Experience from an indirect bedload transport measuring system with geophone sensorsExperience from an indirect bedload transport measuring system with geophone sensors
Jens M. Turowski
With contributions by and thanks to:
D. Rickenmann, B. Fritschi, A. Ludwig, R. Hegglin, M. Böckli, A. Klaiber , A. Badoux, J. Schneider, BW. McArdell, K. Steiner, M. Nitsche, A. Beer (Swiss Federal Research Research Institute WSL)
J. Laronne, R. Barzilai (Ben Gurion University of the Negev, Israel)
H. Habersack, H. Seitz (University of Applied Sciences, Boku, Vienna, Austria)
EM. Yager, H. Schott (University of Idaho, Boise, USA)
P. Molnar, R. Boes (ETH Zurich, Switzerland)
Tyrolean Water Power Company TIWAG
Kraftwerke Mattmark
Bedload prediction in mountain rivers
Unfortunately, we are not very good in doing bedload predictions for mountain rivers…
Bedload transport predictions for the Erlenbach with three commonly used bedload equations.
Measured transport rates
Time / min
Discharge / m3/s
Records vibrations
4.- → 50g pebbles
5.- 70g pebbles
Number of grains
Probability of triggering
Bedload transport rates are measured in various ways
Step-pool morphology
Bedload transport rates are measured in various ways
Measuring bedload transport
ErDat1999
Datum
Impulse Geophone: Platte 8
Imp./Gewicht [kg]
Impulse [1/1000]
Neuer Sensor GP8 = alter Sensor Hy3
Datum
Bemerkung
276725
444962
SP (G8 bzw. PBIS-H3)
54.555
591.311
266.239
31.962
712.789
916.77152
23.499
38.785
32.178
94.856
135.847
62.165
712.789
8.844
223.179
120.261
276.598
196.133
411.389
29.865
890.503
191.301
168.019
4.077
31.326
102.741
181.849
56.794
83.389
362.397
179.559
154.814
851.8570247538
324.606
105.63
374.309
90.485
171.877
G8-F(2)
89
49.9
1650
58
572
48
49.6
274
19.5
1650
54.8
265
57.1
274
164.8
527
184.7
1526
24.9
132
98.4
12
100
166
183
32
41
314
119
130
889
260
170
350
181.5
248
31.962
54.555
712.789
23.499
916.77152
32.178
38.785
135.847
94.856
712.789
62.165
223.179
8.844
276.598
120.261
411.389
196.133
890.503
29.865
168.019
191.301
4.077
31.326
102.741
181.849
56.794
83.389
362.397
179.559
154.814
851.8570247538
324.606
105.63
374.309
90.485
171.877
G8-F(3)
89
49.9
1650
58
572
48
49.6
274
19.5
1650
54.8
265
57.1
274
164.8
527
184.7
1526
24.9
132
98.4
12
100
166
183
32
41
314
119
130
889
260
170
350
181.5
248
Fs (m3)
31.962
54.555
712.789
23.499
916.77152
32.178
38.785
135.847
94.856
712.789
62.165
223.179
8.844
276.598
120.261
411.389
196.133
890.503
29.865
168.019
191.301
4.077
31.326
102.741
181.849
56.794
83.389
362.397
179.559
154.814
851.8570247538
324.606
105.63
374.309
90.485
171.877
G8-F(Fangkorb)
89
49.9
1650
0.0902857143
58
572
0.2619428571
48
49.6
0.1270857143
274
19.5
0.1837714286
1650
54.8
0.1817142857
265
57.1
0.0182857143
274
164.8
0.0015554286
527
184.7
0.0148571429
1526
24.9
0.032
132
98.4
0.0258285714
12
0.1163428571
100
0.0029714286
166
0.0148
183
0.0774857143
32
0.1668571429
41
0.0793142857
314
0.1913142857
119
0.2694857143
130
0.0182857143
889
0.0710857143
260
0.1488
170
0.2520685714
350
0.2032
181.5
0.0056114286
248
Fs (m3)
metal basket, 2009-2010
Fs (m3)
metal basket, 2009-2010
M (kg)
metal basket, 2009-2010
Two sensor rows
Tabelle1-Hegg
7/11/95
&C &D/CH
&C &D/CH
double summation
sensor impulses upstream row, SPu er row
double summation
