Seasonal predictions of agro-meteorological drought indicators for the Limpopo basin

The rainfall in southern Africa has a large inter-annual variability, which can cause rain-fed agriculture to fail. The staple crop maize is especially sensitive to dry spells during the early growing season. An early prediction of the probability of dry spells and below normal precipitation can pot...

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Bibliographic Details
Published in:Hydrology and earth system sciences 2015-06, Vol.19 (6), p.2577-2586
Main Authors: Wetterhall, F, Winsemius, H C, Dutra, E, Werner, M, Pappenberger, E
Format: Article
Language:English
Subjects:
Agricultural management
Agriculture
Annual rainfall
Annual variations
Atmospheric precipitations
Basins
Cereal crops
Climatology
Corn
Crops
Drought
Droughts
Dry spells
Drying
Growing season
Interannual variability
Mapping
Monthly precipitation
Precipitation
Predictions
Probability theory
Quantiles
Rain
Rainfall
Rainfed farming
Rainy season
Seasonal forecasting
Seasons
Skills
Statistical analysis
Thresholds
Water damage
Water management
Weather
Weather forecasting
Wet season
Zea mays
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Summary:The rainfall in southern Africa has a large inter-annual variability, which can cause rain-fed agriculture to fail. The staple crop maize is especially sensitive to dry spells during the early growing season. An early prediction of the probability of dry spells and below normal precipitation can potentially mitigate damages through water management. This paper investigates how well ECMWF's seasonal forecasts predict dry spells over the Limpopo basin during the rainy season December-February (DJF) with lead times from 0 to 4 months. The seasonal forecasts were evaluated against ERA-Interim reanalysis data, which in turn were corrected with GPCP (EGPCP) to match monthly precipitation totals. The seasonal forecasts were also bias-corrected with the EGPCP using quantile mapping as well as post-processed using a precipitation threshold to define a dry day. The results indicate that the forecasts show skill in predicting dry spells in comparison with a climatological ensemble based on previous years. Quantile mapping in combination with a precipitation threshold improved the skill of the forecast. The skill in prediction of dry spells was largest over the most drought-sensitive region. Seasonal forecasts have the potential to be used in a probabilistic forecast system for drought-sensitive crops, though these should be used with caution given the large uncertainties.
ISSN:1607-7938
1027-5606
1607-7938
DOI:10.5194/hess-19-2577-2015