Articles | Volume 24, issue 2
https://doi.org/10.5194/nhess-24-681-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-24-681-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Seasonal forecasting of local-scale soil moisture droughts with Global BROOK90: a case study of the European drought of 2018
Ivan Vorobevskii
CORRESPONDING AUTHOR
Department of Hydrosciences, Faculty of Environmental Sciences, Institute of Hydrology and Meteorology, Chair of Meteorology, TUD Dresden University of Technology, 01737 Tharandt, Germany
Thi Thanh Luong
Department of Hydrosciences, Faculty of Environmental Sciences, Institute of Hydrology and Meteorology, Chair of Meteorology, TUD Dresden University of Technology, 01737 Tharandt, Germany
Rico Kronenberg
Department of Hydrosciences, Faculty of Environmental Sciences, Institute of Hydrology and Meteorology, Chair of Meteorology, TUD Dresden University of Technology, 01737 Tharandt, Germany
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In the study we analysed the uncertainties of the meteorological data and model parameterization for evaporation modelling. We have taken a physically based lumped BROOK90 model and applied it in three different frameworks using global, regional and local datasets. Validating the simulations with eddy-covariance data from five stations in Germany, we found that the accuracy model parameterization plays a bigger role than the quality of the meteorological forcing.
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Short summary
This study presents a new version of a framework which allows us to model water balance components at any site on a local scale. Compared with the first version, the second incorporates new datasets used to set up and force the model. In particular, we highlight the ability of the framework to provide seasonal forecasts. This gives potential stakeholders (farmers, foresters, policymakers, etc.) the possibility to forecast, for example, soil moisture drought and thus apply the necessary measures.
This study presents a new version of a framework which allows us to model water balance...
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