Ensemble long-term soil moisture forecast using hydrological modeling

Abstract

ABSTRACT Long-term soil moisture forecasting allows for better planning in sectors as agriculture. However, there are still few studies dedicated to estimate soil moisture for long lead times, which reflects the difficulties associated with this topic. An approach that could help improving these forecasts performance is to use ensemble predictions. In this study, a soil moisture forecast for lead times of one, three and six months in the Ijuí River Basin (Brazil) was developed using ensemble precipitation forecasts and hydrologic simulation. All ensemble members from three climatologic models were used to run the MGB hydrological model, generating 207 soil moisture forecasts, organized in groups: (A) for each model, the most frequent soil moisture interval predicted among the forecasts made with each ensemble member, (B) using each model’s mean precipitation, (C) considering a super-ensemble, and (D) the mean soil moisture interval predicted among group B forecasts. The results show that long-term soil moisture based on precipitation forecasts can be useful for identifying periods drier or wetter than the average for the studied region. Nevertheless, estimation of exact soil moisture values remains limited. Forecasts groups B and D performed similarly to groups A and C, and require less data management and computing time.

Keywords

• Soil moisture
• Ensemble forecast
• Hydrological modeling