An approximation of rainfall-runoff factor in USLE and RUSLE in North and
1
Northwestern of Jordan.
2
N.I. Eltaif 1, M.A. Gharaibeh 2, F. Al-Zaitawi 2
3
1,2 Department
of Natural Resources and The Environment, Faculty of
4
Agriculture, Jordan University of Science and Technology, P.O. Box 3030, Irbid
5
22110, Jordan
6
Erosivity data can be used as indicator of regional variations in erosion potential. In
7
8
9
10
this study, a simplified procedure is adopted to compute R value by correlating R in
11
both USLE and RUSLE with annual rainfall amount or modified Fournier index (F
12
mod). Ten out of fifteen years of monthly rainfall erosivity values were computed for
13
18 standard daily-read rainguage stations in North and Northwestern of Jordan. Iso-
14
erodent map was obtained by superimposing computed values of erosivity (R) and
15
pre-prepared isohyetal map for Jordan. A new picture of erosivity over the whole area
16
was obtained. The mean annual erosivity values in the map may reflect the risk of
17
erosion by rainsplash, overland flow and rills.
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Key words: Erosivity; Fournier index; iso-erodent map; RUSLE; splash erosion
19
Abstract
20
1
Corresponding author Tel.: +1-962-2-720-1000; Fax: +1-962-2-7095-069
Email: nieltaif@just.edu.jo
1
Introduction
21
Soil erosion causes loss of soil productivity and deposition of sediments which may
22
pollute (eutrophy) surface and underground water resources, clog streams, reservoirs,
23
and estuaries( Hillel 1998). The erosion process is also a major transport mechanism
24
for agricultural chemicals , therefore, it is important to reduce soil erosion and
25
understand its effects ( Hill et. al ; 1991). Universal soil loss equation (USLE) has
26
became the major conservation-planning tool used in the United States and other
27
countries of the world. It is currently the most successful and most used prediction
28
model. In 1985 the USDA decided that the USLE should be revised ( RUSLE ) to
29
incorporate additional research, new data sets and improved computer technology that
30
allows users to easily input, update and store the necessary data for assessing soil loss
31
(Rapp et.al ; 2001 ).
32
In most of the developing countries like Jordan there are no sufficient rainfall records
33
available to calculate erosivity nationwide. In such cases, an attempt has to be made,
34
for the recording stations where erosivity can be determined, to find a more widely
35
available rainfall parameter which significantly correlates with erosivity. A best fit
36
regression equation was used to predict erosivity values from this correlation (
37
Morgan 1996 ) .
38
The quantitative expression of the rainfall-runoff parameter causing soil erosion is the
39
R factor . The climatic erosivity data can be used as an indicator of potential erosion
40
risks( Morgan, 1986 ). It is greatly influenced by the intensity and duration of
41
precipitation events and by the amount and rate of the resulting runoff. The R-value
42
incorporates total precipitation, intensity and duration patterns of rainfall. Differences
43
in the R factor reflect differences in precipitation patterns between regions and high
44
2
R- values indicate more erosive weather conditions. However, R-values can be
45
obtained from iso-erodent maps, tables or calculated from historic weather data
46
(Renard et.al 1993a). Lack of long-term rainfall intensity data in some countries
47
makes applying the USLE more difficult, which resulted in high interest to explore
48
new methods and equations to calculate the erosivity factor R using more readily
49
available precipitation data. The annual value of the R factor related to annual
50
precipitation was computed using equation proposed by Deumlich et al. ( 2006):
51
R   12.98  0.0783 * P , Whereas: R = R-factor in English units, P = precipitation
52
(mm year-1).
53
The significantly correlated index with rainfall erosivity is modified Fourniers p²/P
54
index. Maps on this empirical index p²/P, were prepared for different countries
55
(Fournier 1960). A correlation between the Modified Fournier Index (Fmod) and R was
56
1.9
developed for the USA and for some regions of Africa: R  0.03 Fmod
( Arnoldus
57
1977,1980).
58
Renard and Freimund (1993) used more reliable equations to evaluate R value from
59
R  0.07397 F 1.847 17.2 , when F<55mm, and
60
modified Fournier index (F):
R  95.77  6.08 F  0.477 F 2 17.2 , when F>=55mm.
