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

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 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.

Technical note: Comparing three different methods for allocating river points to coarse-resolution hydrological modelling grid cells

“…Several previous studies have stressed the importance of considering the consistency of watershed contours for the evaluation or optimisation of upscaling or allocation methods (Davies and Bell, 2009;Li and Wong, 2010;Sousa and Paz, 2017). Method 3 is similar to Method 1, except that it is not only based on the comparison between upstream watershed surfaces but also between upstream watershed contours.…”

“…Visual inspections were performed to identify obvious inconsistencies between coarseand high-resolution river networks. To reduce these inconsistencies automatically, additional criteria have been proposed to complement the UPA criterion, such as the mean distance between river networks and the percentage within a buffer (Davies and Bell, 2009), the correctness index and the figure of merit (Li and Wong, 2010), and the watershed delineation percentages of consistency (Sousa and Paz, 2017).…”

Research on design method for the blue-green ecological network system to deal with urban flooding: A case study of Charleston Peninsula

“…In the next step, gIS hydrological analysis was performed using DEm data with a precision of 3.0 m downloaded from the NOaa website to establish an overall understanding of the basic hydrological characteristics of the peninsula. Digital elevation models (DEm) are widely used in various environmental studies and are commonly used to obtain information on flow directions, flow accumulation, drainage networks, and watershed partitioning [12]. hydrologic analysis tools in aRcgIS software are used to carry out filling analysis, define flow direction, capture river network outlets, extract flow network and flow network classification, etc.…”

The Comparison of Drainage Network Extraction Between Square and Hexagonal Grid-Based Dem

“…So, the extraction of drainage channels relies not on the isolated elevation sampling points but on the spatial relationship between these points (Vaze et al, 2010). However, traditional researches have regarded data source, resolution and interpolation method as main factors to measure the extraction accuracy (Sousa et al, 2017;Ariza-Villaverde et al, 2015;Woodrow et al, 2016). They ignore the impact of different shape of regular grid on terrain surface representation of DEM, which plays a role in results of streaming extraction.…”