Identifying subsurface weak zones in Riyadh, Saudi Arabia, using multichannel analysis of surface wave technique

1. Introduction

Subsurface cavities in the Riyadh area present geological risks to urban infrastructure and development. The unique geological conditions of the region, combined with the rapid pace of urban expansion, make Riyadh particularly susceptible to the formation of these underground voids. These cavities, whether naturally occurring or induced by human activities, pose a significant threat to the safety and stability of buildings, roads, and other vital infrastructure. Therefore, detecting and understanding their distribution has become essential in the region’s planning and development. Advanced geophysical techniques, including multichannel analysis of surface waves (MASW), have emerged as a powerful tool for identifying and mapping these cavities, offering an invaluable approach to urban risk management (Mohamed et al., 2013; Rehman et al., 2016; Aldahri et al., 2017; Rehman et al., 2018; Alzahrani et al., 2021; Abdelrahman et al., 2024; Hazaea et al., 2024; Sambath et al., 2025). The geological conditions in Riyadh contribute significantly to the formation of subsurface cavities. The region’s underlying rock formations are primarily composed of limestone, gypsum, and other soluble rocks, which are highly susceptible to dissolution when exposed to water over time.

This dissolution process, known as karstification, is a natural phenomenon involving the gradual erosion of these rock formations. It results in cavities and voids beneath the surface. In arid regions such as Riyadh, soluble rock formations coupled with occasional heavy rainfall can accelerate the karstification process, creating voids of varying sizes (Abd El Aal, 2017; Abdelrahman et al., 2023; Al-Hashim et al., 2024; Abdelrahman, 2025). Although often stable for extended periods, these cavities can lead to ground subsidence, sinkholes, and sudden collapses, posing significant threats to surface structures. In addition to natural processes, human activities play a significant role in forming subsurface voids in Riyadh. Rapid urbanization of the city has significantly intensified the demand for groundwater, resulting in increased extraction for agricultural, industrial, and municipal purposes. This increased withdrawal often substantially lowers the water table, which disrupts the stability of subsurface geological structures that provide critical support to the surface, potentially causing ground settlement or subsidence. Furthermore, in specific scenarios, the excessive pumping of groundwater can accelerate the collapse of pre-existing natural cavities or initiate the formation of new voids, particularly in regions where underground aquifers or reservoirs are heavily exploited, as the reduced water pressure exacerbates the dissolution of soluble limestone formations and heightens the risk of structural failure in the subsurface environment (Aljammaz et al., 2021). Furthermore, construction activities, such as mining and tunneling, inadvertently create or enlarge cavities. Excavation in certain regions may lead to ground displacement, compounding the effects of natural dissolution and exacerbating the area’s vulnerability to subsidence and sinkhole formation (Youssef et al., 2016; Abd El-Aal et al., 2021; El-Haddad et al., 2024; Díaz-García & Farfán-Córdova, 2025).

Geophysical techniques have become more widely employed to address these limitations in recent years, offering non-invasive and efficient alternatives for subsurface exploration. Among these, MASW has shown great promise in detecting and mapping subsurface voids (Park et al., 1999; Park et al., 2007; Park & Miller, 2008; Parker Jr & Hawman, 2012; Olafsdottir et al., 2018; Long et al., 2020; Ali et al., 2021; Abdallatif et al., 2022; Rahnema et al., 2022; Putri et al., 2025). MASW is a seismic method that analyzes surface wave velocities, which are sensitive to variations in subsurface material properties. These surface waves travel through the Earth’s surface and are influenced by the density and stiffness of the materials they encounter. Cavities or voids can significantly alter the propagation of these waves, allowing for the detection of underground anomalies (Abbas & Abdelgowad, 2024). MASW involves deploying an array of geophones along the ground surface and measuring the speed at which surface waves travel through the subsurface. By analyzing the dispersion of these waves across multiple channels, MASW can generate a detailed image of the subsurface profile, revealing the depth, size, and distribution of cavities (Peng et al., 2024). This non-invasive technique can cover large areas quickly and efficiently, making it an ideal method for monitoring subsurface conditions in urban environments such as Riyadh (Almalki & Munir, 2013; Mahvelati & Coe, 2017; Almadani et al., 2021; Abdelrahman et al., 2024; Qaysi et al., 2025). The choice of survey areas in this study is crucial due to the proximity of key strategic projects aligned with Vision 2030 and the ongoing urban expansion in these neighborhoods. Riyadh is situated on the expansive Najd Plateau, precisely located (24.7°N and 46.7°E). A detailed map of this region has been meticulously generated using ArcGIS 10.2 software, as illustrated in Fig. 1. The city is situated approximately 600 m above sea level and has a desert climate characterized by extreme temperatures, particularly during the summer.

