The most essential element of the ecosystem that sustains life on Earth is water [1]. Water quality refers to the water's temperature, chemical, biological, and physical characteristics [2]. Climate, location, terrain, and geological structure are just a few of the variables that affect water quality [3]. The primary issues with water quality in Bangladesh are salinity, arsenic (As) [4]. Total dissolved solids (TDS) and conductivity, also known as electrical conductivity (EC), are commonly employed as indicators of water quality which are used to describe salinity level particularly in coastal areas [5]. The term "total dissolved solids" (TDS) refers to the total amount of dissolved solids in water, which measures the quantity of material dissolved in water [6,7]. TDS is measured in grammes per litre (gL-1) and is often known as part per million (ppm). However, determining TDS is crucial for understanding water salinity levels, particularly in regions encircled by the ocean, as in the case of our study area saint martin’s island. On the other hand, the ionic strength of water that permits the flow of electrical current is known as EC. The variety of cations and anions in water is a representation of the ionic strength [8]. EC is measured in (mS/gm). The temperature of the water, as well as the ion's total concentration, mobility, valence, and relative concentration, all affect electrical conductivity (EC). The kind and composition of the dissolved cations and anions in the water determine the relationship between TDS and EC [9]. TDS and EC values are correlated but relationship is not directly linear since the conductive mobility of ionic species is variable [10]. Dissolve oxygen (DO) is the amount of oxygen in water, and it’s measured in milligrams per liter (mg/L). DO is an important indicator of water quality. DO is measured in the field with water and temperature. DO is essential for the survival of fish and other aquatic organisms.

Soil is a very complex ecosystem which is full of useful resources [11]. Soil quality refers to the soil?s capacity to sustain human requirements, preserve and enhance the water and air in the soil and supply nutrients to plants [12]. The sustainability of soil management techniques can be assessed by soil quality assessment [13]. The assessment of soil quality encompasses an examination of the parameters and processes that influence soil [14]. Soil quality parameter includes PH, BM, N2, P, S, B, and K. PH is one of the most crucial physical properties of soil. It significantly impacts solute concentration and absorption within the soil [15]. Nitrogen (N2) is one of the most essential elements in fertilizers. It is the key primary nutrient needed by plants for adequate growth and development and it is a component of all living cells; it is essential for all proteins, enzymes, and metabolic functions associated with energy synthesis and transfer [16]. Phosphorus (P) is a crucial element found in all living cell [14]. It is a vital micronutrient that is essential for the development of plants. Potassium (K) has a significant function in various physiological processes of plants; it is a key component for the development of the plant [17]. Potassium is not a core component of any significant plant structure, but it is essential for numerous physiological processes crucial for plant growth, including protein synthesis and the regulation of water balance [18]. These water and soil quality indicators significantly impact on agriculture. High salinity is a major constraint for agricultural production on coastal lands, reducing yields for most agricultural crops. The impacts of salinity include low agricultural productivity, low economic returns and soil erosions [19]. The very high and very low PH values frequently result in crop failure caused by an imbalance in ionic strength [20]. Nitrogen (N), Phosphorus (P), and Potassium (K) rank among the key elements that are crucial for potato yield [21]. K is a vital nutrient for every plant and significantly influences development and production of potatoes along with the overall condition and strength of the plant [22].

St. Martin's Island is a Bangladesh's only coral island, faces water and soil quality issues. Many researchers work on Soil and Water quality assessment in Saint Martin’s Island but none have shown the correlation between different water and soil quality parameter. We conducted this research on Saint Martin’s Island water and soil quality parameter to fill this research gap. The purpose of this study was to show the correlation between different water and soil quality parameter in Saint Martin’s Island as well as their effect on agriculture. We used a reputable YSI water testing device operating at 556 MPS to analysis water samples. The Soil Resource Development Institute's (SRDI) local laboratory performed the analysis on soils samples. We applied Pearson’s correlation test to find out how water and soil samples were correlated. This study will help to understand what is the relationship between different water and soil quality parameters in Saint Martin’s Island and their effect on agriculture.

