Abstract
The southwestern coastal regions of Bangladesh (SWCRB) are highly exposed to saltwater intrusions brought about through cyclones and storm surges. These salinity intrusions are contributing to soil and water salinity in the coastal areas. This study aimed to determine the impact of these salinity intrusions on the quality of water and soil in three vulnerable coastal areas. In this investigation, water and soil samples were collected and analysed for pH, electrical conductivity (EC) and other trace elements. The analysis found many of the parameters to be higher than the recommended values. The study found that in soil samples there was a significant correlation between OM and ECe dS/m, as well as K and TN; and a highly significant correlation between TN and OM. This study further examined the historical salinity data at low and high tides to determine any patterns occurring alongside storm surges and cyclones. Water salinity statistics were obtained from the three locations of the Bangladesh Water Development Board (BWDB), which neighbours the study area. A Digital Evaluation Model (DEM) predicts the salinity induced by storm gushes in the corresponding impacted zones. Lastly, the study compared projections for future storm surges at current and predicted sea levels. Potential storm gushes circumstances from 1 to 9 m can impact up to 33% of the nation and 97% of the Shyamnagar Upazila. The occurrence of cyclone-related storms will increase and make cultivation and settlement in the region difficult. The predicted sea-level rises and saltwater contamination will intensify the adverse effects of salinity.
Introduction
Bangladesh is a country that is highly susceptible to soil and water salinization due to its geographical location. The reason for Bangladesh’s susceptibility to salinization is due to the ever-present occurrence of cyclones and storm surges annually across the country. Storm surges are disturbances on the sea surface caused by extreme events such as cyclones where wind drag occurs and pressure drops (; ; ). These storm surges can last from several hours up to several days and can encroach up to 10 m inland, bringing with them salinization through saltwater intrusions (; ibid). Saltwater intrusions in the southwestern coastal region of Bangladesh are having devastating consequences on water resources, agriculture and human health. Soil and water resources are essential to life on Earth, having a serious bearing on food and water security, biodiversity, climate, and human well-being (; ). Saline soils are mainly found in arid and semi-arid regions, where evapotranspiration surpasses rainfall. However, they are also found in coastal districts due to seawater infiltration and inundation by coastal tides (). Bangladesh is especially vulnerable to saltwater intrusions, as the country has a vast area of low altitude near the coast and is often subject to tropical cyclones (; ). Saltwater intrusions have detrimental impacts on land, by increasing the soil and surface water salinity (). Salt-affected soils also harm the bioavailability of plant nutrients such as N, P, K, Ca, or Mg (; ; ). Also, the growth potential of legume crops is hampered by saline soil (; ). The high salt content in soil roots is the main obstacle to the intensification of crop production.
The southwestern coastal area of Bangladesh, in the Bay of Bengal, experiences frequent tropical cyclones and their associated storm surges; that flood areas with saline water (). Bangladesh was hit by 154 cyclones between the years 1877 and 1995, many of them included storm surges that went more than 7 m inland (). More recently between the years 2000–2020, there have been eight major cyclones, including Cyclone Sidr in 2007 and its associated storm surge, that affected around 3.45 million people (). Approximately 37% of arable seaside land is currently impacted by fluctuating degrees of soil salinity due to these surges (). Furthermore, 1.02 million hectares (about 70%) of this arable land on the coast is affected by varying degrees of soil salinity in general. The increase in soil and water salinity causes problems within the coastal ecological setting, affecting the cultivation of crops, thus decreasing food security and increasing the shortage of drinking water by significantly reducing the quality of freshwater (). This situation can potentially subject more than 20 million people to the harmful effects of excess salt through food and water resources (). According to the Intergovernmental Panel on Climate Change (IPCC) report, saltwater intrusion in low-lying coastal areas, river deltas and estuaries has increased, leading to salinization of groundwater, surface water and soil resources (). Excessive groundwater Mining has lowered the groundwater level, and rising sea levels have caused seawater to invade coastal aquifers from the ocean, leading to long-term salinization in southwestern Bangladesh (). During the dry season, the flow of the lower Ganges becomes low, and seawater pushes inland saltwater into rivers and canals, through vertical filtration or infiltration into nearby land, resulting in salinization of groundwater and soil, which lasts until the onset of the rainy season (; ). Floods and storm surges caused by severe tropical cyclones such as Sidr (2007) and Aila (2009) are also responsible for the long-term salinization of soil and surface water (Kabir et al., 2016; ). This affects agricultural activities such as plant germination, biomass production and yield, and people’s livelihoods ().
On the Bangladesh Southwestern coast, shrimp and prawn farming has become widespread (). These farms can be for freshwater and saltwater shrimp with saltwater shrimp farming, increasing salinity, especially in the southern coastal areas (). Farmers raise shrimp on their land in saline aquaculture ponds that can contribute to groundwater and soil salinity. Freshwater shrimp farms are, on the other hand, at risk due to saltwater intrusions increasing gher salinity and poisoning the shrimp (). The total area of land affected by salinity in Bangladesh in 1973 was 83.3 million hectares; by 2000, it had risen to 102 million hectares, and by 2009, it reached 105.6 million hectares ().
Another important driving factor increasing soil and water salinization over the previous half-century is climate change (; ). This is because soil and water are closely associated with the atmospheric and climatic schemes through carbon, nitrogen and hydrological rotations. Therefore, the changing climate will impact soil and water processes. Low-lying semi-arid and arid areas are even further exposed to soil and water salinity due to declining groundwater quality and rainfall shortages (). In these areas, irrigation-based cultivation is indispensable, despite causing the salinization of soil and water which can lead to land degradation (). Following rigorous irrigation, soil salinity affects around 40–45% of the Earth’s land and leads to immense economic harm to a universal extent (). One such example is in the Jaffna Peninsula in Sri Lanka where 32.8% of the land and 45% of paddy land have been impacted by salt (). The global average surface temperature in the latter part of the current century (2081–2100) is forecasted to go beyond 1.5–2°C (; ). Around 70% of the global coastal areas are predicted to undergo remarkable sea level rise. Climate change impacts would lead to the increased river and groundwater salinity in Bangladesh’s Southwestern coastal regions by 2050 (). At least 2.9 million poor people are affected by a drinking and irrigation water deficit in the region ().
