Effectiveness of Adaptation Measures for Reducing the Effect of Salinity Intrusion in Agriculture Practice: A Case study from Kolapara Upazila, Bangladesh
Mashura Shammi*, Anirban Das, Ummay Salma, Abid Azad Sakib, Md. Mostafizur Rahman
Department of Environmental Sciences, Jahangirnagar University, Dhaka-1342, Bangladesh
(Received: 25 May 2020, Revised: 11 June 2020, Accepted: 15 June 2020, Online: 30 June 2020) Abstract
Salinity has caused significant negative effects on agricultural production in the coastal regions in Bangladesh. This research is focused on the effect of salinity intrusion in the agricultural sector and the adaptation measures to reduce negative effects considering farmers’ perception. A questionnaire survey was conducted using multi-stage and simple random sampling technique. 120 responses from male farmers were collected from Khaprabhanga and Nilganj Union of Kalapara Upazila of Patuakhali District. Regression analysis and the coefficient of variation was done among the 12 dependent variables as farmers perceived adaptation effectiveness along with the 16 independent variables. Results show that farmers with good agricultural knowledge and participation in the organisational activities had a significant influence on the choice of adaptive measures. Moreover, farming experience, tenure status was significantly associated with planting crops in Rabi season; training experience was significantly associated with rooftop catchment area, solar-powered desalination, and rainwater harvesting. On the other hand, farm size was associated with solar- powered desalination plants, pond sand filter and levelling of land while the annual income was associated with levelling of land and rainwater harvesting. Access to extension services was significantly associated with levelling of land, planting crops in Rabi season and rainwater harvesting while farmer to farmer extension was significantly associated with excavating or renovating pond on the higher ground and plastic sheets with a hole. Responses by the society or policy are the result of undesired impacts of salinity intrusion that have been identified from the DPSIR (driving force-pressure-state-impact-response) framework. From this study the most effective responses identified from the farmers’ perceptions were saline tolerant variety, pond-sand filter, rainwater harvesting, levelling land, applying potassium sulphate fertiliser and avoid fallowing land in the Rabi season.
Keywords: Agriculture, Crop Production, DPSIR Framework, Irrigation Water.
Introduction
Agricultural crop production is exceedingly reliant on the excellence of irrigation water. However, salinity intrusion is an ever-increasing problem to the irrigation water which in turn affects the sustainable agricultural production in the coastal districts of Bangladesh exacerbated by natural disasters and climate change (Shammi et al., 2016). Bangladesh resides in the Ganges–the Brahmaputra–the Meghna delta, which is one of the most populated regions in the world with 165 million people. Different environmental stressors, including salinity intrusion, threatens the Delta with adverse effects on life and health. Most of the coastal districts in Bangladesh are situated on the riverbanks of low-lying tidal zones at an average elevation of 1.0–1.5m from the sea level
(Rahman and Rahman, 2015). Spatio-temporal trend investigation of surface water salinity in the coastal region of Bangladesh had specified the most saline-intruded areas in the wet-monsoon season is the extreme south-west coastal zone of Bangladesh encompassing the districts of Khulna, Satkhira, Bagerhat, Jessore and Gopalganj. Mid-south zone of Bangladesh especially the Barisal, Jhalkathi, Patuakhali and Barguna districts, on the other hand, are highly salinity affected in the wet-monsoon followed by the dry-season (Shammi et al., 2017).
53% of the coastal region is affected by different degrees of salinity (Shammi et al., 2017).
Increasing salt intake has substantial negative impacts on human health and well-being because of the presence of a substantial amount of sodium in the drinking water (DWS). Saline water is an important factor for hypertension or high blood pressure in the coastal areas (Shammi et al., 2019).
