A robust real-time flood forecasting method based on error estimation for reservoirs

The observed discharge, an important input for flood forecasting systems, can significantly affect the accuracy of forecasting results. Since the reservoir inflow is not measured directly but calculated based on the observed reservoir stage and the reservoir outflow, it always contains gross errors...
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Autor*in:	Dandan Shen [verfasserIn] Weimin Bao [verfasserIn] Peng Ni [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	error distribution flood forecasting fluctuation coefficient reservoir inflow robust estimation

Übergeordnetes Werk:	In: Aqua - IWA Publishing, 2021, 71(2022), 4, Seite 518-532
Übergeordnetes Werk:	volume:71 ; year:2022 ; number:4 ; pages:518-532

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.2166/aqua.2022.156

Katalog-ID:	DOAJ031330495

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520			\|a The observed discharge, an important input for flood forecasting systems, can significantly affect the accuracy of forecasting results. Since the reservoir inflow is not measured directly but calculated based on the observed reservoir stage and the reservoir outflow, it always contains gross errors causing some inflow to be outliers. In this study, a robust error estimation method for real-time flood forecasting has been developed for reservoirs’ data processing. The method differs from the conventional flood forecasting method, in that it represses the gross errors by a robust loss function based on the real error distribution of measurements. Furthermore, a fluctuation coefficient has been proposed to quantify the degree of fluctuation of a jagged reservoir inflow. The performance of the method is evaluated by both synthetic data and real cases. By using floods generated synthetically by an ideal model in which the true values and errors are known, the method is shown to be efficient as theoretically expected. The results show that the method is efficient and universally applicable in different cases. And the degree of forecast improvement is positively related to the fluctuation coefficient of the floods. The more severe the fluctuation of the flood hydrograph, the more robust the method. HIGHLIGHTS A robust error estimation method for real-time flood forecasting in reservoirs is developed.; A fluctuation coefficient is proposed to quantify the degree of fluctuation of a jagged reservoir inflow.; The method is demonstrated to be efficient by an ideal model and 10 reservoir basins of different characteristics.; The performance of the proposed method is positively related to the fluctuation coefficient of the floods.;
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spelling	10.2166/aqua.2022.156 doi (DE-627)DOAJ031330495 (DE-599)DOAJa550c919ab494299b297ced86be6a194 DE-627 ger DE-627 rakwb eng TD1-1066 GE1-350 Dandan Shen verfasserin aut A robust real-time flood forecasting method based on error estimation for reservoirs 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The observed discharge, an important input for flood forecasting systems, can significantly affect the accuracy of forecasting results. Since the reservoir inflow is not measured directly but calculated based on the observed reservoir stage and the reservoir outflow, it always contains gross errors causing some inflow to be outliers. In this study, a robust error estimation method for real-time flood forecasting has been developed for reservoirs’ data processing. The method differs from the conventional flood forecasting method, in that it represses the gross errors by a robust loss function based on the real error distribution of measurements. Furthermore, a fluctuation coefficient has been proposed to quantify the degree of fluctuation of a jagged reservoir inflow. The performance of the method is evaluated by both synthetic data and real cases. By using floods generated synthetically by an ideal model in which the true values and errors are known, the method is shown to be efficient as theoretically expected. The results show that the method is efficient and universally applicable in different cases. And the degree of forecast improvement is positively related to the fluctuation coefficient of the floods. The more severe the fluctuation of the flood hydrograph, the more robust the method. HIGHLIGHTS A robust error estimation method for real-time flood forecasting in reservoirs is developed.; A fluctuation coefficient is proposed to quantify the degree of fluctuation of a jagged reservoir inflow.; The method is demonstrated to be efficient by an ideal model and 10 reservoir basins of different characteristics.; The performance of the proposed method is positively related to the fluctuation coefficient of the floods.; error distribution flood forecasting fluctuation coefficient reservoir inflow robust estimation Environmental technology. Sanitary engineering Environmental sciences Weimin Bao verfasserin aut Peng Ni verfasserin aut In Aqua IWA Publishing, 2021 71(2022), 4, Seite 518-532 (DE-627)1757644571 27098036 nnns volume:71 year:2022 number:4 pages:518-532 https://doi.org/10.2166/aqua.2022.156 kostenfrei https://doaj.org/article/a550c919ab494299b297ced86be6a194 kostenfrei http://aqua.iwaponline.com/content/71/4/518 kostenfrei https://doaj.org/toc/2709-8028 Journal toc kostenfrei https://doaj.org/toc/2709-8036 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 71 2022 4 518-532
