High-resolution global topographic index values for use in large-scale hydrological modelling
High-resolution global topographic index values for use in large-scale hydrological modelling
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DOI：
10.5194/hess-19-91-2015
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发表时间：
2015-01-01
影响因子：
6.3
通讯作者：
Gedney, N.
中科院分区：
文献类型：
--
作者：
Marthews, T. R.;Dadson, S. J.;Gedney, N.
模拟地表水流对于模拟地表通量、预测地表径流和地下水位动态以及地表模式的许多其他应用至关重要。许多方法都是基于流行的水文模型TOPMODEL (TOPography-based hydrological model)，该模型最重要的参数是众所周知的地形指数。本文提出了利用GA2算法（GRIDATB 2）从水文条件下的水系（基于多比例尺穿梭高程导数的水文数据和地图）数据计算出的所有无冰土地像元的地形指数的新的高分辨率参数图。在15弧秒的分辨率下，这些层的分辨率是之前可用的最佳地形指数层（HYDRO1k的复合地形指数层，CTI）的4倍。对于各大洲最大的河流集水区，我们发现，与CTI相比，我们的修正值在亚马逊等地区低了20%。我们发现墨累-达令河和尼尔森-萨斯喀彻温河的集水区均值最高，而不是CTI发现的亚马逊河和圣劳伦斯河。然而，对于大多数大流域，我们的新GA2指数值的分布与CTI的分布非常相似，但在细尺度上具有更明显的空间变异性。我们相信这些新的指数层代表了大大改进的全球尺度地形指数值，并希望它们在未来的陆地表面模拟应用中得到广泛应用。
Modelling land surface water flow is of critical importance for simulating land surface fluxes, predicting runoff and water table dynamics and for many other applications of Land Surface Models. Many approaches are based on the popular hydrology model TOPMODEL (TOPography-based hydrological MODEL), and the most important parameter of this model is the well-known topographic index. Here we present new, high-resolution parameter maps of the topographic index for all ice-free land pixels calculated from hydrologically conditioned HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales) data using the GA2 algorithm (GRIDATB 2). At 15 arcsec resolution, these layers are 4 times finer than the resolution of the previously best-available topographic index layers, the compound topographic index of HYDRO1k (CTI). For the largest river catchments occurring on each continent we found that, in comparison with CTI our revised values were up to 20% lower in, e.g. the Amazon. We found the highest catchment means were for the Murray-Darling and Nelson-Saskatchewan rather than for the Amazon and St. Lawrence as found from the CTI. For the majority of large catchments, however, the spread of our new GA2 index values is very similar to those of CTI, yet with more spatial variability apparent at fine scale. We believe these new index layers represent greatly improved global-scale topographic index values and hope that they will be widely used in land surface modelling applications in the future.