431One application of the use of RZWQM2 is development of a decision-aid tool to
guide the choice of a summer crop to replace summer fallow based on knowledge
of soil water at planting for use in the U.S. Central Great Plains. The model was
parameterized and validated based on published field research from two locations,
Akron, CO and Sidney, NE, in the U.S. Central Great Plains (Saseendran et al.
2008 , 2009 , 2010a). The model was used to simulate long-term yields and output
was used to calculate net returns for maize, canola, and proso millet and two annual
forage crops, foxtail millet and spring triticale, in a wheat-summer crop-fallow rota-
tion. The simulations were performed with varying plant available water (PAW) at
the time of planting (25, 50, 75 and 100 % PAW). By simulating multiple crop years
using historic weather but variable PAW at planting as model inputs, yield probabil-
ity curves were generated (Fig. 5 ). With this information, growers can forecast
probable yields of different crops based on the PAW at planting. Yield increased for
all crops as initial PAW increased, but the response was greatest for forage crops and
least for maize (Fig. 5 ). Probable yields can then be used with current production
costs and commodity prices to select the most advantageous summer crop. Under
the conditions used in the study, forage crops had greater net economic returns than
any of the grain crops (Fig. 6 ). Among the grain crops, proso millet was the most
profitable crop at Akron, while canola was the most profitable crop at Sidney, illus-
trating the value of the model for guiding site specific decisions. Modelling allows
users to evaluate many alternatives, including different environmental conditions,
climate scenarios, production costs, and commodity prices.
In addition to guiding management decisions, models can provide mechanistic
understanding of how management practices or environmental conditions control
observed cropping system outcomes. This understanding can lead to development
of new ideas and technology for improving resource use. To illustrate, Saseendran
et al. (2005a) evaluated RZWQM for its ability to simulate a 2-year winter wheat-
summer fallow rotation under tilled and no-till conditions on a Weld silt loam soil
in semi-arid northeastern Colorado. Field observations of increased water storage
during no-till fallow were explained by model predictions of crop residue dynamics
and the effects of residue on soil evaporation (Fig. 7 ). In the tilled wheat-summer
fallow rotation, residue mass increased at harvest but decreased shortly thereafter
due to tillage. In the no-till wheat-summer fallow rotation, residue remaining at the
soil surface during the summer fallow period increased evaporative resistance and
decreased water lost from evaporation relative to the tilled system. The model out-
put of residue dynamics explained why increased soil moisture was observed in
no-till fallow and gives details about the temporal dynamics. This information can
be useful in developing different cropping practices. For example, the model showed
that the increased soil moisture during fallow does not always translate to greater
yield in a wheat-summer fallow rotation because the is often adequate water for a
single wheat crop even in the tilled system. This gave rise to intensified wheat-
summer crop-fallow rotations to take advantage of the increased water retention in
no-till systems.
Dryland Agriculture in North America