Wei Zhang - Design and risk assessment tool for vegetative treatment areas receiving agricultural wastewater: Preliminary results

Document created by Wei Zhang on Aug 22, 2014
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  Publication Details (including relevant citation   information): Faulkner, Joshua W., Easton, Zachary M.,   Zhang, Wei, Geohring, Larry D., Steenhuis, Tammo S., Journal   of Environmental Management, 2010,   91 (8), pp 1794-1801

  Abstract: Vegetative treatment areas (VTAs) are   commonly being used as an alternative method of agricultural   process wastewater treatment. However, it is also apparent that   to completely prevent discharge of pollutants to the surrounding   environment, settling of particulates and bound constituents from   overland flow through VTAs is not sufficient. For effective   remediation of dissolved agricultural pollutants, VTAs must   infiltrate incoming wastewater. A simple water balance model for   predicting VTA soil saturation and surface discharge in   landscapes characterized by sloping terrain and a shallow   restrictive layer is presented and discussed. The model accounts   for the cumulative effect of successive rainfall events and   wastewater input on soil moisture status and depth to water   table. Nash–Sutcliffe efficiencies ranged from 0.65 to 0.81 for   modeled and observed water table elevations after calibration of   saturated hydraulic conductivity. Precipitation data from   relatively low, average, and high annual rainfall years were used   with soil, site, and contributing area data from an example VTA   for simulations and comparisons. Model sensitivity to VTA width   and contributing area (i.e. barnyard, feedlot, silage bunker,   etc.) curve number was also investigated. Results of this   analysis indicate that VTAs should be located on steeper slopes   with deeper, more-permeable soils, which effectively lowers the   shallow water table. In sloping landscapes (>2%), this model   provides practitioners an easy-to-use VTA design and/or risk   assessment tool that is more hydrological process-based than   current methods.

  Address (URL): http://www.sciencedirect.com/science/article/pii/S0301479710000915