Unraveling bed sediment dynamics and accumulation rates in the Northern Arabian Gulf: a synthesis of modeling, radiometric techniques, and field data

The Northern Arabian/Persian Gulf (NG) experiences complex sedimentary dynamics influenced by aeolian and fluvial inputs under highly variable hydrodynamic conditions. This study integrates numerical modeling (Delft3D-FM), radiometric dating, and field observations to quantify sediment accumulation rates and map cohesive bed sediments. Seasonal simulations for summer and winter reveal distinct sediment accumulation trends, with deposition exceeding 0.9 g/cm²/yr in the NG. Model validation against radiometric data shows strong agreement, with minor discrepancies in mid-range deposition zones (e.g., 0.24 vs. 0.48 g/cm²/yr). Wind-driven shear stress emerges as a key driver of bed sediments, particularly in winter, when higher variability and stronger bed shear stresses are observed compared to summer. These findings highlight the importance of combining field-based and numerical approaches to improve sediment transport predictions in arid coastal environments. This study provides critical insights for sediment management and coastal resilience, particularly in the context of climate change, which is expected to reshape sediment budgets and pose significant challenges to the stability of coastal ecosystems in the NG.

GRAPHICAL ABSTRACT

Graphical Abstract.

1 Introduction

Cohesive bed sediments, such as clay and silt, are fundamental components of marine ecosystems, influencing water clarity, benthic habitats, and circulation (Keen and Furukawa, 2007). The deposition of these sediments is governed by a complex interplay between hydrodynamic forces (waves, tides, currents), sediment sources, and grain properties (Huntley et al., 2008; Egan et al., 2021). While processes like tidal asymmetry are well-understood drivers of sediment trapping in fluvial-dominated estuaries (Allen et al., 1980), arid regions like the Northern Arabian/Persian Gulf (NG) are primarily influenced by aeolian sediment transport, which introduces sediment over a much larger area (Al-Ghadban and El-Sammak, 2005; Alosairi et al., 2024). These aeolian inputs are critical for marine productivity but also create unique challenges for understanding sediment dynamics (Madhusoodhanan et al., 2024). In addition to these primary drivers, other complex hydrodynamic processes such as coastal long-period waves and their associated resonance can also play a role in sediment mobilization and transport within semi-enclosed basins and estuaries (Gao et al., 2021).

Despite its importance, the NG remains a region where bed sediment dynamics are not fully understood. Previous studies have provided foundational knowledge, identifying a complex mixture of cohesive and non-cohesive sediments (Emery, 1956; Al-Gadhban et al., 2008). However, these efforts were often limited in spatial scope or did not quantify accumulation rates. Crucially, a significant knowledge gap persists regarding the role of seasonal hydrodynamics, particularly the dominance of winter Shamal winds, in controlling sediment accumulation. Furthermore, while radiometric dating has been widely used to determine accumulation rates (Aba et al., 2014; Al-Mur et al., 2017; Carvalho et al., 2011; Díaz-Asencio et al., 2019), these techniques have rarely been integrated with numerical models to validate simulations of physical processes.

Therefore, the primary objective of this study is to test the hypothesis that wind-driven shear stress is the dominant seasonal control on bed sediment accumulation in the NG. This study evaluates the effectiveness of a coupled numerical model, validated with radiometric dating, in quantifying these seasonal dynamics and delineating depositional patterns. By doing so, we aim to establish a quantitative framework for understanding the fundamental processes that govern sediment budgets in this arid, wind-dominated marine system.

To achieve this objective, we integrate high-resolution Delft3D-FM numerical simulations with radiometric dating of bed sediment cores. This approach combines surface grab samples and core analyses to provide both spatial and temporal perspectives on seabed processes. By running seasonal model scenarios (summer and winter), we isolate the effects of wind, tidal, and density-driven circulation on bed shear stress, allowing for an evaluation of the key forcing mechanisms.

Fulfilling this objective is particularly important as coastal vulnerability in the NG is intensified by climate-driven changes, including stronger Shamal winds and enhanced evaporation. By developing an integrated framework that couples numerical modeling and radiometric validation, this study provides a transferable methodology for other arid region estuaries (e.g., the Red Sea, Gulf of Oman) and delivers critical insights for improving sediment management and coastal resilience 40 under changing climatic conditions.

2 Study site

2.1 Northern Gulf region

The NG, as shown in Figure 1, is an estuary oriented from northwest to southeast. It is geographically located between 48°00’ and 51°30’ East longitude and 27°00’ and 30°00’ North latitude. The estuary is linked with the Arabian Sea and the Indian Ocean via the Strait of Hormuz (56 km in width) (Figure 1). The estuary is notable for its limited river inflow due to climatic and anthropogenic effects. The main river inflow is the Shatt Al-Arab River (Figure 1), which ranges from 60 to 300 m³/s seasonally (Alosairi and Pokavanich, 2017). Therefore, circulations and sediment dynamics in estuarine areas are relatively weak. The NG has an average width of approximately 230 km (Figure 1). The depth near the coastal areas varies (≈15 m) along Kuwait and Saudi Arabia’s coastline and deepens toward the Iranian coastline (Alosairi and Pokavanich, 2017) (Figure 1). The central axis of the basin exhibits greater depths, often exceeding 50 m, which is described as a geosyncline region (Emery, 1956). The geosynclinal region is typically described as a long, narrow trough filled with thick sediment deposits. In the Gulf, sediments are rich in shell fragments, primarily due to the activity of mollusks: a group of marine organisms that include clams, oysters, and snails, which produce calcium carbonate shells that contribute to sediment formation. Evaporite minerals, such as gypsum and halite, are abundant in shallow zones due to high temperatures (Emery, 1956). The high concentration of calcium carbonate, quartz, and resistant heavy minerals suggests slow deposition in the Gulf, contrasting with typical geosynclinal sedimentation (Emery, 1956). In the NG, the seabed is primarily composed of fine silt and clay, which originate from both aeolian and fluvial processes (Al-Gadhban et al., 2008; Foda et al., 1985). It is important to note that while the broader sediment system includes a range of grain sizes, this study and the presented model are specifically focused on the transport and deposition of fine-grained cohesive sediments. The dynamics of coarser fractions, such as medium to coarse sands, are considered outside the scope of the cur.

