Comparison of grid‐based algorithms for computing upslope contributing area

Erskine, Robert H.; Green, Timothy R.; Ramı́rez, Jorge A.; MacDonald, Lee H.

doi:10.1029/2005wr004648

Cited by 120 publications

(122 citation statements)

References 44 publications

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“…The higher predictive quality of these multidirectional flow redistribution methods (Schmidt and Persson, 2003;Güntner et al, 2004;Pan et al, 2004;Erskine et al, 2006) raise the question whether there are any advantages for computing flow distances too. Here we present a flow-path length algorithm that takes divergent flow into account.…”

Section: Hillslope Analysismentioning

confidence: 99%

Curvature distribution within hillslopes and catchments and its effect on the hydrological response

Bogaart

Troch

2006

Hydrol. Earth Syst. Sci.

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Abstract. Topographic convergence and divergence are first order controls on the hillslope and catchment hydrological response, as evidenced by similarity parameter analyses. Hydrological models often do not take convergence as measured by contour curvature directly into account; instead they use comparable measures like the topographic index, or the hillslope width function. This paper focuses on the question how hillslope width functions and contour curvature are related within the Plynlimon catchments, Wales. It is shown that the total width function of all hillslopes combined suggest that the catchments are divergent in overall shape, which is in contrast to the perception that catchments should be overall convergent. This so-called convergence paradox is explained by the effect of skewed curvature distributions and extreme curvatures near the channel network. The hillslopestorage Bossiness (hsB) model is used to asses the effect of within-hillslope convergence variability on the hydrological response. It is concluded that this effect is small, even when the soil saturation threshold is exceeded. Also described in this paper is a novel algorithm to compute flow path lengths on hillslopes towards the drainage network, using the multidirectional flow redistribution method.

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Section: Hillslope Analysismentioning

confidence: 99%

Curvature distribution within hillslopes and catchments and its effect on the hydrological response

Bogaart

Troch

2006

Hydrol. Earth Syst. Sci.

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“…Mean snow depth for each 1 m 2 elevation band with > 100 m 2 area was computed from the snow-depth grid. Additionally, a 5 m elevation model, aggregated from the 1 m 2 bare-earth model, was produced to remove scaling biases in the analysis of slope and aspect (Kienzle, 2004;Erskine et al, 2006).…”

Section: Lidar Altimetrymentioning

confidence: 99%

LiDAR measurement of seasonal snow accumulation along an elevation gradient in the southern Sierra Nevada, California

Kirchner

Bales

Molotch

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. We present results from snow-on and snow-off airborne-scanning LiDAR measurements over a 53 km 2 area in the southern Sierra Nevada. We found that snow depth as a function of elevation increased approximately 15 cm per 100 m, until reaching an elevation of 3300 m, where depth sharply decreased at a rate of 48 cm per 100 m. Departures from the 15 cm per 100 m trend, based on 1 m elevation-band means of regression residuals, showed slightly less steep increases below 2050 m; steeper increases between 2050 and 3300 m; and less steep increases above 3300 m. Although the study area is partly forested, only measurements in open areas were used. Below approximately 2050 m elevation, ablation and rainfall are the primary causes of departure from the orographic trend. From 2050 to 3300 m, greater snow depths than predicted were found on the steeper terrain of the northwest and the less steep northeast-facing slopes, suggesting that ablation, aspect, slope and wind redistribution all play a role in local snow-depth variability. At elevations above 3300 m, orographic processes mask the effect of wind deposition when averaging over large areas. Also, terrain in this basin becomes less steep above 3300 m. This suggests a reduction in precipitation from upslope lifting and/or the exhaustion of precipitable water from ascending air masses. Our results suggest a cumulative precipitation lapse rate for the 2100-3300 m range of about 6 cm per 100 m elevation for the accumulation period of 3 December 2009 to 23 March 2010. This is a higher gradient than the widely used PRISM (Parameter-elevation Relationships on Independent Slopes Model) precipitation products, but similar to that from reconstruction of snowmelt amounts from satellite snow-cover data. Our findings provide a unique characterization of the consistent, steep average increase in precipitation with elevation in snow-dominated terrain, using high-resolution, highly accurate data and highlighs the importance of solar radiation, wind redistribution and mid-winter melt with regard to snow distribution.

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“…Alternate routing methods, based upon MFD, have been proposed such as DEMON [18] and D ∞ [19]. The relative merits of these methods were discussed by Erskine [20] and although it is acknowledged that MFD produces more realistic drainage patterns in certain areas, the computational overhead introduced, especially for large DEMs, has seen it largely ignored in favour of the more efficient SFD. The influence of routing choice on LEM outcome is, however, unequivocal [21].…”

Section: Addressing the Flow Routing And Accumulation Problem Onmentioning

confidence: 99%

Massively parallel landscape-evolution modelling using general purpose graphical processing units

McGough

Liang

Rapoportas

et al. 2012

2012 19th International Conference on High Performance Computing

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Abstract-As our expectations of what computer systems can do and our ability to capture data improves, the desire to perform ever more computationally intensive tasks increases. Often these tasks, comprising vast numbers of repeated computations, are highly interdependent on each other -a closely coupled problem. The process of Landscape-Evolution Modelling is an example of such a problem. In order to produce realistic models it is necessary to process landscapes containing millions of data points over time periods extending up to millions of years. This leads to non-tractable execution times, often in the order of years. Researchers therefore seek multiple orders of magnitude reduction in the execution time of these models. The massively parallel programming environment offered through General Purpose Graphical Processing Units offers the potential for multiple orders of magnitude speedup in code execution times.In this paper we demonstrate how the time dominant parts of a Landscape-Evolution Model can be recoded for a massively parallel architecture providing two orders of magnitude reduction in execution time.

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Comparison of grid‐based algorithms for computing upslope contributing area

Cited by 120 publications

References 44 publications

Curvature distribution within hillslopes and catchments and its effect on the hydrological response

Curvature distribution within hillslopes and catchments and its effect on the hydrological response

LiDAR measurement of seasonal snow accumulation along an elevation gradient in the southern Sierra Nevada, California

Massively parallel landscape-evolution modelling using general purpose graphical processing units

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