Overview

One striking feature in northwestern Central Valley, California is the uniform spacing between ridges and valleys along hills. Contemporary soil-mantled landscape evolution theory is built based on physics of conservation of mass and geomorphic transport laws. Transport laws include soil transport, fluvial sediment transport, soil production, and landslide transport. As a result, characteristic frequency in landscape may be a result of competitions between environments (e.g. geology, tectonics, climate) and these geomorphic transport laws. Yet, the bedrock interactions to landscape, including lithological differences, bedding orientation, and lithological spacing, have not been explored. Here I propose to utilize high-resolution digital elevation model (DEM), field survey, and 3D numerical models to investigate the ridge-and-valley landscape and how bedrock influences to this type of landscape in northwestern California. 

With ongoing collaboration with groups at UC Berkeley, UT Austin, Vanderbilt University, Simon Fraser University, and Sacramento State University, we investigate a field site in northern California Coast Range in Colusa County. The Mesozoic Great Valley Sequence contains meter-to-kilometer thick siltstone, sandstone, and conglomerate units, and is generally 50°-60° dipping to east. We have conducted several shallow seismic refraction surveys to estimate bedrock depth and seismic velocity along and across ridges in this area. This information helps us understand the bedrock-to-soil processes, local bedrock-type variation influence on sediment flux and soil production, bedrock uplift rate, and the drainage network in this area, which will provide key observations for the development of bedrock contribution to the ridge-and-valley landscape.

In the future, we will continue fieldwork including shallow seismic survey, geomorphologic mapping, and evidences of human impacts that may have changed infiltration and flow pattern in this area. Ultimately we will combine in-situ observations as well as numerical modeling tools to understand evolution from different kind of bedrock to soil and how bedrock type and orientation would influence erosion and sediment transport that shapes landscapes to what it is like today.

We develop a Transdimensional Hierarchical Bayesian (THB) framework with reversible-jump Markov Chain Monte Carlo (rjMCMC) to generate samples from the posterior distribution of velocity structures.