A phenomenon‐based approach to upslope contributing area and depressions in DEMs

Rieger, Wolfgang

doi:10.1002/(sici)1099-1085(199805)12:6<857::aid-hyp659>3.3.co;2-2

Cited by 31 publications

(51 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To use a DEM as a data source in hydrologic analyses, sinks must be removed, a "necessary evil" according to Burrough and McDonnell (1998) and Rieger (1998). Sinks, however, can be real components of the surface.…”

Section: Surface Modification For Hydrologic Analysesmentioning

confidence: 99%

Uncertainties associated with digital elevation models for hydrologic applications: a review

Wechsler

2007

Hydrol. Earth Syst. Sci.

293

181

View full text Add to dashboard Cite

Abstract. Digital elevation models (DEMs) represent the topography that drives surface flow and are arguably one of the more important data sources for deriving variables used by numerous hydrologic models. A considerable amount of research has been conducted to address uncertainty associated with error in digital elevation models (DEMs) and the propagation of error to derived terrain parameters. This review brings together a discussion of research in fundamental topical areas related to DEM uncertainty that affect the use of DEMs for hydrologic applications. These areas include: (a) DEM error; (b) topographic parameters frequently derived from DEMs and the associated algorithms used to derive these parameters; (c) the influence of DEM scale as imposed by grid cell resolution; (d) DEM interpolation; and (e) terrain surface modification used to generate hydrologicallyviable DEM surfaces. Each of these topical areas contributes to DEM uncertainty and may potentially influence results of distributed parameter hydrologic models that rely on DEMs for the derivation of input parameters. The current state of research on methods developed to quantify DEM uncertainty is reviewed. Based on this review, implications of DEM uncertainty and suggestions for the GIS research and user communities are offered.

show abstract

Section: Surface Modification For Hydrologic Analysesmentioning

confidence: 99%

Uncertainties associated with digital elevation models for hydrologic applications: a review

Wechsler

2007

Hydrol. Earth Syst. Sci.

293

181

View full text Add to dashboard Cite

show abstract

“…The mean filter generalised slightly the elevation values of DTMs. Thus, different kinds of filters are used for reducing data noise and removing small depressions [41,43,68].…”

Section: The Variation Of the Hydrological Depression Variablesmentioning

confidence: 99%

“…Consequently, depressions are removed from a grid DTM prior to hydrologic analyses that are based on automated simulation of surface runoff [41][42][43]. These analyses require hydrologically connected flow networks, in which the flow to the actual pour point of the watershed is not prevented.…”

Section: Introductionmentioning

confidence: 99%

Nationwide Digital Terrain Models for Topographic Depression Modelling in Detection of Flood Detention Areas

Vesakoski

Alho

Hyyppä

et al. 2014

Water

View full text Add to dashboard Cite

Topographic depressions have an important role in hydrological processes as they affect the water balance and runoff response of a watershed. Nevertheless, research has focused in detail neither on the effects of acquisition and processing methods nor on the effects of resolution of nationwide grid digital terrain models (DTMs) on topographic depressions or the hydrological impacts of depressions. Here, we quantify the variation of hydrological depression variables between DTMs with different acquisition methods, processing methods and grid sizes based on nationwide 25 m × 25 m and 10 m × 10 m DTMs and 2 m × 2 m ALS-DTM in Finland. The variables considered are the mean depth of the depression, the number of its pixels, and its area and volume. Shallow and single-pixel depressions and the effect of mean filtering on ALS-DTM were also studied. Quantitative methods and error models were employed. In our study, the depression variables were dependent on the scale, area and acquisition method. When the depths of depression pixels were compared with the most accurate DTM, the maximum errors were OPEN ACCESSWater 2014, 6 272 found to create the largest differences between DTMs and hence dominated the amount and statistical distribution of the depth error. On the whole, the ability of a DTM to accurately represent depressions varied uniquely according to each depression, although DTMs also displayed certain typical characteristics. Thus, a DTM's higher resolution is no guarantee of a more accurate representation of topographic depressions, even though acquisition and processing methods have an important bearing on the accuracy.

show abstract

“…Garbrecht and Martz, 1997;Grimaldi et al, 2007;Santini et al, 2009) first fill sinks, and then introduce a gradient to all flat areas to provide non-zero gradients for flow routing. The method complementary to sink filling is carving or breaching (Rieger, 1998;Martz and Garbrecht, 1998) where a channel is carved out of each sink, breaking through the (artificial) obstacle. Both principles can be combined in an impact reduction approach (IRA; Lindsay and Creed, 2005) that for each sink determines the method that causes the least impact on the source dataset.…”

Section: Introductionmentioning

confidence: 99%

Efficient extraction of drainage networks from massive, radar-based elevation models with least cost path search

Metz

Mitášová

Harmon³

2011

Hydrol. Earth Syst. Sci.

142

View full text Add to dashboard Cite

Abstract. The availability of both global and regional elevation datasets acquired by modern remote sensing technologies provides an opportunity to significantly improve the accuracy of stream mapping, especially in remote, hard to reach regions. Stream extraction from digital elevation models (DEMs) is based on computation of flow accumulation, a summary parameter that poses performance and accuracy challenges when applied to large, noisy DEMs generated by remote sensing technologies. Robust handling of DEM depressions is essential for reliable extraction of connected drainage networks from this type of data. The least-cost flow routing method implemented in GRASS GIS as the module r.watershed was redesigned to significantly improve its speed, functionality, and memory requirements and make it an efficient tool for stream mapping and watershed analysis from large DEMs. To evaluate its handling of large depressions, typical for remote sensing derived DEMs, three different methods were compared: traditional sink filling, impact reduction approach, and least-cost path search. The comparison was performed using the Shuttle Radar Topographic Mission (SRTM) and Interferometric Synthetic Aperture Radar for Elevation (IFSARE) datasets covering central Panama at 90 m and 10 m resolutions, respectively. The accuracy assessment was based on ground control points acquired by GPS and reference points digitized from Landsat imagery along segments of selected Panamanian rivers. The results demonstrate that the new implementation of the least-cost path method is significantly faster than the original version, can cope with massive datasets, and provides the most accurate results in terms of stream locations validated against reference points.

show abstract

A phenomenon‐based approach to upslope contributing area and depressions in DEMs

Cited by 31 publications

References 0 publications

Uncertainties associated with digital elevation models for hydrologic applications: a review

Uncertainties associated with digital elevation models for hydrologic applications: a review

Nationwide Digital Terrain Models for Topographic Depression Modelling in Detection of Flood Detention Areas

Efficient extraction of drainage networks from massive, radar-based elevation models with least cost path search

Contact Info

Product

Resources

About