虚拟站点在黑河流域降水模拟中的应用

降水作为气候系统的关键因素,也是影响区域植被生长以及生态变化规律的重要因子。本文针对黑河流域气象站点分布稀疏情况,采用信息熵及半变异函数理论构建该流域虚拟气象站点,并结合部分已有站点对整个流域降水进行插值模拟。信息熵可以计算每个站点降水值所包含的信息,通过联合熵以及条件熵来依次选取所含信息量多的站点,同时结合半变异函数模型来观察各站点之间的空间相关性,以此构建最优站点数据集。利用1991-2003年该流域15个气象台站的年平均降水量作为基础数据,考虑高程、坡度、坡向对降水的影响,对降水进行相关性分析,建立回归方程反演虚拟站点降水值。最后,采用协同克里金（Co-Kriging）与具有漂移的克里金（KED）方法对该流域进行插值,对比插值精度。结果表明,增加虚拟站点有效提高了降水插值精度,在该情况下使用KED方法插值结果与观测值最接近。

Application of Virtual Sites to Simulate Precipitation Across Heihe River Basin

As a key factor in the climate system, precipitation plays an important role in the survival and development of human beings. Accurate precipitation information is essential for climate and environmental research, and the spatial distribution of precipitation data is important for addressing the rational use of water resources. The distribution of national meteorological stations in most areas of China is relatively scattered. In some regions, the terrain is undulating, and the original weather station cannot accurately reflect the actual situation of local precipitation. To accurately reflect the spatial distribution of precipitation in regions of this kind, this paper used the original data of the Heihe river National Meteorological Station, and built virtual sites to establish a precipitation network across the entire basin. The information network entropy and semi-variogram theory were used to optimize the precipitation network, and some existing sites were used to interpolate precipitation across the whole basin. Information entropy can calculate the value of information contained in the precipitation of each station. The larger the amount of information, the larger is the entropy value. To establish an optimal site dataset, we combined the joint entropy and conditional entropy to select sites with a large amount of information, and then combined the nugget value and range of the semi-variogram model to take account of the spatial correlation betweenthese stations. This paper took the annual average precipitation data of 15 national meteorological stations in the Heihe River Basin from 1991 to 2003 as the raw data. According to the characteristics of elevation and vegetation growth, Heihe river is divided into three regions: upstream, midstream, and downstream. The effects of altitude, slope, and aspect on precipitation were considered for each of the three regions, and the relevant factors affecting the precipitation value were determined. We considered multiple factors to establish multiple linear regression equations to invert virtual station precipitation values. Finally, the watershed was interpolated using the drift function KED method and Co-Kriging method to compare the interpolation precision. The results show that the existence of virtual sites has effectively improved the accuracy of precipitation interpolation. Due to the appearance of the drift function, the error between the simulated precipitation value and the observed value in Dingxin, Jinta, and Ma Zongshan is within 5 mm. In this case, the interpolation result using the KED method is closest to the observation value.