How to evaluate the quality of coarse‐resolution DEM‐derived drainage networks. Issue 19 (1st August 2017)

• Record Type: Journal Article
• Authors: Sousa, Thâmara Martins Ismael; Paz, Adriano Rolim
• Is Part Of: Hydrological processes. Volume 31:Issue 19(2017)
• Page Start: 3379
• Page End: 3395
• Publication Date: 2017-08-01
• Subjects: digital elevation model -- flow direction -- large scale -- river network; Hydrology -- Periodicals; Hydrology -- Research -- Periodicals; Hydrologic models -- Periodicals; Hydrological forecasting -- Periodicals; 631.432
• DOI: 10.1002/hyp.11262
• Languages: English
• ISSNs: 0885-6087

Abstract

Abstract: 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 km 2 ) 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.