Dam Spillways Adequacy Evaluation through Bivariate Flood Frequency Analysis and Hydrological Continuous Simulation

Author(s):  
L. Giustarini ◽  
S. Camici ◽  
A. Tarpanelli ◽  
L. Brocca ◽  
F. Melone ◽  
...  
2014 ◽  
Vol 14 (5) ◽  
pp. 1283-1298 ◽  
Author(s):  
D. Lawrence ◽  
E. Paquet ◽  
J. Gailhard ◽  
A. K. Fleig

Abstract. Simulation methods for extreme flood estimation represent an important complement to statistical flood frequency analysis because a spectrum of catchment conditions potentially leading to extreme flows can be assessed. In this paper, stochastic, semi-continuous simulation is used to estimate extreme floods in three catchments located in Norway, all of which are characterised by flood regimes in which snowmelt often has a significant role. The simulations are based on SCHADEX, which couples a precipitation probabilistic model with a hydrological simulation such that an exhaustive set of catchment conditions and responses is simulated. The precipitation probabilistic model is conditioned by regional weather patterns, and a bottom–up classification procedure was used to define a set of weather patterns producing extreme precipitation in Norway. SCHADEX estimates for the 1000-year (Q1000) discharge are compared with those of several standard methods, including event-based and long-term simulations which use a single extreme precipitation sequence as input to a hydrological model, statistical flood frequency analysis based on the annual maximum series, and the GRADEX method. The comparison suggests that the combination of a precipitation probabilistic model with a long-term simulation of catchment conditions, including snowmelt, produces estimates for given return periods which are more in line with those based on statistical flood frequency analysis, as compared with the standard simulation methods, in two of the catchments. In the third case, the SCHADEX method gives higher estimates than statistical flood frequency analysis and further suggests that the seasonality of the most likely Q1000 events differs from that of the annual maximum flows. The semi-continuous stochastic simulation method highlights the importance of considering the joint probability of extreme precipitation, snowmelt rates and catchment saturation states when assigning return periods to floods estimated by precipitation-runoff methods. The SCHADEX methodology, as applied here, is dependent on observed discharge data for calibration of a hydrological model, and further study to extend its application to ungauged catchments would significantly enhance its versatility.


2013 ◽  
Vol 1 (6) ◽  
pp. 6785-6828 ◽  
Author(s):  
D. Lawrence ◽  
E. Paquet ◽  
J. Gailhard ◽  
A. K. Fleig

Abstract. Simulation methods for extreme flood estimation represent an important complement to statistical flood frequency analysis because a spectrum of catchment conditions potentially leading to extreme flows can be assessed. In this paper, stochastic, semi-continuous simulation is used to estimate extreme floods in three catchments located in Norway, all of which are characterised by flood regimes in which snowmelt often has a significant role. The simulations are based on SCHADEX, which couples a precipitation probabilistic model with a hydrological simulation such that an exhaustive set of catchment conditions and responses are simulated. The precipitation probabilistic model is conditioned by regional weather patterns, and a "bottom-up" classification procedure was used for defining a set of weather patterns producing extreme precipitation in Norway. SCHADEX estimates for the 1000 yr (Q1000) discharge are compared with those of several standard methods, including event-based and long-term simulations which use a single extreme precipitation sequence as input to a hydrological model, with statistical flood frequency analysis based on the annual maximum series, and with the GRADEX method. The comparison suggests that the combination of a precipitation probabilistic model with a long-term simulation of catchment conditions, including snowmelt, produces estimates for given return periods which are more in line with those based on statistical flood frequency analysis, as compared with the standard simulation methods, in two of the catchments. In the third case, the SCHADEX method gives higher estimates than statistical flood frequency analysis and further suggests that the seasonality of the most likely Q1000 events differs from that of the annual maximum flows. The semi-continuous stochastic simulation method highlights the importance of considering the joint probability of extreme precipitation, snowmelt rates and catchment saturation states when assigning return periods to floods estimated by precipitation-runoff methods. The SCHADEX methodology, as applied here, is dependent on observed discharge data for calibration of a hydrological model, and further study to extend its application to ungauged catchments would significantly enhance its versatility.


2014 ◽  
Vol 14 (2) ◽  
pp. 295-308 ◽  
Author(s):  
K. Kochanek ◽  
B. Renard ◽  
P. Arnaud ◽  
Y. Aubert ◽  
M. Lang ◽  
...  

Abstract. Flood frequency analysis (FFA) aims at estimating quantiles with large return periods for an extreme discharge variable. Many FFA implementations are used in operational practice in France. These implementations range from the estimation of a pre-specified distribution to continuous simulation approaches using a rainfall simulator coupled with a rainfall–runoff model. This diversity of approaches raises questions regarding the limits of each implementation and calls for a nation-wide comparison of their predictive performances. This paper presents the results of a national comparison of the main FFA implementations used in France. More accurately, eight implementations are considered, corresponding to the local, regional and local-regional estimation of Gumbel and Generalized Extreme Value (GEV) distributions, as well as the local and regional versions of a continuous simulation approach. A data-based comparison framework is applied to these eight competitors to evaluate their predictive performances in terms of reliability and stability, using daily flow data from more than 1000 gauging stations in France. Results from this comparative exercise suggest that two implementations dominate their competitors in terms of predictive performances, namely the local version of the continuous simulation approach and the local-regional estimation of a GEV distribution. More specific conclusions include the following: (i) the Gumbel distribution is not suitable for Mediterranean catchments, since this distribution demonstrably leads to an underestimation of flood quantiles; (ii) the local estimation of a GEV distribution is not recommended, because the difficulty in estimating the shape parameter results in frequent predictive failures; (iii) all the purely regional implementations evaluated in this study displayed a quite poor reliability, suggesting that prediction in completely ungauged catchments remains a challenge.


2013 ◽  
Vol 1 (5) ◽  
pp. 4445-4479 ◽  
Author(s):  
K. Kochanek ◽  
B. Renard ◽  
P. Arnaud ◽  
Y. Aubert ◽  
M. Lang ◽  
...  

Abstract. Many flood frequency analysis (FFA) implementations are used in operational practice in France. These implementations range from the estimation of a pre-specified distribution to continuous simulation approaches using a rainfall simulator coupled with a rainfall-runoff model. This diversity of approaches raises questions regarding the optimal ambits of each implementation and calls for a nation-wide comparison of their predictive performances. This paper presents the results of a national comparison of the main FFA implementations used in France. More accurately, eight implementations are considered, corresponding to the local, regional and local-regional estimation of Gumbel and Generalized Extreme Value (GEV) distributions, as well as the local and regional estimation of a continuous simulation approach eventually resulted in a local and a regional version. A data-based comparison framework is applied to these eight competitors to evaluate their predictive performances in terms of reliability and stability, using daily flow data data from more than one thousand gauging stations in France. Results from this comparative exercise suggest that two implementations dominate their competitors in terms of predictive performances, namely the local version of the continuous simulation approach and the local-regional estimation of a GEV distribution. More specific conclusions include the following: (i) the Gumbel distribution is not suitable for Mediterranean catchments, since this distribution demonstrably leads to an underestimation of flood quantiles; (ii) the local estimation of a GEV distribution is not recommended, because the difficulty in estimating the shape parameter results in frequent predictive failures; (iii) all the purely regional implementations evaluated in this study displayed a quite poor reliability, suggesting that prediction in completely ungauged catchments remains a challenge.


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