Digital maps of mechanical geotechnical parameters using GIS

Abstract

Geographical Information System (GIS) is a powerful tool for representing huge data and producing an actual visualization of subsurface information and parameters in the form of 3D scenes that can be used by the geotechnical engineers in the design of footing and foundation. This paper focuses on producing digital geotechnical maps for the main geotechnical parameters that can be used in the preliminary design stage. Considerable data of 164 borehole logs presenting a 17,000 km² (i.e. Wasit province, south of Baghdad, Iraq) are collected, analyzed, tabulated in an excel sheet, and used as input data to create the digital maps. The studied parameters are bearing capacity, shear strength, coefficient of consolidation, compressibility parameters, and groundwater levels. The results show that the GIS technique is a great tool to visualize the geotechnical parameters that can be easily used directly in the assessment of the site investigation reports and even in the foundation design. The digital values of the bearing capacities, shear strength, and compressibility parameters are clearly visualized and accurately replicate the soil layers of the study area. However, other geotechnical parameters are needed to further consider it in more digital maps.

Keywords:

• GIS
• bearing capacity
• compressibility
• shear strength
• water table

PUBLIC INTEREST STATEMENT

Geographical Information System (GIS) is a powerful tool for representing huge data and producing an actual visualization of subsurface information and parameters in the form of 3D scenes that can be used by the geotechnical engineers in the design of footing and foundation. This paper focuses on producing digital geotechnical maps for the main geotechnical parameters that can be used in the preliminary design stage. Considerable data of 164 borehole logs presenting a 17,000 km² (i.e. Wasit province, south of Baghdad, Iraq) are collected, analyzed, tabulated in an excel sheet, and used as input data to create the digital maps. The studied parameters are bearing capacity, shear strength, compressibility parameters, and groundwater levels. The results show that the GIS technique is a great tool to visualize the geotechnical parameters that can be used in the assessment of the site investigation reports. The preliminary assessment of the site investigation report can be accomplished for any project based on the digital maps.

1. Introduction

The soil site investigation is one of the main important steps before the construction of infrastructures. It includes a collection of disturbed and undisturbed specimens at different depth levels under the ground surface and many geotechnical tests are performed to these specimens to determine different parameters that are widely and commonly used by a geotechnical designer to select proper footing and foundation design.

In geotechnical practice, the traditional procedure for data collection in situ can be a laborious job. Existing historical data sources in the form of hard, electronic and paper copy, such as maps, site investigation reports, manuals and even photos which can be integrated with Less time may be spent using GIS digital mapping platform as a tool to improve the efficiency and effectiveness (Player, 2006).

Geological and geographical engineers produced a new technique to collect, store, manage, retrieve, visualize, and analyze all types of site investigation data. Digital maps and other graphic information can be displayed using the GIS for analyzing, presenting, and producing the right vision for the designer.

This type of technique was used widely around the world for the last two decades. In Faisalabad, the second-largest in the eastern province of Punjab, 200 km south of Pakistan capital, Islamabad, the GIS technique is proved by investigating the allowable bearing capacity and the foundation information simply regarding the foundation types for different structures (Kamal et al., 2016). In Toshka city, new valley governorate, south of Egypt, the expansive soil and the swelling characteristics of the clays for the soil strata have been considered and different digital GIS maps were created (Labib & Nashed, 2013).

Data of 464 boreholes are collected and tabulated using an excel sheet and the GIS software is used to investigate the allowable bearing capacity of Al-Najaf and Al-Kufa city, southwest of Baghdad, Iraq (Al-Maliki et al., 2018). Geo-hazard warning system including the rainfall prediction is modeled and tested using the functions of the GIS system (Al-Maliki et al., 2018).

The hazard warning system is implemented using GIS technology to determine the warning dissemination due to disaster and risk assessment is also evaluated (Ghosh et al., 2015). The functionality is to be modular in architecture having GIS-graphical user interface (GUI), input, understanding, rainfall prediction, expert, output, and warning modules (Bhattacharya et al., 2014). The variability of the quality and depth of the groundwater in Delhi City is investigated using the GIS technique (Gupta & Sarma, 2016). A digital terrain map is prepared and analyzed in the north of Thailand that was integrated from different data of existing maps (Liengsakul et al., 1993). Many other studies are implemented to produce digital maps for different soil properties in the south of Iraq (i.e. Kadhim & Al-Abody, 2015; Al-Baghdadi, 2016; Camera et al., 2017 & Al-Shukriji & Al-Khuzaie, 2011). Hellawell et al. (2001) concluded that the GIS-enabled creation and visualization of site investigation data and search procedures quickly became the tool of choice. Subsequently, this gives opportunities for analysing data and enhancing the engineers’ capabilities of the project.

The GIS is used for the preparation of a terrain mapping unit (TMU) map which integrates data from existing maps and data interpreted from satellite images.

However, utilizing big data and dealing with a large area has never been done to cover all the geotechnical characteristics of soil (i.e. the physical and mechanical properties). Such a large amount of data will give greater accuracy to the engineers at the preliminary design stage to select the proper foundation for the project. Such a digital map will help the geotechnical engineers to get an indication and obtain significant information about the soil layers and decide the kind of footing in preliminary studies and even in feasibility studies.

In this paper, extensive site investigation data results of tens of boreholes (i.e. 146 boreholes) are collected, classified, and analyzed. These data represented around 17,000 km² (i.e. from the north of Wasit governorate to the south; and from the east to the west) and covered depth is approximately 12 m under the ground level. These data were collected from many directories of different ministries in this area and most of the site investigations and reports are done at Al-Kut construction laboratory and college of engineering geotechnical laboratories by known consultants and geotechnical engineers.

Using ArcGIS (10.5) environment facilities, a digital database was made for the physical and mechanical soil properties for the whole investigated area. The used technique here in this paper (i.e. 3D GIS mapping software) can be used later to cover all soil properties in the south of Iraq, which helped the engineers in re-cyclization, treatment, and analysis easily which subsequently makes the designing and planning of any engineering project easier (National Center for Construction Laboratories & Research [NCCLR], 2016 & Al-Maliki et al., 2018).

