scholarly journals Have applications of continuous rainfall-runoff simulation realized the vision for process-based flood frequency analysis?

2016 ◽  
Vol 30 (14) ◽  
pp. 2463-2481 ◽  
Author(s):  
Rob Lamb ◽  
Duncan Faulkner ◽  
Paul Wass ◽  
David Cameron
Keyword(s):  
Frequency Analysis ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Continuous Rainfall

scholarly journals Alternative Approaches to a Calibration of Rainfall- Runoff Models for a Flood Frequency Analysis

2014 ◽  
Vol 10 (2) ◽  
pp. 161-174
Author(s):  
Peter Valent ◽  
Ján Szolgay ◽  
Roman Výleta
Keyword(s):  
Frequency Analysis ◽  
Flood Frequency ◽  
Cumulative Distribution ◽  
Flood Frequency Analysis ◽  
Rainfall Runoff ◽  
Efficiency Criterion ◽  
Empirical Cumulative Distribution Function ◽  
Extreme Flows ◽  
Alternative Approaches ◽  
Calibration Techniques

Abstract One of the tools which are currently being used in flood frequency analysis (FFA) is rainfall-runoff (RR) modelling. Its use in FFA often confronts the problem of how to correctly calibrate RR models to extreme flows. Since FFA only deals with extreme flows, traditional calibration techniques using simple objective functions such as the Nash-Sutcliffe model’s efficiency criterion are not sufficient. In this paper we have focused on proposing alternative approaches for calibration techniques of RR models in order to enhance the description of extreme flows. We have selected the HBV type conceptual, lumped model HRON as an RR model. We have suggested two alternative calibration approaches: 1) the use of a new optimization function that compares only values higher than the 95th percentile of observed flows and 2) using two sets of parameters to separately simulate low and high flows. Each of these improvements has enhanced the simulation of extreme flows, which has been demonstrated in the empirical cumulative distribution function calculated for the simulated and observed annual maximum series of flows. The results of this paper show that improvement can be obtained by both approaches, which give good agreement between observed and simulated extreme flows, while preserving a good simulation of low and medium flows

scholarly journals An integrated simulation method for flash-flood risk assessment: 1. Frequency predictions in the Bisagno River by combining stochastic and deterministic methods

2002 ◽  
Vol 6 (2) ◽  
pp. 267-284 ◽  
Author(s):  
M.C. Rulli ◽  
R. Rosso
Keyword(s):  
River Basin ◽  
Frequency Analysis ◽  
Extreme Values ◽  
Flash Flood ◽  
Simulation Method ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Rainfall Runoff ◽  
Rainfall Runoff Model ◽  
Runoff Model

Abstract. A stochastic rainfall generator and a deterministic rainfall-runoff model, both distributed in space and time, are combined to provide accurate flood frequency prediction in the Bisagno River basin (Thyrrenian Liguria, N.W. Italy). The inadequacy of streamflow records with respect to the return period of the required flow discharges makes the stochastic simulation methodology a useful operational alternative to a regionalisation procedure for flood frequency analysis and derived distribution techniques. The rainfall generator is the Generalized Neyman-Scott Rectangular Pulses (GNSRP) model. The rainfall-runoff model is the FEST98 model. The GNSRP generator was calibrated using a continuous 7-years' record of hourly precipitation measurements at five raingauges scattered over the Bisagno basin. The calibrated rainfall model was then used to generate a 1000 years' series of continuous rainfall data at the gauging sites and a flood-oriented model validation procedure was developed to evaluate the agreement between observed and simulated extreme values of rainfall at different scales of temporal aggregation. The synthetic precipitation series were input to the FEST98 model to provide flood hydrographs at selected cross-sections across the river network. Flood frequency analysis of the annual flood series (AFS) obtained from these simulations was undertaken using L-moment estimations of Generalized Extreme Value (GEV) distributions. The results are compared with those determined by applying a regional flood analysis in Thyrrhenian Liguria and the derived distribution techniques to the Bisagno river basin. This approach is also useful to assess the effects of changes in land use on flood frequency regime (see Rosso and Rulli, 2002). Keywords: flood frequency, stochastic rainfall generator, distributed rainfall runoff model, derived distribution

scholarly journals Flood Frequency Analysis for the Annual Peak Flows Simulated by an Event-Based Rainfall-Runoff Model in an Urban Drainage Basin

Water ◽  
2014 ◽  
Vol 6 (12) ◽  
pp. 3841-3863 ◽  
Author(s):  
Jeonghwan Ahn ◽  
Woncheol Cho ◽  
Taereem Kim ◽  
Hongjoon Shin ◽  
Jun-Haeng Heo
Keyword(s):  
Frequency Analysis ◽  
Drainage Basin ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Urban Drainage ◽  
Rainfall Runoff ◽  
Annual Peak ◽  
Rainfall Runoff Model ◽  
Event Based ◽  
Runoff Model

scholarly journals Continuous Simulation of Catchment Runoff in Flood Frequency Analysis: A Case Study from Slovakia

Proceedings ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 16
Author(s):  
Peter Valent ◽  
Roman Výleta
Keyword(s):  
Time Series ◽  
Frequency Analysis ◽  
Stochastic Models ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Reliable Estimate ◽  
Return Periods ◽  
Rainfall Runoff ◽  
Weather Generators ◽  
Air Temperatures

Research questions relating to a reliable estimate of flood discharge have always interested both hydrologists and civil engineers. Over the decades, numerous methods have been proposed and used more or less successfully, all of them with known limitations restricting their use in a wide range of conditions and problems. In the past, the characteristics of hydrological extremes were mostly estimated by the methods of statistical analyses. As this type of method is not suitable to estimate design discharges of high return periods, and by default does not account for uncertainty, a new family of methods is slowly taking the place of the traditional approaches. Many of these methods are based on a combination of stochastic rainfall models (weather generators) and rainfall-runoff models, which enables generation of an arbitrary number of synthetic floods, even in places with short or no record of river discharges available. In addition, as this type of method produces flood hydrographs, they can also be used in a multivariate flood frequency analysis to estimate joint probabilities of two or more flood characteristics. This study presents a methodology for flood frequency analysis that combines stochastic models of both rainfall amounts and air temperatures with a lumped rainfall-runoff model to transfer the outputs of the stochastic models into a series of corresponding river discharges. Both of the stochastic models are single-site weather generators that produce continuous time series of mean areal daily rainfall amounts and air temperatures. In this study, the method was used to generate a time series of 10,000 years of mean daily discharges, which was used to build a flood frequency curve and to estimate extreme flood discharges of given return periods. The method was applied to a mountainous catchment of the River Váh in Slovakia.

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