61
Wischmeier et al. (1958) evaluated the R factor in several places around the world.
62
For example in Tunisia it ranged from 60 to 300, in Morocco from 50 to 300, and in
63
North America ranged from 62 to 220 hundreds of foot tons inch acre-1 h-1 (To covert
64
to SI units , MJ mm ha-1 h-1 year-1 multiply by 17.02) .
65
The objective of this paper is to predict and approximate the annual erosivity using
66
RUSLE and USLE equations. An attempt is made to introduce provisional erosivity
67
3
maps for several sites in north and northwestern part of Jordan which may help in
68
rating erosivity and assessment of erosion risk.
69
70
Materials and methods
71
The study was conducted in north and northwestern part of Jordan located between
72
coordinates of 32º 48´ to 32º 04´ N, and 35º 88´ to 35º 72´ E, just north Amman. The
73
study area is about 370km2 with an average annual rainfall around 480mm, occurring
74
mostly from November to April (rainy season). Information on rainfall amount,
75
intensity and the maximum 30-minute intensity (EI30) was collected for three sites
76
namely Gmaim, Kufranjeh and As-Salt. Pluviometric data over 15 years in 15 other
77
sites were obtained from daily-read rain gauges located in each location to
78
accommodate the whole area of study . The sites are ; Kherbet El-Wahadneh, Um
79
Qais, Huwwara, Huson, Nueiyme, Turra, Wadi El-Yabis, Ras Muneef, Ajlun Police
80
Station, Bal`ama, Jerash, Dibbin, Qafqafa, Wdi Es-Sir, and Sahab. The most
81
problematic years were eliminated because of the expected bias in rain gauge
82
measurements in the scope of the current research.
83
Evaluation of Rainfall-Runoff Factor R
84
The rain erosivity index is calculated for three sites vertically aligned in the Eastern
85
Jordan Valley Tributary basin; Gmaim (in the upper part of the basin); Kufranjeh (in
86
the middle part of the basin) and As-Salt (in the lower part of the basin). The R factor
87
is usually calculated of EI values measured over 20 years to accommodate what is
88
known climatic period . Daily rainfall data for each of the three sites were collected
89
during rainy seasons (November- March) over 15 years (from 1989 to 2003; less than
90
climatic period). However, due to technical reasons, 5 years were eliminated from
91
4
analysis in our study secondary to missing dates. The R value is the sum of erosive
92
storm EI30 values occurring during a mean year.
93
R
 EI
100
30
…………. (1)
94
Where R in MJ mm ha-1 h-1 year-1, and EI30 is the total storm energy (E) in MJ ha-1
95
multiplied by the maximum 30-min intensity (I30) in mm hr-1. Calculations of EI30 in
96
USLE and RUSLE differ in the equation used to express the relationship between the
97
kinetic energy and the rainfall intensity. The equations proposed by Wischmeier and
98
Smith ( 1965) and Brown and Foster (1987) were adopted in calculation of kinetic
99
energy in USLE and RUSLE respectively .The relationship between the kinetic
100
energy and the intensity of the storm according to the USLE was calculated as
101
follows:
102
e  0.119  0.0873 ( log 10 i) ………….. (2)
103
Where (e) is the kinetic energy in MJ ha-1 mm-1 h-1per unit depth, and (i) is the
104
intensity in mm h-1. In RUSLE, the kinetic energy was mathematically calculated as:
105


e  0.29 1  0.72 e 0.05 i ………………. (3)
106
Where, (e) is the kinetic energy in MJ ha-1 mm-1 h-1 per unit depth, and (i) is the
107
intensity in mm h-1. The RUSLE contains a correction for R that is a function of the R
108
factor and slope. On flat surfaces, raindrops tend to absorb rainfall energy and retard
109
erosion (Mutchler and Larson, 1971). Multiplier was proposed to account for ponding
110
on flat slopes (Renard et. al 1993a).
111
5
112
The modified Fournier index is defined as:
 p ……………… (4)
2
Fmod 
113
P
Where, p is the average monthly precipitation and P is the annual precipitation. For
114
the three stations, Gmaim, Kufranjeh, and As-Salt, the results of the modified
115
Fournier Index were calculated using the average of 10 years rainfall data. The index
116
was calculated for the 15 other sites using the average of 8 years rainfall data (1998 –
117
2003).