2. The study area

The Wasit governorate is located in southeast of the Baghdad, Capital of the republic of Iraq (about 180 km) and it has an international border with Islamic republic of Iran (see Figure 1). It has also local borders with five governorates (i.e. Diyala, Babil, Al-Qadisiya, Dhi Qar, and Maisan).

Plain Sedimentary soil layers are predominate geological formation except for north-east of governorate (i.e. Badrah City, 60 km) which is aligned the borderline with Iran and which are considered mountainous terrain. It has an area of approximately (17,000) km² which represents (4) % of Iraq’s’ total area (437,072 km²). The governorate includes 16 districts and collected data of the soil investigations are the outputs of tens of boreholes at different depths.

This paper included producing a digital map for different physical and mechanical properties of soil layers representing all the area of the governorate which is mathematically located between the coordinate (44°30ʹE,31°45ʹN) (lower-left corner) and (46°45ʹE,33°30ʹN)(upper right corner) (see Figure 2). The Tigris River passes through the center of the governorate and divides the governorate into two parts from the north of the province to its south.

Figure 1. Location of Wasit governorate (Shubber, 2009).

3. Methodology

The procedure and the methodology was followed in this paper by collecting huge data and results of site investigation (i.e. bearing capacity, settlement, and soil strength parameters of soil strata) over a wide range of area. Then, these data are used as input data to create digital maps using 3D GIS mapping software.

3.1. The GIS software platform

GIS is an abbreviation for the Geographic Information System which is a framework for data collection, managing, and analyzing. As results of fast development of engineering technologies, the modern sciences of geography are merged with engineering and produced new hybrid technique (i.e. GIS) to integrate many types of data. It is also used in analyzing different locations and organizing soil layer information and visualize these information using digital maps and 3D scenes. With this unique facility, deeper insights into soil strata data can be revealed using GIS, such as patterns of soil formation, mechanical relationships, and situations helping the decision-makers (i.e. geotechnical engineers and designers) to take the right decision.

3.2. The collected data

The used data in this paper were collected, classified, and analyzed before utilizing it as input data into the GIS environment. The information in this paper represents the data collected from (146) boreholes covering all the study area and the range of the depth is (0–10) meters. The Whole data that were used in this paper are used under the authorization from the school buildings department in the province of Wasit, ministry of water resources, directorate of municipalities of Wasit. Whereas the soil investigation reports are used with permission from the laboratory of Al-Kut construction and Andrea laboratories. Table 1 shows the re-arranged data with all the physical and mechanical properties at the desired depth of the different sites.

