Sundarbans Region Research Articles

Assessing Vulnerability to Cyclone Hazards in the World’s Largest Mangrove Forest, The Sundarbans: A Geospatial Analysis

The Sundarbans is the world’s largest contiguous mangrove forest with an area of about 10,000 square kilometers and shared between Bangladesh and India. This world-renowned mangrove forest, located on the lower Ganges floodplain and facing the Bay of Bengal, has long served as a crucial barrier, shielding southern coastal Bangladesh from cyclone hazards. However, the Sundarbans mangrove ecosystem is now increasingly threatened by climate-induced hazards, particularly tropical cyclones originating from the Indian Ocean. To assess the cyclone vulnerability of this unique ecosystem, using geospatial techniques, we analyzed the damage caused by past cyclones and the subsequent recovery across three salinity zones, i.e., Oligohaline, Mesohaline, and Polyhaline. Our study also examined the relationship between cyclone intensity with the extent of damage and forest recovery. The findings of our study indicate that the Polyhaline zone, the largest in terms of area and with the lowest elevation, suffered the most significant damage from cyclones in the Sundarbans region, likely due to its proximity to the most cyclone paths. A correlation analysis revealed that cyclone damage positively correlated with wind speed and negatively correlated with the distance of landfall from the center of the Sundarbans. With the expectation of more extreme weather events in the near future, the Sundarbans mangrove forest faces a potentially devastating outlook unless both natural protection processes and human interventions are undertaken to safeguard this critical ecosystem.

Assessing vulnerabilities and resilience in the Indian Sundarbans: A case study of gosaba C.D block, West Bengal, India

The Sundarbans region, being a largest mangrove extending over 10,000 sq. Km, is one of the most critical ecosystems in the world. Due to its coastal location, the region has been severely affected by climatic events, including recent cyclones Amphan and Yaas. The present study examines the nature of vulnerabilities and subsequent adaptation and recovery processes of the affected villages in the Gosaba C.D block due to the impacts of back-to-back extreme cyclonic events. In this study, we first introduce the sample characteristics with the help of descriptive statistics, followed by Principal Component Analysis (PCA) to assess the vulnerabilities faced by the coastal communities due to super-cyclones. A binary logistic regression was computed to predict the schemes accessed by the coastal communities based on criteria and predicted variables. Results indicate that agricultural land is most affected by saline intrusion, inundation, and erosion; while homesteads are affected by cyclones, inundation and erosion. This study also reveals the strong disparities among villagers’ in accessing the schemes provided by different institutions. Therefore, the socio-economic conditions of the coastal communities have deteriorated and altered their occupations from farming to fishing and other economic activities, with many migrating in search of employment. In conclusion, the adaptation strategies and recovery processes toward resilience building of the communities have been measured through frequency distribution based on selected variables. There is a need for building resilience in order to live with uncertainties, as their changing occupations have already indicated. Moving to other locations with proper planning and policy formulation by the state government may help them face the multiple challenges along with providing multiple options for livelihood security.

Spatial heterogeneity of cyclone induced social psychology in the Indian Sundarbans using empirical data and geospatial techniques

Recurrent cyclones in the Bay of Bengal affect the lives and livelihoods of coastal communities. However, studies on the socio-psychological behaviour of cyclone-affected communities in the Indian Sundarbans received less attention in the existing literature. Thus, the present work intends to explore the tropical cyclone induced livelihood vulnerability and spatial heterogeneity of socio-psychological behaviour. The study was systematically carried out considering four selected mouzas (villages) from Indian Sundarbans using robust geospatial and statistical methods. The results depict that during the cyclone, the maximum decrease of monthly per-capita income was recorded for Amrabati mouza due to the southernmost location with comparatively higher perceived socio-psychological threats as portrayed by the interpolation maps and hotspot analysis. Considering all the six cyclones, Dwariknagar mouza recorded a maximum rating for fear/phobia, psychological stress and shock while a minimum rating for physical stress. Thus, income, age, gender, caste and religion also significantly control socio-psychological behaviour as shown by p < 0.05 and principal component analysis. This research calls for a thorough investigation of cyclone-affected victims in the Indo-Bangladesh Sundarban region. This study helps better comprehend the mental health of the cyclone victims which is important before the policymakers for designing the appropriate measures.

