Skip to main content
SpringerLink
Log in

Assessment of Ensemble Flood Forecasting with Numerical Weather Prediction by considering Spatial Shift of Rainfall Fields

  • Water Resources and Hydrologic Engineering
  • Published:
KSCE Journal of Civil Engineering Aims and scope

Abstract

This study evaluated the ensemble flood forecasting by using ensemble forecast outputs of the Numerical Weather Prediction (NWP) model with a distributed hydrologic model. Ensemble NWP rainfall with a 2 km horizontal resolution and 30 hour forecast time was assessed whether it can produce suitable rainfall compared with the deterministic rainfall forecast during the typhoon TALAS, 2011. The ensemble flood forecast based on ensemble NWP rainfall was also assessed for hydrological applications. This study presents a methodology using the spatial movement of ensemble rainfall field in order to improve the accuracy of ensemble flood prediction considering the location correction of Quantitative Precipitation Forecast (QPF). This study was conducted using the largest flood events occurred by typhoon TALAS in 2011 with regard to the Futatsuno (356.1 km2) and Nanairo (182.1 km2) dam catchments in the Shingu river basin (2,360 km2) located in Kii Peninsula of Japan. As a result, the flood prediction using the spatial movement of ensemble rainfall field could improve the under-predicted interval of the flood prediction using the original ensemble rainfall. In addition, it was able to reproduce the peak discharge in the first and second prediction intervals for both catchments and to cover the observed value. The method we proposed in this study can be used in hydrological applications such as real-time flood prediction including flood prediction and warning systems, optimized discharge flow for dam operation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Bartholmes, J. and Todini, E. (2005). “Coupling meteorological and hydrological models for flood forecasting.” Hydrology and Earth System Sciences, Vol. 9, pp. 333–346, DOI: 10.5194/hess-9-333-2005.

    Article  Google Scholar 

  • Buizza, R., Miller, M., and Palmer, T. N. (1999). “Stochastic representation of model uncertainties in the ECMWF ensemble prediction system.” Quarterly Journal of the Royal Meteorological Society, Vol. 125, No. 560, pp. 2887–2908, DOI: 10.1002/qj.49712556006.

    Article  Google Scholar 

  • Cloke H. L. and Pappenberger, F. (2009). “Ensemble flood forecasting: A review.” Journal of Hydrology, Vol. 375, Nos. 3–4, pp. 613–626, DOI: 10.1016/j.jhydrol.2009.06.005

    Article  Google Scholar 

  • Cuo, L., Pagano, T. C., and Wang, Q. J. (2011). “A review of quantitative precipitation forecasts and their use in short-to medium-range streamflow forecasting.” Journal of Hydrometeorology, Vol. 12, pp. 713–728, DOI: 10.1175/2011JHM1347.1.

    Article  Google Scholar 

  • Demeritt, D., Cloke, H., Pappenberger, F., Thielen, J., Bartholmes, J., and Ramos, M. H. (2007). “Ensemble predictions and perceptions of risk, uncertainty, and error in flood forecasting.” Environmental Hazards, Vol. 7, No. 2, pp. 115–127, DOI: 10.1016/j.envhaz.2007.05.001.

    Article  Google Scholar 

  • Duc, L., Saito, K., and Seko, H. (2013). “Spatial-temporal fractions verification for high resolution ensemble forecasts.” Tellus A, Vol. 65, No. 1, p. 18171, DOI: 10.3402/tellusa.v65i0.18171.

    Article  Google Scholar 

  • Ebert, E. and McBride, J. (2000). “Verification of precipitation in weather systems: Determination of systematic errors.” Journal of Hydrology, Vol. 239, Nos. 1–4, pp. 179–202, DOI: 10.1016/S0022-1694(00)00343-7.

    Article  Google Scholar 

  • Gouweleeuw, B., Thielen, J., Franchello, G., de Roo, A., and Buizza, R. (2005). “Flood forecasting using medium-range probabilistic weather prediction.” Hydrology and Earth System Sciences, Vol. 9, No. 4, pp. 365–380, DOI: 10.5194/hess-9-365-2005.

