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<br /> CASS COUNTY ROADWAY 18 EXTENSION STUDY – CASS COUNTY, <br />ND <br /> <br />7 <br />3.5 EXISTING ENVIRONMENTAL FEATURES <br />The wetlands for the study area were reviewed using data from the National Wetlands Inventory available <br />from the United States Fish and Wildlife Service. Two figures are provided with Figure 3 showing the <br />palustrine and riverine wetlands that are located within and near the study area and Figure 4 showing a <br />more detailed view of the palustrine and riverine wetlands within the study area. The project study area <br />has the Sheyenne River and the Sheyenne River tributary for flowing water. There are three primary <br />locations for palustrine wetlands located in sections 23 and 26 of the Normanna Township. As shown in <br />Figure 4, the locations that are within the roadway ditch section that are classified as wetlands are located <br />in the section from the Sheyenne River bridge to the west approximately a 0.5 mile. <br />3.6 2018 TRAFFIC VOLUMES <br />Traffic volumes at two segments of 52nd Street SE and one segment of CR 18 were collected Tuesday <br />May 15th to Friday May 18th and Monday October 15 to Friday October 19 of 2018. The traffic volumes <br />were counted for approximately 72 consecutive hours at all locations. The Kindred Public School system <br />was in session when the traffic volumes were collected. The traffic volumes were reviewed for any <br />differences, and an average of the two counting periods was determined. The traffic volumes included in <br />this report are Average Annual Daily Traffic (AADT) volumes that are based on the actual number of <br />vehicles counted during the two count periods and then adjusted to account for daily and seasonal <br />variations. AADTs provide the average volume of traffic using the roadway throughout the year. Actual <br />traffic counts on random days may be either above or below the AADT, but the AADT provides an <br />average for the entire year. Intersection turning movements were not counted as a part of this study. <br /> <br />The AADTs for the three count locations are shown in Figure 5, Figure 6, and Figure 7. The AADTs for <br />the spring and fall ranged from 86 and 136 vehicles per day (VPD) on CR 18 near CR 17 to 115 and 197 <br />VPD on the west end of the study area. The traffic consisted of 20 to 25 percent heavy vehicles (vehicles <br />with more than 2 axles) throughout the study area. The heavy vehicle percentages were slightly lower on <br />the existing CR 18 section. It is important to note that the traffic counts were taken while agricultural <br />producers were starting to plant and harvest the agricultural fields in the area surrounding the study area. <br />The travel direction distribution at the count locations was approximately 55 to 60 percent travelling <br />westbound to approximately 40 to 45 percent travelling eastbound during the spring count period and 50 <br />percent eastbound and westbound during the fall count period. The directional distribution may signal <br />that vehicles are traveling west to Kindred or elsewhere on 52nd Street SE, but returning to their residence <br />or place of origin by another route such as North Dakota 46 and a north-south county or township <br />roadway. <br /> <br />The peak hour, the highest volume of four consecutive 15-minute counting periods, for all locations was <br />consistent between 7:00 am and 8:00 am with minor 15-minute adjustments for the morning period of <br />each day. The afternoon/evening peak hour was not as consistent as the morning peak hour for all three <br />locations. The PM peak hour was typically either 3:30 pm to 4:30 pm or approximately around the 5:00 <br />pm hour. A potential reason for the variation of the evening/afternoon peak hour may be due to rain <br />events on one of the count days and the resulting saturated condition of the gravel roadways. Although, <br />there is not enough evidence to draw a conclusion that the condition of the roadway impacts the traffic <br />volume on the roadway. The peak hours from the fall traffic counts were similar in the hour that had the <br />peaking volumes to the spring data.