Evaluation and Improvement of the Method for Selecting the Ridge Parameter in System Differential Response Curves

Author:

Xiao Hao1,Qu Simin1ORCID,Zhang Xumin2,Shi Peng1ORCID,You Yang3,Li Fugang4,Yang Xiaoqiang5,Chen Qihui1

Affiliation:

1. College of Hydrology and Water Resources, Hohai University, Nanjing 210024, China

2. Research Institute of Disaster Prevention and Reduction, Beijing Water Science & Technology Institute, Beijing 100000, China

3. Department of Water Resources of Jiangsu Province, Nanjing 210024, China

4. Xin’anjiang Power Plant in Jiande, Hangzhou 311699, China

5. Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210024, China

Abstract

The selection of an appropriate ridge parameter plays a crucial role in ridge estimation. A smaller ridge parameter leads to larger residuals, while a larger ridge parameter reduces the unbiasedness of the estimation. This paper proposes a constrained L-curve method to accurately select the optimal ridge parameter. Additionally, the constrained L-curve method, traditional L-curve method, and ridge trace method are individually coupled with the system differential response curve to update the streamflow in the Jianyang Basin using the SWAT model. Multiple evaluation criteria are employed to analyze the efficacy of the three methods for correction. The results demonstrate that the constrained L-curve method accurately identifies the optimal ridge parameter in the actual model. Furthermore, the coupling of the constrained L-curve method with the system differential response curve exhibits markedly superior accuracy of simulated streamflow compared to the traditional L-curve and ridge trace methods, with the mean Nash–Sutcliffe efficiency (NSE) improving from 0.71 to 0.88 after correction. The constrained L-curve method, which incorporates the physical interpretation of the estimated parameters, effectively identifies the optimal ridge parameter in practical scenarios. As a result, it demonstrates superior usability and applicability when compared to the traditional L-curve method.

Funder

THE NATIONAL NATURAL SCIENCE FOUNDATION OF CHINA

Publisher

MDPI AG

Subject

Water Science and Technology,Aquatic Science,Geography, Planning and Development,Biochemistry

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