Tidal variation and flow dynamics in Indian Sundarban based on field observation and numerical models

Sundarban is made up of a mesh of macrotidal estuarine systems that contain the world's largest mangroves, the eco-geomorphic environment of which is heavily influenced by tidal behaviour and flow characteristics. The present study aimed to identify the tidal attributes and document the flow character of Indian Sundarban throughout a fortnightly tidal cycle. As such, seven tide monitoring stations were installed across the Saptamukhi-Hariabhanga and connected river system to monitor tidal water levels. Based on this data, the Institute of Ocean Sciences' (IOS) method was used to extract 17-major tidal harmonic components to study the links between various oceanic and shallow-water tidal constituents that may contribute to tidal asymmetry. A Mike-21-flow model was also run to simulate the tidal flow of the regime. Result shows that the progression and convergence of tidal waves in the funnel-shaped estuarine system causes notable lag between the southern and northern limits (avg. 45 min over a 52 km-long stretch of Thakuran estuary). The harmonic components indicate that semi-diurnal M2, S2; over tide 2MS6; and diurnal O1, K1 are the major forces, shaping the tidal amplitude in this region. The third, fourth, and sixth diurnal constituents represent additional tidal components, although with relatively minor amplitudes. The transition from coastal to headward stations sees a shift in the relative phase from 93.73° to 96.17°, suggesting a flood dominance and minimal dissipation of energy within the system. Mike-21FM found that the spring flood-current speed with an average value of 0.42–0.56 m/s is significantly higher than the ebb current of averaging 0.25–0.32 m/s. The nature of neap tidal current speed in the Sundarban region generally mirrors that of the spring condition, although with much less intensity. We assume that since any bi-weekly hydraulic analysis has not yet been conducted in Sundarban, it may be highly valuable for future studies.

Quantification of heavy metals in wild gravid female mud crab (Scylla olivacea) collected from different rivers of Sundarbans mangrove region

Heavy metals pollution is one of our major problems in Sundarbans mangrove zone as we all their surrounding rivers. The presence of industrial development in the nearby areas of coastal and marine aquacultures sites are the cause of heavy metals pollution. The aim of the research was to quantify heavy metals in gravid female mud crabs (Scylla olivacea) in three different rivers of Sundarbans region. Mud crabs and their surrounding water and soil sediments were collected from Mongla, Kholpetua, and Kopotakkho rivers. Analysis of river water was conducted in the laboratory of Shiva Analyticals (India) Private Limited, India, whereas live mud crabs and sediment samples were analyzed from Quality Control Laboratory (QCL), Khulna, Bangladesh for the quantification of heavy metals. The results showed that the heavy metals As, Cr, Cd, Hg and Pb were detected in mud crabs and their surrounding river water and sediments, but the concentration of heavy metals in mud crabs was remains below the limit of human’s consumptions except the heavy metal Chromium (Cr). Maximum concentration of heavy metals was detected Kopotakkho river followed by Mongla and Kholpetua river. The concentration of heavy metals was highest in soil sediments followed by mud crabs and river waters. Mud crabs were contaminated by heavy metals that bioaccumulated from their surrounding sediments and water sources. The hierarchy of mean concentrations (mg/kg) of the heavy metals were Pb>As>Cr>Pb>Hg. Heavy metals are carcinogenic for human consumption when exceeded their permissible levels. It is urgent to stop pollution in Sundarbans mangrove zone and led to serve healthy foods for the nations.

Disaster management in the Sundarbans delta ecosystem through environmental governance and sustainable planning

The Sundarbans region is facing significant impacts on its ecosystem, business, agriculture, and environment due to inadequate disaster management. Storm surges, cyclones, and rising sea levels threaten the mangrove environment, causing permanent damage to farming and fishing communities, poverty, and revenue loss. The loss of mangroves affects ecological services like carbon sequestration, coastal protection, and biodiversity. To mitigate these risks, laws, growth promotion, catastrophe management plans, improved infrastructure, and public engagement in disaster response planning are necessary. Balancing environmental protection and economic expansion through climate-resilient farming techniques and sustainable agriculture is crucial. Tighter regulations, sustainable development strategies, stakeholder engagement, and advanced technology like AI can contribute to creating a resilient Sundarbans that protects the environment, improves community welfare, and ensures a sustainable future.

