MODELING THE EFFECTS OF TOPOGRAPHIC SHADING ON
SNOW-FED RUNOFF WITH WARMER TEMPERATURES
Frederic Lott and Jessica D. Lundquist
University of Washington, Dept. of Civil & Environmental Engineering, Box 352700, Seattle, WA 98195
lottf@u.washington.edu
Abstract
3. Shading Matters in the Sierra Nevada
Discharge in small, tributary streams affects water table heights, riparian vegetation, and habitat in subalpine
meadows. Because of this, meadows are very sensitive to the dates when the ephemeral streams go dry. The Distributed
Hydrology Soil Vegetation Model (DHSVM) is used in conjunction with a high density hydroclimate monitoring
network in the Tuolumne River basin of Yosemite National Park, California to investigate how high elevation subbasins with different aspects and elevations respond to warmer temperatures. Specifically, this project investigates how
topographic shading affects the advance of snowmelt onset and the date snow disappears as temperatures warm.
Observations show that in years where the temperature warms earlier in the season, south-facing sub-basins start
melting over a week earlier than north-facing basins. Thus, meadow areas fed by sub-basins with southern aspects are
expected to be much more sensitive to warming temperatures than areas fed by sub-basins with northern aspects.
Traditionally, most future hydrologic simulations are run for large basins, and these effects would not be captured.
DHSVM is used to test if high-resolution (150 m) modeling with a complete topographic shading component can
represent these observed differences and be used to simulate how warmer temperatures will differentially affect various
sub-basins and meadow regions.
1. Motivation
RMSE = 9.1 days
Bias = -6.3 days
Tuolumne Meadows is a dynamic ecosystem, with plant communities
forming based on the subtle topography of the meadows. Small changes in
seasonal water levels have the potential to drastically alter the vegetation
distribution and meadow ecosystem.
The figure on the left shows the difference between a temperature-index melt
model (Snow-17) and observed MODIS snow cover imagery with respect to the
date when the snow is gone from each pixel. Most pixels in the basin are
melting away earlier than what was observed. These differences can be as
much as three weeks between modeled and observed, pointing to a problem
with either the PRISM precipitation distributions or the simplicity of the
model, which does not incorporate shading or land use. When shading is not
considered, the largest errors are seen in the headwater cirques and steep
river valleys.
Shading matters on a large scale as well. The Sierra Nevada have some of the
steepest terrain in the US, which get washed out in low-resolution DEMs. The
figure below, from Mote et al. (2005), shows changing trends in mountain
snow pack in the western US. While the model has good accuracy in most
places, it fails to properly capture the dynamics seen in the Sierra (circled).
Planners in this region need better resolution modeling that can resolve these
significant topographic effects.
A. March 1st Potential radiation
(from Lundquist and Flint, 2006)
600
500
Model melts
snow earlier
than observed
Count
400
300
Model melts
snow later
than
observed
200
The mod eled
“no snow”
date was:
100
0
-70
How do we get our models to properly represent this?
You’re soooo
overprotective, Dad!
I don’t care if your
south-facing friends
started melting already.
It’s too early, I say!
Shaded cirques in steep topography and snowpack
heterogeneity impose strong controls on melt timing.
2. Study Area – Headwaters of the Tuolumne River
6. Radiation and Resolution
-60
-50
-40
-30
-20
-10
0
10
Modeled minus MODIS "no snow" date
4. The Distributed
Hydrology Soil
Vegetation Model
(DHSVM)
DHSVM is a distributed hydrology
model that incorporates a full mass
and energy balance and allows for fine
spatial and temporal resolutions. The
spatial inputs used by the model are
shown in the adjacent figure. Soil and
vegetation parameters are userdefined. The meteorological forcing
data include temperature, precipitation, wind speed and direction,
humidity, and solar radiation. For this
study, the model was run at a 150meter resolution with a three hour
time step.
20
30
5. Preliminary DHSVM Results
The preliminary results from DHSVM show good agreement in
the amount of runoff generated in the basin. The total modeled
flow is about 101% of observed over the run period. While the
flow volume is representative, the timing is not. The onset of
the spring melt season causes the model to melt a large portion
of the snow in a short amount of time, leaving less water
available for late season flows.
