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Join us for an informative session to learn about the CIG Specialist program and explore the digital watershed and high impact targeting applications. Lunch will be provided.
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CIG SpecialistIntroductory MeetingWednesday, December 20th, 2006Computer Lab Room 105Farrall Agriculture Engineering HallMichigan State UniversityEast Lansing, MI
Agenda 10:00 – 10:15 Opening Remarks by IWR and MDA Staff 10:15 – 10:25 CIG Specialist Introductions 10:25 – 11:00 Digital Watershed – IWR’s On-line Watershed Mapping Application Overview Hands-on Exercise Question and Answer 11:00 – 11:10 Break 11:10 – 12:00 High Impact Targeting (HIT) – IWR’s On-line Sediment Mapping Application Overview Hands-on Exercise Question and Answer 12:00 – 1:00 Lunch (pizza and subs provided) Discussion Next Steps
CIG Technical Flow Determine reduction targets Develop and deliver outreach plan Monitoring Model sediment yield in select watersheds Build and refine on-line HIT system Interface with Provide user feedback Feedback provided by a Technical Advisory Committee NRCS MDEQ MDA Year 1 Cost/benefit analysis of BMPs Conservation Districts On-going IWR Year 1 Year 1-Year 2 Year 1 Farmers CIG Specialists On-going On-going CREP Technicians On-going
HIT utility Outreach effectiveness Modeling improvements Composition of IWR Technical Committee Representatives of CIG Specialists MACD Farm Bureau Watershed Orgs FSA NRCS MSU Ag Engineering MDA CREP Technicians Technical CommitteeInputs IWR Ease of system use Refine and enhance HIT technical capacity
High Impact Targeting (H.I.T.) A web-accessible system that allows users to identify and prioritize, at multiple-scales, areas at high-risk for sediment loading. The data delivered through H.I.T. are the product of results from the Spatially Explicit Delivery Model (SEDMOD)¹ and the Revised Universal Soil Loss Equation (RUSLE)². • Fraser. May 1999 • Renard, Foster, Weesies, McCool, Yoder. 1996.
SEDMOD/RUSLE Methodology SEDMOD Land Cover Surface Roughness Delivery Ratio Soil Texture Weighting Soil Clay Content Distance to Stream DEM Sediment Yield LS Factor C Factor Landuse/Tillage K Factor Soil Erosion Soil Erodibility R Factor Rainfall P Factor Support Practice RUSLE
Prioritization of 8-digit HUCs Using 90m Resolution Data(Great Lakes Basin) Estimated Potential Sediment LoadingContributed from Cropland (tons/yr.) Source: Ouyang, Bartholic, Selegean (2005)
Prioritization of 12-digit HUCs Using 10m Resolution Data (Lower Maumee River Watershed – NW Ohio)
Applying BMP (no-till) on highest risk acres in contrasting watersheds
Slide “A” shows a 30 square mile area of watershed that can be examined to rapidly locate and magnify high risk contributing areas. 10
2,000 feet 0 “C” shows further enlargement with a photographic image of the area. C
2,000 feet 0 “D” shows this resolution with the photo overlaid with the sediment risk layer. D
1,000 feet 0 Specific problem areas can be interpreted from slide “E” by overlaying the sediment risk layer over the photograph. E
Slide “F” shows contour lines and three example areas of high sediment delivery. F 2 1 3 1) High sediment deliveries 2) Potential concentrated flow 3) High sediment delivery no riparian buffer
Benefits and Limitations of the Methodology • Benefits • Quick prioritization of areas with a high risk for sediment loading • Field-level resolution • Limitations • RUSLE does not account for ephemeral gully erosion • 10 meter resolution DEMs not available for all areas
In order to realize the benefits of the H.I.T. modeling process, the data needs to be readily available to decision makers. Making the Data Web-Accessible: H.I.T. front page. User selects a watershed.
Making the Data Web-Accessible: Users can choose from multiple scales and formats to view data. User has the option to view data for the entire 8-digit watershed in three formats: Tabular Bar Graph Spatial Those options are also available for viewing sub-watersheds of the 8-digit watershed. In this example, the user chooses to compare all sub-watersheds.
Making the Data Web-Accessible: Build a results table Sediment statistics will be calculated. User has the option to view data for the entire 8-digit watershed in three formats: Several watersheds will be compared. Cost benefit analyses will be run for each of two BMPs: No Till on the worst 5% of areas Mulchtill on the worst 5% of areas Totals and rates will be calculated for each sub-watershed.
Making the Data Web-Accessible: Table Results
Making the Data Web-Accessible: Closer look at the tabular results Results sorted by BMP cost per ton reduction (by clicking on column title). BMP cost/acre provided by NRCS. This can help an organization determine where (and which) conservation efforts would yield the maximum return in sediment reduction within its budget.
Making the Data Web-Accessible: Same data displayed in the table is also available in bar graph format.
Making the Data Web-Accessible: Viewing the data spatially If Wade Creek is identified as the targeted watershed, the user can use H.I.T. to connect to Digital Watershed in order to explore Wade Creek’s high risk areas spatially.
HIT site: 35.9.116.206/hit/hit.asp CIG Project site: www.iwr.msu.edu/CIG-MDA/
Summary • SEDMOD/RUSLE methodology facilitates prioritization of areas in terms of sediment loading at small and large scales. • H.I.T. system makes SEDMOD/RUSLE results readily accessible over the web. • H.I.T. allows results to be explored in either tabular, bar graph, or spatial formats. • Empowers decision makers in targeting areas at high-risk for sediment loading.
http://www.iwr.msu.edu Thanks for Caring and Acting to Sustain Water Resources 30