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Investigación de vangarda para o desenvolvemento sostible

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2019

Fraga, Ignacio; Cea-Gómez, Luis; Puertas-Agudo, Jerónimo

Effect of rainfall uncertainty on the performance of physically based rainfall–runoff models Journal Article

In: Hydrological Processes, vol. 33, no. 1, pp. 160-173, 2019, ISSN: 08856087, (cited By 38).

Abstract | Links | BibTeX | Etiquetas: Catchments; Glues; Gluing; Rain; Runoff; Storms, Conditional simulations; Fully distributed modeling; Generalized likelihood uncertainty estimation; Hydrological models; Quantitative precipitation estimation; Rainfall uncertainties; Runoff modelling; Transformation process, discharge; estimation method; precipitation assessment; quantitative analysis; rainfall-runoff modeling; uncertainty analysis, Spain, Uncertainty analysis

@article{Fraga2019160,

title = {Effect of rainfall uncertainty on the performance of physically based rainfall–runoff models},

author = {Ignacio Fraga and Luis Cea-Gómez and Jerónimo Puertas-Agudo},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057832365&doi=10.1002%2fhyp.13319&partnerID=40&md5=8bbb0e74a81e6b2f7faed33c5596c9e0},

doi = {10.1002/hyp.13319},

issn = {08856087},

year  = {2019},

date = {2019-01-01},

urldate = {2019-01-01},

journal = {Hydrological Processes},

volume = {33},

number = {1},

pages = {160-173},

publisher = {John Wiley and Sons Ltd},

abstract = {This paper analyses the effect of rain data uncertainty on the performance of two hydrological models with different spatial structures: a semidistributed and a fully distributed model. The study is performed on a small catchment of 19.6 km2 located in the north-west of Spain, where the arrival of low pressure fronts from the Atlantic Ocean causes highly variable rainfall events. The rainfall fields in this catchment during a series of storm events are estimated using rainfall point measurements. The uncertainty of the estimated fields is quantified using a conditional simulation technique. Discharge and rain data, including the uncertainty of the estimated rainfall fields, are then used to calibrate and validate both hydrological models following the generalized likelihood uncertainty estimation (GLUE) methodology. In the storm events analysed, the two models show similar performance. In all cases, results show that the calibrated distribution of the input parameters narrows when the rain uncertainty is included in the analysis. Otherwise, when rain uncertainty is not considered, the calibration of the input parameters must account for all uncertainty in the rainfall–runoff transformation process. Also, in both models, the uncertainty of the predicted discharges increase in similar magnitude when the uncertainty of rainfall input increase. © 2018 John Wiley & Sons, Ltd.},

note = {cited By 38},

keywords = {Catchments; Glues; Gluing; Rain; Runoff; Storms, Conditional simulations; Fully distributed modeling; Generalized likelihood uncertainty estimation; Hydrological models; Quantitative precipitation estimation; Rainfall uncertainties; Runoff modelling; Transformation process, discharge; estimation method; precipitation assessment; quantitative analysis; rainfall-runoff modeling; uncertainty analysis, Spain, Uncertainty analysis},

pubstate = {published},

tppubtype = {article}

}