Search

The effect of environmental policy on water resources is often challenging to evaluate due to dynamic interactions between people and water, particularly in data‐scarce watersheds. Increasing interactions between society and hydrology present a need to understand causal relations for improved assessment and prediction in complex human‐water systems. Conventional approaches to causal assessment in hydrology are sometimes insufficient due to data scarcity or system complexity. We argue that natural experiments present a promising and complementary avenue for assessing causal relations in such systems. In this spirit, we describe a natural experiment to assess causal effects of the Ganges water treaty, between India and Bangladesh, on streamflow and channel salinity in the Ganges delta in Bangladesh. We apply causal inference to assess the effect of the treaty on streamflow and use the results to generate synthetic ensembles of streamflow and salinity under a realistic scenario (with the treaty) and a counterfactual scenario (without the treaty). We then use synthetic streamflow ensembles to model salinity ensembles. The Ganges water treaty increased dry‐season streamflow in Bangladesh by approximately 18% and decreased channel salinity by approximately 10%. The treaty has the greatest effect on salinity in Bangladesh in the driest years, but the overall effect is small compared with natural variability. We show that our approach accounts for natural hydrologic variability to accurately assess the causal effect of the treaty, compared with a naive approach that greatly overestimates the effect. This research demonstrates the value of natural experiments for causal assessment in coupled human‐water systems. Key Points: Natural experiments and counterfactuals are promising tools for causal assessmentWe use a natural experiment and generate counterfactuals to assess the effect of the Ganges water treaty on streamflow and salinityThe Ganges water treaty plays a modest yet important role in reducing salinity in the delta in Bangladesh [ABSTRACT FROM AUTHOR]

• We enumerate 25,000 + solutions for the Ganges water sharing treaty, renewed in 2026. • Hierarchical clustering identifies redundant objectives and governing trade offs. • Pareto-optimization & scenario-neutral analysis finds climate-robust treaty solution. 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 objectives associated with each party's priorities are not necessarily common knowledge (framing uncertainty), and the direction, amplitude and effect of long term changes in hydro-climatic drivers can be highly uncertain (climate uncertainty). We frame the design of a transboundary treaty as a multi-objective optimization problem. We use hierarchical clustering to address problem-framing uncertainty by identifying the subset of objectives associated with the governing trade-offs imposed by the bio-physical characteristics of the shared river system. We then carry out a scenario-neutral climate sensitivity analysis to identify climate-robust Pareto-optimal treaty solutions. We illustrate the approach for the Ganges water agreement, which is due to be renewed in 2026. Based on an enumerated population of 25,121 feasible treaty solutions, we identify governing objectives and 16 treaty solutions that 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 for the Ganges water treaty and, more broadly, a template to support transboundary cooperation over shared international rivers. [ABSTRACT FROM AUTHOR]