CATENA-01778; No of Pages 6
Catena 95 (2012) xxx–xxx
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A regional analysis of the effects of largest events on soil erosion
J. Carlos Gonzalez-Hidalgo a, b,⁎, Ramon J. Batalla c, d, e, Artemio Cerda f, Martin de Luis a, b
a
Department of Geography, University of Zaragoza, Spain
IUCA, University of Zaragoza, Spain
c
Department of Environment and Soil Sciences, University of Lleida, Spain
d
Forestry Science Center of Catalonia, Solsona, Spain
e
Catalan Institute for Water Research, Spain
f
Department of Geography, University of Valencia, Spain
b
a r t i c l e
i n f o
Article history:
Received 7 December 2010
Received in revised form 12 March 2012
Accepted 13 March 2012
Available online xxxx
Keywords:
Soil erosion
Daily events
USLE database
Regional analyses
a b s t r a c t
A large amount of geomorphic work is caused by a small number of extreme events that are mainly responsible for the time compression of geomorphic processes. The classic approach defines extreme events by their
magnitude and they are quantified by certain deviation from a central value. Alternatively, we define extreme
events as the largest events sorted by rank, whatever their absolute magnitude. In this case, events with equal
rank from two different sites can be responsible for different magnitudes of geomorphic work, e.g., the
amount of erosion. The new approach applied to soil erosion is that, whatever the magnitude of soil eroded,
erosion is a time compressed process and the percentage contribution to total soil erosion by the few largest
events (regardless of their magnitude) is negatively related to the total number of daily soil erosion events
recorded. To verify and generalize this approach, we used the most extensive daily soil erosion dataset available (USLE database). In this paper, we present a geographical analysis of the effects of largest daily event on
soil erosion by comparing 594 erosion plots located in agricultural fields under various climatic temperate
conditions across the central-east of the USA. Plots differ in cover, soil types and length of records. Results
indicate that: i) soil erosion in agricultural fields is a highly time compressed process and soil erosion
mean values calculated over short time periods are biased, regardless of the magnitude of daily events
recorded; ii) the relative effects of the n-largest daily events (whatever their magnitude) on total soil erosion
depends on the length of records and, particularly, on the total number of events recorded; iii) the derived
relationship of the required time length for records is generalized on a semi-continental scale; and iv) thus
seems to be independent of climate conditions. This new approach can help us to define the minimum number of recorded soil events needed to avoid bias in soil erosion evaluation, in other words: the minimum
period of field research on erosion should be evaluated not in years, but by the total number of daily erosive
events. Thus, the number of daily erosive events is the key parameter for characterizing soil erosion processes
at each measuring location.
© 2012 Elsevier B.V. All rights reserved.
1. Introduction
Due to the fact that rainfall is concentrated into short periods of
time, most geomorphic work (such as soil erosion) occurs in very
short temporal intervals (i.e., in few events) (Edwards and Owens,
1991; Larson et al., 1997; McBroom et al., 2003; Piest, 1965;
Wischmeier, 1962; Zhang and Garbrecht, 2002; Zuzel et al., 1993).
The magnitude-frequency analysis by Wolman and Miller (1960)
demonstrated that daily events, which may not necessarily be extreme events and represent short time intervals, could be responsible
for a high amount of sediment transport.
⁎ Corresponding author at: Department of Geography, University of Zaragoza, Spain.
Tel.: + 34 876553900.
E-mail address: [email protected] (J.C. Gonzalez-Hidalgo).
Long-term studies have shown that an individual year can result in
different volumes of soil loss, sometimes depending on the occurrence
of infrequent severe storms (Burwell and Kramer, 1983), showing
annual and inter-annual temporal compression. Thus, there is a great
deal of uncertainty in soil erosion mean values from short records,
because the results depend upon which study period is selected, and
on the occurrence or absence of extreme soil loss events (Burwell and
Kramer, 1983; Hjelmfelt et al., 1986; Lane and Kidwell, 2003). This
means, that for practical purposes, long-term records should be used
to evaluate soil erosion mean values (Edwards and Owens, 1991;
Larson et al., 1997; Piest, 1965) and simple extrapolation from shortterm records is likely to produce large errors in estimation (Kirkby,
1987).
