Craig J. Allan
University of North Carolina at Charlotte
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Publication
Featured researches published by Craig J. Allan.
Journal of Environmental Science and Health Part A-toxic\/hazardous Substances & Environmental Engineering | 2005
Jun Han; Jy S. Wu; Craig J. Allan
Structural best management practices (BMPs) are often used to mitigate the impact of storm water runoff on receiving waters. Vegetative filter strips (VFS) are an example of a structural BMP that has been used to treat storm water and highway runoff. Physical factors affecting the performance of VFS include pollutant characteristics, vegetation composition and density, soil properties, and the physical dimensions of the filter strip. In this study, field-suspended sediment data were collected from an experimental VFS treating highway runoff in eastern North Carolina. Field data were used to test the design concepts of the VFS treatment train and to validate a simulation model for evaluating the impact of these physical factors on sediment removal as a function of filter strip length. It was concluded that the experimental filter strip was effective in removing more than 85% of the incoming total suspended sediment (TSS). Simulation results support field observations that a 10-m or longer filter strip can retain most of the medium and large particles (> 8 μ m) transported in runoff. Simulations also indicate infiltration loss is largely responsible for the retention of small-size sediment particles (< 8 μ m). Saturated hydraulic conductivity and initial water contents have little effects on TSS removal. The condition of vegetative coverage, in particular vegetation density, is another factor affecting the performance of filter strip.
Archive | 2018
Minrui Zheng; Wenwu Tang; Yu Lan; Xiang Zhao; Meijuan Jia; Craig J. Allan; Carl C. Trettin
Very high resolution digital elevation models (DEM) provide the opportunity to represent the micro-level detail of topographic surfaces, thus increasing the accuracy of the applications that are depending on the topographic data. The analyses of micro-level topographic surfaces are particularly important for a series of geospatially related engineering applications. However, the generation of very high resolution DEM using, for example, LiDAR data is often extremely computationally demanding because of the large volume of data involved. Thus, we use a high-performance and parallel computing approach to resolve this big data-related computational challenge facing the generation of very high resolution DEMs from LiDAR data. This parallel computing approach allows us to generate a fine-resolution DEM from LiDAR data efficiently. We applied this parallel computing approach to derive the DEM in our study area, a bottomland hardwood wetland located in the USDA Forest Service Santee Experimental Forest. Our study demonstrated the feasibility and acceleration performance of the parallel interpolation approach for tackling the big data challenge associated with the generation of very high resolution DEM.
The Journal of Water Management Modeling | 2013
Zhaochun Meng; Jy S. Wu; Craig J. Allan
State transportation agencies are a potential stakeholder in the total maximum daily load process and, in some cases, NPDES stormwater permits could be issued …
Journal of The American Water Resources Association | 2010
Philippe Vidon; Craig J. Allan; Douglas A. Burns; Tim P. Duval; Noel P. Gurwick; Shreeram Inamdar; Richard Lowrance; Judy Okay; Stephen D. Sebestyen
Journal of Environmental Engineering | 1998
Jy S. Wu; Craig J. Allan; William L. Saunders; Jack B. Evett
Journal of The American Water Resources Association | 2010
Michael G. Dosskey; Philippe Vidon; Noel P. Gurwick; Craig J. Allan; Tim P. Duval; Richard Lowrance
Forest Ecology and Management | 2006
Cherie J. Westbrook; Kevin J. Devito; Craig J. Allan
Hydrological Processes | 2008
Craig J. Allan; P. Vidon; R. Lowrance
Journal of The American Water Resources Association | 2014
Vijaya Gagrani; John A. Diemer; Jarrod J. Karl; Craig J. Allan
Journal of Environmental Management | 2001
W.A. Harman; Craig J. Allan; Randall D. Forsythe