In the following sections, the results were categorized under, textural classification (section 4.1), index properties (section 4.2), and an empirical formula derived for the plasticity index of marshy soils (section 4.4). SPT-N values and strength properties of soils were given in section 4.3 while an overview of the study was given in section 4.5.
4.2. Index Properties
Index properties could be used to describe the observable behaviour of the soils with their physical characteristics. Index properties such as the grain sizes distribution range, soil consistency (Atterberg limits), liquidity index, compression index, natural moisture content, the activity of soils, and swell potential of soils were studied.
4.2.1. Soil groups and their grain sizes distribution ranges
Soil gradation is an important aspect of geotechnical engineering because it is an indicator of other vital engineering properties such as compressibility, shear strength, and hydraulic conductivity. Lee (1961) noted that the colloidal content of clays provides the necessary plasticity or workability. Akinmusuru and Adebayo, (1981) indicated that the sand size particles contribute to the mechanical strength.
Figure 3 indicates partial size distribution ranges of studied soils. Although soil samples were classified with the same name, they contained different gravel, sand, silt, and clay fractions in different soils (see Figs. 3a, b, c, d, e, f). For example, sandy soil groups encountered in Re_W had a relatively small range of gravel fractions (Fig. 3a). However, the same soil group in SED_D (Fig. 3f) had a relatively high range of gravel fraction while particular soil groups that occurred in MY_W (Fig. 3c) are associated with either no or negligible amounts.
The highest gavel fractions associated with Al_W (Fig. 3b) fall within 7.00-7.45m, 11.00-11.45m, and 14.00-14.45m depth range from the surface. These gravel beds might have been deposited after strong flood events. At present, remnants of large gravel deposits can be observed along with earlier flood plains of the Mahaveli river around Peradeniya. Marshy areas were associated with a relatively larger fraction of fine grains. However, considering the fine-grain soil groups of all other soils, it revealed that geomorphologically flat terrains with low elevations in the vicinity were responsible. Therefore, during the flood period, fine-grain particles may reach such marshy areas as suspension load and be deposited. Considering the same soil group, a sand fraction (e.g. in SC) is relatively highest in Co_D (Fig. 3e) while lowest in the shell of earth dams SED_D (Fig. 3f).
4.2.2. Soil Consistency (Atterberg) Limits
The consistency states of soils are extensively used both in the construction industry (buildings and roads) and in agricultural practices (Archer, 1972). The parameter is evaluated based on Shrinkage Limit (SL), Plastic Limit (PL), and Liquid Limits (LL). The consistency limits have also been repeatedly shown to be useful indicators of clay behaviour (Jefferson and Rogers, 1998; Mbagwa and Abeh, 1998; Keller and Dexter, 2012). In addition, consistency limits also provide information for interpreting a number of soil mechanical and physical properties such as the shear strength, compressibility, shrinkage, and swelling potentials, etc., (Archer 1975; Campbell 2001; McBride 2008; Seybold et al. 2008). Figure 4 indicates the variation of SL (Fig. 4a), PL (Fig. 4b), LL (Fig. 4c), and Plasticity Index (PI; Fig. 4d) of studied soils.SL variation of plastic soils does not make a significant difference except for Co_D which shows relatively low SL (Fig. 4a).
However, PL and LL exhibit significant differences among the studied soils (Figs. 4b and c). Arthur (1942) showed that the Atterberg limits have increased with decreasing particle size. Since My_W contains organic and inorganic clay-rich soil groups such as OH, OL, Pt/CL, CH, and CL, high PL and LL values can be observed. LL of soil is proportional to clay content (Skempton, 1944). Clay + Silt fraction of marshy soils as high as 91% in some localities while the highest gross clay fraction (up to 55 %) also can be obtained here. Although the gross clay fraction of Al_D soils is lower than My_W and Al_D soils also represent high average PL, LL, and PI after the My_W soils. The Al_D soils also show high average PL, LL, and PI (Fig. 4d) which could be due to highly plastic clay types. It may be possible because the whole drainage basin of Koill Aru river (see Supplementary document 1) is concentrated in the dry zone of the country. Therefore, the occurrence of high plastic clay type in the soils such as illite has more probability. At the same time, the Mannar area in the northwest of Sri Lanka is the most recognized for occurring highly plastic montmorillonite type clay (e.g. Senevirathna and Senaratne, 2011).
