1 Introduction

Grain size parameters of beach sediments provide wealthy geological information on sediment transportation history, depositional environment, and sedimentary geochemistry (Folk and Ward 1957; Medina et al. 1994; le Roux and Rojas 2007; Nugroho and Putra 2018; Lepesqueur et al. 2019; Woodruff et al. 2021). The statistical parameters in grain size analysis such as mean, standard deviation, skewness, and kurtosis are used to characterize textural parameters in both modern (unconsolidated sedimentary archives in age from a few years to maximum hundreds of years) and ancient beach sediments (Spencer 1963; Pedreros et al. 1996; Nugroho and Putra 2018). Grain size distribution is controlled by several factors such as mainly source composition, weathering, climate, and hydrodynamic changes. Accordingly, spatial and temporal changes in grain size parameters are used to understand coastal processes (e.g., net, longshore, and cross-shore sediment transportation) along with hydrodynamics and engineering applications (Amalan et al. 2018; Ratnayake et al. 2018; Gunasinghe et al. 2021). For example, beach nourishment (i.e., additional sediments place on or near the beach to protect coastal structures) improves beaches for recreation, and creates new habitats/ecological values (Dean 2002; de Schipper et al. 2021). Sediment grain size is a critical parameter in the beach nourishment process, affecting (i) stability (larger grain sizes like gravel, and cobble are resistant to erosion), (ii) beach profile (selection of sediment grain size depends on the desired beach profile), (iii) habitat (coarse sediments provide better habitat for larger organisms like crabs, whereas fine sediments provide better habitat for smaller organisms like worms), and (iv) cost (coarse grains are generally having high operation cost) (Ratnayake et al. 2019; Gunasinghe et al. 2022; Saengsupavanich et al. 2023).

Textural characteristics of beach sand also affect the nesting process of sea turtles (Siqueira-Silva et al. 2020). There are seven marine turtle species living in the world, and five of them including Green Turtle (Chelonia mydas), Olive Ridley (Lepidochelys olivacea), Hawksbill (Eretmochelys imbricata), Loggerhead (Caretta caretta), and Leatherback (Dermochelys coriacea) select southern coastal belt of Sri Lanka as their nesting sites. Sri Lanka is thus located at a unique geographical location in the Indian Ocean, at the southern tip of the Indian subcontinent (Fig. 1). The shape of Sri Lanka like a droplet promotes a dynamic beach environment with active longshore currents (Amalan et al. 2018). Accordingly, beach erosion is one of the main issues in coastal zone management (Palamakumbure et al. 2020; Ratnayake and Perera 2022), and a few researchers focus continuous attention to study coastal erosion in Sri Lanka (Lin and Pussella 2017; Senevirathna et al. 2018; Weerasingha and Ratnayake 2022). However, the impacts of grain sizes on coastal erosion are poorly investigated yet in Sri Lanka.

Fig. 1
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Map of Sri Lanka showing sampling locations and different geographical quadrants (Refer to Additional file 1 for sampling locations)

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Although grain size analysis is a fundamental study, the understanding of textural characteristics in Sri Lanka addresses several potential research gaps in geological research, engineering applications, ecological conservation, and coastal management. In addition, the current study is the first attempt to study grain size distribution, covering the entire coastline of Sri Lanka (Fig. 1). Consequently, this case study provides baseline data to answer several important and unresolved questions in multidisciplinary research.

2 Study area

The coastline of Sri Lanka consists of different geological features such as mainly beaches, lagoons, estuaries, bays, mangrove swamps, brackish lakes, and rocky cliffs. These landforms contain different types of clastic materials such as clay/silt, sand, and boulder rocks. However, the current study focuses on about 1620 km long sandy beaches in Sri Lanka (Fig. 1). Sri Lanka consists of three major climatic zones, namely the wet zone (covering mainly the southwest region and central highlands), dry zone (predominantly northern and eastern parts), and intermediate zone (Fig. 1). According to the geological framework, about 90% of the basement of Sri Lanka is composed of Precambrian high-grade metamorphic rocks (Cooray 1994; Kröner et al. 1994), and it is subdivided into crustal blocks of Highland Complex, Vijayan Complex, Wanni Complex, and Kadugannawa Complex (Fig. 1). The southwest part of Sri Lanka faces the Laccadive Sea, and the northwest part is positioned in the Mannar Basin between the landmasses of Sri Lanka and India (Fig. 1). The eastern part of the country is geographically located in the Bay of Bengal (Fig. 1). In addition, the west and east coasts of Sri Lanka are influenced by mainly southwest (Northern Hemisphere summer) and northeast (Southern Hemisphere summer) monsoon currents, respectively.

