scholarly journals Flood frequency analysis of historical flood data under stationary and non-stationary modelling

2015 ◽  
Vol 12 (1) ◽  
pp. 525-568 ◽  
Author(s):  
M. J. Machado ◽  
B. A. Botero ◽  
J. López ◽  
F. Francés ◽  
A. Díez-Herrero ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Flood Frequency ◽  
City Council ◽  
Additive Models ◽  
Water Levels ◽  
Flood Frequency Analysis ◽  
Environmental Drivers ◽  
Exceedance Probability ◽  
Nao Index ◽  
Flood Magnitude

Abstract. Historical records are an important source of information about extreme and rare floods with a great value to establish a reliable flood return frequency. The use of long historic records for flood frequency analysis brings in the question of flood stationarity, since climatic and land-use conditions can affect the relevance of past flooding as a predictor of future flooding. In this paper, a detailed 400 year flood record from the Tagus River in Aranjuez (Central Spain) was analysed under stationary and non-stationary flood frequency approaches, to assess their implications on hazard studies. Historical flood records in Aranjuez were obtained from documents (Proceedings of the City Council, diaries, chronicles, memoirs, etc.), epigraphic marks, and indirect historical sources and reports. The water levels associated with different floods (derived from descriptions or epigraphic marks) were computed into discharge values using a one-dimensional hydraulic model. Secular variations on flood magnitude and frequency, found to respond to climate and environmental drivers, showed a good correlation between high values of historical flood discharges and a negative mode of the North Atlantic Oscillation index (NAO index). Over the systematic gauge record (1913–2008), an abrupt change on flood magnitude was produced in 1957 due to constructions of three major reservoirs in the Tagus headwaters (Bolarque, Entrepeñas and Buendia) controlling 80% of the watershed surface draining to Aranjuez. Two different models were used for the flood frequency analysis: (a) a stationary model estimating statistical distributions incorporating imprecise and categorical data based on maximum likelihood estimators; (b) a time–varying model based on "generalized additive models for location, scale and shape" (GAMLSS) modelling, that incorporates external covariates related to climate variability (NAO index) and catchment hydrology factors (in this paper a reservoir index; RI). Flood frequency analysis using documentary data (plus gauged record) improved the estimates of the probabilities of rare floods (return intervals of 100 year and higher). Under non-stationary modelling flood occurrence associated with an exceedance probability of 0.01 (i.e. return period of 100 year) has changed over the last 500 year due to decadal and multi-decadal variability of the NAO. Yet, frequency analysis under stationary models was successful on providing an average discharge around which value flood quantiles estimated by non-stationary models fluctuate through time.

scholarly journals Flood frequency analysis of historical flood data under stationary and non-stationary modelling

2015 ◽  
Vol 19 (6) ◽  
pp. 2561-2576 ◽  
Author(s):  
M. J. Machado ◽  
B. A. Botero ◽  
J. López ◽  
F. Francés ◽  
A. Díez-Herrero ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Flood Frequency ◽  
City Council ◽  
Additive Models ◽  
Water Levels ◽  
Flood Frequency Analysis ◽  
Environmental Drivers ◽  
Historical Records ◽  
Nao Index ◽  
Flood Magnitude