Close

Fig. 1.

Map illustrating the location of Riyadh area.

Export to PPT

These cavities present multiple risks to Riyadh’s growing infrastructure. For instance, buildings and roads constructed above unstable ground may suffer structural damage due to uneven settlement, manifesting in cracks or complete collapse in the most severe cases. Additionally, the formation of sinkholes can disrupt transportation networks, creating dangerous conditions for residents and posing significant logistical challenges. Given the increasing population and continuous urban expansion, identifying the locations of subsurface cavities is critical for effective urban planning and construction, helping mitigate potential risks to infrastructure and public safety (Abd El Aal, 2017). Traditional methods for detecting subsurface cavities, such as drilling or borehole surveys, is often impractical for large-scale applications due to their high cost and time-consuming nature. Additionally, these methods may only provide localized data and fail to comprehensively understand the distribution of cavities across a broader area.

While previous studies have utilized MASW and other geophysical methods to detect subsurface voids in karst terrains, a critical gap remains in quantitatively linking shear wave velocity anomalies with verified geotechnical failure zones, particularly in rapidly urbanizing arid environments like Riyadh. Most existing work lacks the integration of MASW results with systematic borehole validation across a broad spatial scale, which limits the reliability of interpretations for engineering decision-making. Moreover, few studies have assessed the spatial extent, frequency, and engineering relevance of low-Vs zones in terms of construction risk (e.g., bearing capacity thresholds or foundation suitability). Additionally, long-term monitoring of weak zone evolution, especially under varying hydrological and anthropogenic stressors, such as groundwater withdrawal, is virtually absent, leaving the temporal dynamics of sinkhole susceptibility poorly understood. This study addresses these gaps through a combined geophysical-geotechnical approach and proposes a baseline for future predictive and regulatory frameworks.

The pioneering use of MASW for large-scale subsurface mapping in Riyadh’s karst environment, combined with borehole validation, represents a multifaceted novelty. It offers a scalable, non-invasive solution to a pressing regional challenge, enhances the accuracy of subsurface characterization through integrated methodologies, and sets a new standard for geophysical investigations in karst-prone urban areas. This approach advances the scientific understanding of Riyadh’s subsurface and provides a replicable framework for other cities facing similar geological risks. This study aims to detect and map subsurface cavities and weak zones in Riyadh, Saudi Arabia, using the MASW technique, addressing the significant risks these features pose to urban infrastructure amid the region’s rapid expansion and unique karst-prone geological conditions, while overcoming the limitations of traditional methods like drilling by providing a comprehensive understanding of their spatial distribution; it further seeks to assess the impact of both natural karstification and human-induced factors, such as groundwater extraction and construction, on the safety and stability of buildings, roads, and other infrastructure, ultimately supporting sustainable urban development and effective risk management near key Vision 2030 projects by mitigating hazards like subsidence, sinkholes, and structural collapse through a non-invasive method.

2. Geological setting

Riyadh is situated on the Najd Plateau in the heart of the Arabian Peninsula. It is characterized by a geological framework dominated by sedimentary rock layers, mainly limestone, shale, and marl, which have evolved over millions of years spanning the Mesozoic and Cenozoic eras. Located on the stable Arabian Shelf, the region has experienced geological influences from the Red Sea rifting, resulting in faulting, folding, and sediment accumulation that have sculpted its current topography, with elevations averaging around 600 m above sea level. The prevalence of limestone, particularly from the Upper Cretaceous and Tertiary periods, facilitates karstification, a process where slightly acidic water dissolves the rock over time, forming caves, sinkholes, and subsurface voids. This threatens infrastructure stability and complicates groundwater management in this arid region (Al-Othman, 2002; Mogren, 2020). Riyadh’s harsh desert climate exacerbates these challenges, producing loose, unconsolidated soil, which is highly susceptible to erosion, compaction, and uneven settlement, thereby undermining building foundations and complicating construction efforts. Several key geological formations shape this environment, including the Arab, Jubaila, Aruma, Sulaiy, Yamamah, and Alluvium, each contributing uniquely to the region’s subsurface dynamics (Fig. 2).

