The ‘Groundwater for Crops’ TKI project is the basis of a decision-support system (DSS) that helps agriculturalists and water managers take anticipatory water management measures at the land-parcel and regional levels.
The DSS provides early warnings of water shortages or flooding and, taking current moisture conditions and weather forecasts into account, determines the optimal groundwater and surface water levels. At the core of the system is the hydrological Soil, Water, Atmosphere and Plant (SWAP) model, which is fed with real-time information from online soil moisture sensors, groundwater pressure sensors, the climate-adaptive drainage (CAD) system and remote sensing data. The surface water and groundwater levels can be optimised online with CAD, and any possible remaining moisture shortfall can be rectified through tailored irrigation. Existing models and measurement techniques are improved and smartly combined. Because the SWAP model is used on the local, point scale, by connecting it with the SPHY hydrological model of project partner FutureWater, we are able to use it to sketch a spatial hydrological picture of the water management situation. The integration with remote sensing information occurs via SPHY.
The solution takes the form of a decision-support system with the SWAP hydrological model at its core, fed with information from field sensors (e.g., soil moisture, groundwater level, soil temperature) and weather forecasts. The system helps optimise soil moisture and groundwater levels using climate-adaptive drainage (CAD). A timely signalling of possible moisture shortfalls allows them to be rectified through subirrigation.
The project set up the DSS, so that calculations using SWAP, based on observed, actual soil moisture conditions and forecast meteorological conditions, provide the management information for the drainage level that can be established with CAD. The objective is to prevent water damage through oxygen stress, or to retain water to prevent drought stress. On the basis of field measurements of groundwater levels and of soil moisture measurements in 2013 and 2014, the DSO was successfully tested at the Haaksbergen location and spatially scaled-up using the SPHY model code.
Automatic control of the CAD system represents an important step towards more adaptive water management. CAD can be used to continuously maintain soil moisture conditions in the root range as optimal as possible for crop growth purposes. As a follow-up step, the management algorithm has to be put into practice with real online control and monitoring of soil moisture and crops. In the first instance, this can be done at the level of the land parcel. The application allows a glimpse into its regional-level application, with an area framework within reach.