1 Introduction

Classifying soil is a way to arrange it into groups or subgroups to describe its characteristics concisely (Das 2013) (Das and Sobhan 2013; Das 2013). It is essential to clarify the soil classes before designing and constructing any project as the engineering characteristics of soil (stiffness, permeability, and strength) are influenced by the soil particles’ shape, size, arrangement and microscopic structure (Budhu 2015).

Generally, soils are classified into (fine-grained) or (granular or coarse-grained) soils depending on the distributions of particles of the same size. Fine soils are determined by the percentage of the soil mass passing through a 0.075 mm sieve, while granular soils are the soil mass that retained in a 0.075 mm sieve, including sand, gravel, cobbles, and boulders. If the percentage of fine soil passes through the sieve at a predefined proportion, usually 50% (but this could be less according to the soil classification system used), the soil is considered as Fine-grained. Fine-grained soils are furthermore classified into clay or silt using a hydrometer test. Finally, soils are subclassified according to their consistency (Reale et al. 2018).

There are many soil classification systems used by engineers, and they mostly use the same criteria for classification, such as the distribution of particles and plasticity (Das and Sobhan 2013). However, the two main systems used by engineers are the unified system and the AASHTO system, and they are both almost similar in using simple index properties like grain-size and Atterberg limits (Das and Sobhan 2013; ASTM 2000).

Sundry studies have conducted regarding the geotechnical properties of soil in different Iraqi regions. Al-Baghdadi (2016) prepared a set of maps for An-Najaf city using the (SURFER 11) software to produce a contour line for different geotechnical properties of the soil (Al-Baghdadi 2016). Ali and Fakhraldin (2016) investigated and analysed the physical and chemical soil properties of five selected locations for An-Najaf city (Ali and Fakhraldin 2016). Al-Shakerchy and Al-Khuzaie (2011) introduced geotechnical maps of the Iraqi governorates of Baghdad, Diyala, Wasit, and Babylon using the (SURFER 7) software. Al-Maliki et al. (2018) produced a GIS map for the soil allowable bearing capacity of AN-Najaf city at depths 0–2 m (Al-Maliki et al. 2018). Al-Mamoori and his colleagues conducted studies for different geotechnical soil properties to build a geodatabase for the city of AN-Najaf, which will be helpful in the preliminary design stage (Al-Mamoori 2017; Al-Mamoori et al. 2018, 2019). Geographic information systems (GIS) are widely used for spatial data handling and manipulation. A geotechnical assessment usually requires a large amount of spatial data. It is a robust and useful tool for analyzing large quantities of data for geotechnical assessments and the undertaking of similar analyses on very large areas in a short period of time. A paramount feature of the GIS is its capability to create new data by combining current varied data that share a compatible spatial referencing system (Dai et al. 2001).

This paper is part of a series of research papers aiming to create an extensive geodatabase for soil chemical and physical properties for part of the Najaf governorate using GIS. The objective of this paper is to produce the geotechnical maps for the unified soil classification system of the study area and assess the geotechnical suitability of the foundations of residential areas. A GIS (ArcMap 10.5) software was used. For determining the geotechnical properties of the study area, data from 464 boreholes were used.

2 Study Area Description

An-Najaf city is a double city (An-Najaf and Kufa) and is considered the capital of An-Najaf province, which is one of the eighteen provinces of Iraq. The city is situated 161 km to the southwest of the Iraqi capital, Baghdad on the edge of Mesopotamia (Tigris and Euphrates flood plain) in the east of the city, and of the southern desert (Western Plateau) in the west, and the ground slopes gently toward the flood plain (Al-Mamoori et al. 2019).

An-Najaf and Kufa city are situated between 44° 17′ 00″ and 44° 25′ 0″ East and 32° 7′ 0″ and 31° 56′ 0″ latitudes North (Fig. 1). This area is considered one of the most continuously developing urban areas, and it currently covers an area of approximately 105.1 km2. Each neighborhood in the selected study area has been given a corresponding number, as displayed in Table 1.

Fig. 1
figure 1

Study area location

Full size image
Table 1 Neighborhood numbering.
Full size table

The climate of An-Najaf city is characterized as an arid and semi-arid, with long hot and dry summers with an average temperature of about 45 °C, and short winters with an average temperature of 24 °C. The rainy season runs from October to April. The average gross annual rainfall is about 100 mm in a wet year, and about 30 mm in a dry year (Mail et al. 2016; Beg and Al-Sulttani 2020).