Close

Fig. 2.

Map depicting the geological setting of Riyadh area.

Export to PPT

The Arab Formation, a highly permeable limestone unit from the Cretaceous period, is integral to the region’s aquifer system, channeling groundwater through its fractured and porous structure; however, its solubility leads to extensive karstification, creating voids that destabilize the ground (Abu-Ali, 2005; Almajed et al., 2021). Similarly, the Jubaila Formation, composed of thick limestone and dolomite sequences from the same period, serves as a critical groundwater reservoir, trapping water in its less permeable layers, yet its exposure to surface water promotes karst features that further weaken the subsurface (Abadah, 2002; Khalifa et al., 2021). The Aruma Formation, primarily composed of clastic sediments such as sandstone and conglomerates, impacts local drainage patterns and soil stability, presenting challenges for construction due to its coarse-grained nature. However, limestone units are less prone to dissolution (Philip et al., 2002). In northern Riyadh, the Sulaiy Formation, a Middle Cretaceous deposit of chalky limestone and marl, is highly vulnerable to dissolution when in contact with groundwater, significantly contributing to the development of underground cavities and caves (Wolpert et al., 2015). The Yamamah Formation, a widespread carbonate unit with interbedded clay layers, supports major aquifers across central Saudi Arabia but is prone to karstification. Its near-surface presence in certain areas leads to soil erosion and subsidence risks when groundwater levels fluctuate (Bamousa, 2019; Aziz et al., 2024). Lastly, alluvium formation, comprising recent deposits of sand, gravel, and clay along ephemeral streams and valleys, introduces additional instability due to its unconsolidated nature, which impacts infrastructure development and facilitates groundwater recharge during rare rainfall events (Table 1).

These geological characteristics highlight the critical need for MASW, which effectively maps subsurface voids and weak zones by analyzing shear wave velocity variations, enabling better urban risk management and supporting safer infrastructure development in Riyadh’s karst-prone environment. The digital elevation model (DEM) of the study area in Riyadh shows elevation ranging from 564 to 794 m above mean sea level (AMSL). The map highlights varying terrain, with red indicating higher elevations (around 794 m) in the west and transitioning to green for lower elevations (around 564 m) in the east. Key features include boreholes (BH1 to BH4) and MASW profiles (P1 to P12), marked with red and blue triangles, respectively. Major roads, such as King Fahad Road, King Salman Bin Abdulaziz Road, and the Northern Ring Road, are also depicted, as illustrated in Fig. 3.

Close

Fig. 3.

DEM of the study area, showing a range from 564 to 794 (AMSL).

Export to PPT

3. Materials and Methods

The MASW is an advanced geophysical technique that has garnered considerable attention in recent years due to its capacity to non-invasively evaluate subsurface properties, such as shear wave velocity profiles, without the need for drilling or excavation (Park et al., 1999). This method employs the analysis of surface wave propagation to provide detailed insights into subsurface material characteristics, which are vital for various applications, including geotechnical investigations, seismic hazard assessments, and the detection of subsurface cavities or voids (Dorman et al., 1960; Knopoff, 1972; Pegah & Liu, 2016; Abdelrahman et al., 2017; Ashraf et al., 2018; Clinton, 2020). In areas where cavities and karst features are a concern, such as Riyadh, Saudi Arabia, MASW is an effective tool for detecting and mapping these anomalies, which pose significant risks to urban infrastructure and development. Surface waves, particularly Rayleigh waves, propagate along the Earth’s surface, with their velocities influenced by the elastic properties of the subsurface materials they traverse. MASW measures the dispersion characteristics of these surface waves, which refers to the variation of wave velocity with frequency and is closely reliant on the material properties of the ground. Through the analysis of this dispersion, MASW enables the creation of shear wave velocity profiles of the subsurface. These profiles are crucial for identifying weak zones, soft layers, and anomalies such as subsurface cavities, which are essential to assess in urban areas prone to sinkholes, ground subsidence, or karstification.

