Updating Bathymetric Surveys for Drinking Water Reservoirs

Transcription

1 Updating Bathymetric Surveys for Drinking Water Reservoirs Crystal K. Williams Rick Twait Catherine O Reilly Eric Peterson

2 INTRODUCTION Globally high water demand - Drinking water - Irrigation in agriculture - Power generation Reservoirs used to meet this demand Reservoir lifetime is limited

3 Sediment accumulation Sediment decreases storage capacity and shortens reservoir lifetime Evaluation of reservoir sedimentation is important Imperative to manage surface water resources

4 Methods for estimating accumulations yearly or daily hydrologic records set by geomorphic region land use sediment grain size and distribution Multi-frequency profiling using an echo sounder Bathymetry

5 Bathymetric Maps Practical method for sediment accumulation when previous data exists Bathymetry: measurement of depths of water bodies from the surface (map of the lakebed) Typically generated using point data - Location (GPS) - Depth (elevation)

6 Bathymetric map from data points Create lines/contours representing depths Fill in spaces with depths by creating a raster surface (interpolation)

7 Interpolation to create surface Using known values to estimate the unknown areas in between since estimating, errors are created

8 Interpolation methods Spatial Analyst Toolbox offers the following interpolation methods: - inverse distance weighting (IDW) - kriging - natural neighbor - spline - spline with barriers - topo to raster - trend

9 Interpolation methods Inverse Distance Weighting (IDW) Kriging Natural Neighbor Spline

10 OBJECTIVES 1. To evaluate multiple interpolation methods to determine which method produces the raster that most accurately represents the bathymetric surfaces 2. To determine the current bathymetry of Lake Bloomington and Evergreen Lake - To estimate the volume of sediment that has accumulated in each lake since 1999

11 STUDY AREA

12 METHODS collect point data Collect current data June and July - 4 to 5 days per lake Hanson Engineers Inc Received data as dwg files (AutoCAD) from City of Bloomington - Converted to shapefiles in GIS

13 2014 Equipment: HydroLite-TM set up RTK-GPS SonarMite BT echo sounder SonarMite transducer Trimble GeoExplorer GeoXH

14 Evaluate interpolation methods Import all data into GIS Remove 10% - Subset Features tool in Geostatistical Analyst Run all interpolation methods with 90% - Developed model to facilitate Calculate Root Mean Square Error (RMSE)

15 Model

16 Evaluation method flow chart

17 Calculate Root Mean Square Error (RMSE) original data point (10%) Interpolated data point RRRRRRRR = ii 1 nn (oooooo. ssssss. ) 2 nn Larger RMSE means larger error

18 Density Differences - Section of Evergreen Lake 1999 (Lower density) 2014 (Higher density) Lake Data Year Total Data Points Bloomington Evergreen , , , ,551

19 Lake Bloomington Interpolation RMSE RMSE (ft.) IDW Kriging Natural Neighbor Spline Spline Barriers Topo to Raster Trend Interpolation Method

20 Evergreen Lake Interpolation RMSE RMSE (ft.) IDW Kriging Natural Neighbor Spline Spline Barriers Topo to Raster Trend Interpolation Method

21 Evaluation of Interpolations Probable reason for lower RMSE values in density of points - equipment allowed for more points to be taken in shorter period - higher accuracy of equipment Recommended methods by past bathymetric studies - kriging & natural neighbor Chose spline - had low RMSE values for both lakes and both sets of data - best practice to use same methods when comparing

22 Spline Interpolation Rasters Lake Bloomington Evergreen Lake

23 Problem with these surfaces Lake Bloomington Evergreen Lake

24 Collected Ground Truth Data Absolute Difference from Manual Measurement Lake Point IDW Krig NN Spline Spline B Topo to Raster Bloomington Evergreen

25 Better Interpolation Method Absolute Difference from Manual Measurement Lake Point IDW Krig NN Spline Spline B Topo to Raster Bloomington Evergreen

26 Final Bathymetric Maps Lake Bloomington Evergreen Lake

27 Secondary Output Sediment Accumulation Found Volumes of lakes for 1999 and Surface Volume tool Calculated Difference between years to estimate accumulation Lake Data Year Volume (m 3 ) Bloomington ,900, ,433,000 Evergreen ,892, ,311,000 Difference in Volumes (m 3 ) Percentage of Total Lake Volume Lost 467, % 581, %

28 Sediment volume estimations for lifetime of lakes Lake Bloomington Sediment Volume since 1999 Sediment Volume of Lake s Lifetime Data Year ac-ft. m 3 ac-ft. m ,400 3,004, ,000 2,800 3,472,000 Evergreen ,500 1,872, ,000 2,000 2,453,000

29 Lake Bloomington - Capacity Curve Management Water Surface Elevation (ft.) Capacity (ac-ft.) Evergreen Lake - Capacity Curve Water Surface Elevation (ft.) Capacity (ac-ft.)

30 CONCLUDING REMARKS To create a good bathymetric maps - High density data, many paths (cross sections) - Recommend similar evaluations of methods Ground truth importance - Check instrumentation - Check surface interpolation - Does it represent true conditions?

31 ACKNOWLEGEMENTS Rick Twait City of Bloomington Catherine O Reilly Illinois State University Eric Peterson Illinois State University John Kostelnick Illinois State University - Brian Grebliunas, Matt Meyers, Tom Rodgers, Matthew Dondanville, Troy Olson - Lake Bloomington Courtesy Patrol Staff - Bloomington Water Treatment Plant Employees

32 Thank you Crystal K. Williams