Due to the threat of increasing salinity, there is a need to study the effects of soil and water salinity in the southwestern coastal region of Bangladesh in the Shyamnagar Upazila, Shatkhira district, where it has caused significant negative effects on crops, fish and livestock production. This study area is adjacent to the low-lying plains at the confluence of the Ganges, Brahmaputra and Meghna (GBM) rivers which cover over 80% of Bangladesh (). These regions at the coast usually have a mean elevation ranging between one and 4 m above mean sea level (MSL) (). Slight variations in the tidal levels can cause sea water to travel far inland, depending on the tidal conditions and freshwater upstream flows (). These low lying areas make the country vulnerable to sea level rises and saline intrusions, as well as other potential extreme weather events ().
The main goal of this research is to analyse the geochemical properties of saltwater and its related compounds, the response to saltwater intrusion in river systems, and the possible areas affected by storm surges in the present and the hypothetical 2100 conditions. Similar studies have been conducted to investigate the effect of cyclones and storm water surges on disaster-prone areas. One such study was conducted in the same Shyamnager Upazila district in Bangladesh (). In the above-mentioned study, water samples were collected from ponds, pond sand filters and deep tube wells in the Buri Goalini and Gabura unions. The authors found that water from the pond sand filters was fit for drinking purposes according to the World Health Organisation (WHO), but water from the ponds and deep tubes were saline and not suitable for drinking purposes. The study by reflects the impacts that extreme weather events have had on the freshwater supplies in the coastal regions of Bangladesh. It is no surprise that years of saltwater intrusions have harmed the country however little is still known about the impacts on the region’s soil and the long-term response to these events. It is important to consider the impact on the soil as well as on the water as these 2 are highly linked and influenced by each other in natural systems. Furthermore, assessing the response to these salinization events over the past decades can assist in pattern identification in how water and soil responds. Recognising these patterns can help the people and governments of disaster-prone areas to better prepare for the after-effects of such extreme weather events, particularly in the agricultural sectors.
Therefore, the objectives of this study are: 1) to assess the primary water and soil parameter results through laboratory tests; 2) to assess the geochemical composition, abundance and effects of saltwater related compounds in soil and water samples in Shyamnagar Upazila; 3) to analyse the relationship of the response to saltwater intrusion at three stations along the Betna-Kholpetua River using historical data and 4) to create a map of the areas commonly affected by storm surges under current conditions and predicted 2100 conditions for Bangladesh and the Shyamnagar Upazila regions.
Methodology
Study Area
The investigation was carried out at the Buri Goalini, Munshigonj and Gabura Unions under the Shyamnagar Upazila of Satkhira District, situated between 22°36′ and 22°24′ north latitudes and between 89°00′ and 89°19′ east longitudes (). The 2011 Bangladesh census identifies a population base of 318,254 in Shyamnagar alone whilst 10% of the nationwide population, 14 million people, reside in the South-western coast (; ; ibid). The main rivers of the region are the Kobadak, Sonai, Kholpatua, Morischap, Raimangal, Hariabhanga, Ichamati, Betrabati, Kalindi and Jamuna. Usual rainfall is 1, 68 mm with a day-to-day temperature fluctuating from 21 to 30°C. The yearly comparative moisture fluctuates between 7 and 80%. The standard deviation of annual precipitation around this expanse differs from 334.0 to 586.3 mm, () previously reported average maximum and minimum temperatures of 27.7 and 15.6°C during the dry season (November–February), 33.2 and 23.3°C during pre-monsoon season (March–May), and 31.7 and 25.5°C during monsoon season (June–October) for the South-western region of Bangladesh ().
The investigated region displays even topography, where the maximum expanse remains within 1 m from sea level. The soils are classified as histosols and are described as having grey, slightly calcareous, loamy soils on river banks and grey or dark grey, non-calcareous clays, mainly containing silts, in the extensive land area across the water bodies (; ; ibid). Histosols form when organic matter is generated fast than it is decomposed, this often occurs in areas prone to flooding, but not freezing, where there is poor drainage (). Saline and exceedingly saline zones enclose approximately 3336.67 and 241.4 ha, corresponding to 41.46 and 36.6% of all the land of the study region (). The pH level usually varies from 5.4 to 7.44 (; ).
Generally, Shyamnagar Upazila soils are highly dominated by silty clay and silty-clay loam texture (fine-textured and plastic in nature) where the presence of clay particles is much (). Clay particles are mainly negatively charged which attract and adsorb positively charged particles to their surface (ibid) Also, lateral movement of water occurs in clay textured soil and that’s why waterlogging conditions develop. When these waterlogging conditions are saline, soil salinity develops (). Cations responsible for salt production, such as Ca2+, K+, Na+, and Mg2+, in the soil, get adsorbed by clay particles. stated that the salinity level of the soil in Shyamnagar Upazila varies from moderate to high. Cation exchange capacity (CEC) of clay or clay loam type soils lie within 15–30 meq/100 g soil or above ().
found that the cation exchange capacity (CEC) of the Shyamnagar Upazila soil varies from 12.0 to 27.6 meq/100 g soil. Also, Shaibur et al. depicted that the status of bicarbonate (HCO3−), sodium (Na), magnesium (Mg) and sulfur (S) were within 366–793 ppm, 7.50–13.50 ppm, 5.11–6.01 meq/100 g soil and 264–431 ppm respectively (). Bangladesh’s coastal zones have undergone key alterations around the previous five decades, mainly due to recurrent and varied natural catastrophes with direct and indirect bearings on land assets and their various uses (). The land is despoiled and disappearing due to the impact of increasing salinity, flooding of low-lying swampy land, deluges, and land attrition due to involuntary and chaotic land exploitation by the inhabitants. This intense variation in land exploitation and alteration of the agricultural system has impeded normal crop production during the year (ibid).