Study Area and Samples

Saint Martin Island was selected study area (Figure 1). This little Island in the Bay of Bengal is located between latitudes 20°30′ and 20°39′ N and longitudes 92°18′ and 92°21′ E. The Island is approximately seven square kilometers in size, with a maximum cliff height of 6 meters and an average elevation of 2.5 meters above mean sea level [23]. Bangladesh's St. Martin's Island, a designated marine protected area, is different and predominantly coral-dominated [23]. The island is known to the natives as "Narical Gingira" because of its profusion of coconut trees. St. Martin's Island is inhabited to about 7,000 people. Most of the island is made up of coral reefs. The island's two most prevalent land uses are agriculture and sand. Only 3% of the bodies of water are stationary, like as beels; the bulk are wooded. Agriculture, tourism, fish drying, and fishing are the main economic activities. The number of individuals or observations in a study or experiment is known as the sample size. 40 soil samples and 40 water samples are used in our study.

Figure 1: Study Area Map (St. Martin Island, Bay of Bengal).

Data Collection and Testing

Soil samples were taken from 40 locations across the island, including coastal and inland areas, as primary data, to measure pH, CaCO3, total soluble salt, and organic matter. Water samples from coastal areas and tube wells were collected from 40 sampling locations analyzed by a reputable YSI water testing device operating at 556 MPS (Figure 2). Five physiochemical parameters were measured, including temperature, Total Dissolved Solids (TDS), Electrical Conductivity (EC), Salinity, and Dissolved Oxygen (DO) to assess water quality. Secondary information and data were collected from diverse government and nongovernmental organizations, published paper, articles, literature review and internet. The Soil Resource Development Institute's (SRDI) local laboratory performed the analysis on soils samples.

Figure 2: YSI Water Testing Device Operating at 556 MPS.

Descriptive Statistics of Water Quality Indicator in Saint Martin Island of Bay of Bengal

Table 1 presents the descriptive statistics for key water quality indicators. The mean values indicate elevated averages for Salinity (1.763), Electrical Conductivity (2.226 mS/cm), and Total Dissolved Solids (2.275 g/L). At Salinity 0.765, the median for these parameters significantly lags behind the mean, indicating a strong positive skew in their distributions; this is further corroborated by their low modal values of 0.54 g/L TDS. This skew and high standard deviations such as Salinity 3.955 and TDS 4.141 g/L suggest significant variability and the presence of extreme values. Conversely, Dissolved Oxygen (DO) and Temperature show smaller standard deviations of 0.504 mg/L and 1.521 respectively, along with more symmetric distributions since their means and medians are almost the same.

Table 1: Water quality indicator in Saint Martin Island of Bay of Bengal.

The third result showed that there was a significant positive moderate correlation between electrical conductivity and total dissolved solids in this island; the correlation coefficient was 0.473 at 0.002 significance level (Table 2).

Figure 3: TDS-Salinity and EC-Salinity Relationship.

Table 2: Pearson Correlation Test Results Regarding the Research Hypotheses.

**Significant level at 1% (2- tailed)

The first result showed that there was a significant positive strong correlation between Salinity and Total Dissolved Solids in Saint Martin Island of Bay of Bengal; the correlation coefficient was 0.961 at 0.001 significance level (Table 2). The second result showed that there was significant positive moderate correlation between salinity and electrical conductivity in Saint Martin Island; the correlation coefficient was 0.480 at 0.002 significance level (Table 2).

There was a linear relationship between TDS and Salinity but relationship between EC and Salinity was not directly linear (Figure 3). On the other hand, the relationship between TDS and EC are non-linear [24]. However, Electrical Conductivity and TDS, have a nonlinear connection that is dependent on ionic strength, the average activity of all the ions in the liquid, and the activity of particular dissolved ions [25,26,27].

Table 3: Multiple Linear Regression Model (3 Tables).

