The need for the implementation of innovative governance of water resources in general and coastal aquifers in particular taking into account the technological development as well as socio-economic factors has become a worldwide necessity. In compliance with the challenges and scope of the PRIMA call topic 1.1.2 entitled “Sustainable, integrated water management”, Sustain-COAST main goal is to implement a new innovative governance approach of coastal aquifers between multiple water users and beneficiaries under severe changing climate conditions in 4 countries located in the both sides of the Mediterranean Sea (Greece, Tunisia, Italy and Turkey). For this aim, this project intends to establish an adapted multi-criteria decision supporting system (DSS) and Geographical Information System (GIS) platform with an online access for water stakeholders and policy makers. This DSS and platform will be based on: i) an active and continuous social participation and learning, ii) the use of advanced technologies and tools, such as optical sensors and remote sensing capacities, iii) the use of various available numerical models (Feflow and Modflow) for the prediction of these coastal aquifers quantity and quality progress in time and iv) the use of smart, adapted and visualized web applications. On the other hand, this project will permit the preservation of the studied coastal aquifers against anthropogenic pollution through the promotion of the local water management concept which is based on the 4R principles (Reduce; Recycle; Reuse and Recover). The main outcomes of this project will be communicated and disseminated by using the best practices and means for the highest profit of all the concerned actors. Thanks to this project, Mediterranean coastal groundwater will be managed in harmony and enthusiasm under the responsibility of all the concerned actors taking into account the local socio-economic context and the meteo-climatic trends.

The “C and N Models Inter-comparison and Improvement to assess management options for GHG mitigation in agrosystems worldwide” (CN-MIP) addresses theme 1, topic 1 of the FACCE-JPI 2013 call. Our project will coordinate international development, evaluation and inter-comparison of agricultural process-based models to reduce uncertainty in estimating greenhouse gas emissions from crops, grassland and livestock systems. The project will focus on improving the simulation of management options to enable evaluation of credible mitigation strategies adapted to diverse agrosystems under different climatic conditions. CN-MIP responds to the priority of the core theme 5 "Mitigation of Climate Change" of the FACCE-JPI strategic research agenda, to improve the greenhouse gas (GHG) inventory methods, particularly the "certified" modellingTIER3 modelling approach for quantifying emissions and the effects of mitigation options. The project also supports initiatives outlined in the Global Research Alliance (GRA) on Agricultural Greenhouse Gases, which aim to improve measurement methodology and modelling, as well as inventory of GHG emissions and C sequestration in soils. The consortium comprises eleven partners: INRA (France), University of Aberdeen (UK), Helmholt-Zentrum Postam (GER), University of Florence (IT), CRA-Consiglio per la Ricerca in Agricoltura (IT), University of Milan (It), University of Sassari (IT), New Zealand Institute for Plant and Food Research (NZ), Colorado State University (USA), Woods Hole Research Center (USA), Queensland University of Technology (AU). The proposing partners are experienced modelers and experimentalists, already involved in internationally funded projects on measuring and modelling of greenhouse gas emissions,soil carbon sequestration, and reactive nitrogen, for a variety of agricultural conditions (annual crops, grasslands, tree crops) under temperate, Mediterranean and tropical conditions (GRA CN, Livestock and Cropland groups, AgMIP, MACSUR, Reactive N RCN, NANORP, etc.). This network will provide connections and sharing of models, modelling protocols and datasets, but also the necessary interactions with stakeholders. The project will be undertaken from January 2014 to December 2016, in 4 work packages (i) Definition of model data requirements, selection of process-based CN models (i.e. DNDC, DNDC mobile, DSSAT, Roth C, DayCent, PaSim, STICS, APSIM, EPIC, CN-SIM), selection of appropriate databases; (ii) development of common protocols for modelling and model inter-comparison; (iii) identification and testing of mitigation options, improvement of models for coverage, predictive capability and reliability; (iv) dissemination and training. Deliverables will be guidelines for the selection of database and the simulation of mitigation options, evaluation of uncalibrated and calibrated model performances for an array of GHG emission outputs, improved model tools, peer-reviewed research papers, communication and reports to policy makers and stakeholders, and training sessions for students and scientists.