PREDICTING THE EFFECTS OF FLOODPLAIN VEGETATION ON PATTERNS OF SEDIMENT DEPOSITION USING A MORPHODYNAMIC LANDSCAPE EVOLUTION MODEL

The presence of plants along a river can drastically change the dynamics of sediment transport and the patterns of erosion and deposition created by large floods by steering and slowing the flow as well as increasing the effective cohesiveness of surface material. A fundamental goal of fluvial geomorphology is to develop predictive models of landscape evolution that can reproduce the effects that a given event will have on a known landscape. Our research explores the interactions between vegetation and complex topography during a large flood, and to understand the dynamics involved, we have developed a vegetation module for a predictive morphodynamic model and tested the results against a well-constrained case study.

The vegetation component of a landscape evolution model is, by necessity, a drastic simplification of the behavior of plants in the real world. Our goal is to determine the minimum level of complexity that such a component must have to accurately predict the effects of vegetation on sediment transport. For this purpose, we developed a landscape evolution model that can simulate the movement of water and sediment through the channel and floodplain of a dryland river during a large flood, and combined it with a series of vegetation modules of increasing complexity to obtain maps of topographic change. Initial model results suggest that simulations in which the vegetation and channel are uniformly covered by vegetation see greater aggradation than those free of vegetation, and that this effect is greater for more densely packed stems.

The lower Rio Puerco, NM, serves as an ideal natural experiment for the study of large floods. In 2003, herbicides were sprayed on a section of the river to remove saltcedar, an invasive species. In 2006, severe floods caused extreme erosion on the de-vegetated sections of Rio Puerco, while widespread sedimentation took place downstream, where vegetation was present. Repeat LiDAR surveys of this downstream reach reflect the patterns and magnitudes of erosion and deposition that resulted from the 2006 event. We will compare the outputs of our model against the results from the LiDAR differencing to establish the accuracy of the models, and select the least complex vegetation component necessary for a predictive landscape evolution model.