Table 1. The collected data of 164 borehole logs

Long	Lat	year	month	B.H.	Depth (m)	Sample type	BC (T/m^2)	LL	PL	PI	ɣ (kN/m^3)	W	Gs	C (kPa)	$\phi$ (deg.)	e˳	Pc (kPa)	Cc	Cr	Swelling	TSS	CI	OM	PH	WT	PHH
44.794	32.963	2014	1	3	1.5–2.0	US	6	0	0	0	14.4	26.5	2.69	28	0	0	0	0	0	0	6.74	1.23	7.72		0
44.782	32.911	2013	11	3	1.5–2.0		7.5	0	0	0	21.2	0	0	0	0	0.608	110	0.121	0.014	0	0	0	0		0
45.608	32.520	2013	12	3	1.5–2.0		3.5	35	23	12	19.2	23.1	0	0	0	0.642	68	0.155	0.02	0	0	0	0		0.7
46.048	32.171	2014	3	3	1.5–2.0	US	5	42	27	15	14.3	28.7	2.89	0	0	0.789	80	0.14	0.022	0	8.37	1.38	8.81		0.3
45.610	32.480	2013	10	3	1.5–2.0	US	5.5	0	0	0	14.5	27.2	2.7	0	0	0.796	90	0.21	0.032	9	0	0	0		1
45.279	32.678	2013	10	3	1.5–2.0	US	9	47	23	24	15.6	19.7	2.69	0	0	0.703	95	0.19	0.036	9	0	0	0		1.85
46.039	32.179	2014	1	3	1.5–2.0		5.5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		0
45.165	32.746	2013	11	3	1.5–2.0	DS	8.5	36	18	18	15.1	23.4	2.71	0	0	0.631	105	0.18	0.029	6	0	0	0		1.55
46.070	32.456	2014	1	3	1.5–2.0		4.5	0	0	0	20.5	26.21	0	0	0	0.682	87	0.19	0.023	0	0	0	0		0.8
45.421	32.546	2014	7	3	1.5–2.0	US	6	0	0	0	15.3	21.2	2.69	0	0	0.738	120	0.13	0.02	0	7.43	0.09	6.51		1.5
46.000	33.150	2014	2	3	1.5–2.0	US	8	40	23	17	15.2	21.9	2.69	44	5.6	0.692	105	0.15	0.021	0	0	0	0		1.4
46.043	33.167	2014	2	3	1.5–2.0	US	15	0	0	0	15.8	22.1	2.7	0	0	0.628	115	0.15	0.021	0	0	0	0		1.85
45.280	32.518	2014	1	3	1.5–2.0		5.5	0	0	0	21.2	27.81	0	0	0	0.531	155	0.158	0.019	0	0	0	0		1.5
46.225	32.402	2013	12	3	1.5–2.0		6	41	25	16	19.64	0	2.78	0	0	0.653	140	0.154	0.024	0	0	0	0		1.5
44.974	32.698	2014	1	3	1.5–2.0	US	7.5	0	0	0	14.7	23.9	2.69	0	0	0.809	75	0.19	0.025	4	8.81	1.93	8.47	7.9	1.1	7.9
44.781	32.937	2014	1	3	1.5–2.0		4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		1
45.157	32.776	2014	1	3	1.5–2.0		4.5	0	0	0	0	28.78	0	0	0	0	0	0	0	0	0	0	0		0.7
45.059	32.913	2013	10	3	1.5–2.0		7	53	24	29	0	0	0	0	0	0	0	0	0	0	0	0	0		1
45.806	31.881	2014	1	3	1.5–2.0	US	8.5	0	0	0	15.4	25.7	2.71	0	0	0.752	90	0.18	0.028	0	0	0	0		1.1
44.793	33.036	2014	4	3	1.5–2.0	US	5.5	0	0	0	14.9	25.3	2.69	46	3	0.708	105	0.16	0.018	7	3.71	1.14	8.77	8.1	0.55	8.1
44.785	33.039	2013	10	3	1.5–2.0		7.5	33	0	0	0	22.77	0	0	0	0	0	0	0	0	0	0	0	7.25	0.6	7.25
45.927	33.102	2014	1	3	1.5–2.0	US	10.5	40	19	21	16	19.7	2.7	0	0	0.695	120	0.15	0.028	0	0	0	0		7.6
45.867	32.961	2014	2	3	1.5–2.0		5.5	0	0	0	20.7	25.2	0	0	0	0.654	130	0.135	0.021	0	0	0	0	7.39	1.4	7.39
46.448	32.527	2014	2	3	1.5–2.0	US	7	38	26	12	14.6	23.2	2.69	0	0	0.739	80	0.17	0.024	6	0	0	0		1.1
45.428	32.503	2014	4	3	1.5–2.0	DS	7	37	26	11	0	23.3	0	0	0	0	0	0	0	0	0	0	0		0.9
45.493	32.302	2013	10	3	1.5–2.0	US	8	0	0	0	14.6	26.1	2.7	0	0	0.701	120	0.2	0.032	0	0	0	0		2
45.821	32.504	2013	9	3	1.5–2.0	US	5.5	48	32	16	14	29.3	2.69	0	0	0	0	0	0	0	0	0	0		2.05
46.298	32.783	2013	10	3	1.5–2.0	US	6.5	0	0	0	15	20.9	2.69	0	0	0.729	90	0.18	0.028	7	0	0	0		0.45
45.851	32.540	2013	11	3	1.5–2.0	US	4.5	0	0	0	13.7	28.2	2.68	16	0	0.932	95	0.19	0.028	0	6.11	1.58	8.92	7.9	1.6	7.9
45.845	32.566	2013	3	3	1.5–2.0	US	6	0	0	0	14	28.8	2.7	0	0	0.809	80	0.15	0.026	4	0	0	0		1.5
45.861	32.482	2013	11	3	1.5–2.0	US	8	48	23	25	15.1	21.9	2.71	0	0	0.692	100	0.19	0.028	6	0	0	0		1
45.834	32.503	2014	4	3	1.5–2.0	US	5	0	0	0	14	27.3	2.69	0	0	0.776	90	0.16	0.023	4	0	0	0		0.8
45.821	32.525	2014	2	3	1.5–2.0		5.5	0	0	0	19.9	29.73	0	0	0	0.796	100	0.15	0.037	0	0	0	0	7.41	1.4	7.41
45.816	32.530	2014	1	3	1.5–2.0		5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		1
45.818	32.522	2014	4	3	1.5–2.0	DS	7	46	30	16	0	0	0	0	0	0	0	0	0	0	0	0	0		0.5
45.913	32.487	2014	1	3	1.5–2.0		4	0	0	0	22.1	21.95	0	0	0	0.563	84	0.104	0.013	0	0	0	0	7.72	1.1	7.72
45.832	32.530	2007	7	3	1.5–2.0		5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		1.65
45.831	32.503	2007	7	3	1.5–2.0		4.8	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		1.75
45.811	32.474	2007	7	3	1.5–2.0		5.5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		1.7
45.843	32.511	2007	7	3	1.5–2.0		4.4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		1.5
45.851	32.489	2007	7	3	1.5–2.0		5.1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		1.75