The classic approach defines the extreme event as a rare, low
probability event, usually defined in relation to their exceeding certain threshold values (e.g. means, percentiles). Notwithstanding, the
0341-8162/$ – see front matter © 2012 Elsevier B.V. All rights reserved.
doi:10.1016/j.catena.2012.03.006
Please cite this article as: Gonzalez-Hidalgo, J.C., et al., A regional analysis of the effects of largest events on soil erosion, Catena (2012),
doi:10.1016/j.catena.2012.03.006
2
J.C. Gonzalez-Hidalgo et al. / Catena 95 (2012) xxx–xxx
time compression of geomorphic processes could be focused by a new
complementary approach based on the effects of largest events, defined
by rank, regardless of the magnitude of the daily erosion value. An
example of the viability of this approach was shown in Mediterranean
ecosystems (Gonzalez-Hidalgo et al., 2007) where research based on
erosion plots has revealed high temporal compression of soil erosion.
As an example, the 3-largest aggregated daily events produce an average of 50% of total soil eroded on annual and inter-annual scales. With
temperate ecosystems, similar results were found from an analysis of
300 plots from the USLE database (Gonzalez-Hidalgo et al., 2009a)
and research showed that the n-largest daily events, representing 10%
of the total daily erosion events recorded, produce on average 50%
of the total soil eroded. This study was carried out with no distinction
between the geographical origin of plots (i.e. effects of climate or local
differences were not addressed).
In this paper, we investigate the geographical differences in time
compression of soil erosion by analysing the effects of the n-largest
events on total soil erosion. For this purpose we used information
from daily data provided by the USLE database. The study analyses
in detail hundreds of soil loss measurements obtained from erosion
plots under different climate conditions on a semi-continental scale.
The number of daily events recorded in the plots differs, and plots had
varying plant covers, crops and soil types. Thus, the general hypothesis
of the study was that the time compression of soil erosion would follow
a general pattern in which the relative contribution of the n-largest
daily erosion events do not differ under different climatic conditions,
but rather depends on the number of events recorded (i.e. period of
time with records). Furthermore, we hypothesized that this behaviour
would not depend on the existence or absence of recorded extreme
events.
2. Database and methods
2.1. Database
Daily erosive events from the original 594 erosion plots and 35
field sites provided by the United States Department of Agriculture
(USDA) were analysed. Plots were located in different agricultural
regions in the eastern half of the North American subcontinent and
divided in the following regions: Midwest-North (226), New EnglandNorth Atlantic (100), South (79) and South East (189). Field sites are
located under different climate types. Rainfall amounts and rainfall erosivity vary from southeast (highest) to north and northwest (lowest)
(see Wischmeier and Smith, 1978). Table 1 lists the various research
stations and number of plots per site. Their location is shown in Fig. 1.
The total number of daily records is 44,528, and data collection times
range from 1930 to 1971. Plots differed in soil type and management
(including crop types and cover).
2.2. Methods
In a time data series, when the events are ordered by magnitude, the
largest is rank 1, the second largest is the second rank event, etc. regardless of the absolute magnitudes of the events. Therefore ranks 1, 2, 3…,
could differ in magnitude between plots and furthermore the rank 1, 2
3… should not necessarily be considered as extreme events (see general
definition in the Introduction section). Also, as the time record progresses in the same plot (i.e. new events are recorded), events 1, 2, 3,
etc. will change accordingly.
