| 基于CAR-SVM模型的季节性冻融区地下水埋深预测 |
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| 引用本文： | 赵天兴,朱焱,杨金忠,毛威.基于CAR-SVM模型的季节性冻融区地下水埋深预测[J].排灌机械工程学报,2018,36(11):1180-1186. |
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| 作者姓名： | 赵天兴 朱焱 杨金忠 毛威 |
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| 作者单位： | 武汉大学水资源与水电工程科学国家重点实验室, 湖北 武汉 430072 |
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| 摘 要： | 准确预测地下水埋深是灌区水资源管理的重要依据.考虑到地下水埋深在时间序列上呈现滞后性和非线性,耦合了多变量时间序列CAR与支持向量机SVM,构建了CAR-SVM地下水埋深预测模型.为了提高模型在冻融期的模拟效果,构建了季节性冻融灌区地下水埋深拟合模型--CAR-SVM(T-TF)模型.模拟结果显示,只考虑冻融期气温的CAR-SVM(T-TF)模型优于考虑全年气温的CAR-SVM(T)模型及不考虑气温的CAR-SVM模型.CAR-SVM(T-TF)模型在全灌区地下水埋深的模拟结果:在验证期模型决定系数R2为0.954,冻融期R2为0.973;RMSE均小于0.090 m,模型精度较高.将全灌区得到的3阶CAR-SVM(T-TF)模型结构用于灌区内5个灌域地下水埋深模拟,模型在各灌域均有较好的适用性.
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| 关 键 词： | 河套灌区 CAR-SVM 地下水埋深 冻融期 气温 |
| 收稿时间： | 2018-04-12 |
CAR-SVM model based water table depth prediction in seasonal freezing-thawing areas |
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| ZHAO Tianxing,ZHU Yan,YANG Jinzhong,MAO Wei.CAR-SVM model based water table depth prediction in seasonal freezing-thawing areas[J].Journal of Drainage and Irrigation Machinery Engineering,2018,36(11):1180-1186. |
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| Authors: | ZHAO Tianxing ZHU Yan YANG Jinzhong MAO Wei |
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| Institution: | State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, Hubei 430072, China |
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| Abstract: | Accurately predicting water table depth is an important basis for water resources management in irrigation areas. Based on hysteresis and nonlinearity of groundwater in time series, a CAR-SVM water table depth prediction model was developed by integrating multivariate time series controlled auto-regressive(CAR)and support vector machine(SVM). To improve the performance of the model in freezing-thawing period, a water table depth fitting model, i.e. CAR-SVM(T-TF)model, was established for seasonal freezing-thawing irrigation district. Simulation results indicate that the performance of the CAR-SVM(T-TF)model with ambient temperature effect in the freezing-thawing period is better than either the CAR-SVM(T)model with ambient temperature effect of the whole year or the CAR-SVM without any ambient temperature effect. The CAR-SVM(T-TF)model was applied to predict the water table depth in Hetao Irrigation District. The results demonstrate that the coefficient of multiple determination, R2, is 0.954 and 0.973 in validation period and freezing-thawing period, respectively, and all the RMSE in different periods are less than 0.09 m. suggesting a relatively high accuracy. The 3-order CAR-SVM(T-TF)model structure obtained from Hetao Irrigation District as a whole was used to simulate the water table depths in five irrigation areas in the district. The model has a good applicability in each area, and the predicted water table depths are closed to the measurements. Specially, R2 is more than 0.90, RMSE is less than 0.10 m, and BIAS is less than 0.04 in the freezing-thawing period in each area. |
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| Keywords: | Hetao Irrigation District CAR-SVM water table depth freezing-thawing period temperature |
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