Selecting the best structure and parameterization of rainfall-runoff models is not straightforward and depends on a broad number of factors. In this study, the "Modello Idrologico Semi-Distribuito in continuo" (MISDc) was tested on 63 mountainous catchments in the western Po Valley (Italy) and the optimal model parameters were regionalized using different strategies. The model performance was evaluated through several indexes analysing hydrological regime, high-flow condition and flow-duration curve (FDC). In general, MISDc provides a good fit behaviour with a Kling-Gupta Efficiency index greater than 0.5 for 100% and 84% of cases for calibration and validation, respectively. Concerning the regionalization, spatial proximity approach is the most accurate solution obtaining satisfactory performance. Lastly, the predicted FDCs showed an excellent similarity with the observed ones. Results encourage to apply MISDc over the study area for flood forecasting and for assessing water resources availability thanks to the modest computational efforts and data requirements.
Combining a rainfall–runoff model and a regionalization approach for flood and water resource assessment in the western Po Valley, Italy / A. Cislaghi, D. Masseroni, C. Massari, S. Camici, L. Brocca. - In: HYDROLOGICAL SCIENCES JOURNAL. - ISSN 0262-6667. - 65:3(2020 Feb 17), pp. 348-370. [10.1080/02626667.2019.1690656]
Combining a rainfall–runoff model and a regionalization approach for flood and water resource assessment in the western Po Valley, Italy
A. Cislaghi
;D. Masseroni;
2020
Abstract
Selecting the best structure and parameterization of rainfall-runoff models is not straightforward and depends on a broad number of factors. In this study, the "Modello Idrologico Semi-Distribuito in continuo" (MISDc) was tested on 63 mountainous catchments in the western Po Valley (Italy) and the optimal model parameters were regionalized using different strategies. The model performance was evaluated through several indexes analysing hydrological regime, high-flow condition and flow-duration curve (FDC). In general, MISDc provides a good fit behaviour with a Kling-Gupta Efficiency index greater than 0.5 for 100% and 84% of cases for calibration and validation, respectively. Concerning the regionalization, spatial proximity approach is the most accurate solution obtaining satisfactory performance. Lastly, the predicted FDCs showed an excellent similarity with the observed ones. Results encourage to apply MISDc over the study area for flood forecasting and for assessing water resources availability thanks to the modest computational efforts and data requirements.File | Dimensione | Formato | |
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