sensor impulses upstream row, SPu er row
double summation
sensor impulses upstream row, SPu er row
double summation
0.6720710012
1.0385005828
0.6915973012
0.6887372223
1.0510431829
1.3698871996
1.1957129543
1.4271604938
1.1476645998
0.4759503602
0.1475393354
0.5589812332
0.1222664016
0.1387867647
0.8097826087
1.1741177209
1.1637901861
1.7185104053
0.7853107345
0.7208
0.8476075593
1.1539876275
0.8395348837
3.0344314652
0.6073298429
0.431358885
0.7469135802
1.6865005309
0.6028119508
1.1028905712
1.1291492329
1.7534172272
0.5781922525
1.2306836248
1.4652652653
0.8961892247
1.7011590094
0.2702957464
1.7854545455
1.0978723404
0.4404761905
0.7569444444
0.7168141593
0.7587719298
1.1307692308
0.1785714286
1.4904822335
1.4775784753
1.6836734694
2.1835514623
1.3977481561
0.8806306306
0.5300484455
RaSdSu-(Su-Sd)-all
41.383
1.024
213.559
0.162
50.851
1.052
0.091
22.626
0.21
0.173
4.739
73.477
33.916
0.329
0.086
0.883
1.874
0.07
22.192
0.484
18.368
0.304
0.349
0.379
0.921
0.069
46.501
0.075
0.098
0.816
0.123
104.103
0.226
0.299
0.926
6.945
0.882
1.451
0.214
0.478
6.972
0.158
8.409
6.193
0.216
0.023
0.188
0.035
0.096
0.055
0.017
1.104
0.773
0.639
0.134
21.975
128.129
0.296
0.477
0.084
15.327
SPd/SPu
0.6720710012
1.0385005828
0.6915973012
2.6530612245
0.6887372223
1.0510431829
0.4347826087
1.3698871996
1.1957129543
1.4271604938
1.1476645998
0.4759503602
0.1475393354
0.5589812332
0.362962963
0.1222664016
0.1387867647
0.8097826087
1.1741177209
1.1637901861
1.7185104053
0.7853107345
0.7208
0.8476075593
1.1539876275
0.8395348837
3.0344314652
0.6073298429
0.1694915254
0.431358885
0.7469135802
1.6865005309
0.6028119508
1.1028905712
1.1291492329
1.7534172272
0.5781922525
1.2306836248
0.0572687225
0.0362903226
1.4652652653
0.8961892247
1.7011590094
0.2702957464
1.7854545455
1.0978723404
0.4404761905
0.7569444444
0.7168141593
0.7587719298
1.1307692308
0.1785714286
1.4904822335
1.4775784753
1.6836734694
2.1835514623
1.3977481561
25.6666666667
0.8806306306
2.0243902439
0.5300484455
RaSdSu-(Su-Sd)-red
41.383
1.024
213.559
0.162
50.851
1.052
0.091
22.626
0.21
0.173
4.739
73.477
33.916
0.329
0.086
0.883
1.874
0.07
22.192
0.484
18.368
0.304
0.349
0.379
0.921
0.069
46.501
0.075
0.098
0.816
0.123
104.103
0.226
0.299
0.926
6.945
0.882
1.451
0.214
0.478
6.972
0.158
8.409
6.193
0.216
0.023
0.188
0.035
0.096
0.055
0.017
1.104
0.773
0.639
0.134
21.975
128.129
0.296
0.477
0.084
15.327
SPd/SPu
0.6720710012
1.0385005828
0.6915973012
0.6887372223
1.0510431829
1.3698871996
1.1957129543
1.4271604938
1.1476645998
0.4759503602
0.1475393354
0.5589812332
0.1222664016
0.1387867647
0.8097826087
1.1741177209
1.1637901861
1.7185104053
0.7853107345
0.7208
0.8476075593
1.1539876275
0.8395348837
3.0344314652
0.6073298429
0.431358885
0.7469135802
1.6865005309
0.6028119508
1.1028905712
1.1291492329
1.7534172272
0.5781922525
1.2306836248
1.4652652653
0.8961892247
1.7011590094
0.2702957464
1.7854545455
1.0978723404
0.4404761905
0.7569444444
0.7168141593
0.7587719298
1.1307692308
0.1785714286
1.4904822335
1.4775784753
1.6836734694
2.1835514623
1.3977481561
0.8806306306
0.5300484455
RaSdSu-Sd-red
84.812
0.1
0.1
27.621
1000
1000
478.909
0.26
112.519
21.662
0.07
83.796
1.283
0.578
36.832
66.733
5.87
0.417
0.049
0.123
0.302
0.298
149.646
3.439
43.932
1.112
0.901
2.108
6.902
0.361
69.358
0.116
0.02