45.807	32.522	2007	7	3	1.5–2.0		5.3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		2
45.868	32.501	2007	7	3	1.5–2.0		4.2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		2.2
45.819	32.477	2007	7	3	1.5–2.0		4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		1.6
45.833	32.502	2007	7	3	1.5–2.0		5.7	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		1.7
45.828	32.549	2007	7	3	1.5–2.0		7	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		2
45.852	32.485	2007	7	3	1.5–2.0		6	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		1.9
45.884	32.471	2007	7	3	1.5–2.0		4.75	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		1.6
45.995	32.237	2013	10	3	1.5–2.0	US	6	0	0	0	14.6	24.7	2.7	0	0	0.756	95	0.19	0.029	6	0	0	0		0.9
45.873	32.438	2014	1	3	1.5–2.0	US	10	34	19	15	15.5	24.8	2.69	0	0	0.748	90	0.14	0.025	4	0	0	0		1.2
46.067	32.637	2014	2	3	1.5–2.0	DS	5.5	38	26	12	0	26.7	0	0	0	0	0	0	0	0	0	0	0		1
45.914	32.632	2014	2	3	1.5–2.0	US	4.5	43	29	14	0	31.5	2.71	21	0	0.911	70	0.26	0.024	3	0	0	0		0.5
44.800	32.909	2014	6	3	1.5–2.0		4	0	0	0	20.3	26.34	0	0	0	0.704	100	0.18	0.028	0	0	0	0		1.5
45.829	32.538	2014	2	3	1.5–2.0	DS	6	0	0	0	0	28.3	0	0	0	0	0	0	0	0	0	0	0		0.2
45.370	32.689	2014	4	3	1.5–2.0	US	7.5	0	0	0	15.4	28.3	2.71	0	0	0.673	100	0.19	0.024	7	6.75	1.24	7.71	8.2	1.05	8.2
45.093	32.839	2013	10	3	1.5–2.0	US	8.5	0	0	0	15.2	24.3	0	45	3	0	0	0	0	0	0	0	0		1.45
44.791	32.912	2013	9	3	1.5–2.0	US	5	34	19	15	13.5	29.6	2.68	0	0	0.963	80	0.26	0.023	0	0	0	0		1.1
44.792	32.962	2014	1	1	1.5–2.0	US	6	0	0	0	14	27.6	2.77	28	0	0.864	75	0.24	0.031	8	0	0	0	0	0	0
44.780	32.909	2013	11	1	1.5–2.0		7.5	0	0	0	0	0	0	0	0	0.653	0	0.09	0.011	0	0	0	0	0	0	0
45.606	32.519	2013	12	1	1.5–2.0		3.5	40	25	15	18.7	32.95	0	0	0	0.938	0	0.223	0.019	0	0	0	0	0	1.7	0
46.046	32.169	2014	3	1	1.5–2.0	US	5	45	30	15	14.1	28.8	0	27	0	0.815	75	0.21	0.038	9	0	0	0	0	1.3	0
45.609	32.479	2013	10	1	1.5–2.0	DS	5.5	0	0	0	14.4	26.3	2.7	34	2	0.812	90	0.2	0.029	6	6.71	1.38	7.8	8.1	1	8.1
45.278	32.677	2013	10	1	1.5–2.0	US	9	0	0	0	15.3	21.6	2.7	48	3	0.734	90	0.19	0.034	8	0	0	0	0	1.85	0
46.038	32.178	2014	1	1	1.5–2.0		5.5	38	25	13	0	27.24	0	0	0	0.806	100	0.185	0.017	0	0	0	0	0	0.9	0
45.164	32.744	2013	11	1	1.5–2.0	US	8.5	0	0	0	14.4	23.6	2.7	0	0	0.765	90	0.21	0.032	8	0	0	0	0	1.6	0
46.068	32.455	2014	1	1	1.5–2.0		4.5	47	28	19	0	26.64	0	0	0	0.719	105	0.212	0.024	0	0	0	0	0	0.8	0
45.419	32.544	2014	7	1	1.5–2.0	US	6	47	30	17	14.8	0	2.71	0	0	0.819	110	0.25	0.022	6	0	0	0	0	1.55	0
45.999	33.149	2014	2	1	1.5–2.0	US	8	0	0	0	15.7	21.7	2.71	48	4.5	0.676	105	0.29	0.031	6	8.43	1.76	6.92	8	1.5	8
46.041	33.165	2014	2	1	1.5–2.0	DS	15	41	28	13	0	14.3	0	0	0	0	0	0	0	0	7.61	1.19	7.48	8	1.8	8
45.279	32.516	2014	1	1	1.5–2.0		5.5	0	0	0	0	24.31	0	0	0	0.684	130	0.168	0.011	0	0	0	0	0	1.5	0
46.224	32.401	2013	12	1	1.5–2.0		6	36	21	15	19.1	27.45	2.74	0	0	0.736	170	0.208	0.025	0	7	0	0	6.98	1.6	6.98
44.972	32.696	2014	1	1	1.5–2.0	US	7.5	0	0	0	14.6	24.8	2.68	0	0	0.821	75	0.15	0.021	0	0	0	0	0	1.1	0
44.780	32.935	2014	1	1	1.5–2.0		4	47	24	23	0	0	2.74	0	0	0.808	90	0.166	0.021	0	0	0	0	6.54	1	6.54
45.156	32.774	2014	1	1	1.5–2.0		4.5	0	0	0	0	25.91	0	0	0	0	0	0	0	0	0	0	0	0	0.7	0
45.057	32.911	2013	10	1	1.5–2.0	DS	7	52	28	24	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.9	0
45.765	32.152	2014	1	1	1.5–2.0	US	8.5	37	20	17	15.2	26.1	2.69	0	0	0.776	85	0.14	0.024	4	0	0	0	0	1.3	0
44.792	33.035	2014	4	1	1.5–2.0	US	5.5	0	0	0	14.2	27.3	2.7	0	0	0.753	115	0.26	0.027	8	0	0	0	0	0.5	0
44.784	33.038	2013	10	1	1.5–2.0		7.5	33	0	0	0	0	0	0	0	0.501	80	0.15	0.019	0	0	0	0	6.77	0.6	6.77
45.925	33.100	2014	1	1	1.5–2.0	US	10.5	0	0	0	15.6	21.7	0	62	4	0.721	115	0.16	0.026	6	0	0	0	0	7.8	0
45.865	32.960	2014	2	1	1.5–2.0		5.5	0	0	0	19.8	26.84	0	0	0	0.765	65	0.169	0.025	0	0	0	0	7.79	1.4	7.79
46.447	32.525	2014	2	1	1.5–2.0	US	7	42	29	13	14.9	23	2.7	0	0	0.783	85	0.21	0.024	7	0	0	0	0	0.9	0
45.427	32.502	2014	4	1	1.5–2.0	US	7	48	31	17	14.5	28.7	2.7	0	0	0.728	90	0.26	0.029	4	9.71	1.63	6.09	7.5	0.9	7.5
45.491	32.301	2013	10	1	1.5–2.0	US	8	0	0	0	14.9	23	2.7	41	3	0.735	110	0.19	0.028	8	7.42	1.47	9.43	8	1.9	8
45.820	32.503	2013	9	1	1.5–2.0	US	5.5	0	0	0	14.3	27.6	0	38	0	0.809	95	0.22	0.028	4	7.96	1.94	8.32	7.9	1.9	7.9