The severely salinity affected region of the Khulna district is Batiaghata Upazila, where irrigation water sources are a crisis for farmers even during the monsoon caused by lower or no rainfall and drought (Shammi et al., 2016). Subsequently, the severity of the salinity problem would further be amplified over time with the desiccation of the soil (Habiba et al., 2014). Moreover, coastal agriculture often experiences a yield reduction or in some cases destruction due to tidal inundation and salinity (Baten et al., 2015). It is projected that a net reduction of 0.5 million metric ton of rice would less produce due to a 0.3m sea-level rise (SLR). During the dry season, the issue is aggravated when precipitation is not adequate and unable to minimise salinity concentration on surface water and salt drainage from the ground (Shammi et al., 2016).
Irrigation and drinking water quality are severely threatened by salinity intrusion in Southern Bangladesh (Islam et al., 2017) both environmentally and anthropogenically (Khanom, 2016). The over-extracted water resources, low upstream flow due to the Farakka barrage, the consequences of climate change are the deciding factor for sustainable agriculture in the region (Shammi et al., 2016). Agriculture which is the leading source of revenue in that region is severely altered due to soil and groundwater degradation, health problems and long term effect on the ecosystem (Khanom, 2016). The farming system in the region has therefore evolved dynamically illustrated by the combination of varying agricultural practices including freshwater prawns, rice, fish, vegetables, and brackish water shrimp (Faruque et al., 2017).
The cause and effect of salinity intrusion in the coastal area are noticeably clear. Groundwater quality index performed on 925 groundwater samples of two seasons show that 65% of the samples were poor to unsuitable (Islam et al., 2020). Consequently, the systematic diagnosis of farmers’
perception and climate data on decreasing yearly rainfall and rising temperature are highly associated. It further shows that the livelihood activity of farmers migrating to shrimp and crab cultivation (Akter and Ahmed, 2020). It is predictable that the crop production of the coastal area to be severely affected which in turn will cause a significant threat for the farmers. During the dry season, the issue is aggravated when precipitation is not adequate and unable to minimise salinity concentration on surface water and salt drainage from the ground. Therefore, the effect of salinity intrusion will adversely affect food production and in turn, affect food security. Driving force- pressure-state-impact-response or simply the DPSIR framework depicts a chain of links of events responsible for causing the impact and responses identified breaking the task into sub-task by considering pressure and state association (Kristensen, 2004). Developed from an Organization for
Economic Cooperation and Development (OECD) approach, societal responses are identified starting from the cause (Atkins et al., 2011). The aim of this study is, therefore, to identify the effectiveness of mitigation measures for reducing the effect of salinity problem in the agricultural production in coastal areas, considering the farmers’ perception on the effectiveness of adaptation measures using DPSIR framework.
Methodology
Kalapara Upazila is one of the most salinity affected prone areas of Patuakhali district, Bangladesh.
The people of this area face different types of problem where the effect of salinity intrusion is very severe. From the analysis of the previous study (Shammi et al., 2017), it is found that most of the people of the area face the problem of salinity intrusion. Especially the farmer of this area can grow crop once in a year due to salinity. Besides, they are not capable of producing other crops because the surface water is saline which is not appropriate for irrigation. On the other hand, they have truly little access to modern technique. For this reason, this area is selected for the research.
Kalapara Upazila is adjacent to the Amtali Upazila of Barguna district on the north, the Bay of Bengal on the south, and Rabnabad channel and Galachipa Upazila on the east. The geographical location of this area is 21°52´ to 21°54´ north latitude and 90°6´ to 90°20´ east longitude. Two unions of Kalapara Upazila were selected for this research (Figure 1). Khaprabhanga Union with a population of 26,295 where the number of males 13,675 and number of females 12,620 whereas, Nilganj Union with a population of 28,556 where the number of males 15,648 and the number of females 12,908. The literacy rate of Khaprabhanga and Nilganj is 58.30% and 64.22%, respectively.
Figure 1: The map of Khaprabhanga and Nilganj Union of Kalapara Upazila, Patuakhali District.
Data collection method
Multi-stage and simple random sampling technique were used for the selection of sample size.
