Intra-catchment comparison and classification of long-term streamflow variability in the

Alps using wavelet analysis

Teresa Pérez Ciriaa, *, Gabriele Chiognaa,b

a Institute of Geography, University of Innsbruck, Innrain 52f, 6020 Innsbruck, Austria

b Faculty of Civil, Geo and Environmental Engineering, Technical University of Munich, Arcistr.

21, 80333 Munich, Germany

* Corresponding author: E-mail address: gabriele.chiogna @uibk.ac.at

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a)

b)

Fig. A1. Comparison between the coherence analysis between Kajetansbrücke and Innsbruck discharge

time series using daily data and monthly data, in panel a) and b), respectively.

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Table A1. Classification of the gauging stations (including their catchment area, mean Q, and mean

catchment elevation) in cluster 1, cluster 2, and cluster 3 (for the yearly scale) using our suggested

Wavelet Transform Coherence (WTC) approach and the k-means approach. Gauging stations whose

classification differs are highlighted in grey.

Gauging station Catchment Area (km2)

Mean Q (m3/s)

Mean catchment elevation (m.a.s.l.)

WTC approach k-means

1 Anger 249.60 3.87 535.00 3 32 Bad Aibling 144.10 3.10 516.00 3 33 Berninabach - Pontresina 107.00 4.62 2615.00 1 14 Bleyerbrücke 116.40 3.44 1077.00 1 25 Brixlegg 8503.60 267.32 2010.00 1 16 Bruckhäusl 321.08 10.94 1331.00 1 17 Cinuos-Chel 733.00 23.44 2456.00 1 18 EKW-Valtorta - 18.18 - 1 19 Erb - Leitzach 202.70 1.74 964.00 2 210 EW-Gmünd 140.54 6.28 1957.00 1 211 Feldolling 754.00 8.13 921.00 2 212 Galtür-Au 97.60 1.54 2361.00 1 113 Hart im Zillertal 1094.19 45.00 1921.00 1 114 Hörbrunn 134.21 5.37 1548.00 1 115 Huben 516.91 19.94 2614.00 1 116 Innsbruck 5771.60 165.00 2138.00 1 117 Innsbruck-Reichenau 853.11 24.72 1899.00 1 118 Jenbach 7230.70 213.61 2045.00 1 119 Kajetansbrücke 2148.00 59.40 2319.00 1 120 Kirchbichl 9310.00 292.00 1940.00 1 121 Klaushof (Brücke) 135.28 2.86 2250.00 1 222 Landeck-Bruggen 727.00 19.81 2124.00 1 123 Magerbach 5118.80 145.74 2212.00 1 124 Mariathal 271.88 10.34 1239.00 1 225 Martina 1941.00 55.86 2343.00 1 126 Mayrhofen 611.07 27.14 2128.00 1 127 Oberaudorf 9713.20 304.93 1903.00 1 128 Persal 129.26 4.05 2045.00 1 129 Prutz 2461.50 74.40 2283.00 1 130 Puig 342.12 10.78 1910.00 1 131 Punt dal gall 295.00 1.03 2389 1 132 Rohr 197.40 8.18 1870.00 1 133 Rosenheim 10153.50 315.00 1859.00 1 134 Rosenheim tributary 1094.60 17.60 829.00 2 135 Sausteinaste 225.57 3.46 2280.00 1 236 Schalklhof 107.80 2.85 2276.00 1 2

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37 Schmerold 222.70 8.69 1068.00 1 138 See im Paznauntal 385.40 8.80 2235.00 1 2

39 St. Anton am Arlberg-Moos

130.60 4.94 2250.00 1 1

40 St. Jodok am Brenner 109.20 3.40 2019.00 1 141 St. Leonhard im Pitztal 165.31 3.01 2560.00 1 142 St. Moritzbad 155.00 5.82 2399.00 1 143 Steinach am Brenner 111.58 4.19 1952.00 1 144 Strengen 271.30 9.70 2085.00 1 145 Tarasp 1581.00 25.94 2384.00 1 146 Tumpen 784.27 26.54 2481.00 1 147 Valley 381.70 5.47 955.00 2 248 Wasserburg 11960.40 356.70 1681.00 1 149 Weichselbaum 162.70 2.40 503.00 3 350 Zell am Ziller-Zellbergeben 696.26 29.40 2055.00 1 1

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Table A2. Topological information about the clusters derived at different temporal scales, including the

class, the number of stations belonging to that specific class, the closing station of the class and its

catchment area (i.e., the maximum spatial extension of the cluster), the smallest nested catchment and its

area and if all stations belonging to the cluster are nested or not nested.

