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Indices for the estimation of interrill erodibility of Moroccan soils
CATENA
vol. 18, p. 537-550
Cremlingen 1991 ]
I N D I C E S F O R THE E S T I M A T I O N OF INTERRILL ERODIBILITY OF M O R O C C A N SOILS A. Merzouk, Rabat G.R. Blake, St Paul Summary
as observed in the field and reported by other authors in the region. A multiple Replicated runoff and soil loss measure- regression model using only three soil ments were made on nine Morrocan soils variables, i.e. % soil >2 mm + % sand, having 9 to 10% slopes using a rainfall electrical conductivity, and % silt and simulator. Soil physical, chemical and clay size so-called "active" CaCO3, premineralogical properties were measured dicted soil loss with an R 2 = 0.980. This at each site. regression model used as a relative erodiForty-two individual soil properties or bility index could represent a valuable combinations of properties were related tool for areas in Morocco where limited by regression analysis to soil loss. Vari- information is available on soil erosion. ation in erodibility of the major soils studied are explained by the resistance of aggregates to dispersion and interrill 1 Introduction transportation. The high relative erodibility of the calcareous soils was partly The prediction of soil loss or erosion on attributed to the occurrence of CaCO3 in the basis of soil and site properties has the silt size fraction. The smectitic nature been one of the goals of research on soil of the clay minerals in the vertisols and erosion in many parts of the world. Sevtheir low organic matter content are im- eral indices and predictive models have portant factors in their low infiltration been developed, but all limitations when capacity and higher soil loss rate. The their use is extended beyond the soil, clislaking process resulted in strong small mate, and crop conditions contained in aggregates that were vulnerable to trans- the data base of the model. port and removal from the soil surface. Since the well-known pioneering studAgreement was found between the rel- ies of Middleton in the 1930's, many reative erodibility obtained with the use searchers have attempted to define paof the rainfall simulator and the rela- rameters important in predicting soil erotive magnitude of the erosion problems sion susceptibility, denoted as "soil erodibility". Recently Bryan et al. (1989) ISSN 0341-8162 presented a much updated review of the (~)1991 by CATENA VERLAG, concept of this important soil property W-3302 Cremlingen-Destedt, Germany as well as the problems of its assessment 0341-8162/91/5011851/US$ 2.00 + 0.25 CATENA--An Interdiaciplinm-y Journal of SOIL S C I E N C E - - H Y D R O L O G y ~ G E O M O R P H O L O O Y
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Merzouk & Blake
and application. Structure parameters, such as aggregation, were prominent subjects for studies around mid-century. In many of these studies, there was a compounding of structure, texture, organic matter content and possibly other variables (Bryan 1968a). In recent years the correlation of numerous soil properties with soil loss under natural and simulated rainfall have allowed the selection of the most dominant soil loss determinant for a given study. Thus, Wischmeier et al. (1971) proposed a widely used nomograph for estimating the K factor in the well known USLE equation. It employed five parameters: two related to particle size distribution, and the other three to organic matter content, soil structure and permeability class. In 1977, RSmkens et al. (1977) developed a multiple linear regression using the parameters of Wischmeier et al. (1971) that explained 90% of the variation in the erodibility factor K (USLE) of scalped surface soils. They found that the Wischmeier et al. (1971) texture, combined with one or more binding agent factors, such as percent A1203 plus Fe203 or sodium periodate consumption in the reaction, gave a significant prediction of K. Trott & Singer (1983) in a study of California range and forest soils in which they included a mineralogical component, found the most powerful soil loss predictor was a combined smectite plus vermiculite clay term. Also included in their four-variable regression equation were bulk density pyrophosphate extractable (Fe + A1), and the texture term of Wischmeier et al. (1971). Several studies on soils similar to those of Morocco emphasize the importance of calcium salts to erodibility. Massoud (1977) and Kadry (1977) have considered (ATENA
the unique texture and structure problems of calcareous soils. Silleos (1981} found that the nomograph of Wischmeier et al. (1971) underestimated the erodibility of soils in northern Greece. He attributed this to removal of CaCO3, before determining texture thus giving a false picture of the effective texture, and to the easy disintegration of calcareous soil aggregates, especially those high in the silt and clay size CaCO3 so-called "active" form of CaCO3, that leads to sealing of pores, crust formation, and decreased infiltration capacity. Consequently, he believed that the addition of organic matter to highly calcareous soils was especially important in the formation of stabilizing complexes between soil colloids and CaCO3. Imeson & Verstraten (1985) and Gaiffe (1990) have also recently confirmed these observations of easy slaking and of "effective" texture in calcareous Spanish and French soils. Dumas (1965) provided an erodibility index for Tunisian soils based on the percent of soil material >2 mm that he called percent stoniness. He obtained the following equation: log 100K = 2.586 - 0.0294 × % stoniness (r2 = 0.70), where K is a soil erodibility factor. Still little information is available on the erodibility of Mediterranean soils and particularly Moroccan soils, and solutions to curb soil erosion are still incomplete. For these reasons, more research is needed in almost all aspects of erosion to meet the increasing demands of conservation for better land management. The objectives of the present study were: 1. to relate soil erodibility to major
An Interdisciplinary Journal of SOIL SCIENCE
HYDROLOGY
GEOMORPHOLOGY
Estimation o f Interdll Erodibility, Morocco
539
Soil identification
Soil Classification U.S. Soil Taxonomy"
Parent material
References"
Aine A Biad Calci Hamri P. Vert Sable Tleta Trias Vert
Oehraqualf Calcixeroll Petro Calcic Palexeroll limestone Calcixeroll Palexeroll Quartzipsamrnent Xerofluvent Xerorthent Chromoxerert
Shale Marl Cretaceous Quaternary Quaternary Sandstone Marly Trias Quaternary
Ghanem (1978) Badraoui (1985) Badraoui(1985) Djibet(1984) Badraoui(1981) Ghanem (1978) FAO (1977) Djibet (1984) Badraoui(1981)
" Soil Survey Staff (1975) '" For additional information on these soils Tab. 1 : Description of the nine selected Moroccan soils.
physical, chemical and mineralogical properties of some surface soils in Morocco, and 2. to develop a predictive erodibility index that uses simple laboratorydetermined properties applicable to these soils.
2
Materials and methods
Using a rainfall simulator, soil losses were measured on 1 m 2 field plots on nine Moroccan soils located to the west of the Rif and Atlas mountains. Six replicates were measaured at seven locations, and four replicates were made at two of the field sites. Slopes of 9 to 10% were selected for the experimental sites described in tab. 1. All test sites were located on fields which had been cultivated to wheat for the last three or more years. The plots were prepared by removing any crop cover; roots protruding from the soil were clipped at the surface, leaving a soil surface condition similar to that of the fall season. The first storms of this season are very damaging as far as erosion is concerned. CATENA--An Interdisciplinary Journal of SOIL SCIENCE
The rainfall simulator was similar in principle to that described by Dixon & Peterson (1964). Soil at each plot was first wetted with a storm event of 100 m m h -~ intensity for 30 min. Runoff and soil loss measurements were made the following day under storm-like duration and intensity. The 10 crn hr-1 intensity is higher than that normally recorded in Morocco, but available data show several occurances of similar or higher intensities (Badou 1976). The simulator and plot area were covered with a tent to prevent disturbance by wind. Antecedent soil water content was measured in the surface 8 cm of soil immediately adjacent to the plot prior to the runoff measurements. Eight basic physical, eight chemical and three mineralogical soil parameters were measured on surface soil samples from each site. Physical soil measurements included bulk density using a core method; porosity was calculated from particle and bulk densities. Consistency limits were determined with an A S T M procedure, soil as well as a sediment particle size distribution by a pipette method. Satu-
HYDROLOGY~OEOMORPHOLOGY
Merzouk & Blake
540
I
Soil Aggregates (2 - 8 mm) 200 g -Air Dried1
-50g-
- 150 g -
['-
Sieve Analysis = Size Distribution of Aggregates before rainfall apilieation
Dry
-I
20
cm Diameter Sieve (US No: 70)
Controlswitch
On asemi-loggraph paperplotboth disn-ibut'ion curvesto evaluate aggregatc's stability Dry Sieve Analysis = Size distribution of Aggregates after rainfall application
i
(UnderFume Hood) [ Infra Red
,,',',, ' ,,",
I I I If II I I I I I I
_
~
:,',',, Methanol ,,,','~J,-r~pray
I ~N'~ ilk.t:..,. I :,:'::?.:.~J
°
.
Appl. Time = 10 rain 1 Rain. Int. = 50 mm• hr
",'
Screen Time = I0 - 15 rain
Fig. 1: Procedure for the proposed method of aggregate stability testing under simulated rainfall.
CATENA An Interdisciplinary Journal of SOIL SCIENCE
HYDROLOGY GEOMORPHOLOGY
Estimation o f Internll Erodibility, Morocco
541
100
S¢
m
¢= 6{
B
~J n
&O--
2Cm
¢XX
O.Ot
O~
!.0
10
Mid-point Diameter (mm)
Fig. 2: Dry aggregates distribution curves, before and after rainfall application.
