An adaptive approach to selecting a flow‐partition exponent for a multiple‐flow‐direction algorithm
An adaptive approach to selecting a flow‐partition exponent for a multiple‐flow‐direction algorithm
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DOI：
10.1080/13658810601073240
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发表时间：
2007-01
影响因子：
5.7
通讯作者：
Chengzhi Qin;A-Xing Zhu;Tao Pei;Baoluo Li;Chenghu Zhou;Lin Yang
中科院分区：
文献类型：
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作者：
Chengzhi Qin;A-Xing Zhu;Tao Pei;Baoluo Li;Chenghu Zhou;Lin Yang
大多数多流向算法（MFD）使用流量分配系数（指数）来确定流向所有下坡邻居的部分。常用的MFD通常在整个流域上采用固定的指数。固定系数策略不能有效地模拟局部地形条件对局部流扩散的影响。本文解决了这个问题的基础上的想法，分散的当地流量在空间上变化，由于当地地形条件的空间变化。因此，MFD的流分配指数也应该随空间而变化。我们提出了一种自适应的方法来确定流分区指数的基础上控制局部流分区的局部地形属性。在我们的方法中，局部地形对流量分配的影响通过基于局部最大下坡坡度的流量分配函数来模拟（我们将这种方法称为基于最大下坡坡度的MFD，简称MFD-md）。通过这种新方法，可以使用较大的流动分区指数值来模拟诱导收敛流动条件的陡峭地形。类似地，可以使用较小的流分区指数值对平缓地形进行建模。MFD‐md使用四种类型的数学曲面及其比集水面积（SCA）的理论“真实”值进行定量评估。均方根误差（RMSE）表明，MFD-md计算的SCA的误差低于广泛使用的SFD和MFD算法计算的SCA的误差。应用东北某流域的真实的DEM数据进行了计算，结果表明，基于视觉判断的MFD‐md方法计算的径流累积量更适合地形条件。
Most multiple‐flow‐direction algorithms (MFDs) use a flow‐partition coefficient (exponent) to determine the fractions draining to all downslope neighbours. The commonly used MFD often employs a fixed exponent over an entire watershed. The fixed coefficient strategy cannot effectively model the impact of local terrain conditions on the dispersion of local flow. This paper addresses this problem based on the idea that dispersion of local flow varies over space due to the spatial variation of local terrain conditions. Thus, the flow‐partition exponent of an MFD should also vary over space. We present an adaptive approach for determining the flow‐partition exponent based on local topographic attribute which controls local flow partitioning. In our approach, the influence of local terrain on flow partition is modelled by a flow‐partition function which is based on local maximum downslope gradient (we refer to this approach as MFD based on maximum downslope gradient, MFD‐md for short). With this new approach, a steep terrain which induces a convergent flow condition can be modelled using a large value for the flow‐partition exponent. Similarly, a gentle terrain can be modelled using a small value for the flow‐partition exponent. MFD‐md is quantitatively evaluated using four types of mathematical surfaces and their theoretical ‘true’ value of Specific Catchment Area (SCA). The Root Mean Square Error (RMSE) shows that the error of SCA computed by MFD‐md is lower than that of SCA computed by the widely used SFD and MFD algorithms. Application of the new approach using a real DEM of a watershed in Northeast China shows that the flow accumulation computed by MFD‐md is better adapted to terrain conditions based on visual judgement.