Birr - Identifying Critical Portions of the Landscape


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  • Critical area = disproportionate flow/loads. Nothing new have used HEL for targeting purposes, etc but largely based on qualitative interpretations, this enables us to establish a standardized approach that can be quantified. Also identifies areas that may not be necessary to change management practices. Index not used for quantitative predictions but rather establish relative differences and aid in targeting and increase efficiency of limited conservation dollars.
  • This includes features such as gullies. It is believed that LIDAR data will eventually become available statewide over time.
  • Birr - Identifying Critical Portions of the Landscape

    1. 1. Identifying Critical Portions of the Landscape for Water Quality Protection Using Terrain Attributes Jake Galzki, David Mulla, Joel Nelson Department of Soil, Water, and Climate University of Minnesota Adam Birr and Kevin Kuehner Minnesota Department of Agriculture
    2. 2. Terrain Analysis - DEM <ul><li>Use of a (Digital Elevation Model) DEM to model the landscape. </li></ul><ul><li>Quantitative approach to representing features on the landscape. </li></ul><ul><li>Accurately characterize large areas quickly. </li></ul><ul><li>Describe, analyze, and interpret any topographically-related feature: soils, vegetation, wildlife, etc. </li></ul>
    3. 3. Digital Terrain Analysis Overview Example Point Elevations with GPS DEM Terrain Attributes Spatial Interpolation Attribute Calculation
    4. 4. Terrain Attributes <ul><li>Divided into primary and secondary (compound) attributes. </li></ul><ul><li>Primary attributes are calculated directly from the elevation data. </li></ul><ul><ul><li>Examples: Aspect, slope, catchment area, profile curvature, etc. </li></ul></ul><ul><li>Compound attributes involve combinations of primary attributes and are indices that describe the spatial variability of specific process occurring in the landscape such as the potential for sheet erosion (Moore et al., 1991). </li></ul><ul><ul><li>Examples: Wetness index, Stream power index, etc. </li></ul></ul>
    5. 5. Slope Gradient Primary <ul><li>Describes overland and subsurface flow velocity and runoff rate. </li></ul><ul><li>Slope quantifies the maximum rate of change in value from each cell to its neighbors. </li></ul>
    6. 6. Slope Blue Earth County Minnesota Beauford Sub-Watershed High Low
    7. 7. Slope Curvature Primary <ul><li>Plan Curvature: measured perpendicular to the direction of descent. </li></ul><ul><li>Describes converging/diverging flow. </li></ul><ul><li>Profile Curvature: measured in the direction of maximum descent or aspect direction. </li></ul><ul><li>Measure of flow acceleration, erosion/deposition rate. </li></ul>
    8. 8. Plan Slope Curvature Profile Convex Concave
    9. 9. Specific Catchment Area (SCA) Primary <ul><li>Measure of surface or shallow subsurface runoff at a given point on the landscape. </li></ul><ul><li>Combines the effects of upslope surface drainage area and convergence of runoff. </li></ul>
    10. 10. Stream Power Index (SPI) Secondary <ul><li>Measure of the erosive power of overland flow. </li></ul><ul><li>Combines specific catchment area with slope. </li></ul><ul><li>Steep slope with large drainage areas result in a high value for SPI. </li></ul><ul><ul><li>Indicator of where gullies may form in a field. </li></ul></ul>
    11. 11. Terrain Analysis Applications <ul><li>Why do we care, and what can we do with it? </li></ul><ul><li>Many applications in which terrain analysis can be very useful: </li></ul><ul><ul><li>Soil Mapping; </li></ul></ul><ul><ul><li>Surface Hydrology/Water Quality; </li></ul></ul><ul><ul><li>General Land-Use Planning; </li></ul></ul><ul><ul><li>Natural Disaster Control and Relief; </li></ul></ul><ul><ul><li>Wildlife Biology; </li></ul></ul><ul><ul><li>Soil Conservation and Planning; </li></ul></ul><ul><ul><li>Precision Management; </li></ul></ul><ul><ul><li>Forest Site Assessment; </li></ul></ul><ul><ul><li>Viewshed Analysis. </li></ul></ul>
    12. 12. Applications of Digital Terrain Analysis <ul><li>The reduction of nonpoint source pollution loads in agricultural watersheds is dependent on the implementation of BMPs in critical source areas. </li></ul><ul><li>Defining critical source areas is a challenge due to the hydrologic complexity and natural variability that occurs across the landscape. </li></ul><ul><li>Terrain attributes can be used to assist water resource managers in identifying critical source areas. </li></ul><ul><li>LiDAR data can greatly enhance our ability to identify the critical source areas. </li></ul>
    13. 13. Courtesy of the Brown, Nicollet, Cottonwood Water Quality Board
    14. 14. Characteristics of Digital Terrain Analysis <ul><li>Sacrifices physical sophistication to allow simple calculations to develop estimates of soil moisture patterns in the landscape. </li></ul><ul><li>Input requirements are consistent with the level of data available to water resource managers and are appropriate for the precision with which many management questions need to be and can be answered (Barling et al., 1994). </li></ul><ul><li>Several studies have demonstrated the use of topographic indices to characterize the spatial distribution of soil moisture and soil mapping components controlled by soil hydrology (Bell et al., 1994; Thompson et al., 1998; Fried et al., 2000). </li></ul>
