Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloReliability of reanalysis and remotely sensed precipitation products for hydrological simulation over the Sefidrood River Basin, Iran
Anno di pubblicazione2020
FormatoElettronico
Autore/iAfshin Shayeghi, Asghar Azizian, Luca Brocca
Affiliazioni autoriWater Engineering Department, Imam Khomeini International University (IKIU), Qazvin, Iran Research Institute for Geo-Hydrological Protection, IRPI, Perugia, Italy
Autori CNR e affiliazioni
  • LUCA BROCCA
Lingua/e
  • inglese
AbstractHydrological models require different inputs for the simulation of processes, among which precipitation is essential. For hydrological simulation, four different precipitation products - Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE); European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-Interim); Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) real time (RT); and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) - are compared against ground-based datasets. The variable infiltration capacity (VIC) model was calibrated for the Sefidrood River Basin (SRB), Iran. APHRODITE and ERA-Interim gave better rainfall estimates at daily time scale than other products, with Nash-Sutcliffe efficiency (NSE) values of 0.79 and 0.63, and correlation coefficient (CC) of 0.91 and 0.82, respectively. At the monthly time scale, the CC between all rainfall datasets and ground observations is greater than 0.9, except for TMPA-RT. Hydrological assessment indicates that PERSIANN is the best rainfall dataset for capturing the streamflow and peak flows for the studied area (CC: 0.91, NSE: 0.80).
Lingua abstractinglese
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RivistaHydrological sciences journal
Attiva dal 1982
Editore: published for the International Association of Hydrological Sciences by Blackwell, - Oxford
Paese di pubblicazione: Regno Unito
Lingua: multilingue
ISSN: 0262-6667
Titolo chiave: Hydrological sciences journal
Titolo proprio: Hydrological sciences journal
Titolo abbreviato: Hydrol. sci. j.
Titolo alternativo: Journal des sciences hydrologiques
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DOI10.1080/02626667.2019.1691217
Verificato da refereeSì: Internazionale
Stato della pubblicazionePostprint
Indicizzazione (in banche dati controllate)-
Parole chiaveprecipitation, remote sensing, hydrological modelling, VIC-3L, streamflow
Link (URL, URI)https://www.tandfonline.com/doi/full/10.1080/02626667.2019.1691217
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Strutture CNR
  • IRPI — Istituto di ricerca per la protezione idrogeologica
Moduli/Attività/Sottoprogetti CNR
  • DTA.AD003.164.001 : Studio e monitoraggio dei processi idrologici
Progetti Europei-
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