46.296	32.782	2013	10	1	1.5–2.0	US	6.5	0	0	0	14.7	24.9	2.69	0	0	0.809	80	0.16	0.021	0	8.81	1.76	8.43	7.9	0.45	7.9
45.849	32.539	2013	11	1	1.5–2.0	US	4.5	0	0	0	14.1	26.4	0	24	0	0.845	90	0.19	0.028	5	0	0	0	0	1.5	0
45.844	32.565	2013	3	1	1.5–2.0	US	6	45	29	16	15	24.4	2.59	56	4	0.732	100	0.16	0.026	5	8.72	1.49	7.42	7.8	1.2	7.8
45.860	32.481	2013	11	1	1.5–2.0	US	8	41	23	18	14.8	21.5	2.7	46	2.5	0.706	95	0.17	0.028	7	7.88	1.26	7.17	7.8	1	7.8
45.833	32.502	2014	4	1	1.5–2.0		5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.8	0
45.819	32.524	2014	2	1	1.5–2.0		5.5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1.4	0
45.815	32.529	2014	1	1	1.5–2.0		5	0	0	0	20.9	0	0	0	0	0.625	95	0.149	0.023	0	0	0	0	0	1	0
45.816	32.521	2014	4	1	1.5–2.0		7	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.5	0
45.911	32.486	2014	1	1	1.5–2.0		4	30	25	5	20.6	24.76	0	0	0	0.654	83	0.12	0.014	0	0	0	0	7.77	1.1	7.77
45.831	32.529	2007	7	1	1.5–2.0		5	34	24	10	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1.65	0
45.829	32.502	2007	7	1	1.5–2.0		4.8	57	30	27	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1.75	0
45.810	32.473	2007	7	1	1.5–2.0		5.5	56	31	25	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1.7	0
45.841	32.510	2007	7	1	1.5–2.0		4.4	57	30	27	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1.5	0
45.850	32.488	2007	7	1	1.5–2.0		5.1	55	30	25	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1.75	0
45.805	32.521	2007	7	1	1.5–2.0		5.3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0
45.866	32.499	2007	7	1	1.5–2.0		4.2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2.2	0
45.817	32.475	2007	7	1	1.5–2.0		4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1.6	0
45.831	32.501	2007	7	1	1.5–2.0		5.7	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1.7	0
45.826	32.548	2007	7	1	1.5–2.0		7	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0
45.851	32.484	2007	7	1	1.5–2.0		6	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1.9	0
45.883	32.469	2007	7	1	1.5–2.0		4.75	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1.6	0
45.993	32.235	2013	10	1	1.5–2.0	US	6	0	0	0	14.6	22.8	2.7	0	0	0	0	0	0	0	7.81	1.19	8.18	7.6	0.85	7.6
45.871	32.437	2014	1	1	1.5–2.0	US	10	35	19	16	15.3	25.7	2.7	58	3.5	0.789	85	0.15	0.021	4	0	0	0	0	0.95	0
46.066	32.636	2014	2	1	1.5–2.0	US	5.5	0	0	0	14.2	27.1	2.69	0	0	0.722	95	0.18	0.025	7	0	0	0	0	1	0
45.912	32.631	2014	2	1	1.5–2.0	US	4.5	0	0	0	14.2	29.2	2.69	0	0	0.826	75	0.24	0.029	4	0	0	0	0	0.5	0
44.799	32.908	2014	6	1	1.5–2.0		4	53	28	25	0	18.32	2.75	0	0	0	0	0	0	0	0	0	0	0	1.5	0
45.828	32.537	2014	2	1	1.5–2.0		6	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.2	0
45.368	32.688	2014	4	1	1.5–2.0	DS	7.5	52	30	22	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.9	0
45.092	32.837	2013	10	1	1.5–2.0	US	8.5	0	0	0	14.7	24.9	2.69	47	3	0	0	0	0	0	6.42	1.84	9.31	7.7	1.9	7.7
44.789	32.911	2013	9	1	1.5–2.0	DS	5	0	0	0	13.9	29.2	2.7	0	0	0.781	90	0.32	0.029	7	7.12	1.46	7.54	7.6	0.9	7.6
45.767	32.153	2014	1	3	1.5–2.0	US	8.5	0	0	0	15.4	25.7	2.71	0	0	0.752	90	0.18	0.028	0	0	0	0		1.1
46.048	32.171	2014	3	3	1.5–2.0	US	5	42	27	15	14.3	28.7	2.89	0	0	0.789	80	0.14	0.022	0	8.37	1.38	8.81		0.3
46.039	32.179	2014	1	3	1.5–2.0		5.5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		0
45.995	32.237	2013	10	3	1.5–2.0	US	6	0	0	0	14.6	24.7	2.7	0	0	0.756	95	0.19	0.029	6	0	0	0		0.9
46.046	32.169	2014	3	1	1.5–2.0	US	5	45	30	15	14.1	28.8	0	27	0	0.815	75	0.21	0.038	9	0	0	0	0	1.3	0
46.038	32.178	2014	1	1	1.5–2.0		5.5	38	25	13	0	27.24	0	0	0	0.806	100	0.185	0.017	0	0	0	0	0	0.9	0
45.765	32.152	2014	1	1	1.5–2.0	US	8.5	37	20	17	15.2	26.1	2.69	0	0	0.776	85	0.14	0.024	4	0	0	0	0	1.3	0
45.993	32.235	2013	10	1	1.5–2.0	US	6	0	0	0	14.6	22.8	2.7	0	0	0	0	0	0	0	7.81	1.19	8.18	7.6	0.85	7.6
45.767	32.153	2014	1	3	1.5–2.0	US	8.5	0	0	0	15.4	25.7	2.71	0	0	0.752	90	0.18	0.028	0	0	0	0		1.1
45.776	31.815	2014	1	3	1.5–2.0	US	8.5	0	0	0	15.4	25.7	2.71	0	0	0.752	90	0.18	0.028	0	0	0	0		1.1
45.776	31.815	2014	1	3	1.5–2.0	US	8.5	0	0	0	15.4	25.7	2.71	0	0	0.752	90	0.18	0.028	0	0	0	0		1.1