Re_W are shown with a wide range of PL, LI, and PI, possibly due to Atterberge limits directly correlated with parent rock from which soils were derived. Higher PI values can be obtained from soils over the Garnet Biotite Gneiss while those soils were mainly classified as SC while the lowest PI over the Hornblende Biotite Gneiss which represent soil groups mainly SM and SM-SC. Soils derived over Marble and Undifferentiated Charnockite exhibit intermediate PI values. Soil which has been developed over Hornblende biotite gneiss has relatively high PL although gross clay and gross silt fraction are relatively less. Seed et al. (1964), pointed out, at a range of the small amount of clay fraction, the PL is independent of clay content or increases slightly with simultaneous increases of non-clay content due to the frictional resistance between non-clay particles. Soils with plastic soils in SED_D, Al_W and are represented by lower Atterberg limits because those soil are associated with a lower fine-grain faction. PL and LL are closely associated with SED_D, and as a result, the lowest PI can be obtained.
4.2.3. Plasticity of Soils
The position of soil as defined on Casagrande’s (1948) plasticity chart is a useful indicator of its engineering properties. Soils that plot well below the “A”- line has good engineering properties (Wesley, 2010). The soil in general has higher plasticity under cold and dry weather conditions and lower plasticity under warm and wet weather conditions (Scott and Yates1931).
Soils collected from various depths in Re_W have represented an uneven distribution with low to high plasticity (Fig. 5a). Plasticity has no significant relationship with the depth except for soils in the My_W (Fig. 5b), where the LL and PI of marshy soils show a linear relationship. The data were plotted around the “A” line while LL and PI were decreased with depth. Soils studied from the marshy area lie along with the abandoned paddy fields and it extended more than 20km along a structural lineament (Supplementary Fig. 3). During the rainy season, the Kaduwala area is frequently subjected to flood since the overflow of the Kalani river (Basnayake et al. 2007). Therefore, stratification of sediments deposited in the soil profiles can be observed.
Alluvial soils collected from 1.00 to 15.00m in the wet zone are generally plotted into the shaded area (named CL-ML) of the plasticity chart (Fig. 5c). Low clay fraction could be mainly responsible for the low plastic behaviour of those soils. Soils in the upper 16m of Al_D soils (Fig. 5d), indicated low to intermediate LL (27% - 47%) and relatively high PI (8% – 16%) compared to Al_W soils.
All the soil samples from Co_D (Fig. 5e) were plotted above the “A” line and had low plasticity, especially those SPT boreholes around Batticaloa located within the sandbars toward the seaward from the Batticaloa lagoon. These sand bars may represent former barrier islands with specific depositional characteristics due to genetic history. As a result, within the upper 3m, all soil types were classified as SW and SP. However, considering the locations around Pottuvil, non-plastic soil groups (SW and SP) are prominent while SC group occurs in SPT holes closer to small tanks (Villu).
Since the shell of the earth-dams is generally constructed using clay-poor, and sand-rich well-graded soils, SED_D (Fig. 5f) is characteristics with low PI (generally >7) and relatively low LL (mostly >25).
4.1.4. Natural Moisture Content (NMC)
When classifying cohesive soils and assessing their engineering properties, moisture content (or water content) measurements, both in the natural state and under defined test conditions, could offer us extremely useful information. Figure 6a shows the variation of natural moisture content of studied soils (except for Co_D). Marshy soils represent the highest NMC out of all soils studied since they contain clay-rich soil groups mostly confined to water-saturated conditions. However, soils in the earth dams located in the dry zone usually consist of well-compacted soils. Since the void spaces are minimal resulting in the lowest moisture content of those soils. Vanapalli (1996) pointed out that the electrostatic force within the soils is increasing with decreasing water content which leads to the soil particles being packed closer. Hence the soil itself becomes more compact and strong.
4.1.5. Liquidity Index (LI)
The liquidity index (LI) provides a quantitative measure of the current state of soils. The softness of saturated clay can be expressed numerically by the liquidity index. Values of LI greater ≥ 1 are indicative of liquefaction or “quick” potential. In other words, the soil structure may be converted into a viscous fluid when disturbed or remolded by pile driving, caisson drilling, or helical screw foundation installation.
