Urbanization typically leads to erosion and instability in rivers, and many management and restoration strategies have been developed to dampen the worst impacts. Stream power, defined as the rate of energy expenditure in a river, is a promising metric for analyzing cumulative effects. In this paper we describe a spatial decision support system called the Stream Power Index for Networks (SPIN) toolbox that can be used to assess urban river stability at a watershed scale. The objectives of the paper are to: a) describe the toolbox algorithms and procedures and b) demonstrate the utility of the approach. SPIN is written in Python and packaged as an ArcGIS toolbox. The toolbox combines existing landscape analysis algorithms with new algorithms to model river confluences, channel sinuosity, and threshold sediment particle sizes. Data can also be ingested from a standard hydraulic model. Two case studies demonstrate use of the toolbox to: i) anticipate current morphology; ii) predict urban morphologic change; and iii) analyze the benefits for stormwater management and channel restoration scenarios on channel stability.

城市化通常会导致河流侵蚀和不稳定，并且已经制定了许多管理和恢复策略来抑制最严重的影响。河流功率，定义为河流中的能量消耗率，是分析累积效应的一个很有前途的指标。在本文中，我们描述了一个称为网络河流功率指数 (SPIN) 工具箱的空间决策支持系统，该系统可用于评估流域尺度的城市河流稳定性。本文的目标是：a) 描述工具箱算法和程序，以及 b) 演示该方法的实用性。SPIN 用 Python 编写并打包为 ArcGIS 工具箱。该工具箱将现有的景观分析算法与新算法相结合，对河流汇流、河道曲折度和阈值沉积物粒径进行建模。还可以从标准水力模型中获取数据。两个案例研究展示了该工具箱的用途：i) 预测当前形态；ii) 预测城市形态变化；iii) 分析雨水管理和渠道恢复方案对渠道稳定性的好处。