Flood frequency analysis and generation of flood hazard indicator maps in a semi-arid environment, case of Ourika watershed (western High Atlas, Morocco)

2018 ◽  
Vol 141 ◽  
pp. 94-106 ◽  
Author(s):  
Abdelhafid El Alaoui El Fels ◽  
Noureddine Alaa ◽  
Ali Bachnou ◽  
Said Rachidi
Keyword(s):  
Frequency Analysis ◽  
Flood Hazard ◽  
Arid Environment ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
High Atlas ◽  
Ourika Watershed ◽  
Semi Arid

Application of Gumbel’s Distribution Method for Flood Frequency Analysis of Lower Ganga Basin (Farakka Barrage Station), West Bengal, India

2021 ◽  
pp. 51-58
Author(s):  
Kajal Kumar Mandal ◽  
K. Dharanirajan ◽  
Sabyasachi Sarkar
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Flood Hazard ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Ganga Basin ◽  
Distribution Method ◽  
Discharge Data ◽  
Gumbel’S Distribution ◽  
Farakka Barrage

The analysis of flood frequency will depend on the historical peak discharge data for at least 10 years. This study has taken into account peak annual maximum discharge data for 72 years (1949 to 2020). The discharge data was collected from the Farakka Barrage Gauging station (24°48'15.10" N and 87°55'52.70" E) situated in the upper part of lower Ganga basin. The flood frequency analysis of the lower Ganga basin’s upper portions has been carried out using Gumbel’s frequency distribution method. Gumbel’s method (XT) is a prediction analysing statistical approach. The discharge data was tabulated in descending order and rank has been assigned based on the discharge volume. The return period was calculated based on Weibull’s formula (P) for this analysis. The flood frequency data was plotted on a graph where X-axis shows the return period and the Yaxis is the discharge value. The R2 value of this graph is 0.9998 which describe Gumbel’s distribution method is best for the flood frequency analysis. The flood frequency analysis is an essential step to assess the flood hazard.

scholarly journals Probabilistic Flood Hazard Maps from Monte Carlo Derived Peak Flow Values—An Application to Flood Risk Management in Zamora City (Spain)

2021 ◽  
Vol 11 (14) ◽  
pp. 6629
Author(s):  
Julio Garrote ◽  
Evelyng Peña ◽  
Andrés Díez-Herrero
Keyword(s):  
Risk Management ◽  
Monte Carlo ◽  
Frequency Analysis ◽  
Peak Flow ◽  
Flood Hazard ◽  
Flood Risk Management ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Hazard Maps ◽  
Flood Hazard Maps

All flood hazard and risk assessment suffer from a certain degree of uncertainty due to multiple factors, such as flood frequency analysis, hydrodynamic model calibration, or flood damage (magnitude–damage functions) models. The uncertainty linked to the flood frequency analysis is one of the most important factors (previous and present estimation point to 40%). Flood frequency analysis uncertainty has been approached from different points of view, such as the application of complex statistical models, the regionalization processes of peak flows, or the inclusion of non-systematic data. Here, we present an achievable approach to defining the uncertainty linked to flood frequency analysis by using the Monte Carlo method. Using the city of Zamora as the study site, the uncertainty is delimited by confidence intervals of a peak flow quantile of a 500-year return period. Probabilistic maps are derived from hydrodynamic results, and further analysis include flood hazard maps for human loss of stability and vehicle damage. Although the effect of this uncertainty is conditioned by the shape of the terrain, the results obtained may allow managers to achieve more consistent land-use planning. All those Zamora city results point out the probable underestimation of flood hazard (the higher hazard areas increase around 20%) and risk when the uncertainty analysis is not considered, thus limiting the efficiency of flood risk management tasks.

scholarly journals Flood Hazard Estimation under Nonstationarity Using the Particle Filter

Geosciences ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 13
Author(s):  
Cuauhtémoc Tonatiuh Vidrio-Sahagún ◽  
Jianxun He
Keyword(s):  
Particle Filter ◽  
Frequency Analysis ◽  
Flood Hazard ◽  
Flood Frequency ◽  
Mitigation Measures ◽  
Flood Frequency Analysis ◽  
Flood Hazards ◽  
Point Estimates ◽  
Infrastructure Design ◽  
Hazard Estimation

The presence of the nonstationarity in flow datasets has challenged the flood hazard assessment. Nonstationary tools and evaluation metrics have been proposed to deal with the nonstationarity and guide the infrastructure design and mitigation measures. To date, the examination of how the flood hazards are affected by the nonstationarity is still very limited. This paper thus examined the association between the flood hazards and the nonstationary patterns and degrees of the underlying datasets. The Particle Filter, which allows for assessing the uncertainty of the point estimates, was adopted to conduct the nonstationary flood frequency analysis (NS-FFA) for subsequently estimating the flood hazards in three real study cases. The results suggested that the optimal and top NS-FFA models selected according to the fitting efficiency in general align with the pattern of nonstationarity, although they might not always be superior in terms of uncertainty. Moreover, the results demonstrated the association and the sensitivity of the flood hazards to the perceived patterns and degrees of nonstationarity. In particular, the variations of the flood hazards intensified with the increase in the degree of nonstationarity, which should be assessed in a more elaborate manner, i.e., considering multiple statistical moments. These advocate the potential of using the nonstationarity characteristics as a proxy for evaluating the evolutions of the flood hazards.

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