Optimizing tourist flows through operative carrying capacity assessment: The case of Bakkhali coastal tourism, W.B., India

&lt;p&gt;Carrying capacity assessment of nature-based tourist destinations is important for keeping the consumption of natural resources and anthropogenic pollution levels within environmentally safe and sustainable limits. With the mostly rural character of such destinations, the local community's well-being also needs to be prioritized. Exposure to natural hazards and climate crises have further exacerbated concerns about the long-term sustainability of these locations. The interrelationship between tourism intensity and its impacts clearly reflects Butler’s Tourism Area Life Cycle model of 1980. The ‘elements of capacity’ and their ‘critical range’ mark a significant threshold in the model that leads us to the concept of carrying capacity. The capacity may be physical, spatial, ecological, environmental, social, economic, management, and governance, among others. This is also linked with the quality of the touristic experience and satisfaction. In this context, aiming to understand the optimum level of tourist traffic flow in Bakkhali, one of the popular beach destinations of the deltaic island system of the Indian Sundarbans, this study assesses its visitor carrying capacity at three levels—physical, real, and effective. It also briefly introduces the idea of ‘operative’ carrying capacity at the fourth level. The study is based on tourist data until 2019 and adopts the well-established methodological framework of carrying capacity assessment applied widely in several settings. The result suggests that tourism operations at Bakkhali may optimally handle 2040 visitors per day, which may be stretched to a maximum of 2267 visitors per day. This may be used as baseline information for sustainable coastal tourism policy framing in the long term while planning for tourism management and infrastructure development in the Sundarban region in immediate terms.&lt;/p&gt;

Floral scents, specialized metabolites and stress-response activities in Heritiera fomes and Bruguiera gymnorrhiza from Sundarban mangrove ecosystem.

Floral biochemistry and stress physiology is an underexplored aspect of mangroves, which should be investigated as part of preservation and restoration efforts. A thriving true mangrove tree (Bruguiera gymnorrhiza (L.) Lamk.) and a threatened mangrove-associate species (Heritiera fomes Buch. Ham.) were studied in the Sundarban region of India for seasonal variations in floral odours, non-volatile phytochemicals, antioxidant enzyme activities, and surface water chemistry in surrounding habitat. Both species were found to exhibit significant differences in floral volatilomes, protein contents, antioxidant enzyme activities, total flavonoids, and total phenolic contents between spring and autumn blooms. The bird-pollinated flowers of B. gymnorrhiza also showed considerable seasonal differences in floral anthocyanin and proline contents, indicating vulnerability of the post-anthesis open flowers to environmental factors. Contrarily to previous findings, B. gymnorrhiza floral bouquet appeared to be enriched in various classes of volatiles - dominated by sulphurous compounds in bud stage and terpenoids in open stage. Floral anthocyanins, contributing to the striking colouration of the calyx, were found to comprise cyanidin and delphinidin derivatives. Other glycosides of cyanidin and delphinidin were detected in H. fomes flowers, contributing to visual guides to potential food rewards for pollinating insects. Floral tissue in H. fomes was found to be protected by densely overlapping layers of stellate trichomes containing sesquiterpenoids as phytoprotectants. Comparison of the two floral species suggested that H. fomes flowering is optimized to oligohaline (but not freshwater) vernal conditions; whereas B. gymnorrhiza blooms are adapted for biologically enriched (including abundant herbivores and microbial growth), mesohaline forest habitats.