0.619
0.363
255.746
0.343
3.205
8.096
16.163
1.209
7.741
0.013
0.018
21.957
1.364
20.402
2.294
0.491
0.258
0.148
0.109
0.243
0.173
0.147
0.24
2.349
1.977
0.33
40.542
450.265
0.308
3.519
0.166
17.287
SPd/SPu
0.3279289988
-0.0385005828
0.3084026988
-1.6530612245
0.3112627777
-0.0510431829
0.5652173913
-0.3698871996
-0.1957129543
-0.4271604938
-0.1476645998
0.5240496398
0.8524606646
0.4410187668
0.637037037
0.8777335984
0.8612132353
0.1902173913
-0.1741177209
-0.1637901861
-0.7185104053
0.2146892655
0.2792
0.1523924407
-0.1539876275
0.1604651163
-2.0344314652
0.3926701571
0.8305084746
0.568641115
0.2530864198
-0.6865005309
0.3971880492
-0.1028905712
-0.1291492329
-0.7534172272
0.4218077475
-0.2306836248
0.9427312775
0.9637096774
-0.4652652653
0.1038107753
-0.7011590094
0.7297042536
-0.7854545455
-0.0978723404
0.5595238095
0.2430555556
0.2831858407
0.2412280702
-0.1307692308
0.8214285714
-0.4904822335
-0.4775784753
-0.6836734694
-1.1835514623
-0.3977481561
-24.6666666667
0.1193693694
-1.0243902439
0.4699515545
Ra(SuSd)Su-Sd-red
126.195
26.597
692.468
0.098
163.37
20.61
0.161
61.17
1.073
0.405
32.093
140.21
39.786
0.746
0.135
1.006
2.176
0.368
127.454
2.955
25.564
1.416
1.25
2.487
5.981
0.43
22.857
0.191
0.118
1.435
0.486
151.643
0.569
2.906
7.17
9.218
2.091
6.29
0.227
0.496
14.985
1.522
11.993
8.487
0.275
0.235
0.336
0.144
0.339
0.228
0.13
1.344
1.576
1.338
0.196
18.567
322.136
0.012
3.996
0.082
32.614
(SPu-SPd)/SPu
SPd
0.3279289988
-0.0385005828
0.3084026988
0.3112627777
-0.0510431829
-0.3698871996
-0.1957129543
-0.4271604938
-0.1476645998
0.5240496398
0.8524606646
0.4410187668
0.8777335984
0.8612132353
0.1902173913
-0.1741177209
-0.1637901861
-0.7185104053
0.2146892655
0.2792
0.1523924407
-0.1539876275
0.1604651163
-2.0344314652
0.3926701571
0.568641115
0.2530864198
-0.6865005309
0.3971880492
-0.1028905712
-0.1291492329
-0.7534172272
0.4218077475
-0.2306836248
-0.4652652653
0.1038107753
-0.7011590094
0.7297042536
-0.7854545455
-0.0978723404
0.5595238095
0.2430555556
0.2831858407
0.2412280702
-0.1307692308
0.8214285714
-0.4904822335
-0.4775784753
-0.6836734694
-1.1835514623
-0.3977481561
0.1193693694
0.4699515545
Shift both in
Measuring bedload transport
Bedload trap
Measuring bedload transport
From: Rickenmann & McArdell, Geodin. Acta 2008
The scatter reduces when the data is averaged over longer timescales
Measuring bedload transport
Measuring bedload transport
Large scatter
Fischbach
Fischbach, Griess-Mühlau
Geophon-Werte aus Sekundendaten
Werte aus Minutendaten: in Flussmitte, für 2009: Mittelwert geophon 6 und 7
Sek.dat
Min.dat
Sek.dat
Sek.dat
Min.dat
Min.dat
Min.dat
Min.dat
Min.dat
Min.dat
Messstelle
Datum
Greg*/G
Greg/G
Greg*/G
Greg*/G
8/6/09
Imp./Gewicht [kg]
Impulse [1/1000]
Integrale (Su-RMS)
M-IQA (Impulsperiode)
421600
kg
879139
Neuer Sensor GP8 = alter Sensor Hy3
Datum
Bemerkung
276725
444962
1091
0.375
732
1.4707
0.0145
96.8578
1.2834
Summe
2455
2286
5
0.0464
274
1.097
Laronne et al. (2003): The continuous monitoring of bedload flux in various fluvial environments
[mm]
41
Possible graph for GBR7: Imp. No.1 versus LC per 0.5 m width
Periods Ronel Barzilai, email 28Jul10
weight per 1 m width
N.E. 27.03.2010
Geophon 1
N.E. 18.01.2010 (case 1)
06:00-07:57
102.4
3450
DATA NOT TO BE USED, PRESSURE PILLOW MEASUREMENTS ARE NOT RELIABLE
