This study presents MISDc v3.1, a process-based, flexible and open-source hydrological model developed to simulate complex water dynamics in large and human-impacted river systems. The model is applied to the Po River basin, Italy, subjected to strong anthropogenic impact. Calibration uses hydrometeorological data from 2000 to 2023, while validation is performed through multi-variable comparison against observed river discharge and satellite-based measurements of soil moisture, evaporation, snow water equivalent, and irrigation volumes. Quantitative performance assessment indicates strong simulation accuracy across multiple gauge stations (modified Kling–Gupta Efficiency = 0.88–0.93). The inclusion of irrigation and reservoir operation modules markedly enhances river discharge simulations, particularly during low-flow conditions and the 2022–2023 extreme drought. Uncertainty, assessed through the BLUECAT method, fosters a better understanding of model reliability across flow regimes. Owing to its Python-based and open-access architecture, MISDc v3.1 is easily transferable to other basins, offering a robust and flexible tool for integrated water resources management.

Modelling the human impact on hydrological cycle: The MISDc v3.1 model

Filippucci, Paolo;Dari, Jacopo;
2026

Abstract

This study presents MISDc v3.1, a process-based, flexible and open-source hydrological model developed to simulate complex water dynamics in large and human-impacted river systems. The model is applied to the Po River basin, Italy, subjected to strong anthropogenic impact. Calibration uses hydrometeorological data from 2000 to 2023, while validation is performed through multi-variable comparison against observed river discharge and satellite-based measurements of soil moisture, evaporation, snow water equivalent, and irrigation volumes. Quantitative performance assessment indicates strong simulation accuracy across multiple gauge stations (modified Kling–Gupta Efficiency = 0.88–0.93). The inclusion of irrigation and reservoir operation modules markedly enhances river discharge simulations, particularly during low-flow conditions and the 2022–2023 extreme drought. Uncertainty, assessed through the BLUECAT method, fosters a better understanding of model reliability across flow regimes. Owing to its Python-based and open-access architecture, MISDc v3.1 is easily transferable to other basins, offering a robust and flexible tool for integrated water resources management.
2026
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1625436
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact