1986
DOI: 10.3133/ofr86468
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An Analysis of thermal data from the vicinity of Cajon Pass, California

Abstract: Twenty-two heat-flow determinations and eight estimates (from thermal gradients) in the region near Cajon Pass indicate a somewhat more complex thermal regime than was heretofore apparent. At the Cajon Pass site, a combination of Pleistocene-Holocene uplift and erosion, topography, and a steeply dipping but poorly characterized contact between rocks of differing thermal conductivity introduce large uncertainties into the value for regional heat flow to 1.8 km. Heat flow near the San Andreas fault and within th… Show more

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Cited by 9 publications
(7 citation statements)
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“…[13] To compute near-surface heat flow from model simulations, we extract temperatures at 150-300 m below land surface from the simulated steady state temperature fields. This depth range is comparable to that used to determine heat flow in most boreholes for the California data set [Lachenbruch and Sass, 1980;Sass et al, 1986Sass et al, , 1994Sass et al, , 1997Saffer et al, 2003;Fulton et al, 2004] (Table 1). In addition, we remove conductive topographic refraction effects from the simulated heat flow values in order to compare them with the data, which have been previously corrected for these effects [e.g., Fulton et al, 2004].…”
Section: Model Domain and Boundary Conditionssupporting
confidence: 68%
See 1 more Smart Citation
“…[13] To compute near-surface heat flow from model simulations, we extract temperatures at 150-300 m below land surface from the simulated steady state temperature fields. This depth range is comparable to that used to determine heat flow in most boreholes for the California data set [Lachenbruch and Sass, 1980;Sass et al, 1986Sass et al, , 1994Sass et al, , 1997Saffer et al, 2003;Fulton et al, 2004] (Table 1). In addition, we remove conductive topographic refraction effects from the simulated heat flow values in order to compare them with the data, which have been previously corrected for these effects [e.g., Fulton et al, 2004].…”
Section: Model Domain and Boundary Conditionssupporting
confidence: 68%
“…In this region, heat flow ranges from ∼63 to 94 mW m −2 [ Lachenbruch and Sass , 1980; Sass et al , 1997; Fulton et al , 2004] (Table 1 and Figure 2) and varies by up to 20 mW m −2 over distances as small as 5 km. In contrast, surface heat flow data elsewhere in the California data set displays substantially less variability [ Sass et al , 1986, 1994]; for example, in the western Mojave Desert, most heat flow measurements range from 62 to 69 mW m −2 [ Sass et al , 1986]. With the exception of a suggested gradual 20 mW m −2 decrease in surface heat flow along strike of the SAF from Coalinga southeastward to Cholame that may reflect a long‐wavelength regional change in basal heat flux, and which corresponds to a deepening of the base of the seismogenic zone [ Sass et al , 1997; Williams et al , 2004], the observed variations in surface heat flow do not exhibit clear trends with lithology or location.…”
Section: Introductionmentioning
confidence: 99%
“…Mean heat flow in this region is 63 mW m À2 , and is remarkably consistent over a large area [e.g., Lachenbruch and Sass, 1980]. Heat flow measurements used in this study were made at depths ranging from 107-1067 m (Table 1) [Sass et al, 1986]. In general (and where possible), heat flow stations are sited in areas of moderate elevation, relatively flat topography, and in crystalline rock to avoid hydrologic and topographic effects on heat flow.…”
Section: Geologic Setting and Backgroundmentioning
confidence: 75%
“…We consider this 15% range as a probable upper bound to the uncertainty in comparing model results and observations because (1) most heat flow corrections are less than $5% [e.g., Sass et al, 1997] (for example, the smooth topography northeast of the San Andreas Fault in the Mojave study area should result in a relatively small correction) and (2) the 1.5 km topographic sampling we use for our models is comparable to the distance over which much of the topographic heat flow correction is applied. However, because the magnitude of slope orientation and vegetation effects are poorly characterized and can approach several Sass et al [1986] and C. Williams (personal communication, 2001)) are given. Stations are ordered according to location, from SW to NE on the profiles shown in Figures 2b, 4c, 4d, 5b, and 6. percent in some cases [e.g., Blackwell et al, 1980], we use an uncertainty of ±15% for all data points.…”
mentioning
confidence: 99%
“…One core was obtained near the bottom of the well, and a complete suite of drill cuttings was available for measurements of thermal conductivity. Conductivity measurements on chips at 30-m intervals were combined with temperature gradients to produce an estimate of heat flow [Lachenbruch et al, 1986a, b;Sass et al, 1986]. The initial heat flow result of--•90 mW m -2 was surprising in that it was higher than data from shallow (100-200 m) wells in the region, which were tightly grouped about a mean of about 70 mW m -2 [cf.…”
Section: Introductionmentioning
confidence: 99%