HR: 1340h
AN: H23F-1679    [Abstracts]
TI: Prediction of moisture availability in agricultural soils using probabilistic monthly forecasts
AU: Bolius, D
EM: david.bolius@art.admin.ch
AF: Agroscope Reckenholz-Taenikon ART, Reckenholzstrasse 191, Zurich, 8046, Switzerland
AU: Calanca, P
EM: pierluigi.calanca@art.admin.ch
AF: Agroscope Reckenholz-Taenikon ART, Reckenholzstrasse 191, Zurich, 8046, Switzerland
AU: * Weigel, A P
EM: andreas.weigel@meteoswiss.ch
AF: Federal Office of Meteorology and Climatology MeteoSwiss, Kraehbuehlstrasse 58, P.O. Box 514, Zurich, 8044, Switzerland
AU: Liniger, M A
EM: mark.liniger@meteoswiss.ch
AF: Federal Office of Meteorology and Climatology MeteoSwiss, Kraehbuehlstrasse 58, P.O. Box 514, Zurich, 8044, Switzerland
AB: Despite technological advances in breeding and agricultural practice, crop yield remains subject to considerable inter-annual variability related to short-term (seasonal) climate fluctuations. Of utmost importance in this context are variations in soil water availability. Extreme conditions such as the heat wave observed in Europe during the summer of 2003 can lead to anomalous soil moisture depletion and induce considerable losses in crop production. The prediction of soil water levels using monthly forecasts could provide valuable means for risk assessment and mitigation. We present first results of a prediction system for soil moisture forecasts with a lead time of up to one month. The system uses dynamical, probabilistic forecasts of daily temperature, precipitation and global radiation from the European Centre for Medium-Range Weather Forecasts. The forecasts drive a bucket model of the water balance in the root zone. We show that the seasonal evolution of the soil water available to crops is well reproduced by the system. The prediction system was tested for a grid point in Switzerland (47N, 8E) using monthly hindcasts covering the time period 1994-2005. Simple downscaling of raw model data was performed by applying model anomalies from the model climatology to the observed climatology. Resulting soil moisture forecasts showed to be skilful over climatology (0 < skill < 0.6) up to a lead time of three weeks. The system allows for the probabilistic estimation of reaching a critical level of soil moisture within such a forecast period. This can serve as a valuable information for the farmers' decision-making process.
DE: 1807 Climate impacts
DE: 1816 Estimation and forecasting
SC: Hydrology [H]
MN: 2007 Fall Meeting