CN05.1气象数据在流域水文模拟中的应用——以新疆开都河流域为例

doi:10.12006/j.issn.1673-1719.2019.178

摘要/Abstract

摘要：

为探讨中国再分析气象数据集CN05.1在流域水文模拟中的适用性潜力,以开都河流域为研究区,分别使用CN05.1数据集和传统气象站数据驱动SWAT水文模型,采用决定系数（R ²)、纳什效率系数（NSE）和相对误差（R_e）等评价指标对二者模拟效果进行对比分析,以确定CN05.1数据的适用性;最后采用两种数据订正方法对CN05.1降水数据进行了订正,并以水文模拟效果进行评价。研究结果表明:(1) CN05.1气象数据在开都河流域的水文气象模拟中具有较强的适用性;(2) 基于SWAT模型的水文模拟显示,CN05.1数据驱动的水文模拟精度高于传统气象站数据,其率定期（1995—2005年）和验证期（2006—2016年）的R ²分别为0.81和0.73,NSE分别为0.81和0.72,R_e分别为-0.97%和0.39%;(3)两种数据订正方法均能较好地再现流域径流变化过程,但基于空间关系订正法的径流模拟效果更好,R ²和NSE均在0.72以上,|R_e|＜1.7%。由此,订正后的CN05.1降水数据一方面弥补了传统气象站数据缺失的问题,另一方面补足了未订正CN05.1降水数据在径流模拟中峰值欠佳的问题。

关键词: CN05.1, SWAT模型, 适用性评价, 降水数据订正, 开都河

Abstract:

In order to explore the applicability potential for China’s reanalyzed meteorological dataset CN05.1 in watershed hydrological modeling, the SWAT hydrological model was driven by CN05.1 dataset and traditional meteorological station data, respectively, by taking the Kaidu River basin the as research area in this paper. The comparison between the two simulation results was carried out by using evaluation factors such as coefficient of determination (R ²), Nash efficiency coefficient (NSE) and relative error (R_e). Finally, two precipitation data correction methods were used to correct the CN05.1 precipitation data and the hydrological simulation results were evaluated. The results are as follows. (1) CN05.1 meteorological data has certain applicability in the hydrometeorological simulation of the Kaidu River basin. (2) Hydrological simulation based on SWAT model shows that CN05.1 data-driven hydrological simulation accuracy is higher than traditional meteorological station data, and the R ² over the period of calibration (1995-2005) and verification period (2006-2016) is 0.81 and 0.73, NSE is 0.81 and 0.72, and R_e is -0.97% and 0.39%, respectively. (3) The two kinds of correction data can both simulate the process of runoff change well, but runoff simulation based on spatial relationship correction method shows better effect, and the R ² and NSE are above 0.72, |R_e| is less than 1.7%. Therefore, the corrected CN05.1 precipitation data can compensate for the lack of data in the traditional meteorological station and the unsatisfactory peak value of the CN05.1 meteorological data in the runoff simulation to a certain extent.

Key words: CN05.1, SWAT model, Applicability evaluation, Precipitation correction method, Kaidu River basin

罗映雪,徐长春,楚智,孙琪,陈丽. CN05.1气象数据在流域水文模拟中的应用——以新疆开都河流域为例[J]. 气候变化研究进展, 2020, 16(3): 287-295.

Ying-Xue LUO,Chang-Chun XU,Zhi CHU,Qi SUN,Li CHEN. Application of CN05.1 meteorological data in watershed hydrological simulation: a case study in the upper reaches of Kaidu River basin[J]. Climate Change Research, 2020, 16(3): 287-295.

图/表 9

图1 研究区示意图

Fig. 1 Sketch map of the study area

图2 用于空间插值的气象站点和验证站点分布图

Fig. 2 Meteorological and verification sites for spatial interpolation

表1 大山口水文站SWAT模型模拟效果评价

Table 1 Evaluation of SWAT model simulation effect

图3 1995—2016年开都河大山口水文站月尺度径流模拟

Fig. 3 Simulation of monthly scale runoff in the Kaidu River basin during 1995-2016

图4 两种气象数据多年平均月降水量对比

Fig. 4 Comparison of the average monthly precipitation of two kinds of meteorological data

表2 CN05.1站点与传统气象站点多年平均月度降水量比值

Table 2 Multi-year average monthly precipitation ratio of CN05.1 grids and traditional meteorological sites

图5 订正数据与各降水数据对比

Fig. 5 Corrected data and each precipitation data comparison

图6 不同订正方法下的CN05.1数据对月尺度径流模拟结果对比

Fig. 6 Comparison of CN05.1 data on monthly scale runoff simulation results under different correction methods

图7 传统气象站与CN05.1各格点的数据相关性

Fig. 7 Correlation coefficient between traditional weather station and CN05.1 station

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