Figure 1

Figure 1. Northern Gulf geographical settings and focus on the study area (right panel).

2.2 Winter and summer hydrodynamic features

The NG features a unique hydrodynamic characteristic. These hydrodynamic features are mainly related to high sea temperature variations (15 to 37°C) and high salinity (≈45 ppt) at shallow semi-enclosed areas. Additionally, the NG experiences variable winds, including the northwesterly “Shamal” and the southeasterly “Kaus”. These winds occur year-round, in both summer and winter, with similar frequency but differing intensities. Due to the Gulf’s shallow waters, the effects of these winds are more pronounced, making wind-driven circulation highly visible (Pous et al., 2013). Tides in the Gulf are mixed semi-diurnal and are considered the main driving force for mixing and horizontal dispersion of dissolved and particulate material, such as sediments (Alosairi et al., 2011). As a result of these hydrographical settings, the Gulf is considered as a large inverse estuary (Kämpf and Sadrinasab, 2006). The Shamal also affects the dispersal and transport of the Shatt Al-Arab fluvial material toward the western coast of the Gulf (Alosairi and Pokavanich, 2017; Pous et al., 2013). Additionally, the inflow of Indian Ocean Surface Waters (IOSW) through the Strait of Hormuz introduces a distinct water mass that interacts with the local hydrographic conditions, leading to unique circulation patterns. The bathymetric variations, with shallow waters predominantly along the western and northern coast and deeper areas toward the eastern boundary, further contribute to the Gulf’s hydrodynamic complexity, influencing the distribution of temperature, salinity, and density across different seasons.

During winter, the NG experiences hydrodynamic changes characterized by a stable water column and apparent horizontal density-driven currents. The water temperature is lowest near the shallow coastal areas (≈15°C). The dense cold-water mass (≈1034 kg/m³) generated in these shallow regions flows from northwest to southeastwards along the seabed toward deeper areas of the Gulf. This dense water mass results from minimal river discharge during this season and the strong northwesterly Shamal winds, which enhance mixing and cooling, contributing to a homogeneous vertical temperature and salinity profile throughout much of the water column. This dense water flows southward near the seabed, while relatively weaker IOSW enter the Gulf through the Strait of Hormuz and flow along the Iranian coast, slightly opposing the dense water currents.

In contrast, summer in the NG is marked by stratification of the water column due to the formation of a thermocline in relatively deep waters (>30 m). The thermocline separates the warmer, less dense surface waters from the cooler, denser deep waters, creating a barrier restricting vertical mixing during calm conditions (low winds and neap tides). The high evaporation rates along the shallow western coast increase the salinity of surface waters, leading to horizontal density gradients that drive complex circulation patterns. These gradients create a unique non-uniform flow approximately 25 km offshore along the western coast, influencing vertical mixing and dispersion processes. The prevailing northwesterly winds during summer, often exceeding 9 m/s, further influence surface currents, which are generally directed southward along the Kuwait and Saudi Arabia coast, enhancing the region’s overall hydrodynamic activity.

2.3 Aeolian and fluvial sediment estimates

In marine systems, sediment primarily comes from aeolian and fluvial sources. In the NG case, the arid conditions and limited fluvial runoffs result in a predominance of aeolian inputs (Alosairi et al., 2024). The deserts of Iraq, Syria, and Saudi Arabia act as major sand and dust sources, continually mobilized by the Shamal winds and deposited into the NG (Al-Hemoud et al., 2022; Aba et al., 2018). The Shamal winds, especially during the summer, significantly contribute to aeolian sediment deposition on the sea surface extending approximately 200 km from land (Al-Ghadban and El-Sammak, 2005; Foda et al., 1985). Foda et al. (1985) estimated the average Aeolian sedimentation rate in the NG at 0.8 mm/yr for the first 200 km offshore. Closer to the Kuwait coast, Al-Dousari and Al-Awadhi (2012) found an average dust deposition of 265 tons/km² annually, equating to 0.17 mm/yr. Across the NG, this equates to 32 million m³ of aeolian sediments per year, or about 51 million tons given a density of 1,600 kg/m³. Foda et al. (1985) also noted that these sediments are primarily fine-grained (<50 µm), often settling in nearshore muddy seafloors (Emery, 1956).