Abstract. Historical records are an important source of information on extreme and rare floods and fundamental to establish a reliable flood return frequency. The use of long historical records for flood frequency analysis brings in the question of flood stationarity, since climatic and land-use conditions can affect the relevance of past flooding as a predictor of future flooding. In this paper, a detailed 400 yr flood record from the Tagus River in Aranjuez (central Spain) was analysed under stationary and non-stationary flood frequency approaches, to assess their contribution within hazard studies. Historical flood records in Aranjuez were obtained from documents (Proceedings of the City Council, diaries, chronicles, memoirs, etc.), epigraphic marks, and indirect historical sources and reports. The water levels associated with different floods (derived from descriptions or epigraphic marks) were computed into discharge values using a one-dimensional hydraulic model. Secular variations in flood magnitude and frequency, found to respond to climate and environmental drivers, showed a good correlation between high values of historical flood discharges and a negative mode of the North Atlantic Oscillation (NAO) index. Over the systematic gauge record (1913–2008), an abrupt change on flood magnitude was produced in 1957 due to constructions of three major reservoirs in the Tagus headwaters (Bolarque, Entrepeñas and Buendia) controlling 80% of the watershed surface draining to Aranjuez. Two different models were used for the flood frequency analysis: (a) a stationary model estimating statistical distributions incorporating imprecise and categorical data based on maximum likelihood estimators, and (b) a time-varying model based on "generalized additive models for location, scale and shape" (GAMLSS) modelling, which incorporates external covariates related to climate variability (NAO index) and catchment hydrology factors (in this paper a reservoir index; RI). Flood frequency analysis using documentary data (plus gauged records) improved the estimates of the probabilities of rare floods (return intervals of 100 yr and higher). Under non-stationary modelling flood occurrence associated with an exceedance probability of 0.01 (i.e. return period of 100 yr) has changed over the last 500 yr due to decadal and multi-decadal variability of the NAO. Yet, frequency analysis under stationary models was successful in providing an average discharge around which value flood quantiles estimated by non-stationary models fluctuate through time.

scholarly journals Non-stationary flood frequency analysis in continental Spanish rivers, using climate and reservoir indices as external covariates

2013 ◽  
Vol 17 (8) ◽  
pp. 3189-3203 ◽  
Author(s):  
J. López ◽  
F. Francés
Keyword(s):  
Frequency Analysis ◽  
Western Mediterranean ◽  
Flood Frequency ◽  
Additive Models ◽  
Stationary Time Series ◽  
Flood Frequency Analysis ◽  
Climate Indices ◽  
Flood Regime ◽  
Mediterranean Oscillation ◽  
The Impact

Abstract. Recent evidences of the impact of persistent modes of regional climate variability, coupled with the intensification of human activities, have led hydrologists to study flood regime without applying the hypothesis of stationarity. In this study, a framework for flood frequency analysis is developed on the basis of a tool that enables us to address the modelling of non-stationary time series, namely, the "generalized additive models for location, scale and shape" (GAMLSS). Two approaches to non-stationary modelling in GAMLSS were applied to the annual maximum flood records of 20 continental Spanish rivers. The results of the first approach, in which the parameters of the selected distributions were modelled as a function of time only, show the presence of clear non-stationarities in the flood regime. In a second approach, the parameters of the flood distributions are modelled as functions of climate indices (Arctic Oscillation, North Atlantic Oscillation, Mediterranean Oscillation and the Western Mediterranean Oscillation) and a reservoir index that is proposed in this paper. The results when incorporating external covariates in the study highlight the important role of interannual variability in low-frequency climate forcings when modelling the flood regime in continental Spanish rivers. Also, with this approach it is possible to properly introduce the impact on the flood regime of intensified reservoir regulation strategies. The inclusion of external covariates permits the use of these models as predictive tools. Finally, the application of non-stationary analysis shows that the differences between the non-stationary quantiles and their stationary equivalents may be important over long periods of time.

scholarly journals Non-stationary flood frequency analysis in continental Spanish rivers, using climate and reservoir indices as external covariates

2013 ◽  
Vol 10 (3) ◽  
pp. 3103-3142 ◽  
Author(s):  
J. López ◽  
F. Francés
Keyword(s):  
Frequency Analysis ◽  
Western Mediterranean ◽  
Flood Frequency ◽  
Additive Models ◽  
Stationary Time Series ◽  
Flood Frequency Analysis ◽  
Climate Indices ◽  
Flood Regime ◽  
Mediterranean Oscillation ◽  
The Impact