Soil name
Aine A Biad Calci Hamri P. Vert Sable Tleta Trias Vert
Soil loss" Mean 10-2 Mg'ha - l
Sd
82 614 170 294 380 70 190 299 504
22 254 55 72 142 14 73 84 151
Water loss" Mean Sd mm 28.6 32.1 32.2 28.0 29.5 5.2 34.6 42.9 31.8
3.7 7.3 4.7 3.9 1.0 0.5 12.5 4.5 5.5
Infiltration** Mean Sd mm h-t 31.0 23.0 22.9 31.0 28.3 82.2 18.8 9.5 21.5
6.3 16.2 7.4 5.9 4.7 4.8 12.4 3.2 9.6
" Applied = 50 mm of rainfall "" Equilibrium Infiltration rate
Tab. 2: Measured runoff, soil loss, and infiltration rate of nine soils. rated hydraulic conductivity was measured in the field adjacent to the plot by use of a double cylinder, constant head method, and soil water retention at 33 and 1500 KPa was determined using gravimetric and pressure apparatus, respectively. Other parameters, such as available water content or sand content for example, were derived from these
measurements. The above physical soil measurements were made using standard methods as outlined in methods of soil analysis (Part 1) by Klute (1986). Three variations of aggregate stability measurements were made, namely dry sieving by a method described by Kemper & Chepil (1965), wet sieving as outlined by Kemper (1965), and a laboratory test based
CATENA--An Interdis~plinary Journal of SOIL SCIENCE--HYDROLOGY~EOMORPHOLOGY
542
Merzouk & Blake
on breakdown of aggregates under simulated rainfall developed for this study. This method was designed to simulate breakdown of a mass sample of aggregates when subject to rainfall. Impact of water drops was considered by EIlison (1944) to be one of the principal agents for the detachment and subsequent transport of soil particles. Bryan (1968b) has pointed out that aggregates that are stable in gently agitated water may prove to be much less stable when subject to the impact of high velocity raindrops. For this reason, the proposed method was used to simulate, better than wet sieving, the aggregate breakdown due to raindrops as it occurs in the field. Fig. 1 represents the procedure for the aggregate stability testing under simulated rainfall. Air-dried bulk surface soil was carefully broken to pass an 8 mm sieve. A sample remaining on 2 mm sieve was retained for the aggregate stability measurements. A subsample (150 g) was used to determine aggregate size distribution by dry sieving using the method of Kemper & Chepil (1965). A second 50 g sample was placed in a 20 cm diameter sieve with 0.2 mm openings. The sample size corresponded to the correct amount of aggregates that uniformly covered the sieve screen without having aggregates unexposed to falling raindrops. The sieve with the aggregates was placed beneath a small rainfall simulator and showered with simulated rain of 5 cm hr -I intensity for 10 min. The rainfall simulator used in this experiment is similar to the one described by Beggs (1982). The sieve was located 1.6 m below the oscillating nozzel. After being exposed to the simulated rainfall, the sieve was placed under a fume hood, the aggregates sprayed with ('AI'ENA
100 ml of methanol, and dried using infra-red lamps. Aggregate size distribution was then after determined by dry sieving. Dry sieving was used because of the weakness of the traditional wet sieving; that is wet sieving aggregates are plastic and less coherent, consequently their morphology is altered during sieving (Brandeau 1982). The objectif was then to use dry-sieving which is less erosive after drying the aggregates and permits them to retain their original character. For this puspose, a drying method was used similar to that used by Green-Kelly (1973) to prepare clay soils for determination of structure. The method consist of drying the aggregates under infra-red lamps in a dry atmosphere (under fume hood) and spraying them with methanol. The aggregates are hardened and the degree of hardening is increased by subsequent exchange with the methanol which is a water-miscible organic solvant and has a lower surface tension and lower viscosity. The gentle hardening of the aggregates limits excessive shrinkage and lessens the risks of structural rearrangement. This method which tends to preserve the aggregates, made the wet sieving unnecessary. The aggregate size distribution before and after rainfall application were used to evaluate the aggregate susceptibility to breakdown by drop impact into small sizes which are easily transported by splash and runoff water. Aggregate mean weight diameters (MWD) were computed from the size distribution curves. Fig. 2 shows the representation of the results. A large area between the curves means that the aggregates did not resist the raindrop impact. Several chemical properties of the soils were determined. Soil pH was measured in both a 1:2.5 soil to water ra-
An Interdisciplinary Journal of'SOIL, SCIENCE
HYDROLOGY
GEOMORPHOLOGY
Estimation o f Internll Erodibility, Morocco
Characteristics Coarse fragments, >2 ram, % Coarse sand, 2-0.1 mm, % Fine sand, 0-1-1.5 mm, % Coarse silt, 0.05-0.02 mm, % Fine silt, 0.02-0.002 mm, % Clay, <0.002 ram, % Bulk density, Mg/m 3 Ksat, mm/fi Permeability class Liquid limit, % Plasticity index Water content, 33 KPa, % Water content, 1500 KPa, % 33 - 1500 KPa, % Antecedent water content, % g/g Computed nomograph K (USLE)
543
/Line A
Biad
Calci
Hamri
P.Vert
Sable
Tleta
Trias
Vert
33.5 24.4 21.3 18.4 19.1 16.9 1.32 29 mod 28.5 1.6 16.8 8.4 8.5 19.7 0.375
1.8 2.8 7.7 15.4 33.3 40.8 1.17 35 mod 39.3 10.8 28.5 13.1 15.2 37.7 0.283
23.4 30.0 9.3 19.6 15.0 26.1 1.12 186 rapid 41.9 8.9 31.0 16.0 15.0 35.9 0.224
7.5 6.1 23.1 13.5 19.9 37.8 1.40 58 rood 26.4 9.0 25.7 11.3 14.4 28.6 0.303
2.5 1.0 6.6 10.6 23.1 58.7 1.37 39 slow 60.6 18.0 39.6 24.7 14.5 50.3 0.217
0 56.2 35.7 5.8 0.8 2.3 1.36 227 rapid 16.4 1.0 10.6 4.0 6.6 11.6 0.255
18.8 13.2 5.1 6.8 33.8 41.4 1.56 2.2 slow 42.2 9.1 28.8 20.3 8.5 23.6 0.236
7.1 8.7 18.7 31.8 22.4 18.9 1.38 34 rood 25.7 10.7 19.7 9.9 9.8 21.1 0.566
0.5 0.8 7.0 7.3 12.7 67.2 1.58 3 slow 65.1 12.0 42.1 26.0 16.1 46.9 0.178
Tab. 3: Some physical characteristics of soils at test sites. tio and soil to 1N KC1 solution. Total organic matter, total nitrogen, and available phosphorus contents were determined by chromic acid titration, a micro-Kjehldahl method, and soil extraction with a 0.5 molar NaHCO3, respectively. Exchangeable bases were determined in soil extracts by an atomic absorption spectro-photometer and exchangeable Ca ++ and Mg ++ amounts were estimated by an EDTA extraction method. Total CaCO3 and "active" CaCO3 were determined by the methods of Allison & Moodie (1965) and Douchaffour & Souchier (1979) respectively. Electrical conductivity was determined on a 1:5 soil-water ratio (Bower & Wilcox 1965). Clay fractions from which CaCO3, and organic matter were removed were Xrayed after saturation with Mg for a semi-quantitative estimation of different phases. Total iron and total free iron were determined by colorimetric methods. Statistical analysis of relations beCATENA
tween soil loss parameters as dependent variables and soil properties as independent variables were performed by use of a computerized statistical package of Bachacou et al. (1981).
3
Results and discussion
Results from simulated rainfall studies in the field are shown in tab. 2. Runoff and soil loss were measured directly and infiltration rate at the end of a 30-min run was determined by plotting. Standard deviations show that soil loss varied to a greater extent between replicates than did runoff. Mean soil loss was ranked by soil type. The time from initiation of simulated rainfall until beginning of runoff varied from around 20 seconds for the Vert soil to 15 minutes for the Sable. Measured physical characteristics of soils are given in tab. 3. The wide range of properties between soils is abundantly evident. Coarse fragments in the Aine
An Interdisciplinary Journal of SOIL SCIENCE - - H Y D R O L O G Y ~ G E O M O R P H O L O G Y
Merzouk & Blake
544
Characteristics
Aine A
pH, water pH, Kcl EC, S.m ] Exchangeable CEC, cm°lKg-I Na + K+ Ca ++ Mg++ Base saturation, % Organic matter, % Total N, % Available P, mg.kg -1 CaCO3, total, % CaCO3, "active" Fe(Fe203), total, % Fe(Fe203), free, %
6.2 5.5 0.0207 12.6 0.24 1.91 6.4 2.6 88.5 2.66 0.16 14.2 0.0 0.0 4.21 2.59
Biad 8.4 7.3 0.0308 31.0 0.75 2.55 28.4 4.2 115.8 2.05 0.16 34.6 61.2 26.6 2.16 0.75
Calci
Hamri
P.Vert
Sable
Tleta
Trias
8.4 8.5 8.4 7.2 6.2 7.8 7.4 7.8 6.1 5.1 0 . 0 2 7 6 0 . 0 1 7 0 0.0276 10.023 0 . 0 9 5 27.4 25.0 69.6 5.3 16.1 1.2 3.42 23.2 4.0 l 16.0 3.32 0.28 120.3 19.0 4.0 2.73 1.05
0.43 2.62 16.3 2.4 87.0 1.64 0.16 22.8 5.8 2.7 3.4 1.36
0.64 0.74 61.6 3.9 96.0 1.72 0.16 22.8 0.7 1.4 5.21 2.04
0.19 0.12 3.9 0.5 87.7 0.55 0.08 9.0 0.0 0.0 1.47 0.75
0.37 1.76 8.9 4.2 94.4 0.99 0.12 5.5 0.0 0.0 7.28 3.08
Vc~-t
8.7 8.5 i: 7.6 7.2 I 0 . 0 1 6 4 (7.278 ~i 8.2 68.9 il 0.33 1.47 i 2.64 (/.72 ii 5.2 54.6 i 0.3 8.4 103.6 94.4 ! 0.63 1.05 0.08 0.08 ,i 23.3 10.7 il 9.74 0.84 ![ 3.1 3.42 [ 2.70 5.35 i 1.29 t.96 !
