wyoming fater equivalent variability based on...
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Wyoming SnowFWater Equivalent Variability Based on Historical SNOTEL9 Data;enitza ;q Voutchkova F Scott jq >iller
Wyoming ,enter for {nvironmental ~ydrology and 'eophysics F
;epartment of {cosystem Science and >anagement
University of Wyoming
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Y~eight 9 % 2 0 JY J9 J%
,luster dendrogram
j#T{S
data5 SW{max J44Yb9YJ7 Bn:97 x p:6YT
BJ464bJ404O J44%O 9YJ%O 9YJ8 excludedT
transformation5 centered and scaled1 |5scale {base}
distance5 euclideanO |5dist {stats}
clustering5 hierarchical
aglomeartion5 wardq;9 methodO |5hclust {stats}
uncertainty5 approximately unbiased pbvalues BwTO
computed by multiscale bootstrap resampling1
|5pvclust {pvclust} with replication ):JYLYYYO
sample sizes nL:cBJJO J7O J2O J0O 9YO 97O 98
96O 94O 79TO reproducibility iseed:JY
W y o m i n gW y o m i n g
%L9Y6mqaqsql
j
4%%mqaqsql Y %Y 0Y km
BJ7L0Y% ftTB7LY44 ftT
WyomingSj#T{+ stations
@owderbTongue
,heyenne
South @latte
jorth @latte
WhitebYampa
'reat ;ividebUpper 'reen
)ig ~ornUpper
Snake
)ear
Upper Yellowstone>isso
uri~eadwaters
>issourib
+ittle>issouri
jiobrara
jot included
,luster J
,luster 9
,luster 7
,luster %
,luster 8
{levation ;istance
B%4O6 miT
~ydrologic subregions B~U%T
Bshort recordT
7L9YY
7LYYY
9L0YY
9L2YY
9L%YY
9L9YY
mean
median
Jst quartile
7rd quartile
min
max
J44Y J44J J449 J447 J448
J444 9YYYJ442 J446 J440
9YYJ 9YY9 9YY7 9YY% 9YY8
9YY2 9YY6 9YY0 9YY4 9YJY 9YJJ 9YJ9 9YJ7
SW{max dataset used for cluster analysis
6Y stations
year
SW{max
d : maxBSW{maxT : J
d
97 years
colors5clusters Jb8
SW{max
tmax
SW{aprqJ
Sj#T{+ is automated snowpack monitoring network5
b operated by the jatural |esources ,onservation Service Bj|,STO
b 67Y remote high elevation stations in JJ Western statesO
b openbaccessO nearbreal time F ~7Y years of historical dataq
@U|@#S{5 forecasting of water supplies in the West
xf xxx = h / k 6 7 8 9WORK FLOW
download daily data
n:6Y WY stations
period5J464b9YJ8
exclude incomplete water
years F convert units
Bfeet in mmT
extract SW{ signatures
all stations F years
check SW{ signatures
for errors Btoo lowAhighO
earlyAlateO negative periodsT
check raw data F
maintenance comments
select common period
for all 6Y stations
hierarchical clustering
SW{max variability
pbvalues via multiscale
bootstrap resampling
linear trends for 8
regions in WY
multiannual variability
8year moving window
implications F future work
numberofSj#T{+sites 6Y
2Y
8Y
%Y
7Y
9Y
JY
YPressure transducer types
6Y
2Y
8Y
%Y
7Y
9Y
JY
YPillow type
JY
Y
8 new pressure transducersBno change in typeT
new site Bn:%T or replacedpillow Bno change in typeT
Jq8 @si Usbr
2YLL @illow Usbr b Validyne
JYYLL Transducer b ;ruck
8YLL Transducer b Sensotec
JYYLL Transducer b Sensotec
unconfirmed from archives
@V,
)utyl
>etal~ypalon
not specified
= {quipment F maintenance h 6 @retreatment F selection
{levation BmqaqsqlT
/ SW{ signatures
taprqJ tY
@melt : tY b tmax
Jd
nmms
#ctq J Sepq 7Y
Snowbwater equivalent
BSW{T accumulation
SW{max annual peak accumulation
SW{aprqJ snow water equivalent accumulation on =pril Jst
@melt duration of snowbablation period
S rate of ablation in mmAday
J40Y
J408
J44Y
J448
9YYY
9YY8
9YJY
9YJ8
incomplete water years
per cluster
Y
9Y
%Y
2Y
0Y
JYYhistogram of incomplete
water years per station
wy J464b9YJ8
Y J 9 7 % 8 2 6 0 JY
incomplete water years BnT
frequency
Y
8
JY
J8
9Y
w
;id Wyoming snowbwater equivalent BSW{T change
in the period J464b9YJ8-
/s there a subbregional difference in SW{ variability in WY-
What are the implications for water resources-
9
x979F=fxksignificant changeBlinear regressionsT
s
SW{max
tmax tY
82 mmAJYy Bp3YqY8T
8Y mmAJYy Bp3YqY8T
7q2 dAJYy Bp3YqJT
%qJ dAJYy Bp3YqJT
7q6 dAJYy Bp3YqJT
Jq7% mmAdAJYy Bp3YqY8T