In cities like Riyadh, where subsurface cavities frequently develop in limestone formations due to dissolution processes, MASW plays a key role in recognizing and mapping these voids (Ali et al., 2021). Detecting such voids is imperative because their presence can lead to significant structural instability and pose hazards to existing infrastructure and ongoing development projects. For instance, regions with karstic limestone formations may contain underground voids or caves that conventional geotechnical methods, such as drilling, could overlook. MASW provides a more comprehensive understanding of the subsurface without the need for invasive exploration, offering a means to map and quantify these cavities for improved planning and risk management. Shear-wave velocity models can be generated in 1D and 2D formats. The MASW flowchart outlines a two-step methodology where Step 1 involves the processing of seismic Rayleigh wave records through wavefield transformation to derive experimental dispersion, and Step 2 involves iteratively refining an initial theoretical model via forward modeling and inversion, using curve fitting to achieve the final model Vs distribution (Fig. 4). This study concentrates on the 1D Shear-wave velocity model derived from the MASW method (Olafsdottir et al., 2018). The average Shear-wave velocity for the depth (h) of soil, referred to as cap V sub cap H, is computed as follows (Kanlı et al., 2006):

Close

Fig. 4.

MASW flowchart showing the two-step process for determining the final Vs distribution.

Export to PPT

where $H=\sum hi$ is the cumulative depth in m. For 30 m average depth, shear-wave velocity is written as:

Where $h_i$ and ${\text{v}}_{\text{i}}$ denote the thickness (in meters) and Vs in m/s (at a shear strain level of 10 − 5 or less) of the formation or layer, in a total of N layers, existing in the top 30m. ${\text{V}}_{{\text{s}}_{30}}$ is accepted for site classification as per NEHRP Classification (Safety, 2004, Table 2).

4. Data acquisition and processing

The MASW survey was executed along 12 profiles in Riyadh, employing vertical 4.5 Hz geophones spaced 1 m apart along each 50 m profile. A 1D receiver array of 24 geophones was used, with the seismic source positioned 5 m beyond the last geophone. The roll-along acquisition geometry, illustrated in Fig. 5, facilitated systematic repositioning of the source and geophone array to effectively map subsurface conditions, capturing shear wave velocity variations that highlight weak zones and cavities. Data were recorded with a 0.125 ms sample interval, five stacks, and a 0.500-second duration, collected during low-noise nighttime hours (2:00 AM to 6:00 AM) on weekends in 2024 to minimize traffic interference. Borehole data from private companies were integrated to enhance the study, combining geophysical MASW results with geotechnical borehole insights for a more robust characterization of the subsurface. The MASW data underwent a multi-stage processing workflow using ParkSEIS software, as outlined in Fig. 6. Initially, Seg-2 formatted data were imported into ParkSEIS, where geometric parameters were applied to seismic traces to identify the Rayleigh wave window and generate dispersion curves. After selecting these curves and creating an initial subsurface model, an inversion process was used to produce shear-wave velocity (Vs) profiles. Synthetic dispersion curves, generated using established numerical methods, were compared with field data. The Jacobian matrix was employed to compute the partial derivatives of the field velocity data concerning the model’s S-wave data, thereby improving the fit and providing uncertainty estimates for the Vs values. The processing workflow encompassed four key stages: (1) acquiring multi-channel seismic records with the geophone array, (2) extracting fundamental-mode dispersion curves by analyzing velocity-frequency relationships, (3) inverting these curves to create 1D Vs models for each shot gather, and (4) interpolating these 1D models into 2D Vs models to depict variations across depth and lateral distance for each profile. For instance, the first 0.1-second segment of a shot gathered from Profile-12 (Fig. 6a) was analyzed across 24 channels, assessing frequency characteristics, signal integrity, noise levels, and geometric attributes essential for further processing. The dispersion curve (Fig. 6b) was derived by evaluating arrival times, amplitude changes, and phase shifts across frequencies, revealing fundamental and higher-order Rayleigh wave modes that indicate shallow subsurface geology. Data were then transformed into the frequency-wavenumber domain using a 2D Fast Fourier Transform to enhance subsurface feature resolution. The final MASW outputs were presented as 1D Vs profiles showing velocity with depth (Fig. 6c) or as 2D cross-sections combining multiple 1D profiles to illustrate Vs variations with both depth and lateral extent (Fig. 6d), offering a comprehensive view of the subsurface structure.

