Inverting Topography for Landscape Evolution Model Process Representation: 3. Determining Parameter Ranges for Select Mature Geomorphic Transport Laws and Connecting Changes in Fluvial Erodibility to Changes in Climate

Abstract

We review select mature geomorphic transport laws for use in temperate ridge and valley landscapes and compile parameter estimates for use in applications. This work is motivated by a case study of sensitivity analysis, calibration, validation, multimodel comparison, and prediction under uncertainty, which required bounding values for parameter ranges. Considered geomorphic transport formulae span hillslope sediment transport, soil production, and erosion by surface water. We compile or derive estimates for the parameters in these transport formulae. Additionally, we address a common challenge-connecting changes in precipitation distribution to changes in effective erodibility-by using a simple hydrologic model and a method to estimate precipitation distribution parameters using commonly available data. While some parameters are reasonably well constrained, others span orders of magnitude. Some, such as soil infiltration capacity, have a direct physical meaning but are challenging to measure on geologically relevant timescales. Through the process of compiling these ranges we identify common challenges in parameter determination. The issue of comparable units derives from considering an exponent as an empirically inferred coefficient rather than as an expression of a fundamental relationship. The issue of appropriate timescales derives from the mismatch between human measurement and geologic timescales. This contribution thus serves both as a practical compilation for applications and as a synthesis of outstanding challenges in parameter selection for geomorphic transport laws.

Constructing a spatial analysis model in assessing the sensitivity of landscape erosion in mountainous regions of Vietnam

“…Furthermore, most of those 50 studies merely focus on analyzing single landscape factors. Prominently, they are a study on soil erosion following the Universal Soil Loss Equation (USLE) of Wiscehmeir and Smith [2]; a study on soil erosion through the sensitivity of natural environments [3][4][5][6][7][8]; a study on landscape assessment according to quantitative methods with the calculation of erosion indexes following terrain and rainfall [9,10]; a study on the landscape sensitivity in line with space and time based on landscape equilibrium indexes [11,12]; soil erosion indexes were established based on the calculations of potential, practical soil loss indexes, and soil erosion susceptibility (soil erosion and conservation, models of soil erosion and land use, spatial patterns of soil erosion susceptibility) [13][14][15]; approaching landscape analysis in accordance with the analytical hierarchy process (AHP) [16][17][18]; constructing a model calculating erosion rates in terms of landscapes [19][20][21][22][23]; and a study on the geomorphic limitations on landscape sensitivity owing to the climate of tectonically active sites [24][25][26]. It can be seen that the erosion indexes of those studies are derived from only soil erosion or from studying separately on factors that are influential in erosion including terrain, geomorphology, rainfall, and vegetation cover.…”

Projections of Landscape Evolution on a 10,000 Year Timescale With Assessment and Partitioning of Uncertainty Sources

“…Three scenarios are considered, with K increasing by 0%, +14%, and +25% (Barnhart, Tucker, et al., 2020d, their Section 6.3). Representing changes in climate as changes in K reflects propagating changes in local precipitation distributions into effective erodibility changes using a simple hydrologic model (Barnhart, Glade, et al., 2019; Rossi et al., 2016).…”

“…While most of Buttermilk Creek's recent incision has been into the glaciogenic sediments, sandstone bedrock is now exposed in parts of the channel (M. Wilson & Young, 2018). Barnhart, Tucker, et al (2020b, 2020c, 2020d used this geomorphic natural experiment to conceptualize and test a set of 37 alternative Landscape Evolution Models (LEMs), each of which represents a plausible representation of the geomorphic processes for the late glacial to Holocene. LEMs were calibrated by running forward in time from a reconstruction of the 13 ka paleotopography to the present day.…”

Hillslope erosion in a grassland environment: Calibration and evaluation of the SIBERIA landscape evolution model

“…While many LEMs are available, the majority of these have only undergone rudimentary evaluation for their ability to predict erosion and deposition rates and patterns (Willgoose & Riley, 1998; Evans, Saynor, & Willgoose, 1999; Evans et al, 2000; Evans & Willgoose, 2000; Hancock et al, 2000, 2007) as well as limited testing for natural catchments (Schoorl et al, 2004; Hancock et al, 2008; Martinez, Hancock, & Kalma, 2009; Coulthard, Hancock, & Lowry, 2012). All LEMs have their weaknesses and strengths, and a good summary and history can be found in the papers by Tucker (2009), Temme et al (2013), Coulthard & Skinner (2016) Willgoose (2018) and (Barnhart et al, 2020b, 2020c, 2020d). Here we focus on the SIBERIA model, one of the most used, publicly available LEMs.…”

“…Evaluation at millennial time scales involved qualitative and semi‐quantitative assessment (Tucker, 2009; Hancock et al, 2014; Barnhart et al, 2020b,Barnhart et al, 2020d). Landscape predictions were found to qualitatively ‘look’ correct, and the predicted erosion rates were within regional denudation rates.…”