Kalapara Upazila is consisted of 11 unions (BBS, 2011) out of which Khaprabhanga and Nilganj were selected randomly. Primary data were collected with the questionnaire survey of farmers (Box 1), focus group discussions (FGD), and key informant interview (KII) method. A semi-structured questionnaire was designed for data collection to identify the effectiveness of the farmer’s perception of effective adaptation measures to reduce salinity (Box 1). Ethical permission was taken from the authority of the Department of Environmental Sciences, Jahangirnagar University. The sample size was determined based on the method of Cochran (1977). Taking 95% confidence level and 10% margin of error, the sample size was 150. However, the sample size was reduced to 120 as only the male farmers were selected for this research. The sample size is calculated through the following equation:
Total Targeted Population, N= 54851 Confidence level = 95%
Margin of Error, e = 8%
95% level of Significance, Z= 1.96
The estimated proportion of successes, Standard Deviation, P= 0.5 (Male and Female Base) Estimated proportion of failures, q = (1- p) = (1- 0.5) = 0.5
Sample Size, 𝑛 =𝑧2∗𝑝∗𝑞𝑒2 ………. (i) = 1.960.082∗0.5∗0.52 = 150.56
In addition, four focus group discussion (FGD) containing groups about 5-10 farmers were conducted. Key informant interview of sub assistant agriculture Officer (SAAO), schoolteachers, members of different GO and NGO, community leaders were conducted face to face and over a cell phone using an open-ended questionnaire. For the FGD and KII, the following two questions were asked with the scale of “Not at all, little, moderate, high, very high”.
What kind of salinity intrusion effects are observed in your area? And what is the severity of the effect?
What kind of adaptation techniques are used to reduce the effect of salinity intrusion?
The study used ordinal dependent variable taking the value 0=Not at all; 1=little; 2=Moderate;
3=High; 4=Very High. This is done to know about the farmer’s knowledge about the mitigation measure of salinity intrusion. A farmer is considered to have adapted to salinity intrusion if he has employed at least one of the adaptation strategies such as planting saline tolerant variety, using pond sand filter, levelling of land, planting crops in Rabi season, fallowing lands, rainwater harvesting and others. The choice of independent variables used in the study is influenced by the literature reviewed on factors that influence farmers’ decisions to reduce the effect of salinity intrusion based on previous research findings on different socioeconomic research. The independent variables include age group, educational status, family size, annual income, occupation, farming experiences and farm size, agricultural knowledge, access to extension
services, farmer to farmer extension services, knowledge on climate change, training experiences, tenure status, communication exposure, organisational participation, access to credit. These variables are therefore assumed to influence farmers’ adaptation efforts to salinity intrusion either positively or negatively.
Data analysis and statistics
Data were entered and processed using the Microsoft Excel program. Statistical analysis was performed using SPSS Version 22. Descriptive analyses were performed to describe the findings.
Descriptive statistics, mean, standard deviation, frequency and percentage distribution have been used to explore the variable. Besides regression analysis, coefficient of variation has been done for the significance test where significance value *p < 0.10; **p < 0.05; ***p < 0.01.
Data analysis and statistics
Data were entered and processed using the Microsoft Excel program. Statistical analysis was performed using SPSS Version 22. Descriptive analyses were performed to describe the findings.
Descriptive statistics, mean, standard deviation, frequency and percentage distribution have been used to explore the variable. Besides regression analysis, coefficient of variation has been done for the significance test where significance value *p < 0.10; **p < 0.05; ***p < 0.01.
Box 1
A. General characteristics of farmers socio-demographic, economic and household information Name
Village & Upazila Age
1. Level of education
2. Number of the family members
3. Number of the dependent family members 4. Primary occupation and secondary occupation 5. Annual household income
6. Did you receive any loan from bank or other sources? If yes, please mention the loan receiving status.
7. Do you or your family members are group members of any NGOs and government organizations? If Yes, please mention type of NGOs and government organizations.
