Skip to main content
Erschienen in: Water Resources Management 3/2018

08.11.2017

Concept of Equivalent Reliability for Estimating the Design Flood under Non-stationary Conditions

verfasst von: Yiming Hu, Zhongmin Liang, Vijay P. Singh, Xuebin Zhang, Jun Wang, Binquan Li, Huimin Wang

Erschienen in: Water Resources Management | Ausgabe 3/2018

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Stationary hydrological frequency analysis (SHFA) has been commonly employed for estimating the design flood in most countries. Fundamental to applying SHFA is the assumption that the data series is stationary. In theory it is not applicable if the series is non-stationary. In this paper, we propose a concept of Equivalent Reliability (ER) to estimate the design flood under non-stationary conditions, which considers the impact of design life period of an engineering on design flood. ER implies that regardless of environmental changes, the design reliability of engineering under non-stationary conditions should be identical with the planned design reliability specified at the stage of the engineering planning. ER is expected to solve two key questions: (i) to estimate the design flood with a given return period for an engineering to be constructed, and (ii) to adjust the original design flood of an already constructed engineering to obtain a new design flood for making the engineering adapt to the changing conditions. Two experiments are provided to demonstrate how to employ ER to solve the above two questions. In addition, an example of annual peak flow series was also used to illustrate ER. Results show that the design life poses a considerable impact on the estimation of design flood and the uncertainty of parameter estimations leads to a non-negligible uncertainty on the estimation of design flood. Overall, ER can be a potential method for estimation of design flood under non-stationary conditions.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Literatur
Zurück zum Zitat Burn DH, Hag Elnur MA (2002) Detection of hydrologic trends and variability. J Hydrol 255:107–122CrossRef Burn DH, Hag Elnur MA (2002) Detection of hydrologic trends and variability. J Hydrol 255:107–122CrossRef
Zurück zum Zitat Cooley D (2013) Return periods and return levels under climate change, in extremes in a changing climate: detection, analysis and uncertainty, edited by A. Agha Kouchak et al., Springer, Dordrecht Cooley D (2013) Return periods and return levels under climate change, in extremes in a changing climate: detection, analysis and uncertainty, edited by A. Agha Kouchak et al., Springer, Dordrecht
Zurück zum Zitat Du T, Xiong LH, Xu CY et al (2015) Return period and risk analysis of nonstationary low-flow series under climate change. J Hydrol 527:234–250CrossRef Du T, Xiong LH, Xu CY et al (2015) Return period and risk analysis of nonstationary low-flow series under climate change. J Hydrol 527:234–250CrossRef
Zurück zum Zitat Hosking JRM, Wallis JR (1997) Regional Frequency Analysis. Cambridge University Press, New York Hosking JRM, Wallis JR (1997) Regional Frequency Analysis. Cambridge University Press, New York
Zurück zum Zitat Hu YM, Liang ZM, Jiang XL et al (2015) Non-stationary hydrological frequency analysis based on the reconstruction of extreme hydrological series. Proc Int Assoc Proc Int Assoc Hydrol Sci 371:163 Hu YM, Liang ZM, Jiang XL et al (2015) Non-stationary hydrological frequency analysis based on the reconstruction of extreme hydrological series. Proc Int Assoc Proc Int Assoc Hydrol Sci 371:163
Zurück zum Zitat Khaliq MN, Ouarda TBMJ, Ondo JC et al (2006) Frequency analysis of a sequence of dependent and/or non-stationary hydrometeorological observations: a review. J Hydrol 329(3):534–552CrossRef Khaliq MN, Ouarda TBMJ, Ondo JC et al (2006) Frequency analysis of a sequence of dependent and/or non-stationary hydrometeorological observations: a review. J Hydrol 329(3):534–552CrossRef
Zurück zum Zitat Li JZ, Tan SM (2015) Nonstationary flood frequency analysis for annual flood peak series, adopting climate indices and check dam index as covariates. Water Resour Manag 29(15):5533–5550CrossRef Li JZ, Tan SM (2015) Nonstationary flood frequency analysis for annual flood peak series, adopting climate indices and check dam index as covariates. Water Resour Manag 29(15):5533–5550CrossRef
Zurück zum Zitat Liang ZM, Chang WJ, Li BQ (2012) Bayesian flood frequency analysis in the light of model and parameter uncertainties. Stoch Env Res Risk A 26:721–730CrossRef Liang ZM, Chang WJ, Li BQ (2012) Bayesian flood frequency analysis in the light of model and parameter uncertainties. Stoch Env Res Risk A 26:721–730CrossRef
Zurück zum Zitat Liang ZM, Hu YM, Li BQ et al (2014) A modified weighted function method for parameter estimation of Pearson type three distribution. Water Resour Res 50(4):3216–3228CrossRef Liang ZM, Hu YM, Li BQ et al (2014) A modified weighted function method for parameter estimation of Pearson type three distribution. Water Resour Res 50(4):3216–3228CrossRef
Zurück zum Zitat Liu DD, Guo SL, Lian YQ (2015) Climate-informed lowflow frequency analysis using nonstationary modelling. Hydrol Process 29(9):2112–2124CrossRef Liu DD, Guo SL, Lian YQ (2015) Climate-informed lowflow frequency analysis using nonstationary modelling. Hydrol Process 29(9):2112–2124CrossRef
