Open-Earth-Monitor Global Workshop 2026

Soil-Moisture Memory as a Regulator of Hydrologic Response in the Po River Basin (Italy)
2026-10-08, 16:15–16:30 (Europe/Amsterdam), Aula Magna

Hydroclimatic forcing of similar magnitude can produce contrasting hydrologic responses within the same basin. Here, we investigate how soil-moisture memory (SMM) regulates the translation of atmospheric anomalies into basin-scale hydrologic response across the Po River Basin. To address this question, we developed an open and reproducible Earth-observation workflow based on a multi-source data cube that integrates Sentinel-1 observations with hydroclimatic forcing represented by the Precipitation–Evapotranspiration Anomaly Index (PEAI), derived from HYPER-P precipitation and GLEAM evapotranspiration for 2016–2022. This framework enables assessment of how SMM varies across land-surface types and during major hydroclimatic transition episodes.

The analysis reveals marked contrasts across the basin. Irrigated agricultural areas exhibit the strongest memory, with median persistence close to 3 weeks and low instability (~0.19), whereas changed surfaces show weaker and more volatile behavior, with persistence of about 1.7 weeks and instability approaching 0.24. Non-irrigated agricultural areas define a distinct intermediate regime, characterized by lower persistence and higher instability than irrigated areas, but less volatility than changed surfaces. At the basin scale, major forcing episodes affect approximately 80–90% of the basin, yet response hotspots typically occupy only 20–40%, indicating that atmospheric anomalies are not expressed uniformly but are selectively filtered by antecedent basin state and land-surface conditions.

Event-based analysis further shows that the hydrologic expression of forcing reversal depends strongly on antecedent SMM conditions. A continuous 28-day drought–flood abrupt alternation (DFAA) sequence in May–June 2020, automatically detected from the 2016–2022 record, includes a major drought-to-flood transition (DTF) from 21 May to 4 June and a major flood-to-drought transition (FTD) from 4 to 18 June. Although the two phases exhibit near-equivalent PEAI amplitudes, reversing from -1.195 to 2.176 during the DTF phase (Δ = 3.371) and from 2.176 to -1.250 during the subsequent FTD phase (Δ = 3.426), the resulting basin-scale responses are asymmetrical, indicating that forcing reversal of similar magnitude is not translated into equivalent hydrologic expression. These results indicate that hydrologic response to forcing reversal depends more strongly on antecedent soil-moisture memory than on forcing amplitude alone.

Additional comparisons among automatically detected FTD events with similar forcing trajectories reinforce this interpretation. Two major transitions, detected on 5 March 2020 and 13 May 2021, show comparable forcing duration and amplitude but differ substantially in timing, coherence, and post-transition evolution. These contrasts are consistent with distinct memory regimes: the 2020 event is associated with low persistence (~0.20) and sustained high instability (~0.75), whereas the 2021 event combines very low persistence at transition (~0.13) with rapid recovery toward higher persistence and lower instability thereafter. Overall, the results show that antecedent soil-moisture memory and land-surface conditions exert a strong control on how hydroclimatic forcing is translated into basin-scale hydrologic response.


What is your current associations to EU Horizon projects (if any)?

Open-Earth-Monitor Cyberinfrastructure (Grant agreement ID: 101059548)

Imane Serbouti received the M.S. degree in GIS and Remote Sensing for Geosciences and Environment and the Ph.D. degree in Geospatial Big Data and Geosciences, both with excellence, from Hassan II University, Casablanca, Morocco. She is currently a researcher at the National Research Council of Italy (CNR). She was previously a postdoctoral researcher at Mohammed VI Polytechnic University (UM6P), where she worked on geospatial urban big data. Her main research interests lie in remote sensing, satellite Earth observation, geospatial data analysis, and GeoAI for applications in environmental monitoring, disaster risk assessment, climate resilience, and sustainable land and water systems.