Modeling Miscanthus in the soil and water assessment tool (SWAT) to simulate its water quality effects as a bioenergy crop.
There is increasing interest in perennial grasses as a renewable source of bioenergy and feedstock for second-generation cellulosic biofuels. The primary objective of this study is to estimate the potential effects on riverine nitrate load of cultivating Miscanthus x giganteus in place of conventional crops. In this study, the Soil and Water Assessment Tool (SWAT) is used to model miscanthus growth and streamwater quality in the Salt Creek watershed in Illinois. SWAT has a built-in crop growth component, but, as miscanthus is relatively new as a potentially commercial crop, data on the SWAT crop growth parameters for the crop are lacking. This leads to the second objective of this study, which is to estimate those parameters to facilitate the modeling of miscanthus in SWAT. Results show a decrease in nitrate load that depends on the percent land use change to miscanthus and the amount of nitrogen fertilizer applied to the miscanthus. Specifically, assuming a nitrogen fertilization rate for miscanthus of 90 kg-N/ha, a 10%, 25%, and 50% land use change to miscanthus will lead to decreases in nitrate load of about 6.4%, 16.5%, and 29.6% at the watershed outlet, respectively. Likewise, nitrate load may be reduced by lowering the fertilizer application rate, but not proportionately. When fertilization drops from 90 to 30 kg-N/ha the difference in nitrate load decrease is less than 1% when 10% of the watershed is miscanthus and less than 6% when 50% of the watershed is miscanthus. It is also found that the nitrate load decrease from converting less than half the watershed to miscanthus from corn and soybean in 1:1 rotation surpasses that from converting the whole watershed to just soybean.
Ng
Tze Ling
TL
Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 205 N. Mathews Avenue, Urbana, Illinois 61801, USA.
Eheart
J Wayland
JW
Cai
Ximing
X
Miguez
Fernando
F
D056804:Biofuels; D018533:Biomass; D003198:Computer Simulation; D018556:Crops, Agricultural / Q000254:growth & development / Q000378:metabolism*; D005308:Fertilizers; D007087:Illinois; D008954:Models, Biological; D018515:Plant Leaves / Q000033:anatomy & histology; D006109:Poaceae / Q000378:metabolism*; D012621:Seasons; D012987:Soil / Q000032:analysis*; D013997:Time Factors; D014867:Water / Q000592:standards*
D056804:Biofuels; D005308:Fertilizers; D012987:Soil; D014867:Water