missouri basin river forecaster’s meeting 28-29 january 2014 carrie m. vuyovich, pe erdc/crrel
DESCRIPTION
Capability of passive microwave and SNODAS SWE estimates for hydrologic predictions in selected U.S. watersheds. Missouri Basin River Forecaster’s Meeting 28-29 January 2014 Carrie M. Vuyovich, PE ERDC/CRREL. Overview. Background Distributed snow data available in the U.S. - PowerPoint PPT PresentationTRANSCRIPT
INNOVATIVE SOLUTIONSfor a safer, bett er world
Capability of passive microwave and SNODAS SWE estimates for hydrologic predictions in selected U.S. watersheds
Missouri Basin River Forecaster’s Meeting28-29 January 2014
Carrie M. Vuyovich, PE
ERDC/CRREL
Overview
• Background • Distributed snow data available in the U.S.• Previous study to evaluate Snow Water Equivalent
(SWE) data
• Motivation for current study• Water Budget Analysis• Snowmelt Timing Comparison• Conclusions• 2011 Flood Demonstration
Distributed Snow Data in the U.S.NOAA National Operational Hydrologic Remote Sensing Center (NOHRSC) SNODAS
• SWE estimates based on multi-sensor snow observations combined with energy balance snow model
• Hourly/Daily gridded SWE product for conterminous U.S.
• 1 km2 resolution• POR: October 2003 – Present • Sources of Error:
• Uncertainty in forcing and observation data• Gaps in available observation data
Snow Water Equivalent 21 Feb 2006 (Cline 2008)
NOHRSC Flight Lines (http://www.nohrsc.noaa.gov/)
Distributed Snow Data in the U.S.
Passive Microwave SWE• SSM/I
• POR: July 1987 – Present• Algorithm: SWE = C(TB,19 – TB,37)
• AMSR-E• POR: June 2002 – July 2011• Algorithm accounts for forest cover,
shallow/deep snow
• Sources of Error– Wet snow– Vegetation– Saturation depth– Topography– Snow metamorphosis
• 25x25 km resolution
Comparison of passive microwave and SNODAS SWE by HUC8
Conclusion: Best comparison in areas with < 20% forest cover with an average annual maximum SWE < 200 mm
Vuyovich et al, (in press), Water Resources Research
SNODAS - AMSR-E SNODAS - SSM/I
R2
Comparison of passive microwave and SNODAS SWE by HUC8
SNODAS - AMSR-E
SNODAS - SSM/I
Nash-Sutcliffe Efficiency measure:
Great Plains SWE estimates
Objective: Evaluate SWE estimates from the 3 datasets (SNODAS, AMSR-E and SSM/I) by comparison to water budget components in selected Great Plains basins.
1. Sheyenne River near Cooperstown, ND
2. Cannonball River at Breien, ND
3. Moreau River near Whitehorse, SD
4. Bad River near Ft. Pierre, SD
5. Cheyenne River at Spencer, WY
6. White River near Interior, SD
7. White River near Oacoma, SD
8. Ponca Creek near Verdel, NE
9. South Loup River at St. Michael, NE
Methods
Where the SWE was the max annual value R, P and ET are the total volume measured through the spring melt
period, typically March – June GW is the loss to deep groundwater ΔSM is the change in soil moisture from the beginning to end of the
period
Water Budget data• Discharge: USGS daily streamflow records at basin outlet• Precipitation: NOAA CPC model output, NCDC stations• Evapotranspiration: NOAA CPC model output, NCDC stations• Soil Moisture: NOAA CPC model output for soil moisture
R² = 0.86
R² = 0.74
R² = 0.870
50
100
150
200
250
300
350
0 20 40 60 80
SWE+
P-ET
+/-S
M (m
m)
Runoff (mm)
Runoff and calculated water budget
SNODAS
AMSRE
SSMI
R² = 0.35
R² = 0.46
R² = 0.810
50
100
150
200
250
300
0 20 40 60 80 100
SWE+
P-ET
+/-S
M (m
m)
Runoff (mm)
Runoff and calculated water budget
SNODAS
AMSRE
SSMI
Example ResultsSheyenne River at Cooperstown, ND
Ponca Creek at Verdel, NE
020406080
100120140160
SWE
(mm
)
AMSRE-E
SSM/I
SNODAS
0
50
100
150
200
SWE
(mm
)
AMSRE-E
SSM/I
SNODAS
Results
0
0.2
0.4
0.6
0.8
1
Corr
elati
on, R
2
SNODAS
AMSR-E
SSM/I
0
50
100
150
200
250
300
0
20
40
60
80
100
120
140
Nov Dec Jan Feb Mar Apr May Jun
Dis
char
ge (c
ms)
SWE
(mm
)
SNODAS AMSR-E SSM/I Moreau River Discharge
Timing of snowmelt
Timing of Spring runoff: typically corresponds to onset of snowmelt. Method: calculated timing difference between start of spring runoff and peak SWE
Winter snowpack and spring runoff for the 2008-09 water year in the Moreau River basin, SD.
Results
-15.0 -10.0 -5.0 0.0 5.0 10.0 15.0
SNODAS
AMSR-E
SSM/I
Average Difference between peak SWE and start of runoff (days)
South Loup River, NE
Ponca Creek near Verdel, SD
White River Near Oacoma, SD
White River Near Interior, SD
Bad River near Ft. Pierre, SD
Cheyenne River at Spencer, WY
Moreau River near Whitehorse, SD
Cannonball River at Brien, ND
Sheyenne River, ND
Conclusion• Passive microwave estimates of SWE are well-correlated to water
budget components in the Great Plains region of the US.
• Potential use for satellite SWE estimates in water resource applications in the Plains.
2011 Missouri River Flood
Comparison to historical statisticsSSMI_January
Above Record Maximum
Above 75th percentile
Between Average and 75th percentile
Between 25th percentile and Average
Below 25th percentile
Below Record Minimum
1May1Apr
1Mar1Feb1Jan
0
2,000
4,000
6,000
8,000
10,000
0
20
40
60
80
Nov Dec Jan Feb Mar Apr May Jun JulD
isch
arge
(cm
s)
SWE
(mm
)
SSM/I Missouri River at St. Charles, MO US Army Corps of Engineers, 2011
15
Passive Microwave signal observations
Questions?