3 Materials and methods

Beach sediment samples were systematically collected from beach berms based on accessibility to the coasts, at 90 locations using a hand shovel. A berm is a nearly horizontal and parallel ridge on the beach that contains relatively coarse sand deposited by low-energy waves. Accordingly, sampling sites are located about 1–2 m above the mean sea-level. In this study, sampling locations were divided into four geographical zones such as southwest (n = 30, from Kiralakale to Browns Beach), northwest (n = 24, from Nainamadama to Point Pedro), northeast (n = 16, from Manatkaadu to Sallathive), and southeast (n = 20, from Pasikuda to Hambantota) regions (Fig. 1, and refer Additional file 1 for specific locations of the samples). The collected samples were transferred into a pre-labeled airtight container. Samples were mixed thoroughly for homogenization. Bulk samples were reduced using the coning and quartering method, and 600 g portion of the sample was selected for laboratory analysis.

These representative samples were then washed with distilled water to remove salt and shell particles. Samples were oven dried at 120 °C for 4 h before sieving. The dried sediment samples were split again to obtain about 450 g of samples using the standard Riffle Splitter, while the remaining samples were kept for further reference. Mechanical sieve analysis was done at ¼ phi intervals (BS sieves) between mesh #10 and #230 for 20 min using a digital sieve shaker (Endecotts EFL 2000). After that, the sieved materials were collected and weighed. The data of the grain-size weight obtained after sieving was processed using GRADISTATV9.1 software. The GRADISTAT software was used to calculate all the statistical parameters such as mean size, sorting, skewness, and kurtosis (Folk and Ward 1957; Blott and Pye 2001).

4 Results and discussion

4.1 Grain size variations

Descriptive statistical parameters such as mean size (µm), sorting (σI), skewness (SkI), and kurtosis (KG) of the grain size analysis are shown in Table 1. The spatial variation of mean grain size is shown in Fig. 2a. The mean grain size indicates the overall average size or central tendency of the entire distribution of sediments. Therefore, the mean grain size is an indicator to explain the energy of deposition environments. Generally, the finer sediments are found in a low-energy regime and the coarser sediments are found in a high-energy environment (Bhattacharya et al. 2016; Saengsupavanich et al. 2023). Wave/tidal actions, littoral currents, river discharges (or runoff), and source area compositions are also important factors to control the sediment composition of the coastal area (Venkatramanan et al. 2011; Mohanty et al. 2023).

Table 1 Descriptive statistical parameters of grain size analysis
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Fig. 2
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Spatial variation of (a) mean grain size and (b) sorting for beach sediments (n = 90) in Sri Lanka

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The mean grain size values of the southwest region of Sri Lanka vary from 108.2 to 599.2 µm, with an average grain size of 334.5 µm (Table 1). Similarly, the mean grain size values of the northwest region of Sri Lanka vary from 189.4 to 609.8 µm, with an average grain size of 335.6 µm (Table 1). Therefore, both southwest and northwest regions of the country mainly consist of medium sand quantitatively 57% and 63%, respectively (Fig. 2a and Additional file 1). The mean grain size values of the northeast region of Sri Lanka range from 116.5 to 501.9 µm, with an average grain size of 248.1 µm (Table 1). The mean grain size values of the southeast region of Sri Lanka range from 175.2 to 525.9 µm, with an average of 321.8 µm (Table 1). Consequently, the northeast and southeast parts of the country consist of mainly medium sand (44% in northeast and 71% in southeast) with some amount of fine sand (44% in northeast and 24% in southeast) (Fig. 2a and Additional file 1). According to the textural classification based on Blott and Pye (2012) gravel-sand-mud ternary diagram (Fig. 3) and grain size distribution (Fig. 4), beach sediments mainly consist of sand (99.40%), and a minor amount of gravel (0.54%) and mud (0.05%). These observations suggest moderate energy depositional environment/wave action around the coastline of Sri Lanka. Furthermore, the grain size variations show that climatic zonation (e.g., wet, dry and intermediate climatic zones in Fig. 1) has less impact on the variation in the textural characteristics of beach sediments along the coastline of Sri Lanka. Since samples were collected from the passive layer (beach berm), seasonal variations and the current transport events are limited in grain size parameters.