Close

Fig. 5.

Diagram of the MASW field survey configuration.

Export to PPT

Close

Fig. 6.

MASW data processing sequence for Profile No. 12: (a) unprocessed data, (b) dispersion curve, (c) 1D shear-wave velocity model, and (d) 2D Vs geoseismic section composed of multiple 1D Vs profiles.

Export to PPT

5. Results and Interpretation

Variations in subsurface elasticity and rigidity result in differences in measured shear wave velocity (Vs) values, which are key indicators for evaluating the ground conditions beneath the surface. These variations reflect the differing physical properties of subsurface materials, such as their capacity to deform under stress. Generally, shear wave velocity (Vs) is influenced by the lithification of the soil. In this process, the soil transforms into rock through compaction and cementation, as well as the stiffness of the underlying rock formations. Consequently, areas with more rigid, consolidated materials exhibit higher Vs values, while less compacted or more porous materials display lower Vs values. This serves as a crucial metric for understanding the mechanical properties of the subsurface and evaluating its suitability for construction and other engineering purposes. The Vs values range from approximately 600 to 3600 m/s, with a depth of investigation extending to 30 m in this study. The 2D Vs profiles indicate variations in subsurface stratigraphy, revealing an increasing trend in shear wave velocity with depth up to the investigation depth. The general underground conditions and characteristics of the site can be summarized as follows:

The uppermost subsurface stratum, designated as Layer 1, is characterized by relatively low shear wave velocity (Vs) values, ranging up to a maximum of 1000 m/s, which are visually represented by a spectrum of colors from bluish-white to deep sky-blue across (Fig. 7). This layer spans a depth range of 6 to 15 m beneath the surface, as depicted in the figures above, and is predominantly composed of highly fractured and weathered limestone, a finding substantiated by detailed analyses of drilled borehole samples. Within this layer, a distinct subzone with exceptionally low Vs values, not exceeding 650 m/s and highlighted by a whitish hue, emerges between 4 and 10 meters deep, signifying a vulnerable region prone to instability within Layer 1. The thickness and spatial extent of this weak zone exhibit considerable variability, as evidenced by its presence and fluctuating dimensions across profiles 1, 2, 4, 5, 6, 7, 8, 9, 10, and 12. The intermediate stratum, Layer 2, exhibits Vs values ranging from 1000 m/s to 1800 m/s, as depicted through a color gradient from sky blue to green in profiles 1 through 12. Its thickness varies between 5 and 17 m below the current ground surface, as determined by the MASW sections. Borehole data corroborate that this layer consists of fractured, weathered limestone. Based on the recorded Vs values, the depth to the engineering bedrock, defined as the depth at which Vs exceeds 1500 m/s, is estimated to be between 6 and 17 m. Careful evaluation of the thickness and distribution of weak zones within this layer across individual MASW profiles is essential for establishing the optimal foundation depth, particularly given the presence of low-velocity areas (cavities and cavity zones) marked by dotted lines and reduced Vs values in profiles 1 through 12, which borehole data confirms as zones of significant fracturing and weathering. The deepest stratum, Layer 3, is distinguished by elevated Vs values of 1800 m/s or higher, represented by a color range from yellow to red and black across all profiles (1 through 12), and comprises two lithologic units with comparable Vs ranges, extending from 17 m down to the maximum investigation depth. This layer comprises massive, intact limestone, as indicated by the MASW data. Notably, Profile No. 3, situated in an area of pronounced subsurface heterogeneity, reveals significant variations in shear wave velocity across its layers, with the first layer exhibiting Vs values between 600 and 1800 m/s, suggestive of fractured to moderately weathered limestone that has undergone substantial physical alteration due to natural processes such as weathering and fracturing, leading to diminished consolidation and heightened porosity. This layer persists to a depth of 17 m below the surface. Beneath it, the second layer shows a considerable increase in shear wave velocity, ranging from 1800 to 3600 m/s. This higher velocity indicates the presence of hard, massive limestone, a dense and solid material that is more resistant to deformation. The transition from weathered limestone above to intact, consolidated limestone below marks a significant change in material properties, signifying a shift from less consolidated rock to more consolidated rock. Profile No. 11 is in an area dominated by loose sediments, specifically Wadi deposits, which typically consist of unconsolidated materials like sand, silt, and gravel. The first layer of Profile No. 11 has a shear wave velocity ranging from 300 to 700 m/s, suggesting the presence of soft, loosely packed sediment. This indicates that the layer comprises poorly consolidated or unconsolidated sediments with low compaction and stiffness. The depth of this first layer reaches 14 m below the surface. However, the second layer exhibits a marked increase in shear wave velocity, ranging from 1,800 to 3,600 m/s. This higher velocity aligns with massive limestone, which is dense, consolidated, and highly resistant to deformation. The sharp increase in velocity signifies a transition from the soft, loose sediments above to a more rigid and solid rock formation below. Comparing Profile No. 3 with Profile No. 11 highlights the differences in subsurface conditions between the two locations. Profile No. 3 consists of fractured to moderately weathered limestone followed by hard limestone, while Profile No. 11 features loose sedimentary layers overlying massive limestone. The variations in shear wave velocities across these profiles provide valuable insights into the geological characteristics of the region, including the degree of consolidation, porosity, and the overall composition of the subsurface layers.

