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The application of grey Markov model for forecasting annual peak water level

机译：灰色马尔可夫模型在预测年峰水水平预测中的应用

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Flood is caused by heavy rainfall from the upper reach or storm surge from the sea. Serious hazards occur in coastal cities in China, especially during the typhoon season. One of the primary public concerns is whether the flood peak will be able to pass through flood-prevention structures. In flood mitigation and control works the flood stage forecast is especially important to minimize the loss of industrial and agricultural production as well as to ensure the safety of life and property. The earlier the people obtain flood warnings through forecasting system, the much more damage can be reduced. Compared with traditional real-time forecasting, this paper proposes a Gray Markov Model (GMM) to forecast the flood peak water levels. GMM combines the Grey System and the Markov theory into a higher precision model. The historical water level records at Yuqiao Hydrologic Station in Tianjin area are utilized to calibrate and verify the proposed model. Simulated results show the reasonable agreement between the predicted values and the measured data.
机译：洪水是由大海从大海或风暴浪涌的大雨造成的。在中国沿海城市发生严重危险，特别是在台风赛季。其中一个主要的公众关注是洪峰是否能够通过防洪结构。在洪水缓解和控制作品中，洪水阶段预测尤为重要，可以尽量减少工业和农业生产的损失，确保生命和财产的安全性。人们早些时候通过预测系统获得洪水警告，可以减少更多的伤害。与传统的实时预测相比，本文提出了一款灰色马尔可夫模型（GMM），预测洪水峰水水平。 GMM将灰色系统和马尔可夫理论结合在更高的精度模型中。天津地区玉桥水文站的历史水位记录用于校准并验证所提出的模型。模拟结果显示了预测值与测量数据之间的合理协议。

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