ISELE Anchorage, September 18-21, 2011
Erosion Plot Monitoring
Impact of different Tillage Systems on average Annual Soil Erosion
and the Significance of Extreme Rainfall Events
University of Natural Resources
And Life Sciences, Vienna
Introduction
The protection of agricultural lands against rainfall driven surface soil erosion is a major
objective in hilly and mountainous regions.
The Lower Austrian field plot experiment started in 1994 to evaluate different tillage systems
concerning surface runoff and soil loss. The monitoring experiment has been executed since
nearly 20 years, available meteorological data has been recorded considerably longer.
Station
MI (Mistelbach)
PX (Pixendorf)
PY (Pyhra)
Mean Prec. Mean Temp.
[mm]
[°C]
686
768
883
8,1
9,5
8,6
The effort of the present study is to determine the significance of extreme rainfall events in
coherence to the long term mean erosion data – and so to combine the knowledge out of long
term meteorological monitoring with observed event based erosion records. With the result of
determining the most significant rainfall events, soil conservation measures can be optimized
by concentrating onto this information.
Fig. 1: Location of the erosion plot sites (Austria)
Materials and Methods
The erosion plot experiment consists of three plot sites, located in the hilly surroundings of the
north-eastern alpine uplands in Lower Austria (Fig. 1). Considering the constraints of
comparability of data, all further investigations relate to the conventional tillage (CT) plot in
Mistelbach under developing maize crop cover conditions only.
Erosion plot conditions
• Plot width is 3 meters and plot length is 15 meters (defined by steel panels)
• The uniform hill slope is about 12% to 13%
• The surface soil layer is specified as a loamy silt (66% of silt, 19% of clay, and 15% of sand)
• Climatic situation of Mistelbach, Lower Austria (Fig. 1)
Procedure of erosion plot measures
• Surface runoff and eroded soil from the plot get collected at the downstream plot boundary
and piped to the measurement equipment
• Routing of the suspension of runoff and eroded material trough a measurement wheel.
The logging sensitivity of the meas. wheel is 0.1 mm of plot runoff suspension.
• Executing sample splitting for detecting the sediment (and nutrient) concentrations
• Rainfall and temperature data are recorded continuously at the sites
Fig. 2: Overview of the erosion experiment in Pixendorf, Lower Austria
(developing maize crop cover conditions)
Procedure of extreme rainfall event analyses
Concept: The significance of extreme rainfall events was analyzed by the overlay of the
physical impact (soil erosion) of the storms with the corresponding event occurrence
probability.
Different interrill erosion equations (Tab. 2) were applied and calibrated by means of recorded
erosion plot data. Extreme rainfall data (*Ann.1) was used to simulate soil erosion scenarios
with heavy rainstorm characteristics. As the plot length is limited by 15 meter, the general
assumption is to relate the total monitored soil loss to interrill erosion processes only. Basic
concept of this erosion study was to define lower and upper boundary assumptions for
infiltration rates, interception, surface water storage and various storm intensity distributions
(Fig. 6). In this way the model output is evaluated in a range of expected soil loss considering
different plot conditions (Fig. 8).
The occurrence probabilities of various rainstorms are applied as a weighting function. The
procedure is to examine the annually related probability of occurrence by 1/T where T is the
return period in years. And then to extract the probability P that the event of interest X is in
between the quantiles x and x’ ; so P(x ≤ X ≥ x’) = F(x’) – F(x). By cutting off at the 100 year
return period and starting at the lowest detectable event, the differences in exceeding
occurrence probability for every defined return period class was taken for weighting of the
physical impact of the event groups. The demonstrated case study regards to the 60 min.
duration rainfall events under spring and early summer maize field conditions only.
Fig. 3: Erosion plot; geometric definition by steel panels and runoff
routing outlet at the downstream boundary
Following analyses were investigated:
• Analysis of erosion events considering the erosion plot monitoring program
• Analysis and extrapolation of the pre-processed local extreme rainfall data (*Ann. 1)
• Calibration of the applied interrill erosion equations (Tab. 2) by means of the monitored data
• Simulation of the erosion processes using the extreme rainfall input data (Fig. 8)
• Overlay of the calculated erosion rates (Fig. 8) and the corresponding event occurrence
probability (Fig. 6) with the result illustrated in Fig. 9
Acknowledgements
This study was partly funded by the Government of Lower Austria and the Ministry of Agriculture and Forestry, Environment
and Water Management.
Special thanks to the Austrian Establishment of Meteorology and Geodynamics (ZAMG) for providing the pre-processed
rainfall data
Fig. 4: Measurement equipment; routing tube inlet, measurement
wheel, data logging and sample splitting
Stefan STROHMEIER, Andreas KLIK
Institute of Hydraulics and Rural Water Management
Department of Water – Atmosphere – Environment
BOKU Vienna, Muthgasse 18, 1190 Vienna
stefan.strohmeier@boku.ac.at, andreas.klik@boku.ac.at
University of Natural Resources
And Life Sciences, Vienna
Results
Constraints and assumptions
PEAK INTENSITY
BASE INTENSITY
Rainfall Intensity [mm/h]
(function of the return period [RP])
180,0
+ 20% [IPeak]
160,0
46
40
48
120,0
y = 8.38 Ln[RP]+14.70
34
26
IPeak= 25.59 Ln[RP]+55.52
140,0
43
42
- 20% [IPeak]
100,0
28
80,0
24
IMean = 8.38 Ln[RP]+14.70
60,0
21
15
40,0
5
9
60% [IMean ]
20,0
20% [IMean]
0,0
0,1
1
10
100
00:05
00:10
00:15
00:20
00:25
00:30
00:35
00:40
00:45
00:50
00:55
01:00
Return Period [years]
Time [min.]
