The Role of Sediments and Aquatic Plants in the Nutrient Budget o

University of Washington Tacoma UW Tacoma Digital Commons GIS Certificate Projects Urban Studies 6-1-2011 The Role of Sediments and Aquatic Plants in the Nutrient Budget of Spirit Lake at Mount St Helens, WA Laura Alskog Follow this and additional works at: https://digitalcommons.tacoma.uw.edu/gis_projects Part of the Urban, Community and Regional Planning Commons, and the Urban Studies and Planning Commons Recommended Citation Alskog, Laura, "The Role of Sediments and Aquatic Plants in the Nutrient Budget of Spirit Lake at Mount St Helens, WA" (2011) GIS Certificate Projects 35 https://digitalcommons.tacoma.uw.edu/gis_projects/35 This GIS Certificate Project is brought to you for free and open access by the Urban Studies at UW Tacoma Digital Commons It has been accepted for inclusion in GIS Certificate Projects by an authorized administrator of UW Tacoma Digital Commons Laura Alskog- GIS Certificate and Environmental Science Programs, University of Washington, Tacoma Figure Kriging interpolation of sediment phosphorus concentrations derived from sampling point data The 1980 eruption of Mount St Helens caused the bathymetry of Spirit Lake to change drastically, resulting in an increase in surface area and a decrease in average depth Subsequently, Spirit Lake is experiencing an increase in productivity This analysis examines concentrations of carbon, nitrogen and phosphorus obtained from sediment samples collected over the summer of 2010, as well as aquatic plant height data, in order to identify sources of the lake’s increasing productivity The results of these analyses will be used as part of a larger nutrient cycling model examining changes in the lake over time Figure Zonal statistics for carbon concentrations in parts per million for each 200 meter buffer zone for all calculated drainage basins BASIN 10 11 12 13 14 15 16 17 18 19 AREA 54026.5 61468.9 59263.7 50443.1 42449.4 63122.7 53475.2 3307.7 55680.3 60641.9 71392.1 85725.6 54302.1 9096.3 44930.2 65603.5 48513.6 30596.6 58161.1 MIN 3862.5 3838.2 6604.1 9581.0 14612.2 6820.8 7608.7 22864.3 21348.2 20316.4 34219.5 38655.2 36495.4 37439.6 37280.6 33499.6 11915.4 18119.2 7796.0 MAX 11991.4 6823.8 9846.9 13654.1 15739.9 15407.9 10340.8 24704.2 22645.7 24654.4 36031.0 40459.4 38678.4 38680.1 38987.7 36354.7 19204.2 19263.4 8970.1 RANGE 8128.9 2985.6 3242.7 4073.2 1127.6 8587.1 2732.0 1839.9 1297.4 4338.1 1811.6 1804.2 2183.0 1240.6 1707.1 2855.1 7288.8 1144.2 1174.1 MEAN 6641.9 5337.8 8365.0 11655.6 15265.7 12224.1 9106.1 24295.1 22027.8 23134.5 34940.5 39647.7 37807.8 38223.7 38107.6 34979.3 17817.9 18636.4 8297.9 STD 2260.6 827.6 927.6 1122.8 267.7 2041.9 676.7 519.8 343.3 1049.4 440.4 428.7 544.2 320.4 378.1 767.5 2015.8 285.3 309.7 Figure Kriging interpolation of nitrogen concentrations derived from sediment sampling data Nutrient concentration results and GPS sediment sampling location data were added to ArcMap and joined The resulting table was added as a layer as XY data Kriging Interpolations were done for Carbon, Nitrogen and Phosphorus concentrations for the lake in total A bathymetric point shapefile was obtained from PSU and was interpolated using IDW Field calculator was used to calculate depth in meters from the given the elevation attribute determine mean plant height, a point shapefile containing canopy heights was manipulated to exclude any values over meters to eliminate inaccuracies caused by logs still lodged in the lake floor from the eruption Next, an IDW interpolation was performed on the plant height attribute Using the bathymetry layer reclassified into photic (≤10m deep) and sub-photic (≥10 m deep) zones, zonal statistics were run to determine total lake area per zone as well as average plant heights per zone Figure Plant heights in the lake’s photic zone, which includes areas of lake less than or equal to 10 meters in depth Figure 10 Zonal statistics for nitrogen concentrations in parts per million for each 200 meter buffer zone for all calculated drainage basins Figures Zonal statistics for phosphorus concentrations in parts per million for each 200 meter buffer zone for all calculated drainage basins VALUE 10 11 12 13 14 15 16 17 18 19 