46.056	31.833	2014	3	3	1.5–2.0	US	5	42	27	15	14.3	28.7	2.89	0	0	0.789	80	0.14	0.022	0	8.37	1.38	8.81		0.3
46.056	31.833	2014	3	3	1.5–2.0	US	5	42	27	15	14.3	28.7	2.89	0	0	0.789	80	0.14	0.022	0	8.37	1.38	8.81		0.3
46.054	31.831	2014	3	1	1.5–2.0	US	5	45	30	15	14.1	28.8	0	27	0	0.815	75	0.21	0.038	9	0	0	0	0	1.3	0
46.047	31.841	2014	1	3	1.5–2.0		5.5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		0
46.045	31.840	2014	1	1	1.5–2.0		5.5	38	25	13	0	27.24	0	0	0	0.806	100	0.185	0.017	0	0	0	0	0	0.9	0
46.047	31.841	2014	1	3	1.5–2.0		5.5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		0
45.774	31.814	2014	1	1	1.5–2.0	US	8.5	37	20	17	15.2	26.1	2.69	0	0	0.776	85	0.14	0.024	4	0	0	0	0	1.3	0
46.045	31.840	2014	1	1	1.5–2.0		5.5	38	25	13	0	27.24	0	0	0	0.806	100	0.185	0.017	0	0	0	0	0	0.9	0
45.774	31.814	2014	1	1	1.5–2.0	US	8.5	37	20	17	15.2	26.1	2.69	0	0	0.776	85	0.14	0.024	4	0	0	0	0	1.3	0
46.054	31.831	2014	3	1	1.5–2.0	US	5	45	30	15	14.1	28.8	0	27	0	0.815	75	0.21	0.038	9	0	0	0	0	1.3	0
45.828	33.540	2014	2	3	1.5–2.0	US	15	0	0	0	15.8	22.1	2.7	0	0	0.628	115	0.15	0.021	0	0	0	0		1.85
45.826	33.539	2014	2	1	1.5–2.0	DS	15	41	28	13	0	14.3	0	0	0	0	0	0	0	0	7.61	1.19	7.48	8	1.8	8
45.712	33.475	2014	1	3	1.5–2.0	US	10.5	40	19	21	16	19.7	2.7	0	0	0.695	120	0.15	0.028	0	0	0	0		7.6
45.711	33.474	2014	1	1	1.5–2.0	US	10.5	0	0	0	15.6	21.7	0	62	4	0.721	115	0.16	0.026	6	0	0	0	0	7.8	0
45.786	33.524	2014	2	3	1.5–2.0	US	8	40	23	17	15.2	21.9	2.69	44	5.6	0.692	105	0.15	0.021	0	0	0	0		1.4
45.784	33.523	2014	2	1	1.5–2.0	US	8	0	0	0	15.7	21.7	2.71	48	4.5	0.676	105	0.29	0.031	6	8.43	1.76	6.92	8	1.5	8
45.650	33.333	2014	2	1	1.5–2.0		5.5	0	0	0	19.8	26.84	0	0	0	0.765	65	0.169	0.025	0	0	0	0	7.79	1.4	7.79
45.652	33.335	2014	2	3	1.5–2.0		5.5	0	0	0	20.7	25.2	0	0	0	0.654	130	0.135	0.021	0	0	0	0	7.39	1.4	7.39
44.485	32.919	2013	11	3	1.5–2.0		7.5	0	0	0	21.2	0	0	0	0	0.608	110	0.121	0.014	0	0	0	0		0
44.488	33.047	2013	10	3	1.5–2.0		7.5	33	0	0	0	22.77	0	0	0	0	0	0	0	0	0	0	0	7.25	0.6	7.25
44.484	32.944	2014	1	3	1.5–2.0		4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0		1
44.483	32.917	2013	11	1	1.5–2.0		7.5	0	0	0	0	0	0	0	0	0.653	0	0.09	0.011	0	0	0	0	0	0	0
44.497	32.971	2014	1	3	1.5–2.0	US	6	0	0	0	14.4	26.5	2.69	28	0	0	0	0	0	0	6.74	1.23	7.72		0
44.495	32.970	2014	1	1	1.5–2.0	US	6	0	0	0	14	27.6	2.77	28	0	0.864	75	0.24	0.031	8	0	0	0	0	0	0
44.486	33.045	2013	10	1	1.5–2.0		7.5	33	0	0	0	0	0	0	0	0.501	80	0.15	0.019	0	0	0	0	6.77	0.6	6.77
44.503	32.917	2014	6	3	1.5–2.0		4	0	0	0	20.3	26.34	0	0	0	0.704	100	0.18	0.028	0	0	0	0		1.5
44.492	32.918	2013	9	1	1.5–2.0	DS	5	0	0	0	13.9	29.2	2.7	0	0	0.781	90	0.32	0.029	7	7.12	1.46	7.54	7.6	0.9	7.6
44.482	32.943	2014	1	1	1.5–2.0		4	47	24	23	0	0	2.74	0	0	0.808	90	0.166	0.021	0	0	0	0	6.54	1	6.54
44.494	32.920	2013	9	3	1.5–2.0	US	5	34	19	15	13.5	29.6	2.68	0	0	0.963	80	0.26	0.023	0	0	0	0		1.1
44.496	33.044	2014	4	3	1.5–2.0	US	5.5	0	0	0	14.9	25.3	2.69	46	3	0.708	105	0.16	0.018	7	3.71	1.14	8.77	8.1	0.55	8.1
44.502	32.915	2014	6	1	1.5–2.0		4	53	28	25	0	18.32	2.75	0	0	0	0	0	0	0	0	0	0	0	1.5	0
44.494	33.043	2014	4	1	1.5–2.0	US	5.5	0	0	0	14.2	27.3	2.7	0	0	0.753	115	0.26	0.027	8	0	0	0	0	0.5	0
45.630	32.033	2014	1	1	1.5–2.0	US	8.5	37	20	17	15.2	26.1	2.69	0	0	0.776	85	0.14	0.024	4	0	0	0	0	1.3	0
45.357	32.183	2013	10	3	1.5–2.0	US	8	0	0	0	14.6	26.1	2.7	0	0	0.701	120	0.2	0.032	0	0	0	0		2
45.631	32.034	2014	1	3	1.5–2.0	US	8.5	0	0	0	15.4	25.7	2.71	0	0	0.752	90	0.18	0.028	0	0	0	0		1.1
45.630	32.033	2014	1	1	1.5–2.0	US	8.5	37	20	17	15.2	26.1	2.69	0	0	0.776	85	0.14	0.024	4	0	0	0	0	1.3	0
45.631	32.034	2014	1	3	1.5–2.0	US	8.5	0	0	0	15.4	25.7	2.71	0	0	0.752	90	0.18	0.028	0	0	0	0		1.1
45.356	32.182	2013	10	1	1.5–2.0	US	8	0	0	0	14.9	23	2.7	41	3	0.735	110	0.19	0.028	8	7.42	1.47	9.43	8	1.9	8
45.114	32.406	2014	1	3	1.5–2.0		5.5	0	0	0	21.2	27.81	0	0	0	0.531	155	0.158	0.019	0	0	0	0		1.5
44.895	32.624	2014	1	3	1.5–2.0	US	7.5	0	0	0	14.7	23.9	2.69	0	0	0.809	75	0.19	0.025	4	8.81	1.93	8.47	7.9	1.1	7.9
44.893	32.622	2014	1	1	1.5–2.0	US	7.5	0	0	0	14.6	24.8	2.68	0	0	0.821	75	0.15	0.021	0	0	0	0	0	1.1	0
46.690	32.544	2014	2	3	1.5–2.0	US	7	38	26	12	14.6	23.2	2.69	0	0	0.739	80	0.17	0.024	6	0	0	0		1.1