The highest LI is represented by My_W where most of the soil behaves plastic to the liquid state (Fig. 6b). However, Re_W and Al_W soils behave differently from above with plastic to semisolid.-state. The SED_D and Al-W are represented mostly by negative LI values, indicating semi-solid or solid behaviour (Fig. 6b). Since the moisture content lacks in the data set from the soils in the coastal-dry zone, LI was not calculated.
4.1.6. Compression Index (Cc)
The consolidation settlement of a structure founded on a normally consolidated soil can be calculated from the knowledge of the compression index (Robinson and Allam 2003). It has been postulated that the determination of Cc has many practical significances, especially during the planning stage of a construction project, since it permits computations of approximate settlements of structures founded on particular soils.
Since the well-controlled primary compaction in SED_D is high, it represents the lowest compression index. As it leads to less porosity due to artificial compaction, those soils would contain lower moisture content and result in decreased Cc. When the moisture content is incasing, simultaneously the compressibility of the soil is also increased up to optimum moisture content. Re_W represents a wide range of Cc (Fig. 6c) which could be due to those soils derived from various rock types. For example, soils derived from hornblende-biotite gneiss, Cc range from 0.043 to 0.162. However, soil derived from undifferentiated charnockitic gneiss and garnet-biotite gneiss, Cc ranges from 0.124 to 0.270 and from 0.170 to 0.536 respectively. For soils derived from marble Cc range from 0.043 to 0.484 (Fig. 6c).
The highest Cc values of plastic soils can be encounter in My_W where OH associates the highest (0.36) while SC has the lowest (0.07). Usually, highly organic soils are characterized by a high compression index (Ying and Michael, 2011). Therefore, in most instances, organic soil groups such as OH, OL, and Pt/CL have represented relatively high Cc values. Peat and organic soils are the toughest foundation soils to be worked with, that exhibit unusual compression behaviour having high compressibility with a significant secondary compression stage (Cola and Cartellazo, 1999). However, MH-like inorganic soils also tend to have high Cc values as they have high LL in such weathering environments.
Al_W also shows a relatively low compression index after SED-W due to low moisture content. Dealing with the plastic soil of Al_D, Cc values are relatively high than Al_W due to high LL and relatively high moisture content (see Fig. 6a). Plastic soil types of Co_D also show low Cc and could be placed after the SED_D and Al_W. Since data of only five plastic soil samples were analyzed, the reliability of results in the coastal-dry zone may reduce (all other data were obtained relevant to the non-plastic soils in this environment).
4.1.7. Activity of Soils
According to the activity and relative classification of soils (Seed and Lundgren, 1964), all studied soils other than some soils in Re_W and SED_D show inactive clay types (activity <0.75). The highest range of activity values can be obtained in Re_W (Fig. 6d). The soils derived from garnet-biotite gneiss represent higher activity but those from the hornblende biotite gneiss show lower values. Soils formed over marble exhibit a wide range of activities that vary from 0.12 – 1.34. As a result, soil can be classified as inactive to normal clay in Re_W. At the same time, the soil in SED_D can also be classified as inactive to normal clay. In a recent study, Dias and Seneviratne, (2010) show cracking intensity of earth dams is significantly correlated with clay percentage and PI, so that the activity plays a major role.
4.1.8. Swell Potential of soils
The swelling potential is influenced by many factors. Some of which are indigenous to the clay body. The others that are related to its weathering environment and other physical conditions, which include clay mineral composition, amount of non-clay material, density, void ratio, size, the orientation of clay particles, cementation, macrostructure, size, and thickness of the clay body, and depth below the ground surface (Olive et al., 1989). The swelling of soils is often characterized by a high liquid limit and plasticity index with a variable content of more active swelling clay minerals (Youssef et al., 1957; Popesco, 1980, Adhikar et al. 2006). Figure 7 shows a variation of the swell potential of studied soils.
In the top 6m Re_W (Fig. 7a), a large number of samples were plotted on low potential expansiveness zone other than the CL and SC, which are shown under medium swell potential (medium expansiveness). Out of 80% of SC samples with medium Swell potential in Re_W have been derived from garnet-biotite gneiss. Soils developed over marble and hornblende-biotite gneiss are frequently represented by low swell potential. At the same time, CL derived from undifferentiated charnockitic gneiss also shows medium swell potential. Therefore, in Re_W, the swell potential of soil groups is directly correlated with the lithology.
