Published online 11 January 2008
Published in Soil Sci Soc Am J 72:33-40 (2008)
DOI: 10.2136/sssaj2006.0343
© 2008 Soil Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
SOIL PHYSICS
Bimodal Zone of the Soil Textural Triangle: Common in Tropical and Subtropical Regions
Devaraj de Condappaa,b,*,
Sylvie Gallea,c,
Benoit Dewandeld and
Randel Haverkampa,c
a Lab. for Transfers in Hydrology and Environment (LTHE), UMR 5564 CNRS-INPG-IRD-UJF, BP 53, 38041 Grenoble cedex 9, France
b Indo-French Center for Groundwater Research (IFCGR), National Geophysical Research Institute (NGRI), Uppal Road, Hyderabad 500007, India
c Institut de Recherche pour le Développement, 08BP 841, Cotonou, Bénin
d Bureau de Recherches, Gèologiques et Minières (BRGM), Water Division, 1039 rue de Pinville, 34000 Montpellier, France
* Corresponding author (condappa{at}gmail.com).
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ABSTRACT
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The USDA soil textural triangle shows a zone where soils have a low silt fraction compared with the fractions of sand and clay. These soils have a particle-size distribution function showing two local maxima in weight percentage for the particle-size ranges of sand and clay. The soils are referred to as bimodal soils, with an associated bimodal zone in the soil textural triangle. It was shown that processes of pedogenesis in tropical and subtropical regions favor the generation of bimodal soils. Data from the Maheshwaram watershed in South India (subtropical), the Ouémé watershed in Bénin (subhumid), and soil databases established for (sub)tropical regions confirmed that bimodal soils are common in (sub)tropical climates. These results were backed up by the fact that sample populations of bimodal soils are underrepresented in databases such as UNSODA, GRIZZLY, or the Soil Information System of the Netherlands, all three of which contain soils mainly from temperate regions. The consequences of bimodal soil behavior are important. The hydrodynamic flow behavior of these soils should be different from that of monomodal soils. The concept of shape similarity between the cumulative particle-size distribution curve and the water retention curve, validated for monomodal soils, implies that bimodal soils should theoretically exhibit bimodal hydraulic properties. These consequences are far reaching since most of the soil hydraulic models in the literature are monomodal and hence inadequate to describe the hydraulic behavior of bimodal soils from (sub)tropical regions.
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INTRODUCTION
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As shown by many studies on preferential flow and transport in the literature (e.g., Beven and Germann, 1982; Germann and Beven, 1985; Edwards et al., 1988; Gerke and van Genuchten, 1993; Zurmühl and Durner, 1996), heterogeneous porous systems of natural soils have been puzzling scientists for a long time. In their review, 
im
nek et al. (2003) proposed a multiporosity approach for modeling heterogeneous soils. Nimmo (1997) divided the soil total porosity into two components, one relating to soil texture (e.g., the particle-size distribution), and the other relating to soil structure (e.g., the macropores). The concept of multiporosity has consequences on hydraulic properties, as Laplace's capillary theory implies a multimodal retention curve.
Multiporous systems are generally associated with structural effects only, without considering soil textural effects (e.g., Nimmo, 1997). Several studies presented in the literature (e.g., Fiès, 1971; Chrétien and Bisdom, 1983; Fiès and Bruand, 1998), however, show that the texture of a soil, in addition to structural effects, can itself be a cause of hydraulic functional multimodality.
The purpose of this study was to delineate a zone of the USDA soil textural triangle where soils have low silt content compared with the fractions of sand and clay, and thus exhibit a textural bimodal behavior. It will be shown that soils belonging to this textural zone are common in tropical or subtropical regions and are likely to have hydraulic bimodal behavior.