B. Impacts of salinity intrusion
1. What kind of salinity intrusion effects are observed in your area? Salinity intrusion causes:
i) Loss of crop production ii) Loss of fisheries
iii) Loss of freshwater fishes iv) Drinking water scarcity v) Migration
vi) Loss of biodiversity vii) Others
C. Adaptation and mitigation measures
1. Do you use any indigenous knowledge for reducing the effect of salinity intrusion? If yes, then mention the name of indigenous knowledge-
Results and Discussion
Social and demographic characteristics of the farmers
The age of the farmer ranged from 23 to 62 years with a mean value of 44.10 and standard deviation of 17.21. For analysis, the farmers were classified into three categories as young aged (up to 35 years), middle-aged (36-50 years) and old-aged (Above 50 Years). Most of the farmers (70.8%) in the study area were middle-aged compared to 20% of the older group and 15% of the younger group (Figure 2(a)). The education score of the farmers ranged from 0 to 14, with a mean value of 2.79 and a standard deviation of 0.83. Based on the educational scores the farmers were classified into four categories, illiterate and can sign only (0 and 0.5); primary education (1-5); secondary education (6-10) and above secondary education (above 10). Most of the farmers (48.3%) had secondary education, whereas 25% had primary education; 19.2% had above secondary education and 7.5% could sign only or illiterate (Figure 2(b)). According to the analysed data, most of the family size (68.30%) was medium whereas 19.2% are a large family and 12.5% were larger. Large family size means the input of more labour and more adapting capacity (Figure 2(c)).
Figure 2: The social and demographic information of farmers from the Khaprabhanga and Nilganj Union of Kalapara Upazila, Patuakhali District. In figure (a) The dispersal of farmers according to their age-group; (b) the distribution of farmers according to the level of education; (c) the family size of the farmers.
The study further revealed that most of the farmers (78.3%) only depended on on-farm activity while 21.7% of respondents depended on non-farm activity such as job, wage labour, services, and self-employed small business. In most cases, these activities are the secondary livelihood of the
farmers (Figure 3(a)). Besides, it was also revealed that about 78% of farmers cultivated their land while 21% of farmers did not cultivate their land or it was leased. For analysis, the farm sizes were categorized as small farm size (0.21-1.00 acre), medium farm size (1.01-3.00 acre) and large farm size (above 3.00 acre). About 42% of farmers had medium size farmland while 30% of farmers had small size followed by 27.5% large size farmland (Figure 3(b)). In addition, the annual household income of the farmers was classified into three categories as low, medium, and high. From the analysis of the data, it is found that 50% of farmers’ income fell into the medium category while 24% of farmers had an exceedingly high income. The annual income of the respondents ranged from 144000 to 450000 taka where the average income is 21,2507 taka, and the standard deviation is 59,539 (Figure 3(c)).
Figure 3: The economic status of farmers from the Khaprabhanga and Nilganj Union of Kalapara Upazila, Patuakhali District. (a) Depicts the type of occupation of the farmers, including own farm or leased; (b) the size of the farmlands, and (c) indicates the status of income from the farmland.
Farming experiences and knowledge of farmers
To analysis, the farmers’ experience was classified into four categories as low (1-10 years), medium (11-20 years), high (21-30 years) and extremely high (31-40 years). The farming experience of the farmer ranged from 3 to 40 years with a mean 17.79 and a standard deviation of 8.80. From the
analysis of data, it can be said that most of the farmers (45%) had the medium experience while 28.3% of farmers had high experiences. 6.7% of farmers had an extremely high experience while exceptionally low experience accounted for approximately 20% (Figure 4(a)). Training the farmers who had a different experience of training, may know about different adaptation measures for reducing the effects of the different agricultural problem. The survey found that about one-third farmer had no previous training experiences, whereas, 53.3% of farmers had low training. Medium trained farmers and highly trained farmers were in small numbers accounting for only 8.3% and 7.5%, respectively (Figure 4(b)).
