Testing the reliability of soil moisture forecast for its use in agriculture

The increased frequency and intensity of drought events are among the major impacts of climate change in various regions worldwide, including Central Europe. These changes have increased the demand for precise drought monitoring and forecasting tools and their validation. The Czech Drought Monitoring System, which is widely utilized across Central Europe, provides daily soil moisture monitoring and medium-range forecasts using the SoilClim model. The main objective of this study was to describe and evaluate the spatiotemporal reliability of these forecasts. The forecasting performance was evaluated for three variables (relative soil moisture content, soil moisture deficit, and drought intensity) and was evaluated using Pearson’s correlation, mean bias error, and mean absolute error. All the statistical analyses were performed on data from the years 2019 to 2021 aggregated at the administrative district level in the Czech Republic. The growing season data were analyzed in detail to assess the forecasting accuracy during spring and summer. Furthermore, the ability to forecast rapid changes in the soil moisture content according to changes in meteorological variables, such as precipitation and air temperature, was evaluated. Our findings demonstrate that the SoilClim model forecasts are accurate and suitable for practical applications in sectors such as agriculture and forestry. The lowest reported correlation between the monitored and forecasted values was +0.68 for nine-day forecasts at a soil depth of 0–40 cm. For shorter forecast periods of one and four days, the correlation values were +0.80 or greater. For drought intensity, the errors did not exceed one category of drought severity. We identified summer as the most dynamic season, with corresponding variations in the soil moisture and meteorological forecasting accuracy. This study validates the ability of the Czech Drought Monitoring System to provide reliable soil moisture forecasts, thus contributing to our ability to manage and mitigate drought impacts effectively. • Local soil moisture forecasts were generally highly accurate. • Drought intensity forecast errors did not exceed one severity class. • Soil moisture forecasts were more accurate than meteorological variable forecasts. • The highest uncertainty in the soil moisture forecasts was observed during summer. • Rapid soil drying was reliably predicted from soil moisture forecasts.