Abstract. Recent evidences of the impact of persistent modes of regional climate variability, coupled with the intensification of human activities, have led hydrologists to study flood regime without applying the hypothesis of stationarity. In this study, a framework for flood frequency analysis is developed on the basis of a tool that enables us to address the modelling of non-stationary time series, namely, the "generalized additive models for location, scale and shape" (GAMLSS). Two approaches to non-stationary modelling in GAMLSS were applied to the annual maximum flood records of 20 continental Spanish rivers. The results of the first approach, in which the parameters of the selected distributions were modeled as a function of time only, show the presence of clear non-stationarities in the flood regime. In a second approach, the parameters of the distributions are modeled as functions of climate indices (Arctic Oscillation, North Atlantic Oscillation, Mediterranean Oscillation and the Western Mediterranean Oscillation) and a reservoir index that is proposed in this paper. The results when incorporating external covariates in the study highlight the important role of interannual variability in low-frequency climate forcings when modelling the flood regime in continental Spanish rivers. Also, with this approach is possible to properly introduce the impact on the flood regime of intensified reservoir regulation strategies and to be used as predictive tools. Application of non-stationary analysis shows that the differences between the quantiles obtained and their stationary equivalents may be important over long periods of time.

scholarly journals Flood frequency analysis for annual maximum streamflow using a non-stationary GEV model

2019 ◽  
Vol 79 ◽  
pp. 03022
Author(s):  
Shangwen Jiang ◽  
Ling Kang
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Yangtze River ◽  
Flood Frequency ◽  
Additive Models ◽  
Flood Frequency Analysis ◽  
Annual Maximum ◽  
The Yangtze River ◽  
Stationary Model ◽  
Risk Of Failure

Under changing environment, the streamflow series in the Yangtze River have undergone great changes and it has raised widespread concerns. In this study, the annual maximum flow (AMF) series at the Yichang station were used for flood frequency analysis, in which a time varying model was constructed to account for non-stationarity. The generalized extreme value (GEV) distribution was adopted to fit the AMF series, and the Generalized Additive Models for Location, Scale and Shape (GAMLSS) framework was applied for parameter estimation. The non-stationary return period and risk of failure were calculated and compared for flood risk assessment between stationary and non-stationary models. The results demonstrated that the flow regime at the Yichang station has changed over time and a decreasing trend was detected in the AMF series. The design flood peak given a return period decreased in the non-stationary model, and the risk of failure is also smaller given a design life, which indicated a safer flood condition in the future compared with the stationary model. The conclusions in this study may contribute to long-term decision making in the Yangtze River basin under non-stationary conditions.

scholarly journals Frequency Analysis of Snowmelt Flood Based on GAMLSS Model in Manas River Basin, China

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2007
Author(s):  
Chaofei He ◽  
Fulong Chen ◽  
Aihua Long ◽  
Chengyan Luo ◽  
Changlu Qiao
Keyword(s):  
Time Series ◽  
Frequency Analysis ◽  
Flood Frequency ◽  
Additive Models ◽  
Flood Frequency Analysis ◽  
Climate Indices ◽  
Design Flood ◽  
Stationary Model ◽  
Snowmelt Flood ◽  
The Impact

With the acceleration of human economic activities and dramatic changes in climate, the validity of the stationarity assumption of flood time series frequency analysis has been questioned. In this study, a framework for flood frequency analysis is developed on the basis of a tool, namely, the Generalized Additive Models for Location, Scale, and Shape (GAMLSS). We introduced this model to construct a non-stationary model with time and climate factor as covariates for the 50-year snowmelt flood time series in the Kenswat Reservoir control basin of the Manas River. The study shows that there are clear non-stationarities in the flood regime, and the characteristic series of snowmelt flood shows an increasing trend with the passing of time. The parameters of the flood distributions are modelled as functions of climate indices (temperature and rainfall). The physical mechanism was incorporated into the study, and the simulation results are similar to the actual flood conditions, which can better describe the dynamic process of snowmelt flood characteristic series. Compared with the design flood results of Kenswat Reservoir approved by the China Renewable Energy Engineering Institute in December 2008, the design value of the GAMLSS non-stationary model considers that the impact of climate factors create a design risk in dry years by underestimating the risk.

