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The paper narrates an empirical research conducted for developing four alternative socio-ecological scenarios for the lower Gangetic delta in India (aka the Indian Sundarban). We used the Story and Simulation (SAS) approach' to build four short-term, landscape-scale scenarios for 2030, which include a Business as Usual (BAU)', and three alternative scenarios, namely Market forces', Delta Republic' and Green Sundarban'. The storylines were built after careful screening of existing development and conservation plans, as well as by consulting local government officials. The storylines were then simulated using the Multi-Layer Perceptron-Markov Chain Analysis (MLP-MCA) model, with a multitude of factors, constraints, and attributes for each scenario. Historical and current land use maps of 2006 and 2016, derived from Landsat series (ETM+ and OLI), were used as the fundamental input to the model, which were also utilized to locate decadal changes, create several independent driver variables, calculate transition potentials and ultimately to develop future land use maps. To generate the scenarios, we used a Linear Programming (LP)-based land demand optimization method to alter the transition potential matrix. Our results indicated considerable loss of mud/tidal flats and viz.-a-viz. increase in river/water areas under all the four scenarios. We further observed moderate to a significant expansion of aquaculture for all the scenarios, with an almost two-fold increase under the Market forces scenario. In addition, three of the four scenarios indicated moderate loss of mangroves. The future extent of mangroves may vary from 1997.92km(2) (BAU) to 2172.25km(2) (Green Sundarban), which indicates to 3.72% overall decline (0.31% decline/year) to 4.67% (or 0.38% increase/year) overall gain from the present extent. As such, the Green Sundarban scenario was identified to the best possible pathway to serve the conservation interests and future sustainability of the delta. The results from the scenario analysis remain imperative to understand, plan and prepare for the plausible alternative regional futures, thereby optimizing conservation and development through proactive policy planning.