Introduction:
I have looked at the spatial distribution of depth to first lava and the spatial relationship between the depth to first lava and the depth to first water. I found that the distance from volcanic centers might affect the depth we find the contact with first lava. I did not find any strong correlation between first water and first lava, but that does not preclude the idea that first water correlates to deeper lava contacts.
Now I want to look at what else might be effecting the spatial distributions of lava in the region. Note, that the techniques I used for looking at lava can also be applied to looking at the spatial distribution for water in the field area.
Figure 1: The style of active faulting in the Pit River Study area (delineated roughly in green). N-S trending faults accommodate dip slip (up-down) motion, while NW-Se trending faults accommodate oblique slip motion (up-down and side to side). Structurally controlled volcanoes often lie at the elbows of intersection between the N-S and NW-SE trending faults. Modified from Blakely et al 1997.
The Northern California Field area lies at the intersection of the Walker Lane Fault Zone, the Basin and Range and the Cascadia subduction zone. For the purpose of this examination I will focus on the relationship between the spatial distribution between Walker Lane style faulting (fig 1) and the spatial distribution of the depth to first water and the depth to first lava in the region.
The topography in the region reflects the interplay between active Walker Lane Style Faulting in the region and the higher frequency volcanism that mutes it. For, example, in the northern portion of the field area, Medicine Lake Volcano, with flanks covered by volcanism less than 10 kyr (fig 2), active faults disappear beneath the volcanic edifice. They do not appear in the topography, but they exist in the subsurface. However, in regions where faults are well expressed, enough displacement has occurred to 1) be resistant to burial by periodic lavas, and 2) to either serve as conduits to lava flow, or to displace lava itself.
The Data:
Figure 2: Map of the Field area with active faults (pink lines), the Pit River (blue line), rough locations of ground water discharge (yellow circles), young lava flows (green outlines) and all of the available well data (blue dots).
The subset of the data we used in figure 2 is depicted in figure 3. Temporally they range from wells dug in the1950s to the present. It is important to note that depths to first water might have changed in the 60 years since the older well logs were recorded. For this reason I did not use many of the older well logs in my analyses.
Figure 3: The center of the township and range sections for the wells used and corresponding depths to first lava. Purple logs are the shallowest and Blue logs are the deepest.
Hypotheses:
Figure 3: Conceptual design for the project. A) Configuration before slip upon the fault. The lava flow is continuous. B) If a normal fault displaces a lava flow, then one side will go down with respect to the other. The lower block experiences deposition, and the development of a soil profile. If enough time has passed, then there will be a difference between the depth to first lava between the upper and lower block.
I predict that faults will run parallel to and coincide with large step changes in the depth to first lava.
If there are no large step changes in depth to first lava, I predict that these changes will be driven by changes in elevation and correspond to channelized lava flows rather than faults.
Methods:
I used the Threshold Kriging function in Arc to make a surface that corresponded to the likelihood of the depth to first lava being less than 30 feet deep. The Kriged surface then interpolates the probability that location at other points in the map correspond to less than 30 feet deep. When the surface has a value of 1, values are close to less than 30ft deep. When it is close to zero, values are greater than 30 feet deep.
I then preformed a confusion matrix to see how my results compared to what I expected. This part I did by eye.
Results:
Figure 4: Kriged Surface with faults superimposed.
| High-Low | Low-Low or High-High | |
| parallel | 257 | 315 |
| perpendicular | 213 | 5 |
Table 1: Corresponding confusion matrix. There were 257 High-Low values that corresponded to parallel faults, but there were 315 Low-Low or High Values that also corresponded to parallel faults. See discussion below.
Figure 5: Kriged surface with contours.
Discussion:
257 out of 790 of the faults were gradient parallel. If, corresponded to step function in kriged depth to first lava. However, many more did not. What is happening here? If you look to figure 5, you can see that while some of the high gradients correspond to rapid changes in elevation. This block is the footwall of a range bounding normal fault. That fault is not mapped because it is no longer active. But it has large amounts of uplift upon it, and likely corresponds to a different lithology entirely and so does not fall into our hypothesis.
If I do this analysis for every lava layer I find, and can correctly link the well logs together, then this analysis could help me constrain slip upon the faults in the region. This information is good for hazards assessment in the region as PG&E has a hydroelectric dam in the area.
Learning outcomes:
Throughout the course of this class, I learned a few of the nuances of R, though my work here has just begun. I also feel like I have a better understanding of how to think about spatial processes, which I why I enrolled in the first place. Future goals include better locating my data in space. This way, many of the techniques I used in this class will pick up on actual processes, and not on the gridded spacing of my data.
Sources:
Blakely, Richard et al. “Gravity Anomalies, Quaternary Vents, and Quaternary Faults in the Southern Cascade Range, Oregon and California: Implications for Arc and Backarc Evolution.” Journal of Geophysical Research: Solid Earth, vol. 102, no. B10, 1997, pp. 22513–22527.