Silvalis jairajpurii sp.n. with diagonostic compendium and keys to species including one known rare soil nematode (Nematoda: Dorylaimida) from Sundarban region of South 24 Parganas district, West Bengal, India

Silvalis jairajpurii sp. n., a new dorylaimid nematode under the subfamily Thornenematinae is described and illustrated in this study. This is found from rhizospheric soil of paddy in Gosaba block of Sunderban region of South 24 Parganas District of West Bengal, India. The species is characterised by medium sized body (1.5-1.6 mm) with sclerotized cheliorhabdions encircling the strong odontostyle, amphidelphic reproductive system with a very minute vaginal opening terminated by a short blunt, but rounded tail which show marked differences from other species of the genus. This is a plant parasite that affects paddy cultivation and rice in our staple food. So, this type of plant parasite causes economic loss of our country. The species key of this genus with compandium is also provided. Mylodiscus nanus is also rare nematode, reported from paddy field rhizospheric zone of Gosaba block, Sundarbans part of South 24 Parganas, West Bengal of India. It is a predatory nematode.

Using unsupervised machine learning models to drive groundwater chemistry and associated health risks in Indo-Bangla Sundarban region

Groundwater is an essential resource in the Sundarban regions of India and Bangladesh, but its quality is deteriorating due to anthropogenic impacts. However, the integrated factors affecting groundwater chemistry, source distribution, and health risk are poorly understood along the Indo-Bangla coastal border. The goal of this study is to assess groundwater chemistry, associated driving factors, source contributions, and potential non-carcinogenic health risks (PN-CHR) using unsupervised machine learning models such as a self-organizing map (SOM), positive matrix factorization (PMF), ion ratios, and Monte Carlo simulation. For the Sundarban part of Bangladesh, the SOM clustering approach yielded six clusters, while it yielded five for the Indian Sundarbans. The SOM results showed high correlations among Ca2+, Mg2+, and K+, indicating a common origin. In the Bangladesh Sundarbans, mixed water predominated in all clusters except for cluster 3, whereas in the Indian Sundarbans, Cl−-Na+ and mixed water dominated in clusters 1 and 2, and both water types dominated the remaining clusters. Coupling of SOM, PMF, and ionic ratios identified rock weathering as a driving factor for groundwater chemistry. Clusters 1 and 3 were found to be influenced by mineral dissolution and geogenic inputs (overall contribution of 47.7%), while agricultural and industrial effluents dominated clusters 4 and 5 (contribution of 52.7%) in the Bangladesh Sundarbans. Industrial effluents and agricultural activities were associated with clusters 3, 4, and 5 (contributions of 29.5% and 25.4%, respectively) and geogenic sources (contributions of 23 and 22.1% in clusters 1 and 2) in Indian Sundarbans. The probabilistic health risk assessment showed that NO3− poses a higher PN-CHR risk to human health than F− and As, and that potential risk to children is more evident in the Bangladesh Sundarban area than in the Indian Sundarbans. Local authorities must take urgent action to control NO3− emissions in the Indo-Bangla Sundarbans region.

Vegetation Health and Forest Canopy Density Monitoring in The Sundarban Region Using Remote Sensing and GIS

The present study explores vegetation health and forest canopy density in the Sundarbans region using Landsat-8 images. This work analyzes changes in vegetation health using two vegetation indices, the Normalized Difference Vegetation Index (NDVI) and Forest Canopy Density (FCD) values of the Sundarbans, from 2014 to 2020. NDVI, comprising two bands, Red and Near-infrared (NIR), shows a declining trend during the period. Two NDVI land cover classification maps for 2014 and 2020 are produced, and the interest area is divided into five classes: Scanty, Low, Medium, and Densely Vegetated Regions and Water Bodies. A single-band linear gradient pseudo-color is used to assess the land cover difference between 2020 and 2014, showing marked changes in densely vegetative areas. The NDVI difference marks the coastal regions with a higher depletion rate of vegetation than the regions away from the seacoasts. FCD has been taken to compare the results of NDVI with it. FCD consists of another four models: AVI (advanced vegetative index), BI (Bare soil index), SSI (scaled shadow index), and TI (thermal index). FCD is also called crown cover or canopy coverage, which refers to the portion of an area in the field covered by the crown of trees. 2014 and 2015 FCD maps are produced with a single band linear gradient pseudocolor with five land cover classifications: bare soil, Bare Soil, Shrubs, Low, Medium, and Highly vegetated regions. Both maps bear a significant resemblance to NDVI land classification maps. Further, the FCD values of the two maps are scaled between 1 and 100, and the area of each class is calculated. To check the veracity of the NDVI and FCD analysis, a Deep Neural Network (DNN) model has been developed to classify each year’s image taken from Google Earth Engine (GEE). It classifies each year’s image with 99% accuracy. The calculation of the area of each class emphasizes the rapid decline of densely wooded vegetation. Almost 80% of the highly forested zone has been diminished and has become part of the medium-forested region. Area inflation in medium-forested regions corroborates the same. The study also analyzes the migration of vegetation density, i.e., where and how many areas are unchanged, growing, or deforested.

