Effect of DEM data resolution on SWAT output uncertainty

Chaubey, Indrajeet; Cotter, Amy S.; Costello, Thomas A.; Soerens, Thomas S.

doi:10.1002/hyp.5607

Cited by 186 publications

(113 citation statements)

References 18 publications

(20 reference statements)

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“…For instance, Veregin (2000) and Cheung and Shi (2004) Usery, and Madden (2008), and Pogson and Smith (2015) investigated the effects of input rasters using different resolutions and found a significant difference in the outcome of a spatial analysis. For example, the study of Chaubey et al (2005) indicates that the resolution of digital elevation models affects the output of a hydrologic spatial analysis.…”

Section: Representation-induced Errormentioning

confidence: 99%

The effect of acquisition error and level of detail on the accuracy of spatial analyses

Biljecki

Heuvelink

Ledoux

et al. 2017

Cartography and Geographic Information Science

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There has been a great deal of research about errors in geographic information and how they affect spatial analyses. A typical GIS process introduces various types of errors at different stages, and such errors usually propagate into errors in the result of a spatial analysis. However, most studies consider only a single error type thus preventing the understanding of the interaction and relative contributions of different types of errors. We focus on the level of detail (LOD) and positional error, and perform a multiple error propagation analysis combining both types of error. We experiment with three spatial analyses (computing gross volume, envelope area, and solar irradiation of buildings) performed with procedurally generated 3D city models to decouple and demonstrate the magnitude of the two types of error, and to show how they individually and jointly propagate to the output of the employed spatial analysis. The most notable result is that in the considered spatial analyses the positional error has a much higher impact than the LOD. As a consequence, we suggest that it is pointless to acquire geoinformation of a fine LOD if the acquisition method is not accurate, and instead we advise focusing on the accuracy of the data. ARTICLE HISTORY

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Section: Representation-induced Errormentioning

confidence: 99%

The effect of acquisition error and level of detail on the accuracy of spatial analyses

Biljecki

Heuvelink

Ledoux

et al. 2017

Cartography and Geographic Information Science

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“…(3) At the watershed scale, large research areas reduce the data accuracy of digital elevation models (DEM) which are used to extract such data as slope gradient, drainage network and distance from river. However, DEM accuracy will have a notable effect on the research results [15,16] . Consequently, it is not suitable to use factors such as slope gradient, vertical distance from river and horizontal distance from river as the topographic factor in the soil loss evaluation index at the watershed scale.…”

Section: Basis For Establishing a Multiscale Soil Loss Evaluation Indexmentioning

confidence: 99%

A multiscale soil loss evaluation index

Zhao

Chen

et al. 2006

CHINESE SCI BULL

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Exploring the relationships between land use and soil erosion at different scales is a frontier research field and a hot spot topic in contemporary physical geography. Based on the scale-pattern-process theory in landscape ecology and with consideration of such influential factors as land use, topography, soil and rainfall, this paper applies the scale transition method to establishing a soil loss evaluation index at different scales and puts forward a research path and methodology for multiscale soil loss evaluation indices. The multiscale soil loss evaluation index is applied to the evaluation of relationships between land use and soil erosion and the research of soil erosion evaluation at multiple scales. It provides a new method for optimizing the design of regional land use patterns and integrated multiscale research.

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“…Using Soil and Water Assessment Tool (SWAT) modeling, coarsened DEM resolution was found to reduce the accuracy of both streamflow and NO 3 -N load prediction, but not the accuracy of total P load predictions [13]. A distributed hydrologic model used to predict average soil moisture and streamflow at the hillslope scale showed that using a coarser DEM did not reduce model accuracy, but the spatial pattern of soil moisture was distorted [14].…”

Section: Introductionmentioning

confidence: 98%

“…The effect of DEM resolution on model predictions also varied with the variable of interest [13]. Using Soil and Water Assessment Tool (SWAT) modeling, coarsened DEM resolution was found to reduce the accuracy of both streamflow and NO 3 -N load prediction, but not the accuracy of total P load predictions [13].…”

Section: Introductionmentioning

confidence: 99%

Effects of Model Spatial Resolution on Ecohydrologic Predictions and Their Sensitivity to Inter-Annual Climate Variability

Son

Tague

Hunsaker

2016

Water

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Abstract:The effect of fine-scale topographic variability on model estimates of ecohydrologic responses to climate variability in California's Sierra Nevada watersheds has not been adequately quantified and may be important for supporting reliable climate-impact assessments. This study tested the effect of digital elevation model (DEM) resolution on model accuracy and estimates of the sensitivity of ecohydrologic responses to inter-annual climate variability. The Regional Hydro-Ecologic Simulation System (RHESSys) was applied to eight headwater, high-elevation watersheds located in the Kings River drainage basin. Each watershed was calibrated with measured snow depth (or snow water equivalent) and daily streamflow. Modeled streamflow estimates were sensitive to DEM resolution, even with resolution-specific calibration of soil drainage parameters. For model resolutions coarser than 10 m, the accuracy of streamflow estimates largely decreased. Reduced model accuracy was related to the reduction in spatial variance of a topographic wetness index with coarser DEM resolutions. This study also found that among the long-term average ecohydrologic estimates, summer flow estimates were the most sensitive to DEM resolution, and coarser resolution models overestimated the climatic sensitivity for evapotranspiration and net primary productivity. Therefore, accounting for fine-scale topographic variability in ecohydrologic modeling may be necessary for reliably assessing climate change effects on lower-order Sierra Nevada watersheds (ď2.3 km 2 ).

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Effect of DEM data resolution on SWAT output uncertainty

Cited by 186 publications

References 18 publications

The effect of acquisition error and level of detail on the accuracy of spatial analyses

The effect of acquisition error and level of detail on the accuracy of spatial analyses

A multiscale soil loss evaluation index

Effects of Model Spatial Resolution on Ecohydrologic Predictions and Their Sensitivity to Inter-Annual Climate Variability

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