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EVALUATION OF GRID-BASED DISTRIBUTED SEDIMENT DELIVERY RATIO MODELS

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  Pp. 428-433 in Total Maximum Daily Load (TMDL) Environmental Regulations–II Proceedings of the 8-12 November 2003 Conference (Albuquerque, New Mexico USA), Publication Date 8 November 2003.  .(doi:10.13031/2013.15592)
Authors:   M. A. Al-Smadi1 and C. D. Heatwole
Keywords:   Spatial distribution, SDR, GIS, sediment yield

The emphasis on a watershed-scale approach to management of water quantity and quality has renewed the focus on hydrologic/water quality modeling at that scale. While the most widely used modeling approach to TMDLs continue to be a lumped approach using HSPF, there is also ongoing development of models that use a distributed parameter approach. In addition to the more traditional language-based simulation models, we are also seeing the development of some new modeling approaches that provide a spatially dynamic model built within a geographic information system (GIS) using the native GIS functions. The emphasis to date has been on predicting hydrologic responses, but approaches for modeling water quality constituents have also been developed.

In this preliminary study, three spatially distributed sediment delivery ratio methods (SDR) were evaluated in terms of spatial distribution of the delivery ratio. The three methods use 30m DEM as the base data set and provide a SDR value for each cell in the watershed. Two methods are based on flow velocity as a key model component, and third method is based on a weighted index of key factors. Results from two methods show a higher sensitivity to the flow network (upslope area) and the third method is more sensitive to land use patterns. In future work, those three methods as well as other spatially distributed method of estimating sediment yield with be compared with observed sediment yield data as well as with predictions of spatially distributed, widely used nonpoint source pollution (NPS) models.

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