Hydrological forecasting at impact scale: the integrated ParFlow hydrological model at 0.6 km for climate resilient water resource management over Germany

In the context of the repeated droughts that have affected central Europe over the last years (2018-2020, 2022), climate-resilient management of water resources, based on timely information about the current state of the terrestrial water cycle and forecasts of its evolution, has gained an increasing importance. To achieve this, we propose a new setup for simulations of the terrestrial water cycle using the integrated hydrological model ParFlow/CLM at high spatial and temporal resolution (i.e., 0.611 km, hourly time step) over Germany and the neighboring regions. We show that this setup can be used as a basis for a monitoring and forecasting system that aims to provide stakeholders from many sectors, but especially agriculture, with diagnostics and indicators highlighting different aspects of subsurface water states and fluxes, such as subsurface water storage, seepage water, capillary rise, or fraction of plant available water for different (root-)depths. The validation of the new simulation setup with observation-based data monthly over the period 2011-2020 yields good results for all major components of the terrestrial water cycle analyzed here, i.e., volumetric soil moisture, evapotranspiration, water table depth, and river discharge. As this setup relies on a standardized grid definition and recent globally available static fields and parameters (e.g., topography, soil hydraulic properties, land cover), the workflow could easily be transferred to many regions of the Earth, including sparsely gauged regions, since ParFlow/CLM does not require calibration.

Automated summary

In the context of repeated droughts in central Europe, climate-resilient management of water resources has gained importance. To achieve this, a new simulation setup using ParFlow/CLM model at high resolution was proposed. The setup allows for monitoring and forecasting of subsurface water states and fluxes, showcasing good results for various components of the terrestrial water cycle. The workflow can be easily transferred to other regions with globally available data.