Analysis of Gauging Station Flood Frequency Estimates in Nebraska Using L-Moments and Region of Influence Methods

1998 ◽  
Vol 1647 (1) ◽  
pp. 53-60 ◽  
Author(s):  
Mary Kay Provaznik ◽  
Rollin H. Hotchkiss
Keyword(s):  
Statistical Tests ◽  
Extreme Value Distribution ◽  
Flood Frequency ◽  
Generalized Extreme Value Distribution ◽  
Potential Region ◽  
Unique Region ◽  
Extreme Flood ◽  
Flood Magnitude ◽  
L Moments ◽  
The Impact

Recent advances in predicting flood magnitude and frequency at streamgauging stations are illustrated using stream flow data from Nebraska. Prediction methods were based on statistical techniques referred to as L-moments and the region of influence method (ROI). L-moments are less sensitive to extremely high or low floods than current procedures and may provide more stable estimates of flood frequency. The ROI method for predicting flood frequency does not depend on fixed hydrologic regions but uses information from all appropriate gauges in the state to form a unique region and frequency estimate for each site. Estimates of the 100-year flood using current procedures showed statistically significant differences from estimates made using a generalized extreme value distribution with L-moments. Differences were due to the treatment of extreme flood events and illustrate the robust character of L-moments. L-moments were less sensitive to extreme floods as expected. Creating regions using the ROI method was found to be sensitive to the selection of basin attributes for assembling sites, but was not sensitive to the number of gauges initially used to create a region, nor the criterion used to eliminate a gauge from a potential region. Statistical tests revealed insignificant differences between ROI estimates of the 100-year flood when compared with estimates using current procedures. The similarity in estimates is attributed to current “filtering” procedures used that reduce the impact of extreme events. The ROI method is viewed as a more objective method of achieving the same result.

Performance of L-moments and nonparametric flood frequency analysis

1994 ◽  
Vol 21 (5) ◽  
pp. 856-862 ◽  
Author(s):  
Denis Gingras ◽  
Kaz Adamowski
Keyword(s):  
Frequency Analysis ◽  
Extreme Value Distribution ◽  
Nonparametric Methods ◽  
Extreme Value ◽  
Flood Frequency ◽  
Value Distribution ◽  
Generalized Extreme Value Distribution ◽  
Flood Frequency Analysis ◽  
Generalized Extreme Value ◽  
L Moments

A simulation study was undertaken to compare parametric L-moments and nonparametric approaches in flood frequency analysis. Data of various sample lengths were generated from a given generalized extreme value distribution and the quantiles estimated using the fixed-kernel nonparametric method and from a generalized extreme value distribution fitted by L-moments. From the resulting root-mean-square errors for various quantiles, it was concluded for unimodal distributions that nonparametric methods are preferable for large return period floods estimated from short (<30 years) samples while parametric methods are preferable in other circumstances. It was also pointed out that nonparametric methods are more suitable for mixed distributions. Key words: frequency analysis, L-moments, nonparametric methods, simulation.

Does development reduce fatalities from natural disasters? New evidence for floods

2013 ◽  
Vol 18 (6) ◽  
pp. 649-679 ◽  
Author(s):  
Susana Ferreira ◽  
Kirk Hamilton ◽  
Jeffrey R. Vincent
Keyword(s):  
Natural Disasters ◽  
Flood Frequency ◽  
Lower Income ◽  
Flood Events ◽  
Data Set ◽  
Flood Magnitude ◽  
Lower Income Countries ◽  
The Impact ◽  
New Evidence ◽  
Large Floods

AbstractWe analyze the impact of development on flood fatalities using a new data set of 2,171 large floods in 92 countries between 1985 and 2008. Our results challenge the conventional wisdom that development results in fewer fatalities during natural disasters. Results indicating that higher income and better governance reduce fatalities during flood events do not hold up when unobserved country heterogeneity and within-country correlation of standard errors are taken into account. We find that income does have a significant, indirect effect on flood fatalities by affecting flood frequency and flood magnitude, but this effect is nonmonotonic, with net reductions in fatalities occurring only in lower income countries. We find little evidence that improved governance affects flood fatalities either directly or indirectly.

scholarly journals Trends in floods in West Africa: analysis based on 11 catchments in the region

2015 ◽  
Vol 19 (11) ◽  
pp. 4707-4719 ◽  
Author(s):  
B. N. Nka ◽  
L. Oudin ◽  
H. Karambiri ◽  
J. E. Paturel ◽  
P. Ribstein
Keyword(s):  
Time Series ◽  
West Africa ◽  
Vegetation Indices ◽  
Contingency Tables ◽  
Flood Frequency ◽  
Trend Test ◽  
African Countries ◽  
Rainfall Index ◽  
Flood Magnitude ◽  
The Impact