    Article  Google Scholar 

  • Hlavcova, K., Szolgay, J., Kubes, R., Kohnova, S., and Zvolensky, M. (2006). Routing of numerical weather predictions through a rainfall–runoff model, In: J. Marsalek, G. Stancalie, and G. Balint (Eds.), Transboundary Floods: Reducing Risks through Flood Management, Springer, NATO Science Series, Dordecht, Netherlands, pp. 57–68.

  • Hsiao, L., Yang, M., Lee, C., Kuo, H., Shih, D., Tsai, C., Wang, C., Chang, L., Chen, D., Feng, L., Hong, J., Fong, C., Chen, D., Yeh, T., Huang, C., Guo, W., and Lin, G. (2013). “Ensemble forecasting of typhoon rainfall and floods over a mountainous watershed in Taiwan.” Journal of Hydrology, Vol. 506, pp. 55–68, DOI: 10.1016/j.jhydrol.2013.08.046.

    Article  Google Scholar 

  • Kobayashi, K., Otsuka, S., Apip, and Saito, K. (2016). “Ensemble flood simulation for a small dam catchment in Japan using 10 km and 2 km resolution nonhydrostatic model rainfalls.” Natural Hazards and Earth System Sciences, Vol. 16, pp. 1821–1839, DOI: 10.5194/nhess-16-1821-2016.

    Article  Google Scholar 

  • Komma, J., Reszler, C., Blöschl, G., and Haiden, T. (2007). “Ensemble prediction of floods -catchment non-linearity and forecast probabilities.” Natural Hazards and Earth System Sciences, Vol. 7, No. 4, pp. 431–444, DOI: 10.5194/nhess-7-431-2007.

    Article  Google Scholar 

  • Legg, T. P. and Mylne, K. R. (2004). “Early warnings of severe weather from ensemble forecast information.” Weather Forecast, Vol. 18, pp. 891–906, DOI: 10.1175/1520-0434(2004)019<0891: EWOSWF> 2.0.CO;2.

    Article  Google Scholar 

  • Matsubara, T., Kasahara, S., Shimada, Y., Nakakita, E., Tsuchida, K., and Takada, N. (2013). “Study on applicability of information of typhoons and GSM for dam operation.” Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol. 69, No. 4, pp. I_367–I_372, DOI: 10.2208/jscejhe.69.I_367.

    Article  Google Scholar 

  • Nester, T., Komma, J., Viglione, A., and Blöschl, G. (2012). “Flood forecast errors and ensemble spread–A case study.” Water Resources Research, Vol. 48, No. W10502, p. 9, DOI: 10.1029/2011WR011649.

    Google Scholar 

  • Origuchi, S., Saito, K., Duc, L., and Kobayashi, K. (2013). “Mesoscale ensemble forecast experiment for the Typhoon Talas event.” Technical Report. Japan Meteorological Agency, Vol. 134, pp. 184–194, [in Japanese, available online at https://doi.org/www.jma.go.jp/jma/kishou/books/gizyutu/134/ALL.pdf].

    Google Scholar 

  • Palmer, T. and Buizza, R. (2007). “Fifteenth anniversary of EPS.” ECMWF Newsletter, Vol. 114, pp. 14.

    Google Scholar 

  • Roulin, E. and Vannitsem, S. (2005). “Skill of medium-range hydrological ensemble predictions.” Journal of Hydrometeorology, Vol. 6, No. 5, pp. 729–744, DOI: 10.1175/JHM436.1.

    Article  Google Scholar 

  • Saito, K. (2012). “The JMA nonhydrostatic model and its application to operation and research.” In: Yucel, I. (Eds.). Atmospheric Model Applications, InTech. pp. 85–110.

    Google Scholar 

  • Saito, K., Fujita, T., Yamada, Y., Ishida, J., Kumagai, Y., Aranami, K., Ohmori, S., Nagasawa, R., Kumagai, S., Muroi, C., Kato, T., Eito, H., and Yamazaki, Y. (2006). “The operational JMA nonhydrostatic meso-scale model.” Monthly Weather Review, Vol. 134, pp. 1266–1298, DOI: 10.1175/MWR3120.1.