Quantification of Bioclimatic Performance of Rural Coastal Low-Cost Dwellings in the Sundarbans

As we are aware that climate change poses a significant threat to environmental quality, human health, and well-being, etc., it is important to mitigate the environmental adverse impacts on human health. To do this, a necessary step forward is a bioclimatic analysis that includes a quantitative understanding of eco-human-energy friendliness. The study evaluates the environmental performance of low-cost coastal dwellings by analyzing bioclimatic components. Primary data was collected from field investigation and the perception response of 1332 dwellers from the selected blocks of coastal Sundarban region, West Bengal including remote rural, rural, and semi-urban areas was recorded. The statistical analysis indicated the upper 95% confidence limit for each subgroup and a normalization of the upper confidence limit with a unity score of 10 for each subset of parameters. The total score of the five categories of bioclimatic components was rounded to 150. A comprehensive evaluation of bioclimatic aspects of low-cost dwellings and scoring of features (design strategies, indoor environmental quality, thermal comfort, and energy efficiency) significantly yielded a quantitative rating of the performance of a rural built environment. Overall, this study successfully quantified the evaluation of the bioclimatic performance of low-cost coastal rural dwellings, which may be useful to develop strategies or building codes for the passive design of dwellings in the coastal, rural areas of India.

Kharif rice growth and area monitoring in Gosaba CD block of Indian Sundarbans region using multi-temporal dual-pol SAR data

Kharif rice growth and area monitoring in Gosaba CD block of Indian Sundarbans region using multi-temporal dual-pol SAR data

Evaluation of overwash vulnerability and shoreline dynamics in cyclone-prone Sagar Island, Sundarbans (India)

Situated in the climatically vulnerable Sundarbans region, Sagar Island has increasingly been subjected to intense cyclonic events, including Yaas, Amphan, Bulbul, and Aila, leading to significant alterations in its coastal morphology. This study aims to elucidate the overwash vulnerability and shoreline dynamics in Sagar Island, spanning the period from 2000 to 2020. Utilizing satellite imagery, the study employs three indices—Overwash Shoreline Ratio (OSR), Maximum Overwash Intrusion Recurrence (MOIR), and Complete Barrier Overwash (CBO)—to assess overwash vulnerability. These indices collectively indicate a heightened susceptibility to overwash intrusion, with a particular focus on the years following severe cyclonic events. Additionally, shoreline change dynamics were quantitatively analyzed using the Digital Shoreline Analysis System (DSAS) tool, revealing a strong positive correlation between shoreline recession and climatic variables. Interlinkages between overwash vulnerability and shoreline dynamics were established, confirming that both phenomena are exacerbated by climate change and extreme weather events. The study's findings have critical implications for a broad range of sectors such as agriculture, fisheries, transportation, and ecosystem conservation. The research underscores the urgency for an integrated coastal management strategy that considers both overwash vulnerability and shoreline change dynamics to enhance sustainability and resilience. This study contributes to the global discourse on coastal dynamics, serving as a benchmark for climate adaptation measures in other cyclone-prone regions.

