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Evaluating digital terrain indices for soil wetness mapping – a Swedish case study

机译:评估数字地形指数以绘制土壤湿度图–瑞典案例研究

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Trafficking wet soils within and near stream and lake buffers can cause soil disturbances, i.e. rutting and compaction. This – in turn – can lead to increased surface flow, thereby facilitating the leaking of unwanted substances into downstream environments. Wet soils in mires, near streams and lakes have particularly low bearing capacity and are therefore more susceptible to rutting. It is therefore important to model and map the extent of these areas and associated wetness variations. This can now be done with adequate reliability using a high-resolution digital elevation model (DEM). In this article, we report on several digital terrain indices to predict soil wetness by wet-area locations. We varied the resolution of these indices to test what scale produces the best possible wet-areas mapping conformance. We found that topographic wetness index (iT/isubWI/sub) and the newly developed cartographic depth-to-water index (iD/isubTW/sub) were the best soil wetness predictors. While the iT/isubWI/sub derivations were sensitive to scale, the iD/isubTW/sub derivations were not and were therefore numerically robust. Since the iD/isubTW/sub derivations vary by the area threshold for setting stream flow initiation, we found that the optimal threshold values for permanently wet areas varied by landform within the Krycklan watershed, e.g. 1–2 ha for till-derived landforms versus 8–16 ha for a coarse-textured alluvial floodplain.
机译:在溪流和湖泊缓冲区内和附近贩运湿土会引起土壤干扰,即车辙和压实。反过来,这会导致表面流量增加,从而促进有害物质向下游环境的泄漏。泥潭,溪流和湖泊附近的潮湿土壤的承载力特别低,因此更容易发情。因此,重要的是对这些区域的范围和相关的湿度变化进行建模和绘图。现在,可以使用高分辨率数字高程模型(DEM)以足够的可靠性完成此操作。在本文中,我们报告了几种数字地形指数,以通过湿区位置预测土壤湿度。我们更改了这些指标的分辨率,以测试哪种比例尺可以产生最佳的湿区贴图一致性。我们发现地形湿度指数( T WI )和新开发的制图深度水指数( D TW WI 派生对规模敏感,但 D TW 派生则不敏感,因此在数值上很稳健。由于 D TW 的推导因设置流开始流动的面积阈值而异,因此我们发现永久湿润区域的最佳阈值随Krycklan流域内的地貌而变化。耕作地貌为1–2公顷,而粗糙结构的冲积平原为8–16公顷。

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