Abstract. After the drought of the 1970s in West Africa, the variability in rainfall and land use changes mostly affected flow, and recently flooding has been said to be an increasingly common occurrence throughout the whole of West Africa. These changes have raised many questions about the impact of climate change on the flood regimes in West African countries. This paper investigates whether floods are becoming more frequent or more severe and to what extent climate patterns have been responsible for these changes. We analyzed the trends in the floods occurring in 11 catchments within West Africa's main climate zones. The methodology includes two methods for sampling flood events, namely the AM (annual maximum) method and the POT (peak over threshold), and two perspectives of analysis are presented: long-term analysis based on two long flood time series and a regional perspective involving 11 catchments with shorter series. The Mann–Kendall trend test and the Pettitt break test were used to detect nonstationarities in the time series. The trends detected in flood time series were compared to the rainfall index trends and vegetation indices using contingency tables in order to identify the main driver of change in flood magnitude and flood frequency. The relation between the flood index and the physiographic index was evaluated through a success criterion and the Cramer criterion calculated from the contingency tables. The results show the existence of trends in flood magnitude and flood frequency time series, with two main patterns. Sahelian floods show increasing flood trends and one Sudanian. catchment presents decreasing flood trends. For the overall catchments studied, trends in the maximum 5-day consecutive rainfall index (R5d) show good coherence with trends in flood, while the trends in normalized difference vegetation indices (NDVIs) do not show a significant agreement with flood trends, meaning that this index has possibly no impact on the behavior of floods in the region.

The value of regional information to flood frequency analysis using the method of L-moments

1992 ◽  
Vol 19 (1) ◽  
pp. 137-147 ◽  
Author(s):  
Paul J. Pilon ◽  
K. Adamowski
Keyword(s):  
Nova Scotia ◽  
Frequency Analysis ◽  
Sampling Error ◽  
Extreme Value ◽  
Flood Frequency ◽  
Generalized Extreme Value Distribution ◽  
Flood Frequency Analysis ◽  
Generalized Extreme Value ◽  
Regional Flood Frequency Analysis ◽  
L Moments

The value of regional flood frequency analysis is investigated using the method of L-moments. This study shows that the variability of L-skewness in the province of Nova Scotia is due in large part to sampling error. This implies that a relation between the L-skewness and the basin's characteristics cannot be determined. This study demonstrates that flood data in Nova Scotia can best be described by the generalized extreme value (GEV) distribution. The results also indicate that the regional GEV model is more accurate than the single site analysis. Key words: L-moments, skewness, regional flood analysis, generalized extreme value distribution, simulation.

Exploring Uncertainties in Flood Frequency Analysis Using Bayesian MCMC Method

2013 ◽  
Vol 663 ◽  
pp. 768-772
Author(s):  
Li Jie Zhang
Keyword(s):  
Frequency Analysis ◽  
Extreme Value Distribution ◽  
Flood Frequency ◽  
Generalized Extreme Value Distribution ◽  
Flood Frequency Analysis ◽  
Distribution Model ◽  
Mcmc Method ◽  
Design Flood ◽  
Pearson Type ◽  
Flood Estimation

The evaluation and reducing of uncertainty is central to the task of hydrological frequency analysis. In this paper a Bayesian Markov Chain Monte Carlo (MCMC) method is employed to infer the parameter values of the probabilistic distribution model and evalue the uncertainties of design flood. Comparison to the estimated results of three-parameter log-normal distribution (LN3) and the three-parameter generalized extreme value distribution (GEV), the Pearson Type 3 distribution (PIII) provides a good approximation to flood-flow data. The choice of the appropriate probabilistic model can reduce uncertainty of design flood estimation. Historical flood events might be greatly reduced uncertainty when incorporating past extreme historical data into the flood frequency analysis.

scholarly journals Theoretical investigation of process controls upon flood frequency: role of thresholds

2006 ◽  
Vol 3 (5) ◽  
pp. 3279-3319 ◽  
Author(s):  
I. Struthers ◽  
M. Sivapalan
Keyword(s):  
Field Capacity ◽  
Relative Strength ◽  
Flood Frequency ◽  
Generation Process ◽  
Rainfall Runoff ◽  
Frequency Curve ◽  
Rainfall Frequency ◽  
Extreme Flood ◽  
The Impact ◽  
Process Controls