Fig. 5: Pre-processed extreme rainfall data (*Ann. 1)
grey values are extrapolated
Fig. 6: Generation of the rainfall intensity distributions
Model calibration (Ki)
Applied modeling equations:
Ann.
Date
Precipitation
(mm)
Return Period
(years)
Soil Loss
(t ha-1)
1
2
CS*
26.05.1994
14.05.2002
51,0
9,3
75
0,5
2,3E+01
1,0E-01
09.06.2002
19,0
1,7
7,2E+00
VP**
06.08.2002
20,4
2,0
8,4E-01
5
6
7
13.05.2010
7,7
0,4
3,0E-02
26.05.2010
16,3
1,2
5,1E+00
28.05.2010
4,0
0,3
0,0E+00
1) Di = Ki ⋅ I 2 ⋅ S f
(Liebenow, 1990) WEPP
2) D = K ⋅ I ⋅ q ⋅ S
i
i
f
(Kinnell,1993)
0,2
[ ] Min, Max … Min. resp. Max. amount
(highest, lowest combination)
Meas. Events… data from erosion plot monitoring
60
Equation [1]
[1] Min
[1] Max
50
Equation [2]
[2] Min
-1
Interrill Erosion [t . ha ]
Weighting Factor
0,3
Equations [ ] … average result of all combinations
of input data (rainfall, infiltration,
interception resp. surf. storage)
ME (CS) …
data from conservational tillage
(CS) plot
ME (VP) …
data out of analyzed vegetation
period (mid summer)
Tab. 2: Applied interrill erosion equations
(Overlay)
Tab. 1: Recorded extreme event data
for model calibration purposes
0,4
Data points, lines (Fig.8)
3) D = K ⋅ I ⋅ q 12 ⋅ S 2 3 (Zhang, 1998)
i
i
* CS measured soil loss data from conservational tillage plot
** VP measured soil loss data under changed vegetation period conditions (August)
OUTPUT
Di …interrill sediment del. rate
Ki …interrill erodibility coeff.
I … rainfall intensity
q … flow unit discharge
S … slope
Sf …slope factor
Di = K i ⋅ I b
40
[2] Max
Equation [3]
[3] Min
30
[3] Max
Meas. Events
CS
20
ME (CS)
ME (VP)
0,1
10
(Result)
MODEL
General relation (Meyer, 1981)
Meas. Event
(No.)
4
Parameters (interrill equations Tab. 2)
Empirical interrill erosion equations
• Soil loss data
(erosion plot experiment)
• Rainfall event data
(erosion plot experiment)
3
• Interrill erosion is dominant process
(15 meter plot length)
• Extreme rainfall distribution is extrapolate able
(Log. Gaussian distribution), (Fig.5)
• Generated rainfall intensity distributions are
defined adequately (Fig. 6, *Ann.2)
• Empirical erosion equations describe the erosion
processes adequately (Tab. 2)
• Range of infiltration rates and interceptions resp.
surface storage are defined adequately (*Ann.3)
• Minimum erosive 60 min. rainstorm is defined
adequately (1/3 year return period; Fig. 7)
100
Equation [1]
90
[1] Min
Proportion of Total Interrill Erosion
(60 min. Events) [%]
Accumulated Rainfall (60 min.) [mm]
INPUT
200,0
53
51
80
[1] Max
Equation [2]
70
[2] Min
60
[2] Max
Equation [3]
50
[3] Min
40
[3] Max
30
20
10
0
VP
0
1/3-1/2 1/2-1
1-2
2-3
3-4
4-5
5-10
10-20 20-30 30-40 40-50 40-75 75-100
Return Period [years]
Fig. 7: Weighting of the event occurrences
0,1
1
0
10
Return Period [years]
Fig. 8: Simulated event based soil erosion
in relation to the event occurrence
100
0.33 - 1
1 - 10
10 - 100
Return Period Classes [years]
Fig. 9: Overview of the significance of erosive events related
to the return periods; 0* is defined to be 0,33
Conclusions
CONCLUSIONS
• Events in between one and ten years of return period produce more than 50% of the expected total soil erosion caused by interrill erosion processes (Fig. 9)
• Through pointing out the impact of single events by means of the occurrence probability, soil conservation techniques could be optimized easily by concentrating
on the significant erosion events
• Through further analyses as in the change in time duration and vegetation period and by accounting for the appearance frequency in between the event durations
the total expected annual soil erosion rate could be estimated and compared to the results of the direct erosion plot monitoring
*Ann.1: Pre-processed extreme rainfall data was provided by the Austrian Establishment of Meteorology and Geodynamics (ZAMG)
*Ann.2: Generation of four different intensity distribution curves, with different peak size and behavior.
*Ann.3: Generated infiltration rates ranged from 5 to 20 mm.h-1, interception ranged from 2 to 5 mm
References
Bradford, J.M., and G.R. Foster, 1996. Interrill soil erosion and slope steepness factors. Soil Sci. Soc. Am. J. 60: 909-915
Kinnell, P., 1993. Interrill erodibilities based on the rainfall intensity flow discharge erosivity factor. Aust. J. Soil Res. 31: 319-332
Liebenow, A.M., W.J. Elliot, J.M. Laflen, and K.D. Kohl, 1990. Interrill erodibility: collection and analyses of data from cropland soils. Transaction of the ASAE 33: 1882-1888
Zhang, X.C., AM.A. Nearing, W.P. Miller, L.D. Norton, and L.T. West, 1998.Modelling interrill sediment delivery. Soil Sci. Soc. Am. J. 62: 438-444