scholarly journals Flood frequency analysis of the Djetinja river

2010 ◽  
Vol 90 (2) ◽  
pp. 15-28 ◽  
Author(s):  
Dragana Milijasevic
Keyword(s):  
Water Resources ◽  
Water Level ◽  
Frequency Analysis ◽  
Drainage Basin ◽  
Flood Frequency ◽  
Water Levels ◽  
Flood Frequency Analysis ◽  
Extreme Water Levels ◽  
High Flows ◽  
Hydrological Forecast

Based on extreme water levels data, using the method of series, a forecast for protection of river has been accomplished, i.e. probable water level maximums of the Djetinja river at Sengolj were measured. High flows were analyzed with a probability from 0.01% to 99.9%. These probabilities indicate the occurrence of high flows of certain values once in 10.000, 1.000, 100, 33, 20 etc years. Applying a hydrological forecast, one can perceive the possibility for using water resources for various purposes, as well as protection of areas and people from flooding. A review of the greatest floods in the Djetinja drainage basin in the last hundred years is given in this paper. .

scholarly journals Assessing the impacts of reservoirs on downstream flood frequency by coupling the effect of scheduling-related multivariate rainfall with an indicator of reservoir effects

2019 ◽  
Vol 23 (11) ◽  
pp. 4453-4470 ◽  
Author(s):  
Bin Xiong ◽  
Lihua Xiong ◽  
Jun Xia ◽  
Chong-Yu Xu ◽  
Cong Jiang ◽  
...  
Keyword(s):  
Bayesian Inference ◽  
Frequency Analysis ◽  
Reservoir Operation ◽  
Storage Capacity ◽  
Flood Frequency ◽  
Return Level ◽  
Flood Frequency Analysis ◽  
Exceedance Probability ◽  
Antecedent Rainfall ◽  
Reservoir Storage

Abstract. Many studies have shown that downstream flood regimes have been significantly altered by upstream reservoir operation. Reservoir effects on the downstream flow regime are normally performed by comparing the pre-dam and post-dam frequencies of certain streamflow indicators, such as floods and droughts. In this study, a rainfall–reservoir composite index (RRCI) is developed to precisely quantify reservoir impacts on downstream flood frequency under a framework of a covariate-based nonstationary flood frequency analysis using the Bayesian inference method. The RRCI is derived from a combination of both a reservoir index (RI) for measuring the effects of reservoir storage capacity and a rainfall index. More precisely, the OR joint (the type of possible joint events based on the OR operator) exceedance probability (OR-JEP) of certain scheduling-related variables selected out of five variables that describe the multiday antecedent rainfall input (MARI) is used to measure the effects of antecedent rainfall on reservoir operation. Then, the RI-dependent or RRCI-dependent distribution parameters and five distributions, the gamma, Weibull, lognormal, Gumbel, and generalized extreme value, are used to analyze the annual maximum daily flow (AMDF) of the Ankang, Huangjiagang, and Huangzhuang gauging stations of the Han River, China. A phenomenon is observed in which although most of the floods that peak downstream of reservoirs have been reduced in magnitude by upstream reservoirs, some relatively large flood events have still occurred, such as at the Huangzhuang station in 1983. The results of nonstationary flood frequency analysis show that, in comparison to the RI, the RRCI that combines both the RI and the OR-JEP resulted in a much better explanation for such phenomena of flood occurrences downstream of reservoirs. A Bayesian inference of the 100-year return level of the AMDF shows that the optimal RRCI-dependent distribution, compared to the RI-dependent one, results in relatively smaller estimated values. However, exceptions exist due to some low OR-JEP values. In addition, it provides a smaller uncertainty range. This study highlights the necessity of including antecedent rainfall effects, in addition to the effects of reservoir storage capacity, on reservoir operation to assess the reservoir effects on downstream flood frequency. This analysis can provide a more comprehensive approach for downstream flood risk management under the impacts of reservoirs.

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