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BIMODAL SOILS ZONE OF THE USDA SOIL TEXTURAL TRIANGLE
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Conventionally, soil particles with diameter D [L] <2000 µm are classified into the three particle-size fractions of sand, silt, and clay. Particles >2000 µm are classified as gravel. Using the USDA soil classification system (Soil Survey Laboratory Staff, 1992), the three particle-size fractions are defined as: sand (Sa) with 50 
D 2000 µm, silt (Si) with 2 < D < 50 µm, and clay (Cl) limited by D 2 µm. The size fractions are expressed in percentages by weight such that
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The textural classification of soils as a function of their particle-size distribution is generally presented through the use of the USDA soil textural triangle (Fig. 1
). For example, a soil consisting of 50% sand, 5% silt, and 45% clay by weight is a sandy clay (identified by an open square in Fig. 1), whereas a soil with 5% sand, 50% silt, and 45% clay is classified as a silty clay (identified by a filled circle in Fig. 1). The difference between the two examples lies in the silt and sand fraction. The particle-size distribution of the first example (sandy clay) has two local maxima in weight percentage for two distinct particle-size ranges, one in the clay range and another in the sand range; while the second example (silty clay) has only a single maximum in the particle-size ranges of silt or clay. The soils of the former and the latter examples have bimodal and monomodal behavior, respectively. The bimodal behavior is obviously determined by the condition
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Fig. 1. The USDA soil textural triangle. Open square: a sandy clay with 50% sand, 5% silt, and 45% clay; filled circle: a silty clay with 5% sand, 50% silt, and 45% clay. The shaded area corresponds to bimodal soils satisfying Eq. [2].
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Considering the USDA soil textural triangle (Fig. 1), Eq. [2] defines an area that is limited by the segment [A,G], where Sa = Si, and the segment [G,S], where Cl = Si, G being the gravity point such that Sa = Si = Cl = 100/3. Any soil satisfying Eq. [2] will have a bimodal behavior, with its sand and clay fractions greater than its silt fraction. Hence, the soil textural triangle has two distinct areas: the bimodal zone given by Eq. [2] and the monomodal zone covering the rest of the triangle surface.
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BIMODAL SOILS ARE COMMON IN (SUB)TROPICAL REGIONS
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Let bimodal soils be defined as soils belonging to the bimodal area of the USDA soil textural triangle: their silt fraction in weight percentage is then systematically smaller than their clay and sand percentages. To explain the existence of such soils, it is essential to consider the processes of soil genesis. The two main processes are weathering of the parent rock and pedogenesis (e.g., Fanning and Fanning, 1989). Soils are the final output of rock weathering and they are generated on top of the weathering profile. Among the different pedogenic processes, physical weathering (e.g., disintegration into smaller fragments), hydrolysis (e.g., dissolution of minerals in water), leaching (e.g., downward leaching of clay particles) and erosion (by water and wind) are particularly active in the creation of soil particles (e.g., Fanning and Fanning, 1989).
The phenomenon of hydrolysis, which requires water and which is accelerated by increasing temperature, is dominant in tropical and subtropical regions (Tardy, 1993). Hydrolysis dissociates and alters the original rock minerals, hereafter referred to as primary minerals, into entities in equilibrium for the surface conditions, noted as secondary minerals. While some primary minerals such as olivine are highly affected by hydrolysis, others such as quartz are hardly altered at all (Tardy, 1971). Moreover, the kinetics of hydrolysis increases with the specific surface (Ss) of soil particles, defined as the ratio of area to mass, equivalent to the ratio of area to volume, which in turn is equivalent to the inverse of the particle-size diameter. Hence, the smaller the particle of a given primary mineral, the sooner it will be eliminated (e.g., Legros and Pedro, 1983). For a parent rock without quartz minerals <50 µm, the percentage of primary minerals in the soil decreases from sand to clay. Simultaneously, neoformation occurs, that is the genesis of secondary minerals. Most of these secondary minerals, having a dimension <2 µm, are called clay minerals (e.g., Buol et al., 2003) and contribute to the total clay content of (sub)tropical soils. In summary, for a parent rock without quartz minerals <50 µm, the combination of clay minerals with sand particles of primary minerals, gives ultimately bimodal soils with clay and sand fractions larger than their silt fractions.
Moreover, for the case of a permeable soil surface layer, leaching of clay by infiltrated water may also be a major process of pedogenesis. It creates in the soil profile an upper eluviation layer (E horizon) poor in secondary clay minerals and an underlying illuviation layer (B horizon) rich in secondary clay minerals (e.g., Buol et al., 2003). The B horizons of these soils are likely to show bimodal behavior.
