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Author: Wechsung, F. × End date: 2024 × Start date: 2020 × Start date: 1990 × DDC: 550 × WGL Institute: PIK ×

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    Three perceptions of the evapotranspiration landscape: Comparing spatial patterns from a distributed hydrological model, remotely sensed surface temperatures, and sub-basin water balances
    (Chichester : John Wiley and Sons Ltd, 2013) Conradt, T.; Wechsung, F.; Bronstert, A.
    A problem encountered by many distributed hydrological modelling studies is high simulation errors at interior gauges when the model is only globally calibrated at the outlet. We simulated river runoff in the Elbe River basin in central Europe (148 268 km2) with the semi-distributed eco-hydrological model SWIM (Soil and Water Integrated Model). While global parameter optimisation led to Nash-Sutcliffe efficiencies of 0.9 at the main outlet gauge, comparisons with measured runoff series at interior points revealed large deviations. Therefore, we compared three different strategies for deriving sub-basin evapotranspiration: (1) modelled by SWIM without any spatial calibration, (2) derived from remotely sensed surface temperatures, and (3) calculated from long-term precipitation and discharge data. The results show certain consistencies between the modelled and the remote sensing based evapotranspiration rates, but there seems to be no correlation between remote sensing and water balance based estimations. Subsequent analyses for single sub-basins identify amongst others input weather data and systematic error amplification in inter-gauge discharge calculations as sources of uncertainty. The results encourage careful utilisation of different data sources for enhancements in distributed hydrological modelling.
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    Potential for Early Forecast of Moroccan Wheat Yields Based on Climatic Drivers
    (Hoboken, NJ [u.a.] : Wiley, 2020) Lehmann, J.; Kretschmer, M.; Schauberger, B.; Wechsung, F.
    Wheat production plays an important role in Morocco. Current wheat forecast systems use weather and vegetation data during the crop growing phase, thus limiting the earliest possible release date to early spring. However, Morocco's wheat production is mostly rainfed and thus strongly tied to fluctuations in rainfall, which in turn depend on slowly evolving climate dynamics. This offers a source of predictability at longer time scales. Using physically guided causal discovery algorithms, we extract climate precursors for wheat yield variability from gridded fields of geopotential height and sea surface temperatures which show potential for accurate yield forecasts already in December, with around 50% explained variance in an out-of-sample cross validation. The detected interactions are physically meaningful and consistent with documented ocean-atmosphere feedbacks. Reliable yield forecasts at such long lead times could provide farmers and policy makers with necessary information for early action and strategic adaptation measurements to support food security. ©2020. The Authors.