Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloWhich rainfall metric is more informative about the flood simulation performance? A comprehensive assessment on 1318 basins over Europe
Anno di pubblicazione2020
Autore/iCamici, S. and Massari, C. and Ciabatta, L. and Marchesini, I. and Brocca, L.
Affiliazioni autoriCNR IRPI, Perugia, Italy - CNR IRPI, Perugia, Italy - CNR IRPI, Perugia, Italy - CNR IRPI, Perugia, Italy - CNR IRPI, Perugia, Italy
Autori CNR e affiliazioni
  • inglese
AbstractThe global availability of satellite rainfall products (SRPs) at an increasingly high temporal/spatial resolution has made possible their exploitation in hydrological applications, especially over in-situ data scarce regions. In this context, understand how uncertainties transfer from SRPs into flood simulation, through the hydrological model, is a main research question. SRPs accuracy is normally characterized by comparing them with ground observations via the calculation of categorical (e.g., threat score, false alarm ratio, probability of detection) and/or continuous (e.g., bias, root mean square error, Nash-Sutcliffe index, Kling-Gupta efficiency index, correlation coefficient) metrics. However, whether these metrics are informative about the associated performance in flood simulations (when the SRP is used as input to an hydrological model) is an underdiscussed research topic. This study aims to relate the accuracy of different SRPs both in terms of rainfall and in terms of flood simulation. That is, the following research question are addressed: is (are) there appropriate performance metric (s) to drive the choice of the best performing rainfall product for flood simulation? To answer this question three SRPs, namely the Tropical Rainfall Measurement Mission Multi-satellite Precipitation Analysis, TMPA; the Climate Prediction Center Morphing algorithm, CMORPH, and the SM2RAIN algorithm applied to the ASCAT (Advanced SCATterometer) soil moisture product, SM2RAIN-ASCAT, have been used as input into a lumped hydrologic model (MISDc, "Modello Idrologico Semi-Distribuito in continuo") on 1318 basins over Europe with different physiographic characteristics. Results have suggested that, among the continuous metrics, correlation coefficient and Kling-Gupta efficiency index are not reliable scores to select rainfall product performing best for hydrological modelling whereas bias and root mean square error seem more appropriate. In particular, by constraining the relative bias to values lower than 0.2 and the relative root mean square error to values lower than 2, good hydrological performances (Kling-Gupta efficiency index on discharge greater than 0.5) are ensured for almost 75 % of the basins fulfilling these criteria. Conversely, the categorical scores have not provided suitable information to address the SRPs selection for hydrological modelling.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da1
Pagine a35
Pagine totali-
RivistaHydrology and earth system sciences
Attiva dal 1997
Editore: Copernicus Publ. - Göttingen
Paese di pubblicazione: Germania
Lingua: inglese
ISSN: 1027-5606
Titolo chiave: Hydrology and earth system sciences
Titolo proprio: Hydrology and earth system sciences.
Titolo abbreviato: Hydrol. earth syst. sci.
Titoli alternativi:
  • HESS (Göttingen. Print)
  • Hydrology and earth system sciences (Print)
Numero volume della rivista2020
Fascicolo della rivista-
Verificato da refereeSì: Internazionale
Stato della pubblicazionePreprint
Indicizzazione (in banche dati controllate)-
Parole chiaveeurope, flood simulation, flood, rainfall metric
Link (URL, URI)
Titolo parallelo-
Scadenza embargo-
Data di accettazione17/08/2020
Note/Altre informazioniAccepted for publication
Strutture CNR
  • IRPI — Istituto di ricerca per la protezione idrogeologica
Moduli/Attività/Sottoprogetti CNR-
Progetti Europei-