |
| projects-553 |
1461 |
MEDSAL |
Salinization of critical groundwater reserves in coastal Mediterranean areas: Identification, Risk Assessment and Sustainable Management with the use of integrated modelling and smart ICT tools |
PRIMA |
PRIMA-2018 |
Water Management |
2019-09-01 |
2023-02-28 |
Completed |
€ 001 268 000.00 |
MEDSAL Project aims to secure availability and quality of groundwater reserves in Mediterranean coastal areas, which are one of the most vulnerable regions in the world in terms of water scarcity and quality degradation. This objective will be addressed by providing a novel holistic approach directed towards sustainable management of coastal aquifers are affected by increased salinization risk. The proposed framework is envisaged to integrate different tools, techniques and methods – such as environmental isotopes, hydrogeological and hydrogeochemical modelling, advanced geostatistics and deep learning techniques – into an innovative assessment and management approach to: a) identify salinization sources (single or multiple) and decipher their governing processes, b) assess potential interactions with other compartments (small scale) and with other systems at basin (large) scale, c) forecast the spatiotemporal evolution of primary salinization and secondary impacts, d) perform risk assessment under variable climatic projections, and e) develop a public web-GIS observatory to support monitoring, management and decision making. |
https://mel.cgiar.org/projects/medsal |
Groundwater', 'Coastal waters' |
| projects-554 |
1520 |
RESERVOIR |
Sustainable groundwater RESources managEment by integrating eaRth observation deriVed monitoring and flOw modelIng Results |
PRIMA |
PRIMA-2019 |
Water Management |
2020-03-01 |
2024-05-31 |
Completed |
€ 001 240 000.00 |
RESERVOIR project is dealing with: the understanding of the hydrogeological properties, their spatial heterogeneous distribution and their changes in the time in the targeted areas through Earth Observation technique; the implementing numerical groundwater flow and geomechanical models to forecast the future response of aquifer systems to stresses, including those related to climate changes; the knowledge and understanding of the current groundwater users (tourism vs. agriculture). |
https://mel.cgiar.org/projects/reservoir |
Water reservoir', 'Groundwater' |
| projects-555 |
1509 |
GOTHAM |
Governance tool for sustainable water resources allocation in the Mediterranean through Stakeholder’s collaboration. Towards a paradigm shift in groundwater management by end-users |
PRIMA |
PRIMA-2019 |
Water Management |
2020-04-01 |
2023-03-31 |
Completed |
€ 001 600 000.00 |
Governance tool for sustainable water resources allocation in the Mediterranean through Stakeholder’s collaboration. Towards a paradigm shift in groundwater management by end-users |
https://mel.cgiar.org/projects/gotham |
Groundwater' |
| projects-556 |
Not available |
AGREEMAR |
Adaptive agreements on benefits sharing for managed aquifer recharge in the Mediterranean region |
PRIMA |
PRIMA-2021 |
Water Management |
2022-06-01 |
2025-05-31 |
Completed |
€ 001 000 909.00 |
AGREEMAR “Adaptive agreements on benefits sharing for managed aquifer recharge in the Mediterranean region” is a project funded under the PRIMA 2021 program for a period of three years (June 2022 – May 2025) with partners from Germany, Spain, Portugal, Cyprus and Tunisia. AGREEMAR intends to develop an adaptive governance framework integrated with a set of management tools that will assist water policy makers and water managers to reach Sustainable Integrated Water Resources Management. |
https://mel.cgiar.org/projects/agreemar |
Groundwater' |
| projects-557 |
1821 |
WATERMED4.0 |
EFFICIENT USE AND MANAGEMENT OF CONVENTIONAL AND NON- CONVENTIONAL WATER RESOURCES THROUGH SMART TECHNOLOGIES APPLIED TO IMPROVE THE QUALITY AND SAFETY OF MEDITERRANEAN AGRICULTURE IN SEMI-ARID AREAS |
PRIMA |
PRIMA-2018 |
Water Management |
2019-06-01 |
2022-11-30 |
Completed |
€ 001 862 042.00 |
In the new economy, the role of digitization is increasingly present, and procedures, tools and other resources are becoming available in a new era in water management and smart agriculture. In the future agriculture of the Mediterranean region, concepts like “big data”, “Internet of Things” and “cyber-physical systems”, will have to coexist with the physical environments that need to be more sustainable to assure food and quality of life for the population especially regarding water resources. |
https://mel.cgiar.org/projects/watermed40 |
Urban water' |
| projects-558 |
Not available |
ANDROMEDA |
Advanced and novel hydrology models based on enhanced data collection, analysis, and prediction |
CHIST-ERA |
Call 2019 |
Novel Computational Approaches for Environmental Sustainability (CES) |
2021-05-01 |
2024-05-31 |
Completed |
€ 000 411 190.00 |
In the last years, many European countries have experienced the effects of climate change, in the form of a scarcity of drinking water resources, prolonged periods of drought, and extremely heavy rainfall, with unprecedented dramatic environmental, economic, and social costs. Therefore, understanding, modelling, and predicting the movement and distribution of water on Earth, and effectively managing water resources is of paramount importance. Unfortunately, hydrology involves atmospheric, surface, and underground water systems, which are difficult to model on their own, and even more so when considered as a whole. As a result, modern hydrology often relies on a number of mathematical and empirical models that focus on isolated portions of the whole water cycle, thus providing only partial, defective and often times inconsistent information. Furthermore, such models are either based on complex physical theories that involve a large number of variables, which are often difficult to observe in practice, or empirically obtained from observations, thus lacking generality and adaptability and interpretability. The ultimate goal of ANDROMEDA is to push the research frontier in the science of hydrology beyond its current limits by leveraging cutting-edge ICT methodologies, such as data analytics and deep learning techniques, in order to: (i) determine the optimal location of sensors to collect different types of environmental data; (ii) extract the most relevant features from such data, thus reducing the complexity of current hydrologic models; (iii) optimize the models’ parameters in a distributed manner to better adapt to the spatio-temporal dynamics of the underlying water system; (iv) build comprehensive and more powerful models of the whole water cycle, capable of providing more accurate prediction of extreme-yet-critical events; and (v) develop augmented and virtual reality tools to visually represent the outcome of the hydrological models, so as to increase their usability by different stakeholders. Besides these immediate returns, ANDROMEDA will seed new applications and technical challenges into the ICT domain, fostering technological innovations in the fields of environmental sensing, low power communication, computation, distributed machine learning, and visualization tools. |