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VALIDATION OF BIMODAL BEHAVIOR FOR SOME (SUB)TROPICAL SOILS
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The validation of the climatic specificity of bimodal soils was performed for two different watersheds and is illustrated for four classical soil databases.
The Maheshwaram Watershed
The Maheshwaram watershed is located in Andhra Pradesh State, South India. It covers 53 km2 and is situated between 78°24'30'' to 78°29'00'' E and 17°06'20'' to 17°11'00'' N. The topography of the area is rather flat, with an altitude ranging from 590 to 670 m above sea level. The climate is subtropical, controlled by the periodicity of the Indian southwest monsoon (June–October), with a mean annual rainfall of 750 mm. The average annual temperature is 26°C, but temperature can occasionally reach 45°C during summer (April and May).
The geology of the area is relatively homogeneous and is composed of Archean granites without quartz minerals <50 µm (Dewandel et al., 2006). The two main soil taxonomic classes according to the USDA pedological classification system (Soil Survey Staff, 1960) are (i) the Alfisols, predominant soils of the watershed resulting from autochthonous pedogenesis on the weathered granite, and (ii) the Entisols, allochthonous soils resulting from cycles of alluvial deposits. Alfisols are a result of three active pedogenesis processes: (i) hydrolysis of granitic primary minerals, (ii) leaching of secondary clay minerals, and (iii) water erosion. The first process eliminates primary minerals <50 µm, leading to a residual concentration of sand particles; additionally, it generates secondary clay minerals. The second process generates the E and B horizons, and the third process limits the thickness of the Alfisols. Typical depths of the horizon base are 0 to 40 cm for the E horizon, 60 to 300 cm for the B horizon, and lower for the C horizon. The horizons are clearly observable in Alfisols, whereas Entisols show less contrasting horizons.
A total of 157 samples of Alfisols and Entisols was taken at several locations and depths (0–300 cm) in the watershed. Particle-size analyses were performed using dry sieving and the hydrometer method. For each sample, 15 different particle-size classes were determined down to a diameter D = 2 µm. Hence, only the silt and sand fractions were fully determined; the clay fraction was calculated from Eq. [1]. An example taken from the B horizon of an Alfisol is given in Fig. 2
. With a particle-size distribution of 35% clay, 12% silt, and 53% sand, the soil is classified as a sandy clay. Starting at D = 2000 µm, the cumulative particle-size distribution curve F(D) decreases sharply as D decreases, showing an inflection point in the sand range at a particle diameter for which a local maximum in weight percentage is attained. Next, it decreases gradually without any additional inflection point in the silt zone, indicating a low silt content. No data are available in the clay zone. But, since the clay content is high (i.e., 35%), the F(D) curve may certainly decrease steeply as D decreases, with a second inflection point in the clay zone. These results clearly illustrate a bimodal soil. They also show that it is advisable to carry out more extensive particle-size analyses for this type of Alfisol, including the clay zone (D < 2 µm).
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Fig. 2. Bimodal cumulative particle-size (D) distribution of a sandy clay soil with 53% sand, 12% silt, and 35% clay. The soil sample was taken from the B horizon of an Alfisol at the Maheshwaram watershed (South India). The vertical dotted line indicates an inflection point in the sand zone.
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The particle-size distribution statistics of the 157 samples are given in Table 1
. The textural classifications of the E, B, and C horizons of both Alfisols and Entisols are plotted in Fig. 3a to 3c and 4a to 4c
on the USDA soil textural triangle. Starting with the Alfisols, a small and rather constant silt fraction (around 12%) is observed for all three horizons (Table 1). The samples from the E horizon are very sandy (mostly loamy sand, Fig. 3a), with 33% being bimodal soils (11 samples out of 33). The samples from the B horizon are more clayey and mostly sandy clay loam (Fig. 3b), with as much as 99% bimodal soils (66 samples out of 67). Finally, the samples from the C horizon become again sandier, mostly sandy loam (Fig. 3c), with 54% bimodal soils (14 samples out of 26). Even though the soil profiles of the Entisols are more silty than those observed for the Alfisols (Table 1), they still contain a similar proportion of bimodal soils, i.e., 63% (five samples out of eight) for the E horizon (Fig. 4a
), 82% (18 samples out of 22) for the B horizon (Fig. 4b), and none for the C horizon (the only sample collected is a monomodal soil). It is noteworthy that most samples of the Alfisols' B horizons are gravelly (the gravel weight represents around 30% of the total soil sample weight). The gravel content was not considered in this work since the gravel percentage is not a variable of the USDA textural triangle.
