The research team, led by scientists at the Department of Geology of the University of Dhaka, collected 34 sediment samples along a land-sea transect spanning three environmentally contrasting areas: Cox’s Bazar on the eastern coast, Kuakata in the central deltaic zone, and the Sundarbans mangrove forest in the west. Sampling took place during winter, within the intertidal zone at elevations of roughly 0.5 to 4 meters above mean sea level, with cores extracted to a depth of 30 centimeters using a hand auger at low tide. Each sample was dried at 60 degrees Celsius for 24 hours, and 100-gram aliquots were sieved through meshes ranging from 63 to 1000 micrometers at one-phi intervals, following the Wentworth grain-size scale. Mean grain size and sorting were calculated using the Folk and Ward method.

The three study areas could hardly be more different. Cox’s Bazar, home to one of the longest natural beaches on Earth at 145 kilometers, is dominated by fine and medium sand, with fine sand reaching up to 75.1 percent of a sample and averaging 48.2 percent, while mud fractions are scarce. Kuakata displays a mixed picture: sediments at the Tin Nodir Mohona river mouth average 62.4 percent coarse sand, whereas the nearby Jhau Bon and Lebu Bon sites are rich in fine and very fine sand. The Sundarbans, the world’s largest mangrove forest covering roughly 6017 square kilometers, is a low-energy setting where fine and very fine sand dominate, averaging 59.5 and 27.2 percent respectively. These textural contrasts reflect fundamentally different hydrodynamic regimes, from wave-dominated open coast to tide-swept estuary to sheltered, freshwater-influenced mangrove plain.

When the researchers examined the foraminifera preserved in these sediments, the diversity patterns mapped almost perfectly onto the sediment map. Cox’s Bazar yielded 36 species across 26 genera, the highest diversity of the three areas, with Fisher’s alpha index ranging from 9.95 to 17.06 and Shannon values between 2.71 and 3.23. Kuakata produced 32 species from 20 genera with intermediate indices, while the Sundarbans assemblage contained only 19 species from 14 genera, the lowest diversity, with Fisher’s alpha falling as low as 4.89. The single most diverse site was Inani beach in Cox’s Bazar, and the least diverse was Kotka in the Sundarbans, a contrast that the authors link directly to substrate texture and the ecological conditions it implies.

The composition of the assemblages was equally revealing. The genera Ammonia and Elphidium dominated throughout the entire coastline, demonstrating their remarkable ecological tolerance, but each region carried a distinctive signature of companion taxa. Cox’s Bazar was characterized by Rotalinoides, Ammonia, Elphidium, and Asterorotalia, with mean relative abundances of 17.9, 17.4, 12.8, and 9.3 percent respectively. Kuakata was overwhelmingly dominated by Elphidium and Cribroelphidium at 33.8 and 20.7 percent, alongside several Ammonia species. In the Sundarbans, Ammonia reached individual-sample abundances of up to 55.6 percent, accompanied by Rosalina, Haplophragmoides, Entzia, Haynesina, and Trochammina, a suite of stress-tolerant and salt-marsh agglutinated forms typical of fine-grained, organically enriched, freshwater-influenced environments.

To test whether these patterns were statistically robust rather than coincidental, the team deployed a battery of complementary analyses. Spearman’s rank correlation across the combined 34-sample dataset showed that 18 of the 30 analyzed genera had at least one statistically significant association with a sediment fraction. Medium sand emerged as the fraction with the strongest biological signal: twelve genera, including Amphistegina, Spiroloculina, Cibicides, Rotalinoides, Neorotalia, and Operculina, showed significant positive correlations with it, while Ammonia, Elphidium, Rosalina, and Haplophragmoides were significantly and negatively correlated, reflecting their preference for finer substrates. The genus Gyroidella stood out as the only taxon significantly and positively correlated with coarse sand while being negatively correlated with both fine and very fine sand, marking it as a specialist of high-energy, coarse-grained settings.