The Shatt Al-Arab River is the main source of fluvial sediment for the NG. However, it is very limited compared to aeolian deposits. Early estimates by Milliman and Meade (1983) suggested an annual fluvial sediment load of 53 to 105 million tons based on 1960s data, with sediment concentrations of 0.85 to 1.7 g/l. However, Al-Ansari et al. (1979) found lower contributions from the Tigris and Euphrates, estimating 4.6 million tons/yr. The recent decline in sediment discharge from the Shatt Al-Arab is due to reduced river flows and sediment retention in reservoirs and marshlands (Alosairi and Pokavanich, 2017; Baltzer and Purser, 1990). About 10% of fine particles reach the NG, with 90% depositing in the delta (Emery, 1956). Today’s fluvial sediment discharge to the NG is much lower, estimated at just 0.93 million tons/yr, with peak supply from June to October (Al-Ghadban et al., 1999).

3 Methods

3.1 Field observations

The field observations are divided into two key assessments: the first focuses on evaluating the bed sediment texture and characteristics using grab sampling techniques, while the second involves core sampling for sediment chronology analysis to determine the accumulation rates of bed sediment. These assessments provide insights into the distribution of sediment types, ranging from fine particles like clay to coarser materials such as sand, and offer a detailed understanding of sediment accumulation rates. Both datasets are integral for validating the numerical model results for the NG, ensuring accuracy in simulating bed sediments and deposition processes. It is important to note that grab and core samples were collected at different times, which does not affect the findings, as the study focuses on interannual sediment accumulation linked to model validation rather than short-term variations.

3.1.1 Geophysical assessment of surface sediments

To investigate sediment characteristics in the NG, bed sediment samples were collected using the well-recognized grab sampling technique (Figure 2). This method involves deploying a grab sampler to extract sediment from the seabed, providing a representative sample of approximately 5–12 cm from the surface (Figure 2B). Sampling was conducted in late 2023 and 2024 at strategically selected locations covering most of the northwestern Gulf region to ensure comprehensive spatial coverage and representation of the sedimentary environment.

Figure 2

Figure 2. Sampling location (A) Grab and core samples, (B) Example of actual sample from grab sampler.

The primary objective of this sampling campaign was to characterize sediment types and evaluate their physical properties for classification. These parameters are crucial for understanding sediment distribution patterns and depositional processes in the region. Furthermore, the collected samples serve as key input data for validating the numerical model developed and utilized in this study. By integrating field data with modeling, we aim to evaluate the predictive accuracy of sediment accumulations and provide deeper insights into the interactions between sediments and hydrodynamic forces in this coastal environment.

3.1.2 Sediment core sampling, preparation and radioactivity determination

Five sediment cores were collected from sites at the NG to represent various sediment accumulation rates (Figure 2). Sediment cores (30–60 cm in length) were retrieved using a 2-inch KC Denmark Kajak Gravity Corer. Each core was sectioned into 2 cm intervals, dried at 90°C, and sieved through a 0.5 mm mesh. Subsamples were sealed for approximately one month to reach secular equilibrium, ensuring accurate ²²⁶Ra measurement (Radium-226 is a naturally occurring 159 radioactive isotope of radium).

Radioactivity was analyzed using an Ultra Low Background Gamma-Spectrometry system (Canberra BEGe detector) with Veto shielding, achieving a Minimum Detectable Activity (MDA) of ∼7 mBq/g for ²¹⁰Pb at 46.5 keV. ²¹⁰Pb (Lead-210) is a radioactive isotope of lead, widely used in sediment chronology and environmental studies, particularly for dating recent sediment deposits over the past 100–150 years. Efficiency calibration was performed using spiked sediments pre165 pared from mixed-gamma standard solutions. Activity concentrations of ²²⁶Ra and ²¹⁰Pb were then calculated using Genie 2000 software.

3.1.3 ²¹⁰Pb-based sediment accumulation rates

The ²¹⁰Pb dating method calculates sediment age based on the radioactive decay of ²¹⁰Pb, with a half-life of 22.3 years, assuming uniform atmospheric deposition over the studied area. Total ²¹⁰Pb in sediments consists of supported ²¹⁰Pb (derived from in-situ ²²⁶Ra decay) and excess (unsupported) ²¹⁰Pb_ex from atmospheric deposition. Sediment age (t) is derived using the decay Equation (1) as follows:

$\begin{array}{ll}{A}_Z{{(}^{210}\text{Pb})}_{\text{ex}}=A_0{{(}^{210}\text{Pb})}_{\text{ex}}{e}^{-\lambda t}& (1)\end{array}$

where A_Z is the activity at depth z, A₀ is the initial activity, and λ = 0.03114y⁻¹ (decay constant).

The Constant Rate of Supply (CRS) model refines this process by using the total cumulative activity (A_tot, Bq/m²) and the cumulative activity of ²¹⁰Pb_ex in the sediment column below the depth x (A_x, Bq/m²) to calculate the age of a sediment segment (layer), t_x is using Equation (2) as follows:

$\begin{array}{ll}{t}_x=\frac{1}{\lambda }\ln \left(\frac{A_{tot}}{A_x}\right)& (2)\end{array}$

The Sediment Accumulation Rates (SAR, g/cm²/y) are determined from the regression line of cumulative sediment mass depth (g/cm²) against sediment age (y). Uncertainties in SAR estimates are determined from the regression standard error. Detailed procedures for sampling, sample preparation, radioactivity measurements, and sediment dating are described in Aba et al. (2014).

