Performances of Rainfall-Runoff Models Calibrated over Single and Continuous Storm Flow Events

Tan, Stephen Boon Kean; Chua, Leok Poh; Shuy, Eng Ban; Lo, Edmond Yat-Man; Lim, Lai Wan

doi:10.1061/(asce)1084-0699(2008)13:7(597)

Cited by 54 publications

(34 citation statements)

References 28 publications

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“…Negative Sr values indicate that the output parameters (runoff depth and peakflow) decrease with increasing input parameters as observed for D imp and N imp . Tan et al (2008) in Singapore also found strong influence of %Imp, W and N imp on peak flow and runoff depth. However, D imp was less important in the Singapore's study because the site was not intensively developed.…”

Section: Sensitivity Analysis Resultsmentioning

confidence: 82%

“…The most widely used urban water quality model is the Storm Water Management Model (SWMM), developed by the Environmental Protection Agency's (EPA). Application and validation of SWMM have been undertaken at different parts of urban catchments around the world (Warwick and Tadepalli 1991;Abustan 1998;Tsihrintzis and Hamid 1998;Barco et al 2008;Temprano et al 2006;Hood et al 2007;Jang et al 2007;Nazahiyah et al 2007;Park et al 2008;Tan et al 2008). However, most of these studies were carried out in the temperate areas which have very different storm characteristic from tropical rainfall.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Modelling runoff quantity and quality in tropical urban catchments using Storm Water Management Model

Fai

Yusop

Toriman

2012

Int. J. Environ. Sci. Technol.

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Due to differences in rainfall regimes and management practices, tropical urban catchments are expected to behave differently from temperate catchments in terms of pollutant sources and their transport mechanism. Storm Water Management Model (SWMM) was applied to simulate runoff quantity (peakflow and runoff depth) and quality (total suspended solids and total phosphorous) in residential, commercial and industrial catchments. For each catchment, the model was calibrated using 8-10 storm events and validated using seven new events. The model performance was evaluated based on the relative error, normalized objective function, Nash-Sutcliffe coefficient and 1:1 plots between the simulated and observed values. The calibration and validation results showed good agreement between simulated and measured data. Application of Storm Water Management Model for predicting runoff quantity has been improved by taking into account catchment's antecedent moisture condition. The impervious depression storages obtained for dry and wet conditions were 0.8 and 0.2 mm, respectively. The locally derived build-up and wash-off parameters were used for modelling runoff quality.

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Section: Sensitivity Analysis Resultsmentioning

confidence: 82%

Section: Introductionmentioning

confidence: 99%

Modelling runoff quantity and quality in tropical urban catchments using Storm Water Management Model

Fai

Yusop

Toriman

2012

Int. J. Environ. Sci. Technol.

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“…Even if the effects of the calibration approach (continuous or event-based) are not insignificant for the overall performance of the model (see e.g. Tan et al, 2008), we do not discuss this aspect here for the sake of brevity.…”

Section: Modus Operandimentioning

confidence: 99%

How crucial is it to account for the antecedent moisture conditions in flood forecasting? Comparison of event-based and continuous approaches on 178 catchments

Berthet

Andréassian²,

Perrin³

et al. 2009

Hydrol. Earth Syst. Sci.

173

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Abstract. This paper compares event-based and continuous hydrological modelling approaches for real-time forecasting of river flows. Both approaches are compared using a lumped hydrologic model (whose structure includes a soil moisture accounting (SMA) store and a routing store) on a data set of 178 French catchments. The main focus of this study was to investigate the actual impact of soil moisture initial conditions on the performance of flood forecasting models and the possible compensations with updating techniques. The rainfall-runoff model assimilation technique we used does not impact the SMA component of the model but only its routing part. Tests were made by running the SMA store continuously or on event basis, everything else being equal. The results show that the continuous approach remains the reference to ensure good forecasting performances. We show, however, that the possibility to assimilate the last observed flow considerably reduces the differences in performance. Last, we present a robust alternative to initialize the SMA store where continuous approaches are impossible because of data availability problems.

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“…Note that basin 1 (B1) is located along the southeast side of basin 2 (B2), B1 is much smaller than B2, and that the total size of both basins is 2285 km 2 as a continuous event. It is easier to analyze the overall shape of the hydrograph, peak flow and time to peak for a single event compared to a continuous event (Tan et al 2008). The simulation was performed using Vflo TM with 100 runs per event in the MCS to produce reliable results.…”

Section: Results Of Rainfall-runoff Simulationmentioning

confidence: 99%

Error influence of radar rainfall estimate on rainfall-runoff simulation

Park

Lee

Ahn

et al. 2015

Stoch Environ Res Risk Assess

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Radar systems have been widely employed to measure precipitation and predict flood risks. However, radar as a rainfall measuring device and the produced rainfall estimate contain uncertainties and errors resulting from sources such as mis-calibration, beam blockage, anomalous propagation, and ground clutter. Previously, these radar errors have been individually studied. However, in practical applications, separating and estimating these errors are not possible. In the current study, to analyze the effects of radar rainfall errors, especially for their effect on the peak discharge, through a synthetic runoff simulation, a spatial error model based on univariate Gaussian random numbers was employed. Furthermore, a Monte Carlo simulation, one of the most widely used techniques for intensive simulation toward obtaining practical results, was performed. The results indicated that the variability of the peak discharge increases as the assumed true rainfall increases. In addition, the higher standard deviation of the tested radar rainfall error leads to a higher peak discharge bias. To investigate the cause of this bias, an additional simulation was performed. This simulation revealed that the regression line for the peak discharge corresponding to rainfall amount increases quadratically. The results show that the higher bias is a result of the higher deviation of peak discharges in the cells, with a greater than mean rainfall, even with the same number of cells for lower and higher rainfall amounts.

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Performances of Rainfall-Runoff Models Calibrated over Single and Continuous Storm Flow Events

Cited by 54 publications

References 28 publications

Modelling runoff quantity and quality in tropical urban catchments using Storm Water Management Model

Modelling runoff quantity and quality in tropical urban catchments using Storm Water Management Model

How crucial is it to account for the antecedent moisture conditions in flood forecasting? Comparison of event-based and continuous approaches on 178 catchments

Error influence of radar rainfall estimate on rainfall-runoff simulation

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