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allfieldsGer	10.2166/aqua.2022.156 doi (DE-627)DOAJ031330495 (DE-599)DOAJa550c919ab494299b297ced86be6a194 DE-627 ger DE-627 rakwb eng TD1-1066 GE1-350 Dandan Shen verfasserin aut A robust real-time flood forecasting method based on error estimation for reservoirs 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The observed discharge, an important input for flood forecasting systems, can significantly affect the accuracy of forecasting results. Since the reservoir inflow is not measured directly but calculated based on the observed reservoir stage and the reservoir outflow, it always contains gross errors causing some inflow to be outliers. In this study, a robust error estimation method for real-time flood forecasting has been developed for reservoirs’ data processing. The method differs from the conventional flood forecasting method, in that it represses the gross errors by a robust loss function based on the real error distribution of measurements. Furthermore, a fluctuation coefficient has been proposed to quantify the degree of fluctuation of a jagged reservoir inflow. The performance of the method is evaluated by both synthetic data and real cases. By using floods generated synthetically by an ideal model in which the true values and errors are known, the method is shown to be efficient as theoretically expected. The results show that the method is efficient and universally applicable in different cases. And the degree of forecast improvement is positively related to the fluctuation coefficient of the floods. The more severe the fluctuation of the flood hydrograph, the more robust the method. HIGHLIGHTS A robust error estimation method for real-time flood forecasting in reservoirs is developed.; A fluctuation coefficient is proposed to quantify the degree of fluctuation of a jagged reservoir inflow.; The method is demonstrated to be efficient by an ideal model and 10 reservoir basins of different characteristics.; The performance of the proposed method is positively related to the fluctuation coefficient of the floods.; error distribution flood forecasting fluctuation coefficient reservoir inflow robust estimation Environmental technology. Sanitary engineering Environmental sciences Weimin Bao verfasserin aut Peng Ni verfasserin aut In Aqua IWA Publishing, 2021 71(2022), 4, Seite 518-532 (DE-627)1757644571 27098036 nnns volume:71 year:2022 number:4 pages:518-532 https://doi.org/10.2166/aqua.2022.156 kostenfrei https://doaj.org/article/a550c919ab494299b297ced86be6a194 kostenfrei http://aqua.iwaponline.com/content/71/4/518 kostenfrei https://doaj.org/toc/2709-8028 Journal toc kostenfrei https://doaj.org/toc/2709-8036 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 71 2022 4 518-532
allfieldsSound	10.2166/aqua.2022.156 doi (DE-627)DOAJ031330495 (DE-599)DOAJa550c919ab494299b297ced86be6a194 DE-627 ger DE-627 rakwb eng TD1-1066 GE1-350 Dandan Shen verfasserin aut A robust real-time flood forecasting method based on error estimation for reservoirs 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The observed discharge, an important input for flood forecasting systems, can significantly affect the accuracy of forecasting results. Since the reservoir inflow is not measured directly but calculated based on the observed reservoir stage and the reservoir outflow, it always contains gross errors causing some inflow to be outliers. In this study, a robust error estimation method for real-time flood forecasting has been developed for reservoirs’ data processing. The method differs from the conventional flood forecasting method, in that it represses the gross errors by a robust loss function based on the real error distribution of measurements. Furthermore, a fluctuation coefficient has been proposed to quantify the degree of fluctuation of a jagged reservoir inflow. The performance of the method is evaluated by both synthetic data and real cases. By using floods generated synthetically by an ideal model in which the true values and errors are known, the method is shown to be efficient as theoretically expected. The results show that the method is efficient and universally applicable in different cases. And the degree of forecast improvement is positively related to the fluctuation coefficient of the floods. The more severe the fluctuation of the flood hydrograph, the more robust the method. HIGHLIGHTS A robust error estimation method for real-time flood forecasting in reservoirs is developed.; A fluctuation coefficient is proposed to quantify the degree of fluctuation of a jagged reservoir inflow.; The method is demonstrated to be efficient by an ideal model and 10 reservoir basins of different characteristics.; The performance of the proposed method is positively related to the fluctuation coefficient of the floods.; error distribution flood forecasting fluctuation coefficient reservoir inflow robust estimation Environmental technology. Sanitary engineering Environmental sciences Weimin Bao verfasserin aut Peng Ni verfasserin aut In Aqua IWA Publishing, 2021 71(2022), 4, Seite 518-532 (DE-627)1757644571 27098036 nnns volume:71 year:2022 number:4 pages:518-532 https://doi.org/10.2166/aqua.2022.156 kostenfrei https://doaj.org/article/a550c919ab494299b297ced86be6a194 kostenfrei http://aqua.iwaponline.com/content/71/4/518 kostenfrei https://doaj.org/toc/2709-8028 Journal toc kostenfrei https://doaj.org/toc/2709-8036 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 71 2022 4 518-532
