430
Despite supplying only 45 kg N ha, the PV treatment produced more SOC than a
treatment receiving 90 kg N ha (Fig. 4 ).
5 Modelling Management Practices for Water Productivity
in Dryland Cropping Systems
In the U.S. Great Plains, reduced tillage system have allowed for replacement of the
summer fallow period with a summer annual crop, a dryland practice that improves
productivity and precipitation use efficiency (Farahani et al. 1998 ; Nielsen et al.
2005 ). The summer crop uses water for growth (evapotranspiration) that would oth-
erwise have been lost through soil evaporation during the summer fallow period.
While this practice has been widely adopted, the selection of the most advantageous
summer crop in the rotation is challenging and costly due to variation in geographic
and temporal conditions. The choice of summer crop must consider its economic
return but also not compromise the subsequent wheat crop due to excessive water
use. The summer crop selected should also help with weed and pest control and soil
conservation needs. Research has documented conditions suitable for summer crops
including maize, grain sorghum, proso millet, and annual forages (Dhuyvetter et al.
1996 ; Nielsen et al. 2006 ; Shanahan et al. 1988 ; Smika and Unger 1986 ). However,
results of field research can only be applied within the spatial and temporal limits
that it was conducted in. This limitation highlights the need for tools to extrapolate
research information beyond its limits. The use and application of cropping system
models is one approach, which has been successful in expanding knowledge from
field research to answer important production question over a broader range of loca-
tions and years.
Several cropping systems models have been developed and applied to dryland
cropping systems including The Root Zone Water Quality Model (RZWQM; Ahuja
et al. 2000 ; Ma et al. 2009 ), APSIM (McCown et al. 1996 ), CropSyst (Stockle et al.
2003 ), DSSAT-CSM (Jones et al. 2003 ; Jame and Cutforth 1996 ; Saseendran et al.
2004 , 2005a; Elliott and Cole 1989 ; Mathews et al. 2002 ). Here we highlight the use
of the Root Zone Water Quality Model (RZWQM2). RZWQM2 is a process-
oriented model that uses algorithms to integrate biological, physical, and chemical
processes for integration, synthesis, and extrapolation across soils and climates of
effects at the system level. The model includes a wide spectrum of cultural practices
to allow for simulations of varying tillage, residue management, fertilizers, and crop
rotation. Driving factors such as weather, soil, and crop parameters can be modified
and outputs include crop production and water quality parameters (Ahuja et al.
2000 ; Ma et al. 2009 ). RZWQM2 has been successfully used to inform manage-
ment in dryland cropping systems for the U.S. Great Plains (Ma et al. 2003 ;
Saseendran et al. 2004 , 2005a, b, 2008 , 2009 ).
N.C. Hansen et al.