Improving the skill of the Chao Phraya hydrologic forecasting system using pre-processed numerical weather forecasts

Theerapol Charoensuk; Jakob Luchner; Nicola Balbarini; Piyamarn Sisomphon; Peter Bauer-Gottwein

doi:10.3850/978-90-833476-1-5_iahr40wc-p0343-cd

Improving the skill of the Chao Phraya hydrologic forecasting system using pre-processed numerical weather forecasts

Theerapol Charoensuk^*, Jakob Luchner, Nicola Balbarini, Piyamarn Sisomphon, Peter Bauer-Gottwein

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

Accurate predictions of flooding are important for emergency response and flood management. The quality of numerical weather forecasts is one main parameter controlling the quality of flood forecasts. This study focused on improving the skill of the Chao Phraya hydrologic forecasting system using pre-processed numerical weather forecasts. The applied preprocessing method was quantile mapping bias correction (QM). The rainfall forecast data with QM (WRF-QM) pre-processing were evaluated against the daily rainfall measurements from HydroInformatics Institute (HII)’s stations in each sub-catchment and compared with the raw rainfall prediction (Raw WRF). Evaluation results for the period 2016 – 2019 (training period) and 2020-2021 (testing period) showed that the WRF-QM method effectively improves the rainfall prediction by around 15 percent. Reforecasting experiments were performed with the hydrological model using pre-processed forecast precipitation to compare runoff forecast with and without the pre-processing method. The overall performance results show that runoff forecasting with WRF-QM preprocessing can significantly improve accuracy by ca. 30 percent when compared to runoff without preprocessing (Raw WRF). Our study demonstrates that the pre-processed numerical weather forecasts can improve the skill of hydrologic forecasting systems to benefit the real-time Chao Phaya flood operation system.

Original language	English
Title of host publication	Proceedings of the 40th IAHR World Congress
Editors	Helmut Habersack, Michael Tritthart, Lisa Waldenberger
Number of pages	7
Publisher	International Association for Hydro-Environment Engineering and Research (IAHR)
Publication date	2023
Pages	38-44
ISBN (Print)	9789083347615
DOIs	https://doi.org/10.3850/978-90-833476-1-5_iahr40wc-p0343-cd
Publication status	Published - 2023
Event	40th IAHR World Congress, 2023 - Vienna, Austria Duration: 21 Aug 2023 → 25 Aug 2023

Conference

Conference	40th IAHR World Congress, 2023
Country/Territory	Austria
City	Vienna
Period	21/08/2023 → 25/08/2023

Series	Proceedings of the IAHR World Congress
ISSN	2521-7119

Keywords

Flood
Forecasting
Performance
Uncertainty
Chao Phraya River basin

Access to Document

10.3850/978-90-833476-1-5_iahr40wc-p0343-cd

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Charoensuk, T., Luchner, J., Balbarini, N., Sisomphon, P., & Bauer-Gottwein, P. (2023). Improving the skill of the Chao Phraya hydrologic forecasting system using pre-processed numerical weather forecasts. In H. Habersack, M. Tritthart, & L. Waldenberger (Eds.), Proceedings of the 40th IAHR World Congress (pp. 38-44). International Association for Hydro-Environment Engineering and Research (IAHR). https://doi.org/10.3850/978-90-833476-1-5_iahr40wc-p0343-cd

Charoensuk, Theerapol ; Luchner, Jakob ; Balbarini, Nicola et al. / Improving the skill of the Chao Phraya hydrologic forecasting system using pre-processed numerical weather forecasts. Proceedings of the 40th IAHR World Congress. editor / Helmut Habersack ; Michael Tritthart ; Lisa Waldenberger. International Association for Hydro-Environment Engineering and Research (IAHR), 2023. pp. 38-44 (Proceedings of the IAHR World Congress).

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abstract = "Accurate predictions of flooding are important for emergency response and flood management. The quality of numerical weather forecasts is one main parameter controlling the quality of flood forecasts. This study focused on improving the skill of the Chao Phraya hydrologic forecasting system using pre-processed numerical weather forecasts. The applied preprocessing method was quantile mapping bias correction (QM). The rainfall forecast data with QM (WRF-QM) pre-processing were evaluated against the daily rainfall measurements from HydroInformatics Institute (HII){\textquoteright}s stations in each sub-catchment and compared with the raw rainfall prediction (Raw WRF). Evaluation results for the period 2016 – 2019 (training period) and 2020-2021 (testing period) showed that the WRF-QM method effectively improves the rainfall prediction by around 15 percent. Reforecasting experiments were performed with the hydrological model using pre-processed forecast precipitation to compare runoff forecast with and without the pre-processing method. The overall performance results show that runoff forecasting with WRF-QM preprocessing can significantly improve accuracy by ca. 30 percent when compared to runoff without preprocessing (Raw WRF). Our study demonstrates that the pre-processed numerical weather forecasts can improve the skill of hydrologic forecasting systems to benefit the real-time Chao Phaya flood operation system.",

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Charoensuk, T, Luchner, J, Balbarini, N, Sisomphon, P & Bauer-Gottwein, P 2023, Improving the skill of the Chao Phraya hydrologic forecasting system using pre-processed numerical weather forecasts. in H Habersack, M Tritthart & L Waldenberger (eds), Proceedings of the 40th IAHR World Congress. International Association for Hydro-Environment Engineering and Research (IAHR), Proceedings of the IAHR World Congress, pp. 38-44, 40th IAHR World Congress, 2023, Vienna, Austria, 21/08/2023. https://doi.org/10.3850/978-90-833476-1-5_iahr40wc-p0343-cd

Improving the skill of the Chao Phraya hydrologic forecasting system using pre-processed numerical weather forecasts. / Charoensuk, Theerapol; Luchner, Jakob; Balbarini, Nicola et al.
Proceedings of the 40th IAHR World Congress. ed. / Helmut Habersack; Michael Tritthart; Lisa Waldenberger. International Association for Hydro-Environment Engineering and Research (IAHR), 2023. p. 38-44 (Proceedings of the IAHR World Congress).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Charoensuk T, Luchner J, Balbarini N, Sisomphon P, Bauer-Gottwein P. Improving the skill of the Chao Phraya hydrologic forecasting system using pre-processed numerical weather forecasts. In Habersack H, Tritthart M, Waldenberger L, editors, Proceedings of the 40th IAHR World Congress. International Association for Hydro-Environment Engineering and Research (IAHR). 2023. p. 38-44. (Proceedings of the IAHR World Congress). doi: 10.3850/978-90-833476-1-5_iahr40wc-p0343-cd

Improving the skill of the Chao Phraya hydrologic forecasting system using pre-processed numerical weather forecasts

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