The three most vulnerable unions, Gabura, Burigoalini and Munshiganj located in the Shyamnagar Upazila were the focus areas of this study (Figure 1B). A total of 18 soil samples and 29 water samples were collected in these areas. Data was collected during rainy season in Bangladesh besides the rainy season in Bangladesh coincides with the summer monsoon season (June to mid-October), this season’s rainfall accounts for 75–80% of the total rainfall the country’s annual rainfall ().
FIGURE 1
Soil and Water Sampling
Soil and water samples were collected between the 10th and 13th of July 2019 at the three unions. Samples were collected in bottles that were shaken overnight with 20% nitric acid and rinsed with deionized water to remove internal and external contaminants. Soil samples were collected using a manual auger at a depth of 10–15 cm deep (
Eighteen soil samples were collected within these areas from agricultural fields, ponds, riverbanks, and shrimp ghers. The coordinates and land use information for the soil samples are displayed in Table 1 and the water samples are displayed in Table 2. Photographs of the sites are also shown in Figures 2, 3 for soil and water samples respectively.
TABLE 1
| Union | Sample no. | Land use | Geographical location | |
|---|---|---|---|---|
| Latitude | Longitude | |||
| Gabura | G-1 | Af | 22.2833̊ | 89.2833̊ |
| G-2 | Ps | 22.3021̊ | 89.7143̊ | |
| G-3 | SGs | 22.2812̊ | 89.2791̊ | |
| G-4 | Ps | 22.2849̊ | 89.2852̊ | |
| G-5 | Af | 22.2742̊ | 89.2764̊ | |
| G-6 | Ps | 22.2736̊ | 89.2751̊ | |
| G-7 | Ps | 22.2824̊ | 89.2798̊ | |
| Burigoalini | B-1 | Rb | 22.2453̊ | 89.2467̊ |
| B-2 | Af | 22.2458̊ | 89.2463̊ | |
| B-3 | Ps | 22.2443̊ | 89.2454̊ | |
| B-4 | SGs | 22.2439̊ | 89.2460̊ | |
| B-5 | Ps | 22.2478̊ | 89.2403̊ | |
| B-6 | SGs | 22.2475̊ | 89.2416̊ | |
| B-7 | Af | 22.2478̊ | 89.2403̊ | |
| B-8 | Ps | 22.2430̊ | 89.2452̊ | |
| Munshiganj | M-1 | Af | 23.7053̊ | 88.8527̊ |
| M-2 | Af | 23.7167̊ | 88.9167̊ | |
| M-3 | Af | 23.7182̊ | 88.9132̊ | |
Areas where soil samples were collected and GPS coordinates with land use coded according to sampling source.
Af, Agricultural field soil; Ps, Pond soil; SGs, Shrimp gher soil; Rb, River-bank soil.
TABLE 2
| Union | Sample no. | Land use | Geographical location | |
|---|---|---|---|---|
| Latitude | Longitude | |||
| Gabura | G-1 | Pw | 22.2736̊ | 89.2751̊ |
| G-2 | SGw | 22.2742̊ | 89.2764̊ | |
| G-3 | SGw | 22.2812̊ | 89.2791̊ | |
| G-4 | Rw1 | 22.2915̊ | 89.2702̊ | |
| G-5 | Pw | 22.2824̊ | 89.2798̊ | |
| G-6 | Pw | 22.3021̊ | 89.7143̊ | |
| G-7 | HTw | 22.2833̊ | 89.2833̊ | |
| G-8 | Pw | 22.2849̊ | 89.2852̊ | |
| Burigoalini | B-1 | Pw | 22.2758̊ | 89.2463̊ |
| B-2 | Sw | 22.2439̊ | 89.2460̊ | |
| B-3 | Rw2 | 22.2453̊ | 89.2467̊ | |
| B-4 | RHw | 22.2717̊ | 89.2439̊ | |
| B-5 | RHw | 22.2719̊ | 89.2436̊ | |
| B-6 | Pw | 22.2478̊ | 89.2403̊ | |
| B-7 | Pw | 22.2443̊ | 89.2454̊ | |
| B-8 | PSFw | 22.2471̊ | 89.2412̊ | |
| B-9 | Pw | 22.2713̊ | 89.2440̊ | |
| B-10 | SGw | 22.2726̊ | 89.2430̊ | |
| B-11 | Pw | 22.2478̊ | 89.2403̊ | |
| B-12 | SGw | 22.2475̊ | 89.2416̊ | |
| B-13 | HTw | 22.2478̊ | 89.2403̊ | |
| B-14 | RHw | 22.2478̊ | 89.2403̊ | |
| B-15 | Pw | 22.2430̊ | 89.2452̊ | |
| Munshiganj | M-1 | RHw | 23.7053̊ | 88.8527̊ |
| M-2 | Sw | 23.7150̊ | 89.8241̊ | |
| M-3 | SGw | 23.7053̊ | 88.8527̊ | |
| M-4 | Pw | 23.7411̊ | 89.7853̊ | |
| M-5 | Pw | 23.6923̊ | 89.2725̊ | |
| M-6 | PSFw | 23.7167̊ | 88.9167̊ | |
Water sample collection areas and GPS location with land use coded according to sampling source.
RHw, Rain harvested water; PSFw, Pond sand filter water; SGw, Shrimp gher water; Rw1, Kholpatua River water; Rw2, Chuna River water; Sw, Supply water; Pw, Pond water; HTw, Hand pumped tube well water.
FIGURE 2

Sample of soil collection areas.
FIGURE 3

Water sample collection areas.
After the samples were collected, all samples were sent to the laboratory of the Soil Resources Development Institute (SRDI) within 21 h and kept in a refrigerator at a temperature below four degrees Celsius (
Twenty-nine water samples were also collected in these areas from tube wells, pond sand filters, and rainwater harvesting tanks. The coordinates and land use information for the soil samples are displayed in Table 2 and photographs of the collection sites are shown in Figure 3 below.