Abstract. Traditional statistical approaches to flood frequency inherently assume homogeneity and stationarity in the flood generation process. This study illustrates the impact of heterogeneity associated with threshold non-linearities in the storage-discharge relationship associated with the rainfall-runoff process upon flood frequency behaviour. For a simplified, non-threshold (i.e. homogeneous) scenario, flood frequency can be characterised in terms of rainfall frequency, the characteristic response time of the catchment, and storm intermittency, modified by the relative strength of evaporation. The flood frequency curve is then a consistent transformation of the rainfall frequency curve, and could be readily described by traditional statistical methods. The introduction of storage thresholds, namely a field capacity storage and a catchment storage capacity, however, results in different flood frequency "regions" associated with distinctly different rainfall-runoff response behaviour and different process controls. The return period associated with the transition between these regions is directly related to the frequency of threshold exceedence. Where threshold exceedence is relatively rare, statistical extrapolation of flood frequency on the basis of short historical flood records risks ignoring this heterogeneity, and therefore significantly underestimating the magnitude of extreme flood peaks.

scholarly journals Examination for robustness of parametric estimators for flood statistics in the context of extraordinary extreme events

2015 ◽  
Vol 12 (8) ◽  
pp. 8553-8576
Author(s):  
S. Fischer ◽  
R. Fried ◽  
A. Schumann
Keyword(s):  
Maximum Likelihood ◽  
Robust Estimation ◽  
Extreme Events ◽  
Extreme Value Distribution ◽  
Generalized Extreme Value Distribution ◽  
Likelihood Estimator ◽  
Statistical Measures ◽  
L Moments ◽  
Minimum Distances ◽  
Parametric Fitting

Abstract. We compare several estimators, which are commonly used in hydrology, for the parameters of the distribution of flood series, like the Maximum-Likelihood estimator or L-Moments, with the robust estimators Trimmed L-Moments and Minimum Distances. Our objective is estimation of the 99 %- or 99.9 %-quantile of an underlying Gumbel or Generalized Extreme Value distribution (GEV), where we modify the generated random variables such that extraordinary extreme events occur. The results for a two- or three-parametric fitting are compared and the robustness of the estimators to the occurrence of extraordinary extreme events is investigated by statistical measures. When extraordinary extreme events are known to appear in the sample, the Trimmed L-Moments are a recommendable choice for a robust estimation. They even perform rather well, if there are no such events.

scholarly journals Trends in West African floods: a comparative analysis with rainfall and vegetation indices

2015 ◽  
Vol 12 (5) ◽  
pp. 5083-5121 ◽  
Author(s):  
B. N. Nka ◽  
L. Oudin ◽  
H. Karambiri ◽  
J. E. Paturel ◽  
P. Ribstein
Keyword(s):  
Time Series ◽  
West Africa ◽  
Vegetation Indices ◽  
Contingency Tables ◽  
Flood Frequency ◽  
West African ◽  
Trend Test ◽  
Rainfall Index ◽  
Flood Magnitude ◽  
The Impact

Abstract. After the drought of the 1970s in West Africa, the variability of rainfall and land use changes affected mostly flow, and recently flooding has been said to be an increasingly common occurrence throughout the whole of West Africa. These changes raised many questions about the impact of climate change on the flood regimes in West African countries. This paper investigates whether floods are becoming more frequent or more severe, and to what extent climate patterns have been responsible for these changes. We analyzed the trends in the floods occurring in 14 catchments within West Africa's main climate zone. The methodology includes two methods for sampling flood events, namely the AM (annual maximum) method and the POT (peak over threshold), and two perspectives of analysis are presented: long-term analysis based on two long flood time series, and a regional perspective involving 14 catchments with shorter series. The Mann–Kendall trend test and the Pettitt break test were used to assess time series stationarity. The trends detected in flood time series were compared to the rainfall index trends and vegetation indices using contingency tables, in order to identify the main driver of change in flood magnitude and flood frequency. The relation between the flood index and the physiographic index was evaluated through a success criterion and the Cramer criterion calculated from the contingency tables. The results point out the existence of trends in flood magnitude and flood frequency time series with two main patterns. Sahelian floods show increasing flood trends and some Sudanian catchments present decreasing flood trends. For the overall catchments studied, the maximum 5 day consecutive rainfall index (Rx5d) seems to follow the flood trend, while the NDVI indices do not show a significant link with the flood trends, meaning that this index has no impact in the behavior of floods in the region.

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