118
Results and discussions
119
Rainfall- Runoff Erosivity Factor (R):
120
The preliminary USLE erosivity factor was calculated for the three sites Gmaim ,
121
Kufranjeh and As-Salt using equations 1 and 2 alongside with 10 years of rainfall
122
data. For the same sites and with same rainfall data, RUSLE erosivity factor was
123
calculated using equations 1 and 3. Average values of R obtained in USLE were 865,
124
506 and 354 MJ mm ha-1 h-1 year-1, whereas those R-values in RUSLE were 673, 388
125
and 280 MJ mm ha-1 h-1 year-1 for Kufranjeh, As-Salt and Gmaim , respectively
126
(Table1). It is apparent that USLE equation has a tendency to overpredict erosivity
127
values. Renard et al. 1993a recommended to use equation 3 in all future calculations
128
of rainfall energy since it seems to better fit the data at lower intensities ( as likely to
129
be in Jordan).
130
131
132
6
Although the erosivity values are considered low for Jordan compared with values
133
reported in literature, contribution of the other factors in the USLE and RUSLE
134
equations are significant on the amounts of soil eroded. This was proved by a study
135
conducted at Jordan University in corporation with the Food and Agriculture
136
Organization (FAO), where high soil losses reported. Actually, more than 200 t ha-1 of
137
soil is lost in highlands while it ranged between 10 – 200 t ha-1 for the other regions in
138
Jordan (Battikhi and Arabiat 1983).
139
Prediction of R-values for other sites in North and North-west of Jordan for
140
rainfall data:
141
Prediction of R-values using USLE: Using the preliminary data acquired by applying
142
the USLE method (R1 in table 1), a highly correlated power relationship was found
143
between R values and the mean annual precipitation P for the three stations under
144
consideration (Fig 1). The resulting equation from this relationship is:
145
R  4  10 6  p 2.946 …………. (6)
146
From the calculated R-values for the three sites of interest, R-values have been
147
estimated from the rainfall data for the other fifteen sites using equation 6 (Table 2,
148
column 4). The highest value calculated was 944 MJ mm ha-1 h-1 yr-1 in Kufranjeh and
149
the lowest was 32 MJ mm ha-1 h-1 yr-1 in Bal'ama. R values in foot tons acre-1 inch-1 in
150
seven places in central and northern parts of Iraq ranged between 19.4 (330 in SI unit
151
) for Baghdad to 95.8 ( 1630 in SI units ) for Suliamaneiah ( Eltaif & Abbas,1987).
152
The attraction of using readily available data on amounts of rainfall led to search for a
153
method applicable worldwide.
154
7
A modified version of Fournier Index (Fmod) was proposed by the Food and
155
Agriculture Organization (FAO) through soil degradation study (Arnoldus 1980), and
156
first approximation of erosivity using this method (Fmod) was calculated using
157
equation (5). Hussien (1998) used in his study a modified Fournier index to estimate
158
R-factor in northern of Iraq due to the lack of extensive soil loss records and recording
159
rain gauge network in the region.
160
From the mean monthly precipitation values of the 18 meteorological stations, it was
161
possible to calculate Fmod-values (Table2, column 3). A power relationship was found
162
between EI30 and Fmod for the three meteorological stations (Figure 2).
163
R  4 10 6  Fmod
3.6363
…………….. (7)
164
Values of R for the 18 stations were calculated by means of equation (7) and listed in
165
table 2, column 5. The final average erosivity Index R in USLE was calculated for all
166
stations as an average of the two R-values obtained by adopting equations 6 and 7
167
(Table 3, column 6).
168
Prediction of R-values using RUSLE: The same method used in the previous section
169
to calculate USLE-R-values for the 18 different stations was repeated using the
170
revised preliminary R-values of Kufranjeh, As-Salt and Gmaim (R2 in table1). A
171
highly correlated power relationship between R values and the mean annual
172
precipitation P was obtained (Figure 3).
173
The resulting equation of this relationship is:
174
R  4 10 6  p 2.9012 …………….. (8)
8
175
By adopting equation 8, revised R-values were estimated for the 18 sites listed in
176
table3, column 4.