    15. 15. Clean Water Legacy Pilot Study <ul><li>Objective is to develop a tool that uses terrain attributes to identify critical source areas vulnerable surface water runoff. </li></ul><ul><ul><li>Focus primarily on near-stream features in the uplands. </li></ul></ul><ul><li>Pilot studies were conducted in two watersheds with existing LiDAR data: </li></ul><ul><ul><li>Beauford Ditch Watershed (Blue Earth County) </li></ul></ul><ul><ul><li>Seven Mile Creek Watershed (Nicollet County) </li></ul></ul>
    16. 16. Overview of Methods <ul><li>Calculated a suite of primary and secondary terrain attributes in the pilot watersheds. </li></ul><ul><li>Conducted a field survey to relate terrain attributes to critical source features in the field. </li></ul><ul><li>Identified terrain attributes that are of greatest use and used statistics to define threshold values. </li></ul>
    17. 17. Beauford Watershed – 30m DEM
    18. 18. Beauford Watershed – 3m LIDAR DEM
    19. 19. Beauford Watershed – 3D 30m DEM
    20. 20. Beauford Watershed – 3D 3m LIDAR DEM
    21. 21. Field Surveys <ul><li>Handheld Pocket PC with WAAS GPS. </li></ul><ul><li>Field Mapping Software. </li></ul><ul><li>Tape Measure. </li></ul><ul><li>Digital Camera. </li></ul><ul><li>Compass. </li></ul><ul><li>Log book. </li></ul>
    22. 22. Example: Using Specific Catchment Area to Identify Gullies Belle Creek Watershed (Goodhue County)
    23. 23. Example: Using Specific Catchment Area to Identify Gullies Seven Mile Creek Watershed (Nicollet County)
    24. 24. Example: Using Specific Catchment Area to Identify Gullies Seven Mile Creek Watershed (Nicollet County)
    25. 25. Example: Using Specific Catchment Area to Identify Gullies Seven Mile Creek Watershed (Nicollet County)
    26. 26. Example: Stream Power Index to Identify Gullies Seven Mile Creek Watershed (Nicollet County)
    27. 27. Sediment Delivery Potential Courtesy of the Brown, Nicollet, Cottonwood Water Quality Board
    28. 28. Courtesy of the Brown, Nicollet, Cottonwood Water Quality Board
    29. 29. Example: Using Specific Catchment Area to Identify Critical Source Areas Beauford Watershed (Blue Earth County)
    30. 30. Example: Using Specific Catchment Area to Identify Critical Source Areas Beauford Watershed (Blue Earth County)
    31. 31. Example: Using Specific Catchment Area to Identify Critical Source Areas Beauford Watershed (Blue Earth County)
    32. 34. Stream Power Index One-Way ANOVA of mean values p = 4.3x10 -8 95% C.I. Field Verified Gully Random Point SPI
    33. 35. Validation <ul><li>Field verified features corresponded to the highest values of Stream Power Index in each watershed. </li></ul><ul><li>Beauford is a flatter watershed than SMC so inclusion of slope in the SPI calculation did not significantly improve the predictive power of the attribute. </li></ul>67 85 Seven Mile Creek 88 89 Beauford Avg. SCA Percentile Avg. SPI Percentile Watershed
    34. 36. Validation Seven Mile Creek <ul><li>Although not a quantitative assessment of delivery potential, values suggest that there is a relationship to the terrain attribute value and the magnitude of the erosion feature. </li></ul>72.8 Low (SDP = 1) 83.8 Moderate (SDP = 2) 97.4 High (SDP = 3) Avg. Percentile of SPI Sediment Delivery Potential
    35. 37. Validation Seven Mile Creek <ul><li>65 of 83 gullies in the watershed were identified using the top 15% of SPI values. </li></ul><ul><li>31 of 32 largest gullies identified in the field were identified using the top 15% of SPI values. </li></ul>43 No Feature 18 65 Total 12 17 Low (SDP = 1) 5 17 Moderate (SDP = 2) 1 31 High (SDP = 3) Not Identified Identified Sediment Delivery Potential
    36. 38. Validation Beauford Ditch <ul><li>Using side inlet size as a surrogate for the potential for runoff, the values suggest there is a relationship to the Stream Power Index based on the distribution of values in the watershed. </li></ul>81 Small (4 – 12 in.) 93.3 Medium (14 – 18 in.) 98.9 Large (24 – 36 in.) Avg. Percentile of SPI Side Inlet Size
    37. 39. Cost Benefits of Terrain Analysis Seven Mile Creek Watershed <ul><li>Walking survey took 10 days and about 300 labor hours with 3 people. </li></ul><ul><li>Equip. and mileage cost= $2,500 </li></ul><ul><li>Labor cost = $7,000 </li></ul><ul><li>Total cost = $9,500 or about $413/ditch mile </li></ul><ul><li>It is estimated that it would take about 10-12 years at a cost of about $100,000-$120,000 in labor to conduct the same survey for the rest of the County. </li></ul><ul><li>Source: Brown Nicollet Cottonwood Water Quality Board. </li></ul>
    38. 40. Conclusions <ul><li>Terrain attributes such as Specific Catchment Area and the Stream Power Index can be used to identify critical source areas of runoff and sediment transport in upland areas. </li></ul><ul><ul><li>The percentile distribution of terrain attributes in a watershed can be used to identify the location and size of these features (85 th percentile may not be applicable in other watersheds). </li></ul></ul><ul><li>Further work is needed to determine the applicability to other regions of the state. </li></ul><ul><li>Water quality monitoring data is needed to further explore relationships to the terrain attribute values. </li></ul>
    39. 41. Pilot Study: Final Report (to be completed by 6/30/09) <ul><li>A methodology for identifying the critical source areas that is applicable to broad areas of the Minnesota River Basin with similar characteristics as the pilot watersheds. </li></ul><ul><ul><li>Will explore applicability to other regions as data becomes available. </li></ul></ul><ul><li>Goal is that the methods could be utilized by various groups in impaired watersheds for developing BMP implementation strategies. </li></ul><ul><li>Hope to provide formal training in the near future! </li></ul>
    40. 42. <ul><li>Questions? </li></ul>