| 引用本文: | 张 钦,刘赛艳,解阳阳,等.基于交叉验证法与马尔科夫链的年径流丰枯分类可靠性研究[J].灌溉排水学报,2023,42(5):90-99. |
| ZHANG Qin,LIU Saiyan,XIE Yangyang,et al.基于交叉验证法与马尔科夫链的年径流丰枯分类可靠性研究[J].灌溉排水学报,2023,42(5):90-99. |
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| 摘要: |
| 【目的】提出一种用于检验年径流丰枯分类可靠性的方法，为划分流域年径流丰枯类别提供科学依据。【方法】从稳定性和可预测性2个方面分析年径流丰枯分类的可靠性，提出基于交叉验证法和马尔科夫链的检验方法；以常用的均值标准差法、灰色关联分析法和集对分析法为代表，采用交叉验证法和马尔科夫链分别研究各方法所得分类结果的稳定性和可预测性；建立分类差异指数和转移概率差值，用于评价不同分类方法划分年径流丰枯类别的稳定性和可预测性；最后以黄河上游唐乃亥站1956—2021年的年径流序列为例进行验证。【结果】①基于交叉验证法和马尔科夫链，不同分类方法得到的年径流丰枯状态均存在差异，表明不同分类方法划分和预测年径流丰枯状态的稳定性和可预测性不同。②对唐乃亥站而言，分类差异指数表明GRA法的稳定性最好，SPA法其次，MSD法最差；转移概率差值表明GRA法的可预测性最好，SPA法其次，MSD法最差。③综合考虑各分类方法的稳定性和可预测性，对唐乃亥站而言，GRA法划分年径流丰枯状态最为可靠，SPA法其次，MSD法最差。【结论】不同年径流丰枯分类方法在同一流域存在可靠性差异，基于交叉验证法和马尔科夫链的方法能够有效检验各分类方法所得结果的可靠性。 |
| 关键词: 丰枯分类可靠性；交叉验证；马尔科夫链；灰色关联分析；集对分析 |
| DOI：10.13522/j.cnki.ggps.2022364 |
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| Use Cross-validation and Markov Chain to Assess the Reliability of Annual Runoff Classification for Wet and Dry Years Calculated by Different Methods |
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ZHANG Qin, LIU Saiyan, XIE Yangyang, XI Haichao
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1. College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225009, China;
2. Modern Rural Water Conservancy Research Institute, Yangzhou University, Yangzhou 225009, China
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| Abstract: |
| 【Objective】Various methods have been proposed to classify changes in runoff in catchments, but how to assess their reliability remains a challenge. In this paper, we present a method to assess the reliability of the annual runoff classification for wet and dry years calculated by different methods. Its effectiveness was tested against data measured from a watershed.【Method】The reliability of the methods for classifying annual runoff for wet and dry years is analyzed based on their stability and predictability. The assessment is based on the cross-validation method and Markov chain method. We evaluate the stability and predictability of the classified results obtained by the mean-standard deviation method (MSD), gray relational analysis (GRA), and set-pair analysis (SPA). The difference in the classification and the transfer probability of the indices is established to evaluate the stability and predictability of the classified results. The proposed model is tested against annual runoff measured from 1956—2021 at the Tangnaihai Hydrological Station in the upper reaches of the Yellow River basin.【Result】①Analysis using the cross-validation method and Markov chain showed that the results calculated by different classification methods vary, indicating that the stability and predictability of different methods are different. ②The classification difference index indicates that the GRA method is most stable and the MSD method is least stable. The transfer probability differences indicates that the GRA method has the best predictability and the MSD has the worst. ③Considering stability and predictability, the GRA method is most reliable for classifying annual runoff abundance and depletion, and the MSD method is the least.【Conclusion】The reliability of different methods for classifying annual runoff for wet and dry years varies for the same watershed. The method we developed from the cross-validation method and Markov chain can effectively assess the reliability of the results calculated by different classification methods. |
| Key words: reliability of wet-dry classification; cross validation; Markov chain; gray relational analysis; set pair analysis |
