Climate change will alter the flow availability and expected water allocations in international river treaties, many of which were designed using historical flow records. Effective transboundary treaties should anticipate these concerns and seek to satisfy the priorities of all riparian countries while being robust to impending changes in climate. This task is complicated by the fact that specific outcomes associated with each party's priorities are not necessarily public information, and the direction, amplitude and effect of long term changes in hydro-climatic drivers can be highly uncertain. To address these challenges, we use hierarchical clustering to visualize the trade-offs imposed by the bio-physical characteristics of the shared river system and identify key hydrological outcomes associated with each country's priorities. We then use these outcomes in a Pareto-optimization process combined with a climate sensitivity analysis to identify climate-robust treaty alternatives. We illustrate the approach for the Ganges water agreement, which is due to be renewed in 2026. Using the current treaty as a template, we generated 25,121 treaty alternatives, and identified four key clusters of meaningful outcome variables for both India and Bangladesh. We then determined central variables of each cluster and show that 16 of the treaties are Pareto optimal under most considered combinations of changes in sea level and dry season flow regime. This work provides a path towards improving transboundary allocations in the Ganges water treaty and, more broadly, a template to support transboundary cooperation over shared international rivers.