Zurück zum Zitat Lopez J, Frances F (2013) Non-stationary flood frequency analysis in continental Spanish rivers, using climate and reservoir indices as external covariates. Hydrol Earth Syst Sci 10(3):3103–3142CrossRef Lopez J, Frances F (2013) Non-stationary flood frequency analysis in continental Spanish rivers, using climate and reservoir indices as external covariates. Hydrol Earth Syst Sci 10(3):3103–3142CrossRef
Zurück zum Zitat Milly PCD, Betancourt J, Falkenmark M et al (2009) Stationarity is dead: whither water management. Science 319:573–574CrossRef Milly PCD, Betancourt J, Falkenmark M et al (2009) Stationarity is dead: whither water management. Science 319:573–574CrossRef
Zurück zum Zitat Montanari A, Koutsoyiannis D (2014) Modeling and mitigating natural hazards: Stationarity is immortal. Water Resour Res 50(12):9748–9756CrossRef Montanari A, Koutsoyiannis D (2014) Modeling and mitigating natural hazards: Stationarity is immortal. Water Resour Res 50(12):9748–9756CrossRef
Zurück zum Zitat Olsen JR, Lambert JH, Haimes YY (1998) Risk of extreme events under nonstationary conditions. Risk Anal 18(4):497–510CrossRef Olsen JR, Lambert JH, Haimes YY (1998) Risk of extreme events under nonstationary conditions. Risk Anal 18(4):497–510CrossRef
Zurück zum Zitat Parey S, Hoang TTH, Dacunha-Castelle D (2010) Different ways to compute temperature return levels in the climate change context. Environmetrics 21:698–718CrossRef Parey S, Hoang TTH, Dacunha-Castelle D (2010) Different ways to compute temperature return levels in the climate change context. Environmetrics 21:698–718CrossRef
Zurück zum Zitat Read LK, Vogel RM (2015) Reliability, return periods, and risk under nonstationarity. Water Resour Res 51(8):6381–6398CrossRef Read LK, Vogel RM (2015) Reliability, return periods, and risk under nonstationarity. Water Resour Res 51(8):6381–6398CrossRef
Zurück zum Zitat Rootzen H, Katz RW (2013) Design life level: quantifying risk in a changing climate. Water Resour Res 49(9):5964–5972CrossRef Rootzen H, Katz RW (2013) Design life level: quantifying risk in a changing climate. Water Resour Res 49(9):5964–5972CrossRef
Zurück zum Zitat Salas JD, Obeysekera J (2013) Revisiting the concepts of return period and risk for nonstationary hydrologic extreme events. J Hydrol Eng 19(3):554–568CrossRef Salas JD, Obeysekera J (2013) Revisiting the concepts of return period and risk for nonstationary hydrologic extreme events. J Hydrol Eng 19(3):554–568CrossRef
Zurück zum Zitat Strupczewski WG, Singh VP, Feluch W (2001) Non-stationary approach to at-site flood frequency modeling I. Maximum likelihood estimation. J Hydrol 248:123–142CrossRef Strupczewski WG, Singh VP, Feluch W (2001) Non-stationary approach to at-site flood frequency modeling I. Maximum likelihood estimation. J Hydrol 248:123–142CrossRef
Zurück zum Zitat Vasiliades L, Galiatsatou P, Loukas A (2015) Nonstationary frequency analysis of annual maximum rainfall using climate covariates. Water Resour Manag 29(2):339–358CrossRef Vasiliades L, Galiatsatou P, Loukas A (2015) Nonstationary frequency analysis of annual maximum rainfall using climate covariates. Water Resour Manag 29(2):339–358CrossRef
Zurück zum Zitat Volpi E, Fiori A, Grimaldi S et al (2015) One hundred years of return period: strengths and limitations. Water Resour Res 51(10):8570–8585CrossRef Volpi E, Fiori A, Grimaldi S et al (2015) One hundred years of return period: strengths and limitations. Water Resour Res 51(10):8570–8585CrossRef
Zurück zum Zitat Wigley TML (1988) The effect of climate change on the frequency of absolute extreme events. Clim Monit 17(1–2):44–55 Wigley TML (1988) The effect of climate change on the frequency of absolute extreme events. Clim Monit 17(1–2):44–55
Zurück zum Zitat Xiong L, Du T, Xu CY et al (2015) Non-stationary annual maximum flood frequency analysis using the norming constants method to consider non-stationarity in the annual daily flow series. Water Resour Manag 29(10):3615–3633CrossRef Xiong L, Du T, Xu CY et al (2015) Non-stationary annual maximum flood frequency analysis using the norming constants method to consider non-stationarity in the annual daily flow series. Water Resour Manag 29(10):3615–3633CrossRef
Zurück zum Zitat Zhang XB, Zwiers FW, Hegerl GC et al (2007) Detection of human influence on twentieth-century precipitation trends. Nature 448(7152):461–465CrossRef Zhang XB, Zwiers FW, Hegerl GC et al (2007) Detection of human influence on twentieth-century precipitation trends. Nature 448(7152):461–465CrossRef
Zurück zum Zitat Zhang XB, Wang J, Zwiers FW et al (2010) The influence of large-scale climate variability on winter maximum daily precipitation over North America. J Clim 23(11):2902–2915CrossRef Zhang XB, Wang J, Zwiers FW et al (2010) The influence of large-scale climate variability on winter maximum daily precipitation over North America. J Clim 23(11):2902–2915CrossRef
Metadaten
Titel
Concept of Equivalent Reliability for Estimating the Design Flood under Non-stationary Conditions
verfasst von
Yiming Hu
Zhongmin Liang
Vijay P. Singh
Xuebin Zhang
Jun Wang
Binquan Li
Huimin Wang
Publikationsdatum
08.11.2017
Verlag
Springer Netherlands
Erschienen in
Water Resources Management / Ausgabe 3/2018
Print ISSN: 0920-4741
Elektronische ISSN: 1573-1650
DOI
https://doi.org/10.1007/s11269-017-1851-y

Weitere Artikel der Ausgabe 3/2018

Water Resources Management 3/2018 Zur Ausgabe