Upper 5m of My_W exhibits medium to high swell potential. CH always showed high swell potential while OL, OH, and SM also showed high swell potential at some locations (Fig. 7c). Jones and Holtz, (1973) showed the volume changes in clay, because of variations in moisture content, occur within about 30 ft of the ground surface. However, most changes that cause engineering problems take place at depths of less than 10 ft (Hamilton, 1963; Gromko, 1974). My-W is mostly saturated throughout the year since water logging capability and availability of water; the shrink-swell behaviour is very limited. Boreholes in marshy (144 boreholes) indicated that the unsaturation zone only encountered from surface level to 1.50 depths in very few locations. Therefore, it will be very important to pay more attention to the swell potential of the upper 1.50m of My-W where could force geotechnical problems within this depth zone.
Al_W (Fig. 7b), Co_D (Fig. 7e), and soils in SED_D (Fig. 4f) indicate low swell potential could be a result of the relatively low clay fraction. The presence of silt, sand and other non-clay materials reduce the swelling potential in proportion to their amount. The non-clay materials are dilutants that in effect reduce the clay-mineral content per unit volume and hence reduce swelling potential (Komornik and David, 1969).
CL with medium expansiveness distributes within the first 6.00m depth in Al_D soils (Fig. 7d). Olive et al. (1989) show, maximum volume change for a clay body is directly proportional to the size of the body. However, even thick clay bodies composed of highly expandable clay minerals will have no swelling potential if the weight of the overburden is sufficient to counter swelling pressures. Therefore, SC and SM with which encountered within 8.50m it could not behave as expansive soil although those soils were classified as medium expansiveness according to Van Der Merwe’s method.
Expansive soil can be identified by several methods. According to the Unified Soil Classification System (USCS) the studied soil is classified as an inorganic fat clay (CH) and/or elastic silt (MH), organic clay (OH) (Fig. 2) with high plasticity, which is an indication of its expansive nature, since most expansive soils are often clayey (Lew, 2010). In Figure 7 some of the experimental data of My_W and Re_D are found to be around the "A-line" and right of the vertical line crossing LL=50% which is an indication of expansive soils.
4.3. Empirical Formula Derived for Calculating Plasticity Index of Marshy Soils
Out of studied soils, plastic soils of marshy soils in the wet zone represented a better linear relationship between liquid limit and plasticity index. Therefore, the linear regression method was provided to base the development of an empirical formula to calculate the plasticity index of soils in tropical marshy soils (Fig. 8). As a result, no need of measuring plastic limit determination to plasticity index. At the same time, as the liquid limit is known and derived equation could calculate plasticity index, plastic limit also could be obtained using general formula. The derived formula is,
PI% = -1.91 + (0.46 * LL %)
PI – Plasticity index
LL – Liquid limit
Therefore, PL can be determined by the traditional equation,
PI % = LL% - PL %
At present most of the geotechnical laboratories throughout the world are determined the plastic limit of soils according to ASTM Standards. It specifies the value of plastic limit as the moisture content of rolled soil thread at 3.2 mm diameter begins to crumble. The reliability of test results must depend on the skill of the operator and various mechanical factors. In practice, test results of plastic limit have a high variation. Therefore, obtained PI by on empirical formula and based on it finding PL is very easier and saves time during soil investigations. Therefore, the formula obtained by liner recreation analysis is helpful to future geotechnical investigations in marshy. The reason for such a strong linear relationship between LL Vs PI may be a higher fine-grain fraction of My_W.
4.4. Standard Penetration Test (SPT) Data and Strength properties of soils
The Standard Penetration Test (SPT) is a common “in-situ” testing method used to determine the geotechnical engineering properties of subsurface soils and is currently the most popular and economical means to obtain subsurface information. SPT-N values of deferent soil profiles were analyzed in three depth zones, 0.00-6.00m, 6.00-12.00m, and 12.00-16.00m (Supplementary Fig. 6a to f). The Unconfined Compression test is used to measure the shearing resistance of cohesive soils (Oyediran and Durojaiye, 2011). Friction angle (Ø0), relative density (%), and competency were calculated using methods after Meyehof (1956) while consistency and approximate Unconfined Compressive strength were determined according to the method after Arvind and Dhananjaya, (2003). SPT-N value ranges and predicted competency, consistency, and approximate unconfined compressive strength, friction angle, and relative density of Re_W, Al_W, My_W, Al_D, Co_D, and SED_D respectively are given (Figs. 9a to 9f and Supplementary Tables 1 to 6). The highest SPT-N values of 0.00 -6.00m were obtained within the SED_D soils which may be due to artificially induced well-compacted nature. Since natural moisture content is also very low, these soils generally fall into hard consistency. Therefore, higher SPT values can be associated with soil groups such as SC (34-44), SM (30-36), GM (>50), and GW (>50) (Supplementary Fig. 6f). Competency, consistency, and approximate unconfined compressive strength, friction angle, and relative density of SED_D soils are higher than all other soils (Supplementary Table 1). Sandy soils with plastic properties show the widest SPT-N ranges in Re_W when compared with the others.
