Preprints
https://doi.org/10.5194/hess-2024-349
https://doi.org/10.5194/hess-2024-349
20 Nov 2024
 | 20 Nov 2024
Status: this preprint is currently under review for the journal HESS.

The general formulation for runoff components estimation and attribution at mean annual time scale

Yufen He, Changming Li, and Hanbo Yang

Abstract. Estimating runoff components, including surface flow, baseflow and total runoff is essential for understanding precipitation partition and runoff generation and facilitating water resource management. However, a general framework to quantify and attribute runoff components is still lacking. Here, we propose a general formulation through observational data analysis and theoretical derivation based on the two-stage Ponce-Shetty model (named as the MPS model). The MPS model characterizes mean annual runoff components as a function of available water with one parameter. The model is applied over 662 catchments across China and the contiguous United States. Results demonstrate that the model well depicts the spatial variability of runoff components with R2 exceeding 0.81, 0.44 and 0.80 for fitting surface flow, baseflow and total runoff, respectively. The model effectively simulates multi-year runoff components with R2 exceeding 0.97, and the proportion of runoff components relative to precipitation with R2 exceeding 0.94. By using this conceptual model, we elucidate the responses of surface flow and baseflow to available water and environmental factors for the first time. The surface flow is jointly controlled by precipitation and environmental factors, while baseflow is mainly influenced by environmental factors in most catchments. The universal and concise MPS model offers a new perspective on the long-term catchment water balance, facilitating broader application in large-sample investigations without complex parameterizations and providing an efficient tool to explore future runoff variations and responses under changing climate.

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Yufen He, Changming Li, and Hanbo Yang

Status: open (until 01 Jan 2025)

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Yufen He, Changming Li, and Hanbo Yang

Data sets

hydro-meteorological data of the catchments across China Yufen He, Changming Li, and Hanbo Yang https://zenodo.org/records/11058118

Yufen He, Changming Li, and Hanbo Yang

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Short summary
Our research presents an improved method to enhance the understanding and prediction of water flows in rivers and streams, focusing on key runoff components: surface flow, baseflow, and total runoff. Using a streamlined model, the MPS model, we analyzed over 600 catchments in China and the U.S., demonstrating its accuracy in capturing the spatial and temporal variability of these components. This model offers a practical tool for water resource management.