Non-perennial stream networks as directed acyclic graphs: The R-package streamDAG
Non-perennial stream networks as directed acyclic graphs: The R-package streamDAG
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DOI：
10.1016/j.envsoft.2023.105775
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发表时间：
2023-09
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通讯作者：
Ken Aho;C. Kriloff;S. Godsey;Rob Ramos;Chris Wheeler;Y. You;S. Warix;D. Derryberry;S. Zipper;R. Hale;Charles T. Bond;K. Kuehn
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作者：
Ken Aho;C. Kriloff;S. Godsey;Rob Ramos;Chris Wheeler;Y. You;S. Warix;D. Derryberry;S. Zipper;R. Hale;Charles T. Bond;K. Kuehn
许多传统的河流网络指标不太适合非常年河流，这些河流在空间和时间上可能有很大的变化。为了解决这个问题，我们将非常年河流网络视为有向无环图(DAG)。DAG指标允许：1)从本地(单个分段)和全球河流网络的角度总结重要的非常年河流特征(例如，复杂性、连通性和嵌套性)，以及2)随着网络的扩展和收缩跟踪这些特征。我们回顾了大量的图论度量，并介绍了一个新的R包，StreamDAG，它编码了我们认为最有用的方法。ReamDAG包包含处理水存在数据的程序，以及对未加权和加权的河流DAG进行局部和全局分析的功能。我们使用两条北美非常年河流演示了DAG：位于爱达荷州西南部Owyhee山脉的简单排水系统Murphy Creek和位于堪萨斯州中部的相对复杂的网络Konza Prairie。
Many conventional stream network metrics are poorly suited to non-perennial streams, which can vary substantially in space and time. To address this issue, we considered non-perennial stream networks as directed acyclic graphs (DAGs). DAG metrics allow: 1) summarization of important non-perennial stream characteristics (e.g., complexity, connectedness, and nestedness) from both local (individual segment) and global stream network perspectives, and 2) tracking of these features as networks expand and contract. We review a large number of graph theoretic metrics, and introduce a newRpackage,streamDAGthat codifies approaches we feel are most useful. ThestreamDAGpackage contains procedures for handling water presence data, and functions for both local and global analyses of both unweighted and weighted stream DAGs. We demonstratestreamDAGusing two North American non-perennial streams: Murphy Creek, a simple drainage system in the Owyhee Mountains of southwestern Idaho, and Konza Prairie, a relatively complex network in central Kansas.