AREA 56720 63808 62464 51584 44544 63456 57088 1744 58368 64480 71056 91248 64080 3728 51760 70144 50544 36704 63312 MIN 7.97 8.21 8.82 8.87 8.44 8.44 8.62 12.17 12.88 12.18 14.09 14.17 13.90 14.04 13.94 13.31 8.68 9.73 7.27 MAX 8.46 9.09 9.33 9.29 8.74 9.22 9.93 12.91 13.13 12.90 14.39 14.73 14.34 14.17 14.47 13.90 10.25 10.34 7.51 RANGE 0.49 0.89 0.51 0.42 0.30 0.78 1.31 0.74 0.25 0.73 0.30 0.55 0.44 0.13 0.54 0.59 1.58 0.61 0.24 MEAN 8.20 8.73 9.14 9.11 8.58 8.92 9.32 12.65 13.00 12.55 14.23 14.48 14.16 14.11 14.19 13.64 9.90 9.98 7.38 STD 0.12 0.18 0.13 0.10 0.08 0.16 0.29 0.16 0.06 0.16 0.06 0.14 0.10 0.03 0.15 0.15 0.44 0.21 0.06 these entry points in which nutrients can be attributed to the surrounding drainage basin areas Zonal statistics were run to determine C, N, P values within each buffer per drainage basin This analysis tells us how much C, N, and P are being contributed to the lake by each basin in the surrounding watershed To Figure Mean phosphorus concentrations per buffer zone obtained from zonal statistics output Figure Mean carbon concentrations per buffer zone obtained from zonal statistics output BASIN 10 11 13 16 17 18 19 AREA (m) 47780 64447 62003 51780 60003 52225 1111 56003 61558 69781 44447 66670 47336 32224 60892 MIN 159 91 481 707 537 556 663 1293 661 1236 1199 1051 246 445 41 MAX 391 518 818 1057 1238 658 1068 1459 1195 1338 1305 1193 463 527 60 RANGE 232 427 336 349 701 102 405 165 534 102 106 142 218 82 20 MEAN 225 294 674 865 900 612 846 1411 837 1287 1258 1125 419 479 49 STD 56 119 88 93 184 29 151 41 105 25 26 38 55 26 Figure 11 Mean nitrogen concentrations per buffer zone obtained from zonal statistics output Figure Kriging interpolation of sediment carbon concentrations derived from sediment sampling data Figure Zonal statistics for plant heights in photic and subphotic zones These plant heights and area totals will be used to determine total plant nutrients in each zone as well as total nutrient concentrations in lake sediment Figure Bathymetry of lake classified in meter increments ZONE To calculate nutrient concentrations in immediate areas surrounding determined watershed drainage basin entry points in order to identify major source areas of nutrient input To create surfaces of sediment Carbon, Nitrogen, Phosphorus and plant height to determine total nutrients in the lake sediment as well as photic zone VALUE COUNT Photic (≤ 10m) 42455 Sub-Photic (≥ 10m) 61201 AREA MIN MAX RANGE MEAN STD SUM 4245500 0.0000 1.2161 1.2161 0.2377 0.13807 10093.2 6120100 0.0382 1.9647 1.9264 0.3178 0.12559 19448.9 In order to classify regions of the lake with nutrient inputs broken down by drainage basin, the Spatial Analyst hydrology tools Flow Direction and Flow Accumulation were used together with a bare earth LiDAR layer, and pour points - a single entry point in which the majority of watershed streams enter the lake – was created 200 meter buffer zones were then created around The outputs of these analyses will be used to determine total C, N and P due to plant biomass as well as total C, N and P in the lake sediment by volume These results will be used in conjunction with land cover data per drainage basin in order to identify sources of high nutrient input in the surrounding areas NAD_1983_UTM_ZONE_10N WAGDA, Portland State University, Bellarmine High School Thank you to Professor Matthew Kelley, Danielle Dahlquist, Felix Wong and Max Mousseau for the support, direction and good times together working on this project Thank you to Professor Jim Gawel for overseeing and providing guidance and direction Thank you to Gregory Lund, Portland State University and Bellarmine High School  ... Wong and Max Mousseau for the support, direction and good times together working on this project Thank you to Professor Jim Gawel for overseeing and providing guidance and direction Thank you... data, in order to identify sources of the lake’s increasing productivity The results of these analyses will be used as part of a larger nutrient cycling model examining changes in the lake over... Alskog- GIS Certificate and Environmental Science Programs, University of Washington, Tacoma Figure Kriging interpolation of sediment phosphorus concentrations derived from sampling point data The