适用于大尺度水文气候模式的DEM洼地填充和平坦区处理的新方法

A new method for treating the depressions and flat areas in DEM for large-scale hydrology and climate models

针对传统的DEM(Digital Elevation Model)洼地和平坦区处理方法存在的速度慢等问题,提出了新的DEM处理方法。新方法由两个新算法组成:其一为DEM快速分位数分类算法,此算法先利用DEM的统计特征计算出分位数,然后分类,其时间复杂度仅为O(N),速度远大于传统分类方法的O(NlogN);其二为对分类后洼地和平坦区处理的新算法,此算法从高程最小的一类开始逐类处理,直到处理结束。用90m DEM对不同方法进行评价的结果表明:新方法在保证结果准确性前提下显著提高了DEM洼地和平坦区的处理效率。而且,新方法除了可将洼地填平之外,还可对洼地增加微小高程,生成无平坦区的DEM。新方法已成功地应用到地形指数的计算及TOPMODEL水文模拟,还适用于基于DEM的大尺度水文气候模拟与分析。

The new method is composed of two algorithms for processing the depressions and plain areas in DEM. The first one is quantile classification algorithm which utilizes the statistics characteristics to compute the quantile and carries out the classification. Since its time complexity is O（N）, the working speed is much faster than the traditional method. The other algorithm further processes the quantilized depressions and fiat areas initiated from the lowest elevation until the end. The assessments by using various method based on DEM with 90 ×90 grids show that the new method has very high processing speed. In average, this method is faster than the Jenson ＆ Domingue method by thousands times .