    Article  Google Scholar 

  • Schaake, J., Perica, S., Mullusky, M., Demargne, J., Welles, E., and Wu, L. (2004). “Pre-processing of atmospheric forcing for ensemble runoff prediction.” Proceedings of the 84th AMS Annual Meeting, [available at https://doi.org/ams.confex.com/ams/pdfpapers/72172.pdf].

    Google Scholar 

  • Tachikawa, Y., Nagatani, G., and Takara, K. (2004). “Development of stage-discharge relationship equation incorporating saturated–unsaturated flow mechanism.” Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol. 48, pp. 7–12.

    Google Scholar 

  • Takasao, T. and Shiiba, M. (1988). “Incorporation of the effect of concentration of flow into the kinematic wave equations and its applications to runoff system lumping.” Journal of Hydrology, Vol. 102, Nos. 1–4, pp. 301–322, DOI: 10.1016/0022–1694(88) 90104–7.

    Article  Google Scholar 

  • Velazquez, J. A., Anctil, F., Ramos, M. H., and Perrin, C. (2011). “Can a multi-model approach improve hydrological ensemble forecasting? A study on 29 French catchments using 16 hydrological model structures.” Advances in Geosciences, Vol. 29, pp. 33–42, DOI: 10.5194/adgeo-29-33-2011.

    Article  Google Scholar 

  • World Meteorogical Organization. (2011). Manual on flood forecasting and warning (WMO-No. 1072), Geneva, Switzerland.

  • Xuan, Y., Cluckie, I., and Wang, Y. (2009). “Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilizing short-range rainfall prediction.” Hydrology and Earth System Sciences, Vol. 13, pp. 293–303, DOI: 10.5194/hess-13-293-2009.

    Article  Google Scholar 

  • Yu, W., Nakakita, E., Kim, S., and Yamaguchi, K. (2014). “Accuracy improvement of flood forecasting using pre-processing of ensemble numerical weather prediction rainfall fields.” Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol. 70, No. 4, pp. I_151–I_156, DOI: 10.2208/jscejhe.70.I_151.

    Article  Google Scholar 

  • Yu, W., Nakakita, E., Kim, S., and Yamaguchi, K. (2015). “Improvement of rainfall and flood forecasts by blending ensemble NWP rainfall with radar prediction considering orographic rainfall.” Journal of Hydrology, Vol. 531, No. Part 2, pp. 494–507, DOI: 10.1016/j.jhydrol.2015.04.055.

    Article  Google Scholar 

  • Yu, W., Nakakita, E., Kim, S., and Yamaguchi, K. (2016). “Impact assessment of uncertainty propagation of ensemble NWP rainfall to flood forecasting with catchment scale.” Advances in Meteorology, Vol. 2016, Article ID 1384302, p. 17, DOI: 10.1155/2016/1384302.

    Google Scholar 

  • Yu, W., Nakakita, E., Kim, S., and Yamaguchi, K. (2016). “Improving the accuracy of flood forecasting with transpositions of ensemble NWP rainfall fields considering orographic effects.” Journal of Hydrology, Vol. 539, pp. 85–110, DOI: 10.1016/j.jhydrol.2016.05.047.

    Article  Google Scholar 

  • Yu, W., Nakakita, E., and Yamaguchi, K. (2013). “Assessment of probabilistic flood Forecasting using ensemble NWP rainfall with 30hr forecast time during typhoon events.” Advances in River Engineering, Vol. 19, pp. 235–240, DOI: 10.1155/2016/1384302.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. International Water Resources Research Institute, Chungnam National University, Daejeon, 34134, Korea

    Wansik Yu & Kosei Yamaguchi

  2. Disaster Prevention Research Institute, Kyoto University, Kyoto, 611-0011, Japan

    Eiichi Nakakita

  3. Dept. of Civil and Earth Resources Engineering, Kyoto University, Kyoto, 615-8540, Japan

    Sunmin Kim

Authors
  1. Wansik Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eiichi Nakakita
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sunmin Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kosei Yamaguchi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wansik Yu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yu, W., Nakakita, E., Kim, S. et al. Assessment of Ensemble Flood Forecasting with Numerical Weather Prediction by considering Spatial Shift of Rainfall Fields. KSCE J Civ Eng 22, 3686–3696 (2018). https://doi.org/10.1007/s12205-018-0407-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12205-018-0407-x

Keywords

Search

Navigation