177
A power relationship was found between the revised R-values and Fmod for the three
178
meteorological stations (Figure4). The resulting equation from this relationship is:
179
R  4  10 6  F 3.5874 ………………. (9)
180
Values of R for the 18 stations were calculated by means of equation (9) and listed in
181
table3, column 5. The final average erosivity Index R in RUSLE was calculated for all
182
stations as an average of the two R-values obtained by adopting equations 8 and 9
183
(Table 3, column 6).
184
It should be noted that differences in mean annual R-values between the three stations
185
(Kufranjeh, As-Salt and Gmaim) were not only due to differences in mean annual
186
precipitation, as directly shown in equations 6 and 8, but also related to differences in
187
rain intensity. Monthly distribution of rainfall could also affect the R-value; therefore
188
cumulative percentage of annual R by month is plotted in Figure 5 for the three
189
stations. For each month, R represents the accumulation of the averages of the
190
maximum five-years of the erosivity calculations over the period from 1989 – 2003 in
191
Kufranjeh, As-Salt and Gmaim. The shape of the three curves in Fig 8 indicates that
192
the pattern of rain distribution in the three sites was almost the same regardless the
193
amounts of rainfall . This may indicate that precipitation and its intensity are the most
194
important parameters contributing to evaluating erosivity value.
195
Results in table X and figures 6 and 7 indicate that the adopted equations to predict
196
preliminary erosivity factor from precipitation by Deumlich et al.(2006) and Fmod
197
9
(modified Fournier) developed by Arnoldus (1980) or Renard and Freimund (1993)
198
were not completely satisfactory. Most of such equations need detailed and accurate
199
rainfall data, and their applications requires considerable work for collecting and
200
analyzing data, which is time consuming and requires considerable resources. Since
201
our equations show sufficiently reliable results (compared to R values suggested for
202
similar conditions) and relatively easy to use, our equations are probably more
203
suitable for prevailing conditions in Jordan than Deumlich et al.(2006) or Arnoldus
204
(1980 ) or Renard and Freimund (1993) equations for predicting R factor. However,
205
Stocking (1980) commented that factors such as Fournier p2/P and EI30 have no
206
physical basis and are designed to give an idea of the erosivity over large areas. They
207
are therefore, good for purposes but it is very erroneous to extrapolate their use to
208
other cases and smaller cases.
209
Iso-erodent Map of Jordan: The average value of R in tables 2 and 3 could be
210
considered the most acceptable values under the present situation (Table 4).
211
212
213
214
One of the objectives of this research is to introduce an isoerodent map for Jordan. In
215
order to draw this map, a curve related the mean annual precipitation values (P) and
216
the final average R-values in table 4 of the 18 stations was plotted (Fig 8). The
217
resulted equation of this relationship is:
218
R  1 10 6  p3.0904 ………………. (10)
219
10
Iso-erodent map was prepared by superimposing values of erosivity ( R ) from
220
equation ( 10 ) and the isohyetal map of Jordan (Ministry of Water and Irrigation-
221
Jordan Water Authority; Water Resources and Planning Department) . A new picture
222
of erosivity over the whole area is obtained (Fig 9).
223
As shown in table 4, the highest erosivity value 785 MJ mm ha-1 h-1 year-1 (46
224
hundreds of foot tons inch acre-1 h-1 was obtained in Kufranjeh. A remarkable
225
reduction in erosivity observed in Sahab and Bal`ama with only 22 MJ mm ha-1 h-1
226
year-1 (1.3 hundreds of foot tons inch acre-1 h-1), and these values were in accordance
227
with the mean annual precipitation. As the iso-erodents are based on the calculation of
228
only three R-values and estimated from the isohyetals, the rain erosivity map of
229
Jordan (Figure 9) is to be considered provisional. The accuracy and value of the
230
proposed map depends on including more EI30 values for more sites. It would be
231
interesting to compare these results with values obtained in neighboring countries; this
232
may carry out in the framework of the establishment of regional rain erosivity map.
