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Article

Improvement in Ridge Coefficient Optimization Criterion for Ridge Estimation-Based Dynamic System Response Curve Method in Flood Forecasting

1
Department of Hydrology and Water Resources, University of Hohai, Nanjing 210000, China
2
China Institute of Water Resources and Hydropower Research, Beijing 100038, China
3
Institute of Science and Technology, China Three Gorges Corporation, Beijing 100038, China
*
Author to whom correspondence should be addressed.
Academic Editor: Renato Morbidelli
Water 2021, 13(24), 3483; https://doi.org/10.3390/w13243483
Received: 5 November 2021 / Revised: 29 November 2021 / Accepted: 1 December 2021 / Published: 7 December 2021
The ridge estimation-based dynamic system response curve (DSRC-R) method, which is an improvement of the dynamic system response curve (DSRC) method via the ridge estimation method, has illustrated its good robustness. However, the optimization criterion for the ridge coefficient in the DSRC-R method still needs further study. In view of this, a new optimization criterion called the balance and random degree criterion considering the sum of squares of flow errors (BSR) is proposed in this paper according to the properties of model-simulated residuals. In this criterion, two indexes, namely, the random degree of simulated residuals and the balance degree of simulated residuals, are introduced to describe the independence and the zero mean property of simulated residuals, respectively. Therefore, the BSR criterion is constructed by combining the sum of squares of flow errors with the two indexes. The BSR criterion, L-curve criterion and the minimum sum of squares of flow errors (MSSFE) criterion are tested on both synthetic cases and real-data cases. The results show that the BSR criterion is better than the L-curve criterion in minimizing the sum of squares of flow residuals and increasing the ridge coefficient optimization speed. Moreover, the BSR criterion has an advantage over the MSSFE criterion in making the estimated rainfall error more stable. View Full-Text
Keywords: flood forecasting; error correction; residual property; ridge coefficient criterion flood forecasting; error correction; residual property; ridge coefficient criterion
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MDPI and ACS Style

Liu, K.; Bao, W.; Hu, Y.; Sun, Y.; Li, D.; Li, K.; Liang, L. Improvement in Ridge Coefficient Optimization Criterion for Ridge Estimation-Based Dynamic System Response Curve Method in Flood Forecasting. Water 2021, 13, 3483. https://doi.org/10.3390/w13243483

AMA Style

Liu K, Bao W, Hu Y, Sun Y, Li D, Li K, Liang L. Improvement in Ridge Coefficient Optimization Criterion for Ridge Estimation-Based Dynamic System Response Curve Method in Flood Forecasting. Water. 2021; 13(24):3483. https://doi.org/10.3390/w13243483

Chicago/Turabian Style

Liu, Kexin, Weimin Bao, Yufeng Hu, Yiqun Sun, Dongjing Li, Kuang Li, and Lili Liang. 2021. "Improvement in Ridge Coefficient Optimization Criterion for Ridge Estimation-Based Dynamic System Response Curve Method in Flood Forecasting" Water 13, no. 24: 3483. https://doi.org/10.3390/w13243483

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