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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 - PowerPoint PPT Presentation
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Rush River Assessment ProjectHydrologic 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
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
Where’s the Rush?
The Rush River Watershed is one of six subwatersheds within the Lower MN River Subwatershed
Goal: Locate storage areas within watershed to alter peak flowsHydrologic 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
The RRAP involved extensive monitoring
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
Project constraints revolved around budget and scale
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
XP-SWMM: A sewer model goes ag Why use SWMM?
Hydraulics are important
Hydrologic capabilities are in same interface
It accounts for ditch storage
XP-SWMM: A sewer model goes ag Model structure
Conduits
Nodes
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
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
Chart 3.2Hydrological Flow Comparison
0
100
200
300
400
500
600
700
800
900
1000
0 10 20 30 40 50 60 70 80
Time (Hours)
Flo
w (
cfs)
Non-Tiled Runoff (cfs)
Tiled Runoff (cfs)
Land Use Acreage Percent of Total
Cultivated Land 232,337 90
Woodland/Forest 9,272 4
Urban Rural Development
5,804 2
Grassland 4,005 2
Wetland 2,561 1
Water 1,899 1
Conservation Land
1,821 1
Other 77 0
Total 257,775 100
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
Areal to Point Rainfall RelationshipsVarious Storm Durations
From Bulletin 71, Huff and Angel
50%
55%
60%
65%
70%
75%
80%
85%
90%
95%
100%
0 50 100 150 200 250 300 350 400
Area (Square Miles)
Per
cen
t o
f P
oin
t R
ain
fall
0.5 1 2 3
6 12 24 48
Hydrologic assumptions tested against monitoring data in a iterative process Sites monitored in 2003
Compare monitored flows to modeled flows to discover limitations
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
Chart 3.3RP5 Guaging Station
Comparison of Monitored versus Modeled Flows
0
200
400
600
800
1000
4/1/2
003
4/8/2
003
4/15
/2003
4/22
/2003
4/29
/2003
5/6/2
003
5/13
/2003
5/20
/2003
5/27
/2003
6/3/2
003
6/10
/2003
6/17
/2003
6/24
/2003
7/1/2
003
7/8/2
003
7/15
/2003
7/22
/2003
7/29
/2003
8/5/2
003
8/12
/2003
8/19
/2003
8/26
/2003
9/2/2
003
9/9/2
003
9/16
/2003
9/23
/2003
9/30
/2003
Date
Flo
w (
cfs)
Modeled
Monitored
Chart 3.4RP1 Gauging Station
Comparison of Monitored versus Modeled Flows
0
600
1200
1800
2400
3000
4/1/2
003
4/8/2
003
4/15
/2003
4/22
/2003
4/29
/2003
5/6/2
003
5/13
/2003
5/20
/2003
5/27
/2003
6/3/2
003
6/10
/2003
6/17
/2003
6/24
/2003
7/1/2
003
7/8/2
003
7/15
/2003
7/22
/2003
7/29
/2003
8/5/2
003
8/12
/2003
8/19
/2003
8/26
/2003
9/2/2
003
9/9/2
003
9/16
/2003
9/23
/2003
9/30
/2003
Date
Flo
w (
cfs)
Modeled
Monitored
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
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
Chart 3.7RP1 Guaging Station
Comparison of Monitored versus Modeled Flowswith Area Distribution Calibration
0
600
1200
1800
2400
3000
4/1/2
003
4/8/2
003
4/15
/2003
4/22
/2003
4/29
/2003
5/6/2
003
5/13
/2003
5/20
/2003
5/27
/2003
6/3/2
003
6/10
/2003
6/17
/2003
6/24
/2003
7/1/2
003
7/8/2
003
7/15
/2003
7/22
/2003
7/29
/2003
8/5/2
003
8/12
/2003
8/19
/2003
8/26
/2003
9/2/2
003
9/9/2
003
9/16
/2003
9/23
/2003
9/30
/2003
Date
Ave
rage
Dai
ly F
low
(cf
s)
Monitored
Modeled
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
Season ConditionSCS Curve Number
Runoff Depth for 5.4-inch Rainfall
Spring Fallow 86 3.8
Summer Average 75 2.8
Late Summer/Fall Mature 64 1.8
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
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%
Goal: Locate storage areas within watershed to alter peak flows Where are the restorable surface waters -
everywhere
Goal: Locate storage areas within watershed to alter peak flows
Existing
Conservation
5/40
10/80
Goal: Locate storage areas within watershed to alter peak flows
Reach
Existing Conservation 5% Wetland/Storage 10% Wetland/Storage
(ac-ft) (ac-ft) (%) (ac-ft) (%) (ac-ft) (%)
North Branch 27,100 18,200 67.2% 8,800 32.5% 2,600 9.6%
Middle Branch 24,100 16,100 66.8% 7,700 32.0% 2,300 9.5%
North Fork, South Branch 23,000 15,700 68.3% 7,600 33.0% 2,200 9.6%
South Fork, South Branch 21,600 14,600 67.6% 7,000 32.4% 2,100 9.7%
Rush River Mouth 110,900 74,700 67.4% 36,000 32.5% 10,600 9.6%
Average Annual Flow Volume Comparison
Goal: Locate storage areas within watershed to alter peak flows
100-Year Event Comparison
Reach
Existing Conservation 5% Wetland/Storage 10% Wetland/Storage
(cfs) (cfs) (%) (cfs) (%) (cfs) (%)
North Branch 1,707 1,257 74% 765 45% 265 16%
Middle Branch 4,153 3,268 79% 2,129 51% 611 15%
South Branch 4,716 4,565 97% 2,817 60% 808 17%
Rush River Mouth 9,085 8,042 89% 5,097 56% 1,458 16%
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)
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Date
% o
f B
asin
Sto
rag
e U
tili
zed
Pre
cip
itat
ion
(in
ches
)
Storage w/Evaporation
Storage w/Evap. & Infiltration
Precipitation
Where are the areas of focus for restoration activity?
What should the restoration goal be?
Looking beyond the Rush River Assessment Project
Identify funding sourcesUSFWSStateClean Water
PartnershipPrivate entities
Identify, assess, and implement pilot project
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.