233
Summary and Conclusions
234
The Universal Soil Loss Equation (USLE) was the result of enormous data collection
235
and analysis effort extending from the 1930s through the 1970s and culminating in
236
Agriculture Handbook 282 and finally in Agriculture Handbook 537. RUSLE was
237
developed as an update to the USLE, with development work beginning in the late
238
1980s. The need for a USLE update became apparent as users demanded more
239
flexibility in modeling erosion for new conditions, which clearly did not work well
240
within the standard USLE .
241
11
The preliminary rainfall erosivity factor (R) was calculated for Kufranjeh, As-Salt and
242
Gmaim by using rainfall data (amount and intensity) of 10 years out of an intensive
243
data of 15 years acquired from the Ministry of Water and Irrigation in Jordan. R factor
244
was calculated using both the USLE and its revised version. R-values calculations
245
were extended by using rainfall data for another 15 sites to establish relationship
246
between mean annual erosivity (R) and mean annual rainfall (P). These relationships
247
were used to produce a map of erosivity from mean annual data and Fournier index
248
for the whole area. Using the average value of erosivity factor of USLE and the
249
revised one, a provisional iso-erodent map was proposed.
250
The main conclusions of this study are:
251
1- The USLE model has a tendency to give higher erosivity values than RUSLE
252
model. However, land managers in Jordan can use R-values in both models because
253
they are generally accepted as compared to the R-values in literature.
254
255
2- As the iso-erodents were based on the calculation of only limited EI30 values and
256
approximated using the isoheytal map, the rain erosivity map, herewith presented, is
257
to be considered as provisional and further work is recommended.
258
3- Further work should concentrate on obtaining more data about rainfall and its
259
intensity over longer periods to provide a basis for detailed calculation of erosivity of
260
rainfall.
261
4- This study could be considered a first step on the way to evaluate methods for
262
rainfall diversity impacts on soil loss.
263
264
12
References
265
Arnoldus H.M.J., 1977. Methodology used to determine the maximum potential
266
average annual soil loss due to sheet and rill erosion in Morocco. In: Assessing Soil
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Degradation, FAO Soil Bulletin 34, pp 39-44, Rome
268
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Arnoldus H.M.J., 1980. An approximation to the rainfall factor in the universal soil
270
loss equation. In: Assessment of Erosion (De Boodt, Gabriels D, ed.), pp 127-132,
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Wiley, New York
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Battikhi A.M., Arabiat S., 1983. Constraints to the successful application of modern
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technology for soil conservation in Jordan. Part1: Environmental features and extent
275
of erosion. Dirasat, 10, 129-165.
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Brown L.C., Foster G.R., 1987. Storm erosivity using idealized intensity distributions.
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Transactions of ASAE, 30, 379-386
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Deumlich D., Funk R., Frielinghaus M.O., Schmidt W.A., Nitzsche O., 2006. Basics
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of effective erosion control in German agriculture. Journal of Plant Nutrition and Soil
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Eltaif N.I., Abbas M., 1987. Estimation of erosivity indices for universal soil-loss
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Fournier F., 1960. Climat et Erosion. Universitaries de France, Paris
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Hill R.L., Gross C.M., Angle J.S., 1991. Rainfall simulation for evaluating
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agrochemical surface loss. In: Groundwater Residue Sampling Design; (Nash R G;
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367 - 382. Amer. Chem. Soc.,Washington, DC
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Hillel D., 1998. Environmental Soil Physics. Academic Press, San Diego, USA
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Hussein M.H., 1998. Water erosion assessment and control in Northern Iraq. Soil and
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tillage Research. 45, 161-173
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Morgan R.P.C., 1996. Soil Erosion and Conservation. Longman Malaysia,
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reprint of second edition .
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Mutchler C.K., Carter C.E., 1983. Soil erodibility variation during the year.
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Mutchler C. K., 1970. Splash of a water drop at terminal velocity. Science, 169, 1311-
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1312
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Rapp J.F., Lopes V.L., Renard K.G., 2001. Comparing Soil Erosion Estimates from
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RUSLE and USLE on natural runoff plots. Soil Erosion Research for the 21st
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Century, Proc. International Symposium St. Joseph, MI. 24-27
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Renard K.G., Foster G.R., Weesies G.A., McCool D.K., Yoder D.C., 1993a.
