Geometric analysis of surface runoff and the computation order of unit elements in distributed hydrological models

Palacios-Vélez, Óscar L.; Gandoy-Bernasconi, William; Cuevas-Renaud, Baltasar

doi:10.1016/s0022-1694(98)00196-6

Cited by 23 publications

(15 citation statements)

References 9 publications

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“…A full description of the RUICELLS model, including its mathematical structure, can be found in Delahaye et al (2001), Langlois and Delahaye (2002), Jaziri 2004 andDouvinet et al (2013). The diversity of the topography and the variety of the mechanisms involved precludes a global modelling of the run-off process (Mita et al 2001;Palacios-Vélez et al 1998;Tucker et al 2001) and it requires a sharp division of the concerned area into homogeneous and interconnected cells. In RUICELLS, the original CA concept is generalized to incorporate the variety of the topographical conditions: elementary surfaces on hillslopes, linear portions of thalwegs, and local depressions.…”

Section: Methodsmentioning

confidence: 99%

A flash flood hazard assessment in dry valleys (northern France) by cellular automata modelling

et al. 2014

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This paper presents an application of a cellular automaton-based run-off model (RUICELLS) to a series of small dry valleys in the Seine-Maritime department, northern France, to better assess their susceptibility to flash flood. These muddy floods shortly follow high rainfall (50-100 mm in less than 6 h) and occur in very small areas (\20 km 2 ). A surge generally rushes down through the main valley just a few minutes after rains have peaked. Previous events (n = 69, in the period 1983-2005) have occasionally threatened human lives and have caused significant damage to property and infrastructure. Nonetheless, given the variation among the valleys and the infrequency of events, these floods have not been numerous enough to permit a statistical analysis. Instead, we numerically simulate the possible future flash floods using RUICELLS, a cellular automaton model driven by a set of three deterministic hydrological rules. Simulations have been conducted for 148 basins, each subject to 16 different rainfall scenarios (2.368 simulations in total) to (1) estimate the peak flow discharges (Q), the specific peak flows (Q s ), and the lag times (T) of the flash floods and (2) 123Nat Hazards (2015) 75:2905-2929 DOI 10.1007/s11069-014-1470 warnings and increased vigilance. Our simulations indicate that the number of basins susceptible to flash flooding greatly increases with the higher rainfall intensity, the distribution of sensitive crops (sugar beet, corn, maize, and flax) and the basin morphology. Several small basins could also induce by convergence a bigger flood in the downstream humid valleys. The location of the highest simulated discharges is aligned with observed events, and this comparison provides an evaluation of the modelling performance and of the credibility of the results.

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Section: Methodsmentioning

confidence: 99%

A flash flood hazard assessment in dry valleys (northern France) by cellular automata modelling

et al. 2014

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“…The size of the strip map of a fat terrain is Θ(N 2 ) in the worst case [9], in which case the exact computation of watersheds becomes infeasible. An approach often taken in practice [16][17][18] is to assume that water flows only along terrain edges, allowing the computation of watersheds using O(sort(N )) I/Os. While this may lead to poor approximations of the watersheds for irregular terrains [9], TIN's derived from LIDAR data, for example, are rather regular, and the computed watersheds match the real watersheds rather closely.…”

Section: Related Workmentioning

confidence: 99%

I/O-efficient computation of water flow across a terrain

Arge

Revsbæk

Zeh

2010

Proceedings of the Twenty-Sixth Annual Symposium on Computational Geometry

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Consider rain falling at a uniform rate onto a terrain T represented as a triangular irregular network. Over time, water collects in the basins of T , forming lakes that spill into adjacent basins. Our goal is to compute, for each terrain vertex, the time this vertex is flooded (covered by water). We present an I/O-efficient algorithm that solves this problem using O(sort(X) log(X/M ) + sort(N )) I/Os, where N is the number of terrain vertices, X is the number of pits of the terrain, sort(N ) is the cost of sorting N data items, and M is the size of the computer's main memory. Our algorithm assumes that the volumes and watersheds of the basins of T have been precomputed using existing methods.

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“…De acordo com Palacios-Vélez et al (1998), a demanda por modelos que permitam melhor previsão hidrológica aumenta com a notificação de prejuízos causados por inundações. O desenvolvimento de melhores modelos, entretanto, requer um esforço contínuo da pesquisa e da comunidade acadêmica, uma vez que estes modelos necessitam de informações consistentes sobre precipitação, escoamento, topografia, solo, entre outras.…”

Section: Introductionunclassified

Modelo para obtenção do hidrograma de escoamento superficial em bacias hidrográficas. 1. Desenvolvimento e análise de sensibilidade

Silva

Pruski

Cecílio

2009

Agraria

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Desenvolveu-se um modelo para obter o hidrograma de escoamento superficial em bacias hidrográ-ficas considerando tanto o escoamento em encostas como em canais. O modelo usa a equação de intensidade, duração e frequência na análise de eventos extremos ou o pluviograma correspondente ao evento em estudo na análise de eventos específicos e a equação de Green-Ampt-Mein-Larson para estimar a taxa de infiltração. A taxa de escoamento superficial é estimada considerando o modelo de ondas cinemáticas, no qual o hidrograma para cada célula é obtido somando-se o hidrograma produzido na célula com os provenientes das células contribuintes. O modelo é mais sensível à umidade de saturação, umidade inicial, armazenamento superficial, potencial matricial na frente de umedecimento e condutividade hidráulica do solo e menos sensível ao coeficiente de rugosidade e à interceptação pela cobertura vegetal. Palavras-chave: modelagem hidrológica, hidrologia, recursos hídricosModel to obtain the runoff hydrogram in watersheds. 1. Development and sensitivity analysis AB S TR ACTA model was developed to estimate the runoff hydrogram in watersheds for hill slope and channel. The model uses the intensity-duration-frequency equation to calculate the extreme rainfall intensity and the Green-Ampt-Mein-Larson equation to estimate the infiltration rate. The runoff is calculated using the kinematic wave model and the hydrogram for each cell is obtained summing the hydrogram produced on the cell with those that come from the cells that contribute with runoff for the cell in analysis. The model is more sensible to the soil saturation moisture content, initial soil moisture, surface storage, matrix potential at wetting front and soil hydraulic conductivity, and less sensible to the surface roughness and canopy interception.

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Geometric analysis of surface runoff and the computation order of unit elements in distributed hydrological models

Cited by 23 publications

References 9 publications

A flash flood hazard assessment in dry valleys (northern France) by cellular automata modelling

A flash flood hazard assessment in dry valleys (northern France) by cellular automata modelling

I/O-efficient computation of water flow across a terrain

Modelo para obtenção do hidrograma de escoamento superficial em bacias hidrográficas. 1. Desenvolvimento e análise de sensibilidade

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