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Table 1. Mean particle-size fractions determined for 157 soil samples collected in the Maheshwaram watershed (South India) for the two main pedological soil classes of Alfisols and Entisols.
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Fig. 3. Textural classification of Alfisols collected at various depths in the Maheshwaram watershed (South India) plotted on the USDA soil textural triangle: (A) E horizon, (B) B horizon, and (C) C horizon.
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Fig. 4. Textural classification of Entisols collected at various depths in the Maheshwaram watershed (South India) plotted on the USDA soil textural triangle: (A) E horizon, (B) B horizon, and (C) C horizon.
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These results show that bimodal soils are predominant in the Maheshwaram watershed. They are mainly present in the B horizon (60–300 cm in depth) of Alfisols and are typically sandy clay loam or sandy clay. As for the Entisols, pedogenesis processes develop bimodal soils in the B horizon of these alluvium soils with time.
The Ouémé Watershed
The Ouémé watershed (14,600 km2) is a meso-scale observation basin of the international African Monsoon Multidisciplinary Analysis (AMMA)1 project that aims at a better understanding of the African monsoon mechanisms and the interaction between the atmosphere and the continental surface (Redelsberger et al., 2006). It is located in central Benin, between 1°30' and 2°48' W and 9° and 10°12' N. The topography of the area is characterized by a gently undulating relief 250 to 500 m above sea level. The region has a subhumid climate with a monsoon season between April and October. The average annual rainfall is 1100 mm, the mean annual temperature is 26.4°C, and the maximum annual temperature can reach 39°C during the dry season (February–May).
The catchment is situated in the Dahomeyan crystalline basement and the prevailing geology is granite gneiss. The dominant soils in the catchment are autochthonous "ferrugineux tropicaux lessivé" (Faure, 1977; Faure and Volkoff, 1998) according to the French soil classification and autochthonous Alfisols according to the USDA taxonomy (Soil Survey Staff, 1960). As for the case of the Maheshwaram watershed, the Alfisols of the Ouémé basin were formed through hydrolysis of primary minerals, leaching of secondary clay minerals, and water erosion. The three pedological horizons A, B, and C are observed. Typical depths of the horizon base are 15 to 40 cm for the A horizon, 70 to 160 cm for the B horizon, and lower for the C horizon (Faure, 1977).
In the framework of the AMMA program, 63 particle-size distribution samples of the A horizon taken at several locations were analyzed. Additionally, 71 particle-size distributions of the A, B, and C horizons were collected from the literature (Agossou, 1977; Faure, 1977; Igue, 1991). The statistics of the particle-size distributions are given in Table 2
and the soil classification of the three horizons (A, B, and C) is plotted in Fig. 5
on the USDA soil textural triangle. The silt percentage within the soil profile is relatively small (around 15%), but not as significantly small as for the Maheshwaram watershed. Similar to the results for the E horizon of the Indian watershed, the samples from the A horizon are very sandy, mainly sandy loam (Fig. 5a), with 24% bimodal soils (22 samples out of 90). The samples from the B horizon are more clayey, mainly sandy clay loam (Fig. 5b), with 83% bimodal soils (30 samples out of 36). Finally, the samples from the C horizon become even more clayey and less sandy, mainly sandy clay and sandy clay loam (Fig. 5c), with 100% bimodal soils. Moreover, as for the Maheshwaram watershed, some soils from the B horizon contain gravel with a weight percentage around 30% of the total soil sample weight.
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Table 2. Mean particle-size fractions determined for 134 Alfisol samples collected in the Ouémé watershed (Benin, western Africa).
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Fig. 5. Textural classification of Alfisols collected at various depths in the Ouémé watershed (Benin, western Africa) plotted on the USDA soil textural triangle: (A) A horizon, (B) B horizon, and (D) C horizon.
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In agreement with these results, Giertz and Diekkrüger (2003) reported sandy clay loams, i.e., bimodal soil behavior, for some soils of the B horizon in the Ouémé catchment.