Canonical correspondence analysis reinforced these findings in striking visual terms. The first two ordination axes together accounted for 90.9 percent of the constrained species-environment variance, with Cox’s Bazar samples aligning strongly with medium sands and Sundarbans samples clustering consistently with finer grains. Species vectors in the biplot closely tracked the sediment gradients, and the analysis independently reproduced the genus-substrate affinities identified by the correlation analysis. Finally, a two-way PERMANOVA based on Bray-Curtis dissimilarity and 9999 permutations confirmed that both location and sediment category significantly structured the assemblages, with p-values of 0.0001 and 0.0031 respectively. Crucially, the interaction term was not significant, meaning that sediment grain size exerts the same directional effect on community composition regardless of which of the three coastal environments is considered.

Why should grain size matter so much to organisms barely visible to the naked eye? The authors point to an indirect but well-supported mechanism: fine-grained sediments have greater surface area and adsorption capacity and are typically associated with higher organic matter concentrations, which in turn can deplete oxygen in the uppermost sediment layer. Although organic matter and dissolved oxygen were not directly measured in this study, a limitation the authors openly acknowledge, the dominance of opportunistic and stress-tolerant taxa such as Ammonia, Elphidium, and agglutinated forms in the Sundarbans is consistent with assemblages known from organically enriched coastal settings worldwide. The reduced diversity there likely reflects these stressed conditions, where a few tolerant species outcompete the rest.

The assemblages also encode hydrodynamic history. At Inani beach in Cox’s Bazar, the researchers found transported planktonic foraminifera, including Globigerina bulloides and Hantkenina alabamensis, species that live in the open water column and could only arrive on the beach through active wave and tidal transport. Their presence signals a well-connected, open-marine setting characteristic of the inner to middle neritic zone, rather than evidence of local productivity. In Kuakata, the combination of Elphidium, Cribroelphidium, Ammonia, and various miliolids, together with the complete absence of planktonic species, points to estuarine to very inner neritic conditions. In the Sundarbans, salt-marsh agglutinated foraminifera such as Trochammina inflata, Miliammina, Haplophragmoides, and Entzia were confined to areas under strong freshwater influence, echoing ecological patterns reported from karstic coasts of the Adriatic.

Beyond its scientific interest, the study carries practical weight for a coastline facing mounting natural and anthropogenic pressures, from sea-level rise to pollution and sediment starvation. By establishing sediment texture as a tractable, measurable, and directly comparable control on foraminiferal diversity, the work provides a framework for using these microfossils as bioindicators in environmental assessment. The authors recommend that future investigations incorporate direct measurements of organic matter, dissolved oxygen, salinity, and sediment mineralogy to refine the picture. For now, the message from the northern Bay of Bengal is clear: the grains on the seafloor, and the energy that arranges them, set the rules by which life at the smallest scale thrives or struggles, and reading those grains through the lens of foraminifera offers a powerful window into the health of coastal ecosystems under change.

Subject of Research: Relationship between sediment grain size and benthic foraminiferal diversity across contrasting coastal environments of Bangladesh

Article Title: Spatial patterns of benthic foraminiferal diversity in relation to sediment type across contrasting coastal environments of Bangladesh

Article References: Al Kabir, M. S., Saha, S. K., Tushar, M. A. N., & Maria, R. S. (2026). Spatial patterns of benthic foraminiferal diversity in relation to sediment type across contrasting coastal environments of Bangladesh. Discover Geoscience, 4(1), Article 344. https://doi.org/10.1007/s44288-026-00712-1

Image Credits: AI Generated

DOI: 10.1007/s44288-026-00712-1

Keywords: benthic foraminifera, sediment grain size, Bay of Bengal, Bangladesh coast, Sundarbans, Cox's Bazar, Kuakata, PERMANOVA, canonical correspondence analysis, coastal biomonitoring, microfossils, Ganges-Brahmaputra-Meghna delta

Led by Md. Khairul Amin and G. M. Jahid Hasan of the Department of Civil Engineering at the Military Institute of Science and Technology in Dhaka, the study tackles a notorious modeling gap. Previous efforts along the Bangladesh coast typically validated either water level or wave height in isolation, leaving current velocity largely untested. The new model, built on the widely used Delft3D suite, closes that gap by coupling a hydrodynamic component with the SWAN spectral wave model and confronting both against real observations at multiple coastal stations. The payoff is impressive: Pearson correlation coefficients ranging from 0.79 to 0.99 and Nash-Sutcliffe efficiency values of 0.72 to 0.99 across all tested parameters.

