...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Earth Surface Processes and Landforms: The journal of the British Geomorphological Research Group >Modeling wet headwater stream networks across multiple flow conditions in the Appalachian Highlands
【24h】

Modeling wet headwater stream networks across multiple flow conditions in the Appalachian Highlands

机译：在阿巴拉契亚高地的多个流动条件下建模湿散水流网络

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Despite the advancement of remote sensing and geospatial technology in recent decades, maps of headwater streams continue to have high uncertainty and fail to adequately characterize temporary streams that expand and contract in the wet length. However, watershed management and policy increasingly require information regarding the spatial and temporal variability of flow along streams. We used extensive field data on wet stream length at different flows to create logistic regression models of stream network dynamics for four physiographic provinces of the Appalachian Highlands: New England, Appalachian Plateau, Valley and Ridge, and Blue Ridge. The topographic wetness index (TWI) was the most important parameter in all four models, and the topographic position index (TPI) further improved model performance in the Appalachian Plateau, Valley and Ridge, and Blue Ridge. We included stream runoff at the catchment outlet as a model predictor to represent the wetness state of the catchment, but adjustment of the probability threshold defining wet stream presence/absence to high values for low flows was the primary mechanism for approximating network extent at multiple flow conditions. Classification accuracy was high overall ( 0.90), and McFadden's pseudo R-2 values ranged from 0.69 for the New England model to 0.79 in the Appalachian Plateau. More notable errors included an overestimation of wet stream length in wide valleys and inaccurate reach locations amid boulder deposits and along headwardly eroding tributaries. Logistic regression was generally successful for modeling headwater streams at high and low flows with only a few simple terrain metrics. Modification and application of this modeling approach to other regions or larger areas would be relatively easy and provide a more accurate portrayal of temporary headwaters than existing datasets. (c) 2018 John Wiley & Sons, Ltd.
机译：尽管近几十年来，尽管遥感和地理空间技术的进步，但是沿着沿着湿度扩展和收缩的临时流，尽管遥感和地理空间技术的进展。然而，流域管理和政策越来越需要有关沿着溪流的流动空间和时间变异性的信息。我们在不同流动的湿流长度上使用了广泛的现场数据，以创建Appalachian高地的四个地理省份流网络动态的逻辑回归模型：新英格兰，阿巴拉契亚高原，山谷和山脊和蓝岭。地形湿度指数（TWI）是所有四种模型中最重要的参数，以及地形位置指数（TPI）进一步提高了Appalachian高原，山谷和山脊和蓝岭的模型性能。我们包括在集水器插座处的流径向作为模型预测器来表示集水器的润湿状态，但是将定义湿流的概率阈值的调整限定为低流量的高值是用于近似网络范围的主要机制状况。分类精度总体上很高（＆ 0.90），McFadden的伪R-2值在阿巴拉契亚高原的新英格兰模型中为0.69。更值得注意的错误包括宽阔谷的湿流长度高估，并且在巨石沉积物中和沿着前向侵蚀支流中不准确到达位置。 Logistic回归通常是成功的，用于在高和低流量下建模下线和低流量，只有几个简单的地形指标。对其他地区或更大区域的这种建模方法的修改和应用将相对容易，并且提供比现有数据集更准确地写临时返波。 （c）2018 John Wiley＆Sons，Ltd。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号