Modeling soil-plant dynamics: Assessing simulation accuracy
by comparison with spatially distributed crop yield measurements
G. Manoli
Nicholas School of the Environment, Duke University, Durham, NC, USA
S. Bonetti
Pratt School of Engineering, Duke University, Durham, NC, USA
E. Scudiero
USDA-ARS, US Salinity Lab., Riverside, CA, USA
F. Morari
Dept. Environmental Agronomy, University of Padova, Legnaro, Italy
M. Putti
Dept. of Mathematics, University of Padova, Padova, Italy
P. Teatini
Dept. of Civil, Environmental and Architectural Engineering, University of Padova, Padova, Italy
ABSTRACT
Coupling hydrological models with plant physiology is crucial to capture the
feedback mechanisms occurring within the soil-plant-atmosphere continuum.
However, the ability of such models to describe the spatial variability
of plant responses to different environmental factors remains to be proven,
especially at large scales (field or watershed). We used an innovative threedimensional
soil-plant model to quantify temporal and spatial variability of
crop productivity at the field scale, and we assessed simulation accuracy
by comparison with spatially distributed crop yield measurements. A 25-ha
field located in the Venice coastland, Italy, cultivated with a maize (Zea
mays L.) crop and characterized by a highly heterogeneous soil subject
to salt contamination, has been extensively studied by soil sampling, geophysical
surveys, and hydrological monitoring. Based on these observations,
field-scale simulations of soil moisture dynamics coupled with plant transpiration,
photosynthesis, and growth were run and compared with crop
yield maps of different growing seasons. The model captured the observed
crop productivity (grain yield varying between 2 and 15 Mg ha-1), but the
accuracy of the predicted spatial patterns was limited by the available
information on soil heterogeneities. Further model uncertainties are related
to the characterization of the rooting systems and their responses to environmental
factors (soil characteristics, precipitation) that were shown to be
crucial to describe the effect of drought conditions on growth processes.
These results demonstrate that large-scale mechanistic simulations of soil-plant
systems require a trade-off between site characterization, model
processes, and computational efficiency, offering an open challenge for
future ecohydrological research.