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Predicting soil erosion by water: A guide to conservation planning with the revised
313
universal soil loss equation. United States Department of Agriculture (USDA).
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(Agricultural Handbook No. 703)
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Renard K.G., Freimund J.R., 1993. Using Monthly Precipitation Data to Estimate the
317
R factor in the Revised USLE. Journal of Hydrology, 157: 287-306.
318
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Stocking M.A., 1980. Working Session: Rain Erosivity. In: Assessment of Erosion
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(De Boodt M; Gabriels D, ed), pp 177-183, John Wiley & Sons, Chichester.
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Wischmeier W.H., Smith D.D., 1958. Rainfall energy and its relation to soil loss.
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American Geophysical union Transactions, 39, 285-291
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Wischmeier W.H., Smith D.D., 1965. Predicting rainfall erosion losses from cropland
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east of the Rocky Mountains - Guide for selection of practices for soil and water
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conservation. United States Department of Agriculture (USDA). Washington,
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DC.1965. (Agric. Handb. No. 282)
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Wischmeier W.H., Smith D.D., 1978. Predicting rainfall erosion losses: A guide to
331
conservation planning. U.S. Dep. Agric., Agric. Handb. No. 537. Washington, DC.
332
333
334
335
15
Table 1. Mean annual rainfall-runoff erosivity index for three rainfall stations in
Jordan calculated using USLE and RUSLE.
Years of
observation
1989-2003*
Kufranjeh
As-Salt
Gmaim
R1
R2
R1
R2
R1
R2
865
673
506
388
354
280
R1 and R2 are in MJ mm ha-1 h-1 year-1)
* The investigated period were10 out of 15 years record.
16
336
337
338
339
340
341
342
343
Table 2. Precipitation, Fourneir Index and average erosivity index for 18 sites in
north and Northwestern of Jordan.
Station
P (mm)
Fmod
R (using P)
R (using F mod)
344
345
346
Avg. R
(MJ mm ha-1 h-1 yr-1)
1
Bal'ama
219.5
68.6
32
19
26
2
Sahab
221.0
65.4
32
16
24
3
Nueiyme
269.3
80.2
58
34
46
4
Turra
291.4
86.3
73
44
59
5
W. el-Yabis
314.8
84.8
91
41
66
6
Huson
315.1
103.0
92
83
88
7
Qafqafa
334.6
100.1
110
75
93
8
K el-wahadneh
347.7
111.0
123
110
117
9
Huwwara
366.1
122.9
143
159
151
10
Jerash
391.0
116.2
173
129
151
11
Um Qais
391.6
139.1
174
249
212
12
W. Es-Sir
460.3
131.2
280
201
241
13
Gmaim
513.0
152.0
385
343
364
14
Dibbin
555.0
161.5
486
428
457
15
Ras Muneef
580.1
155.2
554
371
463
16
Salt
581.5
165.8
558
471
515
17
Ajlun Police St.
628.3
186.0
701
716
709
18
Kufranjeh
695.2
194.2
944
837
891
347
348
17
Table3. Precipitation, Fourneir Index and average annual revised rainfall runoff erosivity factor values for 18 sites in Jordan .
Station
P (mm)
Revised
R (using P)
Fmod
Revised R
(using F)
349
350
351
Revised
Avg. R
(MJ mm ha-1 h-1 yr-1)
1
Bal'ama
219.5
68.6
25
15
20
2
Sahab
221.0
65.4
25
13
19
3
Nueiyme
269.3
80.2
45
27
36
4
Turra
291.4
86.3
56
35
46
5
W. el-Yabis
314.8
84.8
71
33
52
6
Huson
315.1
103.0
71
67
69
7
Qafqafa
334.6
100.1
84
60
72
8
K el-wahadneh
347.7
111.0
94
87
91
9
Huwwara
366.1
122.9
110
125
118
10
Jerash
391.0
116.2
133
103
118
11
Um Qais
391.6
139.1
133
195
164
12
W. Es-Sir
460.3
131.2
213
158
186
13
Gmaim
513.0
152.0
291
269
280
14
Dibbin
555.0
161.5
366
334
350
15
Ras Muneef
580.1
155.2
416
290
353
16
Salt
581.5
165.8
419
367
393
17
Ajlun Police St.
