Inseeyong et al. (2025) Regionalization of standardized sediment rating curves for enhancing data continuity in ungauged catchments

Identification

• Journal: CATENA
• Year: 2025
• Date: 2025-09-01
• Authors: Nantawoot Inseeyong, Pavisorn Chuenchum, Bofu Yu, Mengzhen Xu
• DOI: 10.1016/j.catena.2025.109418

Research Groups

• State Key Laboratory of Hydroscience & Engineering, Tsinghua University, Beijing 100084, PR China
• Key Laboratory of Hydrosphere Sciences of the Ministry of Water Resources, Tsinghua University, Beijing 100084, PR China
• Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, PR China
• Department of Water Resources Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand
• Australian Rivers Institute, School of Engineering and Built Environment, Griffith University, Nathan, Queensland 4111, Australia

Short Summary

This study develops a regionalization approach for sediment rating curve (SRC) parameters to estimate sediment load in ungauged catchments using only discharge data and catchment attributes. The approach, validated in the Mun River Basin, demonstrates acceptable performance (0.43 < NSE < 0.95, −58 % < PBIAS < 53 %) and provides a practical framework for data-scarce regions.

Objective

• To develop a regionalization approach for sediment rating curve (SRC) parameters to estimate sediment load using only discharge data and catchment attributes of ungauged catchments.

Study Configuration

• Spatial Scale: Mun River Basin, Thailand (the largest tributary of the Mekong River Basin, which covers approximately 606,000 square kilometers).
• Temporal Scale: Not explicitly specified for the observed data used in the study; the methodology aims to provide data continuity for sediment load estimation.

Methodology and Data

• Models used: Sediment rating curves (SRCs) in the form Qs = aQb; Revised Universal Soil Loss Equation (USLE) for the cover and management factor (CUSLE).
• Data sources: Observed flow and sediment data (original data); Catchment attributes including mean catchment slope gradient (SC) and CUSLE factor.

Main Results

• A regionalization approach with a fixed rating exponent (b₀ = 0.98) and the rating coefficient (aᵢ) as a function of mean catchment slope gradient (SC) and the CUSLE factor showed acceptable performance.
• The sediment load predictions achieved performance metrics of 0.43 < Nash-Sutcliffe Efficiency (NSE) < 0.95 and −58 % < Percent Bias (PBIAS) < 53 %.
• This regional approach performs comparably to individual SRC parameterization while minimizing error propagation risks in sediment load predictions.

Contributions

• Provides a practical and transferable framework for estimating sediment load in data-scarce regions, particularly in developing and transboundary river basins.
• Enables sediment load estimation using minimal data requirements (only discharge and catchment attributes).
• Minimizes error propagation risks compared to traditional individual station-based SRC parameterization.
• Supports sustainable water resources management, hydrological, morphological, and erosion management.

Funding

• Not explicitly mentioned in the provided text.

Citation

@article{Inseeyong2025Regionalization,
  author = {Inseeyong, Nantawoot and Chuenchum, Pavisorn and Yu, Bofu and Xu, Mengzhen},
  title = {Regionalization of standardized sediment rating curves for enhancing data continuity in ungauged catchments},
  journal = {CATENA},
  year = {2025},
  doi = {10.1016/j.catena.2025.109418},
  url = {https://doi.org/10.1016/j.catena.2025.109418}
}