Exposure to communication and participation in organisational activities are especially important to get information on changes. Moreover, agriculture knowledge helps the farmer to produce different high yielding crop variety and help them to cope with a different problem such as salinity intrusion. From the study, it is found that about 35% of farmers had a poor communication exposure while 60% of farmers had medium communication exposure. Only 4% of farmers had exceedingly high communication exposure (Figure 4(c)). According to the survey, about 45% of farmers had no experiences of organisational participation. Low and medium organisational participation varied from 24.2-25.8% while only 5% of farmers had a satisfactory level of organisational participation (Figure 4(d)).
Figure 4: Farming experiences, training, and knowledge sharing gathering of farmers from the Khaprabhanga and Nilganj Union of Kalapara Upazila, Patuakhali District. (a) distribution of farmers according to their farming experiences; (b) distribution of farmers according to their training experiences; (c) classification of farmers according to their communication exposure; (d) classification of farmers according to their organisational participation.
Based on the level of agricultural knowledge, farmers were grouped into three categories of low agricultural knowledge, medium agricultural knowledge, and high agricultural knowledge. The majority (53.3%) of the farmers had low agricultural knowledge compared to the 36.7% of medium agricultural knowledge. Only 10% of farmers belonged to the group of high agricultural knowledge (Figure 5(a)). Extension services play a significant role in the improvement of farming knowledge, updated information on farming practice, training experiences, communication exposure of the farmers. Even knowledge sharing by the experienced farmers (e.g., farmer to farmer extension service) to the novice, inexperienced and illiterate farmers often plays a vital role in the improvement of agricultural development. According to the survey, most of the farmers (56.7%) had medium access to agricultural extension services while 19.2% farmers and 24.2% farmers had low and high access to agricultural extension services, respectively. Most authors have documented a positive correlation between extension contact an adoption decision of farmers (Maponya and Mpandeli, 2013; Obayelu, et al., 2014; Shongwe et al., 2014). Agricultural extension is an essential source of information, knowledge, and advice to smallholder farmers in Bangladesh. Subsequent provision of technical supports (extension services) will increase farmers’ knowledge, skills, and awareness towards innovations. Therefore, extension contact is hypothesized to influence farmers’
adaptation to salinity intrusion negatively/positively.
For the farmer to farmer extension services, it was found that about 60% of farmers had farmer to farmer extension services while 40% farmers had no access to this facility (Figure 5(b)).
Subsequently, the farmers who have enough knowledge of climate change will be able to adapt to the effect of salinity intrusion. Most of the farmers (42.5%) had low knowledge about climate changes while approximately 30% of farmers had exceptionally low knowledge to no knowledge at all on climate change. Only 10.8% of farmers had a piece of remarkably high knowledge of climate change (Figure 5(c)). Credit accessibility is very much important for the farmers, especially for the smallholder farmers. The farmers should have easy access to credit so that they can be able to take proper action. From the study, it is found that 70% of farmers had medium access to credit whereas 20.8% had high access to credit. Only 8.3% had low access to credit (Figure 5(d)). Access to credit service is an important factor to narrow the financial gap of the farmers so that they could purchase the required farm inputs and technologies that are useful for improving agricultural production and also to carry out income-generating activities other than farming (Komba and Muchapondwa, 2015). This variable is therefore assumed to influence farmers’ adaptation efforts to salinity intrusion either positively or negatively.
Figure 5: (a) The category of farmers according to their knowledge of agriculture; (b) category of farmers according to their agricultural extension services; and (c) farmer to farmer extension services; (d) classifies the farmer according to their knowledge on climate change.
