Effects of excess rainfall on the temporal variability of observed peak-discharge power laws

Furey, Peter R.; Gupta, Vijay

doi:10.1016/j.advwatres.2005.03.014

Cited by 64 publications

(55 citation statements)

References 15 publications

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“…Their study underscored that the flood scaling parameters vary from event to event. Furey and Gupta [2005] later analyzed 148 rainfall-runoff events from the GCEW and showed that the exponent varies as a function of rainfall duration, whereas the intercept varies as a function of excess rainfall intensity. Furey and Gupta [2007] affirmed these results through a detailed diagnostic study of the same data set.…”

Section: 1002/2014wr016258mentioning

confidence: 99%

“…In a major departure from the peak discharge quantile based analysis used in the regional flood-frequency methodology, a number of rainfallrunoff event based studies were undertaken in an effort to describe the flood scaling parameters in terms of rainfall and catchment physical processes that transform rainfall to peak discharge [Ayalew et al, 2014a[Ayalew et al, , 2014bDi Lazzaro and Volpi, 2011;Furey and Gupta, 2005;Gupta, 2004;Gupta et al, 1996Gupta et al, , 2007Gupta et al, , 2010Mandapaka et al, 2009;Mantilla et al, 2006Mantilla et al, , 2011Morrison and Smith, 2001;Ogden and Dawdy, 2003]. These studies, which cover a range of theoretical and empirical studies, revealed that peak discharges from nested catchments exhibit scale-invariance with drainage area at the rainfall-runoff event scale and the relationship between the two exhibits the following power law relation:…”

Section: Introductionmentioning

confidence: 99%

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Analyzing the effects of excess rainfall properties on the scaling structure of peak discharges: Insights from a mesoscale river basin

Ayalew

Krajewski

Mantilla

2015

Water Resources Research

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Key theoretical and empirical results from the past two decades have established that peak discharges resulting from a single rainfall-runoff event in a nested watershed exhibit a power law, or scaling, relation to drainage area and that the parameters of the power law relation, henceforth referred to as the flood scaling exponent and intercept, change from event to event. To date, only two studies have been conducted using empirical data, both using data from the 21 km 2 Goodwin Creek Experimental Watershed that is located in Mississippi, in an effort to uncover the physical processes that control the event-to-event variability of the flood scaling parameters. Our study expands the analysis to the mesoscale Iowa River basin (A 5 32,400 km 2 ), which is located in eastern Iowa, and provides additional insights into the physical processes that control the flood scaling parameters. Using 51 rainfall-runoff events that we identified over the 12 year period since 2002, we show how the duration and depth of excess rainfall, which is the portion of rainfall that contributes to direct runoff, control the flood scaling exponent and intercept. Moreover, using a diagnostic simulation study that is guided by evidence found in empirical data, we show that the temporal structure of excess rainfall has a significant effect on the scaling structure of peak discharges. These insights will contribute toward ongoing efforts to provide a framework for flood prediction in ungauged basins.

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Section: 1002/2014wr016258mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analyzing the effects of excess rainfall properties on the scaling structure of peak discharges: Insights from a mesoscale river basin

Ayalew

Krajewski

Mantilla

2015

Water Resources Research

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“…Ogden and Dawdy (2003) conducted the first study in the 21 km 2 Goodwin Creek experimental watershed (GCEW), and observed that the slopes and intercepts of the peakflow scaling, or power-law, relations vary from one event to the next. Furey and Gupta (2005) found that the eventto-event variability in the slopes and intercepts of the peakflow scaling relations is connected to rainfall-excess depth and duration for storms. Building on this finding, Furey and Gupta (2007) developed a diagnostic framework to predict slopes and intercepts of peak flow scaling functions in GCEW.…”

Section: Introductionmentioning

confidence: 99%

Scaling of peak flows with constant flow velocity in random self-similar networks

Mantilla

Gupta

Troutman

2011

Nonlin. Processes Geophys.

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Abstract.A methodology is presented to understand the role of the statistical self-similar topology of real river networks on scaling, or power law, in peak flows for rainfall-runoff events. We created Monte Carlo generated sets of ensembles of 1000 random self-similar networks (RSNs) with geometrically distributed interior and exterior generators having parameters p i and p e , respectively. The parameter values were chosen to replicate the observed topology of real river networks. We calculated flow hydrographs in each of these networks by numerically solving the link-based mass and momentum conservation equation under the assumption of constant flow velocity. From these simulated RSNs and hydrographs, the scaling exponents β and φ characterizing power laws with respect to drainage area, and corresponding to the width functions and flow hydrographs respectively, were estimated. We found that, in general, φ > β, which supports a similar finding first reported for simulations in the river network of the Walnut Gulch basin, Arizona. Theoretical estimation of β and φ in RSNs is a complex open problem. Therefore, using results for a simpler problem associated with the expected width function and expected hydrograph for an ensemble of RSNs, we give heuristic arguments for theoretical derivations of the scaling exponents β (E) and φ (E) that depend on the Horton ratios for stream lengths and areas. These ratios in turn have a known dependence on the parameters of the geometric distributions of RSN generators. Good agreement was found between the analytically conjectured values of β (E) and φ (E) and the values estimated by the simulated ensembles of RSNs and hydrographs. The independence of the scaling exponents φ (E) and φ with respect Correspondence to: R. Mantilla (ricardo-mantilla@uiowa.edu) to the value of flow velocity and runoff intensity implies an interesting connection between unit hydrograph theory and flow dynamics. Our results provide a reference framework to study scaling exponents under more complex scenarios of flow dynamics and runoff generation processes using ensembles of RSNs.

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“…For each event, step (4) requires that antecedent conditions include a 24 h period of zero rainfall. This step provides little constraint on antecedent soil moisture, which can be near zero in late summer and near 1 in winter (Furey and Gupta, 2005).…”

Section: Selecting Rainfall-runoff Events From Streamflow Datamentioning

confidence: 99%

A top-down model to generate ensembles of runoff from a large number of hillslopes

Furey

Gupta

Troutman

2013

Nonlin. Processes Geophys.

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Abstract. We hypothesize that total hillslope water loss for a rainfall-runoff event is inversely related to a function of a lognormal random variable, based on basin-and pointscale observations taken from the 21 km 2 Goodwin Creek Experimental Watershed (GCEW) in Mississippi, USA. A top-down approach is used to develop a new runoff generation model both to test our physical-statistical hypothesis and to provide a method of generating ensembles of runoff from a large number of hillslopes in a basin. The model is based on the assumption that the probability distributions of a runoff/loss ratio have a space-time rescaling property. We test this assumption using streamflow and rainfall data from GCEW. For over 100 rainfall-runoff events, we find that the spatial probability distributions of a runoff/loss ratio can be rescaled to a new distribution that is common to all events. We interpret random within-event differences in runoff/loss ratios in the model to arise from soil moisture spatial variability. Observations of water loss during events in GCEW support this interpretation. Our model preserves water balance in a mean statistical sense and supports our hypothesis.As an example, we use the model to generate ensembles of runoff at a large number of hillslopes for a rainfall-runoff event in GCEW.

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Effects of excess rainfall on the temporal variability of observed peak-discharge power laws

Cited by 64 publications

References 15 publications

Analyzing the effects of excess rainfall properties on the scaling structure of peak discharges: Insights from a mesoscale river basin

Analyzing the effects of excess rainfall properties on the scaling structure of peak discharges: Insights from a mesoscale river basin

Scaling of peak flows with constant flow velocity in random self-similar networks

A top-down model to generate ensembles of runoff from a large number of hillslopes

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