The aforementioned approach has already been presented recently as
complementary to the classic magnitude-frequency analysis (GonzalezHidalgo et al., 2007, 2009b) and it works as an indicator of the temporal
compression of geomorphic processes. This is the approach followed in
the present study, and it is exemplified by the effects of the 5-largest
daily events on total soil erosion, after analysis of aggregations of the 3,
5, 10, 15, 20 and 25 largest daily events.
2.2.1. Contribution of n-largest events to total soil loss
To analyze the contributions of the n-largest daily events to total soil
loss, the complete series of daily erosive events per plot were ordered
by magnitude. Next, the total amount of soil erosion during the entire
record period from each plot was calculated and the percentage contribution of each event computed. Finally, the percentage contribution of
the n-largest events from each plot was added. A simplified example
for the 5-largest events is shown in Table 2 using random data. The
table shows a set of individual events (column Date and Value) and
the rank of each event (column Rank), with the amount of “soil eroded”
being 11.55 g m- 2. After ranking the event by magnitude and calculating the individual percentage contribution of each event to the total,
the value of the contribution of the 5-largest accumulated events is
36.7%.
2.2.2. Geographical analysis
Analysis of geographical variation in the contribution of the nlargest daily events to total soil erosion was done using a general linear
model (GLM) because it allows normally distributed dependent variables
and categorical or continuous independent variables to be included. The
univariate (nested) ANOVA model was selected, taking the number of
events as a cofactor, the region as a fixed factor, and the site as a random
effect. The p level was set at 0.05. Further information on the soil types,
plant cover, tillage systems and management practices is not currently
available and was not included in the model.
Table 1
USLE field research stations. N, number of plots per site.
Region
State
Site
N
Region
State
Site
N
Midwest-North
Midwest-North
Midwest-North
Midwest-North
Midwest-North
Midwest-North
Midwest-North
Midwest-North
Midwest-North
Midwest-North
Midwest-North
Midwest-North
Midwest-North
Midwest-North
South-East
South-East
South-East
South-East
Iowa
Missouri
Iowa
Iowa
Illinois
Iowa
Illinois
Wisconsin
Wisconsin
Missouri
Minnesota
Illinois
Ohio
South Dakota
Arkansas
S. Carolina
Mississippi
N. Carolina
Beaconsfield
Bethany
Castana
Clarinda
Dixon Springs
Independence
Joilet
LaCrosse
Madison
McCredle
Morris
Urbana
Zanesville
Madison
Batesville
Clemson
Holly Springs
Raleigh
2
37
6
50
20
2
13
39
5
31
3
4
11
3
14
14
13
58
South-East
South-East
South-East
South-East
South-East
New England-North
New England-North
New England-North
New England-North
New England-North
New England-North
New England-North
New England-North
South
South
South
South
S. Carolina
Mississippi
N. Carolina
Georgia
Georgia
New York
New Jersey
Virginia
New York
New York
New Jersey
New Jersey
Maine
Oklahoma
Kansas
Texas
Texas
Spartanburg
State College
Statesville
Tifton
Watkinsville
Arnot (Ithaca)
Beemerville
Blacksburg
Geneva
Marcellus
Marlboro
New Brunswick
Presque Isle
Guthrie
Hays
Temple
Tyler
12
11
12
18
37
16
6
15
8
2
24
8
21
5
26
30
18
Atlantic
Atlantic
Atlantic
Atlantic
Atlantic
Atlantic
Atlantic
Atlantic
Please cite this article as: Gonzalez-Hidalgo, J.C., et al., A regional analysis of the effects of largest events on soil erosion, Catena (2012),
doi:10.1016/j.catena.2012.03.006
J.C. Gonzalez-Hidalgo et al. / Catena 95 (2012) xxx–xxx
3
Fig. 1. Spatial distribution of field research station USLE database.
Thus, we used the total number of events recorded per plot as a surrogate for time, because as time passes, an increasing number of events
is accumulated at each plot. The geographical variations were indicated
by region, with the site as the indicator of more local conditions, such as
soil type, plant cover, tillage systems etc.