Adaptation measures of salinity intrusion Management of cropping pattern
Crop production loss is the main outcome of salinity intrusion in the area. If the production loss is reduced, the effect of salinity intrusion on the agricultural sector will also be mitigated. For this reason, different adaptation techniques for crop production is identified. Due to high salinity levels, it is difficult to cultivate any high yielding variety (HYV) crops, such as HYV Aman and HYV boro. To ensure food security, the farmers in this area cultivate 13 local saline-tolerant varieties of rice that are especially suited to the current circumstances of this area. These rice varieties include jotabalam, ashfall, ghunshi, and benapol. Based on the land type, some of these local rice varieties are categorized for shrimp farms and other agricultural lands. Akter and Ahmed (2020) recently showed that seasonal livelihood calendar changed in the coastal areas due to climate change and salinity problems, and farmers are adopting shrimp and crab cultivation. For example, Jotabalam and Ghunshi varieties are selected for cultivation in the shrimp farms. On the contrary, Ashfall and Benapol varieties are destined for other agricultural farms (Table 1). Besides, approximately 39%
of the farmers had a moderate perception of saline tolerant crop variety. Although many rice and vegetable varieties with salt-tolerance are suggested for coastal agriculture, an effective plan should be carefully assessed during the low-rainfall and dry season, identify which water sources can be used to irrigate, so that excess salinity in the crop fields does not accumulate and plant failure can be avoided (Shammi et al., 2016). Moreover, the changed cropping pattern helps to reduce the effect of salinity intrusion on crop production. Cropping intensity should be modified in slightly saline
areas by adopting proper soil and water management practices with the introduction of salt-tolerant crop varieties. During this dry season (Rabi/winter season), salt-tolerant minor cereal crops such as lentil, mung bean, and pea and different vegetables might be cultivated through the proper management of drainage systems.
Table 1: A list of saline tolerant varieties suitable for crop production in the study area No. Name of the crop Variety References 1 Rice BRRI dhan 40, 41, 47, 54, 78
BINA dhan 8, 10
(BRRI, 2011) (BINA, 2020)
2 Potato BARI Alu-72, 73 (BARI, 2020)
3 Tomato BINA Tomato 6 (BINA, 2020)
4 Mustard BINA Sarisha 5, 6 BARI Sarisha 11, 16, 17 Daulot (RS-81)
(BINA, 2020) (BARI, 2020) 5 Sweet potato BARI Sweet Potato 6, 7 (BARI, 2020)
6 Wheat BARI gom 25, 26
7 Turmeric BARI halud-5 (BARI, 2020)
8 Mungbean BINA Mung-8
BARI Mung-2
(BINA, 2020) (BARI, 2020) 9. Vegetable BARI puishak-1, 2 (BARI, 2020) Agricultural land and groundwater management
Levelling of land is an effective technique that helps to reduce the effect of salinity intrusion in crop production. Slight variations in the land lead to salt accumulation in the crop fields. Land should be properly levelled to prevent the accumulation of water in the low-lying patches with shallow groundwater tables and to facilitate a uniform drainage system for removing excess water.
It will also help to apply irrigation water uniformly in the field during Rabi season (January–
March), which will facilitate uniform germination of seeds and better growth of crops. Haque (2006) recommends that the levelling of soil also supplies nutrients uniformly in the salinity affected crop fields.
The saline groundwater in is found in a shallow depth (about 1.0 metre) in the study area. Keeping lands fallow leads to high salinity in soil due to the evaporation of excessive soil moisture.
Therefore, it is recommended that keeping lands fallow during Rabi season (winter season) should be avoided. This can be done by the reintroduction of deep-rooted salt-tolerant perennial plants that continue to grow and use water during the seasons that do not support annual crop plants. This may restore the balance between rainfall and water use, thus preventing rising water tables and the movement of salt to the soil surface. This will help maintain of soil salinity profile. It is also necessary to decrease the water table level and maintain it below the critical depth to prevent the salt from influencing crops. To achieve this objective, proper subsurface drainage must be installed to keep the groundwater at least 1.5 metres below the soil surface. Salinity is managed by a combination of vegetation and engineering strategies designed to create the reduction of water in these areas. The planting of vegetation with high water usage can be utilized to reduce groundwater recharge and to intercept water as it moves through the soil.