For soil characteristics of the study area, the internal friction angle Ø of An-Najaf soil varies between 26.3 and 41.2 in most of the region (Ali and Fakhraldin 2016). The bearing capacity ranges between 5 and 20 Ton/m2 in this region (Al-Maliki et al. 2018). While the percentage of sulfate content ranges between 0.36 and 14% for soil and varies between 84 and 239% in groundwater (Al-Mamoori et al. 2018). The gypsum content ranges between 10 and 25%, values that are considered very high (Al-Mamoori 2017). The liquid limit (LL) and plastic limit (PL) vary from 21 to 29% and 11 to 15%, respectively. The low values of LL and PL for the soil in western locations increases towards the eastern locations. The maximum dry density and optimum moisture content vary from 17 to 19 KN/m3 and 8 to 14%, respectively (Ali and Fakhraldin 2016).

Geologically, the study area is covered by different deposits. The oldest is the Dibdiba formation (Pliocene–Pleistocene), which is exposed in a small area in the Tar An-Najaf, west of study area. The lithological component of the Dibdiba is sandstone. Ill-sorted, fine-coarse grained small pebbles often reported with a thickness of about 10 m (Barwary and Slewa 1995). The lower contact of the Dibdiba formation is with the Injana Formation (Upper Miocene). The thickness of the Injana ranges from 20 to 35 m, and it is composed mainly of red, partly greenish silty, sandy calcareous clay stone and lenticels of grey, brownish, greenish and yellowish sandstone, and thin beds (0.30 m.) of marly and chalky limestone are occasionally present in the sequence (Buday 1980; Barwary and Slewa 1994). The Dibdiba formation is non-uniformly covered by Gypcrete (Pleistocene–Holocene), which is found in most of the study area to a thickness of (0.5–2) m of secondary gypsum in a powdery form or fibrous prismatic, hard well-crystallized form, and as brownish spongy form (Al-Mubarak and Amin 1983). The Holocene deposits are Flood plain and Anthropogenic deposits, and these are found in a small area in the east and south of study area. Flood Plain deposits consist of a loam which is a mixture of clayey silt deposits from the Euphrates river to a thickness of up to 15 m (Jassim and Goff 2006). Anthropogenic deposits are mainly composed of the bodies of ancient irrigation canals and hillocks of ancient settlements (Barwary and Slewa 1994) (Fig. 2).

Fig. 2
figure 2

Source: After (Barwary and Slewa 1994; Barwary and Slewa 1995)

Geological deposits formation in the study area

Full size image

3 Materials and Methods

The study draws on data from 464 boreholes “(Appendix)”, with 13 soil tests for each borehole starting at a depth of 0–2 m and increasing to 24–26 m. Two approaches have been utilized to calculate the SPT-N-value. The first approach involved collecting the geotechnical data, and the second data set arranged by using Excel to make it familiar with the ArcGIS 10.5 environment. The coordinates of the spatial boreholes are designated by using the GPS device. The geotechnical maps were created using the ArcGIS 10.5 software, (Fig. 3).

Fig. 3
figure 3

Flowchart of the work

Full size image

3.1 Materials

The study data obtained from the reports of the National Center for Construction Laboratories & Researches (NCCLR)/Babylon laboratory, which is a branch of the National Center for Construction Laboratories & Research (NCCLR). NCCLR is a branch of the Iraqi Construction and Housing Ministry. Since its establishment in 1977, the laboratory (NCCLR) has been performing soil tests for the Euphrates river basin area (known as the Middle Euphrates region) besides testing construction materials (NCCLR 2016). The data used was collected from 464 boreholes spread throughout An-Najaf and Kufa cities at depths of 0–26 m. Borehole locations are presented in (Fig. 4). The data contain the sieve analysis for boreholes and the plastic and liquid limits among many other soil properties.

Fig. 4
figure 4

Borehole locations

Full size image

3.2 Methods

3.2.1 USCS Classification

The Unified Soil Classification System is first proposed by Casagrande in 1942 and developed in 1952 by the Army Corps of Engineers (Das and Sobhan 2013). It is widely used in many building codes and books (Reale et al. 2018; Robertson 2016). The soil in this classification system is divided into two master divisions: coarse soil (gravel and sand) and fine soil (clay and silt). If the retained soil in a No. 200 sieve is more than 50%, then the soil is coarse but, if the soil passes through a No. 200 sieve, then the soil is fine (Reese et al. 2006). The soil is then further classified by several subdivisions, as shown in Table 2 (Das 2013).

