Study on Applicability of Information of Thphoons and GSM (Global Spectral Model) for Dam Operation

Matsubara, Takayuki; Kasahara, Satoru; Shimada, Yoshikazu; Nakakita, Eiich; Tsuchida, Kazutoshi; Takada, Nozomu

doi:10.2208/jscejhe.69.i_367

Cited by 6 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Meteorological Data. In Japan, an operational one-week ensemble prediction model from JMA was developed to provide probabilistic information of 51 ensemble members with a horizontal resolution of 60 km, and it used to be applied for hydrological applications (e.g., prior and optimized release discharge for dam operation) [11]. However, operational short-term (1-2 days) ensemble prediction with much finer resolution has not yet been developed.…”

Section: Methodsmentioning

confidence: 99%

Impact Assessment of Uncertainty Propagation of Ensemble NWP Rainfall to Flood Forecasting with Catchment Scale

Wang

Nakakita

Kim

et al. 2016

Advances in Meteorology

View full text Add to dashboard Cite

The common approach to quantifying the precipitation forecast uncertainty is ensemble simulations where a numerical weather prediction (NWP) model is run for a number of cases with slightly different initial conditions. In practice, the spread of ensemble members in terms of flood discharge is used as a measure of forecast uncertainty due to uncertain precipitation forecasts. This study presents the uncertainty propagation of rainfall forecast into hydrological response with catchment scale through distributed rainfall-runoff modeling based on the forecasted ensemble rainfall of NWP model. At first, forecast rainfall error based on the BIAS is compared with flood forecast error to assess the error propagation. Second, the variability of flood forecast uncertainty according to catchment scale is discussed using ensemble spread. Then we also assess the flood forecast uncertainty with catchment scale using an estimation regression equation between ensemble rainfall BIAS and discharge BIAS. Finally, the flood forecast uncertainty with RMSE using specific discharge in catchment scale is discussed. Our study is carried out and verified using the largest flood event by typhoon “Talas” of 2011 over the 33 subcatchments of Shingu river basin (2,360 km2), which is located in the Kii Peninsula, Japan.

show abstract

Section: Methodsmentioning

confidence: 99%

Impact Assessment of Uncertainty Propagation of Ensemble NWP Rainfall to Flood Forecasting with Catchment Scale

Wang

Nakakita

Kim

et al. 2016

Advances in Meteorology

View full text Add to dashboard Cite

show abstract

“…10) However, the operational short-term (1-2days) ensemble prediction of the Meso-Scale Model (MSM), with much finer resolution (e.g., 5 km resolution), has not been developed yet. At this moment, the short-term ensemble prediction model has been experimentally implemented by the Meteorological Research Institute (MRI) for operational applications in hydrological fields.…”

Section: Data and Methodology (1) Meteorological Input Datamentioning

confidence: 99%

Accuracy Improvement of Flood Forecasting Using Pre-Processing of Ensemble Numerical Weather Prediction Rainfall Fields

et al. 2014

View full text Add to dashboard Cite

The use of meteorological ensembles to produce sets of hydrological predictions has increased the ability to issue flood warnings. However, the spatial scale of a hydrological domain is still much finer than that of a meteorological model, and Numerical Weather Prediction (NWP) models have challenges with misplacement. This study assesses the pre-processing methods with consideration of appropriate ensemble members and a spatial shift of ensemble NWP rainfall fields, in order to improve the accuracy improvement of the ensemble flood forecasting. The analysis shows that appropriate ensemble members of NWP rainfall improves the accuracy of the mean value when ensemble forecasting a flood, whereas the transposition of NWP rainfall fields has a more suitable impact on the accuracy of the best values.

show abstract

“…In Japan, an operational one-week ensemble prediction model from Japan Meteorological Agency (JMA) was developed to provide probabilistic information of 51 ensemble members with a horizontal resolution of 60 km, and it used to be applied for hydrological applications (e.g., prior and optimized release discharge for dam operation; Matsubara et al, 2013). However, operational short-term (1-2 day) ensemble prediction with much finer resolution has not yet been developed.…”

Section: Design Of Meteorological Experimentsmentioning

confidence: 99%

Improvement of rainfall and flood forecasts by blending ensemble NWP rainfall with radar prediction considering orographic rainfall

Wang

Nakakita

Kim

et al. 2015

Journal of Hydrology

View full text Add to dashboard Cite

Study on Applicability of Information of Thphoons and GSM (Global Spectral Model) for Dam Operation

Cited by 6 publications

References 0 publications

Impact Assessment of Uncertainty Propagation of Ensemble NWP Rainfall to Flood Forecasting with Catchment Scale

Impact Assessment of Uncertainty Propagation of Ensemble NWP Rainfall to Flood Forecasting with Catchment Scale

Accuracy Improvement of Flood Forecasting Using Pre-Processing of Ensemble Numerical Weather Prediction Rainfall Fields

Improvement of rainfall and flood forecasts by blending ensemble NWP rainfall with radar prediction considering orographic rainfall

Contact Info

Product

Resources

About