Uncertainty of Flood Forecasts via Ensemble Precipitation Forecasts of Seven NWP Models for Spring 2019 Golestan Flood

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SAEDI A.; SAGHAFIAN B.; MOAZAMI S.

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Journal: IRAN-WATER RESOURCES RESEARCH Year:2020 | Volume:16 | Issue:1 Page(s): 347-359

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Title

Uncertainty of Flood Forecasts via Ensemble Precipitation Forecasts of Seven NWP Models for Spring 2019 Golestan Flood

Author(s)

SAEDI A. | SAGHAFIAN B. | MOAZAMI S. | Issue Writer Certificate

Keywords

Ensemble ForecastingQ1

Bias CorrectionQ1

Flood ForecastingQ2

Uncertainty AnalysisQ2

GolestanQ1

Abstract

Nowadays, much effort has been made in improving meteorological forecasts. In this regard, Ensemble Forecasting systems have been developed to reduce forecast uncertainties. In this study, the performance of ensemble precipitation forecasts of seven numerical models in 2019 Gorganroud floods was studied. Initially, the precipitation forecasts of the seven numerical models were bias-corrected via gamma quantile mapping method. Then ensemble streamflow forecasts were obtained by ensemble precipitation of seven models using the GR4J conceptual rainfall-runoff model. Moreover, four optimization methods were used to determine optimal GR4J model parameters in calibration phase. Based on the optimized parameters, ensemble streamflow forecasts were performed with precipitation forecasts inputs while uncertainty of the models was analyzed based on inputs to the hydrological model. The results showed that the Bias Correction had a great impact on the improvement of flood forecast in the study basin such that the uncertainty bands of the ECMWF, NCMRWF and UKMO models well covered the observed flood values. Pfactor and R-factor values of the ECMWF model was 0. 5 and 0. 96, respectively; however, the upper and lower bands of ECMWF model was symmetrical. The NCEP and CMA models had poorer performance in flood forecast compared with other models so that their P-factor values were 0. 2 and 0. 15, respectively. The JMA model overestimated the 2019 flood. Although the ECCC model bands covered 65% of the observed flood values, the gap between the upper and lower bands was quite high. Overall, the results of a number of NWP models in the study basin were satisfactory and their application is generally recommended for flood warning systems.

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APA: Copy

SAEDI, A., SAGHAFIAN, B., & MOAZAMI, S.. (2020). Uncertainty of Flood Forecasts via Ensemble Precipitation Forecasts of Seven NWP Models for Spring 2019 Golestan Flood. IRAN-WATER RESOURCES RESEARCH, 16(1 ), 347-359. SID. https://sid.ir/paper/383885/en

Vancouver: Copy

SAEDI A., SAGHAFIAN B., MOAZAMI S.. Uncertainty of Flood Forecasts via Ensemble Precipitation Forecasts of Seven NWP Models for Spring 2019 Golestan Flood. IRAN-WATER RESOURCES RESEARCH[Internet]. 2020;16(1 ):347-359. Available from: https://sid.ir/paper/383885/en

IEEE: Copy

A. SAEDI, B. SAGHAFIAN, and S. MOAZAMI, “Uncertainty of Flood Forecasts via Ensemble Precipitation Forecasts of Seven NWP Models for Spring 2019 Golestan Flood,” IRAN-WATER RESOURCES RESEARCH, vol. 16, no. 1 , pp. 347–359, 2020, [Online]. Available: https://sid.ir/paper/383885/en

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