The challenge the model confronts is extraordinary. The Bay of Bengal’s distinctive geometry, a wide continental shelf in the west that narrows sharply toward the southeast, combined with the enormous freshwater discharge of the Ganges-Brahmaputra-Meghna river system, creates a uniquely complicated hydrodynamic environment. Bangladesh’s coastal zone covers roughly 47,201 square kilometers and is home to approximately 46 million people, much of it sitting only a few meters above mean sea level. Tides here are predominantly semi-diurnal and amplify toward the head of the bay, while monsoon winds, river discharge, and tropical cyclones all modulate water levels, wave activity, and current patterns in ways that defy simple prediction.

Technically, the model domain stretches from 18 degrees north to 23 degrees north and from 83 degrees east near Vishakhapatnam, India, to 95 degrees east near Gwa beach in Myanmar. The hydrodynamic component employs a curvilinear-orthogonal grid of roughly 27,000 cells with variable resolution, refined to 100-200 meters along the intricately sculpted coastline near the Meghna Estuary and coarsened to 10-15 kilometers near the open ocean boundaries. Bathymetry was drawn from the GEBCO 2020 dataset at 15 arc-second resolution, while tidal forcing at the open boundaries came from the TPXO 8.0 global inverse tide model using 13 principal harmonic constituents. Upstream river boundaries were driven by hourly discharge measurements from the Padma and Upper Meghna rivers.

Atmospheric forcing derives from the European Centre for Medium-Range Weather Forecasts’ ERA5 reanalysis, with hourly 10-meter wind fields and mean sea level pressure at 0.25-degree resolution. The SWAN wave component runs on a separate rectangular grid and incorporates third-generation physics, including depth-induced breaking via the Battjes-Janssen formulation, JONSWAP bottom friction, nonlinear triad interactions, and a phase-decoupled refraction-diffraction approximation. Crucially, the researchers employed online two-way coupling between the wave and flow models, allowing radiation stress gradients, enhanced bed shear stress, wave boundary layer streaming, turbulence mixing, and Stokes drift to be exchanged dynamically between components at every coupling interval, capturing the feedback between waves and currents that is essential during energetic monsoon conditions.

Calibration against observed tide levels and ERA5 wave heights during June 2020, a period spanning a full spring-neap tidal cycle under active monsoon conditions, produced tide-level correlations of 0.88 to 0.99 and Nash-Sutcliffe values of 0.91 to 0.99. Independent validation for October 2020 under contrasting post-monsoon conditions confirmed the model’s robustness, with tide-level correlations holding between 0.86 and 0.99. Perhaps most notably, simulated current velocities at Payra Port achieved a correlation coefficient and Nash-Sutcliffe efficiency of 0.80 each, reasonably capturing the temporal rhythm and dominant directions of the semi-diurnal tidal currents, though the authors note a strongly negative percentage bias that reflects the metric’s known sensitivity to reversing tidal flows rather than a genuine failure of the model.

A year-long simulation for 2020 then revealed the striking spatial texture of the region’s coastal hydrodynamics. At Sandwip, an island adjacent to the tide-dominated Meghna Estuary, water levels ranged from about minus 1.8 meters to nearly plus 2.0 meters relative to mean sea level, and depth-averaged currents commonly reached 1.0 to 1.3 meters per second. At Kuakata on the more open south-central coast, the tidal range was somewhat smaller and currents generally stayed below 0.5 meters per second during neap tides, peaking near 1.0 to 1.1 meters per second at spring tide. Wave heights at Sandwip generally remained below 1.0 meter with a late-August peak of roughly 1.7 meters, while Kuakata’s waves stayed between 0.3 and 0.7 meters most of the time, with mean wave periods of 6 to 11 seconds that are longer and more variable than Sandwip’s estuarine 4.5 to 6.5 seconds.

