Regionalization of standardized sediment rating curves for enhancing data continuity in ungauged catchments

Sediment load observations are often limited in time and space, particularly for river basins in developing regions. Sediment rating curves (SRCs) provide a practical method to calculate sediment loads from streamflow in areas with poorly gauged or no gauged (Q_s = aQ^b). However, the absence of sediment data for ungauged catchments poses challenges in estimating SRC parameters. This study develops a regionalization approach for SRC parameters to estimate sediment load using only discharge data and catchment attributes of ungauged catchments. The methodology was developed and validated in the Mun River Basin, the largest tributary of the Mekong River. Two regionalization approaches were considered and assessed: 1) an overall rating exponent (b_o) for all gauging stations while allowing rating coefficient (a_i) to vary as a function of catchment attributes; 2) both rating coefficient (a_i) and exponent (b_i) are allowed to vary from station to station. The regionalisation approach, with fixed rating exponent (b_o = 0.98) and involving the rating coefficient (a_i) as a function of the mean catchment slope gradient (S_C) and the cover and management factor from the Revised Universal Soil Loss Equation (C_USLE), showed sediment load predictions with acceptable performance metrics (0.43 < NSE < 0.95, and −58 % < PBIAS < 53 %). This regional approach performs comparably to individual SRC parameterization while minimizing error propagation risks in sediment load predictions. This practical and transferable framework enables sediment load estimation in data-scarce regions, supporting hydrological, morphological, and erosion management. Its simplicity and minimal data requirements make it a valuable tool for applications in developing and transboundary river basins.