| 06 Oct 2025
Seasonal forecasting of water table elevation in shallow unconfined aquifers with a case study in the Umbria Region, Italy
Abstract. Accurate seasonal forecasting of water table elevation is critical for effective water resource management in unconfined aquifers, particularly under climate variability and anthropogenic pressures. This study presents a novel methodology for predicting water table elevation on seasonal timescales by coupling reanalysis and seasonal forecast data of soil moisture with a calibrated nonlinear transfer model. The approach leverages ERA5 reanalysis and SEAS5 seasonal forecasts to estimate flux toward the aquifer and forecast water table elevation. A case study in the Umbria Region of central Italy demonstrates the model's ability to simulate and predict monthly water table fluctuations. Two modeling strategies are compared: a static calibration approach (OPT1) and a dynamic calibration approach (OPT2), where model parameters are updated by considering different time periods. Both options yielded skillful forecasts across lead times of 1 to 6 months, with OPT2 showing slightly improved stability in forecast performance metrics. Results confirm the feasibility of incorporating seasonal climate forecasts into operational groundwater prediction frameworks. As expected, forecast accuracy is limited by the skill of precipitation predictions, especially during autumn and winter. The proposed framework lays the groundwork for anticipatory aquifer management and early warning systems under evolving hydroclimatic conditions.
The authors wish to revise Figure 1 of the published preprint of the manuscript. This revision does not affect the presented methodology, analysis, or results. On the contrary, it addresses two minor typographical errors in the original flowchart. The first issue is that the soil moisture forecast, provided by SEAS5 and used in the forecasting procedure, should have been written as θf , as the superscript f indicates the forecasted value. The second one is that, for the same reason, the forecasted relative flux toward the aquifer should have been written as Fg ts,f instead of Fg ts. In fact, the superscript f highlights the distinction between the datasets used for model calibration and those for the seasonal forecasting of the water table elevation. In addition, the figure layout has been refined to improve clarity and readability. The color scheme of several blocks has been adjusted, and the directional arrows between the blocks have been slightly modified to make the procedural flow more intuitive. The authors hope that these minor graphical and labeling revisions enhance the clarity of the proposed methodology.