In addition, Al_D also represents a high average SPT-N value within the fine-grain soil groups, although those soils contained relatively high moisture content (Supplementary Fig. 6d). Since river Koill Aru flows on quaternary limestone terrain, it is possible to dissolve and precipitate a significant amount of calcium carbonate. It could cause some form of cementation within the subsoil which resulted in high SPT. The highest SPT –N values for ML (28-48) were recorded out of all studied soils in Al_D soils within this depth zone. However, fine soil groups such as CH (5), CL (8), and ML (17-21) (Supplementary Fig. 6a) in Re_W show low SPT-N values. Moreover, sandy soil groups such as SP (>50), SW (>50), and SM-SC (36) in Re_W show high average SPT-N values, which may be due to the residual soils been developed by “in-situ” weathering. Therefore, those soils are generally compacted than other naturally transported soils. Re_W soils derived from the hornblende biotite gneiss show relatively high SPT-N values (from 14->50) compared to the soils derived from garnet-biotite gneiss (from 11->50), undifferentiated charnockitic gneiss (from 3->50), and marble (from 3-47) in that order.
The lowest SPT-N values were observed within the top 5m in My_W soils, where SPT-N values vary from 1 - 44 (e.g. CL (1-18), CH (2-3), OH (1-17), Pt/CL (1-4)). The highest SPT-N values were observed in SW (3-31) and SP (1-35) (Fig. 9c). The “N” values are ranging from 1 to 28 in fine-grain soil groups. Soils encountered in marshy areas contain higher fine-grain fractions and high moisture content. Therefore, most of the soils are behaved as plastic to liquefied state according to LI values (Fig. 6b). The lowest competency and consistency of all soil groups varies from very loose to medium dense and from very soft to very stiff or hard respectively while lower approximate unconfined compressive strength, friction angle, and relative density are associated within My_W (Supplementary Table 2).
Plastic soils encountered within the upper 6.00m of Al_W are represented by low SPT-N values (eg. CL-ML (2), ML (2-5), and SM (6-12)) and compared with the Al_D soils having SPT- N value ranges (ML=2, SM=6, SM-SC=18) of (Supplementary Fig. 6b). At the same time are SPT ranges also narrow. It may be due to the poorly cemented or loose nature of these soils.
The upper 3.00m of Co_D, SPT-N values were ranging from 4 to 34. SW represents the highest “N” values (N=34) while SC with lowest “N” value (N=4) within the SW (Supplementary Fig. 6e). The interesting observation is although the coastal soils represent very low “N” values, the “N” values of SP and SW within the top few meters are very high compared to other soils. Based on resulted “N” values, competence and consistency of fine-grain soil vary from loose to hard and from firm to hard respectively. Since coastal soils have been derived by wave action those soils are uncemented and poorly compacted. Therefore, often low SPT-N values are associated with those soils. However, the SC soil group shows high SPT values with the mean strength of the coastal soils are increased when fine fraction soil percent is increased. It is a characteristic feature for Co_D as well, where sand grains are bonded and cemented together by a clay matrix.
SPT-N values within 6.00m -12.00 and 12.00m – 16.00m were obtained only for Al_W, Al_D, and SED_D soils. Although low SPT-N values were obtained within the top 6m in Al_W, it was changed from 14 to 33 at 6.00m – 12.00 depth zone and further increased from 29 to >50 at 12.00m – 15.00m depth zone. The “N” values of sandy soil groups such as SM, SM-SC, and SP are varied within a wider range in Al_W soils compared to other soils.