Because the number of events recorded varies among different sites
and regions, the resulting GLM computation estimated the marginal
mean values of the dependent variable (i.e. soil erosion contribution
of n-largest events) for a common number of events (58 events in this
case, representing the mean number of events recorded from all sites).
It should be noted that these marginal mean values are estimated
based on the selected linear model.
3. Results
The time compression pattern of soil erosion in the global data base
for the effect of the n-largest daily events is expressed by an empirical
power law, with the total number of erosive events as an independent
variable, and the percentage contribution of n-largest daily events to
total soil erosion as the dependent variable. This pattern for the 5largest events is shown in Fig. 2 for different regions, with the power
law being statistically significant in all cases (pb 0.05).
The global results from GLM (nested ANOVA) are shown in Table 3
for the 5-largest daily events. The estimated contribution of the 5largest daily events to total soil erosion varies greatly in relation to
Table 2
Largest event approach. Example of calculation of contribution of 5-largest event to total soil loss during hypothetical 20 events. (Data at random, see text for explanation).
Date
01/01/1920
02/01/1920
03/01/1920
04/01/1920
05/01/1920
06/01/1920
07/01/1920
08/01/1920
09/01/1920
10/01/1920
11/01/1920
12/01/1920
13/01/1920
14/01/1920
15/01/1920
16/01/1920
17/01/1920
18/01/1920
19/01/1920
20/01/1920
Value
(g m- 2)
Rank
0.72
0.17
0.63
0.81
0.83
0.55
0.76
0.51
0.35
0.63
0.74
0.07
0.58
0.65
0.26
0.73
0.86
0.68
0.98
0.06
8
18
11
4
3
14
5
15
16
12
6
19
13
10
17
7
2
9
1
20
Daily events ranked by magnitude
Date
Value (g m- 2)
Rank
Single event contribution
to total (%)
Accumulated contribution
of n-largest (%)
19/01/1920
17/01/1920
05/01/1920
04/01/1920
07/01/1920
11/01/1920
16/01/1920
01/01/1920
18/01/1920
14/01/1920
03/01/1920
10/01/1920
13/01/1920
06/01/1920
08/01/1920
09/01/1920
15/01/1920
02/01/1920
12/01/1920
20/01/1920
Total
0.98
0.86
0.83
0.81
0.76
0.74
0.73
0.72
0.68
0.65
0.63
0.63
0.58
0.55
0.51
0.35
0.26
0.17
0.07
0.06
11.55
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
8.5
7.4
7.2
7.0
6.5
6.4
6.3
6.2
5.9
5.6
5.5
5.4
5.0
4.7
4.4
3.0
2.3
1.5
0.6
0.5
8.5
16.0
23.1
30.1
36.7
43.1
49.4
55.6
61.4
67.0
72.5
78.0
82.9
87.7
92.1
95.2
97.4
98.9
99.5
100.0
Please cite this article as: Gonzalez-Hidalgo, J.C., et al., A regional analysis of the effects of largest events on soil erosion, Catena (2012),
doi:10.1016/j.catena.2012.03.006
New England / North Atlantic
100
Contribution (%) 5-largest
J.C. Gonzalez-Hidalgo et al. / Catena 95 (2012) xxx–xxx
Contribution (%) 5-largest
4
South East
100
-0,3604
y = 218,73 x
2
R = 0,7034, p <0.05
75
50
25
0
0
50
100
150
200
250
300
350
400
-0,4123
y = 250,21x
2
R = 0,5886, p < 0.05
75
50
25
0
0
50
100
150
200
250
300
350
400
Events
Mid-West / North
100
Contribution (%) 5-largest
Contribution (%) 5-largest
Events
South
100
-0,4084
y = 269,98x
2
R = 0,6475, p <0.05
75
50
25
0
0
50
100
150
200
250
300
350
400
-0,4576
y = 318,05x
2
R = 0,8282, p <0.05
75
50
25
0
0
50
100
150
Events
200
250
300
350
400
Events
Fig. 2. Temporal compression of soil erosion in USLE data base. Relationships between number of erosive events per plot and percentage contribution of 5-largest daily event by
Region (see Table 1).
