A comprehensive and generic Decision Support System (DSS) has been developed for the management of water quantity and water quality, using hydrodynamic, hydrologic and unsaturated zone models. The system is used for detailed analysis of soil-water interactions and operational water management.
HydroLogic developed data streams of monitored soil moisture and other hydrologic variables, real-time running models, and information channels in this research project, teaming up with other companies, research organisations and stakeholders of farmer cooperatives, water board and province.
Optimize use of available water
Shortages of freshwater will be one of the most pressing problems in feeding the world this century. To optimize use of available water it is important to distribute it wisely over the various competing interests, in particular agriculture, which is responsible for 70% of all freshwater use. Irrigation is currently often unsustainable, while groundwater reserves are becoming depleted and many places in the world are suffering water shortages.
Action is therefore required now to use space and in-situ monitoring systems, to create a better sense of water availability and optimise use across the planet. WaterSENSE provides water-availability and mapping services for any place in the world at different time and space resolutions, based on integrated Copernicus data, hydrological models; and local data.
WaterSENSE delivers essential value-added services of monitoring compliance of local water use against water rights and regulations: water auditing. The first application is in the multi-climate Murray-Darling Basin in Australia, followed by validation in South Africa and the Netherlands.
Novel research in the project focuses on scalable information services, based on satellite water monitoring, advanced big-data processing algorithms, to determine variables such as evapotranspiration, irrigation water use, rainfall and soil moisture, as well as machine learning to allow automatic data processing and reduce uncertainty in the hydrological variables determined.
ESA DIAS services for data provision, as well as cloud hosting and processing of computational services, are developed and implemented. Existing successful partnership models are further refined to ensure service providers in the water value chain achieve healthy business models.
This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No. 870344.