Understanding the Interannual Variation in the River Stage–Discharge Relationship and Its Impact on Flood Discharge Estimation

Stage–discharge relationships or rating curves are essential for estimating river discharge when direct flow monitoring is challenging. Although various hydrometeorological factors affect streamflow, understanding the rating curve variability and its local and global drivers are crucial for gaining deeper insights into riverine processes. However, limited studies have addressed the uncertainties (such as parametric and observational uncertainties) associated with the stage–discharge relationship and further investigated the potential drivers of the uncertainties. The current study has three major objectives: (1) develop a robust process-based stage–discharge relationship that can account for interannual shifts in rating relationships, (2) estimate the influence of a robust rating curve in flood discharge measurement, and (3) understand the climate and morphological drivers that impact the interannual variation in the stage–discharge relationship. Toward this, a Bayesian rating framework based on on-site hydraulic knowledge was adapted for five gauging stations in the Mahanadi and Godavari basins of the Indian peninsula. Interannual variations in rating parameters and the differences in high and low estimations were obtained using rating curves with all gauging pooled and split yearly. Furthermore, a boosted regression forest model was employed to identify the most significant predictors of key rating parameters based on associations among rating drivers. The findings revealed substantial interannual variations in rating parameters, resulting in a high magnitude of difference in streamflow estimation, ranging from −69.1% to 94.3% when considering rating shifts. Additionally, the natural climate variability modes were identified as key predictors in developing stage–discharge relationships, explaining the significant variance in rating parameters. This study emphasizes the importance of developing holistic river monitoring approaches for accurate flow assessment and minimizing hydrological risks.