Soil and Water Sample Analysis
The major chemical constituents of soil and water and their quality factors were analysed using standard methodologies. Standard saturation paste method was used to determine the ECe where 350 g air-dried soil was taken for each sample to prepare the saturated paste, left it in room temperature for 24 h for equilibrium then the saturated paste extracts were collected by subsequently using Buchner funnel and applying suction (
The Olsen Sodium Bicarbonate test was used to determine soil phosphorus. Soil potassium and sodium were determined separately by flame emission spectrophotometer (Jenway Model: PEP-7), using potassium and sodium filters, respectively, as outlined by
Additionally, historical data for electrical conductivity (EC) and chloride concentration was obtained from the Bangladesh Water Development Board (BWDB) for the South-western coastal region with data ranging from 1968 to 2019. Data from the BWDB was available from 3 stations: Kalaroa (SW 23; 2001–2018), Elarchar (SW 254.5; 2001–2018), Benarpota (SW 24; 1980–2018). The EC and chloride data from the BWDB was averaged on yearly basis for low and high-water levels. This data was plotted in Microsoft Office Excel 16 as the levels of chloride and EC at high and low tide over time in years.
Statistical Analysis
The results of the soil and water samples were analysed using Pearson’s correlation coefficient using the computer software IBM SPSS 25. Pearson’s correlation coefficient is a linear correlation model using two sets of data that produces a value, r, by accounting for the covariance and standard deviations within the data sets. The r vale produced indicts how highly one dataset is correlated or influenced by another with high values being more significant. The standard Pearson’s r is calculated as follows:
Standard deviation and other general calculations were also conducted. A standard linear regression, using historical data, was created to determine the R2 value for chloride and EC at low and high tide for the Kalaroa, Elarchar, and Benarpota stations. This was done to identify variables that correlate with each other to find statistical patterns that might reveal evidence of the physical mechanism underlying them. Most calculations were conducted in Microsoft Excel 16 unless otherwise stated.
Cyclonic Storm Surge Analysis
To calculate the areas affected by different seawater surges, three different storm surge heights were used, 1.5, 5.25, and 9 m as the minimum, mean and maximum surge height (
Results
Soil Analysis
The results of the soil analysis are displayed in Table 3 above.
TABLE 3
| Soil chemical parameters | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Location | Sample ID | ECe (dS/m) | TDS (%) | pH | Ca (meq/100 g soil) | OM (%) | TN (%) | K (meq/100 g soil) | P (ppm) | Land use |
| Gabura | G-1 | 4.3 | 0.28 | 7.8 | 29.5 | 2.2 | 0.15 | 2 | 4.2 | Pw |
| G-2 | 1 | 0.06 | 8.8 | 35.23 | 2.1 | 0.17 | 3 | 8.59 | SGw | |
| G-3 | 11 | 0.70 | 8.8 | 7.47 | 2.3 | 0.14 | 2 | 10.26 | SGw | |
| G-4 | 2.3 | 0.15 | 7.5 | 15.84 | 2.2 | 0.11 | 3 | 12.17 | Rw1 | |
| G-5 | 11.6 | 0.74 | 7.7 | 7.5 | 2.6 | 0.11 | 4 | 6.81 | Pw | |
| G-6 | 32.7 | 2.09 | 7.3 | 15.12 | 4.8 | 0.24 | 5 | 7.52 | Pw | |
| G-7 | 6.9 | 0.44 | 6.8 | 23.07 | 2 | 0.1 | 3 | 3.75 | HTw | |
| Average | 10.0 | 0.64 | 7.8 | 19.10 | 2.6 | 0.15 | 3.1 | 7.61 | ||
| SD | 10.8 | 0.69 | 0.7 | 10.65 | 1.0 | 0.05 | 1.1 | 3.05 | ||
| Burigoalini | B-1 | 14.3 | 0.9152 | 8.4 | 28.45 | 2.9 | 0.14 | 4 | 7.47 | Rb |
| B-2 | 4.8 | 0.3072 | 6.5 | 25.64 | 2.4 | 0.12 | 2 | 6.63 | Af | |
| B-3 | 6.5 | 0.416 | 6.6 | 19.84 | 2.7 | 0.11 | 4 | 9.17 | Ps | |
| B-4 | 17.5 | 1.12 | 7.8 | 33.7 | 2.4 | 0.12 | 3 | 13.39 | SGs | |
| B-5 | 7.9 | 0.5056 | 7.9 | 52.32 | 2.8 | 0.1 | 2 | 7.70 | Ps | |
| B-6 | 10 | 0.64 | 6.6 | 81.03 | 3 | 0.14 | 3 | 8.42 | SGs | |
| B-7 | 24.2 | 1.5488 | 6.5 | 31.14 | 2.2 | 0.11 | 2 | 7.91 | Af | |
| B-8 | 6.7 | 0.4288 | 8.1 | 22.40 | 2.8 | 0.14 | 4 | 15.21 | Ps | |
| Average | 11.5 | 0.74 | 7.3 | 36.82 | 2.7 | 0.12 | 3.0 | 9.49 | ||
| SD | 6.7 | 0.43 | 0.8 | 20.45 | 0.3 | 0.02 | 0.9 | 3.10 | ||
| Munshiganj | M-1 | 13.6 | 0.8704 | 5.1 | 33.62 | 2 | 0.1 | 4 | 11.01 | Af |
| M-2 | 20.2 | 1.2928 | 6.6 | 41.07 | 2.2 | 0.11 | 2 | 6.29 | Af | |
| M-3 | 5.2 | 0.3328 | 6.5 | 29.01 | 2.6 | 0.13 | 2 | 4.3 | Af | |
| Average | 13.0 | 0.83 | 6.1 | 34.57 | 2.3 | 0.11 | 2.7 | 7.20 | ||
| SD | 6.1 | 0.39 | 0.7 | 4.97 | 0.2 | 0.01 | 0.9 | 2.81 | ||
Some selected chemical properties and land use of soil samples collected from Gabura, Burigoalini and Munshiganj sites.