Fig. 3
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a Blott and Pye (2012) gravel-sand-mud classification for (b) beach sediments (n = 90) in Sri Lanka

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Fig. 4
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Grain size distributions for (a) southeast, (b) northeast, (c) northwest, and (d) southwest

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Although Sri Lanka is generally composed of medium sand, the northeast part of the country mixes with fine sand (Figs. 2a, and 4). This observation can indicate the influence of the Bengal submarine fan system. Previous studies suggest that distal Bengal submarine fan sediments record about 800 km south of the equator such as in the Ocean Drilling Project (ODP) Leg 116 at 1°S (Curray 1991; Curray and Munasinghe 1991; Brune et al. 1992; France-Lanord et al. 1993; Alam et al. 2003; Mukherjee et al. 2009).

4.2 Standard deviation (σ1) and skewness (SkI)

The standard deviation measures the scatter of grain size values from the mean (Table 1), and it indicates the spread or sorting of the sample (Fig. 2b). For example, the lower standard deviation values indicate well-sorted samples under low-energy depositional conditions (López 2017; Yun et al. 2023). The sorting values of the southwest region of Sri Lanka range from 1.307 to 2.104, with an average of 1.621 (Table 1), suggesting moderately sorted samples (Fig. 2b). The sorting values of the northwest region vary from 1.330 to 2.436, with an average of 1.709 (Table 1), indicating moderately to poorly sorted samples (Fig. 2b). However, the sorting values of the northeast (1.305 – 1.817, average = 1.518) and southeast (1.444 – 1.755, average = 1.620) regions suggest moderately to well-sorted samples (Fig. 2b). Accordingly, these observations show that the eastern coasts of Sri Lanka are subjected to low-energy oceanic currents compared to west coasts of Sri Lanka. Therefore, the energy of the northeast monsoon current is less compared to the southwest monsoon current (Fig. 1), due to the northeast monsoon winds passing the land areas and the thermal contrast being relatively low (Webster et al. 1998).

The skewness measures the normality or symmetry of the frequency distribution. The skewness also reflects the variation in the energy conditions of the sedimentary process (López 2017; Mohanty et al. 2023). The skewness values of the southwest region of Sri Lanka range from -0.251 to 0.197 with an average of 0.037 (Table 1), and beach sediments show symmetrical (63%) distribution. The skewness values of the northwest region range from -0.166 to 0.446, indicating that symmetrical (46%) distribution (Additional file 1). The skewness values of the northeast (56%) and southeast (85%) regions also show symmetrical distribution. Consequently, symmetrical distribution can indicate a moderate energy depositional environment around the coastline of Sri Lanka.