Soils in Al_D, SPT-N values were ranged from 18 to >50 at depth zone 6.00m – 12.00 while values were increased from 33 to >50 at 12.00m – 15.00m depth zone. It could be a result of high cementation by CaCO3 and well compaction when going deeper. As shown in Figure. 5.15d, the highest “N” value at 6.00m – 12.00m depth zone was obtained within SW (42-50). Depth zone 12.00m – 16.00m highest “N” value (N>50) recorded within SW, SM, and CL while lowest (44->50) observed within SP. It was clearly observed that the average “N” value of the same soil group increased with increasing depth in AL_D soils as observed as Al_W.
Ranges of SPT-N values in SED_D soils at 6.00-12.00m and 12.00-16.00m are concentrated toward the highest order SPT values of the graph (Supplementary Fig. 6f). SW-SC showed a relatively high “N” value in all three depth zone. However, SM show relatively low average “N” values in the 6.00m – 12.00m depth zone than the upper 6.00m. It could be due to the presence of a groundwater table at this depth zone. Therefore, soils can become wet and swell which could result in a relative density of 65-80 range.
4.5 Overview of the study
Field geotechnical research needs data from various sources and therefore, it is a challengeable and tough task that needs significant input from consulting firms, government departments, and individual technical personnel. One of the key problems faced by the researcher is how to collect very expensive and sometimes classified geotechnical data. It is a common consensus that extracting geotechnical data from numerous construction projects in many parts of the world is difficult and needs to overcome legal and ethical issues and constraints. Moreover, the major concern however is the consistency of available data since various geotechnical investigations are focusing on different objects. For instance, geotechnical investigation of road construction (e.g. Song et al., 2003) may differ from the investigations carried out on the bridge and multi-story building sites (e.g. Handa et al., 1984). In road construction, much attention pays to the upper part of the soil sections, whereas for bridge construction, depth to bedrock or lower stratum of the soil sections is excessively investigated. On the other hand, hydrogeological and mining activities are rendered with different datasets which will be generated through different techniques. Therefore, it is much more a tough task to focus on existing geotechnical data collection from different construction projects. The present study however endeavors to overcome some of these problems and to achieve a satisfactory result from existing geotechnical data.
At the same time, statistical analysis of soil properties encountered many difficulties; the first of them being the poor quality of geotechnical tests and their results (Moussouteguy et al. 2002). It is therefore important to properly categorized, catalogued, and assess the data in order to maintain the quality. Thus, it will be possible to validate any statistical output results by testing various limitations including stability, fussiness, and awkwardness associated with when sampling more or less “reliable” data set. However, geotechnical prospecting will remain indispensable. A better knowledge of the subsurface provides a better guide; for instance, with a more reliable estimate of requested depth to reach the sufficiently bearable substratum, or layers of good characteristics (Breysse et al., 2006).
Several important factors were observed in this study. One is a soil classification mechanism applicable to borehole logging. During borehole logging, soils are immediately classified in the field, based on general observations and individual loggers’ experience and senses of soils. Such human intervention and time constraints may lead to confusion. We observed soils with approximately the same plasticity and grain size distributions been classified under different names in the log sheets. On the contrary, sometimes, soils with completely different plasticity and grain size distribution may be classified under the same name. Such output leads people who refer to these log sheets to get ambiguous information on soils which will have real difficulty when interpreting. Therefore, soil groups in the log sheets should be assigned according to a reference standard after completion of the laboratory tests such as sieve analysis and soil consistency limits. Then any professional engineer or geologist who lives in any part of the world could infer soil properties confidently with more clarity as soils have been classified with a standard method.
Other is the distribution of geotechnical properties in residual soils. Most of the geotechnical engineers and engineering geologists presume residual soils usually cause fewer geotechnical problems compared to the transported soils. However, since geotechnical properties are directly correlated with the parent material on which the soils were formed, and weathering phenomena based on topography causing different results. If the terrain is consists of complex geology with the distribution of different rock types, the respective geotechnical properties may also vary. Therefore, proper investigation of soil properties is an essential prerequisite even within the residual soils before any construction work is commissioned.
The third one is a factor based on the genetic distribution of soils under different climatic regimes. The soils in the wet zone have a large number of soil groups compared to the dry zone leads to a wide variation of plasticity and gradation. Therefore, during soil investigation, due concerns should be given to the soils developed in the wet zone compared to the dry zone.