Class Number of stations River Closing station Catchment area

Smallest nested catchment

Catchment area

Nested catchments

Y1 43 Inn Wasserburg 11960.4 Galtür-Au 97.6 Nested

Y2 4 Mangfall Rosenheim tributary 1094.6 Erb - Leitzach 202.7 Nested

Y3 3 Attel Anger 249.6 - - Not nestedM1a 6 Inn Prutz 2461.5 St. Moritzbad 155 Nested

M1b 4 Sanna Landeck-Bruggen 727 St. Anton am

Arlberg-Moos 130.6 Nested

M1c 5 Inn Kirchbichl-Bichlwang 9310 Magerbach 5118.8 Nested

M1d 3 Inn Wasserburg 11960.4 Oberaudorf 9713.2 Nested

M1e 2 Ötztaler Ache Tumpen 784.27 Huben 516.91 Nested

M2 4 Sill Innsbruck-Reichenau 853.11 St. Jodok am

Brenner 109.2 Nested

M3a 3 Ziller Hart im Zillertal 1094.19 Mayrhofen 611.07 NestedM3b 3 Gerlosbach Rohr 197.4 EW-Gmünd 140.54 Not nested

M4a 4 Mangfall Rosenheim tributary 1094.6 Schmerold 222.7 Not nested

M4b 3 Mangfall Feldolling 754 Erb - Leitzach 202.7 NestedM4c 3 Attel Anger 249.6 Bad Aibling 144.1 Not nestedL1 14 Inn Prutz 2461.5 St. Moritzbad 155 NestedL2 31 Inn Wasserburg 11960.4 Galtür-Au 97.6 Nested

L3 2 Ötztaler Ache Tumpen 784.27 Huben 516.91 Nested

L4 2 Attel Anger 249.6 Bad Aibling 144.1 Not nested

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Table A3. Topological information about the final clusters obtained merging different temporal scales,

including the class, the number of stations belonging to that specific class, the closing station of the class

and its catchment area (i.e., the maximum spatial extension of the cluster), the smallest nested catchment

and its area and if all stations belonging to the cluster are nested or not nested. Clusters with only one

station do not have entries for the smallest nested catchment, the smallest nested area and if all stations

belonging to the cluster are nested or not nested.

Final classification

ClassNumber

of stations

River Closing station Catchment area

Smallest nested catchment

Catchment area

Nested catchments

Y1M1aL1 6 Inn Prutz 2461.5 St. Moritzbad 155 Nested

Y1M1bL2 4 Sanna Landeck-Bruggen 727 St. Anton am Arlberg-Moos 130.6 Nested

Y1M1cL2 5 Inn Kirchbichl-Bichlwang 9310 Magerbach 5118.8 Nested

Y1M1dL2 3 Inn Wasserburg 11960.4 Oberaudorf 9713.2 NestedY1M1eL3 2 Ötztaler Ache Tumpen 784.27 Huben 516.91 Nested

Y1M2L2 3 Sill Innsbruck-Reichenau 853.11 St. Jodok am

Brenner 109.2 Nested

Y1M3aL2 3 Ziller Hart im Zillertal 1094.19 Mayrhofen 611.07 NestedY1M3bL2 3 Gerlosbach Rohr 197.4 EW-Gmünd 140.54 Not nested

Y1M4aL2 2 Brandenberger Ache Mariathal 271.88 Bleyerbrücke 116.4 Not nested

Y2M4aL2 1 Mangfall Rosenheim tributary 1094.6 - - -

Y2M4bL2 3 Mangfall Feldolling 754 Erb - Leitzach 202.7 NestedY3M4cL2 1 Murn Weichselbaum 162.70 - - -Y3M4cL4 2 Attel Anger 249.6 Bad Aibling 144.1 Not nested

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Fig. A2. Flow duration curve computed for the normalized streamflow data (subtracting the mean and

dividing by the standard deviation) for stations belonging to class Y1M1aL1.

Fig. A3. Flow duration curve computed for the normalized streamflow data (subtracting the mean and

dividing by the standard deviation) for stations belonging to class Y1M1bL2.

Fig. A4. Flow duration curve computed for the normalized streamflow data (subtracting the mean and

dividing by the standard deviation) for stations belonging to class Y1M1cL2.

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Fig. A5. Flow duration curve computed for the normalized streamflow data (subtracting the mean and

dividing by the standard deviation) for stations belonging to class Y1M1dL2.

Fig. A6. Flow duration curve computed for the normalized streamflow data (subtracting the mean and

dividing by the standard deviation) for stations belonging to class Y1M1eL3.

Fig. A7. Flow duration curve computed for the normalized streamflow data (subtracting the mean and

dividing by the standard deviation) for stations belonging to class Y1M2L2.

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Fig. A8. Flow duration curve computed for the normalized streamflow data (subtracting the mean and

dividing by the standard deviation) for stations belonging to class Y1M3aL2.

Fig. A9. Flow duration curve computed for the normalized streamflow data (subtracting the mean and

dividing by the standard deviation) for stations belonging to class Y1M3bL2.

Fig. A10. Flow duration curve computed for the normalized streamflow data (subtracting the mean and

dividing by the standard deviation) for stations belonging to class Y1M4aL2.

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Fig. A11. Flow duration curve computed for the normalized streamflow data (subtracting the mean and

dividing by the standard deviation) for stations belonging to class Y2M4aL2.

Fig. A12. Flow duration curve computed for the normalized streamflow data (subtracting the mean and

dividing by the standard deviation) for stations belonging to class Y2M4bL2.

Fig. A13. Flow duration curve computed for the normalized streamflow data (subtracting the mean and

dividing by the standard deviation) for stations belonging to class Y3M4cL2.10

Fig. A14. Flow duration curve computed for the normalized streamflow data (subtracting the mean and

dividing by the standard deviation) for stations belonging to class Y3M4cL4.

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