- 1Institute of Physical Geography, Goethe University Frankfurt, Frankfurt am Main, Germany (tina.trautmann@em.uni-frankfurt.de)
- 2Department of Crop Sciences, University of Göttingen, Göttingen, Germany
- 3Institute of Meteorology and Climate Research – Atmospheric Environmental Research (IMK-IFU), Karlsruhe Institute of Technology (KIT), Garmisch- Partenkirchen, Germany
- 4International Centre for Water Resources and Global Change at the Federal Institute of Hydrology (ICWRGC), Koblenz, Germany
- 5Senckenberg Biodiversity and Climate Research Centre Frankfurt (SBiK-F), Frankfurt am Main, Germany
- 6Institute of Geography, University of Augsburg, Augsburg, Germany
With increasing frequency and severity of drought hazards worldwide, reliable monitoring and forecasting of drought conditions becomes more and more relevant for efficient drought management. In this context, the OUTLAST project provides global monitoring and seasonal forecasting of drought hazard indicators (DHIs) across three sectors, ranging from meteorological and agricultural to hydrological DHIs. In OUTLAST, a consistent framework is developed in which ERA5 (for monitoring) and bias-corrected SEAS5 data (for seasonal forecasts) are used to calculate meteorological DHIs. The same climate data forces the Global Crop Water Model1 and the global hydrological model WaterGAP2 in order to derive agricultural and hydrological DHIs respectively. The global OUTLAST DHIs will be freely available via the WMO’s HydroSOS web portal.
To adequately support drought management and decision-making, it is essential to identify and evaluate the accuracy of OUTLAST DHIs. Therefore, we apply a twofold evaluation procedure: 1) a global evaluation against various observation-based datasets with (nearly) global coverage, and 2) a regional evaluation in collaboration with experts who will potentially use OUTLAST products in their daily work. While the first provides a general assessment of the overall performance, the latter allows evaluation whether actual drought conditions are sufficiently monitored by the global OUTLAST system.
Here, we focus on the global evaluation of DHIs for the historical period 1981-2020 by comprehensively comparing the performance of model-based DHIs from multiple sectors, including (1) the standard precipitation index, (2) the rainfed crop drought hazard indicator, and (3) the empirical percentiles of streamflow, against observation-based data, such as (a) remote sensing-based precipitation, (b) global evapotranspiration data, and (c) observed streamflow of large river basins. By analyzing DHIs from multiple sectors simultaneously, we show the effect of drought - and error- propagation in the hydrological cycle on the ability to capture observed drought conditions by model-based DHIs. Besides, the capability to accurately reproduce historic drought conditions represents the accuracy that users can expect when employing the OUTLAST near-real time monitoring and seasonal forecasts for drought management decisions.
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1Siebert, S., & Döll, P. (2010). Quantifying blue and green virtual water contents in global crop production as well as potential production losses without irrigation. Journal of Hydrology, 384(3-4), 198-217. https://doi.org/10.1016/j.jhydrol.2009.07.031
2Müller Schmied, H., Trautmann, T., Ackermann, S., Cáceres, D., Flörke, M., Gerdener, H., Kynast, E., Peiris, T. A., Schiebener, L., Schumacher, M. & Döll, P. (2024). The global water resources and use model WaterGAP v2. 2e: description and evaluation of modifications and new features. Geoscientific Model Development, 17(23), 8817-8852. https://doi.org/10.5194/gmd-17-8817-2024
How to cite: Trautmann, T., Abbasi, N., Weber, J., Vu, T., Dietrich, S., Doell, P., Kunstmann, H., Lorenz, C., and Siebert, S.: Evaluation of a global multi-sectoral drought hazard monitoring and forecasting system, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3754, https://doi.org/10.5194/egusphere-egu25-3754, 2025.
