ABSTRACT
A study was initiated to investigate the sustainability effects of intercropping switchgrass ( L.) in a loblolly pine ( L.) plantation. This forest-based biofuel system could possibly provide biomass from the perennial energy grass while maintaining the economics and environmental benefits of a forest managed for sawtimber. Operations necessary for successful switchgrass establishment and growth, such as site preparation, planting, fertilizing, mowing and baling, may affect hydrology and nutrient runoff. The objectives of this study were (i) to characterize the temporal effects of management on nutrient concentrations and loadings and (ii) to use pretreatment data to predict those treatment effects. The study watersheds (â¼25 ha each) in the North Carolina Atlantic Coastal Plain were a pine/switchgrass intercropped site (D1), a midrotation thinned pine site with natural understory (D2), and a switchgrass-only site (D3). Rainfall, drainage, water table elevation, nitrogen (total Kjedahl N, NH-N, and NO-N), and phosphate were monitored for the 2007-2008 pretreatment and the 2009-2012 treatment periods. From 2010 to 2011 in site D1, the average NO-N concentration effects decreased from 0.18 to -0.09 mg L, and loads effects decreased from 0.86 to 0.49 kg ha. During the same period in site D3, the average NO-N concentration effects increased from 0.03 to 0.09 mg L, and loads effects increased from -0.26 to 1.24 kg ha. This study shows the importance of considering water quality effects associated with intensive management operations required for switchgrass establishment or other novel forest-based biofuel systems.
ABSTRACT
We present a hybrid and stand-level forest ecosystem model, DRAINMOD-FOREST, for simulating the hydrology, carbon (C) and nitrogen (N) dynamics, and tree growth for drained forest lands under common silvicultural practices. The model was developed by linking DRAINMOD, the hydrological model, and DRAINMOD-N II, the soil C and N dynamics model, to a forest growth model, which was adapted mainly from the 3-PG model. The forest growth model estimates net primary production, C allocation, and litterfall using physiology-based methods regulated by air temperature, water deficit, stand age, and soil N conditions. The performance of the newly developed DRAINMOD-FOREST model was evaluated using a long-term (21-yr) data set collected from an artificially drained loblolly pine ( L.) plantation in eastern North Carolina, USA. Results indicated that the DRAINMOD-FOREST accurately predicted annual, monthly, and daily drainage, as indicated by Nash-Sutcliffe coefficients of 0.93, 0.87, and 0.75, respectively. The model also predicted annual net primary productivity and dynamics of leaf area index reasonably well. Predicted temporal changes in the organic matter pool on the forest floor and in forest soil were reasonable compared to published literature. Both predicted annual and monthly nitrate export were in good agreement with field measurements, as indicated by Nash-Sutcliffe coefficients above 0.89 and 0.79 for annual and monthly predictions, respectively. This application of DRAINMOD-FOREST demonstrated its capability for predicting hydrology and C and N dynamics in drained forests under limited silvicultural practices.
