Sunderban delta system, India: revisiting the coastal form-process dynamics


Networked by a complex tidal waterways, mudflats and series of small islands, the Sunderbans Delta System, located at the northern apex of Bay of Bengal (covering an area of 10,000 km2), harbors world’s largest mangrove ecosystem. The Ganges-Brahamaputra-Meghna river delta is represented by a low-lying flood plain covering more than 90,000 sq. km in India and Bangladesh and grades into a more extensive sub-aqueous delta and deep sea fan complex. Known to be recognized as UNESCO world Heritage site, 62% of the total area falls within Bangladesh and 38% in India.   
Geological/geomorphological studies and analysis of historical and recent maps/imagery for the Indian part of the Ganges-Brahmaputra composite macrotidal deltaic coast reveals a continuous trend of shoreline retreat over past hundred years. The long-term as well as the short-term prediction of morphological behaviour in the coastal zone and sediment transport in response to changing environmental conditions is an important issue in the perspective of sustainable development practices. Interaction between coastal processes operative over long (up to 100 years) and short-term period (5-10 years) and mainly two-dimensional evolution of the deltaic shoreline with special reference to sea level rise has been a matter of continued interest to the researchers. A GIS integrated information on long term coastal erosion/accretion rate reflected in the shoreline change index map for West Bengal (including open coast west of Hoogly estuary up to Digha) coast shows that about 75% of the total coastal segment is under retreating condition while 25% of this coast is under stable to advancing condition. This, together with field observations in Hoogly estuary suggest, tidal flow is one of the pivotal processes that controls the transportation and sorting of sediments driving the shoreline/landform changes within the coastal inlet, at least over decadal to sub-decadal scale. Unfortunately, quantification of shoreline change caused by short-term parameters is very difficult due to the inherent complex nature of the process interaction and lack of regular measurements of landform changes in response to these processes. To account for the effect of long term processes the present study shows, sea level rise over long time scale alone, can account at the best for 50-60% of the shoreline retreat following Brunn’s rule. This suggests that sea level rise, over a longer time frame plays a permissive role for shore line retreat for this coastal tract in presence of the other coastal processes like wave, tide etc. As an alternative, a spatio-temporal correlation based empirical model that can account indirectly for the cumulative effect of the short-term processes reflected into the shoreline change over long-term period correlating continuous along shore variation of sea level rise scenarios (for Ghoramara, Sagar and Bhangaduani Islands) was developed. The projected configuration of the islands for different time intervals and for a set of Sea Level Rise (SLR) scenarios shows that generally, with increase in sea level rise rate, rate of erosion increases. Model derived SLR scenario from forecast and hindcast situations indicate a falling trend of rate of sea level rise over last hundred years. The captured SLR for 1988-2001 was 2.8mm/yr. (Sagar) which is not on the higher side. At this rate of sea level rise the western half of the deltaic coast (Digha to Maushani Island) is under lesser threat of erosion compared to the uninhabited, forested eastern part of the deltaic coast (3.1mm/yr. SLR). The general agreement of the projected model output with the observed shoreline configuration establishes the predictive potentiality of the empirical model. As a way forward, the Regional Ocean Modeling System (ROMS) framework derived inputs are further being integrated into the existing empirical model to improve its efficacy. The present model outputs are also compared with few coastal area morphological models (viz., Digital Shoreline Analysis System -DSAS) developed by others for predicting shoreline changes.  The present knowledge base with further research is expected to open up new vistas for coastal zone management plan in this vulnerable populated tract of deltaic coast.