ECe values of the soil samples are shown in Table 3, where the electrical conductivity of the soil samples varies between 1 and 32.7 dS/m. Again, the above results show high salinity statuses for all three respective sampling areas with more than 95% of the samples havilo1ng an ECe dS/m value higher than 8 dS/m across all the sampling areas. Soil salinity is often based on the direct measure of the electrical conductivity, soils with an ECe above 4 dS/m of which most of the samples were; furthermore some scientists have recommended that soils with an ECe above 2 dS/m be classified as saline as most crops will be harmed by salinity above ECe 2 dS/m (
The highest pH values found for Gabura, Burigoalini and Munshiganj were 8.8, 6.8, and 8.4 whilst the lowest pH values were 6.5, 6.6, and 5.1, respectively. The results indicate that most of the areas of Gabura and Burigoalini have higher soil pH levels (mildly to strongly alkaline) as opposed to the neutral range (
Organic Matter (OM), nitrogen (N) and potassium (K) showed statistical significance in their sample abundance (Table 4). Most of the samples displayed a potassium concentration that exceeded the recommended 2.0 meq/100 g range and could be detrimental to certain species. The reason for this high levels of K could be due to the alternating wetting and drying of the soils that can be brought about during extreme weather events, it is known that alternating wetting and drying periods enhances the K fixation in the soil, making it more available (
TABLE 4
| Correlations | |||||||
|---|---|---|---|---|---|---|---|
| pH | ECe (dS/m) | OM (%) | TN (%) | Ca (meq/100 g soil) | K (meq/100 g soil) | P (ppm) | |
| pH | 1 | ||||||
| ECe (dS/m) | −0.189 | 1 | |||||
| OM (%) | 0.101 | 0.555* | 1 | ||||
| TN (%) | 0.351 | 0.375 | 0.752** | 1 | |||
| Ca (meq/100 g soil) | −0.243 | −0.040 | −0.021 | −0.114 | 1 | ||
| K (meq/100 g soil) | −0.006 | 0.299 | 0.560* | 0.395 | −0.263 | 1 | |
| P (ppm) | 0.199 | 0.016 | 0.006 | −0.029 | −0.076 | 0.339 | 1 |
Pearson correlation coefficient of soil nutrients with soil pH, ECe and organic matter (SOM).
*Correlation is significant at the 0.05 level (2-tailed).
**Correlation is significant at the 0.01 level (2-tailed).
The Pearson’s correlation coefficient study in Table 4 showed a significant positive correlation between ECe dS/m and OM (0.555*), OM and TN (0.752**) and OM and K (0.560*). Other correlations were found to be nonsignificant, indicating no influence between the parameters. This correlation study illustrated that organic matter concentration is positively correlated with electrical conductivity (EC), total nitrogen (TN) and potassium (K) and vice versa. The correlation with TN is expected as OM is essentially dead plant and animal material which tend to be mainly made of carbon, nitrogen, phosphorous, and hydrogen. Similarly the correlation between OM and K is expected as an increase in OM increase the CEC of soils, making K fixation higher (
Further comparisons were conducted between pH and phosphorous (P) and are graphically displayed in Figure 4 below.
FIGURE 4

Statistical relationship between Phosphorous (ppm) and pH. The abundance of Phosphorous is greater within the neutral area of pH despite not having any correlation (R2 = 0.039).
Comparing phosphorous content with pH shows that at a pH of 7.0–8.3, samples had P content greater than 12 ppm (
Water Analysis
The results of the water analysis are displayed in Table 5 below where the EC values varies from 0.1 to 41.3 dS/m. The results show that most of the samples have exceeded the permissible limit of salinity in the sampling areas, particularly in river water (>30 dS/m) (
TABLE 5
| Water chemical parameters | ||||||||
|---|---|---|---|---|---|---|---|---|
| Location | Sample ID | EC (dS/m) | TDS (%) | pH | Na (mg/L) | Bicarbonate (mg/L) | Chloride (mg/L) | Land use |
| Gabura | G-1 | 32.8 | 2.10 | 8.1 | 5520 | 219.6 | 12420 | Pw |
| G-2 | 38.2 | 2.44 | 8.4 | 6900 | 122 | 15019 | SGw | |
| G-3 | 41.3 | 2.64 | 8.2 | 7360 | 91.5 | 64005 | SGw | |
| G-4 | 39 | 2.50 | 8.3 | 6440 | 128.1 | 62928 | Rw1 | |
| G-5 | 2.3 | 0.15 | 8.9 | 920 | 256.2 | 2208 | Pw | |
| G-6 | 0.8 | 0.05 | 8.4 | 50.6 | 109.8 | 552 | Pw | |
| G-7 | 1.9 | 0.12 | 8.4 | 460 | 128.1 | 4554 | HTw | |
| G-8 | 5.4 | 0.35 | 8.7 | 460 | 262.3 | 6072 | Pw | |
| Average | 20.2 | 1.29 | 8.4 | 3513.83 | 164.7 | 20969.8 | ||
| SD | 19.0 | 1.22 | 0.3 | 3299.8 | 69.5 | 26676.2 | ||
| Burigoalini | B-1 | 6.1 | 0.39 | 8.9 | 1380 | 311.1 | 7603 | Pw |
| B-2 | 0.2 | 0.01 | 7.7 | 23 | 18.3 | 276 | Sw | |
| B-3 | 39.6 | 2.53 | 8.1 | 6900 | 122 | 63480 | Rw2 | |
| B-4 | 0.7 | 0.04 | 8.1 | 460 | 54.9 | 690 | RHw | |
| B-5 | 0.1 | 0.01 | 7.2 | 460 | 36.6 | 138 | RHw | |