the total daily events recorded from each plot (Events (log), p b 0.001,
Table 3). This contribution also differs significantly, due to local effects (Site, p b 0.001). In contrast, the contribution of the 5-largest
daily events to total soil erosion does not differ significantly between
regions (p = 0.632, Table 3).
According to these results, the contribution of the 5-largest daily
events to total soil erosion (estimated for a common number of events
of 58) is 47% in the South East region, 49% in the South, 51% in New
England-North Atlantic and 50% in the Midwest-North region.
Similar results are obtained when analysing the contribution to total
soil loss for the 3-largest, 5-largest, 10-largest, 15-largest, 20-largest
and 25-largest daily events, and in Table 4 we show the p level for
each factor accordingly n-largest events. Such results suggest that,
despite variations due to different numbers or events considered, or
because of differences in local environmental conditions at each site,
the contribution of large events to soil erosion does not differ between
the regions analysed.
4. Discussion
Previous projects have documented the effects of extreme events
on total soil erosion and sediment transport, both on plot (Burwell
Table 3
Generalized Linear Model (univariate nested ANOVA analysis). The 5-largest daily
event contribution factors on soil erosion in USLE dataset.
Source
Intersection
Region
Events (log)
Site
Hypothesis
Error
Hypothesis
Error
Hypothesis
Error
Hypothesis
Error
SS III
df
MS
F
Sig
79.37
3.87
0.06
1.35
8.39
4.12
1.77
4.12
1
440
3
36
1
556
31
556
79.378
0.009
0.021
0.037
8.391
0.007
0.057
0.007
9017.3
0.001
0.5
0.632
1132.4
0.001
7.7
0.001
SS III: Sum of Squared (type III); MS: Mean Squared; df: degree of freedom; F: Fisher
test; Sig.: p level of significance. Events (log): number of events transformed by log.
Intersection is constant term.
and Kramer, 1983; Hjelmfelt et al., 1986; Piest, 1965; Wischmeier,
1962; Zhang and Garbrecht, 2002; Zuzel et al., 1993) and catchment
scales (Douglas et al., 1999; Edwards and Owens, 1991; Lane and
Kidwell, 2003; Larson et al., 1997; Lenzi et al., 2003; McBroom et al.,
2003; Nearing et al., 2007; Polyakov et al., 2010). Extreme events are
convincing arguments in assessing the importance of time compression
of soil erosion processes, and explaining why extreme events are a classic issue in geomorphology that have received on-going attention; more
so at the present because of the increasingly apparent problem of global
change. However, soil erosion is a temporal compressed process, even
in cases where extreme events are absent from the data record. Thus,
the time frame of soil erosion research requires careful attention, and
the effect of single events must be separated when designing erosion
control technologies and the annual average for conservation planning
(Stroosnijder, 2005). Thus, the classic question of how long an erosion
plot should be maintained in the field is a critical issue as yet unsolved.
The largest daily event approach is focused on the second question
(annual average for conservation planning) and is based on the relationship between the percentage contribution of n-largest daily events (rank
ordered) to total soil erosion and the total number of events recorded.
Under this approach, although events are ranked by magnitude, the nlargest event (1-largest, 2-largest, ….10-largest etc.) of soil eroded in a
plot does not need to be an extreme event, but it could contribute to a
high proportion of total soil eroded, depending on the length of recorded
events.
As has been indicated, this approach was presented in a previous
paper using the 5-largest events and 300 erosion plots from USLE dataset,
but no information was available on the geographical differences between
Table 4
Significance p level factor for n-largest daily event contribution on soil erosion in USLE
dataset. Resume from Generalized Linear Model (univariate nested ANOVA analysis, as
in Table 3).