Model Summary^b

1. Predictors: (Constant), Total Dissolved Solids, Electrical Conductivity
2. Dependent Variable: Salinity Level

   ANOVAa
   Model		Sum of Squares	df	Mean Square	F	Sig.
   1	Regression	563.677	2	281.839	224.067	.000b
   	Residual	46.54	37	1.258
   	Total	610.217	39

Coefficients^a

a.  Dependent Variable: Salinity Level

Multiple regression was used in our study to assess the ability of two control measures (TDS and EC) to predict Salinity level. R2 the coefficient of determination implies that “Salinity level” is explained 92% by the independent variables. Since p-value is less than 0.05, our hypothesis is significant at 5% level of significance. This implies that the model is significant. When all other independent variables are fixed, one unit change in “Electrical conductivity” will increase “Salinity level” by 0.053. One unit change in “Total dissolved solids” will increase “Salinity level” by 0.903 (Table 3). The correlation coefficient (r) was used to measure the correlation between TDS and EC, and (Choo-in, 2019) explains the degree of this relationship in (Table 4.)

Table 4: Degree of Correlation between TDS and EC [28].

Summary of the Descriptive Statistics of Soil Parameter and Nutrient Variables

Table 5 highlight a summary of the descriptive statistics for soil and nutrient variables. The analysis of pH indicates a mean value of 7.97, with both the mode and median observed at 8.1, and a fairly low standard deviation of 0.566 across the samples. The standard deviation of 0.451 indicates moderate variability, while biological materials present a mean of 0.734, a mode of 0.15, and a median of 0.685. Nitrogen (N?) has a mean concentration of 0.043, which is completely close the median value of 0.04 and the mode of 0.01. It has a minimum Standard deviation of 0.027 points, representing a consistent distribution across samples. On the other hand, phosphorus (P) has an average of 9.08, a median of 6.2, and a mode of 3.1. The dispersion of its values shows some variance with a relatively high standard deviation of 7.32 with a median of 15.75 and a mode of 21.1, Sulfur (S) shows the highest mean value (18.69) with a big standard deviation of 12.99, therefore indicating wide dispersion. Boron (B) exhibits a mean of 0.363, with a mode of 0.15 and a median of 0.31, and a standard deviation of 0.229; specify moderate variation across the sample.

Last of all, Potassium (K) shows a mean of 0.138, a median of 0.105, a mode of 0.03; its standard deviation of 0.129 suggests low variations inside the sampled values. The findings in general show detectable variance in the nutrient profile, which indicates fundamental environmental stressors that influence the ecological stability and socioeconomic-ecohydrological resilience of the perceptive coral island ecology.

Table 5: Summary of the Descriptive Statistics of Soil and Nutrient Variables.

Correlations of Different Soil Parameter in Saint Martin Island of Bay of Bengal

Table 6: Pearson Correlations of Different Soil Parameter in Saint Martin Island o Bay of Bengal.

** Correlation is significant at the 0.01 level (2-tailed).

* Correlation is significant at the 0.05 level (2-tailed).

Table 6 represent correlation coefficient (r) between different soil quality parameter. Correlation coefficient between PH and Phosphorus, Phosphorus and Sulfur are -0.491 and -0.398 perspectively. The relationships are negative and statistically significant at 1% and 5% level. However, highest magnitude of relation is shown by PH and Phosphorus. On the other hand, correlation coefficient between BM and N, S and B, S and K are 0.958, 0.573 and 0.569 perspectively. The relationships are positive and statistically significant at 1% level. However, highest magnitude of relation is shown by Biological Materials and Nitrogen (r=0.958). N and organic matter showed the strongest significant relation (r=0.98) [29]. Sulfur had a significant correlation with other parameters such as B and K [30,31].

Table 7: Multiple Linear Regression Model (3 Tables).

1. Predictors: (Constant), Potassium of Soil, Phosphorus of Soil, Boron of Soil
2. Dependent Variable: Sulfur of Soil               

ANOVA^a

Coefficients^a

1. Dependent Variable: Sulfur of Soil

This multiple regression was used to assess the ability of three control measures (Phosphorus, Boron and Potassium) to predict Sulfur. R2 the coefficient of determination implies that “Sulfur” is explained 55% by the independent variables. Since p-value is less than 0.05, our hypothesis is significant at 5% level of significance. This implies that the model is significant. When all other independent variables are fixed, one unit change in “Phosphorus” will decrease “sulfur” by 0.429. One unit change in “Boron” will increase “Sulfur” by 24.068- and one-unit change in “Potassium” will increase “sulfur” by 43.115. The regression coefficient is statistically significant at 5% level (Table 7).

