Spatial Decision Support System for Urban Streams

Abstract

The change of land use from rural to urban tends to radically alter the implicated streams with many symptoms of the “urban stream syndrome”. The key driver of the syndrome is hydrologic change; the product of increased imperviousness and efficient conveyance and characterized by frequent larger flows, increases in peak flows, and seasonal shifts in flood occurrence. Streams are unable to maintain stability due to an imbalance between sediment transport processes and the flow energy, which leads to morphological alteration, ecological degradation and a reduced capacity to support ecosystem services. Many strategies have been tried to prevent damage in or rehabilitate these urban streams. However, significant uncertainty remains about their outcomes because current practices do not consider the marginal impact of additional land use changes within a watershed or the cumulative impact of urbanization beyond the local scale. The objective of the current paper is to describe a spatial decision support system (SDSS) to predict changes in stream power under different scenarios of land use and cover change at the network scale. Change in stream power is modelled as a predictor of changes in channel stability. The SDSS is written as Python scripts and packaged as an ArcGIS toolbox for ease of use. The current framework integrates empirical relationships between discharge, drainage area and imperviousness to assess pre- and post- development impacts of urbanization along the stream networks. A sediment particle size predictive model is also developed for integration in the SDSS. A case study of an urbanizing watershed is presented to demonstrate the application of the SDSS. Continued development of the tool will allow increased use of field and site -specific model results to refine the accuracy of predictions. Cartographic displays of the spatial and temporal sensitivity of streams to urbanization can assist in decision making processes.