Table 2 Unified soil classification system classes.
Full size table

3.2.2 GIS Mapping

A geographic information system (GIS) is a set of rules and tasks for data analysis and processing using a computer. It is used to link information to its geographical location according to the coordinates, to arrange data into layers and then to transform it into maps for the selected area and thus show the geographic or other attributes of that area. As each borehole has its spatial data and geotechnical data, this data has been arranged and horizontally tabulated in the Excel software in a way that is convenient for the ArcGIS 10.5 environment. The interpolation is an estimation of a value within two known values in a sequence of values; in other words, it is a procedure used to predict the values of cells at specific locations that have missing sample data (Childs 2004).

The best approach to soil mapping is by using interpolation techniques, and there are many methods of interpolation. For numerical soil data, for example, the best method for interpolation is Ordinary Kriging (OK) (Bhunia et al. 2018; Zandi et al. 2011), and this method has been used for the interpolation of Fine and Coarse percentages for each depth while for the USCS soil classes, in our case, the classes of USCS are categorical data (nominal), the Indicator Kriging (IK) method has been used because it is considered as the best interpolation methods for categorical (nominal) data (Mendes and Lorandi 2006; Liu et al. 2012). All the interpolated maps have produced with cell size (pixel) 20 m.

4 Results and Discussion

This study is the first of its kind in Iraq to apply the Unified Soil Classification System to the soil of the study area to produce geotechnical maps for soil classes and soil types using the ArcGIS software. The data used are from 464 boreholes for depths of up to 26 m. Geotechnical maps for soil classes and soil types produced, as seen in (Figs. 5, 6, and 7):

Fig. 5
figure 5

Geotechnical maps for (USCS), coarse and fine soils percentage for depths (0-10) m

Full size image
Fig. 6
figure 6

Geotechnical maps for (USCS), coarse and fine soils percentage for depths (10-20) m

Full size image
Fig. 7
figure 7

Geotechnical maps for (USCS), coarse and fine soils percentage for depths (20-26) m

Full size image

The results maps show the followings (Figs. 5, 6, and 7):

  1. a.

    Coarse soils: the classes present are (SP, SP-SM, SM), distributed as shown in the study area, which lacks the classes (Gravels: GW, GP, GM, GC) or (SW, SC), which indicate that the soil is poorly graded silty sands. The percentage for gravels was less than 15%, so it was not considered.

  2. b.

    Fine soils: the present classes are (OH, OL, CH, CL, ML), distributed as shown in the study area, that lacks the classes (MH, PT), which indicate that the soil is silty, clay, or mixed organic soils with low or high plasticity.

  3. c.

    SP soil class distribution is combined with the distribution of SP-SM class almost on all depths. Also, it is noticed, that the distribution area of SP and SP-SM shrinks with depth to the north and east and small area in the middle.

  4. d.

    SM class is dominant in the study area in all depths and its area increases with depth.

  5. e.

    ML and CL classes occupy spotted small areas in the middle, east and south and spread with depth to the north of the study area.

  6. f.

    OL and OH classes mostly are diapered in the first three depths levels (0–6) m, but they have a considerable area with depth. They cover a small area in the southern part at depth (6–8) m and expand with depth in the middle, west and north of the study area.

The Trend linear line and R-square for soil class was drawn and calculated to illustrate the change in the class percentage with depth as follows Table 3, (Fig. 8):

Table 3 Percentage of soil classes with depths
Full size table
Fig. 8
figure 8

Linear trend of soil classes percentage with depth

Full size image
  1. a.

    Silty Sands (SM): This class comprises the greater percentage of the soil for all depths. Its percentage was 62% at 2 m, and 52% at 26 m. Its percentage is nearly constant with depth (Fig. 8e), which is why its R2 is approximately 0.00009.

  2. b.

    Poorly graded sands and silty sand (SP-SM): this soil class occupies the second rank, with a percentage of 39.6% up to a depth of 16 m, after which its values reduce to 6.6%. The (R2) between the percentage and the depth was 0.826, and the correlation relationship is a strong inverse correlation (see Fig. 8c).

  3. c.

    Poorly Graded Sands (SP): this class is the third large percentage (62%) in the soil from 0 to 16 m depth. After 16 m, its values begin to reduce with the depth until it reaches 0%. The (R2) between the percentage and the depth was 0.78, and the correlation relationship is a strong inverse correlation (see Fig. 8a).

