Supplement of Hydrol. Earth Syst. Sci., 21, 1137–1147, 2017
http://www.hydrol-earth-syst-sci.net/21/1137/2017/
doi:10.5194/hess-21-1137-2017-supplement
© Author(s) 2017. CC Attribution 3.0 License.
Supplement of
Developing a representative snow-monitoring network
in a forested mountain watershed
Kelly E. Gleason et al.
Correspondence to: Kelly E. Gleason ([email protected])
The copyright of individual parts of the supplement might differ from the CC-BY 3.0 licence.
Table S1. Accuracy assessment matrix comparing the BRT classes derived from the normal snow year 2009 with those from the high snow year
2008. Overall there is less error in the lowest and highest elevation BRT classes, whereas the mid- elevations there is more error between models.
Many classes were reassigned when the BRT model was rerun between years, underestimating the accuracy of the overall spatial variability
between models.
BRT Class
18 19 20 21 Comission
17
16
14 15
9 10 11 12 13
8
7
6
5
4
3
2
1
2009
error (%)
2008
10
1 55402 6035
0
16467
2
2
369 22960
3
1
3930
52
4
0
9879
5
100
5486
6
50
3232 3232
7
0
4667
8
0
2524
9
34
4007
2053
10
48
5276 5740
11
14
2900
486
12
30
1965 339 5421
13
57
5252 4338 617
14
88
13692 1948 719
15
58
10260 14155
16
100
23580
17
100
5931 705
18
100
1850
19
51
1057 1025
20
0
2039
21
7 100 100 100 71 33
76 24
0 31 16 57 26 10 49
0 36 100
0
28
0
Omission
63
Overall accuracy
error (%)
Table S2. Accuracy assessment matrix comparing the BRT classes derived from the normal snow year 2005 with those from the high snow year
2008. Overall there is less error in the lowest and highest elevation BRT classes, whereas the mid- elevations there is more error between
models. Many classes were reassigned when the BRT model was rerun between years, underestimating the accuracy of the overall spatial
variability between models.
BRT Class
14 15 16 17 18 19 20 21 Comission
9 10 11 12 13
8
7
6
5
4
3
2
1
2009
error (%)
2005
59
1 55402 22923 22960 3930 15365 3232 6013 3365 2243
100
9283 5840
3355
2
100
2900
767
3
100
9212 12939
1965
4
100
5091 757 3973
5
100
1808 879
339 1461
6
100
3718
7
100
2194
8
100
3622
9
100
2697
10
100
3702
11
100
1815
12
100
7239
13
100
4776
14
100
4045
15
100
2347
16
100
3253
17
21
1923 512
18
0
3857
19
35
1562 3612 421
20
0
2643
21
0 14
0 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 92 35
Omission
28
Overall accuracy
error (%)