language	English
source	In Aqua 71(2022), 4, Seite 518-532 volume:71 year:2022 number:4 pages:518-532
sourceStr	In Aqua 71(2022), 4, Seite 518-532 volume:71 year:2022 number:4 pages:518-532
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	error distribution flood forecasting fluctuation coefficient reservoir inflow robust estimation Environmental technology. Sanitary engineering Environmental sciences
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container_title	Aqua
authorswithroles_txt_mv	Dandan Shen @@aut@@ Weimin Bao @@aut@@ Peng Ni @@aut@@
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Since the reservoir inflow is not measured directly but calculated based on the observed reservoir stage and the reservoir outflow, it always contains gross errors causing some inflow to be outliers. In this study, a robust error estimation method for real-time flood forecasting has been developed for reservoirs’ data processing. The method differs from the conventional flood forecasting method, in that it represses the gross errors by a robust loss function based on the real error distribution of measurements. Furthermore, a fluctuation coefficient has been proposed to quantify the degree of fluctuation of a jagged reservoir inflow. The performance of the method is evaluated by both synthetic data and real cases. By using floods generated synthetically by an ideal model in which the true values and errors are known, the method is shown to be efficient as theoretically expected. The results show that the method is efficient and universally applicable in different cases. 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callnumber-first	T - Technology
author	Dandan Shen
spellingShingle	Dandan Shen misc TD1-1066 misc GE1-350 misc error distribution misc flood forecasting misc fluctuation coefficient misc reservoir inflow misc robust estimation misc Environmental technology. Sanitary engineering misc Environmental sciences A robust real-time flood forecasting method based on error estimation for reservoirs
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topic_title	TD1-1066 GE1-350 A robust real-time flood forecasting method based on error estimation for reservoirs error distribution flood forecasting fluctuation coefficient reservoir inflow robust estimation
topic	misc TD1-1066 misc GE1-350 misc error distribution misc flood forecasting misc fluctuation coefficient misc reservoir inflow misc robust estimation misc Environmental technology. Sanitary engineering misc Environmental sciences
topic_unstemmed	misc TD1-1066 misc GE1-350 misc error distribution misc flood forecasting misc fluctuation coefficient misc reservoir inflow misc robust estimation misc Environmental technology. Sanitary engineering misc Environmental sciences
topic_browse	misc TD1-1066 misc GE1-350 misc error distribution misc flood forecasting misc fluctuation coefficient misc reservoir inflow misc robust estimation misc Environmental technology. Sanitary engineering misc Environmental sciences
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title	A robust real-time flood forecasting method based on error estimation for reservoirs
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title_full	A robust real-time flood forecasting method based on error estimation for reservoirs
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author_browse	Dandan Shen Weimin Bao Peng Ni
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title_sort	robust real-time flood forecasting method based on error estimation for reservoirs
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title_auth	A robust real-time flood forecasting method based on error estimation for reservoirs
