The context:
For this exercise, I wanted to figure out if there was a relationship between the temporal pattern of peak discharge in my study creeks and the temporal pattern of grain size distributions. The temporal pattern of grain size distributions could help tell a story about the interplay between hillslope and alluvial process and the forces involved in shaping and stabilizing the streams. One might predict that changes in grain size distribution might be related to extreme events. Large events could associated with debris flows which might reduce sorting while more moderate flow events could increase sorting.
The data:
Pebble counts were conducted in conjunction with cross section surveys at five reaches between 1995 and 2011. They show both the median (D50) and standard deviation of grain size varying over time.
During this time period, two different cross section sampling methods were used, depending on the year. In one method, every cross section in a given year was surveyed. In another method, the only cross sections sampled were ones in which the field crew thought that the creek bed had changed. Because of this, the grain size samples in some year are incomplete and biased towards conditions that favor visible change.
The graphs below show the mean of the D50 and mean of the standard deviation for each set of cross section for each year sampled in subfigure a. The error bars show standard error. The faded points represent years where the field crew only sampled a subset of the cross sections. Subfigure b shows the area-normalized annual peak discharge for the stream gauges on Mack and Lookout Creek. Cold Creek is ungauged.
These figures imply that most reaches were the least sorted in 1997, the year after the flood of record, followed by various decreases and increases over time.
The questions
I asked the following questions to try to understand the relationship between peak flow and grain size distribution:
- Is the standard deviation of grain size in a given water associated with the peak flow from that water year?
- Is the standard deviation of grain size in a given water associated with the peak flow from the previous water year?
- Is the change in standard deviation of grain size between two years associated with the largest peak flow from the interceding years?
- Is the change in D50 between two years associated with the largest peak flow from the interceding years?
The methods and results
I used simple linear regression to relate each of these variables and took the R2 value to represent how much of the sediment distribution variability each variable might explain. The results were negative in all cases.
1.
SITE Rsquared
1 LOL 0.00983
2 LOM 0.00320
3 MAC 0.0340
4 MCC 0.106
2.
SITE Rsquared
1 LOL 0.0546
2 LOM 0.0297
3 MAC 0.0191
4 MCC 0.217
3.
SITE Rsquared
1 LOL 0.0845
2 LOM 0.0718
3 MAC 0.0842
4 MCC 0.0852
4.
SITE Rsquared
1 LOL 0.0440
2 LOM 0.0252
3 MAC 0.0553
4 MCC 0.00688
The answer to these questions all appear to be no – clearly hydrology has some impact on grain size distributions, but the relationship may be too complicated to address using a single predictor variable and limited data.
Arianna, this is a good first step toward using the grain size information. One implication of the findings is that averaging the grain size information throughout a cross section (or throughout a reach) obscures the processes that alter grain size. Thus, it would be important to overlay a map of the channel characteristics on the grain sizes and sub-sample grain sizes according to the channel feature: active channel (pool, or riffle?); gravel bar; etc. I’ve sent you the historical channel maps of LOL starting in the 1970s and you could use them to do this for that reach.