3.2 Numerical modeling

The model used for this study is Delft3D-FM, a state-of-the-art hydrodynamic model developed to simulate water movement and transport processes in complex aquatic environments (Deltares, 2025). To ensure accuracy, the model configurations follow the approach described by Alosairi et al. (2024) for both hydrodynamics and sediment transport modeling. We note here that the validation of the model for hydrodynamic parameters as well as the Suspended Sediment Concentrations (SSC) can be found in Alosairi et al. (2024). It is worth noting that for hydrodynamics, a flexible mesh was applied, with fine grid resolutions tailored for the NG, reaching approximately 63 m × 63 m in critical areas. The model accounts for essential processes such as evaporation and heat fluxes, which are critical in the region’s arid climate. In the vertical, eight sigma layers were configured to capture variations in water column density and stratification. Baroclinic settings were used to incorporate the influence of temperature and salinity on hydrodynamic behavior. Wave generation was modeled using a fetch-length approach described in Deltares (2025), allowing reasonable simulation of wave-driven hydrodynamics.

It is important to clarify that the primary objective of this study is to characterize the regional-scale sediment dynamics driven by natural forcing mechanisms, such as wind and fluvial inputs. As such, modeling the localized hydrodynamic and sedimentary effects of specific anthropogenic point sources, like the thermal discharge from the Subiya power plant, was considered beyond the scope of this investigation. This focus allows for a broader understanding of the baseline sedimentary processes across the NG.

For the sediments, Delft3D-FM was coupled with Delft3D-WAQ, enabling the integrated simulation of suspended sediment transport and deposition. This setup provides a reliable framework for understanding the interplay between hydrodynamics and sediment transport in the NG. The sediment model operates on the classical Partheniades (1965) erosion formulation, with modifications to address different sediment layers and shear stress conditions. Erosion from the surface layer (known as the fluff layer) follows a grain-size-dependent first-order rate, transitioning to a zero-order rate when sediment mass exceeds a threshold (see Appendix for demonstrations). Erosion from the buffer layer (below the fluff layer) follows Van Rijn (1993) empirical power formulation, activated when shear stress surpasses a threshold (see Appendix for demonstrations). The deposition is divided between the fluff and buffer layers (depicted in the Appendix), determined by the settling velocity and sediment fraction. The critical shear stress for resuspension and other deposition factors are computed using Delft3D-FM. In this study, the buffer layer is considered to represent the bed sediment, as it retains deposited material over time, while the fluff layer remains highly dynamic and easily eroded. The general configurations of the fluff and buffer layers adopted in the model are given in the Appendix.

3.2.1 Numerical modeling scenarios setup

In this study, we developed three numerical scenarios to evaluate the forces influencing bed sediment dynamics in the NG across two distinct seasons: winter (January, February, and March) and summer (June, July, and August). Periods were selected based on model validation in Alosairi et al. (2024), as the same model is used here. The assessment focuses on understanding how various physical processes contribute to bed shear stress and, consequently, sediment accumulation. Each scenario is designed to isolate specific factors affecting bed shear stress, providing a clearer picture 224 of their individual contributions to sediment dynamics.

The first scenario, termed ‘Baseline Conditions,’ incorporates the combined effects of tidal forces, wind-induced shear stress, and density-driven currents (resulting from salinity and temperature gradients). By simulating these conditions for both summer and winter, this scenario allows us to analyze the natural interactions of all relevant forces and their collective impact on bed shear stress and sediment accumulation in the NG.

The second scenario, known as the ‘No Wind Effects’ scenario, excludes the influence of wind while retaining the effects of tides and density-driven currents. It is worth mentioning that the wave winds are also excluded in this scenario since there is no wind action.

The third scenario, referred to as ‘Tides Only,’ removes both the influences of wind and density-driven currents, focusing solely on the effects of tidal forces. All scenarios were evaluated for both summer and winter, allowing for a comparative analysis of sediment accumulation between the two seasons while accounting for the varying contributions of dynamic forces.

4 Results

4.1 Grab sediment samples

The grab sediment samples collected from the northwest of the Gulf, including Kuwait Bay (Figure 2), show slight spatial variations in sediment composition, primarily consisting of fine fractions (clay and silt) with some fine sand. Nearshore areas, such as southern Kuwait Bay, exhibit 242 relatively coarser sediment fractions (see Appendix B for sample results). These coarse sediments are indicative of the sedimentological nature of the area and the higher-energy environments influenced by wave action and localized currents. Strong tidal currents in offshore regions further reinforce this pattern, resulting in the deposition of relatively coarser sediment fractions, highlighting the role of hydrodynamics in sediment sorting and deposition.

The central axis of Kuwait Bay, which exhibits a reverse estuarine circulation pattern driven by density gradients and tidal influences (Alosairi et al., 2018), acts as a favorable zone for the deposition of fine sediments. This circulation promotes the trapping and settling of suspended materials, accumulating silts in the bay’s deeper troughs. Similarly, the southern extent of Boubyan Island, with its sheltered environment, serves as another deposition hotspot for fine sediments (see Figure 2 for sample locations).

Near Failaka Island, the distribution of fine-grained sediments appears to follow the island’s width, suggesting the influence of aeolian deposits transported from adjacent terrestrial sources. This pattern reflects the interplay between wind-driven processes and marine sedimentation dynamics, highlighting the complex mechanisms contributing to sediment deposition in the region. These findings highlight the influence of bathymetric features, hydrodynamic conditions, and sediment transport pathways in shaping the sedimentological characteristics of the northwestern Gulf. This aligns with previous regional studies in marine sedimentology, such as Al-Gadhban et al. (2008).