Also, since soils, in general, are infertile with low organic matter content, it is necessary to apply appropriate fertilisers to increase crop production. Potash fertiliser (potassium sulphate K2SO4) has an added advantage in saline soil as it lowers Na+ uptake by plants and increases K+ uptake. Thus, potash fertilizer protects crops from harmful effects of Na+. This crop nutrient management is one of the best options to increase plant productivity in a saline environment. It was observed that the uptake and accumulation of nutrients like calcium, magnesium, potassium, and phosphorus increase in plants subjected to Potassium fertiliser application under saline environments.
Water management
Using the Pond Sand Filter (PSF) technique is mainly used to reduce the effect of salinity intrusion on drinking water quality. This is a popular option of potable water supply through the treatment of surface water in the coastal belt. The intervention of PSF by UNICEF and DPHE was carried out along the coastal belt since 1983 (DPHE and UNICEF, 1989). The technology is very well adapted to coastal areas which are not feasible for Deep Tube Well (DTW) installation because of non-availability of suitable aquifer producing acceptable quality and quantity of water; where the shallow aquifer is contaminated with arsenic or existence of excessive salinity in the groundwater, where there are no available safe water sources and where the sources are far from the users' households. However, regular operation and management mechanism of the ponds and PSFs have been ensured by paid caretakers under the supervision of a management committee. Also, excavating, or renovating ponds on higher ground is another means of producing access to sweet water for drinking and agriculture through building strong and high embankments. Moreover, rooftop catchment areas are set up in roofs of the homestead by the Comprehensive Disaster Management Program (CDMP) with DPHE (Abedin and Shaw, 2018). This technique has been modified through different non-governmental organisations to provide the needy at affordable costs to harvest rainwater for drinking. Likewise, during disasters, many NGOs provide a plastic sheet with a hole in the middle to collect rainwater when scarcity of water is high. This sheet is set by spreading it on four bamboo poles or on a thatched roof to collect rainwater. Very recently, high- tech and high-cost drinking water solutions such as solar-powered desalination plants and reverse osmosis (RO) machines were set by NGOs which are both options to reduce the salinity of the water (Table 2).
Table 2: Adaptation measures of salinity intrusion according to the perception level of farmers
Adaptation Measure Not at
all Little Moderate High Very
High Total Saline Tolerant Crop Variety (STCV) F% 21.7 15.0 39.2 13.3 10.8 100
Pond Sand Filter (PSF) F% 13.3 9.2 30.8 35.0 11.7 100
Excavating or renovating pond on higher ground (ERPHG)
F% 46.7 11.7 18.3 14.2 9.2 100
Rooftop catchment areas (RCA) F% 42.5 22.5 28.3 4.2 2.5 100
Levelling of land (LL) F% 10.0 40.8 30.0 11.7 7.5 100
Planting crops in Rabi season (PCRS) F% 12.5 43.3 36.7 4.2 3.3 100
Fallowing land (FL) F% 18.3 22.5 26.7 20.0 12.5 100
Appling potash fertilizer (APF) F% 10.8 10.8 26.7 43.3 8.3 100
Adaptation Measure Not at
all Little Moderate High Very
High Total Reducing groundwater level (RGWL) F% 10.0 11.7 26.7 43.3 8.3 100 Plastic sheets with a hole (PSH) F% 39.2 20.0 17.5 11.7 11.7 100 Solar-powered desalination (SPDP) F% 65.8 12.5 6.7 9.2 5.8 100
Rainwater harvesting (RH) F% 1.7 5.0 50.0 23.3 20.0 100
Statistical analysis among the socio-economic status of farmers and their choice of adaptation measures
Taking into account the variables of socio-economic analysis such as age-group, level of education, family size, farming occupations, farming experiences, training experiences, farm size, tenure status of farm, annual income, communication skill, organisational participation, access to agricultural extension, farmer to farmer extension and knowledge about climate change significantly influences farmers’ adaptation choices to salinity intrusion. Many of these variables are also indicated as important variables in the studies of (Deressa et al., 2008; Maddison, 2007;
