Transcript No Slide Title

Hydrological Modeling
FISH 513
April 10, 2002
Overview:
What is wrong with simple statistical regressions of
hydrologic response on impervious area?
Toward a more complete understanding of normal flows.
Distributed Hydrological Modeling
Example from applications of Distributed Hydrological
Modeling at UW
Changes in impervious area.
Changes in forest cover.
Global Climate Change.
Typical Representation of Effect of Impervious
Area on Runoff Coefficient
Runoff Coefficient
1
0 0
Percent Impervious Area
100%
What we really want to know is:
What is the change from normal?
Previous graph is 100% correct for dry initial conditions.
What if it has just rained nonstop for five days . . .
Well that never happens around here?
Runoff Coefficient
Representation of Effect of Impervious Area on
Runoff Coefficient for extremely wet initial
conditions
1
0 0
Percent Impervious Area
1
Therefore, normal response depends:
Static Variables:
Land Cover
Impervious Area, etc
Dynamic Variables:
Soil Moisture
Precipitation Intensity
Storm Duration, etc.
Numerous Studies have shown decreased effects of land use
Change as antecedent conditions become wetter.
Our task is to build a predictive model of what is normal…
And that can’t be done without considering interaction of
meteorology with land cover changes
Hydrological Modeling to the
Rescue
DHSVM Snow Accumulation and Melt Model
Land surface characterization required by DHSVM
• Terrain - 150
m. aggregated
from 10 m.
resolution DEM
• Land Cover 19 classes
aggregated from
over 200 GAP
classes
• Soils - 3 layers
aggregated from
13 layers (31
different
classes);
variable soil
depth from 1-3
meters
• Stream
Network - based
on 0.25 km2
source area
Calibration Location (Snoqualmie)
2500
2000
Testing: Cedar
1500
1000
500
0
20-Nov
•Calibration to two USGS
sites
•Split sample validation
at over 60 sites
•Parameters transfer
extremely well to other
watersheds without
recalibration
4-Dec
18-Dec
1-Jan
15-Jan
29-Jan
12-Feb
Effects of Impervious Area
Application of DHSVM to lower Cedar River Watershed to assess
impacts of changes in impervious area on basin hydrology
Taylor Creek (14 km2)
5% imperv.
Madsen Creek (5.4 km2)
20% imperv.
Fraction Impervious
Area (1998)
100 %
75 %
50 %
25 %
0%
CFS
DHSVM Calibration to determine baseline parameters.
Taylor Creek (5% impervious area)
Feb 1991
Mar 1991
Apr 1991
May 1991
80
60
40
20
0
CFS
100
120
Test of Impervious Area Representation (no re-calibration)
Madsen Creek (20% impervious area)
4/1/91
4/4/91
4/7/91
4/10/91
Observed (1991):
120 cfs peak, 3.6 inches total runoff
1991 Land Cover (20 % imperv.):
115 cfs peak, 3.2 inches total runoff
Old Growth Forest:
58 cfs peak, 2.3 inches total runoff
100 % increase in peak
4/5/1991
4/15/1991
4/20/1991
100
80
60 40 20
5
4
3
2
1
Effect of Climate Change
Predicted Change in Mean Monthly Temperature due to Increased
Carbon Dioxide Levels (Mean of 4 GCM’s)
2020’s (w.r.t mid 20th century climate)
2040’s (w.r.t mid 20th century climate)
2020’s Mean Winter Increase = 1.6 C
2040’s Mean Winter Increase = 2.4 C
Change In Temperature
Change in Precipitation
DHSVM
SWE
Reservoir Inflow
0.5
0.4
0.3
0.2
0.1
0
1
2
3
4
Methodology for Assessing Impacts of
Climate Change on
Watershed hydrology
Observed
Meteorology
Synthetic “Observed”
At Stations
Record:
in and near
Talt=Tobs + Delta T
Target
Palt = Pobs*(Delta P)
Watershed
5
6
7
8
9 10 11 12
Snow Water Equivalent (mm)
Cedar River Watershed:
Retrospective Analysis of Average Snow Water
Equivalent Under Current and Altered Climates
Drought
Current
2025
2045
Current Low Year
Becomes . . .
2025/2045 Best Case
Effect of Climate Change on Mean Monthly Inflow
(1988 to 1996) to Cedar Reservoir
Current
2025
2045
Monthly Inflow (meters)
Higher Winter Flows: Increased Precipitation
Higher Freezing Level -> More Rain
Snowmelt
126,000 acre-ft
90,000 acre-ft
78,000 acre-ft
0.5
0.4
0.3
0.2
0.1
0
1
2
3
4
5
6
7
Month
8
9 10 11 12
Effect of Forest Harvest
Basins for which
streamflow was simulated
for each vegetation
scenario. GAP, 1991 is
based on a 1991 LandSat
image. Band Harvest has a
total clear-cut area
identical to GAP, 1991 but
concentrated in the
transient snow zone (700900 m). The control
simulation is the historic
vegetation coverage
(based on GAP with all
clear-cuts regrown).
GAP, 1991
Urban / S u bu rban
Grass / C or p / S h ru b
De cidu ou s For
e st
Dou glas -Fir/ He m lock
Harve s te d
Rock / Ice C ap
Wate r
Historic Vegetation
Band harvest
Effect of forest canopy removal, Snoqualmie River at Snoqualmie Falls, February 1996 event
SWE (mm)
2/4/96
0
2/5/96
2/6/96
2/7/96
2/8/96
2/9/96
2/10/96
10 Hourly Precipitation (mm)
50
40
Low elevation(<300 m) snow (mm SWE)
30
Historic Vegetation
20
Complete Harvest
10
0
Streamflow (cms)
2000
11 %
4%
2%
Historic
Gap 1991
Band Harvest
Complete Harvest
1500
1000
Flood Stage (560 cms)
500
0
2/4/96
87 %
26 %
10 %
2/5/96
2/6/96
2/7/96
2/8/96
2/9/96
2/10/96
Questions?