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Rush River Assessment Project Hydrologic Flow Study

Rush River Assessment Project Hydrologic Flow Study. Sibley County SWCD Presentation to the Minnesota River Research Forum March 10, 2005. Today’s Take Home Messages. Well calibrated, less data intensive, and adaptable watershed response models can be created on reasonable budgets

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Rush River Assessment Project Hydrologic Flow Study

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  1. Rush River Assessment ProjectHydrologic Flow Study Sibley County SWCD Presentation to the Minnesota River Research Forum March 10, 2005

  2. Today’s Take Home Messages • Well calibrated, less data intensive, and adaptable watershed response models can be created on reasonable budgets • Accurate modeling hydrologic flows from agricultural watersheds is strongly dependent upon: • Accounting for the landscape’s changing runoff characteristics over the course of the year • Defining the relationship among surface flow, flow into tile intakes, and subsurface flow (good monitoring data required) • Retention storage is the key to reducing flows in the Rush River

  3. Where’s the Rush? The Rush River Watershed is one of six subwatersheds within the Lower MN River Subwatershed

  4. Goal: Locate storage areas within watershed to alter peak flows Hydrologic Study was part of the RRAP which had the goal of determining: • Pollutant sources and amounts • Actions necessary to reduce pollutant levels to obtain water quality standards and designated uses • Actions to reduce river flows

  5. The RRAP involved extensive monitoring

  6. Project constraints revolved around budget and scale • The budget and scale allowed: • USGS topographic maps • Ditch cross-sections and crossing elevations • Culvert and bridge plans • Flow monitoring – Scott Matteson RRAP Coordinator

  7. Project constraints revolved around budget and scale

  8. Project constraints revolved around budget and scale • The budget and scale did not allow: • Tile sizes, location and capacity • Smaller tributary ditches and crossings • 2’ or better topographic information • Even if we had the data we could not have used it effectively

  9. XP-SWMM: A sewer model goes ag • Why use SWMM? • Hydraulics are important • Hydrologic capabilities are in same interface • It accounts for ditch storage

  10. XP-SWMM: A sewer model goes ag • Model structure • Conduits • Nodes

  11. XP-SWMM: A sewer model goes ag • Model statistics • 165 discrete channels and culverts, 142 nodes • 977,266 feet / 185 miles • 1.4 billion cu. ft. storage in channels • 560 million cu. ft. storage in basins • Furthest upstream ditch: 1042 MSLRush River at Minnesota River: 720 MSL

  12. Some hydrologic parameters had to be assumed • Simplifying assumptions • Flood simulation: SCS composite CN = 75 • One tile intake per 33 acres • Minimal retention on landscape

  13. The “Design Storms” required adjustment • Area to point rainfall relationships are important • Rush River watershed is 400 sq. miles • 9% reduction in 24-hour point rainfall • 45% reduction in ½-hour point rainfall

  14. Hydrologic assumptions tested against monitoring data in a iterative process • Sites monitored in 2003 • Compare monitored flows to modeled flows to discover limitations

  15. Hydrologic assumptions tested against monitoring data in a iterative process • Correlation #1 assumptions • Five RRAP rain gauges • 1 tile intake per 33 acres • 10% direct surface connection to ditches • SCS average CN = 75

  16. Hydrologic assumptions tested against monitoring data in a iterative process • Correlation #2 assumptions • Five RRAP rain gauges plus 5 additional rain gauges • 1 tile intake per 33 acres • 10% direct surface connection to ditches • SCS average CN = 75

  17. Hydrologic assumptions tested against monitoring data in a iterative process • Correlation #3 assumptions • Five RRAP rain gauges plus 5 additional rain gauges • 1 tile intake per 33 acres • 10% direct surface connection to ditches • SCS average CN = 75 • Separation of drainage areas into quick and lagging runoff components

  18. Hydrologic assumptions tested against monitoring data in a iterative process • Correlation #4 assumptions • Separation of drainage areas into quick and lagging runoff components • Use of changing CN through the season

  19. Hydrologic assumptions tested against monitoring data in a iterative process • Correlation #5 assumptions • Use of changing CN through the season • Use of storage instead of quick and lagging runoff components for drainage areas

  20. Goal: Locate storage areas within watershed to alter peak flows • Originally pursued track of single large projects • Problem: feasibility and upstream impacts • Problem: dozens of projects needed • Revised track is programmatic approach – subwatershed by subwatershed • 5% / 40% • 10% / 80%

  21. Goal: Locate storage areas within watershed to alter peak flows • Where are the restorable surface waters - everywhere

  22. Goal: Locate storage areas within watershed to alter peak flows

  23. Existing

  24. Conservation

  25. 5/40

  26. 10/80

  27. Goal: Locate storage areas within watershed to alter peak flows Average Annual Flow Volume Comparison

  28. Goal: Locate storage areas within watershed to alter peak flows 100-Year Event Comparison

  29. What do you do when the basin is filled? • Basin Design Criteria • Watershed to basin area of 8 to 1 • Average bounce of 2.5 feet • Retention equivalent to runoff from 100-year rainfall • Evaporation and infiltration as only outlets • Possible inclusion of valved drawdown (not modeled)

  30. Where are the areas of focus for restoration activity?

  31. What should the restoration goal be?

  32. Looking beyond the Rush River Assessment Project • Identify funding sources • USFWS • State • Clean Water Partnership • Private entities • Identify, assess, and implement pilot project

  33. Summary • Model correlation is a must but it can be done using sound hydrologic concepts – i.e with less data. • Good monitoring data allowed us to acccurately reflect the changing landscape conditions and the relationship between surface and subsurface drainage. • Mitigation strategies emphasize the programmatic approach rather than the big project approach and emphasize retention and not rate control.

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