4.2 Radiometric sediment accumulation rates

The sediment accumulation rate (SAR) for each core was determined from the slope of a regression line fitted to cumulative mass depth versus sediment age. An example from Core 38 is shown in Figure 3, with remaining core results presented in Appendix C. Adjusted R² (Adj. R²) values exceeding 0.95 for all cores indicate excellent statistical confidence in the computed SARs. Among the five collected cores, notable variations were observed, particularly for Cores 5 and 26 near the Subiya plant (see Figure 2), where hydrodynamic changes induced by plant operations likely influenced sedimentation patterns. The results show that recent SARs for Core 5 and Core 26 were 0.380 ± 0.014 g/cm²/y and 0.510 ± 0.017 g/cm²/y, respectively, while older SARs were lower at 0.091 ± 0.010 g/cm²/y and 0.120 ± 0.025 g/cm²/y, suggesting an increase in sedimentation rates in recent years, potentially due to anthropogenic activities.

Figure 3

Figure 3. Radiometric results sample plot of Core 38 (the rest is in Appendix C).

To minimize human-induced influences, the sediment transport validation model used older SARs, representing pre-disturbance deposition conditions (see Appendix C for all core results). It is important to note that the sediment transport model does not account for the effects of plant discharges on the erosion/sedimentation process associated with the flow and the dynamic interactions of the plant discharge in detail, as this is beyond the scope of the current study. Instead, this work aims to provide a broader understanding of bed sedimentation patterns in the NG. A summary of average SAR, core locations, and sediment core lengths is presented in Appendix C, which includes figures that compare radiometric SAR measurements with modeled SAR results, demonstrating consistency between empirical data and simulations similar to the one shown in 281 Figure 3.

4.3 Numerical model

4.3.1 Bed sediment distribution

The spatial distribution of bed sediment produced by the model aligns with known sedimentation patterns in the NG, as documented by studies such as Al-Gadhban et al. (2008). However, while previous assessments were relatively broad and lacked detail, the model offers high-resolution sediment distributions, providing a more precise and refined representation of sedimentation dynamics in the region (Figure 4A). The results illustrate the net accumulated fine sediment mass over the one-year simulation period (Figure 4A), primarily consisting of fine-grained Aeolian and fluvial deposits. In this flux-based representation, darker colors indicate regions of higher net deposition, whereas lighter colors represent areas with lower net deposition, highlighting the key sources and distribution patterns captured by the model. The NG exhibits the highest accumulation rates of fine fractions, with values exceeding 100 kg/m² southeast of Boubyan Island, particularly near the river mouth of the Shatt Al-Arab. This localized high concentration reflects the influence of fluvial inputs and hydrodynamic conditions that promote deposition in these areas. The coefficient of determination (R²) between modeled and measured sediment masses demonstrates good model performance, with R² values exceeding 0.5 at most locations (Figure 4B), reinforcing the model’s reliability in capturing sediment distribution patterns.

Figure 4

Figure 4. Numerical model results for net accumulated mass of fine sediment over the one-year simulation period representing the flux (not the total standing stock): (A) Spatial distribution across the entire NG, and (B) Focused comparisons with grab samples, including R² computations for model validation.

In the central axis of Kuwait Bay, another significant patch is observed, with sediment masses ranging between 60 and 80 kg/m², indicating a secondary deposition zone influenced by circulation patterns and proximity to sediment sources, particularly aeolian deposits. Conversely, the central and southern regions of the Gulf, especially south of 28°N, exhibit lower sediment accumulation, with values typically below 10 kg/m². However, these deposits still fall within the fine sediment category, as silt typically ranges from 2 to 63 µm, indicating the presence of fine-grained material even in areas of reduced accumulation. The southern region of Kuwait Bay shows minimal fine sediment mass (¡10 kg/m²) in the model, a result that reflects the known prevalence of coarse, sandy seabeds in this area. Since the model is configured to simulate only the fine fraction, the exclusion of coarse sediments naturally leads to low predicted mass in these high-energy, sandy environments. This aligns with the observed scarcity of clay, silt, and fine sand in these areas (see Appendix B, sample point G1 for details). Consequently, sandy regions exhibit minimal bed sediment mass in the model, whereas muddy regions correspond well with higher clay and silt content, reflecting sedimentological expectations. The spatial variability in the model results captures both the prescribed sediment sources and the sediment transport dynamics driven by Gulf circulation. The model effectively captures fine sediment distribution around Boubyan Island, reproducing observed clay and silt seabed compositions. The accumulation of mud south of Boubyan Island is consistent with field data, and the southern boundary of this sediment patch at 29°N aligns well with observations (Figure 4), highlighting the model’s ability to replicate spatial sediment trends accurately.

Khor Al Sabiya (west of Boubyan Island) and Khor Boubyan (north of Boubyan Island) are accurately modeled as highly muddy areas, consistent with classifications by Al-Mussawy and Basi (1993). In contrast, Khor Abdullah (east of Boubyan Island) has a sandier bed (50% fine sand), as reported by Darmoian and Lindqvist (1988). The model reflects this with reduced clay and silt content (visible as lighter zones), demonstrating its ability to distinguish sediment classes based on prescribed conditions and observed seabed data. Overall, the model captures key spatial trends and magnitudes of clay, silt, and fine sand deposition in the NG. Although some discrepancies remain in sediment patch shape and extent, they fall within acceptable bounds considering the complexity of sediment transport processes and numerical assumptions. The strong agreement between modeled results and observed seabed classifications (Al-Mussawy and Basi, 1993; Darmoian and Lindqvist, 1988) reinforces the model’s capability in replicating sedimentary processes.