Tab. 4: Some chemical characteristics o f soils at test sites.
A were largely r o u n d e d iron concretions, those for T l e t a were p l a t y fragments, a n d those f r o m Calci were c a l c a r e o u s caliche fragments. A n t e c e d e n t w a t e r contents, m a d e at the b e g i n n i n g o f the soil loss a n d r u n o f f m e a s u r e m e n t s , were all greater t h a n the 33 K P a value except for the T l e t a soils. C h e m i c a l characteristics o f the soils are given in tab. 4 a n d the m i n e r a l o g i c a l in tab. 5. Tab. 6 shows the aggregates m e a n weight d i a m e t e r s for the soils a n d the sediments. F r o m simple c o r r e l a t i o n s a n d regression analysis between 42 soil p r o p e r ties m e a s u r e d directly (or d e d u c e d from m e a s u r e d properties), including c o m b i n a t i o n s o f the properties, a n d soil loss as the d e p e n d e n t variable, we were able to d e v e l o p predictive e q u a t i o n s t h a t show which soil m e a s u r e m e n t s best predict soil losses for the soils in this study. I n c l u d e d a m o n g the 42 variables were eight variations o r c o m b i n a t i o n s o f soil ag,,m'egate measurements. Tab. 7 shows the vail-
ous steps in the stepwise procedure, the first step being the basic e q u a t i o n with a single (combined) variable. The U S L E K value e s t i m a t e d from Wischmeier's n o m o g r a p h using soil p r o p e r t i e s was also included a m o n g the 42 variables t h o u g h its limited validity c a l c u l a t e d from o u r d a t a is recognized by the authors. The K value o f the U S L E estimates b o t h sheet a n d rill erosion a n d t r a n s p o r t by runoff. O n a 1 m a plot m e a sured sediment is p r i m a r i l y the result o f d e t a c h m e n t by r a i n d r o p impact. T h o u g h the t r a n s p o r t - l i m i t i n g c o n d i t i o n prevents a truly representative K ( U S L E ) value, we nevertheless believed that a p s e u d o K value which represents here m o s t l y the interrill-erodibility w o u l d p r o v i d e a valuable c o m p a r i s o n . The r a n k i n g o f erodibility as e v a l u a t e d by the n o m o g r a p h did n o t agree with that o b t a i n e d with the rainfall simulator. T h e relative soil erodibility a m o n g the nine soils was large, the greatest being as m u c h as 11 times as e r o d i b l e as the least,
CATENA A n Interdisciplinary Journal of SOIL SCIENCE
HYDROLOGY
GEOMORPHOLOGY
Estimation o f Intern11 Erodibility, Morocco
Clay minerals Smectite Vermiculite Illite Chlorite Kaolinite Interstratified Polygorskite Feldspar Quartz
Aine A
Biad
Calci
33
- -
. 66 18 2 7"*
.
.
38
.
. 7
- -
-12 10 Tr* 13 .
13
Soils P.Vert
Sable
60
27 17 20 -16 .
23
-19 15 Tr ° . .
19
Tleta
- -
.
-29 6 Tr ° 17
- -
Hamri
545
.
- -
9 7 -30 Tr** .
- -
-29 21 10 Tr*
-38 16 11 --
17
15"" 11
.
9
. 6
Trias
53
Vert 60 --20 11 Tr* - -
-9
Chlorite-Smectite ** Illite-Vermiculite *** Feldspar *
5 : Semi-quantitative estimation of percentage clay mineralogical composition of the a horizon of the soils by X-ray diffraction analysis..
Tab.
Soils
%WSA (mm)
MWDB (mm)
MWDA (mm)
MWD (Sediments)
Vert (mean)* (s.d.)
71.3 1.1
3.90 0.26
0.62 1.32
0.29
P. Vert
73.4 2.5
4.68 0.26
1.32 0.27
0.27
Calci
59.4 5.3
3.85 0.13
0.99 0.07
0.59
Biad
66.2 2.4
3.78 0.21
1.09 0.06
0.34
Trias
46.4 4.2
4.11 0.23
0.51 0.04
0.54
Aine A.
35.3 2.8
4.00 .023
1.90 0.25
0.77
Hamri
38.5 5.5
4.19 0.15
0.82 0.15
0.47
Tleta
46.6 3.0
3.97 0.39
1.16 0.17
0.84
Sable
19.3 1.4
4.78 0.19
1.71 0.25
T °*
* Mean from 6 replicates ** No stable aggregates collected T a b . 6 : Results of aggregates stability testing for (1) wet sieving method (% WSA ), for (2) the simulated rainfall methods (MWDB and MWDA) and the sediments aggregates MWD. M W D B = Dry Aggregates mean weight diameter (mm) before rainfall impact. M W D A = Dry Aggregates mean weight diameter (mm) after rainfall impact.
CATENA--An Interdisciplinary Journal of SOIL S C I E N C E - - H Y D R O L O G Y ~ E O M O R P H O L O G Y
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The susceptibility of the soils to erosion was in the following order: Biad (calcixeroll) > Vert (vertisol) > P. Vert (vertic palexerol) > Trias (xerortent) > Hamri (vertic xerortent) > Tleta (vertic xerofluvent) = Calci (petro calci palexerol) > Aine A. (ochraqual) = Sable (quartzi psament). Agreement was found between the relative erodibility obtained with the use of the rainfall simulator and the relative magnitude of the erosion problems as observed in the field and reported by Badraoui (1981) and Kalman (1970). The smectitic nature of the clay (highly charged biedelite) minerals in the vertisols and their low organic matter content are important factors in their low infiltration capacity and high soil loss rate. It was observed that the slaking produced small aggregates that were easily removed from the plot by runoff. The mean weight diameter of the particles in the sediments washed off from the vertisols was greater than 0.29 mm, while over 70% of the primary particles had a diameter less than 0.002 mm (clay). This confirms what was found recently by Gaiffe (1990). The high structural stability allows the removal and transport of entire aggregates. Soil loss decreased with soil material >2 mm (SM>2 mm) on the surface (r=0.6t) not only because it ordinarily has a high infiltration rate, but also because of raindrop interception by surface exposed fragments acting like a mulch. Another relevant correlation was found between soil loss and the active CaCO3 (r=0.74). The calcareous soil (Biad) was the most erodible one. Greater erodibility on soils high in silt and clay size CaCO3 than on noncalcareous soils has been reported for various mediterranean I AI ENA
regions (Silleos 1981, and Gaiffe 1990). This high relative erodibility is mostly attributed to (l) the distribution of CaCO3 in the silt fraction, and (2) the instability of large aggregates in the presence of active CaCO3 content which causes the sealing of soil pores and crusting. The %WSA from wet sieving was positively correlated to soil loss (r=0.77), meaning that the higher the aggregate stability the higher the soil loss. This is not logical, contradicting all expectations. Many authors found this illogical result (Bolline 1978, Obi et al. 1989 and Gaiffe 1990). It seems that for some regions the %WSA index, as measured, is not a suitable predictor of soil erodibility. This positive correlation is accepted, like in our case, if we see that the erosion acts on the entire stable aggregates. The proposed method for testing aggregate stability bases on simulated rainfall showed a better correlation with soil erodibility than the wet sieving method (%WSA). With this method, the more unstable the aggregates the more soil erosion was observed. Though the correlation was relatively low in absolute value (r=0.5), in contrast to the %WSA the correlation sign was logical. The most powerful predictor in this model was the textural term ( % S M > 2 mm + % sand) with r2=0.81. It took three additional variables to achieve a correlation coefficient of 0.997 and the inclusion of two more variables to attain an r2--0.999. Using the stepwise multiple regression analysis many soil characteristics variables were eliminated because of their non-orthogonality or because of intercorrelations. The result was that only a structural term (aggregate stability) was retained. That a mineralogical term was selected by the computer in the regres-
A n Interdisciplimary Journal o [ ' S O | L S C I E N C E
HYDROI.OGY
(~Er.)MORPHOLOGY
Estimation o f Interrill Erodibility, Morocco
Step No. 1.
variable entered
r 2 of accumulated variables
Sm + Sa= % (soil material >2 mm) + % sand variables Regression coefficient
0.810
Sm + Sa Constant 2.
A C C = Active CaCO3 variables Sm + Sa ACC Constant
3.
