Systems Informatics and Analysis - Engineering and Science of Biomass Feedstock Production and Provision - page 199

such as higher temperature and atmospheric CO 2 concentrations. The results indi-
cated that switchgrass yields increased for the climate change scenario but the effect
on soil erosion was region specifi c. The EPIC model has been recently used as the
foundation to develop the HPC-EPIC to predict biomass productivity at the global
scale [ 31 ]. The simulation platform developed in this work uses high-performance
computing (HPC) simulation with a global natural resource and management dataset
to predict yield of bioenergy crops (Fig. 1 in [ 31 ]). The switchgrass yields predicted
using HPC-EPIC have shown good correlation with observed yields ( r 2 = 0.78 for
lowland cultivar and r 2 = 0.55 for upland cultivar). Such global datasets are extremely
valuable for conducting national and global system studies, as highlighted later.
ALMANAC (Agricultural Land Management Alternatives with Numerical
Assessment Criteria) [ 32 ] is another well-established process-based model that
simulates plant growth, water balance, and soil nitrogen dynamics. The main focus
of ALMANAC is to simulate the intercrop competition, including agricultural crops
as well as weeds. Similar to EPIC, it calculates the total biomass per unit area. Many
subroutines in this model are based on the EPIC model [ 33 ]. ALMANAC also con-
siders varying conditions of soil, rainfall, temperature, and other biophysical condi-
tions to simulate crop growth. The model has been applied successfully to study the
growth of switchgrass in the USA [ 34 - 37 ]. Kiniry et al. [ 36 ] used the model to
simulate switchgrass ( Panicum virgatum L.) yield at fi ve different sites in southeast-
ern USA. The model predicted yields at all sites with reasonable accuracy, and it
also accounted for 47 % of the variability observed in actual yields. This is impor-
tant since it means that the model is capable of predicting seasonal variations in
yield as a function of other driving variables.
Soil and Water Assessment Tool (SWAT) has been developed to study the impact
of different land management practices on water, sediment, and agricultural chemi-
cal yield [ 38 ]. The model can simulate large watersheds over multiple years to
understand the long-term impacts of management practices. It uses mechanistic
relationships rather than regression models, thus enabling the study of watersheds
with limited data. The plant growth model is a simplifi ed version of the EPIC model.
The model has been parameterized to determine the yield of energy crops such as
switchgrass and Miscanthus [ 39 - 41 ]. The model was used to study the impact of
growing switchgrass on agricultural land on environmental and water quality
parameters such as nitrogen runoff, surface runoff, and erosion [ 40 , 42 ].
MISCANMOD is a crop-productivity model to estimate Miscanthus × giganteus
yields [ 43 ]. MISCANMOD uses LAI and RUE parameters related to Miscanthus
combined with a range of climate data to perform simulations using daily time
steps. The model was used to predict Miscanthus yield at various places in Europe,
and the predicted yields matched fairly closely with the measured yield across vari-
ous sites [ 43 , 44 ]. The r 2 value across 32 sites, including rainfed as well as irrigated
sites, was 0.6. The model can also simulate yield in the presence of water stress.
CENTURY model was developed to study the biogeochemistry of terrestrial eco-
systems, in particular the relationship between climate, soil properties, human man-
agement, and plant productivity [ 45 ]. The model provides an important tool to study
the impact of climate change such as higher temperature and altered rainfall patterns