4.3.2 Bed sediment accumulation rate

The sediment accumulation rate computed by the model was validated against radiometric measurements, providing a quantitative assessment of the model’s ability to replicate sedimentary processes (Figure 5). The spatial distribution map of sediment accumulation rates (g/cm²/yr) reveals the highest rates occurring in the NG, particularly in areas near the Shatt al-Arab River delta and southeast of Boubyan Island. A comparison across the core locations yields a Root Mean Square Error (RMSE) of 0.157 g/cm²/yr and a Mean Absolute Error (MAE) of 0.117 g/cm²/yr. These metrics indicate a reasonable agreement between the model and observations, particularly at the extremes. For instance, at Core 26, the modeled rate (0.85 g/cm²/yr) is very close to the measured rate (0.83 g/cm²/yr), demonstrating strong performance in high-deposition zones. Similarly, at Core 5, the model accurately captures low accumulation, with a modeled rate of 0.09 g/cm²/yr compared to the measured 0.10 g/cm²/yr (Figure 5).

Figure 5

Figure 5. Accumulation rates in the Northern Gulf: (A) Comparison between modeled accumulation rates and core samples processed using radiometric dating at six locations. (B) Spatial distribution of accumulation rates across the entire Northern Gulf.

Differences are evident in mid-range accumulation zones, such as Core 25 and Core 38, where modeled rates (0.24 and 0.21 g/cm²/yr) are lower than radiometric measurements (0.48 and 0.41 g/cm²/yr), Figure 5A. These discrepancies may reflect limitations in capturing localized sedimentation dynamics or uncertainties in radiometric dating methods. Nonetheless, the model reproduces the general spatial trends observed in the Gulf, particularly in areas south of Kuwait Bay showing moderate accumulation rates (0.16–0.30 g/cm²/yr), consistent with the modeled and radiometric data.

Additionally, the spatial map highlights areas where sediment accumulation is most pronounced, particularly near the Shatt al-Arab delta, where deposition rates exceed 0.9 g/cm²/yr, indicative of significant fluvial contributions (Figure 5B). Moving away from the delta region, the modeled accumulation rates transition into moderate zones of 0.46–0.75 g/cm²/yr, primarily driven by sediment transport mechanisms and Gulf circulation patterns. In contrast, areas further south and east experience much lower fine sediment accumulation rates, often below 0.15 g/cm²/yr, reflecting not only limited fine sediment supply but also the dominance of sandy seabeds where coarser material, not accounted for by the model, likely constitutes a significant portion of the total sediment bed.

Overall, the sediment accumulation rate validation demonstrates that the model reliably captures spatial and quantitative trends in sediment deposition across the NG. The integration of radiometric data highlights the model’s predictive capability in replicating natural processes while also pointing to areas for future refinement. Strong agreement in high- and low-accumulation zones, coupled with minor discrepancies in mid-range areas, confirms the model’s utility for investigating the hydrodynamics effects on seabed accumulations.

4.3.3 Numerical modeling scenarios

Numerical modeling scenarios reveal a strong correlation between the seasonal dynamic forces and the bed sediment accumulations, as depicted in Figures 6A–C. In each modeled scenario where a specific forcing mechanism, such as wind or density variations (tides only), is excluded, 368 the bed sediment variations between summer and winter significantly decrease (Figures 6A–C). This reduction is particularly evident when comparing the ‘No Wind’ scenario with the ‘Baseline’ scenario, which is shown in the top panels of Figure 6. Bed shear stress is identified as the critical factor controlling seasonal differences in bed sediment accumulation, as clearly demonstrated in Figure 6 (middle panels D–F). Comparing the baseline conditions to the other scenarios, it is evident that the extent of the variations diminishes each time a dynamic force is excluded. For instance, when winds are eliminated, the bed shear stress decreases significantly (compare Figures 6D, E), and this reduction is further pronounced when only tidal forces drive the dynamics (Figure 6F). Consequently, the computed variations in bed sediment distribution and bed shear stress become confined primarily to the shallow zones, approximately around the 5–7 meter isobath.

Figure 6

Figure 6. The temporal and spatially averaged results of the numerical modeling scenarios generated by computing the differences between summer and winter for bed sediment (top panels A, B, and C), bed shear stresses (middle Panels D, E, and F), and depth-averaged velocity (lower panels G, H, and I). The white areas indicate no seasonal difference between summer and winter, while red (positive) represents summer-dominated conditions and blue (negative) indicates winter-dominated conditions.

In principle, an inverse correlation exists between bed sediment concentration and total bed shear stress. Specifically, areas marked as red zones in the top panels of Figure 6, which indicate higher bed sediment concentration during summer dominance, correspond to blue zones in the middle panels, representing lower bed shear stress. Conversely, regions with lower sediment concentrations (blue zones in the top panels, indicating winter dominance) exhibit higher bed shear stress (red zones in the middle panels). This inverse relationship highlights the interplay between bed sediment and hydrodynamic forces. However, seasonal dynamics introduce more complex features in regions influenced by estuarine processes, such as the Shatt al-Arab, and reverse estuarine systems, such as Kuwait Bay. These complexities are particularly evident closer to the shorelines. It is important to note that in the current dataset, winter winds were relatively stronger and associated with extreme events compared to summer. Nevertheless, there are instances where summer winds can be stronger than winter, potentially reversing the observed trends if extreme events were to occur during summer instead.