Close

Fig. 7.

2D shear wave velocity (Vs) profiles for all MASW surveys displaying diverse subsurface characteristics.

Export to PPT

Sinkhole-prone zones were identified using the MASW technique, revealing shear wave velocity (Vs) anomalies below 650 m/s within the upper 4–15 m of the subsurface. These low-Vs zones, annotated by whitish hues and dotted lines in the 2D profiles (Fig. 7), correlate to highly fractured and weathered limestone, confirmed by borehole data. Sixteen distinct weak zones were delineated, occurring at depths of 2–10 m and extending laterally 6–50 m.

6. Discussion and Conclusions

The MASW results in this study provide crucial insights into the subsurface geological conditions of the area. A holistic approach was implemented to establish and validate correlations between the soil properties obtained from geophysical surveys and geotechnical data from drilled boreholes. This correlation enabled a detailed characterization of the subsurface conditions at the site (Bamousa, 2019; Abdallatif et al., 2022; Abdelrahman et al., 2024; Abdelrahman, 2025). By analyzing and averaging shear wave velocities at different depth intervals and integrating borehole data for ground truth, a comprehensive geological model was developed for the site, reaching a depth of 30 m. Based on data from MASW and geotechnical borehole investigations, the subsurface was classified into two distinct layers using the NEHRP classification system. The first layer has highly fractured to moderately weathered limestone, indicating that the material has undergone significant changes due to natural processes such as weathering and fracturing. This has led to a less consolidated and more porous structure compared to the underlying material. In this layer, a decrease in shear wave velocity to less than 650 meters per second was observed in most profiles, indicating the presence of weak zones located at depths ranging from 4 to 10 m. The second layer comprises hard, massive limestone, which is dense, consolidated, and deformation-resistant. This marks a clear transition from the more weathered and fractured limestone above to a more intact and solid rock formation below, distinguishing between less consolidated and more rigid materials. Except for Profile No. 11, which contains sediments, three distinct layers were observed. The first layer had silty sand with gravel, the second layer comprised fractured, weathered limestone, and the third layer was characterized by massive limestone, as determined by shear wave velocity measurements.

Geotechnical borehole data collected from multiple sites offered critical insights into the subsurface characteristics across various profiles, revealing consistent patterns in material composition while also indicating potential variations in consolidation and strength. Borehole No. 1 (Fig. 8a) revealed that the uppermost 2 m comprised a mixture of silt, sand, and gravel deposits, typical of unconsolidated surface materials that offer minimal resistance to deformation due to their loose, non-cohesive nature. From 2 to 7 meters, this borehole encountered highly fractured to moderately fractured limestone, where the fractures reflect significant physical alteration caused by weathering or mechanical stress, leading to reduced consolidation and potentially weakening the limestone’s structural integrity, thus marking a shift from loose surface sediments to a more consolidated but compromised limestone formation.

Close

Fig. 8a.

Geotechnical parameters of borehole No. 1.

