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

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 dist...

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Main Authors: R. Mantilla, V. K. Gupta, B. M. Troutman
Format: Article
Language:English
Published: Copernicus Publications 2011-07-01
Series:Nonlinear Processes in Geophysics
Online Access:http://www.nonlin-processes-geophys.net/18/489/2011/npg-18-489-2011.pdf
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spelling doaj-97de65a664d145d8842a833328ce6d2e2020-11-24T21:39:06ZengCopernicus PublicationsNonlinear Processes in Geophysics1023-58091607-79462011-07-0118448950210.5194/npg-18-489-2011Scaling of peak flows with constant flow velocity in random self-similar networksR. MantillaV. K. GuptaB. M. TroutmanA 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 <i>p</i><sub>i</sub> and <i>p</i><sub>e</sub>, 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<sup><i>(E)</i></sup> and φ<sup><i>(E)</i></sup> 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<sup><i>(E)</i></sup> and φ<sup><i>(E)</i></sup> and the values estimated by the simulated ensembles of RSNs and hydrographs. The independence of the scaling exponents φ<sup><i>(E)</i></sup> and φ with respect 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.http://www.nonlin-processes-geophys.net/18/489/2011/npg-18-489-2011.pdf
collection DOAJ
language English
format Article
sources DOAJ
author R. Mantilla
V. K. Gupta
B. M. Troutman
spellingShingle R. Mantilla
V. K. Gupta
B. M. Troutman
Scaling of peak flows with constant flow velocity in random self-similar networks
Nonlinear Processes in Geophysics
author_facet R. Mantilla
V. K. Gupta
B. M. Troutman
author_sort R. Mantilla
title Scaling of peak flows with constant flow velocity in random self-similar networks
title_short Scaling of peak flows with constant flow velocity in random self-similar networks
title_full Scaling of peak flows with constant flow velocity in random self-similar networks
title_fullStr Scaling of peak flows with constant flow velocity in random self-similar networks
title_full_unstemmed Scaling of peak flows with constant flow velocity in random self-similar networks
title_sort scaling of peak flows with constant flow velocity in random self-similar networks
publisher Copernicus Publications
series Nonlinear Processes in Geophysics
issn 1023-5809
1607-7946
publishDate 2011-07-01
description 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 <i>p</i><sub>i</sub> and <i>p</i><sub>e</sub>, 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<sup><i>(E)</i></sup> and φ<sup><i>(E)</i></sup> 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<sup><i>(E)</i></sup> and φ<sup><i>(E)</i></sup> and the values estimated by the simulated ensembles of RSNs and hydrographs. The independence of the scaling exponents φ<sup><i>(E)</i></sup> and φ with respect 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.
url http://www.nonlin-processes-geophys.net/18/489/2011/npg-18-489-2011.pdf
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