Political ecology of climate change in Sundarbans, India: Understanding well‐being, social vulnerabilities, and community perception

AbstractThis study is an attempt to review the climate change phenomenon through the theoretical lens of “Political Ecology of Health.” It identifies the strategic implications of climate change policies on health and well‐being in the Sundarbans region of India and other related factors which come into play in determining the health status there. It encapsulates the existing vulnerabilities observed in this eco‐sensitive region and tries to reflect on the community's perception of the climate change crises inflicted upon them. The paper presents a comprehensive review of current conditions in the region. In addition to utilizing electronic databases, the author also reached out to experts from pertinent organizations with related expertise to gather supplementary references. Adapting to climate change is crucial to cope with the changing surroundings and elevate competency. Since Sundarbans’ adaptation strategies are intricately dependent on historical positionality, community behavior, gender roles, social capital, and ecoregion sensitivity, the well‐being and recovery in the community are very much context‐specific. Thus, it must give space to discourses of newer politics of adaptation, emerging from a rigorous ecological standpoint. Looking into the matter through the lens of “situated knowledge, political economy and socio‐ecological relationships” brought out important issues like land‐ownership conflict, fading away of the traditional knowledge system, conspicuous utilization of funds and a poor public health system.

Spatial variation in livelihood security among livestock-based agricultural farming systems in climatically vulnerable Indian Sundarbans.

Farm households in the UNESCO World Heritage site Sundarbans face serious problems, including increased soil salinity, frequent extreme weather events, seawater intrusion and flood damage, all of which cause distress to the livelihoods of the farm families. Policymakers commonly acknowledge livestock as a crucial resource for mitigating economic losses caused by crop failures due to extreme weather events. Despite Sundarbans' vulnerability to extreme weather events, smallholder farmers' livelihoods vary across the region. Identifying spatial livelihood variations aids in targeted strategies to address climate extremes. We chose the highest cow- and buffalo-populated blocks among the 19 blocks in the Sundarbans to assess variations in livelihood dimensions, including nutritional, economic, social and infrastructural security. We used dummy variable regression models to examine the differences in livelihood security dimensions among households living in different locations. The study found that Namkhana had the highest livelihood security score among the blocks studied, while Gosaba had the lowest score because it's in a remote area with limited infrastructure. The study found a significant difference in the overall livelihood security score among the blocks we examined, indicating the need for a location-specific, cluster-based approach for the overall development of the Sundarbans. The study can shape a policy framework for socio-economic development in the Indian Sundarbans through its findings on location-specific livelihood security. For securing smallholder farmers' livelihoods in the vulnerable Sundarbans region, policymakers must give priority to improving infrastructure, viz., roads, marketing facilities and animal healthcare centers.

Deployment of entropy information theory in the Indian Sundarban region using hydrogeochemical parameters and GIS for assessment of irrigation suitability.

The evaluation of irrigation suitability plays a crucial role for the socio-economic development of the society, especially in the region of Sundarban. For sustainable agricultural practices, groundwater quality must be suitable for irrigation; otherwise, it can degrade soil and diminish crop yield. The entropy information theory, several irrigational indices, multivariate statistics, GIS, and geostatistics are used in this work to evaluate the geographical distribution and quality of groundwater in the Indian Sundarban region. In total, 33 groundwater samples were collected in 2018 (April and May), and they were evaluated for major cations, anions, as well as other parameters like electrical conductivity (EC), soluble sodium percentage (SSP), potential salinity (PS), total dissolved solids (TDS), Kelly ratio (KR), sodium absorption ratio (SAR), permeability index (PI), residual sodium carbonate (RSC), magnesium hazard (MH), and residual sodium bicarbonate (RSBC). The overall trend of the principal cations and anions is in the sequence of Na+ ≥ Mg2+ ≥ Ca2+ ≥ K2+ and HCO3- ≥ Cl- ≥ NO3- ≥ SO42- ≥ F-, respectively, whereas the spatial variation of %Na, SAR, RSBC, and MH demonstrate very poor irrigation water quality, and spatial variation of KR, RSC, SSP, PI, and PS signifies that the irrigation water quality is excellent to good. In order to identify the specific association and potential source of the dissolved chemical in the groundwater, statistical techniques like correlation and principal component analysis were also employed. The hydrochemical facies indicates that mixed type makes up the bulk (51.51%) of the water samples. Following the Wilcox plot, more than 75% of the water samples are good to doubtful; however, by the US salinity hazard map, roughly 60.60% of the samples had high salinity (C3-S1 zone). The EWQII reports that no samples fall into the very good (no restriction) category, whereas 30.30%, 30.30%, and 39.40% of the sample wells record good (low restriction), average (moderate restriction), and poor (severe restriction) irrigation water quality, respectively. Based on this study, the bulk of the groundwater samples taken from the study area are unsuitable for cultivation. The findings of this study will also help decision-makers develop adequate future plans for irrigation and groundwater resource management.