547
-5.5341 517.2921 0.947 Regression coefficient -4.3744 9.0948 430.1961
E.C. = Electrical conductivity variables Regression coefficient Sm + Sa ACC E.C. Constant %WSA x MWD-B variables Sm + Sa ACC E.C. %WSA x MWD-B Constant % Smectite variables Sm + Sa ACC E.C. % W S A times M W D - B % smectite Constant
-4.4796 6.4491 613.3981 311.8291 0.997 Regression coefficient -6.4603 1.1206 1006.2560 -0.8264 498.5480 0.998 Regression coefficient -6.9452 3.2589 1466.2911 -0.5596 -1.7103 406.2594
K sat = saturated hydraulic conductivity variables Regression coefficient Sm + Sa ACC E.C. %WSA x MWD-B %smectite K sat Constant
0.980
0.999
-6.99993 1.1270 1355,8549 -0.5572 - 1.7215 0.2516 408.8670
Summary of the relative erodibility-predicting equations obtained using multiple regression analysis stepwise procedure ( Bachacou et al. 1981). T a b . 7:
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sion is interesting given the importance that researchers have recently placed on its role in soil aggregation. Kalman (1970) in Morocco and Yrott & Singer (1983) in California have reported that percent smectite clay minerals, because of their slaking tendencies correlated well with erosion. The second-most powerful predictor was the percent "active" calcium carbonate, (ACC). The erosion-controlling effect of this soil constituent has been recently reported by Silleos (1981) and other workers studying soil erodibility in the Mediterranean region. The strong correlation that was found in tab. 7 between soil loss and percent "active" CaCO3, smectite and soil material >2 m m points to the importance of parent material in the erodibility of Moroccan soils. The six soil variables selected through the last model in tab. 7, have been used individually or in combination by different researchers to explain and index the erodibility of Mediterranean and African soils. Though our model does not agree in particulars with the model of Wischmeier et al. (1971), both models show a dependance of soil susceptibility to water erosion on textural and structural properties. One of the objectives of the present study was to provide a simple relative erodibility index using soil parameters that can be obtained from routine laboratory determination with limited laboratory facilities. At the same time the variables should also be free of any intercorrelation. Based on the above criteria, it is suggested that only three of six soil parameters provided by the stepwise procedure (tab. 7) need be used. This would include a textural term ( % S M > 2 m m + % sand) with r2=0.81, the percent
"active" CaCO3 (ACC), r~-=0.5, and the electrical conductivity (EC), rZ=0.25. The multiple regression model obtained using three soil variables is then used as a relative erodibility index KR: Kr = 311.63 - 4.48 • ( % S M > 2 m m + % Sand) + 613.40 • EC + 6.45 < cdot % "active" CaCO3 For the soil conditions of this study this three parameter soil erodibility index satisfies the three major conditions stated above for its adoption and future use. Despite the high coefficient of determination (r2=0.98) that resulted for this index, it is important to bear in mind the limitation of the small plot used to obtain the data. It is not suggested that the model or index presented here be used to determine the Wischmeier K factor. What is suggested is that the present index can be used for the relative ranking of interrill erodibility of soils for the area studied. Acknowledgements
This research is a Contribution from the Institut Agronomique et V&6rinaire Hassan II (IAV Hassan II), Rabat. Support by U S A I D under contract NE/C1279, P R A G 608-0160, M O R O C C O is gratefully acknowledged. References ALLISON, L.E. & MOODIE, C.D. (1965): Carbonate. In C.A. Black (ed.), Methods of Soil
Analysis, Part 2. Agronomy 9, 1379-1400. Am. Soc. Agron., Madison, Wl. BACHACOU, J., MASSON, J.P. & MILLIER, C. (1981): Manuel de la programmatique statis-
tique. Amance 81, Dept. de Biomerie, I.N.R.A., C.N.R.I. 54280, Champenoux, Belgium. BADOU, M.C. (1976): Relation intensit6 frequence duroc dans les precipitations pluviales du Nord-ouest du Maroc. Hommes Terre et Eau. vol. 5. No. 20, Maroc.
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Estimation o f Intertill Erodibility, Morocco
BADRAOUI, M. (1981): Cartographic et caracterisation des sois de la region: Ettnine Khemis (Zone Nord), Province de Settat. Memoire de 36me cycle. D.S.S., I.A.V. Hassan II, Rabat, Morocco. BADRAOUI, M. & BLOOM, P.R. (1985): Mineralogy of Vertic soils of High Chaouia, Morocco. Agron. Abstr. p. 229. BEGGS, R.A. (1982): A portable field sprinkler infiltrometer. Master of Science thesis in Engineering, Utah State University. Logan, Utah. BOLLINE, A. (1978): Study of the importance of splash on the cultivated loamy soils of Hesbaye, Belgium. Earth Surface Processes, a journal of geomorphology 3, 71-84. BOWER, M. & WILCOX, L.V. (1965): Soluble salts. In: Methods of Soil Analysis. Agronomy No. 9, part 1. Amer. Soc. of Agronomy, Madison, WI. BRANDEAU, E. (1982): Fractionnement physique du sol. Methode de separation du comportement d'aggregats de 0.050 fi 2 ram. Cah. ORSTOM serie P6dologie. vol. XIX, No. 4, Paris.
549
FAO/PNUD (1977): Projet MOR 71/536, Sch6ma d'am6nagement du bassin versant du Tleta. Rabat, Morocco. GAIFFE, M. (1990): Erosion of calcimagnesic soils as aggregates in jurassian pedological systems. CATENA 17, 141-149. GHANEM, H. (1978): Contribution ~ la connaissance des sols du Maroc; gen6se, classification et r6partition des sols des r6gions des Zaers, de la basse Chaouia et des Sehouls. Th6se Doctorat d'Etat. Universit6 de Gand. Inst. Geologic. Belgium. GREEN-KELLY, R. (1973): The preparation of clay soils for determination of structure. Journal of Soil Science. vol. 24 No. 3, 276-283. IMESON, A.C. & VERSTRATEN, J.M. (1985): The erodibility of highly calcareous soil material from southern Spain. CATENA 12, 291-306. KADRY, L.T. (1977): Distribution of calcareous soils in the Near East region, their reclamation and land use measures and achievements. In: Calcareous soils. EA.O. Soils Bulletin 21. Rome.
BRYAN, R.B. (1968a): The development, use and efficiency of indices of soil erodibility. Geoderma 2, 5-26.
KALMAN, R. (1970): Ruissellement et 6rosion en nappe (experimentation and simulation de pluie). Annales de la recherche Forestri6re au Maroc. Tome 12. Rabat. pp. 177.
BRYAN, R.B. (1968b): Development of laboratory instrumentation for the study of soil erodibility. Earth So. Journal 2, 38-50.
KEMPER, W.D. (1965): Aggregate stability. In: A. Klute (ed.), Methods of Soil Analysis. Agron. 9, 511-519. Amer. Soc. Agron., Madison, WI.
BRYAN, R.B., GOVERS, G. & POESEN, J. (1989): The concept of soil erodibility and some problems of assessment and application. CATENA 16, 393-412.
KEMPER, W.D. & CHEPIL, W.S. (1965): Size distribution of aggregates. In: C.A. Black (ed.), Methods of Soil Analysis. Agron. 9, 499-511. Amer. Soc. Agron., Madison, WI.
DIXON, R.M. & PETERSON, A.E. (1964): Construction and operation of a modified spray infiltrometer and a flood infiltrometer. Univ. of WI., Agr. Exp. Sta. Res. Rep. 15.
KLUTE, A. (ed.) (1986): Methods of Soil Analysis. Number 9 (Parts I) in the series Agronomy. Amer. Soc. for Agronomy and Amer. Soc. of Soil Sc., Madison, Wis., USA.
DJIBERT, B. (1984): Cartographie au 1/100.000 et caract~risation des sols dans les communes rurales de Bouguergouh et Aine Dorbane. M6moire de 36me cycle DSS. IAV Hassen II. Rabat, Morocco.
LAWS, J.A. & PARSONS, D.A. (1943): The relation of raindrop size to intensity. Trans. Amer. Geophys. Union 24, 452-460.
DOUCHAUFFOUR, P. & SOUCHIER, P. (1979): Pedologie, Tome 1 and Tome 2. Ed. Massan. Paris. DUMAS, J. (1965): Relation entre l'6rodibilit~ des sols et leurs caract6ristiques analytiques. Cahiers de I'O.R.S.T.O.M. S6rie P6dol. Vol. III, Fasc. 4. ELLISON, W.D. (1944): Studies of raindrop erosion. Agricultural Engineering 25, 53-55.
MASSOUD, F.I. (1973): Some physical properties of highly calcareous soil and the related management practices. In: Calcareous Soils. F.A.O. Soils Bull. 21. Rome. MIDDLETON, HE. (1930): Properties of soil which influence soil erosion. USDA Tecb. Bull. 178.
OBI, M., SALAKO, F.K. & LAL, R. (1989): Relative susceptibility of some southeastern Nigeria soils to erosion. CATENA 16, 215-225.
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ROMKENS, M.J., ROTH, C.B. & NELSON, D.W. (1977): Erodibility of selected clay subsoils in relation to physical and chemical properties. Soil Sci. Soc. Am. Jour. 41. 954-960. SILLEOS, M.G. (1981): The effect of calcium carbonate on soil erodibility in survey area in northern Grece. ITC Journal 1981-4. 418433. SOIL SURVEY STAFF (1975): Soil Taxonomy. U.S. Dept. Agr., S.C.S. Agron. Handbook 436. Washington, D.C. TROTT, K.E. & SINGER, M.J. (1983): Relative erodibility of 20 California range and forest soils. Soil Sci. Soc. Amer. J. 47, 753-759. WlSCHMEIER, W.H., JOHNSON, C.B. & CROSS, B.V. (1971): A soil erodibility nomograph for farmland and constructions sites. Jour. Soil and Water Conserv. 26, 189-193.