Effect on Agriculture

In St. Martins Island, farmers stated that there was positive and negative effect of water and soil quality parameters on agriculture. Increased salinity leads to high mortality rates in some trees and results in poor yields of coconuts. In St. Martins, we observed high salinity is a major constraint for agricultural production, reducing yields for most agricultural crops. Under salt stress, agricultural crops have a variety of reactions. Salinity affects the physicochemical characteristics of the soil and the ecological balance of the region in addition to reducing the agricultural productivity of the majority of crops. Low agricultural production, low economic returns, and soil degradation are some of the effects of salinity [32]. Plant development, water and nutrient intake, seed germination, and other morphological, physiological, and biochemical processes combine intricately to produce salinity effects [33,34]. Salinity imposes ion toxicity, osmotic stress, nutrient (N2, K, P, B, S, PH, BM) deficiency and oxidative stress on plants, and thus limits water uptake from soil. Plant phosphorus (P) absorption is greatly decreased by salinity because phosphate ions precipitate with Ca ions [35].

Some elements, potassium (K) and boron (B), have specific toxic effects on plants. Additionally, salinity has an impact on photosynthesis mostly through a decrease in stomatal conductance, leaf area, and chlorophyll content; it also has a little impact on photosystem II efficiency [36]. High K+ concentration is also required for binding tRNA to ribosomes and thus protein synthesis [37]. According to the majority of farmers, salinity has more detrimental impacts on plant development during the reproductive stage. Additionally, recent studies demonstrate that salinity has a negative impact on plant growth and development, impeding enzyme function, seed germination, and seedling growth [38]. K can help plants adjust to biotic and abiotic stresses such diseases, drought, and extremely high or low temperatures [39]. In terms of plant height, a notable reaction was also observed as a result of K. Applying potassium significantly (p < 0.001) affected how many leaves each plant produced [40]. Nitrogen (N), Phosphorus (P) and Potassium (K) are among the most important elements that are essential for crop productivity. Sulphur and Boron showed a significant variation in grain yield. According to numerous authors, phosphorus significantly affected potato yield. One of the best indicators of a soil's chemical characteristics is its PH, which has wide-ranging, potentially beneficial or detrimental effects on agricultural plant growth and nutrient uptake.

The primary issues with water quality in Bangladesh are salinity, arsenic (As). Bangladesh's only coral island St. Martins faces water and soil quality issues. Total dissolved solids (TDS) and conductivity, also known as electrical conductivity (EC), are commonly employed as indicators of water quality which are used to describe salinity level particularly in coastal areas. Soil quality refers to the soil?s capacity to sustain human requirements, preserve and enhance the water and air in the soil and supply nutrients to plants. Soil quality parameter includes PH, BM, N2, P, S, B, and K. Our study aimed to show the correlation between different water and soil quality parameter in Saint Martin’s Island as well as their effect on agriculture. We used a reputable YSI water testing device operating at 556 MPS to analysis water samples. The Soil Resource Development Institute's (SRDI) local laboratory performed the analysis on soils samples. We applied Pearson’s correlation test to find out how water and soil samples were correlated. There was a significant positive strong linear correlation between salinity and total dissolved solids. Analyzed showed positive moderate non-linear correlation between salinity and electrical conductivity. We have seen negative relationship between PH and Phosphorus, Phosphorus and Sulfur. There is positive correlation between BM and N, S and B, S and K. highest magnitude of relation is shown by Biological Materials and Nitrogen (r=0.958). Most of the farmers stated that there was positive and negative effect of water and soil quality parameters on agriculture. Salinity plays negative effect on agriculture among them. Nitrogen (N), Phosphorus (P) and Potassium (K) are among the most important elements that are essential for crop productivity. Sulphur and Boron showed a significant variation in grain yield

Conflicts of Interest

There was no conflict of interest among the authors in this publication

Authors Contributions

Bulbul Ahmmed- Conceptualization, Methodology, Project administration, Resources, Writing original draft.

Shadiqul Islam, Suruj Ali and Ohid Zaman- Sample and data collection.

Acknowledgement

The authors would like to thank Department of Geography and Environmental Studies, University of Rajshahi to arrange this filed work and support to successfully completion of this research. 

Funding

There is no funding in this research.

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