The model also reproduced recognizable large-scale patterns, including the persistent anticlockwise residual circulation around Sandwip Island documented in earlier studies and the pronounced tidal asymmetry near major estuarine systems. Snapshot comparisons showed flood-tide currents reaching 0.69 meters per second and ebb currents 0.38 meters per second during the monsoon neap-tide snapshot, compared with up to 1.11 and 0.90 meters per second respectively during the post-monsoon spring-tide snapshot, with the strongest currents consistently concentrated in shallow nearshore zones and estuarine channels where bathymetry and channel geometry amplify flow. Mean wave directions clustered predominantly between 160 and 210 degrees, a southerly to southwesterly approach consistent with the monsoon wind field and swell arriving from the southern Indian Ocean. The authors are careful to note that the two snapshots differ simultaneously in tidal phase and season, so they illustrate spatial structure rather than isolating a pure seasonal effect.

The study is candid about its limitations. GEBCO bathymetry cannot fully resolve the fine-scale estuarine channels and shoals of the Meghna Estuary, and ERA5’s relatively coarse resolution may smooth localized nearshore wind gradients and coastline-induced variability, meaning wave validation is effectively a comparison against reanalysis fields rather than fully independent observations. Current-velocity validation rests on a single station, and the model is accordingly best suited for regional-scale assessment of tide-wave-current variability rather than absolute sediment-flux estimates or site-specific engineering predictions. The researchers recommend future evaluation against satellite altimetry wave products and in situ buoy records, along with higher-resolution hydrographic surveys and nested local models for areas of specific engineering interest.

Even with those caveats, the significance for Bangladesh is hard to overstate. A physically consistent, statistically validated coupled model of the northern Bay of Bengal provides exactly the platform needed for storm surge forecasting, disaster preparedness, early warning systems, coastal infrastructure design, and long-term climate change impact assessment in a region where sea-level rise and intensifying cyclones threaten millions. By demonstrating that a single coupled framework can simultaneously simulate tides, waves, and currents with good-to-excellent skill, the Dhaka team has established a regional baseline onto which future studies of compound flooding, sediment transport, morphodynamics, and coastal protection interventions can build. For the 46 million people living along this vulnerable deltaic edge, better models mean better warnings, and better warnings mean lives saved.

The statistical metrics used to judge the model deserve a brief explanation for readers outside the field. Pearson’s correlation coefficient measures how closely simulated and observed values move together in time, while the Nash-Sutcliffe efficiency compares the model’s errors against the simple baseline of using the observed mean; a value of one indicates a perfect match, and values above roughly 0.7 are generally considered good for coastal hydrodynamic simulations. The fact that the coupled framework achieved efficiencies as high as 0.99 for tide levels, across both monsoon and post-monsoon conditions, indicates that the model captures not only the timing of the semi-diurnal tidal signal but also its amplitude through spring-neap cycles.

The choice of a full annual simulation spanning 2020 is itself methodologically significant. Many earlier regional studies focused on single cyclone events or short calibration windows, which can overstate skill because a model tuned to one tidal or wind regime may fail when conditions shift. By testing against the June monsoon period, when southwesterly winds and heavy Ganges-Brahmaputra-Meghna discharge dominate, and again in October as conditions relaxed, the researchers exposed the model to the two most contrasting hydroclimatic states the coast experiences.

The two-way coupling approach also reflects a broader trend in coastal oceanography. Earlier generations of surge models treated waves and water levels as separate problems, but studies of cyclone events in the Bay of Bengal have repeatedly shown that wave setup and radiation stress gradients can materially alter coastal water levels during storms. By exchanging radiation stresses, bed shear stress, and turbulence terms between the wave and flow components continuously, the new framework provides a physically consistent foundation for the compound-flooding and storm-surge applications that regional disaster planners increasingly demand.

Subject of Research: Coupled wave-hydrodynamic modeling of tides, waves, and currents in the northern Bay of Bengal

Article Title: Two-dimensional coupled wave-hydrodynamic modeling of the northern Bay of Bengal

Article References: Amin, M. K., & Hasan, G. M. J. (2026). Two-dimensional coupled wave-hydrodynamic modeling of the northern Bay of Bengal. Discover Oceans, 3(1), Article 54. https://doi.org/10.1007/s44289-026-00167-9

Image Credits: AI Generated

DOI: 10.1007/s44289-026-00167-9

Keywords: Bay of Bengal, Bangladesh coast, Delft3D, SWAN wave model, tidal hydrodynamics, storm surge, coastal modeling, Meghna Estuary, monsoon, ERA5 reanalysis, current velocity, climate resilience