Export to PPT

In contrast, Borehole No. 2 (Fig. 8b) exhibited a thicker layer of silt, sand, and gravel deposits extending down to 13 m, akin to Borehole No. 1, with fractured limestone appearing below this from 13 to 15 meters, indicating a deeper transition to fractured rock compared to Borehole No. 1 and underscoring a regional trend of fractured limestone at depths between 7 and 15 meters, albeit with varying transition depths. Borehole No. 3 (Fig. 8c) also began with a surface layer of silt, sand, and gravel. Still, here, the transition to fractured limestone occurs much earlier, at a depth of just 1 meter, and persists down to 15 m, suggesting a thinner unconsolidated surface layer and a subsurface dominated by fractured limestone at shallower depths, with the extensive fracturing likely impacting engineering properties such as compressive strength and stability due to the pronounced alteration of the limestone. The surface layers across these boreholes consistently feature a thin veneer of unconsolidated silt, sand, and gravel deposits underlain by fractured limestone at varying depths (Almadani et al., 2015; Abdelrahman et al., 2023; Abdelrahman et al., 2024). Borehole No. 4 (Fig. 8d) mirrored the pattern seen in Borehole No. 3, with the initial 2 m comprising silt, sand, and gravel, followed by highly fractured to moderately fractured limestone from 2 to 15 m, reinforcing the observed depth range for fractured limestone and the transition from surface deposits to fractured rock occurring between 1 and 2 m in these two boreholes, with the fractured limestone in Borehole No. 4 likely sharing similar traits of reduced consolidation and variable mechanical strength as seen in Borehole No. 3.

Close

Fig. 8b.

Geotechnical parameters of borehole No. 2.

Export to PPT

Close

Fig. 8c.

Geotechnical parameters of borehole No. 3.

Export to PPT

Close

Fig. 8d.

Geotechnical parameters of borehole No. 4.

Export to PPT

While MASW offers reliable resolution for shallow weak zones, its accuracy diminishes with depth or when voids lack distinct velocity contrasts; thus, confidence is highest when anomalies are near the surface and supported by geotechnical data. From an engineering perspective, zones with Vs < 650 m/s typically correspond to very soft rock or loose materials with low allowable bearing capacities (<100 kPa), unsuitable for conventional shallow foundations. In such areas, deep foundations (e.g., piles) anchored into the underlying massive limestone (Vs ≥ 1800 m/s) are recommended to ensure structural stability and mitigate the risk of settlement or collapse due to undetected subsurface voids.

A total of 16 weak zones were detected across the 12 MASW profiles, characterized by shear wave velocities below 650 m/s, indicating highly fractured or weathered limestone and unconsolidated sediments. These zones occur at depths of 2 to 10 m and exhibit lateral extents ranging from 6 to 50 m. Cumulatively, the weak zones affect approximately 28% of the total surveyed profile length, based on the combined horizontal extent of all anomalies relative to the total MASW coverage. The most affected profiles include Profiles 1, 2, 4–10, and 12, with Profile 11 uniquely underlain by loose wadi deposits, exhibiting Vs values as low as 300 m/s. These findings highlight the spatial significance of subsurface hazards in the study area and underscore the need for targeted engineering interventions.

The identification of shallow weak zones and potential sinkhole features has direct implications for construction practices and urban planning in Riyadh. Policymakers should mandate pre-construction geophysical investigations, such as MASW and borehole validation, in karst-prone areas to prevent structural failures. Construction codes should be updated to require deep foundations or ground improvement techniques (e.g., grouting) in areas where Vs values are below 650 m/s. Additionally, land-use zoning regulations should restrict heavy structures in zones with confirmed subsurface instability and promote alternative uses, such as green spaces or light infrastructure. Establishing a centralized geotechnical risk database, supported by ongoing surveys, would enable engineers and developers to make informed decisions, thereby enhancing safety and reducing future remediation costs.

Future work should focus on integrating MASW with additional geophysical methods, such as electrical resistivity tomography (ERT) and ground-penetrating radar (GPR), to enhance detection accuracy, particularly for deeper or smaller-scale voids that MASW may overlook. Long-term monitoring of weak zones using time-lapse surveys could help assess the evolution of subsurface conditions, especially in response to seasonal rainfall or groundwater fluctuations. Expanding the survey area city-wide and developing a GIS-based sinkhole susceptibility map would support regional planning. Furthermore, correlating geophysical anomalies with in-situ geotechnical testing (e.g., SPT, CPT) can refine the empirical relationships between Vs and engineering parameters, such as allowable bearing capacity and modulus of subgrade reaction.