| B-6 | 0.6 | 0.04 | 8.5 | 460 | 128.1 | 690 | Pw | |
| B-7 | 1.4 | 0.09 | 8.2 | 460 | 73.2 | 1794 | Pw | |
| B-8 | 0.7 | 0.04 | 8.6 | 55.2 | 109.8 | 690 | PSFw | |
| B-9 | 3.7 | 0.24 | 8.3 | 460 | 91.5 | 4830 | Pw | |
| B-10 | 39.6 | 2.53 | 8.2 | 5980 | 128.1 | 60720 | SGw | |
| B-11 | 0.1 | 0.01 | 7.9 | 460 | 30.5 | 690 | Pw | |
| B-12 | 38.3 | 2.45 | 8.2 | 5980 | 146.4 | 62100 | SGw | |
| B-13 | 1.2 | 0.08 | 8.2 | 115 | 115.9 | 1104 | HTw | |
| B-14 | 39 | 2.50 | 8.3 | 5980 | 140.3 | 68034 | RHw | |
| B-15 | 16.7 | 1.07 | 8.7 | 2760 | 384.3 | 24978 | Pw | |
| Average | 12.5 | 0.80 | 8.2 | 2128.88 | 126.1 | 19854.5 | ||
| SD | 17.1 | 1.10 | 0.4 | 2641.9 | 99.9 | 28030.8 | ||
| Munshiganj | M-1 | 0.3 | 0.02 | 8 | 920 | 61 | 414 | RHw |
| M-2 | 2.9 | 0.19 | 8.4 | 460 | 280.6 | 3594 | Sw | |
| M-3 | 35.5 | 2.27 | 7.9 | 5980 | 54.9 | 57408 | SGw | |
| M-4 | 2.8 | 0.18 | 8.7 | 920 | 195.2 | 2760 | Pw | |
| M-5 | 0.6 | 0.04 | 7.9 | 920 | 61 | 414 | Pw | |
| M-6 | 1.1 | 0.07 | 8.7 | 96.6 | 244 | 1242 | PSFw | |
| Average | 7.2 | 0.46 | 8.3 | 1549.43 | 149.5 | 10972.0 | ||
| SD | 13.9 | 0.89 | 0.4 | 2196.2 | 102.8 | 22785.0 | ||
Some of the selected chemical properties and land use of water samples collected from the Gabura, Burigoalini and Munshiganj sites.
As seen above, G1–G4 had much higher Na values than compared to the other soil samples in the area. Furthermore, six samples from the Buri Goalini area and one from the Munshigani union had similar high Na concentrations. This is a concern as high Na levels can cause sodicity in soil which makes soil less permeable and more prone to being flooded (
Approximately 93% of the water samples showed a sodium (Na) concentration beyond the recommendation of 200 mg/L as well as chloride above 250 mg/L, these concentrations are unsuitable for drinking water (
TABLE 6
| Correlations | |||||
|---|---|---|---|---|---|
| pH | EC (dS/m) | Na (mg/L) | Bicarbonate (mg/L) | Chloride (mg/L) | |
| pH | 1 | ||||
| EC (dS/m) | −0.084 | 1 | |||
| Na (mg/L) | −0.116 | 0.992** | 1 | ||
| Bicarbonate (mg/L) | 0.790** | 0.024 | −0.007 | 1 | |
| Chloride (mg/L) | −0.094 | 0.914** | 0.892** | −0.028 | 1 |
Pearson correlation coefficient of water nutrients with pH and EC.
*Correlation is significant at the 0.05 level (2-tailed).
**Correlation is significant at the 0.01 level (2-tailed).
The Pearson’s correlation coefficient study of water parameters in Table 6 illustrated a highly significant and positive correlation between pH and bicarbonate (0.79**), EC and Na (0.99**), EC and Cl− (0.91**) and Na and Cl− (0.89**) (
The Pearson correlation coefficient study between the soil and water parameters depicted a significant negative correlation between the ECe dS/m of soil and the EC of water (−0.47*); the ECe dS/m of soil and the Na of water (−0.50*) and a positive correlation between the OM of soil and the Na of water (0.50*) (
Historical Patterns of Water Salinity
Historical data was collected and analysed overtime to try to determine and/or predict future patterns and correlations. The relationship between chloride and EC at different tide levels at the Benaporta station is shown in Figure 5.
FIGURE 5

Chloride concentrations (ppm) and electric conductivity (dS/m) at high and low tides in the Betna-Kholpetua river at Benarpota from 1980 to 2018. This graph shows a large increase in salinity and chloride concentrations in 1982, a smaller one in 2007, and another one from 2009 to 2011.
The Benaporta station shows a matching relationship between Cl− and EC concentrations at low and hide tides, but Cl− at high tide shows a more attenuated relationship (
The relationship between chloride and EC at different tide levels at the Benaporta station is shown in Figure 6.
FIGURE 6

Chloride concentrations (ppm) and electric conductivity (dS/m) at high and low tides in the Betna-Kholpetua River at Kalaroa from 2001 to 2018. This graph shows an increase of both chloride and EC from 2001 to 2003, followed by a more prolonged increase from 2006 to 2011, finally with a slight increase from 2013 to 2015.
The Kalaroa station clearly shows a spike of both chloride and EC from 2001 to 2003, with a salinity level of >4,000 dS/m and a chloride concentration of >1,000 ppm at high tides. These levels are similar to the same spike at Benaporta station. From 2006 to 2011, there is a massive increase in salinity (
FIGURE 7

Chloride concentrations (ppm) and electric conductivity (dS/m) at high and low tides in the Betna-Kholpetua River at Elarchar from 2001 to 2018. An increase of both chloride and EC from 2001 to 2003, followed by a more prolonged increase from 2006 to 2011, finally with a slight increase from 2013 to 2015.