Region
Events (log)
Site
3-largest
5-largest
10-largest
15-largest
20-largest
25-largest
0.677
0.001
0.001
0.632
0.001
0.001
0.402
0.001
0.001
0.260
0.001
0.001
0.306
0.001
0.001
0.091
0.001
0.001
Please cite this article as: Gonzalez-Hidalgo, J.C., et al., A regional analysis of the effects of largest events on soil erosion, Catena (2012),
doi:10.1016/j.catena.2012.03.006
J.C. Gonzalez-Hidalgo et al. / Catena 95 (2012) xxx–xxx
5
5-largest event
contribution total (%)
100
Random
Equal distributed
Arnot_1_7
Zanesville_1_8
Statesville_1_4
75
50
25
0
0
50
100
150
200
250
300
350
400
Daily events
Fig. 3. Relationship between number of erosion events and 5-largest event contribution to total (lag + 1) in a random, equal distributed series, and in three USLE plots.
agronomic divisions and specific local conditions. In this paper, with a
new set of plots (594, twice those for previous research), we show that
the relationship is similar for different n-largest aggregation daily events
for contrasting environmental conditions amongst regions. Furthermore,
the relationship persists geographically and no significant differences between agronomic divisions have been found under different climate conditions. Therefore, on the semi-continental scale analysed (mid-eastern
USA) time compression of soil erosion in agricultural plots was displayed
regardless of climate conditions. Notwithstanding, not all the climate conditions have been analysed because data in the USLE dataset does not represent all climatic regimes, such as Mediterranean climate areas, where
previous analysis has shown high temporal compression of soil erosion
on an annual and inter-annual scale (Gonzalez-Hidalgo et al., 2007). Further analysis should be done to verify the generalization of this pattern
using a more detailed daily erosion data set, which is not available at
present.
A final question arises on why this pattern occurs. In a set of temporal
data equal by magnitude (i.e. equally distributed), as total records increase at interval of n+1 event, the percentage contribution of the nlargest events to the total (n+1) decrease asymptotically, and the same
occurs if the data series is random. For each plot individually, as more
events occur (i.e. along the “life of a soil erosion plot”), the effect of the
largest daily event on total soil erosion at an interval of n+1 decreases.
In Fig. 3, examples from the USLE database are shown with equally distributed and random series data. Thus we may assume an ergodic
transformation.
The simple terms of ergodic hypothesis is that “the mean of observations of an individual made over time is equal to the mean of observations
made of many individuals a single moment in time over an area” (Thorn,
1988, p. 47; also Thornes and Brunsden, 1977, p. 24), or in simplified form
“the hypothesis that, under certain circumstances, space and time can be
considered as interchangeable” (Chorley and Kennedy, 1971, p. 349). Following this reasoning, it is assumed that the percentage contribution of
the n-largest events to total soil erosion in a different set of plots, each
one with a different period of records, follows the pattern of the nlargest decrease in contribution in a single plot.
Soil exhaustion in erosion plots is a critical issue in research. It has
been identified by the decrease of annual soil erosion and the increase
of surface stoniness over time (Ollesch and Vacca, 2002), by the change
in rainfall threshold erosivity (Boix-Fayos et al., 2007) etc. This is probably true in small plots after two or three years, particularly if the soil is
not protected by plant cover and under high rates of rainfall erosivity,
but it is more difficult to accept in larger plots, such as the USLE plots
(dimensions 22 × 2 m) located in agricultural soils with a permanent
supply of soil after tillage. Furthermore, in the examples shown in previous pages, in many cases the largest daily erosive events arose at the
end of records and accumulated soil erosion increased over time, with
no sign of exhaustion. In conclusion, the time compression pattern
shown in this research in the USLE data set does not seem to be affected
by soil exhaustion.
