Cesium-137 and Lead-210 in the San Gabriel Mountains, California: Erosion Rates, Processes And Implications.

摘要

Numerous studies have examined the interplay of climate, tectonics, biota and erosion and found that these variables are intertwined in a complicated system of feedbacks and as a result, some of these factors are often oversimplified or simply neglected. To understand the interplay of these factors one must understand the processes that transport or inhibit transport of soil. This study uses the short-lived, fallout-derived, radionuclides 137Cs and 210Pb to identify soil transport processes and to quantify soil transport using the profile distribution model for 137Cs. Using five field sites in the San Gabriel Mountains of California, I address four questions: (1) Is there a process transition between high and low gradient slopes observable with short-lived isotopes? (2) Do convex hilltops reflect short-term equilibrium erosion rates? (3) Do linear transects of pits accurately characterize hillslope averaged erosion rates? and (4) What role does fire play on short-term soil transport and isotope distribution? I find no evidence supporting a process transition from low gradient to high gradient slopes but also find that significant spatial variability of erosion rates exist. This spatial variability is the result of sensitivity of the method to small scale variations in isotopes and indicates that small scale processes may dominate broader scale trends. I find that short-term erosion rates are not at equilibrium on a convex hilltop and suggest the possibility of a headward incision signal. Data from a post-fire landscape indicates that fires may create complications in 137Cs and 210 Pb distribution that current models for erosion calculation do not account for. I also find that across all my field sites soil transport processes can be identified and quantified using short-lived isotopes and I suggest high resolution grid sampling be used instead of linear transects so that small scale variability can be averaged out.