McNamara et al., 1991), and others cited in sections dealing with determinants of adaptation to salinity intrusion. The responses from the farmers recorded were: STCV= Saline Tolerant Crop Variety; PSF= Pond Sand Filter; ERPHG= Excavating or renovating pond on higher ground; RCA=
Rooftop catchment areas; LL= Levelling of land; PCRS= Planting crops in Rabi season, FL= avoid keeping fallow land; APF=Applying potash fertilizer; RGWL = Reducing groundwater level; PSH=
Plastic sheets with a hole; SPDP= Solar-powered desalination plants and reverse osmosis; RH=
Rainwater harvesting. From Table 3, it was observable that, farmers with good agricultural knowledge and participation in the organisational activities had a significant influence on the choice of technologies. Moreover, farming experience, tenure status with PCRS; training experience with RCA, SPDP and RH; farm size with SPDP, PSF and LL; annual income with LL and RH; access to extension with LL, PCRS and RH; farmer to farmers extension with ERPHG and PSH.
Moreover, knowledge about climate change was significantly related to the ERPHG, RCA, PSH and SPDP.
Table 3: Regression analysis and the coefficient of variation on the determinants of farmers’ choice of adaptation for reducing the effect of salinity intrusion in the study area
In the DPSIR framework driving forces (Figure 4) are the hidden agenda wherein the study area the of salinity intrusion indicates the presence of climate change, flow control of shared transboundary rivers, lack of political willingness, shrimp cultivation. Driving forces lead to human activities that exert pressure on the environment such as water and soil salinisation (Shammi et al., 2019). Subsequently, the state of the environment is affected by the loss of croplands, low crop productions, change of soil structure and cropping patterns. The changes in the physical, biological, and chemical state of the study area are thus impacted by the disease of crops, loss of crops, increased fallow lands that in turn lead to economic loss. Responses by society or policy are the result of undesired impacts of salinity intrusion. From this study the most effective responses identified from the farmers’ perceptions were saline tolerant variety, pond-sand filter, rainwater harvesting, levelling land, applying potassium sulphate fertiliser and avoid fallowing land in the Rabi season.
Figure 4: DPSIR construction is a sequence of linkages beginning in conjunction with ‘driving forces’ through ‘pressures’ to ‘states’ and ‘impacts’ on the environment, socio-economy and demographic functions, ultimately heading towards political or social responses.
Conclusions
The coastal belt is at extreme risk due to high density of soil and water salinity. This coastal area in Bangladesh constitutes 20% of the country of which about 53% is affected by different degrees of salinity. The study has found the effect of salinity intrusion in the coastal area of Bangladesh.
The community people of this area said that the destruction of crop production due to salinity intrusion is a major cause of poor health status of the people. The rate of hypertension will be increased. People face different types of waterborne disease and different skin problems due to
salinity intrusion. The people of this area use different adaptation measures for reducing the effect of salinity intrusion. According to the peoples’ perception, these adaptation measures are effective for salinity intrusion where using saline tolerant crop variety and rainwater harvesting technique is most significant. From the statistical analysis, these adaptation measures are significant for salinity intrusion. Farmers are trying to cope with the effect of salinity intrusion through using these adaptation measures. At last, it can be said that due to natural, and anthropogenic causes as well as weak policy implementation, this salinity problem is increasing which has enhanced the negative impacts on the health of community people.
Acknowledegments
The authors would like to acknowledge all the farmers producing food despite salinity problems and climate disasters. We would also like to thank all the researchers working to improve salt- tolerant varieties, improving, and managing techniques for saline soil and water and maintaining food security.
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