| 山区县域尺度降水量空间插值方法比较 |
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| 引用本文： | 朱蕾,黄敬峰.山区县域尺度降水量空间插值方法比较[J].农业工程学报,2007,23(7):80-85. |
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| 作者姓名： | 朱蕾 黄敬峰 |
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| 作者单位： | 1. 浙江大学环境与资源学院,杭州,310029;山东省农业管理干部学院土地与房地产管理系,济南,250100
2. 浙江大学环境与资源学院,杭州,310029 |
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| 摘 要： | 随着空间降水信息需求的日益增加，降水的空间插值已被广泛应用，而不同的插值方法因不同的地区和研究目的产生不同的效果。该文以浙江省淳安县为例，选取17个站点1959～2000年多年平均和月均降水资料，在地统计学和地理信息系统(GIS)支持下，结合一些地形地理因子，采用多种插值方法对研究区降水量进行了空间插值研究，分析不同插值方法对研究区的适用性和精度，并对模拟的空间降水量图像进行了比较。通过3个检验站点的插值误差的比较，混合插值法，即回归克里金插值法误差最小，效果最好。
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| 关 键 词： | 降水量 克里金插值 混合插值 逆距离加权法 样条法 |
| 文章编号： | 1002-6819（2007）7-0080-06 |
| 收稿时间： | 2006/7/14 0:00:00 |
| 修稿时间： | 2006-07-142007-02-26 |
Comparison of spatial interpolation method for precipitation of mountain areas in county scale |
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| Zhu Lei and Huang Jingfeng.Comparison of spatial interpolation method for precipitation of mountain areas in county scale[J].Transactions of the Chinese Society of Agricultural Engineering,2007,23(7):80-85. |
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| Authors: | Zhu Lei and Huang Jingfeng |
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| Institution: | Resource and Environment College, Zhejiang University, Hangzhou 310029, China;Department of Land and Real Estate Management, Shandong Agriculture Administrators College, Jinan 250100, China;Resource and Environment College, Zhejiang University, Hangzhou 310029, China |
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| Abstract: | With the increasing needs for spatial precipitation information, spatial interpolation method of precipitation is widely used. Different precipitation interpolation methods for different study areas and study aims will have different results. Taking Chun'an county in Zhejiang Province for example, using mean yearly and monthly precipitation of seventeen stations from 1959 to 2000 and some topography and geographical factors to carry on an investigation into spatial interpolation method of precipitation. Different interpolation methods were used to simulate precipitation spatial distribution based on geography information system(GIS) and geostatistics technology. The precisions and model maps of different interpolation methods were compared. Results show that mixed method, namely the combination of multiple regression and kriging interpolation method, is the best one for its high prediction accuracy verified by three validated stations. |
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| Keywords: | precipitation kriging interpolation method mixed method Inverse Distance Weighting(IDW) Spline |
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