Addresaes of authors: A. Merzouk Department of Soil Science Institut agronomique et veterinaire Hassan II BP: 6202 Rabat-Instituts Morocco G.R. Blake Department of Soil Science University of Minnesota St. Paul, MN 55108 U.S.A.
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Cremlingen 1991 ]
I N D I C E S F O R THE E S T I M A T I O N OF INTERRILL ERODIBILITY OF M O R O C C A N SOILS A. Merzouk, Rabat G.R. Blake, St Paul Summary
as observed in the field and reported by other authors in the region. A multiple Replicated runoff and soil loss measure- regression model using only three soil ments were made on nine Morrocan soils variables, i.e. % soil >2 mm + % sand, having 9 to 10% slopes using a rainfall electrical conductivity, and % silt and simulator. Soil physical, chemical and clay size so-called "active" CaCO3, premineralogical properties were measured dicted soil loss with an R 2 = 0.980. This at each site. regression model used as a relative erodiForty-two individual soil properties or bility index could represent a valuable combinations of properties were related tool for areas in Morocco where limited by regression analysis to soil loss. Vari- information is available on soil erosion. ation in erodibility of the major soils studied are explained by the resistance of aggregates to dispersion and interrill 1 Introduction transportation. The high relative erodibility of the calcareous soils was partly The prediction of soil loss or erosion on attributed to the occurrence of CaCO3 in the basis of soil and site properties has the silt size fraction. The smectitic nature been one of the goals of research on soil of the clay minerals in the vertisols and erosion in many parts of the world. Sevtheir low organic matter content are im- eral indices and predictive models have portant factors in their low infiltration been developed, but all limitations when capacity and higher soil loss rate. The their use is extended beyond the soil, clislaking process resulted in strong small mate, and crop conditions contained in aggregates that were vulnerable to trans- the data base of the model. port and removal from the soil surface. Since the well-known pioneering studAgreement was found between the rel- ies of Middleton in the 1930's, many reative erodibility obtained with the use searchers have attempted to define paof the rainfall simulator and the rela- rameters important in predicting soil erotive magnitude of the erosion problems sion susceptibility, denoted as "soil erodibility". Recently Bryan et al. (1989) ISSN 0341-8162 presented a much updated review of the (~)1991 by CATENA VERLAG, concept of this important soil property W-3302 Cremlingen-Destedt, Germany as well as the problems of its assessment 0341-8162/91/5011851/US$ 2.00 + 0.25 CATENA--An Interdiaciplinm-y Journal of SOIL S C I E N C E - - H Y D R O L O G y ~ G E O M O R P H O L O O Y
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and application. Structure parameters, such as aggregation, were prominent subjects for studies around mid-century. In many of these studies, there was a compounding of structure, texture, organic matter content and possibly other variables (Bryan 1968a). In recent years the correlation of numerous soil properties with soil loss under natural and simulated rainfall have allowed the selection of the most dominant soil loss determinant for a given study. Thus, Wischmeier et al. (1971) proposed a widely used nomograph for estimating the K factor in the well known USLE equation. It employed five parameters: two related to particle size distribution, and the other three to organic matter content, soil structure and permeability class. In 1977, RSmkens et al. (1977) developed a multiple linear regression using the parameters of Wischmeier et al. (1971) that explained 90% of the variation in the erodibility factor K (USLE) of scalped surface soils. They found that the Wischmeier et al. (1971) texture, combined with one or more binding agent factors, such as percent A1203 plus Fe203 or sodium periodate consumption in the reaction, gave a significant prediction of K. Trott & Singer (1983) in a study of California range and forest soils in which they included a mineralogical component, found the most powerful soil loss predictor was a combined smectite plus vermiculite clay term. Also included in their four-variable regression equation were bulk density pyrophosphate extractable (Fe + A1), and the texture term of Wischmeier et al. (1971). Several studies on soils similar to those of Morocco emphasize the importance of calcium salts to erodibility. Massoud (1977) and Kadry (1977) have considered (ATENA
the unique texture and structure problems of calcareous soils. Silleos (1981} found that the nomograph of Wischmeier et al. (1971) underestimated the erodibility of soils in northern Greece. He attributed this to removal of CaCO3, before determining texture thus giving a false picture of the effective texture, and to the easy disintegration of calcareous soil aggregates, especially those high in the silt and clay size CaCO3 so-called "active" form of CaCO3, that leads to sealing of pores, crust formation, and decreased infiltration capacity. Consequently, he believed that the addition of organic matter to highly calcareous soils was especially important in the formation of stabilizing complexes between soil colloids and CaCO3. Imeson & Verstraten (1985) and Gaiffe (1990) have also recently confirmed these observations of easy slaking and of "effective" texture in calcareous Spanish and French soils. Dumas (1965) provided an erodibility index for Tunisian soils based on the percent of soil material >2 mm that he called percent stoniness. He obtained the following equation: log 100K = 2.586 - 0.0294 × % stoniness (r2 = 0.70), where K is a soil erodibility factor. Still little information is available on the erodibility of Mediterranean soils and particularly Moroccan soils, and solutions to curb soil erosion are still incomplete. For these reasons, more research is needed in almost all aspects of erosion to meet the increasing demands of conservation for better land management. The objectives of the present study were: 1. to relate soil erodibility to major
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Soil identification
Soil Classification U.S. Soil Taxonomy"
Parent material
References"
Aine A Biad Calci Hamri P. Vert Sable Tleta Trias Vert
Oehraqualf Calcixeroll Petro Calcic Palexeroll limestone Calcixeroll Palexeroll Quartzipsamrnent Xerofluvent Xerorthent Chromoxerert
Shale Marl Cretaceous Quaternary Quaternary Sandstone Marly Trias Quaternary
Ghanem (1978) Badraoui (1985) Badraoui(1985) Djibet(1984) Badraoui(1981) Ghanem (1978) FAO (1977) Djibet (1984) Badraoui(1981)
" Soil Survey Staff (1975) '" For additional information on these soils Tab. 1 : Description of the nine selected Moroccan soils.
physical, chemical and mineralogical properties of some surface soils in Morocco, and 2. to develop a predictive erodibility index that uses simple laboratorydetermined properties applicable to these soils.
2
Materials and methods
Using a rainfall simulator, soil losses were measured on 1 m 2 field plots on nine Moroccan soils located to the west of the Rif and Atlas mountains. Six replicates were measaured at seven locations, and four replicates were made at two of the field sites. Slopes of 9 to 10% were selected for the experimental sites described in tab. 1. All test sites were located on fields which had been cultivated to wheat for the last three or more years. The plots were prepared by removing any crop cover; roots protruding from the soil were clipped at the surface, leaving a soil surface condition similar to that of the fall season. The first storms of this season are very damaging as far as erosion is concerned. CATENA--An Interdisciplinary Journal of SOIL SCIENCE
The rainfall simulator was similar in principle to that described by Dixon & Peterson (1964). Soil at each plot was first wetted with a storm event of 100 m m h -~ intensity for 30 min. Runoff and soil loss measurements were made the following day under storm-like duration and intensity. The 10 crn hr-1 intensity is higher than that normally recorded in Morocco, but available data show several occurances of similar or higher intensities (Badou 1976). The simulator and plot area were covered with a tent to prevent disturbance by wind. Antecedent soil water content was measured in the surface 8 cm of soil immediately adjacent to the plot prior to the runoff measurements. Eight basic physical, eight chemical and three mineralogical soil parameters were measured on surface soil samples from each site. Physical soil measurements included bulk density using a core method; porosity was calculated from particle and bulk densities. Consistency limits were determined with an A S T M procedure, soil as well as a sediment particle size distribution by a pipette method. Satu-
HYDROLOGY~OEOMORPHOLOGY
Merzouk & Blake
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I
Soil Aggregates (2 - 8 mm) 200 g -Air Dried1
-50g-
- 150 g -
['-
Sieve Analysis = Size Distribution of Aggregates before rainfall apilieation
Dry
-I
20
cm Diameter Sieve (US No: 70)
Controlswitch
On asemi-loggraph paperplotboth disn-ibut'ion curvesto evaluate aggregatc's stability Dry Sieve Analysis = Size distribution of Aggregates after rainfall application
i
(UnderFume Hood) [ Infra Red
,,',',, ' ,,",
I I I If II I I I I I I
_
~
:,',',, Methanol ,,,','~J,-r~pray
I ~N'~ ilk.t:..,. I :,:'::?.:.~J
°
.
Appl. Time = 10 rain 1 Rain. Int. = 50 mm• hr
",'
Screen Time = I0 - 15 rain
Fig. 1: Procedure for the proposed method of aggregate stability testing under simulated rainfall.
CATENA An Interdisciplinary Journal of SOIL SCIENCE
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Estimation o f Internll Erodibility, Morocco
541
100
S¢
m
¢= 6{
B
~J n
&O--
2Cm
¢XX
O.Ot
O~
!.0
10
Mid-point Diameter (mm)
Fig. 2: Dry aggregates distribution curves, before and after rainfall application.