628.3
186.0
525
554
540
18
Kufranjeh
695.2
194.2
704
647
676
352
353
354
355
18
356
357
358
Table 4. Average R-values for 18 sites in Jordan .
USLE
Avg. R
RUSLE
Avg. R
Average R
Station
(MJ mm ha-1 h-1 yr-1)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Bal'ama
Sahab
Nueiyme
Turra
W. el-Yabis
Huson
Qafqafa
K el-wahadneh
Huwwara
Jerash
Um Qais
W. Es-Sir
Gmaim
Dibbin
Ras Muneef
Salt
Ajlun Police St.
Kufranjeh
20
19
36
46
52
69
72
91
118
118
164
186
280
350
353
393
540
676
26
24
46
59
66
88
93
117
151
151
212
241
364
457
463
515
709
891
23
22
41
53
59
79
83
104
135
135
188
214
322
404
408
454
625
784
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
19
1000
900
R = 4 E-6 * P
2.946
R (SI units)
800
700
600
500
400
300
0
0
450
500
550
600
650
700
750
800
P (mm)
Figure 1. Erosivity factor (R) vs. precipitation (P) for the three sites in Jordan.
20
379
380
381
382
383
384
1000
900
R = 4E-6 * F3.6363
R (SI units)
800
700
600
500
400
300
0
0
150
160
170
180
190
200
Fmod (mm)
Figure 2. Erosivity factor (R) vs. Fournier Index (Fmod) for the three sites in Jordan.
385
386
387
The resulted equation from this relationship is:
388
389
21
390
800
R revised (SI units)
700
R = 4E-6 * P2.9012
600
500
400
300
0
0 450
500
550
600
650
700
750
P (mm)
Figure 3. Revised erosivity factor (R) vs. precipitation (P) for the three sites in
Jordan.
22
391
392
393
394
395
396
397
800
R revised (SI units)
700
R = 5E-6 * F3.5676
600
500
400
300
0
0
150
160
170
180
190
200
P (mm)
398
399
Figure 4. Revised erosivity factor (R) vs Fournier Index (Fmod) for the three sites in
400
Jordan.
401
402
403
23
404
R (cumulative %)
120
100
80
Gmaim
Salt
Kufranje
60
40
20
0
Nov
Dec
Jan
Feb
March
Month
Figure 5. Monthly distribution of annual R as a cumulative by month for three sites in
Jordan.
24
405
406
407
408
409
410
411
412
900
Deumlich
800
Mean R value from EI30
P (mm)
R (SI units)
700
600
500
400
300
200
100
0
Kufranjeh
Salt
S ite
Gmaim
Figure 6. R values calculated by Deumlich et al. equation compared with values
using EI30 in three sites of Jordan.
413
414
415
416
417
418
25
419
Arnoldus
Mean F value from EI30
Renard and Freimund
Fmod
R (SI units)
1000
250
200
800
150
600
100
Fmod (mm)
1200
400
50
200
0
0
Kufranjeh
Salt
Gmaim
S ite
Figure 7. R values calculated by Arnoldus and Renard equations compared with
values using EI30 in the three sites of Jordan.
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
26
446
1000
R average = 2.583E-6 * P2.985
R average (SI units)
800
600
400
200
0
0
200
400
600
800
P (mm)
Figure 8. Average annual erosivity factor (R) vs. precipitation (P) for 18 stations in
Jordan.
27
447
448
449
450
451
452
200
250
Lake
Tiberias
Um Qeis
Sama Ar-Rosan
Tu rra
Gma im
Hwwara
Idoun
Husn
110
45
200
Ketem
Nueiymi
Sekhra
Ras Muneif Kufur Khal
W. El-Yabis
Qafqafa
K. El-Wahadneh
Ajlun Police St.
Ain Janneh
Kuufrinja
Jerash
150
Bal’ama
45
385
Sa lt
211
110
385 DibbinNationalPark
211
110
W. Es-Sir
Sahab
Dea
d Se
a
N
S c a le
453
454
Figure 9. Iso-erodents obtained by superimposing values of erosivity (R) from
455
equation (10) and pre-prepared of isohyetal map for North and Northwestern Jordan .
456
457
458
459
460
461
462
28