  4. d.

    Silts of Low Plasticity (ML): this class of soil, which describes fine soils, is the fourth rank in percentage until 16 m in depth. After 16 m in-depth, this class comprises the second-largest soil percentage, as its values increase with depth until reaching 20%. The (R2) between the percentage and the depth was 0.76, and the correlation relationship is a strong extrusive correlation (see Fig. 8g).

  5. e.

    The clay of Low Plasticity (CL) and Clay of High Plasticity (CH): these classes are present in small percentages for depths of 0–16 m, after increasing depth their values start to increase. The (R2) between the percentage and the depth for CL and CH was 0.68 and 0.88, respectively. The correlation relationship was a medium extrusive correlation for CL, and a strong extrusive correlation for CH (see Fig. 8b, d).

  6. f.

    Organic Silt, Clay of High Plasticity (OH) and Organic Silt, Clay of Low Plasticity (OL): these classes of fine soil were present in the study area at a very small percentage (OH = 0.3% and OL = 0%) until a depth of 16 m. After this depth, their percentages increase to reach (OL = 2.5 & OL = 12.9). The (R2) between the percentage and the depth was 0.19 for OL, and 0.57 for OL. See (Fig. 8f, h).

In Fig. 9, each class has drawn against its percentage in two depths ranges: first, from 0 to 16 m and, second, from 16 to 26 m. This is done to analysis the change in the soil types before and after the 16 m depth. The figure show that the coarse soil classes (SP, SP-SM) decrease with a constant percentage of SM class, while the fine soil classes (OL, CH, ML) increase. The soil after 16 m depth becomes a mixed soil of sand, clay, high-elastic clay, and organic matter.

Fig. 9
figure 9

Changes in the percentage of soil types before and after the depth of 16 m

Full size image

Figure 10 indicates that the coarse soil (Sand) percentage was very high in the upper depths level, where it was 95% at 2 m. These percentages decrease gradually with depth, and this change in the soil became obvious after 16 m as the coarse soil percentage became 71% at 18 m and reached 64% at 26 m, while the fine soil is opposite as in coarse soil, its percentage increases with depth. It can be noticed that the coarse soil percentage drops while fine soil percentage increases at about 18 m depth, and this depth could be the contact between Dibdiba and Injana formations.

Fig. 10
figure 10

Changes in soil content percentage (Sand and Fine) with depth

Full size image

Geotechnical engineers have created charts based on experience to help designers in selecting the appropriate soil for a particular construction. These charts results are listed in Table 4. The table is used only as a guide and for making a preliminary assessment of the soil suitability for specific use (Budhu 2015). After applying the Unified Soil Classification System, the soil is evaluated depending on Table 4. In the depths between 0 and 16 m, coarse soil is dominant, with an 85–95% percentage. The coarse soil classes present are (SM, SP, and SP-SM). The fine soil percentage was about 5–15%, so when the soil for these depths is compacted and saturated, it will have a permeability of previous to semi- previous, good shearing strength, low to very low compressibility and acceptable workability as a construction material. At depths of between 16 and 26 m, the percentage of fine soil classes increases to 40%, with 60% coarse classes, and this will result in remarkable changes in soil characteristics as the permeability becomes semi-pervious to impervious, fair shearing strength, medium compressibility and fair workability as a construction material.

Table 4 Engineering use chart.
Full size table

5 Conclusions

  1. a.

    This study used the GIS software to produce geotechnical maps, which will help to prepare a database for the city and can be utilised for primary designs.

  2. b.

    Indicator Kriging gives significant interpolated categorical (nominal) data maps for soil USCS classes.

  3. c.

    The results of geotechnical maps of soil classification show that the coarse soil classes occupy most of the study area in all depths, while the fine soil appears with depth especially after the depth 6 m and in the south, middle and north of study area.

  4. d.

    The final geotechnical maps are very easy to use and help save money and time. They also provide a useful database for the city.

  5. e.

    The soil of An-Najaf city for depths of 0–16 m consists of the classes SP, SM, SP-SM at a percentage of 85%. Subsequently, when compacted, this soil has a permeability of pervious to semi-pervious, good shearing strength, low to very low compressibility and acceptable workability as a construction material.

  6. f.

    At depths of 16–26 m, the percentage of fine soil classes increases to 40%, with 60% coarse classes, and this will result in remarkable changes in soil characteristics as the permeability became semi-pervious to impervious, fair shearing strength, medium compressibility and fair workability as a construction material.