Dürreforecast

Dürreforecast is a term used to describe forecast products that project drought conditions and their likely severity over a future period. It is produced by meteorological and hydrological services, research centers, and climate agencies and may combine near-term weather forecasts with longer-term climatic projections to estimate drought risk.

Dürreforecasts typically rely on drought indices such as the Standardized Precipitation Index (SPI), Standardized Drought Index (SPEI), and the Palmer drought severity index, along with hydrological indicators like soil moisture, streamflow, groundwater storage, and reservoir levels. Forecast horizons can range from weeks to seasons or longer, and spatial scales can vary from regional to national.

Methods include statistical approaches, dynamical models driven by general circulation models, data assimilation, and machine learning. Ensemble forecasts are common to quantify uncertainty, and products may present probabilistic risk categories or continuous probability estimates of drought conditions.

Applications include early warning and decision support for water resource management, agriculture, municipal planning, and disaster risk reduction. Dürreforecasts inform reservoir operations, irrigation scheduling, and drought contingency planning, and may be integrated with impact forecasts for crops, hydropower, and ecosystem health.

Limitations include uncertainties from model structure, input data quality, and climate variability. Non-stationarity and changes in land use or water infrastructure can reduce forecast skill; regional calibration and timely data updates are essential. The term Dürreforecast is not universally standardized and may be used variably across institutions.