The Figures 6G–I demonstrates that when all hydrodynamic forces are considered in the hydrodynamic simulations, flow variations and dynamic features are highly complex, with summer conditions exhibiting relatively higher velocities in offshore regions compared to winter, particularly in deeper waters (>20 m). These dynamic features are significantly reduced in the ‘No Wind’ scenario and are further diminished in the ‘Tides Only’ scenario, as shown in the lower panels of Figures 6G, H. Despite the observed velocity variations in deeper offshore regions, their influence on bed sediment distribution is minimal. In contrast, within shallow enclosed regions (<20 m), such as Kuwait Bay and Khor Al Abdullah, flow magnitudes are maintained at similar levels but exhibit varying spatial extents across scenarios. This highlights the dominant role of winds, waves, and tidal forces in shaping hydrodynamics and bed sediment in these areas, where even under force-elimination scenarios, bed sediment accumulation during summer and winter continued to show notable variability (Figures 6B, C).

5 Discussion

Understanding spatial bed sediment deposition patterns in the NG is crucial from an environmental perspective, as sediment dynamics influence habitat health, nutrient cycling, and contaminant transport. The model successfully captures the distribution of fine sediment fractions and regional accumulation driven by aeolian and fluvial inputs. Accurate representation of muddy regions, such as Khor Abdullah, Kuwait Bay, southern Boubyan Island, and offshore areas, features the model’s sensitivity to regional variability. Consistency with previous localized studies reinforces the model’s robustness in replicating fine sedimentary processes in the NG, despite minor discrepancies in sediment patch shapes. These findings enhance our understanding of fine sediment dynamics in the NG and provide a valuable basis for addressing sediment management challenges and assessing the environmental impacts of anthropogenic activities.

Integrating radiometric techniques with modeled sediment accumulation rates provides a valuable framework for understanding sedimentary processes in the NG, particularly in regions characterized by low anthropogenic activities and predominantly aeolian dust deposition. The close agreement between modeled and radiometric rates in high- and low-accumulation zones, such as Core 1 (0.67 vs 0.83 g/cm²/yr) and Core 5 (0.09 vs 0.10 g/cm²/yr), emphasizes the model’s ability to replicate natural deposition patterns. Radiometric techniques have proven effective in validating numerical models, particularly in cases where aeolian deposits were assumed to exhibit linear deposition behavior. This assumption guided the model setup in the current study, where aeolian deposits were treated as continuous and time-invariant. These findings suggest that radiometric methods are valuable for validating sediment models in offshore regions, where simplified assumptions about deposition can help refine numerical simulations. For example, areas further south and east of the Gulf exhibit lower accumulation rates (<0.15 g/cm²/yr), reflecting limited sediment supply and reduced anthropogenic influence. However, discrepancies in mid-range accumulation zones, such as Core 25 (0.24 vs. 0.48 g/cm²/yr), may reflect limitations in the spatial resolution of radiometric dating or uncertainties in sediment mixing and reworking processes, particularly in areas of moderate hydrodynamic activity. These discrepancies can be attributed to several potential sources of uncertainty in both the radiometric dating and the numerical model. For the radiometric measurements, the CRS model used to calculate accumulation rates assumes a constant flux of unsupported 210Pb, which may not always hold true. Furthermore, physical or biological mixing of the upper sediment column (i.e., bioturbation), which is common in marine environments, can vertically redistribute radionuclides, potentially leading to an overestimation of recent accumulation rates. On the numerical modeling side, discrepancies can arise from the model’s spatial resolution; a single grid cell averages hydrodynamic and sedimentation processes over a large area, potentially masking localized depositional hotspots that a physical core sample might capture. Additionally, the parameterization of erosion and deposition processes, while based on established formulations, remains a simplification of complex natural phenomena. The combination of these factors likely contributes to the observed differences in mid-range accumulation zones, and a more detailed investigation into their relative contributions would be a valuable direction for future research.

Although not investigated in the current study, locations near the Shatt al-Arab delta would likely experience significant variation in sediment accumulation rates due to the dynamic nature of fluvial supply. Historical variability, driven by natural processes such as seasonal flooding, and anthropogenic influences, including dam construction and water diversion, make it challenging to characterize sedimentation in these regions accurately. The strong temporal and spatial variation in sediment input highlights the need for detailed, site-specific studies to understand deposition patterns in such complex environments better.

The actual data used to force the model show that the higher frequency of Shamal winds in winter compared to summer directly contributed to the greater shear stresses observed during the winter season. These elevated shear stresses influenced bed sediment distribution, particularly in shallow regions where sediments are more easily mobilized by hydrodynamic forces. While the model reflects the impacts of these observed seasonal forcing conditions, it does not address potential shifts in wind patterns or intensities due to climate change. For instance, if future projections indicate stronger or more frequent Shamal winds, or extended drought conditions leading to enhanced desertification, aeolian sediment inputs to the Gulf could increase substantially. Such changes would not only amplify winter resuspension but may also alter the balance between erosion and deposition, reshaping seabed morphology and sediment budgets across the region. These projected shifts highlight the importance of developing adaptive sediment management strategies that integrate climate-resilient modeling frameworks and long-term monitoring programs. In comparison to winter, if summer Shamal winds were to increase in frequency or strength under changing climatic conditions, this could significantly affect bed sediment dynamics, leading to altered redistribution patterns. Although this aspect was not investigated in the current study, it provides a valuable direction for future research to explore the implications of climate change on sedimentary processes in the NG.

