Graduate Thesis Or Dissertation
 

Surface erosion from a forest road, Polk Inlet, Prince of Wales Island, Alaska

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  • Rainfall, discharge, traffic, and suspended sediment were monitored for a period of 4.5 months at three locations on a secondary haul road at Polk Inlet, Alaska to determine the important processes and variables involved in surface road erosion for this area. Three sites all less than 500m² and within 5 kilometers of each other on the same road were chosen to be instrumented for monitoring. The proximity of the sites to each other resulted in the sections all being nearly identical in age, topographical location, aspect, elevation, and construction materials. Also, the sites were subjected to the same traffic amounts of approximately 3 to 4 loaded logging trucks per day plus other light vehicles. Maps were developed of the sites which helped determine the source areas for each one. The gradients of sites 2 and 3 were approximately 7%, and the gradient of site 1 was 10%. Each study site was equipped with a flume, pressure transducer, datalogger, and pumping sampler to collect data on discharge and suspended sediment. Sites 1 and 3, had rain gages connected to the dataloggers which recorded 5 minute rainfall intensities. Hourly suspended sediment samples were collected at each site. An infrared traffic counter was used to count the daily traffic amount. An infiltration rate for the road was determined to be 0.9mm/hr using a simple water balance method and also by determining the minimum amount of rainfall to initiate runoff. The infiltration rate was used in development of representative hydrographs for the three sites. The runoff response of the sites were very similar when normalized to an area of 280 m². The precipitation catches for the two gages were very similar with precipitation amounts of 893 mm for site 1 and 975 mm for site 3 during 89 days of record. Several regression analyses were completed for both hourly and storm data to determine which variables and technique would be best for estimating total sediment production. The method that proved to be the best for determining hourly production was to multiply the hourly sediment concentration by the average hourly discharge to obtain a total estimated sediment weight produced for that hour. During multiple regression analysis, all three sites and the combined model had rainfall as the most important variable. The variable that averaged the number of axles per day since the last runoff event was also found to be significant in the combined model. Qualitative variables were used to determine that timing of the events may have an influence on the sediment production. The total storm sediment production was determined by summing the total hourly sediment weights for a given storm. The regression analyses found rainfall to be the most significant of ten variables for the total storm sediment production. A comparison of all the different models coefficients was developed. The multiple regression model with total storm rainfall, a qualitative variable for gradient, and axles per day was found to have the best coefficient of determination of 0.66 for the combined data of all the sites. The model for site 3 of axles per day and total storm rainfall was found to have the highest coefficient of determination, R² = 0.85. The simple linear regression model of log of total sediment yield/km of road to total storm precipitation was used to estimate the annual sediment production from a kilometer of road at Polk Inlet. The annual precipitation data was from a gage located about 16 kilometers northeast of Polk Inlet. The annual road surface sediment erosion estimate is 8.1 tonnes/km of road. A comparison of other studies shows this to be similar to other locations in the United States and areas of New Zealand. Several assumptions were made and the resulting limitations are described for this estimate. Any use of this estimate or equation for sites without very similar characteristics would not be advised. Future studies are in progress to expand the understanding of some of the other variables not accounted for in this study.
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