Regional modelling with flood-duration-frequency approach in the middle Cheliff watershed

Renima, Mohamed; Remaoun, Mohamed; Boucefiane, Abdelkader; Abbes, Abdelkader Sadeuk Ben

doi:10.2478/jwld-2018-0013

Cited by 12 publications

(5 citation statements)

References 12 publications

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“…Various authors [2,3] (Remaoun) and (Wischmeier) have examined the processes of this scourge and the methods of the erosion quantification [4,5] ,which indicates that a 30% decrease in the forest multiplies erosion by 5.L'. The specific annual erosion in the Algerian Basin varies between 2000 T/km 2 and 4000 T / km 2 , which makes Algeria one of the most vulnerable countries in the world [6].Many researchers then developed relationships linking solid flow to liquid discharge for some Algerian basins [7,8,9,10].The main objective of our work is to develop a relation allowing to calculate the relation linking the solid and liquid discharge to quantify the solid transport in case of absence of measurement especially during the extreme floods for the watershed of Allala which is controlled at the outlet by the measurement stations of Sidi Akkacha [11].…”

Section: Introductionmentioning

confidence: 99%

Modeling of solid sediment transport in mountain rivers

et al. 2020

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In Algeria, the problems of erosion and sediment transport are critical, since they have the most dramatic consequences of the degradation of agricultural soils on the one hand and the siltation of the dam on the other .The sediment transport in the Algerian basins is very important especially during the periods of floods, It is in this sense that this study, which consists of estimating the sediment transport in suspension and determining the models of relation linking the liquid discharge and the sediment discharge in order to estimate the solid transport in the absence of suspended sediments concentration data at the Sidi Akkacha station at the outlet of the basin of Oued Allala which is subject to a high water erosion, it degrades from one year to the other under the effect of this phenomenon especially during the floods which drain high amounts of fine particles exceeding in general, the concentration of 150 g/l, the results obtained from the application of the models are very encouraging since the correlation between liquid and solid discharge exceeds 80 %.

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Section: Introductionmentioning

confidence: 99%

Modeling of solid sediment transport in mountain rivers

et al. 2020

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“…Renima et al [14]'s research shows that the flood regime modelling is made based on the threshold current quantiles obtained from statistical adjustments that are compared, taking into account the characteristics of the watershed flood regime (QIXA10 and D), with different comparisons. Flow-Duration-Frequency quantile.…”

Section: Discussionmentioning

confidence: 99%

Analysis of Time of Concentration Estimates Using Some Methods and HEC RAS

Biantoro¹,

Wahyudi²,

Ni’am³

2023

cea

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Floods are natural disasters which cause losses that often occur in coastal cities such as Jakarta, Indonesia. Paying attention to rainfall and water flow is in the form of predicting floods. The research goal is to determine the best concentration time method, predict water level and flood inundation, and reduce the impact of flooding for people in the downstream area of the river, Jakarta. The method used in this research is quantitative descriptive analysis, rational approach, time of concentration, artificial neural network (ANN), and the use of the HEC RAS application. The results show that the arrival time of the flood using the Kirpich method shows a concentration time of 12 hours 5 minutes, Travel Time of 12 hours 10 minutes, Velocity of 11 hours 21 minutes and Nakayasu of 9 hours 1 minute. Modelling using an artificial neural network shows that the modelling results can function to predict water levels in the future. The results of the artificial neural network that estimates the water level for the 2020 period are 5.1 m (January), 4.94 m (February), 3.89 m (March), 3.52 m (April), 3.71 m (May), 2.58 m (June), 2.59 m (July), 24.1 m (August), 2.97 m (September), 3.32 m (October), 3.07 m (November) and 3.68 m (December).

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“…In more recent years, the QDF model has been used to characterize flood events of different duration in Algeria (Renima et al, 2018), to inform development of a depth-duration-frequency relationship used to assess risk of rainfall-driven floods in Poland (Markiewicz, 2021) and as a comparison point to IDF models when assessing catchment behavior for runoff extremes in Austria (Breinl et al, 2021). As noted in Breinl et al (2021), the relationship quantified by the QDF model is an analogue to the relationship quantified in IDF modeling for precipitation extremes: in the hypothetical situation where all rainfall becomes runoff and the time of concentration is instantaneous, the QDF and IDF models have identical relationships.…”

Section: Introductionmentioning

confidence: 99%

Flexible flood-duration-frequency modelling: A Bayesian approach

Barna¹,

Barna

Engeland

et al. 2023

Preprint

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Design flood values give estimates of flood magnitude within a given return period and are essential to making adaptive decisions around land use planning, infrastructure design, and disaster mitigation. Many hydrologic applications where flood retention is important, e.g. floodplain management and reservoir design, need design flood values for different durations. Flood-Duration-Frequency (QDF) models extend the standard statistical flood frequency analysis framework to multiple flood durations and are analogous to intensityduration-frequency models for precipitation. Implementations of QDF models commonly assume simple scaling, where only the magnitude of the index flood is assumed to change with duration, despite empirical analyses showing a more complex dependence structure. We propose a multiscaling extension to existing QDF models where the magnitude of the index flood and the slope of the growth curve may scale independently with duration. In an application to 12 locations in Norway, we assess how three different QDF models capture relationships between floods of different duration. Incorporating duration dependency independently in both the index flood and the growth curve improves modeling of both short-duration events and events with long return periods. This model extension further expands the models' ability to simultaneously model a wide range of durations. However, the choice of durations used to fit the QDF model is a highly influential aspect of the modeling process.

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Regional modelling with flood-duration-frequency approach in the middle Cheliff watershed

Cited by 12 publications

References 12 publications

Modeling of solid sediment transport in mountain rivers

Modeling of solid sediment transport in mountain rivers

Analysis of Time of Concentration Estimates Using Some Methods and HEC RAS

Flexible flood-duration-frequency modelling: A Bayesian approach

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