An important limitation of the model lies in its exclusion of coarse sediment fractions, which constrains its ability to fully capture the interplay between sediment size classes and hydrodynamic forces. Coarser sediments, which are less susceptible to resuspension, may introduce stabilizing effects in high-energy environments, such as during extreme wind events. Conversely, the absence of coarse fractions in the current model likely underestimates sediment deposition in high-energy zones, where fine sediments are transported away, leaving coarser material behind. Additionally, in the current study, we assumed that the aeolian desert dust supply is in a steady state and continuously sourced from the Shamal winds. This assumption excludes potential contributions from less frequent southern desert dust events, which could alter sediment dynamics in areas where southern winds prevail. While these events are less common, they may still affect the sediment supply and redistribution, introducing periodic variability that the model does not currently account for. Therefore, the model represents a baseline condition for aeolian deposition, and the results should be interpreted as such, acknowledging that episodic, high-intensity events could introduce significant periodic variability not captured in our simulations. From a broader perspective, improving future model representations could involve incorporating wave–current coupling through SWAN or similar modules, refining grid resolution near deltas, and coupling sediment transport with biogeochemical indicators such as turbidity and particulate organic matter. These extensions would enable multi-objective simulations linking physical, chemical, and ecological dynamics, providing a more complete understanding of how sediment accumulation affects water quality and ecosystem functioning.

Moreover, the length-fetch model employed in Delft-FM for wave generation is a simplified approach. While computationally efficient, it does not capture the full complexity of wave dy489 namics in the same way a dynamically coupled spectral wave model (e.g., SWAN) would. This simplification should be considered a key limitation of the current study, as it likely reduces the accuracy of wave-induced bed shear stress calculations. We explicitly acknowledge that this may affect the absolute values of the predicted shear stress, particularly in this shallow, wind-dominated basin and most notably during high-energy storm events, where wave-current interactions are most critical. Future work incorporating a fully coupled wave model would provide a more refined assessment of these processes and improve the accuracy of sediment transport predictions under extreme conditions.

6 Conclusion

Understanding fine sediment accumulation rates across the NG is crucial for gaining a clearer picture of the region’s environmental dynamics. Radiometric techniques provide precise measurements of sediment accumulation, significantly enhancing the accuracy and reliability of numerical modeling. This approach was successfully applied in the current study and could be adopted elsewhere, offering valuable insights into sediment transport and deposition patterns. Sediment deposition processes are key to understanding nutrient cycling, pollutant trapping, and habitat health, all of which are critical for the sustainability of coastal and offshore ecosystems. By identifying areas of high accumulation, such as near the Shatt al-Arab delta, Kuwait Bay, and southern Boubyan Island and comparing them with offshore zones of lower influence, we gain a deeper understanding of the NG’s sedimentary behavior. It is crucial, however, to recognize that these findings are specific to the cohesive, fine fraction of the sediment bed. Future work is needed to integrate coarse sediment dynamics for a complete picture of the region’s morphodynamics.

In the context of climate change, the increasing frequency and intensity of extreme heat waves are expected to expand arid regions, creating more dry landscapes that serve as additional sediment sources in the Middle East. These sediments, transported by winds and episodic floods, are likely to be deposited in the NG, increasing accumulation rates and widening existing fine sediment patches. Such changes could significantly impact benthic habitats, nutrient dynamics, and broader ecosystem interactions. These findings highlight the importance of combining advanced monitoring techniques with robust numerical modeling to anticipate and mitigate the impacts of climatic and human-driven changes, ensuring effective management and protection of the Gulf’s marine and coastal environments.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author contributions

YA: Conceptualization, Formal Analysis, Validation, Visualization, Writing – original draft, Writing – review & editing. AA: Data curation, Formal Analysis, Methodology, Writing – original draft. AA-R: Formal Analysis, Resources, Writing – review & editing. MA-K: Formal Analysis, Investigation, Resources, Writing – review & editing. DA-H: Project administration, Resources, Writing – review & editing.

Funding

The author(s) declared that financial support was received for this work and/or its publication. Parts of this work was financially supported by the Kuwait Foundation for the Advancement of Sciences (Project No. 2012-1401-01). Additionally, data from KISR-funded project EC010O were utilized in this study. The Authors sincerely appreciate this support.

Acknowledgments

This study was conducted as a continuation of previous collaborative research between the Kuwait Institute for Scientific Research (KISR, Kuwait) and Deltares (The Netherlands).

Conflict of interest

The authors declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that generative AI was used in the creation of this manuscript. Artificial intelligence (AI) was used only to improve the clarity, grammar, and readability of the English language in the manuscript. AI was not used to generate scientific content, research ideas, methodology, data handling, modeling configurations, simulations, analyses, results, interpretations, figures, or conclusions. All numerical modeling work, radiometric analyses, data processing, scientific reasoning, and original contributions are entirely the work of the authors.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

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Supplementary m,aterial

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmars.2025.1749824/full#supplementary-material

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