Soil name
Aine A Biad Calci Hamri P. Vert Sable Tleta Trias Vert
Soil loss" Mean 10-2 Mg'ha - l
Sd
82 614 170 294 380 70 190 299 504
22 254 55 72 142 14 73 84 151
Water loss" Mean Sd mm 28.6 32.1 32.2 28.0 29.5 5.2 34.6 42.9 31.8
3.7 7.3 4.7 3.9 1.0 0.5 12.5 4.5 5.5
Infiltration** Mean Sd mm h-t 31.0 23.0 22.9 31.0 28.3 82.2 18.8 9.5 21.5
6.3 16.2 7.4 5.9 4.7 4.8 12.4 3.2 9.6
" Applied = 50 mm of rainfall "" Equilibrium Infiltration rate
Tab. 2: Measured runoff, soil loss, and infiltration rate of nine soils. rated hydraulic conductivity was measured in the field adjacent to the plot by use of a double cylinder, constant head method, and soil water retention at 33 and 1500 KPa was determined using gravimetric and pressure apparatus, respectively. Other parameters, such as available water content or sand content for example, were derived from these
measurements. The above physical soil measurements were made using standard methods as outlined in methods of soil analysis (Part 1) by Klute (1986). Three variations of aggregate stability measurements were made, namely dry sieving by a method described by Kemper & Chepil (1965), wet sieving as outlined by Kemper (1965), and a laboratory test based
CATENA--An Interdis~plinary Journal of SOIL SCIENCE--HYDROLOGY~EOMORPHOLOGY
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on breakdown of aggregates under simulated rainfall developed for this study. This method was designed to simulate breakdown of a mass sample of aggregates when subject to rainfall. Impact of water drops was considered by EIlison (1944) to be one of the principal agents for the detachment and subsequent transport of soil particles. Bryan (1968b) has pointed out that aggregates that are stable in gently agitated water may prove to be much less stable when subject to the impact of high velocity raindrops. For this reason, the proposed method was used to simulate, better than wet sieving, the aggregate breakdown due to raindrops as it occurs in the field. Fig. 1 represents the procedure for the aggregate stability testing under simulated rainfall. Air-dried bulk surface soil was carefully broken to pass an 8 mm sieve. A sample remaining on 2 mm sieve was retained for the aggregate stability measurements. A subsample (150 g) was used to determine aggregate size distribution by dry sieving using the method of Kemper & Chepil (1965). A second 50 g sample was placed in a 20 cm diameter sieve with 0.2 mm openings. The sample size corresponded to the correct amount of aggregates that uniformly covered the sieve screen without having aggregates unexposed to falling raindrops. The sieve with the aggregates was placed beneath a small rainfall simulator and showered with simulated rain of 5 cm hr -I intensity for 10 min. The rainfall simulator used in this experiment is similar to the one described by Beggs (1982). The sieve was located 1.6 m below the oscillating nozzel. After being exposed to the simulated rainfall, the sieve was placed under a fume hood, the aggregates sprayed with ('AI'ENA
100 ml of methanol, and dried using infra-red lamps. Aggregate size distribution was then after determined by dry sieving. Dry sieving was used because of the weakness of the traditional wet sieving; that is wet sieving aggregates are plastic and less coherent, consequently their morphology is altered during sieving (Brandeau 1982). The objectif was then to use dry-sieving which is less erosive after drying the aggregates and permits them to retain their original character. For this puspose, a drying method was used similar to that used by Green-Kelly (1973) to prepare clay soils for determination of structure. The method consist of drying the aggregates under infra-red lamps in a dry atmosphere (under fume hood) and spraying them with methanol. The aggregates are hardened and the degree of hardening is increased by subsequent exchange with the methanol which is a water-miscible organic solvant and has a lower surface tension and lower viscosity. The gentle hardening of the aggregates limits excessive shrinkage and lessens the risks of structural rearrangement. This method which tends to preserve the aggregates, made the wet sieving unnecessary. The aggregate size distribution before and after rainfall application were used to evaluate the aggregate susceptibility to breakdown by drop impact into small sizes which are easily transported by splash and runoff water. Aggregate mean weight diameters (MWD) were computed from the size distribution curves. Fig. 2 shows the representation of the results. A large area between the curves means that the aggregates did not resist the raindrop impact. Several chemical properties of the soils were determined. Soil pH was measured in both a 1:2.5 soil to water ra-
An Interdisciplinary Journal of'SOIL, SCIENCE
HYDROLOGY
GEOMORPHOLOGY
Estimation o f Internll Erodibility, Morocco
Characteristics Coarse fragments, >2 ram, % Coarse sand, 2-0.1 mm, % Fine sand, 0-1-1.5 mm, % Coarse silt, 0.05-0.02 mm, % Fine silt, 0.02-0.002 mm, % Clay, <0.002 ram, % Bulk density, Mg/m 3 Ksat, mm/fi Permeability class Liquid limit, % Plasticity index Water content, 33 KPa, % Water content, 1500 KPa, % 33 - 1500 KPa, % Antecedent water content, % g/g Computed nomograph K (USLE)
543
/Line A
Biad
Calci
Hamri
P.Vert
Sable
Tleta
Trias
Vert
33.5 24.4 21.3 18.4 19.1 16.9 1.32 29 mod 28.5 1.6 16.8 8.4 8.5 19.7 0.375
1.8 2.8 7.7 15.4 33.3 40.8 1.17 35 mod 39.3 10.8 28.5 13.1 15.2 37.7 0.283
23.4 30.0 9.3 19.6 15.0 26.1 1.12 186 rapid 41.9 8.9 31.0 16.0 15.0 35.9 0.224
7.5 6.1 23.1 13.5 19.9 37.8 1.40 58 rood 26.4 9.0 25.7 11.3 14.4 28.6 0.303
2.5 1.0 6.6 10.6 23.1 58.7 1.37 39 slow 60.6 18.0 39.6 24.7 14.5 50.3 0.217
0 56.2 35.7 5.8 0.8 2.3 1.36 227 rapid 16.4 1.0 10.6 4.0 6.6 11.6 0.255
18.8 13.2 5.1 6.8 33.8 41.4 1.56 2.2 slow 42.2 9.1 28.8 20.3 8.5 23.6 0.236
7.1 8.7 18.7 31.8 22.4 18.9 1.38 34 rood 25.7 10.7 19.7 9.9 9.8 21.1 0.566
0.5 0.8 7.0 7.3 12.7 67.2 1.58 3 slow 65.1 12.0 42.1 26.0 16.1 46.9 0.178
Tab. 3: Some physical characteristics of soils at test sites. tio and soil to 1N KC1 solution. Total organic matter, total nitrogen, and available phosphorus contents were determined by chromic acid titration, a micro-Kjehldahl method, and soil extraction with a 0.5 molar NaHCO3, respectively. Exchangeable bases were determined in soil extracts by an atomic absorption spectro-photometer and exchangeable Ca ++ and Mg ++ amounts were estimated by an EDTA extraction method. Total CaCO3 and "active" CaCO3 were determined by the methods of Allison & Moodie (1965) and Douchaffour & Souchier (1979) respectively. Electrical conductivity was determined on a 1:5 soil-water ratio (Bower & Wilcox 1965). Clay fractions from which CaCO3, and organic matter were removed were Xrayed after saturation with Mg for a semi-quantitative estimation of different phases. Total iron and total free iron were determined by colorimetric methods. Statistical analysis of relations beCATENA
tween soil loss parameters as dependent variables and soil properties as independent variables were performed by use of a computerized statistical package of Bachacou et al. (1981).
3
Results and discussion
Results from simulated rainfall studies in the field are shown in tab. 2. Runoff and soil loss were measured directly and infiltration rate at the end of a 30-min run was determined by plotting. Standard deviations show that soil loss varied to a greater extent between replicates than did runoff. Mean soil loss was ranked by soil type. The time from initiation of simulated rainfall until beginning of runoff varied from around 20 seconds for the Vert soil to 15 minutes for the Sable. Measured physical characteristics of soils are given in tab. 3. The wide range of properties between soils is abundantly evident. Coarse fragments in the Aine
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Characteristics
Aine A
pH, water pH, Kcl EC, S.m ] Exchangeable CEC, cm°lKg-I Na + K+ Ca ++ Mg++ Base saturation, % Organic matter, % Total N, % Available P, mg.kg -1 CaCO3, total, % CaCO3, "active" Fe(Fe203), total, % Fe(Fe203), free, %
6.2 5.5 0.0207 12.6 0.24 1.91 6.4 2.6 88.5 2.66 0.16 14.2 0.0 0.0 4.21 2.59
Biad 8.4 7.3 0.0308 31.0 0.75 2.55 28.4 4.2 115.8 2.05 0.16 34.6 61.2 26.6 2.16 0.75
Calci
Hamri
P.Vert
Sable
Tleta
Trias
8.4 8.5 8.4 7.2 6.2 7.8 7.4 7.8 6.1 5.1 0 . 0 2 7 6 0 . 0 1 7 0 0.0276 10.023 0 . 0 9 5 27.4 25.0 69.6 5.3 16.1 1.2 3.42 23.2 4.0 l 16.0 3.32 0.28 120.3 19.0 4.0 2.73 1.05
0.43 2.62 16.3 2.4 87.0 1.64 0.16 22.8 5.8 2.7 3.4 1.36
0.64 0.74 61.6 3.9 96.0 1.72 0.16 22.8 0.7 1.4 5.21 2.04
0.19 0.12 3.9 0.5 87.7 0.55 0.08 9.0 0.0 0.0 1.47 0.75
0.37 1.76 8.9 4.2 94.4 0.99 0.12 5.5 0.0 0.0 7.28 3.08
Vc~-t
8.7 8.5 i: 7.6 7.2 I 0 . 0 1 6 4 (7.278 ~i 8.2 68.9 il 0.33 1.47 i 2.64 (/.72 ii 5.2 54.6 i 0.3 8.4 103.6 94.4 ! 0.63 1.05 0.08 0.08 ,i 23.3 10.7 il 9.74 0.84 ![ 3.1 3.42 [ 2.70 5.35 i 1.29 t.96 !
