DERIVATION OF “DEEP-TIME” FAULT-SLIP HISTORIES FROM DATED AND DISPLACED LANDFORMS TO TEST FOR SECULAR VARIATION IN SLIP

Morphochronologic investigations of faulted and dated landforms such as terrace risers can be used to extend fault records to “deep-time” (thousands to tens of thousands of years) because the geomorphic landscape is preserved beyond the timescale usually recorded in paleoseismic fault trenching studies. But the method by which morphochronologic datasets should be analyzed, especially to test whether faults slip at uniform or temporally varying rates, is unclear. To address this problem, we have developed a Monte Carlo analysis technique for measuring the distribution of geologically reasonable fault slip histories for populations of dated and displaced landforms that share common histories. The analysis results in (1) a precise average slip rate and (2) a fault-slip history from which uniformly slipping versus secularly varying slip scenarios can be discriminated. We applied this new analytical method to published morphochronologic datasets of faulted late Quaternary terrace risers from the Kunlun Fault (northern Tibet, China) and the Awatere Fault (South Island of New Zealand) to assess the extent to which the modeled average slip rates match the previously reported values and also to examine if previous claims of uniform slip rate are supported by the data. Analysis of datasets from the Kunlun Fault yields average slip rates of 10±2 and 5±1 mm/yr, for the central and eastern reaches, respectively. These results match previously published slip rates and suggest that these fault reaches have slipped uniformly over the late Quaternary. In contrast, analysis of the Saxton River site dataset along the Awatere Fault reveals a deceleration in slip rate in the mid Holocene from 6±2 to 3±1 mm/yr. This result contradicts previous interpretations of uniform slip along the Awatere Fault and provides compelling evidence for secular variation in slip along this fault. This method of analyzing morphochronologic datasets represents a major step forward toward quantitatively distinguishing temporally uniform and secularly varying “deep time” fault-slip records.