B. March 1st total radiation:
DHSVM @ 150m resolution
The above map (A) shows potential
radiation in MJ/day at 30m resolution
as calculated using the method of Flint
and Childs (1987), which takes into
account full topographic shading.
Figures B shows summed output of
direct beam and diffuse radiation
generated from a 150m/1-hr resolution
run of DHSVM, which is also designed to
incorporate topographic shading. There
are some significant differences and
problems evident in these maps. First,
DHSVM is calculating radiation values
higher than potential. This points to
issues with how the model handles the
distribution of diffuse radiation or how it
is distributing observed radiation data at
the meteorological stations.
D. Difference between DHSVM
radiation at 30m and 150m
C. March 1st total radiation:
DHSVM @ 30m resolution
E. Difference between
DHSVM radiation at 30m and
calculated potential
Second, it becomes even more obvious that a 150-meter resolution is still insufficient to capture
topographic effects on radiation. Low radiation values (which reflect heavily shaded portions) in the
headwaters of small tributaries are washed out at this resolution. To test the effect of resolution, files
were prepared to run DHSVM at a 30-meter resolution. Figure C shows the total radiation output of
DHSVM run at 30m resolution. The shading differences in upstream cirques become much more
apparent. In general, the north-facing basins are getting less radiation and the south-facing basins are
getting more radiation than the 150m model, which will give this higher resolution model a better chance
of replicating observed patterns. Differences between the model at both resolutions (D) and the 30m
model with the theoretical potential (E) show that issues still exist.
7. Conclusion and Implications
• Steep topography in the Sierra Nevada introduces an extra challenge in hydrologic modeling.
PRISM precipitation
distribution
• At a course resolution, a complex model like DHSVM offers minimal gains in accuracy over simple
temperature-index snow models like Snow-17.
Percent open sky
Yosemite
Terrain shadowing
Vegetation type
Soil types
Soil depth
Basin mask
Elevations
The study domain covers 316 km2 (122 mi2) of the upper Tuolumne River Basin in
Yosemite National Park, CA. The area contains two meteorological stations, over 70
groundwater wells, and dozens of water level loggers and temperature sensors.
DHSVM input maps
Image source: http://www.tag.washington.edu/research/dv24/dv24.htm
Work by Lundquist and Flint (2006) found that in years when
spring comes earlier, there is a pronounced difference in the
onset of snow melt between north and south-facing basins.
2004 was one such year, with the spring melt pulse in Budd
Creek (a north-facing basin) appearing over a week after melt
began in Gaylor Creek (south-facing). However, the model
output shows the spring pulses arriving within a day of each
other in 2004.
Even at 150-meter and 3-hour resolution, the model still
appears to miss the effects of topographic shading on
snowmelt timing. Like the high early spring flows seen at the
downstream gage, this discrepancy points to an issue with how
the model is handling radiation during the snow melt season.
• Problems exist even at the 150-meter scale. Modeling at 30-meter resolution shows promise for
significant improvement. The next step for this project will involve preparing inputs for a 10-meter
implementation of the model in hopes of fully capturing these effects.
• Radiation differences between the 30 and 150 meter models show a seemingly insignificant difference on
basin average, but significant differences in the portions of the basin where shading matters the most.
• Successful calibration of models to capture these shading effects requires fine-scale observational data;
this underscores the need to find general methods for representing these processes in ungaged basins.
References
Mote, P. W., Hamlet, A. F., Clark, M. P. & Lettenmaier, D. P, 2005. Declining mountain snow pack in western North America.
Bull. Am. Met. Soc. 86, 39 – 49
Lundquist, J. and A. Flint, 2006. Onset of snowmelt and streamflow in 2004 in the Western United States: How shading may
affect spring streamflow timing in a warmer world. J. Hydrometeorology, 7, 1199-1217
Flint, A.L., and S. W. Childs, 1987. Calculation of solar radiation in mountainous terrain. J. Agric. For. Meteor., 40, 233-249.