Consequently, the most plausible explanation for the decrease in
the contribution of aggregated n-largest events seems to be linked
to finite-size effects for rain-wash erosion, which constrain the maximum erosion value events that can occur in a given area (Boardman
and Favis-Mortlock, 1999). Therefore, as the time record enlarges, the
number of events lower than the extreme values will increase. Whatever the magnitude, longer records under such an assumption should
result in a decrease in the percentage of largest events. In any case, if
soil exhaustion occurs, then the question would be to identify a point
between a minimum length of record, to ensure that the measurements are trustworthy, and at the same time to avoid the effect of
soil exhaustion.
Wischmeier and Smith (1978) stated that “care must be taken to
ensure that the duration is sufficient to account for cyclical effects
and random fluctuations in uncontrolled variables whose effects are
averaged in the USLE factor values”. The time frame varies from author
to author and usually is expressed in years (Boix-Fayos et al., 2007;
Lane and Kidwell, 2003; Ollesch and Vacca, 2002; Risse et al., 1993).
We suggest using the largest event approach to select a temporal
threshold value for soil erosion studies, taking into account not a period
in years, but to register a minimum daily erosion events to achieve a
threshold of soil eroded by the n-largest selected.
5. Conclusions
The relationship between largest daily contribution events to total
soil loss in a large set of plots from USLE database from various agricultural regions under different climate conditions, soil types, tillage
systems and plant cover was studied. The main conclusions can be
drawn as follows: i) soil erosion is a compressed process in time, independent of the occurrence of extreme events. A few number of events
(the largest ones, whatever the magnitude of soil eroded) control the
total soil eroded; ii) the analyses showed that the most important
source of variation of percentage contribution of the n-largest daily
event to total soil loss is caused by the total number of erosive events
recorded, thus soil erosion compression in time is higher when the period of records is short, regardless of the occurrence of extreme events;
and iii) no variations in this pattern among agricultural regions were
found. The hypothesis presented in this paper is climate-independent
and geographically generalized on the semi-continental scale of the
USA. To further generalize on a global scale, new analyses of more detailed
daily data sets from other climate conditions, such as Mediterranean,
should be performed; iv) Given the negative relationship between the
relative contribution to total soil loss by the n-largest event and time
Please cite this article as: Gonzalez-Hidalgo, J.C., et al., A regional analysis of the effects of largest events on soil erosion, Catena (2012),
doi:10.1016/j.catena.2012.03.006
6
J.C. Gonzalez-Hidalgo et al. / Catena 95 (2012) xxx–xxx
(i.e. total events recorded), to avoid the bias induced by largest events in
short records, and to validate the soil erosion rates of field research, we
suggest considering a minimum number of daily events according to
the percentage of soil eroded by the n-largest events selected, instead of
a minimum number of years of field research on erosion plots.
Acknowledgments
An earlier version of this manuscript and research on the effects of
the largest daily event on erosion and sediment transport were discussed with Prof. J.B. Thornes from 2006. His comments, suggestions
and corrections allowed us to improve our research and draft.
We would like to thank the USDA for making available the original
dataset, and Dr P. Kinnell, Canberra University, who facilitated data
from more than 300 plots and information on these (at present not
available via internet web site USLE database), increasing the sites
and achieving an improved, denser spatial distribution of soil erosion
data in the mid-east of USA.
Financial support was given by Gobierno de España, Proyectos
CGL2007-65315-CO3-01, CGL2008-05112-C02-01, CGL2011-27574C02-01, Gobierno Regional de Aragón DGA, and Grupo de Investigación Consolidado “Clima, Agua, Cambio Global y Sistemas Naturales”
(BOA 69, 11-06-2007).
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Please cite this article as: Gonzalez-Hidalgo, J.C., et al., A regional analysis of the effects of largest events on soil erosion, Catena (2012),
doi:10.1016/j.catena.2012.03.006