Quantifying Irrigation Water Use and Groundwater Dynamics using Earth Observation Data in Combination with Hydrological Modeling

Irrigation has a significant influence on hydrological and groundwater dynamics through altered evapotranspiration, water abstraction, and return flows.    However, irrigation is often insufficiently represented in hydrological and groundwater models due to limited information on the spatial and temporal variability of irrigation water use. This gap limits the reliable assessment of sustainable groundwater management, particularly in intensively farmed regions.

 

This research proposes a framework that combines satellite-based actual evapotranspiration (ETa) estimates with coupled process-based hydrological and groundwater modeling to quantify irrigation water use and its influence on the landscape water balance in Lower Saxony, Germany. Spatially distributed ETa is derived from the Landsat Provisional ETa Science Product and compared with simulated evapotranspiration from a semi-distributed hydrological model based on natural conditions without irrigation. Net irrigation is estimated as the difference between satellite-based ETa and simulated non-irrigated ETa. The groundwater model is subsequently used to simulate spatial and temporal changes in groundwater levels resulting from irrigation-related withdrawals, and groundwater recharge provided by the hydrological model.

By linking satellite-based evapotranspiration with hydrological and groundwater modeling, the proposed framework provides a method to quantify spatially and temporally varying irrigation water use and to assess its effects on groundwater levels at the landscape scale. While demonstrated for Lower Saxony, Germany, the framework is transferable to other regions where satellite-based evapotranspiration data and hydrological/hydrogeological information are available. It can be applied to analyse irrigation impacts on groundwater systems and to support assessments of groundwater sustainability under increasing agricultural water use and climate variability.