4.3 Kurtosis (KG)

The kurtosis measures peakedness (or broadness), and it is used to describe the departure from the normal distribution. The variations in the velocity of the transportation mode are emulated in the kurtosis values. The kurtosis values of the southwest region of Sri Lanka range from 0.826 to 1.435, with an average of 1.065 (Table 1). The entire area shows 7% platykurtic (the central part is better sorted than the tails), 73% mesokurtic (the central and the tails have uniform sorting), and 20% leptokurtic (tails are better sorted than the central). The kurtosis values of the northwest region range from 0.815 to 1.495, with an average of 1.102 (Table 1). The northwest region shows 8% platykurtic, 50% mesokurtic, and 42% leptokurtic (Additional file 1). In the northeast region, the kurtosis values range from 0.869 to 1.317, with an average of 1.058 (Table 1). The entire area shows 18% platykurtic, 44% mesokurtic, and 38% leptokurtic (Additional file 1). The kurtosis values of the southeast region range from 0.850 to 1.215, with an average of 1.068 (Table 1). The entire southeast region shows 5% platykurtic, 57% mesokurtic, and 38% leptokurtic (Additional file 1). According to the kurtosis values, all four regions indicate a leptokurtic to platykurtic nature, and the average values of the kurtosis in all regions suggest mesokurtic nature. Variations in kurtosis values indicate changes in the flow characteristics of the deposition medium (Baiyegunhi et al. 2017). For example, extremely high or low values of kurtosis imply that a part of the sediment is sorted elsewhere in a high-energy environment. In addition, the kurtosis values reveal the maturity of sands through the predominance of rounded fine-grained particles with platykurtic mesokurtic nature (Baiyegunhi et al. 2017). Therefore, beach sediments in Sri Lanka indicate moderate to low-energy depositional environments, and variations in sorting values due to the continuous addition of fine/coarse materials in varying proportions.

4.4 Importance of grain size distribution

Beach nourishment is the process of depositing additional sediment on or near the beach to enhance beach safety and protect buildings and infrastructure from wave attacks (Dean 2002; Hamm et al. 2002; McLachlan and Brown 2006; de Schipper et al. 2021; Saengsupavanich et al. 2023). Coastal erosion and reduced sediment supply are major natural threats to the coastline in Sri Lanka (Amalan et al. 2018; Ratnayake et al. 2018; Gunasinghe et al. 2021). Therefore, beach nourishment has been proposed as a potential soft engineering structure to control beach erosion along the coastline around Sri Lanka. However, several case studies such as at Uswetakeiyawa and Mount Lavinia beaches questioned the applicability of beach nourishment projects in Sri Lanka (Ratnayake et al. 2019; Gunasinghe et al. 2022), due to the impacts of the grain-size distribution of nourishment sand and prominent longshore currents along the coastlines.

Sediment compatibility is one of the main factors to consider in beach nourishment projects, and it refers to the degree of similarities between nourished sediments and native sediments (Dean 2002). There are various methods for quantifying compatibility, some of which consider only the mean or median diameters of native and borrow materials and some of which consider other parameters such as grain size distributions for sorting (Dean 2002; Saengsupavanich et al. 2023). In more traditional usage, the grain size of nourishing sediments needs to be equal in size to original/native beach sediments (van der Wal 1998; Hartog et al. 2008; Castelle et al. 2009). However, introducing coarser sediments such as gravel can make beaches more stable, but there are differences in habitat associated with the different types of sediments used in nourishment operations. Therefore, gravel filling can change beach morphology and may have ecological impacts (McLachlan and Brown 2006; Saengsupavanich et al. 2022).

Grain size analysis is important in geological research for understanding the physical properties of sedimentary rocks (e.g., strength), depositional environments, sediment transportation/monitoring erosion, and reconstructing past landscapes and environmental conditions (Saengsupavanich et al. 2022; Ratnayake et al. 2023). In addition, grain size analysis provides important information in ecological conservation for understanding habitat suitability, water quality and resource availability, and nutrient cycling (Siqueira-Silva et al. 2020). Furthermore, this type of case study can be applied in coastal management, planning coastal development, evaluating coastal restoration projects, and resource management. Consequently, the case studies on sediment characteristic analysis can apply to develop public policies, support sustainable development strategies, and promote environmental health and safety elsewhere.

5 Conclusions

Grain size variations confirmed a relatively high energy deposition environment on the west coast and a low energy deposition environment on the east coast. Therefore, the impact of southwest monsoon currents is more prominent in the landform changes in Sri Lanka. In addition, these statistical parameters suggested west coast is more vulnerable to coastal erosion compared to the east coast of Sri Lanka. The distal Bengal submarine fan sediments may have controlled the grain size variations on the northeast coast, whereas climatic zones and geological/lithotectonic units have no direct impact on the sediment distribution in Sri Lanka. Sediment grain size changes and statistical parameters can be applied for various future forecasting such as in beach nourishment projects in Sri Lanka.