Urban stream syndrome: Quantifying topographic variation along an urban-rural gradient

Topographic variation within fluvial systems is essential for providing a mosaic of physical habitats and supporting the dynamic hydraulic, geochemical, and biological processes that determine both aquatic and riparian ecosystem function. In highly-modified rivers through both urban and rural settings, the physical heterogeneity of alluvial channels has been diminished by anthropogenic activities. As riparian areas are increasingly under pressure from agricultural and urban development, identifying the geomorphic controls on physical heterogeneity through these environments is critical. In this study, we use the bed coefficient of variation (CV) extracted from a high-resolution bathymetric LiDAR survey as a dimensionless metric for topographic variation and physical heterogeneity over 100 km of the Boise River corridor that spans an urban-rural gradient. Our CV results for both the streambed and channel demonstrate that the average topographic variation of reaches in urban areas is 22-25% lower than reaches located in rural areas along the same river. While these results initially support the application of the urban stream syndrome hypothesis, CV values had similar magnitudes in both urban and rural reaches suggesting there is a dominant control on topographic variation that was not directly related to urban land use. Analysis of CV values relative to normalized levee width indicates that the causative driver of morphologic simplification in the channel was lateral constraints from levees. In the Boise River, topographic variation increased linearly with normalized levee widths that ranged between 50% and >300% of the average channel width. Further, topographic variation was maximized in reaches where flow expansion during high discharge inundated between 1 and 2 times the average channel width (approximately 65-70% of the available floodplain). Our simple and objective watershed-scale approach leverages high-resolution topography data to identify reaches of high physical heterogeneity for river conservation, as well as help guide environmental flow releases in managed rivers.