Transcript Remi Candaele

Flooding in Flathead County
and Kalispell, MT
Initiation to Geo-HMS and HECHMS
Remi Candaele
Hydrology - CE394K
Outline
1. Context & Flood
Events Characteristics
2. ArcGIS Process
3. Geo-HMS Process
4. HMS Model
5. Future Work
Evergreen – Kalispell Suburb - 1995
Context
• Flathead county
subject to flooding
• Located in northwest
corner of Montana
State.
• Total area of 13,614
km² (5,256 mi²),
• 410 km² (158 mi²) of it
(3.01%) is water.
• As of 2000, the
population was
74,471.
Motivations
• Being familiar with a Hydraulic Model !!!
Flood Events Characteristics
Whitefish river nr Kalispell
40
Peak Flow : 2 events at 35m3/s
35
30
20
15
10
5
0
Jun-94
Oct-95
Mar-97
Jul-98
Dec-99
Apr-01
Sep-02
Jan-04
May-05
Oct-06
Stillwater Rv nr Whitefish
140
120
Peak Flow : 2 events
> 100m3/s
100
Flow (m3/s)
Flow (m3/s)
25
80
60
40
20
0
Jun-94
Oct-95
Mar-97
Jul-98
Dec-99
Apr-01
Sep-02
Jan-04
May-05
Oct-06
Flood Events Characteristics
Flathead Valley
• Occurring mostly during
spring time,
• Focus on 2 major events
:
– 04/13/1996
– 04/20/1997
• Low Rainfall intensity :
computation over a long
period,
• Difficulty : 1
meteorological station
and 2 gauge stations.
Date
4/13/1996
4/13/1996
4/13/1996
4/13/1996
4/13/1996
4/13/1996
4/13/1996
4/13/1996
4/13/1996
4/13/1996
4/13/1996
Time Location
Precipitation (inc)
3:00
0.1
4:00
0
5:00
0.1
6:00
0.2
7:00
0.1
8:00 Hungry Horse Dam
0.1
9:00
0.1
10:00
0.2
11:00
0.1
12:00
0.1
13:00
0.2
Time Series
Catchments & Streams Delineation
• Projected Coordinate System : NAD1983_StatePlane_Montana
• 7 Subwatersheds selected
OBJECTID
NAME
BasinSlope
(%)
BasinCN
BasinLag
(hr)
Area_HMS
(km2)
1
W90
24.89
67.02
5.78
476.79
2
W100
20.58
70.21
8.28
498.30
3
W110
22.92
60.90
5.46
211.40
4
W120
6.39
66.50
1.68
3.83
5
W130
22.06
63.12
6.71
557.40
6
W140
10.09
67.78
8.46
282.61
7
W150
13.08
67.39
5.84
115.68
SubWatershed Characteristics
Reclassification of Land Cover
Original NLCD classification
• Data downloaded from
NLCD
• Reclassification in 4
main categories thanks
to Dr Venkatesh
Merwade
Number
11
90
95
Description
Open water
Woody wetlands
Emergent herbaceous wetlands
21
22
23
24
41
42
43
31
Developed, open space
Developed, low intensity
Developed, medium intensity
Developed, high intensity
Deciduous forest
Evergreen forest
Mixed forest
Barren land
52
71
81
82
Shrub/scub
Grassland/herbaceous
Pasture/hay
Cultivated crops
Revised classification (reclassification)
Number
Description
1
Water
2
Medium
Residential
3
Forest
4
Agricultural
Land Use Grid Obtained
Soil Data – Characterization of the Soil Type
• SSURGO (scale
1:24,000) dataset
doesn’t cover the
entire watershed: use
of the Statsgo dataset
(1:250000).
• 4 types of soil:
A/B/C/D. Soil B
assigned to the
unknown soils
Classification
Type of soil
A (low runoff
potential)
Soils having a high infiltration rate (low runoff potential) when
thoroughly wet. These soils have a high rate of water
transmission.
B
Soils having a moderate infiltration rate when thoroughly wet.
These soils have a moderate rate of water transmission.
C
Soils having a slow infiltration rate when thoroughly wet. These
soils have a slow rate of water transmission.
D (high runoff
potential)
Soils having a very slow infiltration rate (high runoff potential)
when thoroughly wet. These soils have a very slow rate of
water transmission.
Curve Number & Grid
• CN obtained from
SCS TR55 (1986)
• Generation of a CN
Grid
• Statistics
– Mean : 66.26
– Std Deviation : 11.06
Geo-HMS
ArcGIS Interface to create input files to HMS
• Processes
–
–
–
–
–
River Length
River Slope
Basin Slope
FlowPaths,
Basin Centroids
• HMS Inputs/Parameters
– Loss, Transform methods by
SCS,
– Route method by Muskingum
– Time Lag
– Basin Curve Numbers
Selection of the contributing
catchments
GeoHMS Interface
Geo-HMS
ArcGIS Interface to create input files to HMS
Basin Lag in Hours
Basin Curve Numbers
Geo-HMS
ArcGIS Interface to create input files to HMS
Schematic
Export to HMS
Running the model under HMS
• Meteorologic model :
–
–
–
–
Weight gages,
Muskingum routing,
Time Lag,
Time Series.
Results – Calibrating the model
• Computations for exercising.
• Next steps :
– Find accurate numbers for Muskingum
routing,
– Calibration factor : Streamflow = Model
Acknowledgments
•
•
•
•
Venkatesh Merwade – Purdue U.
Christine Dartiguenave – ESRI
Ron Schlagenhaufer – Flathead County
Folks : Eusebio, Tyler, Brian & others
Questions ????