In Figure 7, a trend similar to that observed at the Kalaroa station is repeated at Elarchar, where an increase in chloride and EC is observed from 2001 to 2003 with a salinity level of >8,000 dS/m and a chloride concentration of >2,000 ppm at high tides. Surprisingly, these values are twice as high as those seen in Kalaroa. Along with this, a massive increase in salinity, with levels well above 12,000 dS/m at high and low tides, and chlorine levels above 6,000 ppm is recorded from 2007 to 2011 (
TABLE 7
| Correlations | ||||||||
|---|---|---|---|---|---|---|---|---|
| Benarpota | Kalaroa | Elarchar | Legend | |||||
| Cl (ppm) HT | Cl (ppm) LT | Cl (ppm) HT | Cl (ppm) LT | Cl (ppm) HT | Cl (ppm) LT | |||
| Benarpota | Cl (ppm) HT | 0.5855 | 0.1763 | 0.1931 | 0.3049 | 0.3416 | >0.7 | |
| Cl (ppm) LT | 0.5855 | 0.3789 | 0.3621 | 0.5297 | 0.5181 | >0.2 | ||
| Kalaroa | Cl (ppm) HT | 0.1763 | 0.3789 | 0.982 | 0.6897 | 0.7467 | <0.2 | |
| Cl (ppm) LT | 0.1931 | 0.3621 | 0.982 | 0.7172 | 0.7597 | |||
| Elarchar | Cl (ppm) HT | 0.3049 | 0.5297 | 0.6897 | 0.7172 | 0.9574 | ||
| Cl (ppm) LT | 0.34 | 0.5181 | 0.7467 | 0.7597 | 0.9574 | |||
Correlations between Chloride concentration at low and high tides from the Bearpota, Kalaroa and Elarchar stations.
Every correlation is higher than R2 = 0.2 except for the Benarpotas high tide with the Kalaroa’s high and low tide. This indicates that most data sets are affected quite similarly by the same environmental process. The same correlations were done using the EC data in Table 8.
TABLE 8
| Correlations | ||||||||
|---|---|---|---|---|---|---|---|---|
| Benarpota | Kalaroa | Elarchar | Legend | |||||
| EC HT | EC LT | EC HT | EC LT | EC HT | EC LT | |||
| Benarpota | EC HT | 0.9776 | 0.3407 | 0.4120 | 0.5268 | 0.5294 | >0.7 | |
| EC LT | 0.9776 | 0.2592 | 0.3319 | 0.4389 | 0.4518 | >0.2 | ||
| Kalaroa | EC HT | 0.3407 | 0.2592 | 0.9662 | 0.6274 | 0.5935 | <0.2 | |
| EC LT | 0.4120 | 0.3319 | 0.9662 | 0.6345 | 0.6126 | |||
| Elarchar | EC HT | 0.5268 | 0.4389 | 0.6274 | 0.6345 | 0.9939 | ||
| EC LT | 0.5294 | 0.4518 | 0.5935 | 0.6126 | 0.9939 | |||
Correlations between EC concentration at low and high tides from the Bearpota, Kalaroa and Elarchar stations.
All the correlations had values greater than R2 = 0.2, indicating that these data values respond in a similar way to the same environmental process.
The correlation analysis from Table 7 shows the chloride concentrations of the three stations at low and high tide, except for the correlation between Benarpota’s high tide and Kalaroa high and low tide data. Similarly, Table 8 shows that all had a significant correlation above R2 = 0.2. Both tables show correlations above R2 = 0.5. The two most predominant spikes from 2001 to 2003 and 2006/7 to 2011 are therefore statistically supported by these correlations. This means that the physical and environmental processes behind these spikes are affecting trends in salinity levels of the Betna-Kholpetua River in a similar and fairly uniformly manner.
Storm Surges and Sea-Level Rises
Figure 8 below displays two maps with projected impacts of potential storm surges at different distances inland in the Bay of Bengal. Figure 8A is at current sea level and Figure 8B is with a 1-m rise in sea level.
FIGURE 8

Storm surge projections over the Bay of Bengal for areas affected by surges of 1, 5, and 9 m. (A) at current sea level. (B) at a 1 m rise in sea level.
These maps show that a potential storm surge of 9 m has the capacity, in both scenarios, to cover over a third of the country [Self-made with data retrieved from
Based on the maps above it is evident that the most vulnerable areas are the rivers. Many streams enter deep into Bangladesh’s territory, which means that even a moderate cyclone (1-m surge), can affect river environments and freshwater supplies far from the coast. These results may explain the correlations between the Kalaroa, Benarpota and Elarchar stations in Tables 7, 8, as these are within the range of a 1-m storm surge. Also, in Figures 5–7, these stations reflect an increase in salinity over the years, where cyclones have led to an intrusion of saltwater (
As seen in Figure 8B, the map indicates the same seawater surge scenario but based on the scenario of a projected 1-m rise of sea level, according to the IPCC’s RCP8.5 from
Figure 9 displays the maps from two different storm surge scenarios for the Shyamnagar Upazila region. Map A is a projection of the area affected by surges of 1, 5, and 9 m due to a cyclone or a tropical storm, with current sea levels. Map B shows the same area but with a 1-m rise in sea level, similar to Figure 8.
FIGURE 9

Results from two different storm surge scenarios for the Shyamnagar Upazila, map (A) is a projection of the area affected by surges of 1, 5, and 9 m due to a cyclone or a tropical storm, with current sea levels. Map (B) shows the same area but with a 1-m rise in sea level. This map shows that a 9-m storm surge can cover most of the area (>90%) in the Upazila. Self-made with data retrieved from
The maps above show that a 9-m storm surge can cover most of the area (>90%) in the Upazila [Self-made with data retrieved from
Comparatively, Figure 9B shows the same scenario, but with a baseline of 1 m above sea level, indicating that 5.6% of the area or 79 km2 will be submerged by 2100 (
Discussion
Bangladesh is an extremely vulnerable nation due to its low topography, where half of the country lies within 5 m above sea level. Furthermore, Bangladesh is also extremely vulnerable to cyclonic and tropical storm activity, as displayed in the projection scenarios above. Based on several studies this research identifies that from 1891 to 2008, about 178 cyclones have hit the coast of Bangladesh (
At extreme scenarios, the highest prediction of a 9-m surge will have a lower periodicity but will not be uncommon.