JqJ7 mmAdAJYy Bp3YqY8T
x99fF=fxk no significant trendsO except5 @melt IJq0 dAJYy Bp3YqJT
+inear trends summary
mean
I J S;
I 9 S;
b J S;
b 9 S;
J44Y
J448
9YYY
9YY8
9YJY
9YJ8
J40Y
J408
central water year
Scaled kFyear moving mean of SWEmaxJ44Y
J448
9YYY
9YY8
9YJY
9YJ8
Y
9YY
%YY
2YY
J08
J4Y
J48
9YY
9Y8
9JY
9J8
J44Y
J448
9YYY
9YY8
9YJY
9YJ8
99Y
97Y
9%Y
98Y
92Y
96Y
J44Y
J448
9YYY
9YY8
9YJY
9YJ8
J44Y
J448
9YYY
9YY8
9YJY
9YJ8
J44Y
J448
9YYY
9YY8
9YJY
9YJ8
98
7Y
78
%Y
%8
8Y
88
2
0
JY
J9
J%
J2
J0
mm
SWEmax SWEmax timing
dqwqyq
SWE=f timing Rate of snowFablation
mmAd
Duration of snowFablation
daysdqwqyq
xf Variability summary
high
9YJ8
centralwateryear
low
J44Y
x Yq8S;x JS;
Periods with highplow SWEmax
pattern brakes
Jst period
9nd period
Similaritiesbetweenclusters
SW{max
SW{max timing
SW{:Y timing
rate of snowbablation
snowbablation duration
highestlatestlongestfastest
lowestearliestshortestslowliest
Top k
@roject funding5
BJT jational Science }oundation B{@S J9Y04Y4T though the Wyoming ,enter for {nvironmental ~ydrology and
'eophysics BWy,{~'T
B9T University of Wyoming #ffice of |esearch and {conomic ;evelopment
Travel grants5
BJT Wyoming Women in Science and {ngineering BWW/S{T program funded by jS} 'rant K {@S J9Y04Y4
B9T ,onsortium of Universities for the =dvancement of ~ydrologic Science B,U=~S/T
xx /mplications F future work
>ultiannual variability of SW{ signatures
j#T{S
data5 subbregional means Bmean from
the stations in each clusterT
analysis5 centered 8byear moving average
?UST/}/,=T/#j5
We use subbregional means in order to reduce
the effect of potential data quality problems
for individual stationq
ThenO we smooth the interannual variability
of the subbregional means with 8byear moving
averageO in order to study the multiannual patterns
xf
Data limitationsBJT Short time record5limits the ability to study longterm trendsO multiannual or decadal
variabilityO and the changes in itq |egional linear trends Bsee 4T may be biased by
the fewer stations up to J44Yq
B9T ;ata quality5data quality evaluation is limited by the lack of or the inconsistency of
existing metabdataq The equipment maintenance comments are not standartizedq
The metabdata and the daily observations are not linked in a databaseq
twitter5(;enitzaV waterbresearchqinfo
Future workBJT {levation control on SW{ trends and variabilityq =ll 6Y stations are at high
elevations Bx9YYYmTO nevertheless there may be differences in the longterm trends
and variability depending on elevationq
B9T ,oupling SW{ with streamflowO precipitation and data on vegetation disturbances
for high elevation headwater watersheds to evaluate potential
changes in streamflowq
Understanding snowpack dynamics is important step in studying hydrological responce
and water resources availability in the Westq
}ocusing on subbregional differences in snowpack dynamics helps local water
managementO eqgq irrigation and water supply planningq
j#T{S5
BJT 96w of the stations Bn:J4T have an active backup pillow and transducer up to end of water year 9YJ81
B9T different types of instrumentation within the spatial and temporal extent of the study1
B7T errors in labelingO maintenance comments in free textO no unification of codesO not a database1
B%T annual summer maintenance includes5zero sensors and pillowsO fixing equipment due to single damage
events BbearsO falling branchesTO moving equipmentAlocation due to wild firesO or not known reasonsO
cutting vegetation around the site
n:J%
n:J%
n:JY
n:9%
n:0
n:J4
jorthbWest W
Y5YellowsoneplateauOWind
|iverO W
yomingO and
Teton
|anges
Southb{ast WY5Sierra >adreO >edicine )owO and +aramie >ountains
{ast slopes of =bsaroka and Wind |iver |anges
=bsaroka |ange
)ighorn>ountains
SW{max : JqJ9 P SW{aprqJ I J8q26 | |9 : Yq47 | pbvalue : 39q9ebJ2
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