Tab. 4: Some chemical characteristics o f soils at test sites.
A were largely r o u n d e d iron concretions, those for T l e t a were p l a t y fragments, a n d those f r o m Calci were c a l c a r e o u s caliche fragments. A n t e c e d e n t w a t e r contents, m a d e at the b e g i n n i n g o f the soil loss a n d r u n o f f m e a s u r e m e n t s , were all greater t h a n the 33 K P a value except for the T l e t a soils. C h e m i c a l characteristics o f the soils are given in tab. 4 a n d the m i n e r a l o g i c a l in tab. 5. Tab. 6 shows the aggregates m e a n weight d i a m e t e r s for the soils a n d the sediments. F r o m simple c o r r e l a t i o n s a n d regression analysis between 42 soil p r o p e r ties m e a s u r e d directly (or d e d u c e d from m e a s u r e d properties), including c o m b i n a t i o n s o f the properties, a n d soil loss as the d e p e n d e n t variable, we were able to d e v e l o p predictive e q u a t i o n s t h a t show which soil m e a s u r e m e n t s best predict soil losses for the soils in this study. I n c l u d e d a m o n g the 42 variables were eight variations o r c o m b i n a t i o n s o f soil ag,,m'egate measurements. Tab. 7 shows the vail-
ous steps in the stepwise procedure, the first step being the basic e q u a t i o n with a single (combined) variable. The U S L E K value e s t i m a t e d from Wischmeier's n o m o g r a p h using soil p r o p e r t i e s was also included a m o n g the 42 variables t h o u g h its limited validity c a l c u l a t e d from o u r d a t a is recognized by the authors. The K value o f the U S L E estimates b o t h sheet a n d rill erosion a n d t r a n s p o r t by runoff. O n a 1 m a plot m e a sured sediment is p r i m a r i l y the result o f d e t a c h m e n t by r a i n d r o p impact. T h o u g h the t r a n s p o r t - l i m i t i n g c o n d i t i o n prevents a truly representative K ( U S L E ) value, we nevertheless believed that a p s e u d o K value which represents here m o s t l y the interrill-erodibility w o u l d p r o v i d e a valuable c o m p a r i s o n . The r a n k i n g o f erodibility as e v a l u a t e d by the n o m o g r a p h did n o t agree with that o b t a i n e d with the rainfall simulator. T h e relative soil erodibility a m o n g the nine soils was large, the greatest being as m u c h as 11 times as e r o d i b l e as the least,
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Estimation o f Intern11 Erodibility, Morocco
Clay minerals Smectite Vermiculite Illite Chlorite Kaolinite Interstratified Polygorskite Feldspar Quartz
Aine A
Biad
Calci
33
- -
. 66 18 2 7"*
.
.
38
.
. 7
- -
-12 10 Tr* 13 .
13
Soils P.Vert
Sable
60
27 17 20 -16 .
23
-19 15 Tr ° . .
19
Tleta
- -
.
-29 6 Tr ° 17
- -
Hamri
545
.
- -
9 7 -30 Tr** .
- -
-29 21 10 Tr*
-38 16 11 --
17
15"" 11
.
9
. 6
Trias
53
Vert 60 --20 11 Tr* - -
-9
Chlorite-Smectite ** Illite-Vermiculite *** Feldspar *
5 : Semi-quantitative estimation of percentage clay mineralogical composition of the a horizon of the soils by X-ray diffraction analysis..
Tab.
Soils
%WSA (mm)
MWDB (mm)
MWDA (mm)
MWD (Sediments)
Vert (mean)* (s.d.)
71.3 1.1
3.90 0.26
0.62 1.32
0.29
P. Vert
73.4 2.5
4.68 0.26
1.32 0.27
0.27
Calci
59.4 5.3
3.85 0.13
0.99 0.07
0.59
Biad
66.2 2.4
3.78 0.21
1.09 0.06
0.34
Trias
46.4 4.2
4.11 0.23
0.51 0.04
0.54
Aine A.
35.3 2.8
4.00 .023
1.90 0.25
0.77
Hamri
38.5 5.5
4.19 0.15
0.82 0.15
0.47
Tleta
46.6 3.0
3.97 0.39
1.16 0.17
0.84
Sable
19.3 1.4
4.78 0.19
1.71 0.25
T °*
* Mean from 6 replicates ** No stable aggregates collected T a b . 6 : Results of aggregates stability testing for (1) wet sieving method (% WSA ), for (2) the simulated rainfall methods (MWDB and MWDA) and the sediments aggregates MWD. M W D B = Dry Aggregates mean weight diameter (mm) before rainfall impact. M W D A = Dry Aggregates mean weight diameter (mm) after rainfall impact.
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The susceptibility of the soils to erosion was in the following order: Biad (calcixeroll) > Vert (vertisol) > P. Vert (vertic palexerol) > Trias (xerortent) > Hamri (vertic xerortent) > Tleta (vertic xerofluvent) = Calci (petro calci palexerol) > Aine A. (ochraqual) = Sable (quartzi psament). Agreement was found between the relative erodibility obtained with the use of the rainfall simulator and the relative magnitude of the erosion problems as observed in the field and reported by Badraoui (1981) and Kalman (1970). The smectitic nature of the clay (highly charged biedelite) minerals in the vertisols and their low organic matter content are important factors in their low infiltration capacity and high soil loss rate. It was observed that the slaking produced small aggregates that were easily removed from the plot by runoff. The mean weight diameter of the particles in the sediments washed off from the vertisols was greater than 0.29 mm, while over 70% of the primary particles had a diameter less than 0.002 mm (clay). This confirms what was found recently by Gaiffe (1990). The high structural stability allows the removal and transport of entire aggregates. Soil loss decreased with soil material >2 mm (SM>2 mm) on the surface (r=0.6t) not only because it ordinarily has a high infiltration rate, but also because of raindrop interception by surface exposed fragments acting like a mulch. Another relevant correlation was found between soil loss and the active CaCO3 (r=0.74). The calcareous soil (Biad) was the most erodible one. Greater erodibility on soils high in silt and clay size CaCO3 than on noncalcareous soils has been reported for various mediterranean I AI ENA
regions (Silleos 1981, and Gaiffe 1990). This high relative erodibility is mostly attributed to (l) the distribution of CaCO3 in the silt fraction, and (2) the instability of large aggregates in the presence of active CaCO3 content which causes the sealing of soil pores and crusting. The %WSA from wet sieving was positively correlated to soil loss (r=0.77), meaning that the higher the aggregate stability the higher the soil loss. This is not logical, contradicting all expectations. Many authors found this illogical result (Bolline 1978, Obi et al. 1989 and Gaiffe 1990). It seems that for some regions the %WSA index, as measured, is not a suitable predictor of soil erodibility. This positive correlation is accepted, like in our case, if we see that the erosion acts on the entire stable aggregates. The proposed method for testing aggregate stability bases on simulated rainfall showed a better correlation with soil erodibility than the wet sieving method (%WSA). With this method, the more unstable the aggregates the more soil erosion was observed. Though the correlation was relatively low in absolute value (r=0.5), in contrast to the %WSA the correlation sign was logical. The most powerful predictor in this model was the textural term ( % S M > 2 mm + % sand) with r2=0.81. It took three additional variables to achieve a correlation coefficient of 0.997 and the inclusion of two more variables to attain an r2--0.999. Using the stepwise multiple regression analysis many soil characteristics variables were eliminated because of their non-orthogonality or because of intercorrelations. The result was that only a structural term (aggregate stability) was retained. That a mineralogical term was selected by the computer in the regres-
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HYDROI.OGY
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Estimation o f Interrill Erodibility, Morocco
Step No. 1.
variable entered
r 2 of accumulated variables
Sm + Sa= % (soil material >2 mm) + % sand variables Regression coefficient
0.810
Sm + Sa Constant 2.
A C C = Active CaCO3 variables Sm + Sa ACC Constant
3.