The same parameters will apply for storm surges with an estimated 1-m rise in sea level. The increase in the area flooded by sea rise compared to the current conditions depends on the topography of the land, which allows more water to pass inland, rather than an increase in the intensity of cyclones.
Furthermore, evidence of these seawater surges is recorded in the chemical archives within the Kalaroa, Benarpota, and Elarchar stations of the Bangladesh Water Development Board as a pattern of spikes or increases of both salinity and chloride. These spikes reflect the Sidr, Aila, and Nargis storms in 2007, 2008, and 2009 respectively. First, the 1982 spike, with EC levels reaching over 10,000 (dS/m), can be attributed to a storm surge in the same year, which caused heavy loss of life (
The storm surges that create saltwater intrusion far into Bangladesh, permeate the soil and freshwater systems, such as rivers and ponds (
High concentrations of sodium in water reduces its quality, causing high blood pressure in humans and limiting the absorption of nutrients in plants (
The general trend shows an increase in potassium in the soil with increasing water salinity (Table 9). This is in accordance with the findings by
TABLE 9
| Correlations | ||||||||
|---|---|---|---|---|---|---|---|---|
| Soil | ||||||||
| ECe (dS/m) | pH | OM (%) | TN (%) | P (ppm) | Ca (meq/100 g soil) | K (meq/100 g soil) | ||
| Water | EC (dS/m) | −0.47* | 0.39 | −0.12 | 0.01 | −0.12 | 0.04 | −0.19 |
| pH | −0.17 | −0.17 | 0.26 | 0.13 | −0.12 | 0.02 | 0.40 | |
| Na (mg/L) | −0.50* | 0.42 | −0.15 | 0.03 | −0.05 | 0.03 | −0.19 | |
| Bicarbonate (mg/L) | 0.05 | −0.13 | 0.50* | 0.41 | −0.32 | −0.14 | 0.42 | |
| Chloride (mg/L) | −0.31 | 0.22 | −0.01 | −0.14 | −0.02 | 0.02 | −0.13 | |
Pearson correlation coefficient analysis between soil and water parameters.
* Correlation is significant at the 0.05 level (2-tailed).
** Correlation is significant at the 0.01 level (2-tailed).
Eight water samples, all from pond water, as well as 2 soil samples, had pH values above 8.5. This water pH is unfit for human consumption and may have adverse effects on human health (
Low levels of phosphorous in soil could be attributed to the precipitation of phosphorus in solution under alkaline conditions as well as the inability of organic matter to fix phosphates, in which the soils have a high organic matter content (
Low water levels of flooding can reach far into Bangladeshi territory according as seen in Figure 8. The hydraulic dynamics of the river system has a strong influence on surface and groundwater, exchanging the water mass between reservoirs (
Conclusion
Through analysis of the primary data, this study revealed that most of the water samples and more than 50% of the soil samples have moderately alkaline conditions. Also, the concentration of calcium (Ca) and potassium (K) in the soil and sodium (Na) and chloride (Cl−) in the water was very high compared to permit limits for human consumption and agricultural cultivation. This study further revealed the deficient status of phosphorus (P) and total nitrogen (TN) in the soil of the study area which is directly an impact of a high EC that reduces the decomposition of organic matter. Eventually, one large storm surge is predicted along the coast, covering 12% of the region every 5 years, and one third every 20 years. More than half of the Shyamnagar Upazila, on the other hand, is affected every 5 years and almost entirely every 20 years. In the Betna-Kholpetua river station, small surges of 1 m are indicated as cyclonic surges, resulting in increased EC and chloride. They greatly contribute to the salinization of soil and water of the Southwestern coast of Bangladesh, which explains the very serious levels of salinity observed in this report. For the Shyamnagar Upazila, the salinity of most water and soil samples was well above the permissible standards for human use and agriculture. Similarly, extremely alkaline environments would impact natural soil biogeochemical processes that already promote scattered phosphorus precipitation, corrode pipes, and pollute drinking water and decrease crop size and yield.
The salt content of the soil may also adversely affect the supply of other vital nutrients such as K, Ca, and P, and thus impede the optimum cultivation of crops (
The vision of sustainable climate and livelihood in Bangladesh can be achieved with saltwater supply through structural management such as coastal sluice schemes, barriers, sluices, and coastal areas, as well as non-structural management to change land use and other practices. Innovation and cultivation of different types of salt-tolerant crop varieties can also reduce food scarcity in the areas affected by salinity. Furthermore, a more detailed analysis is ultimately necessary to formulate the ambitious management model through various optional scenarios.
Statements
Data availability statement
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.
Author contributions
All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication. Conceptualization, MA; methodology, MA; software, MA and AC; validation, MA, AC, FDS, and SL; formal analysis, MA, and investigation, MA; resources, MA; FDS and SL; data curation, MA; writing—original draft preparation, MA writing—review and editing, MA, FDS, AC, and SL; visualization, MA and AC; supervision, FDS; AC and SL. All authors read and approved the final version of the manuscript.
Acknowledgments
This research is part of MA's PhD study, supported by authors listed in this paper.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontierspartnerships.org/articles/10.3389/sjss.2022.10017/full#supplementary-material
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Summary
Keywords
sea level rise, storm surges, Geochemical of salinity, Soil and water salinity, SWCRB
Citation
Ashrafuzzaman M, Artemi C, Santos FD and Schmidt L (2022) Current and Future Salinity Intrusion in the South-Western Coastal Region of Bangladesh. Span. J. Soil Sci. 12:10017. doi: 10.3389/sjss.2022.10017
Received
07 August 2021
Accepted
02 February 2022
Published
21 March 2022
Volume
12 - 2022
Edited by
José Antonio Martínez Casasnovas, Universitat de Lleida, Spain
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© 2022 Ashrafuzzaman, Artemi, Santos and Schmidt.
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*Correspondence: Md Ashrafuzzaman, frankashru@gmail.com, mdashrafuzzaman@ics.ul.pt
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