4. The analyzed parameters

The main important geotechnical parameters that have to be considered by any geotechnical engineers and the designer are tabulated, analyzed, and prepared in an excel sheet and then used as an input into the GIS environment. The bearing capacity for soil strata for the whole study area is the main parameter which is used directly in the selection decision of the type of the footing and foundation and even in the preliminary assessment for the soil layers. Furthermore, it is intuitive for an engineer in the design requirements of the foundation for any project to investigate the bearing resistance of the soil strata to ensure that no bearing failure for the structure in the future may occur.

Other assessments should be considered during the design of the foundation related to the settlement limits of the structure; thus, the settlement parameters (i.e. consolidation index, C_c, and rebound index, C_r, as well as the consolidation coefficient, C_v) are digitally presented.

Another geotechnical parameter that is widely used by geotechnical engineers is to assess the designed footing and how the shear resistance of the soil strata resists the expected load from the structure to prevent shear failure. These parameters are the soil shear parameters (i.e. cohesion, c, and the angle of internal friction,$\phi$).

The water level in the borehole is measured during the site investigation (24 h) after the drilling process. These data (i.e. water table level, WT) were derived from the collected data and the explanatory digital map for this parameter is achieved as well. The next section will explain the results in detail for all the geotechnical maps produced in this paper.

5. The results and discussion

This section focuses on the explanation of the obtained results that are explained briefly above.

5.1. Bearing capacity

The bearing capacity data in Table 1 are used to produce a digital geotechnical map. Figure 2 shows the distribution of the bearing capacity, BC, from the north to the south and from the east to the west.

It can be seen from the figure that the minimum bearing capacity (30–50 kPa, 3–5 T/m²) is located at the center of the province (i.e. Al-Kut City), west of the center and just the center and around of Al-Sweera city at the north-west. This is not surprising because the weak to moderate stiff silty sandy soil is the predominant formation in this region. On the other hand, it is clearly shown that the north-east of the province (i.e. close to the Iranian borders) has stiff to very stiff soil layer characteristics and the bearing capacity ranges between (110–150 kPa, 11–15 T/m²). The geological formation of this region is mostly mountain rocky soil strata (close to the Zagros mountains between Iraq and Iran) and its elevation about 95 m above the sea level.

Figure 2. Distribution of the bearing capacity; (a) rainbow view and (b) contours.

5.2. Compressibility (consolidation) parameters

The compressibility parameters include the consolidation parameter or coefficient of consolidation, C_v, in m²/year; Compression index, C_c, and rebound (swelling) index, C_r.

5.2.1. Coefficient of consolidation, Cv

The coefficient of consolidation is very important for geotechnical engineers in the calculations of the final settlement’s time and even the settlement to assess the limit of consolidation at each time (the degree of consolidation). The measured coefficients of the values of consolidation from all the obtained samples from borehole logs (i.e. whole the study area) are tabulated in an excel sheet and used as input data in the GIS software. Figure 3 explains the ranges of the coefficient of consolidation for whole the study area.

Figure 3. Coefficient of consolidation distribution, Cv.

It is clearly shown from the Figure 3 that the moderate value of the measured coefficient of consolidation (i.e. 0.7–1.2 m²/year) is the dominant values (i.e. more than 80% of the studied area). However, only west of Al-Kut district and east of Al-Sweera district have very low values (i.e. less than 0.3 m²/year). Moreover, the center of Al-Dejeela and Al-Numaniya townships has very high values of coefficient of consolidation (i.e. more than 1.5 m²/year).

5.2.2. Compression index, Cc, and rebound index, Cr

Compression index and swelling index are the characteristics of the soil settlement under loads. Basically, in consolidation experiments (i.e. the results of the one-dimensional compression test), the value of the swelling index ranges between 0.1 and 0.2 times the compression index (Das & Sivakugan, 2016). The elastic and plastic strain can be seen easily from the smooth consolidation curve and the version compression line. The obtained values of the parameters from the collected data reflect this behavior and small values of the swelling index rely on the plastic strain and showed that the soil does not suffer from high swelling characteristics though the soil is fine-grained silty-clayey soil.

Figure 4a and b show the geotechnical map for both the compression index and swelling index.

Figure 4. Compression index and selling index digital map.