Soil Databases
So far, the analysis of the two watersheds shows, indeed, that bimodal soils seem to be common in tropical and subtropical regions. This may be examined from a different angle by analyzing the various soil databases published in the literature (e.g., the review of Wösten et al., 2001). Since these soil databases compiled data from mainly temperate regions, bimodal soils should be underrepresented. A soil data bank of (sub)tropical soils is presented as well.
Among the four databases analyzed, the UNSODA soil database (Leij et al., 1996) was compiled first. It covers 780 soils, providing basic soil properties such as bulk density, organic matter, particle-size data, soil hydraulic data, and mineralogy. Only 666 soils are documented with soil textural data. Most of these soils are either from Europe (around 46%) or from North America (around 45%) (Nemes et al., 2001). The data of UNSODA are placed on the USDA soil textural triangle in Fig. 6
. Less than a quarter (23%) of the soils belong to the bimodal soil population, hence confirming that the bimodal zone is less represented than the monomodal zone in this compilation of soils collected mainly from temperate regions.
The second database is the GRIZZLY soil database reported by Haverkamp et al. (1998). It contains basic soil properties including dry bulk density, particle-size distribution, organic matter percentage, and soil hydraulic property data for a population of 660 soils. The soils come from different parts of the world, but mainly from the temperate climate regions of Europe (Austria, France, Hungary, Spain, and the Netherlands) and the USA. After thoroughly checking the sample population of the GRIZZLY soil database, it was found that only 12 soil samples were listed from subtropical regions, i.e., Morocco, Ivory Coast, Senegal, Israel and northern Australia. Figure 7
shows the GRIZZLY data placed on the USDA soil textural triangle. Only 16 soils (2%) are in the bimodal soil zone.
The third soil database is a sample of the Soil Information System of the Netherlands. Nemes et al. (1999) randomly extracted 9607 soils from the soil data bank. Their Fig. 3 is reproduced here together with the bimodal zone (Fig. 8
). It clearly shows that the bimodal zone is significantly less represented than the monomodal zone.
The fourth soil database is that of Hodnett and Tomasella (2002). From the IGBP-DIS database, they selected 771 soils belonging to tropical or subtropical regions. Their Fig. 1 is reproduced here together with the bimodal zone (Fig. 9
). About half of the soils belong to the bimodal soil zone. They studied 614 soils from Brazilian Amazonia, which they described as being "characterized by a very low silt content (usually less than 10%), even though the texture ranged from sand to clay" (Tomasella and Hodnett, 1998); their textural triangle clearly suggests that the major part of the 614 soils is comprised of bimodal soils. Similar results were presented by Tomasella et al. (2000) for a population of 630 soil samples collected throughout Brazil.
In conclusion, the foregoing analyses of the four different soil databases clearly confirm that bimodal soils are (i) well represented in (sub)tropical climate regions and, on the contrary, (ii) much more rare in temperate climate regions.
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CONSEQUENCES FOR HYDRAULIC BEHAVIOR
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Textural particle-size properties are determined from the size distribution of individual particles in a soil sample. Classically, the discrete particle-size measurements are represented in a continuous form using particle-size functions of the type F(D) (e.g., Haverkamp and Parlange, 1986; Buchan, 1989; Shiozawa and Campbell, 1991; Bittelli et al., 1999; Skaggs et al., 2001). According to Haverkamp and Reggiani (2002), the cumulative distribution function F(D) is described by an expression similar to that chosen for the water retention curve, h(
), where h [L] is soil water pressure head and [L3 L–3] is volumetric soil water content. Hence, when using a given equation (e.g., that of van Genuchten, 1980) for the F(D) function, the same type of equation should be used for the water retention function h(). This concept of shape similarity was used earlier by Arya and Paris (1981) and Haverkamp and Parlange (1986) for predicting soil water retention characteristics from particle-size information.
