Relating Riparian Vegetation to Present and Future Streamflows

Abstract

The intense demand for river water in arid regions is resulting in widespread changes in riparian vegetation. We present a direct gradient method to predict the vegetation change resulting from a proposed upstream dam or diversion. Our method begins with the definition of vegetative cover types, based on a census of the existing vegetation in a set of 1 ° 2 m plots. A hydraulic model determines the discharge necessary to inundate each plot. We use the hydrologic record, as defined by a flow duration curve, to determine the inundation duration for each plot. This allows us to position cover types along a gradient of inundation duration. A change in river management results in a new flow duration curve, which is used to redistribute the cover types among the plots. Changes in vegetation are expressed in terms of the area occupied by each cover type. We applied this approach to riparian vegetation of the Black Canyon of the Gunnison National Monument along the Gunnison River in Colorado. We used TWINSPAN to cluster plots according to species occurrence. This analysis defined three vegetative cover types that were distinct in terms of inundation duration. Quantitative changes in the extent of cover types were estimated for three hypothetical flow regimes: two diversion alternatives with different minimum flows and a moving average modification of historical flows. Our results suggest that (1) it is possible to cause substantial changes in riparian vegetation without changing mean annual flow, and (2) riparian vegetation is especially sensitive to changes in minimum and maximum flows. Principal advantages of this method are simplicity and reliance on relatively standard elements of plant community ecology and hydrologic engineering. Limitations include use of a single environmental gradient, restrictive assumptions about changes in channel geometry, representation of vegetation as quasi—equilibrium cover types, and the need for model validation.

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