GBR7 poster common: Figure 4C
Nahal Eshtemoa
Summe Maxima (Impuls- periode)
Gc = A IMP^a INT^b IQA^c SuMAX^d
Gc/G
allData
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Fischbach
Ruetz
Rofenache
Erlenbach
Esthemoa
Gc = 30 * IMP^-0.7 * INT^0 * IQA^0 * SuMAX^1.8
Fischbach
Ruetz
Rofenache
Erlenbach
Esthemoa
G mes [kg]
G cal [kg]
Drau measurements:
m=
2.04
1
2.04
1000
2040
1000000
2040000
m=
3.44
1
3.44
2000000
6880000
Bedload mass / kg
bedload mass [kg]
number of impulses
Drau measurements:
m=
2.04
1
2.04
1000
2040
1000000
2040000
6.5
43.99
78.3
0
0
15.5
19
68.08
0
0
7.5
23
21.98
229.2
0
8
37.5
24.27
45.5
24.03
111.2
11.5
24.03
11.5
26.5
24.67
160.8
3.5
27
46.77
10.5
58.04
159
75.17
5
17.34
13
4.5
15.51
28
3.5
22.28
22.6
18.05
21.5
30.33
101.8
36
26.67
2.6
16.5
20.65
39.4
12.95
14.91
67.8
11.21
146
6.51
5.32
16
14.49
8.08
11.39
16.33
16.73
15.8
8.87
6.86
68.75
11.26
10.61
6.18
2.29
2.27
13.82
84.45
7.95
Fischbach basket sampler
Ruetz basket sampler
Rofenache basket sampler
Erlenbach basket sampler
mass [kg]
Drau measurements:
m=
2.3076923077
1
2.6923076923
1000
2308.0769230769
1000000
2307692.69230769
6.5
78.3
77875
0
0
0
15.5
19
50750
0
0
0
7.5
23
229.2
42000
0
8
37.5
239750
45.5
111.2
1443750
11.5
231875
11.5
26.5
160.8
239750
3.5
27
461125
10.5
159
1335250
115500
5
13
4.5
28
3.5
22.6
21.5
101.8
36
2.6
16.5
12.95
67.8
146
16
Drau measurements:
m=
2.04
1
2.04
1000
2040
1000000
2040000
m=
3.44
1
3.44
1000000
3440000
Riedbach Entsander
Riedbach Wehr
Drau measurements:
m=
2.04
1
2.04
1000
2040
1000000
2040000
6.5
43.99
78.3
77875
0
568.5910727928
0
15.5
19
68.08
50750
0
62.7523736767
0
7.5
23
21.98
229.2
42000
163.7018443741
0
8
37.5
24.27
239750
665.7208337881
45.5
24.03
111.2
1443750
11.5
24.03
231875
11.5
26.5
24.67
160.8
239750
3.5
27
46.77
461125
10.5
58.04
159
1335250
75.17
115500
5
17.34
13
4.5
15.51
28
3.5
22.28
22.6
18.05
21.5
30.33
101.8
36
26.67
2.6
16.5
20.65
39.4
12.95
14.91
67.8
11.21
146
6.51
5.32
16
14.49
8.08
11.39
16.33
16.73
15.8
8.87
6.86
68.75
11.26
10.61
6.18
2.29
2.27
13.82
84.45
7.95
Fischbach basket sampler
Ruetz basket sampler
Rofenache basket sampler
Erlenbach basket sampler
Erlenbach retention basin
Nahal Eshtemoa 27.3.2010
bedload mass [kg]
number of impulses
Fischbach
Ruetz
Rofenache
Gewicht [kg]
Erlenbach basket, aver.
Nahal Eshtemoa, aver.
Measuring bedload transport
this event: ~0.08 mm erosion
From: Master‘s dissertation M. Böckli, 2011
Measuring bedload transport
Robust enough for high-energy environments
Reasonable accuracy
Needs independent calibration
Lower limit of particle size (~2 cm)
The influence of hydraulic conditions are almost unknown at the moment
Measuring bedload transport
Provides long-term, high-resolution data
Enables studying transport phenomena, which are otherwise difficult to acces in the field
Threshold of motion
Lots of opportunities for further research!
Measuring bedload transport
3
/s
1986-1999
2002-2009
3
/s
metal basket, 2009-2010
20th June 07: rising hydrograph
20th June 07: receding hydrograph
0.00.10.20.30.40.5
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
0
2
4
6
8
10
12
14
16
Fischbach
Ruetz
Rofenache
3
3
01.07.199409:0014:0019:0000:0005:0010:0015:00
2
4
6
8
10
Time
Discharge
data set B (1hour)
Q
max
[m
3
/s]
G
[m
3
Logarithmisch (data
d
u