A robust, two‐parameter method for the extraction of drainage networks from high‐resolution digital elevation models (DEMs): Evaluation using synthetic and real‐world DEMs

Abstract

[1] In this article, a method for drainage network extraction from high-resolution digital elevation models (DEMs; e.g., those derived from airborne laser swath mapping) is presented, which requires just two user-defined parameters and is capable of handling discontinuous valley networks. The accuracy and robustness of the method are illustrated using synthetic valley networks that mimic the complexities of real landscapes and for which the true drainage network is known exactly by construction. The method involves six principal steps: optimal Wiener filtering to remove microtopographic noise, mapping of the contour curvature, identification of valley heads using a user-defined contour-curvature threshold criterion, routing of a unit discharge of water from each valley head using a multiple-flow-direction routing algorithm, removal of discontinuous reaches from the drainage network using a user-defined discharge-per-upstream-valley-head threshold criterion, and thinning of the valley network to a single pixel width. The method yields accurate results using the same user-defined parameters for the two field sites considered in this study, suggesting that for DEMs with resolution of approximately 1 m, the method has the ability to produce accurate results for a variety of landscapes by using the same parameter values used in this study.

Implementing and Evaluating Variable Soil Thickness in the Community Land Model, Version 4.5 (CLM4.5)

“…Uplands tend to have shallow soil thicknesses, while lowlands have deeper soils. In uplands, soil depths vary from slope to slope because of differences between rates of soil production and erosion, which depend on terrain slope, climate, and rock type (Pelletier and Rasmussen 2009). In principle, variable soil thickness in LSMs should make the models more realistic, but implementation has been impractical because of a lack of global estimates of bedrock depth.…”

“…Instead, localized estimates have been more prevalent. For instance, Dietrich et al (1995), Roering (2008), Rasmussen (2009), andTesfa et al (2009) developed geomorphically based soil depth models, applying them to upland basins.…”

“…Soil thickness is the main determinant of hydrologic response in upland watersheds since thin soils are more likely to produce surface runoff than thicker soils which can store more water (Pelletier and Rasmussen 2009). Soil depth has been shown to control infiltration rates in a desert basin in Nevada (Woolhiser et al 2006).…”

“…Building upon the partial success of previous localized attempts at soil depth generation, Pelletier et al (2016) have developed a 30-arc-s (;1 km) global dataset of the thickness of relatively porous, unconsolidated sediments over bedrock (essentially soil thickness) based on topographic, geologic, and climate data. Separate models for upland hillslopes and valley bottoms/lowlands are utilized.…”

“…Lowland soil thickness is simply predicted using a model that is based on topographic curvature that is calibrated with high-density well data from four U.S. states. Valley bottoms that exist in upland landscapes are determined using topographic analysis (Pelletier 2013), and the thickness of soil/alluvium for a particular valley bottom is predicted from the curvature of the valley bottom and the gradient of the hillslopes flanking the valley. Soil thickness on the remaining upland hillslopes is then predicted by a geomorphic model that balances soil production with erosion.…”