What is the effect of LiDAR-derived DEM resolution on large-scale watershed model results?

Yang, P.; Ames, Daniel P.; Fonseca, André; Anderson, Danny; Shrestha, R.; Glenn, Nancy F.; Cao, Yang

doi:10.1016/j.envsoft.2014.04.005

Cited by 80 publications

(43 citation statements)

References 46 publications

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“…In general, this error increases with coarsening of the spatial resolution, and a predominance of underestimation occurs due to the difficulty of representing the river sinuosity. This underestimation error in river length has been reported by other authors (e.g., Colombo, Vogt, Soille, Paracchini, & de Jager, ; Heine et al, ) and is mainly due to missing meanders, strengthening with increasing cell size (Fekete et al, ; Yang et al, ). For the Intermediate and Lower Uruguay rivers, overestimation error occurs due to flatness, which causes a winding pattern in the traced flow paths (Paz & Collischonn, ).…”

Section: Resultssupporting

confidence: 56%

How to evaluate the quality of coarse‐resolution DEM‐derived drainage networks

Sousa

Paz

2017

Hydrological Processes

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The quality of digital elevation model (DEM)‐derived river drainage networks (RDNs) is influenced by DEM quality, basin physical characteristics, scale, and algorithms used; these factors should not be neglected. However, few research studies analyse the different evaluation approaches used in the literature with respect to adequacy, meaning of the results, advantages, and limitations. Focusing on coarse‐resolution networks, this paper reviews the use of these techniques and offers new insights on these issues. Additionally, we propose adaptations for selected metrics and discuss distinct interpretations for the evaluation of RDNs derived at different spatial resolutions (1, 5, 10, 20, and 30 km) considering the Uruguay River basin (206,000 km2) as a case study. The results demonstrate that lumped basin/river characteristics and basin delineation analysis should not be used as evaluation criteria for RDN quality; however, some of these metrics offer useful complementary information. Percentage of the DEM‐derived RDN within a uniform buffer placed around a river network considered as reference and mean separation distance between these two networks are more suitable metrics, but the former is insensitive to serious errors. The change in reference from a fine‐scale network to a coarse‐resolution manual tracing network significantly augments the discrepancy of these largest errors when the mean distance metric was applied, and visual comparison analysis is necessary to interpret the results for other metrics. We recommend the use of the mean distance metric in combination with a detailed visual assessment, the importance of which increases as the resolution coarsens. In both cases, the impact of network quality can be further refined by quantifying the basin shape and river length errors.

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Section: Resultssupporting

confidence: 56%

How to evaluate the quality of coarse‐resolution DEM‐derived drainage networks

Sousa

Paz

2017

Hydrological Processes

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“…The results indicate that the 3 m grid size is the balance V-A line, whereby DEM resolution does not grossly overestimate and underestimate the reservoir storage capacity as the surface area increases [35]. While the accuracy of DEMs depends on their grid sizes or resolutions, the acquisition technologies, sources of the original data and interpolation methods [18], and that higher resolution DEMs provide more accurate representations of topographic features, [36] found out that much higher improvements in DEM resolutions did not necessarily result into improved watershed hydrologic modeling. This implies, as observed in this study, that grid resolutions of less than 1 m may not only be practically difficult to acquire using terrestrial surveys, but may also not result into better accuracy.…”

Section: Storage Capacity-area Power Relationshipmentioning

confidence: 99%

Evaluation of Multiresolution Digital Elevation Model (DEM) from Real-Time Kinematic GPS and Ancillary Data for Reservoir Storage Capacity Estimation

Ouma

2016

Hydrology

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This study presents the estimation of reservoir storage capacity using multiresolution Real-Time Kinematic Global Positioning System (RTK-GPS) DEM, in comparison with ASTER and contour-derived DEM. Through RMSE comparisons of the elevation point uncertainty and error analysis, the results shows that the RTK-GPS DEM gave the best results for the reservoir capacity-area power curve estimation, defined by a convex slope with an exponential deterministic relationship given by V " 0.09ˆA 1.435 . The results further show the existence an empirical relationship between the reservoir volume certainty and the GPS point density d i as V e " cˆd ρ i . This relationship is dependent on the reservoir terrain, slope and surface area. Validation of the results with in situ data showed the differences between the simulated and observed storage volumes was less than +10%, and using the Nash-Sutcliffe coefficient of efficiency on the storage volumes, an average efficiency of +0.7 on the monthly observed and simulated reservoir storage volume was observed.

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“…The study demonstrated the accuracy of the new elevation data to be even triple the accuracy of the earlier altimetry in the form of ZABAGED® contour lines. The resulting model has a certain dependence on the pixel size of the created DTM (Podhoranyi et al, 2013;Yang et al, 2014). Yang et al (2014) found in their study that the best model when compared with the reference data is not the model created with the smallest pixel resolution (1 meter per pixel), but they recommend lower resolution of 10 meters.…”

Section: Introductionmentioning

confidence: 99%

“…The resulting model has a certain dependence on the pixel size of the created DTM (Podhoranyi et al, 2013;Yang et al, 2014). Yang et al (2014) found in their study that the best model when compared with the reference data is not the model created with the smallest pixel resolution (1 meter per pixel), but they recommend lower resolution of 10 meters. According Podhoranyi et al (2013) the increase in resolution of the input DTM has impact on reducing the extent of the fl ood area.…”

Section: Introductionmentioning

confidence: 99%

Effects of Land Use Changes on the Runoff in the Landscape Based on Hydrological Simulation in HEC-HMS and HEC-RAS Using Different Elevation Data

Divín¹,

Mikita²

2016

Acta Univ. Agric. Silvic. Mendelianae Brun.

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The aim of this paper is to determine the eff ects of land use changes on the runoff in the landscape by means of hydrological modelling. Our partial aim is also to determine the eff ect of diff erent elevation data and defi ne optimal data sources for this modelling. The research was conducted on the Starozuberský stream experimental watershed. For comparing elevation models, three scenarios were developed with diff erent input data. Based on a comparison of these models an optimal data source for hydrological modelling was selected. To simulate the change in land use, we have created two scenarios based either upon the current land use and historical data from the fi ies of the twentieth century. Comparison was carried out using the HEC-HMS so ware interface for rainfall-runoff simulation and HEC-RAS for the fl ooding simulation. Data for the simulation were prepared using the ESRI ArcGIS extensions, namely HEC-GeoHMS and HEC-GeoRAS.

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What is the effect of LiDAR-derived DEM resolution on large-scale watershed model results?

Cited by 80 publications

References 46 publications

How to evaluate the quality of coarse‐resolution DEM‐derived drainage networks

How to evaluate the quality of coarse‐resolution DEM‐derived drainage networks

Evaluation of Multiresolution Digital Elevation Model (DEM) from Real-Time Kinematic GPS and Ancillary Data for Reservoir Storage Capacity Estimation

Effects of Land Use Changes on the Runoff in the Landscape Based on Hydrological Simulation in HEC-HMS and HEC-RAS Using Different Elevation Data

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