Besides these physico-empirical models, the cumulative particle-size distribution function is often used for the determination of soil hydraulic properties through pedotransfer functions or PTFs (Bouma and van Lanen, 1987). These are generally empirical relationships that allow the hydraulic properties of a given soil to be predicted from more widely available data, such as texture (sand, silt, and clay percentages) and bulk density. Among the many PTFs proposed in the literature (e.g., Clapp and Hornberger, 1978; Cosby et al., 1984; Rawls and Brakensiek, 1989; Vereecken et al., 1989; Schaap et al., 1998; Jarvis et al., 2002), some have been developed for predicting the system parameters of the water retention equations of Brooks and Corey (1964) or van Genuchten (1980). For these PTFs, the direct conversion from particle-size shape parameters to water retention shape parameters is generally chosen.
All models presented so far (either physico-empirical or PTFs) have one point in common: they consider a monomodal functional behavior of the cumulative particle-size distribution or the water retention equation. When bimodal functional behavior occurs, however, these models are no longer suitable. The concept of shape similarity between the cumulative particle-size distribution function and the water retention equation has been validated for monomodal behavior by Haverkamp and Reggiani (2002). Suppose this concept is also valid for bimodal behavior; then the hydraulic properties of soils satisfying the textural condition of Eq. [2] would systematically follow bimodal behavior. The consequences for the modeling of water transfer problems in (sub)tropical soils can be far reaching, as the bimodality may require a redefinition of the mathematical framework used so far for the description of soil hydraulic characteristics.
Surprisingly, almost no studies were found in the literature that scrutinize the complication associated with textural bimodal soils and their consequences. Further analysis of these specific problems should be the subject of future research.
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CONCLUSIONS
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This study was focused on the bimodal zone of the USDA soil textural triangle, where soils have a low silt fraction compared with the fractions of sand and clay. Such soils have a cumulative particle-size distribution function showing two local maxima in weight percentage for the two distinct particle-size ranges of sand and clay. These soils are referred to as bimodal soils with an associated bimodal zone in the soil textural triangle.
It was shown that (sub)tropical climates are favorable for the genesis of bimodal soils. Experimental data from the Maheshwaram watershed in South India (subtropical) and the Ouémé watershed in Benin (subhumid) displayed mainly bimodal soils, especially within the B and C horizons. Soil databases from (sub)tropical climate regions confirmed that bimodal soils are common in these regions. These results are backed up by the fact that sample populations of bimodal soils are underrepresented in databases containing soils from mainly temperate regions, such as UNSODA, GRIZZLY, or the Soil Information System of the Netherlands.
A challenging consequence of the textural bimodality concerns the soil hydraulic properties. Cumulative particle-size distribution models are often used for PTFs. Following the concept of shape similarity between the cumulative particle-size distribution curve and the water retention curve, textural bimodal soils should then be characterized by bimodal hydraulic soil characteristics. Most models presented in the literature for soil hydraulic characteristics, however, describe only monomodal functional behavior, and most PTFs were developed for monomodal hydraulic property models. Hence, there is the challenging task to develop a new mathematical framework suitable for bimodal soils of (sub)tropical climate zones belonging to the bimodal zone of the USDA textural triangle.
Additionally, the upper limit of the soil textural classification at D = 2000 µm may be questioned. While this arbitrary threshold value is classically used in soil science, other disciplines such as geotechnics take into account the complete range including gravel (D > 2000 µm). The bimodal soils observed in the B horizons of the Maheshwaram and Ouémé watersheds contain large amounts of gravel, which is likely to occur for other soils of (sub)tropical regions with similar pedogenesis processes. Hence, the classical approach that truncates the gravel range in some arbitrary way is perhaps not fully appropriate for (sub)tropical soils.
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ACKNOWLEDGMENTS
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This study was funded and supported by the Bureau de Recherches Géologiques et Minières (BRGM), France, the National Geophysical Research Institute (NGRI), India, and the African Monsoon Multidisciplinary Analysis international program. We thank Dr. S. Ahmed of the Indo-French Center for Groundwater Research (IFCGR) for his support and Dr. F.J. Leij for providing data from the UNSODA database.
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NOTES
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1 Based on a French initiative, AMMA was built by an international scientific group and is currently funded by a large number of agencies, especially from France, UK, USA, and Africa. It has been the beneficiary of a major financial contribution from the European Community's Sixth Framework Research Program. Detailed information on scientific coordination and funding is available on the AMMA International web site: www.amma-international.org (verified 28 Sept. 2007). 
All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.
Received for publication October 4, 2006.
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ABSTRACT
INTRODUCTION