Clearly, it is noticeable from Figure 4(a,b) that the changing in both the minimum values has a similar trend (i.e. minimum values for both parameter concentrated in west Al-Kut district and Al-Azeziya district and around), whereas the maximum values concentrated north of Al-Kut district for the compression index and south of Al-Azeziya district for swelling index. The moderate values for both parameters are predominant for most of the study area (i.e. green color). This means that the characteristics of the log-stress relationships have smooth compression (loading) curve with the small plastic strain (re-loading).

5.3. Shear strength characteristics

The soil can resist the shear stress governed from the applied load from the structures. The shear strength parameters of any soil are terms that refer to this resistance. The friction between particle interlocks is described by the angle of internal friction ($\phi$) whereas the bonding or the cementation characteristic is described by the cohesion (c). The strength of any soil decreases when shear strain and expansion or contraction may occur (i.e. increasing or decreasing of soil density, respectively) due to applied loads. Once the shear stress and the density trend to be constant during increasing of the shear strain, the shear strength will decrease and this case called critical or residual state. The shear strength parameters are commonly used by the different common equation in the design of foundation particularly in the empirical equations.

Many methods can be followed to determine the shear strength parameters, triaxial test, and direct shear torsional direct shear test (Thermann et al., 2006). The simplest method to calculate the shear strength parameters is by performing the direct shear test. The collected and used shear strength parameters as input data in the GIS software in this paper are determined from the direct shear test methods.

Figure 5 shows the digital geotechnical map for the distributed values of shear strength parameters for Wasit province. From Figure 4(a), it should be noticed that the determined values of the cohesion parameter (i.e. c) are predominantly small values (ranged between 0 and 16 kPa) and this gave an indication that the soil layers of the studied area are sandy silty soil with few very fine grain particles (clay). This is not surprising as the bearing capacities as described above are low values. In contrast, high values of cohesion parameters are noticed in the north of the province particularly at Badra district and around.

The angle of internal friction is measured as a peak state (${\phi }_{\mathrm{p}}$). It can be seen from Figure 4(b) that the angle of friction values is small for the whole studied area and this refers to the fact that the geological formation for the soil layers of the province is predominantly sandy silty soil with few cementation action for few clayey soil.

Figure 5. Shear strength parameters; (a) cohesion, c, and (b) angle of friction, $\phi$.

5.4. Water table level

Once the soil layer is found under the water level, it will obviously be fully saturated. The water table is the upper level of the water in the soil layer for the saturated zone. As described earlier in this paper, the water level is measured from the borehole (24 h) after the end of the drilling process to permit the water to be at a static state due to suction and filtration from the walls of the borehole. These measurements have been taken at different seasonal times during the year.

Figure 6 shows the groundwater level as a geotechnical map for Wasit province. It can be seen that the measured water table level has shallow depth under the ground surface (not exceeding 1.5 m) for most of the study area. In contrast, only the north of the study area (Badra, Zurbatiya) and the north-east Iranian borders are going to be deeper (i.e. up to 8 m for Badra district center). Actually, this is intuitive because the elevation of this region increases and reaches to 95 m at some places due to geological formation and close to the Zagros Mountains.

Figure 6. Water level geotechnical map for Wasit province.

6. Conclusions

This paper focuses on producing digital geotechnical maps for main important geotechnical properties that are commonly used by geotechnical engineers in footing and foundation design. The main conclusion can be summarized as follows:

1. GIS is an effective tool that can be used by engineers to assess preliminary geotechnical site exploration. The obtained information concerned with the main geotechnical properties and parameters of 164 boreholes are collected, analyzed, and used as input data utilizing the GIS environment to produce significant many geotechnical maps.

2. The accomplished digital geotechnical maps for the bearing capacity, compressibility characteristics, and shear strength parameters can be used by the designer as a visual display powerful tool at the preliminary design stage simply by using the digital values of these parameters for the proposed region and appropriate decision can be taken.

3. Preliminary Assessment of the site investigation report can be accomplished for any project based on the digital maps. The considerable advantages of using these techniques are low cost, the ease of data using and quick update of data, and the ability to produce the right , care should be taken preceding the footing design.

4. Moderate bearing capacities are noticed for most of the study area (i.e. 40–60 kN/m²) while only the north of the province has a large bearing capacity (i.e. around 150 kN/m²).

5. From the shear strength digital map of the parameter, the sandy silty soil is the predominant formation for the soil layers (maximum angle of friction is 8° and with predominant cohesion around 16 kPa).

6. Shallow water table level is noticed for 80% of the study area and the rest of the area (i.e. the north) has a water table level up to 8 m below the ground surface.

Cover image

Source: Author.

Acknowledgements

The authors would like to express their truthful thanks to the technical staff of the GIS laboratory at the University of Wasit for their assistance in performing all the digital geotechnical maps. The first author would also like to acknowledge the Ministry of education/schools building directorate for their assistance in providing us with all the site investigation borehole data.

Additional information

Funding

The authors received no direct funding for this research.

Notes on contributors

Asad H. Aldefae

Asad Aldefae has a PhD in civil engineering/geotechnical engineering from the University of Dundee/Scotland/Uk at the end of 2013. He is interested in earthquake engineering, environmental engineering, riverbanks stability, physical and numerical modeling, geotechnical centrifuge, seismic performance of soil-structure interaction and slope stability analysis and soil-water interaction engineering problems.

More than 16 paper were published in high ranking journal by Dr. Aldefae like Géotechnique, Soil Dynamic and Earthquake Engineering, Geotechnical and Geoenvironment Engineering, ASCE, Cogent Engineering, as well as many international conferences like a series of international conferences of physical modeling in geotechnic (ICPMG) in both Perth, Australia (2014) and London, UK (2018) and Greece.

Results of this paper are important to produce digital geotechnical maps using GIS to understand the geographical distribution of mechanical geotechnical parameters which investigated from tens of the soil investigation reports.