OSCILLATION OF HYDROLOGICAL PARAMETERS IN SHRIMP PONDS WITHIN MANGROVE-DOMINATED INDIAN SUNDARBANS

The survival rate of Penaeus monodon was monitored for a decade (2010-2019) in two shrimp culture ponds at Chemaguri located at Sagar Island in the Indian Sundarbans delta complex. The two ponds exhibited significant variations in terms of the survival rate of the cultured species, which is attributed to variations in nitrate, phosphate, and dissolved oxygen. The root cause of such difference is related to variation in stocking density of the cultured species (10 PL20/m2 in pond 1 and 25 PL20/m2 in pond 2) which resulted in the generation of nutrients (except silicate) and alteration of Dissolved Oxygen (DO). Optimization of stocking density and introduction of a biotreatment pond may restore and ecologically balance the situation in the shrimp culture sector of the Sundarban region.

Rapid, Landscape-Scale Assessment of Cyclonic Impacts on Mangrove Forests Using MODIS Imagery

Cyclones are a key disturbance in mangrove ecosystems, but it is challenging to assess post-storm impacts over large areas, along with the recovery of these systems at broad temporal scales. Given the high frequency of these events in the Sundarbans region, prompt and consistent assessment of vegetation conditions is an important research need. Several studies have assessed the impact of an extreme cyclone event in 2007 (Sidr); however, there is little agreement between the extent and severity of the disturbance footprint of the cyclone, and very few studies attempted to assess vegetation recovery. We used a MODIS (Moderate Resolution Imaging Spectroradiometer) time series (2001–2010) to calculate monthly plant productivity anomalies in Google Earth Engine. We summarized dry season anomalies to assess post-storm vegetation change and evaluate the recovery time. Approximately 2100 km2, primarily on the east side, were impacted by Sidr. The number of damaged pixels was reduced by 55% the following dry season (2008) and 93% in the dry season of 2009, indicating a near-full recovery 26 months after the event. Our results provide an additional line of evidence to provide a rapid assessment of the post-storm vegetation damage. The simple framework used can provide a comprehensive view of the extent of the damage, including lag effects on vegetation, in just a matter of months after the event.

Long-term ecological vulnerability assessment of Indian Sundarban region under present and future climatic conditions under CMIP6 model

Vulnerability assessment of ecosystem bestows an idea about the ecosystem health and its ability to resist environmental stress. Indian Sundarban region situated at the southwest part of Ganga-Brahmaputra-Meghna delta has been under constant threat of frequent climate hazards and long-term climate change. Various attempts have been made for vulnerability assessment of this mangrove ecosystem focusing only on static non-temporal variables. The present work hypothesises that mangrove ecosystems are highly adaptive and respond to the changing environment by various natural resilience strategies at the ecosystem level. So, a better understanding of the dynamics of mangrove ecosystem will provide an idea about the state of vulnerability for this ecosystem. The present study uses 16 parameters to create exposure, sensitivity and adaptive capacity risk indices and constructs the vulnerability status for the Indian Sundarban. The results showed that the sea-level rise will happen between 0.7 m to 0.9 m under baseline climate conditions. The CMIP6 multi-model ensemble showed that the future minimum temperature for the region will go up to 29.48 °C, thereby reducing the max and min temperature difference for the region. The fuzzy AHP-based vulnerability assessment revealed that the western Sundarban is more prone to climate vulnerability. The island-like Surendranagar, Lothian, and West-Ajmalmari are extremely vulnerable. The proximity to human habitat will play an important role in climate change sensitivity to the Sundarban region. The time series analysis of mangrove forests showed the Mann-Kendall ‘τ’ value varies between 0.82 to −0.83. The central Sundarban forests area shows a varying degree of forest health deterioration. The assessments from the present study and the maps will help the environmental and risk-managers to identify the regions needing more climate change adaptation strategy.