https://www.chistera.eu/projects/andromeda |
Groundwater', 'Rivers and estuaries', 'Urban water', 'Wetlands', 'Coastal waters', 'Water reservoir', 'Lake', 'Snow and ice' |
| projects-559 |
Not available |
SWAIN |
Sustainable Watershed Management Through IoT-Driven Artificial Intelligence |
CHIST-ERA |
Call 2019 |
Novel Computational Approaches for Environmental Sustainability (CES) |
2021-03-01 |
2024-03-31 |
Completed |
€ 001 157 341.00 |
Water resource contamination substantially threatens the environment. Rapid identification of chemicals and their emission sources in watersheds is crucial for sustainable water resources management. Despite studies on the measurement of micropollutants in the water resources around Europe, efficient utilization of the data in decision-making to protect water resources from detrimental chemical pollution is currently not available. Novel Internet of Things (IoT) technologies, coupled with advanced Artificial Intelligence (AI) strategies, may provide faster and more efficient responses to these challenges in real-time reactions as well as long-term planning. The proposed solution aims at providing: better understanding and near real-time response to pollution incidents; better prediction of pollution spread and improved response for mitigation of effects in the long run; data-driven AI life-long learning and evolution of the algorithm. The primary outcome would be an integrated decision support system utilizing micropollutant measurements along with real-time collected hydrodynamic and meteorological data of a watershed for sustainable water quality management. Since micropollutants are related to emission sources and are resistant to degradation, they are good indicators of pollution and fingerprints of the pollution sources. Our approach is based on introducing and combining novel technologies in improving water pollution management in several critical phases. First of all, we rely on an advanced, scalable IoT technology that adapts to the considered problem's specific needs through a novel mechanism called viscoelasticity. Therefore, we obtain desirable data from the locations and at the time that is optimized for further data analysis. Then, we introduce a novel methodology for creating a more accurate hybrid model integrating the expert-based physical environment model and data-driven, evidence-based techniques. To that end, we introduce a novel graph-based functional representation of data that captures affinities and dependencies among data streams more efficiently. |
https://www.chistera.eu/projects/swain |
Rivers and estuaries', 'Urban water' |
| projects-560 |
Not available |
WATERLINE |
NEW SOLUTIONS FOR DATA ASSIMILATION AND COMMUNICATION TO IMPROVE HYDROLOGICAL MODELLING AND FORECASTING |
CHIST-ERA |
Call 2019 |
Novel Computational Approaches for Environmental Sustainability (CES) |
2021-03-01 |
2024-03-31 |
Completed |
€ 001 379 116.00 |
Hydrological models are an essential tool for water resources assessment and management. Advanced computational algorithms are capable of simulating the relevant physical processes and form the feedback mechanism across a wide range of spatial and temporal scales. However, a bottleneck of these models is the lack of environmental observations to calibrate model parameters and to assess the robustness of model predictions. WATERLINE will employ multi-source information from remote sensing, historical data, in-situ data from meteorological networks as well as crowdsourced data to improve hydrological models and their predictions. The relevant physical processes and heterogeneity of hydrological catchments need to be integrated in hydrological models as a basis for reliable model predictions. A major challenge in this endeavour is identifying the observation data with the highest information content to constrain model parameters. Unfortunately, neither in-situ networks nor remote sensing alone can provide sufficient information to capture the high spatial and temporal variability of hydrological processes. Recently, downscaling frameworks have been developed, building robust models between coarse scale products and high-resolution ancillary variables using in-situ measurements. The lack of in-situ measurements to train such models can be overcome by the growing availability of crowdsourced observations. WATERLINE will improve the efficiency and robustness of hydrological models through strategic integration of variables covering different spatial and temporal scales. Furthermore, we will optimize the computational performances to provide near real-time and short-term predictions of various hydrological states with unprecedented spatial detail. Improved representation of soil moisture, groundwater levels and recharge, stream discharge, and evapotranspiration can significantly advance the sustainable management of water resources for a wide range of stakeholders. The WATERLINE concept will be implemented through development of a web services tool with three modular applications, targeting a) use by scientists (data access, downscaling, filtering, uncertainty analysis, modelling applications), b) use by non-technically trained stakeholders, providing enhanced visualization outputs, in the form of maps, graphs, indices enhanced with Augmented Reality and Virtual Reality functionalities, and c) crowdsourcing of hydrological information where a random user can report about any hydrological-related event and its severity using location-based service and textual input, which is then considered as an additional source of information for modelling and forecast estimation. User groups, such as farmers, water authorities, fire brigade services, entrepreneurs in tourist, agricultural, industrial sector will be actively involved in the development of the web-based interfaces to ensure the usability and adoption of the outcomes by relevant user communities. |
https://www.chistera.eu/projects/waterline |
Rivers and estuaries', 'Groundwater', 'Urban water' |