547
-5.5341 517.2921 0.947 Regression coefficient -4.3744 9.0948 430.1961
E.C. = Electrical conductivity variables Regression coefficient Sm + Sa ACC E.C. Constant %WSA x MWD-B variables Sm + Sa ACC E.C. %WSA x MWD-B Constant % Smectite variables Sm + Sa ACC E.C. % W S A times M W D - B % smectite Constant
-4.4796 6.4491 613.3981 311.8291 0.997 Regression coefficient -6.4603 1.1206 1006.2560 -0.8264 498.5480 0.998 Regression coefficient -6.9452 3.2589 1466.2911 -0.5596 -1.7103 406.2594
K sat = saturated hydraulic conductivity variables Regression coefficient Sm + Sa ACC E.C. %WSA x MWD-B %smectite K sat Constant
0.980
0.999
-6.99993 1.1270 1355,8549 -0.5572 - 1.7215 0.2516 408.8670
Summary of the relative erodibility-predicting equations obtained using multiple regression analysis stepwise procedure ( Bachacou et al. 1981). T a b . 7:
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sion is interesting given the importance that researchers have recently placed on its role in soil aggregation. Kalman (1970) in Morocco and Yrott & Singer (1983) in California have reported that percent smectite clay minerals, because of their slaking tendencies correlated well with erosion. The second-most powerful predictor was the percent "active" calcium carbonate, (ACC). The erosion-controlling effect of this soil constituent has been recently reported by Silleos (1981) and other workers studying soil erodibility in the Mediterranean region. The strong correlation that was found in tab. 7 between soil loss and percent "active" CaCO3, smectite and soil material >2 m m points to the importance of parent material in the erodibility of Moroccan soils. The six soil variables selected through the last model in tab. 7, have been used individually or in combination by different researchers to explain and index the erodibility of Mediterranean and African soils. Though our model does not agree in particulars with the model of Wischmeier et al. (1971), both models show a dependance of soil susceptibility to water erosion on textural and structural properties. One of the objectives of the present study was to provide a simple relative erodibility index using soil parameters that can be obtained from routine laboratory determination with limited laboratory facilities. At the same time the variables should also be free of any intercorrelation. Based on the above criteria, it is suggested that only three of six soil parameters provided by the stepwise procedure (tab. 7) need be used. This would include a textural term ( % S M > 2 m m + % sand) with r2=0.81, the percent
"active" CaCO3 (ACC), r~-=0.5, and the electrical conductivity (EC), rZ=0.25. The multiple regression model obtained using three soil variables is then used as a relative erodibility index KR: Kr = 311.63 - 4.48 • ( % S M > 2 m m + % Sand) + 613.40 • EC + 6.45 < cdot % "active" CaCO3 For the soil conditions of this study this three parameter soil erodibility index satisfies the three major conditions stated above for its adoption and future use. Despite the high coefficient of determination (r2=0.98) that resulted for this index, it is important to bear in mind the limitation of the small plot used to obtain the data. It is not suggested that the model or index presented here be used to determine the Wischmeier K factor. What is suggested is that the present index can be used for the relative ranking of interrill erodibility of soils for the area studied. Acknowledgements
This research is a Contribution from the Institut Agronomique et V&6rinaire Hassan II (IAV Hassan II), Rabat. Support by U S A I D under contract NE/C1279, P R A G 608-0160, M O R O C C O is gratefully acknowledged. References ALLISON, L.E. & MOODIE, C.D. (1965): Carbonate. In C.A. Black (ed.), Methods of Soil
Analysis, Part 2. Agronomy 9, 1379-1400. Am. Soc. Agron., Madison, Wl. BACHACOU, J., MASSON, J.P. & MILLIER, C. (1981): Manuel de la programmatique statis-
tique. Amance 81, Dept. de Biomerie, I.N.R.A., C.N.R.I. 54280, Champenoux, Belgium. BADOU, M.C. (1976): Relation intensit6 frequence duroc dans les precipitations pluviales du Nord-ouest du Maroc. Hommes Terre et Eau. vol. 5. No. 20, Maroc.
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Estimation o f Intertill Erodibility, Morocco
BADRAOUI, M. (1981): Cartographic et caracterisation des sois de la region: Ettnine Khemis (Zone Nord), Province de Settat. Memoire de 36me cycle. D.S.S., I.A.V. Hassan II, Rabat, Morocco. BADRAOUI, M. & BLOOM, P.R. (1985): Mineralogy of Vertic soils of High Chaouia, Morocco. Agron. Abstr. p. 229. BEGGS, R.A. (1982): A portable field sprinkler infiltrometer. Master of Science thesis in Engineering, Utah State University. Logan, Utah. BOLLINE, A. (1978): Study of the importance of splash on the cultivated loamy soils of Hesbaye, Belgium. Earth Surface Processes, a journal of geomorphology 3, 71-84. BOWER, M. & WILCOX, L.V. (1965): Soluble salts. In: Methods of Soil Analysis. Agronomy No. 9, part 1. Amer. Soc. of Agronomy, Madison, WI. BRANDEAU, E. (1982): Fractionnement physique du sol. Methode de separation du comportement d'aggregats de 0.050 fi 2 ram. Cah. ORSTOM serie P6dologie. vol. XIX, No. 4, Paris.
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FAO/PNUD (1977): Projet MOR 71/536, Sch6ma d'am6nagement du bassin versant du Tleta. Rabat, Morocco. GAIFFE, M. (1990): Erosion of calcimagnesic soils as aggregates in jurassian pedological systems. CATENA 17, 141-149. GHANEM, H. (1978): Contribution ~ la connaissance des sols du Maroc; gen6se, classification et r6partition des sols des r6gions des Zaers, de la basse Chaouia et des Sehouls. Th6se Doctorat d'Etat. Universit6 de Gand. Inst. Geologic. Belgium. GREEN-KELLY, R. (1973): The preparation of clay soils for determination of structure. Journal of Soil Science. vol. 24 No. 3, 276-283. IMESON, A.C. & VERSTRATEN, J.M. (1985): The erodibility of highly calcareous soil material from southern Spain. CATENA 12, 291-306. KADRY, L.T. (1977): Distribution of calcareous soils in the Near East region, their reclamation and land use measures and achievements. In: Calcareous soils. EA.O. Soils Bulletin 21. Rome.
BRYAN, R.B. (1968a): The development, use and efficiency of indices of soil erodibility. Geoderma 2, 5-26.
KALMAN, R. (1970): Ruissellement et 6rosion en nappe (experimentation and simulation de pluie). Annales de la recherche Forestri6re au Maroc. Tome 12. Rabat. pp. 177.
BRYAN, R.B. (1968b): Development of laboratory instrumentation for the study of soil erodibility. Earth So. Journal 2, 38-50.
KEMPER, W.D. (1965): Aggregate stability. In: A. Klute (ed.), Methods of Soil Analysis. Agron. 9, 511-519. Amer. Soc. Agron., Madison, WI.
BRYAN, R.B., GOVERS, G. & POESEN, J. (1989): The concept of soil erodibility and some problems of assessment and application. CATENA 16, 393-412.
KEMPER, W.D. & CHEPIL, W.S. (1965): Size distribution of aggregates. In: C.A. Black (ed.), Methods of Soil Analysis. Agron. 9, 499-511. Amer. Soc. Agron., Madison, WI.
DIXON, R.M. & PETERSON, A.E. (1964): Construction and operation of a modified spray infiltrometer and a flood infiltrometer. Univ. of WI., Agr. Exp. Sta. Res. Rep. 15.
KLUTE, A. (ed.) (1986): Methods of Soil Analysis. Number 9 (Parts I) in the series Agronomy. Amer. Soc. for Agronomy and Amer. Soc. of Soil Sc., Madison, Wis., USA.
DJIBERT, B. (1984): Cartographie au 1/100.000 et caract~risation des sols dans les communes rurales de Bouguergouh et Aine Dorbane. M6moire de 36me cycle DSS. IAV Hassen II. Rabat, Morocco.
LAWS, J.A. & PARSONS, D.A. (1943): The relation of raindrop size to intensity. Trans. Amer. Geophys. Union 24, 452-460.
DOUCHAUFFOUR, P. & SOUCHIER, P. (1979): Pedologie, Tome 1 and Tome 2. Ed. Massan. Paris. DUMAS, J. (1965): Relation entre l'6rodibilit~ des sols et leurs caract6ristiques analytiques. Cahiers de I'O.R.S.T.O.M. S6rie P6dol. Vol. III, Fasc. 4. ELLISON, W.D. (1944): Studies of raindrop erosion. Agricultural Engineering 25, 53-55.
MASSOUD, F.I. (1973): Some physical properties of highly calcareous soil and the related management practices. In: Calcareous Soils. F.A.O. Soils Bull. 21. Rome. MIDDLETON, HE. (1930): Properties of soil which influence soil erosion. USDA Tecb. Bull. 178.
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ROMKENS, M.J., ROTH, C.B. & NELSON, D.W. (1977): Erodibility of selected clay subsoils in relation to physical and chemical properties. Soil Sci. Soc. Am. Jour. 41. 954-960. SILLEOS, M.G. (1981): The effect of calcium carbonate on soil erodibility in survey area in northern Grece. ITC Journal 1981-4. 418433. SOIL SURVEY STAFF (1975): Soil Taxonomy. U.S. Dept. Agr., S.C.S. Agron. Handbook 436. Washington, D.C. TROTT, K.E. & SINGER, M.J. (1983): Relative erodibility of 20 California range and forest soils. Soil Sci. Soc. Amer. J. 47, 753-759. WlSCHMEIER, W.H., JOHNSON, C.B. & CROSS, B.V. (1971): A soil erodibility nomograph for farmland and constructions sites. Jour. Soil and Water Conserv. 26, 189-193.
Addresaes of authors: A. Merzouk Department of Soil Science Institut agronomique et veterinaire Hassan II BP: 6202 Rabat-Instituts Morocco G.R. Blake Department of Soil Science University of Minnesota St. Paul, MN 55108 U.S.A.
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