abstract	The observed discharge, an important input for flood forecasting systems, can significantly affect the accuracy of forecasting results. Since the reservoir inflow is not measured directly but calculated based on the observed reservoir stage and the reservoir outflow, it always contains gross errors causing some inflow to be outliers. In this study, a robust error estimation method for real-time flood forecasting has been developed for reservoirs’ data processing. The method differs from the conventional flood forecasting method, in that it represses the gross errors by a robust loss function based on the real error distribution of measurements. Furthermore, a fluctuation coefficient has been proposed to quantify the degree of fluctuation of a jagged reservoir inflow. The performance of the method is evaluated by both synthetic data and real cases. By using floods generated synthetically by an ideal model in which the true values and errors are known, the method is shown to be efficient as theoretically expected. The results show that the method is efficient and universally applicable in different cases. And the degree of forecast improvement is positively related to the fluctuation coefficient of the floods. The more severe the fluctuation of the flood hydrograph, the more robust the method. HIGHLIGHTS A robust error estimation method for real-time flood forecasting in reservoirs is developed.; A fluctuation coefficient is proposed to quantify the degree of fluctuation of a jagged reservoir inflow.; The method is demonstrated to be efficient by an ideal model and 10 reservoir basins of different characteristics.; The performance of the proposed method is positively related to the fluctuation coefficient of the floods.;
abstractGer	The observed discharge, an important input for flood forecasting systems, can significantly affect the accuracy of forecasting results. Since the reservoir inflow is not measured directly but calculated based on the observed reservoir stage and the reservoir outflow, it always contains gross errors causing some inflow to be outliers. In this study, a robust error estimation method for real-time flood forecasting has been developed for reservoirs’ data processing. The method differs from the conventional flood forecasting method, in that it represses the gross errors by a robust loss function based on the real error distribution of measurements. Furthermore, a fluctuation coefficient has been proposed to quantify the degree of fluctuation of a jagged reservoir inflow. The performance of the method is evaluated by both synthetic data and real cases. By using floods generated synthetically by an ideal model in which the true values and errors are known, the method is shown to be efficient as theoretically expected. The results show that the method is efficient and universally applicable in different cases. And the degree of forecast improvement is positively related to the fluctuation coefficient of the floods. The more severe the fluctuation of the flood hydrograph, the more robust the method. HIGHLIGHTS A robust error estimation method for real-time flood forecasting in reservoirs is developed.; A fluctuation coefficient is proposed to quantify the degree of fluctuation of a jagged reservoir inflow.; The method is demonstrated to be efficient by an ideal model and 10 reservoir basins of different characteristics.; The performance of the proposed method is positively related to the fluctuation coefficient of the floods.;
abstract_unstemmed	The observed discharge, an important input for flood forecasting systems, can significantly affect the accuracy of forecasting results. Since the reservoir inflow is not measured directly but calculated based on the observed reservoir stage and the reservoir outflow, it always contains gross errors causing some inflow to be outliers. In this study, a robust error estimation method for real-time flood forecasting has been developed for reservoirs’ data processing. The method differs from the conventional flood forecasting method, in that it represses the gross errors by a robust loss function based on the real error distribution of measurements. Furthermore, a fluctuation coefficient has been proposed to quantify the degree of fluctuation of a jagged reservoir inflow. The performance of the method is evaluated by both synthetic data and real cases. By using floods generated synthetically by an ideal model in which the true values and errors are known, the method is shown to be efficient as theoretically expected. The results show that the method is efficient and universally applicable in different cases. And the degree of forecast improvement is positively related to the fluctuation coefficient of the floods. The more severe the fluctuation of the flood hydrograph, the more robust the method. HIGHLIGHTS A robust error estimation method for real-time flood forecasting in reservoirs is developed.; A fluctuation coefficient is proposed to quantify the degree of fluctuation of a jagged reservoir inflow.; The method is demonstrated to be efficient by an ideal model and 10 reservoir basins of different characteristics.; The performance of the proposed method is positively related to the fluctuation coefficient of the floods.;
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title_short	A robust real-time flood forecasting method based on error estimation for reservoirs
url	https://doi.org/10.2166/aqua.2022.156 https://doaj.org/article/a550c919ab494299b297ced86be6a194 http://aqua.iwaponline.com/content/71/4/518 https://doaj.org/toc/2709-8028 https://doaj.org/toc/2709-8036
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A robust real-time flood forecasting method based on error estimation for reservoirs

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