An Application of a Stochastic Semi-Continuous Simulation Method for Flood Frequency Analysis: A Case Study in Slovakia

Valent, Peter; Paquet, Emmanuel

doi:10.1515/sjce-2017-0016

Cited by 2 publications

(1 citation statement)

References 60 publications

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“…-15.9.2002) with the help of a genetic algorithm (GA) using the Nash Sutcliffe criterion. This calibration procedure based on a genetic algorithm was used in several hydrology studies, e.g., Sleziak et al, (2016); Valent and Paquet (2017); Sleziak et al, (2018). Similarly, as in Baláž et al, (2010), for practical reasons, we constrained the search space from above and below by the maximum K of 100000s and minimal K of 2000s from the previous calibration exercise (see Tab.…”

Section: Parametrisation Of the Multilinear Muskingum Model By The Trmentioning

confidence: 99%

Variable Parameter Multilinear Muskingum Method: Case Study on the Danube River

Danáčová

Szolgay

2018

Slovak Journal of Civil Engineering

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The Muskingum method is based on a linear relationship between a channel’s storage and inflow and outflow discharges. The applicability of using travel-time discharge relationships to model the variability of the K parameter in a Muskingum routing model was tested. The new parameter estimation method is based on the relationships between the traveltime parameter (K) and the input discharge for the reach of the Danube River between Devín-Bratislava and Medveďov, which includes the Gabčíkovo hydropower scheme. The variable parametrisation method was compared with the classical approach. The parameter X was taken as the average of its values from a small set of flood waves, K was estimated as a function of the travel-time parameter and discharge, which was optimized for one flood wave. The results were validated using the Nash-Sutcliffe coefficient on 5 floods. The results obtained by these methods were satisfactory and, with their use, one could reduce the amount of data required for calibration in practical applications.

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Section: Parametrisation Of the Multilinear Muskingum Model By The Trmentioning

confidence: 99%

Variable Parameter Multilinear Muskingum Method: Case Study on the Danube River

Danáčová

Szolgay

2018

Slovak Journal of Civil Engineering

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A hydro-climatic approach for extreme flood estimation in mountainous catchments

Bashirgonbad,

Moghaddam Nia,

Khalighi-Sigaroodi

et al. 2024

Appl Water Sci

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Prediction of rainfall-runoff process, peak discharges, and finally flood hydrograph is essential for flood risk management and river engineering projects. In most previous studies in this field, the precipitation rates have been entered into the models without considering seasonal and monthly distribution. In this study, the daily precipitation data of 144 climatology stations in Iran were used to evaluate the seasonal and monthly pattern of flood-causing precipitation. Then, by determining the rainy seasons and seasonal fit of precipitation with a probabilistic model and using regional precipitation, a semi-distributed conceptual model of rainfall-runoff (MORDOR-SD) was trained and validated using the observed discharge data. Flood prediction was performed using climatic data, modeling of hydrological conditions, and extreme flow data with high performance. According to the results, the Nash–Sutcliffe and Kling–Gupta coefficients were 0.69 and 0.82 for the mean daily streamflow, 0.98 and 0.98 for the seasonal streamflow, 0.98 and 0.94 for the maximum discharges, and 0.57 and 0.78 for low flows, respectively. Moreover, the maximum daily discharges in different return periods were estimated using the results of the MORDOR-SD model, considering the probability distribution function of the probabilistic model of central precipitation (MEWP), the probabilistic model of adjacent precipitation, and probability distribution function of the previous precipitation. Finally, the extreme flows were predicted and compared using different methods including the SCHADEX, regional flood analysis, GRADEX, and AGREGEE. The results showed that the methods GRADEX, AGREGEE, and SCHADEX have the highest performance in predicting extreme floods, respectively.

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An Application of a Stochastic Semi-Continuous Simulation Method for Flood Frequency Analysis: A Case Study in Slovakia

Abstract: A reliable estimate of extreme flood characteristics has always been an active topic in hydrological research. Over the decades a large number of approaches and their modifications

Cited by 2 publications

References 60 publications

Variable Parameter Multilinear Muskingum Method: Case Study on the Danube River

Variable Parameter Multilinear Muskingum Method: Case Study on the Danube River

A hydro-climatic approach for extreme flood estimation in mountainous catchments

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