Water scarcity, defined as an adverse imbalance between freshwater availability and water demand, is a critical concern in the 21st century, and is exacerbated by climate change and increased uncertainties in hydrological cycles. Rising water demands driven by rapid population growth, urbanization, and industrialization further intensify water scarcity, posing significant threats to sustainable development. Addressing water scarcity is particularly challenging in regions with limited data availability, and data constraints can necessitate the use of a water balance approach to quantify water scarcity. Evaluating the hydrological balance of river basins in historical and projected future time periods requires the use of hydrologic and climatic models, wherein the selection of an appropriate model and modelling approach depends on research objectives, data accessibility, site-specific challenges, costs, and model accuracy. In response to these conditions, this study explores hydrological model-based estimates of water scarcity risk in the absence of sector-specific water demand data. Specifically, this study evaluates streamflow, ‘blue’ and ‘green’ water balance components derived from streamflow, and a risk-based measure of water scarcity calculated from those water balance components in the Baitarani river basin (13,000 km2), a basin influenced by climate and land use change. This analysis relies on historical observed climate and hydrologic data (1974–2018) from the Indian Meteorological Department (IMD) and Central Water Commission (CWC), modelled future climate (2020–2064) from the Coupled Model Intercomparison Project 6 (CMIP6), and the Soil Water Assessment Tool (SWAT) hydrologic model. This study finds that Baitarani basin water scarcity has decreased in recent decades (1994–2018) relative to earlier decades (1974–1993), and that water scarcity risk will also decrease in the future (2020–2064). Nevertheless, findings remain uncertain due to limited model structural representation of hydrologic processes that may change alongside land use and climate change drivers. Even so, this study offers valuable insights for parsimoniously evaluating basin-scale water availability and scarcity, aiding in the development of adaptive strategies for sustainable water management in data-scarce river basins.