Geographic Information Systems (GIS)‐based spatially distributed model for runoff routing

Olivera, Francisco; Maidment, David R.

doi:10.1029/1998wr900104

Cited by 150 publications

(111 citation statements)

References 12 publications

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“…7.7). Very similar linear modeling approaches, but which are grid-based rather than link-based, are described in Olivera and Maidment (1999), Liu et al (2003) and Olivera and Koka (2004). We shall assume here for simplicity that all rainfall excess is deposited into the upstream end of the link.…”

Section: On Flowsmentioning

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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Section: On Flowsmentioning

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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“…However, in the present case, the form of the hydrograph is assumed and imposed upon the runoff generated by each cell. This runoff is independent and does not interact with that of the other cells (Olivera and Maidment, 1999;Maidment et al, 1996). Independent grid cells may be a strong simplification; however, runoff is rapidly concentrated, leading to little or no infiltration or storage during flow routing.…”

Section: The Transfer Functionmentioning

confidence: 99%

Correcting the radar rainfall forcing of a hydrological model with data assimilation: application to flood forecasting in the Lez catchment in Southern France

Harader

Borrell-Estupina²,

Ricci³

et al. 2012

Hydrol. Earth Syst. Sci.

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Abstract. The present study explores the application of a data assimilation (DA) procedure to correct the radar rainfall inputs of an event-based, distributed, parsimonious hydrological model. An extended Kalman filter algorithm was built on top of a rainfall-runoff model in order to assimilate discharge observations at the catchment outlet. This work focuses primarily on the uncertainty in the rainfall data and considers this as the principal source of error in the simulated discharges, neglecting simplifications in the hydrological model structure and poor knowledge of catchment physics. The study site is the 114 km 2 Lez catchment near Montpellier, France. This catchment is subject to heavy orographic rainfall and characterised by a karstic geology, leading to flash flooding events. The hydrological model uses a derived version of the SCS method, combined with a Lag and Route transfer function. Because the radar rainfall input to the model depends on geographical features and cloud structures, it is particularly uncertain and results in significant errors in the simulated discharges. This study seeks to demonstrate that a simple DA algorithm is capable of rendering radar rainfall suitable for hydrological forecasting. To test this hypothesis, the DA analysis was applied to estimate a constant hyetograph correction to each of 19 flood events. The analysis was carried in two different modes: by assimilating observations at all available time steps, referred to here as reanalysis mode, and by using only observations up to 3 h before the flood peak to mimic an operational environment, referred to as pseudo-forecast mode. In reanalysis mode, the resulting correction of the radar rainfall data was then compared to the mean field bias (MFB), a corrective coefficient determined using rain gauge measurements. It was shown that the radar rainfall corrected using DA leads to improved discharge simulations and Nash-Sutcliffe efficiency criteria compared to the MFB correction. In pseudo-forecast mode, the reduction of the uncertainty in the rainfall data leads to a reduction of the error in the simulated discharge, but uncertainty from the model parameterisation diminishes data assimilation efficiency. While the DA algorithm used is this study is effective in correcting uncertain radar rainfall, model uncertainty remains an important challenge for flood forecasting within the Lez catchment.

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“…Although it would be logical to model the dynamic interaction between water level and channel flows from the characteristic profiles, this necessitates detailed information on the hydraulic properties of the entire channel network and such information does not exist for the Steinsel sub-basin. Hence, a diffusive wave approximation routing procedure was adopted, which assumes time-independent flow velocities parameterised as a function of the topographic gradient, which is commonly used in GIS-based flow routing schemes (Lee and Yen, 1997;Olivera and Maidment, 1999). The model determines the hydraulic radius by a power law relationship (Molnar and Ramirez, 1998), which, for discharge of a given exceedence probability, relates hydraulic radius to the drained area and is representative of the average behaviour of the cell and the channel geometry.…”

Section: Assessing Approachmentioning

confidence: 99%

Simulation of flood reduction by natural river rehabilitation using a distributed hydrological model

Liu

Gebremeskel

Smedt

et al. 2004

Hydrol. Earth Syst. Sci.

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The effects of river rehabilitation on flood reduction in the Steinsel sub-basin of the Alzette River basin, Grand-Duchy of Luxembourg, are discussed; the rehabilitation measures include planting and changing riparian and in-stream vegetation, and re-meandering of channelised reaches, etc. in the headwater streams. To simulate flood reduction by river rehabilitation, the streams have been classified into different orders and by assessing the response of the stream channels to the resistance or obstruction of flows. Based on this assessment, the roughness to the flow in the first and second order streams is adjusted in line with the river rehabilitation while the roughness of higher order channels downstream is unchanged. The hydrological analysis utilises the WetSpa distributed model based on spatial information on topography, soil type and land use. The increased channel roughness in the headwater channels delays the flows, so that peak discharges at the outlet of the basin are reduced. The simulation indicates that, after river naturalisation, the reduction in peak flow can be as much as 14% and the time of concentration may be delayed by as much as two hours. Also, an impact analysis has assessed the possible flood reduction for a changed climate scenario.

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Geographic Information Systems (GIS)‐based spatially distributed model for runoff routing

Cited by 150 publications

References 12 publications

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

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

Correcting the radar rainfall forcing of a hydrological model with data assimilation: application to flood forecasting in the Lez catchment in Southern France

Simulation of flood reduction by natural river rehabilitation using a distributed hydrological model

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