Agriculture Reference
In-Depth Information
Fig. 8.4. Prototype services showing the soils, land parcel, wetland inventory in a central database used
to automate the development of the PIHM model for a site in Pennsylvania, USA. (From Leonard and
Duffy, 2013.)
impedes current efforts to predict and
manage Earth's water and ecological
resources. To date, databases for large-
scale applications have been created
and applied ad hoc to attend to a spe-
cific demand, rather than a growing set
of new and future demands, with
limited reuse of information due to
lack of compatibility among seemingly
similar efforts.
science understanding to larger domains,
which will improve the prospect of carbon-
nitrogen management greatly.
The novelty of the proposed strategy is
that for the first time a spatially explicit and
physically based hydrological model will be
coupled with the nutrient cycling and agro-
nomic simulation model, a necessary step to-
wards a complete virtual representation of the
physical and biological matrix of a watershed.
This is enabled largely by the steady progress
in computing power, accessibility of high-
resolution soils, weather and land-use data,
and advances in necessary theoretical and em-
pirical knowledge for predictions in terrestrial
hydrologic and biogeochemical processes.
The development of such a model will allow
simulating virtual scenarios in agricultural
catchments, support the analysis of emerging
and fully coupled properties of the soil carbon
system and implement realistic management
optimization schemes that consider the vari-
ability of the landscape explicitly, so that man-
agement in one land unit can be evaluated
transparently for its on-site and off-site effects.
Scaleability of model data for decision
making : it is critical that the next-
generation algorithms and technologies
for data access, simulation and delivery
should apply to all scales for plot, land-
scape and catchment scales, such that
management practice can be tested
across scales, from single fields to large
watersheds, specifically targeting the
impact of landscape practices and
long- term outcomes.
The modelling strategy proposed has im-
portant implications for soils research at
Critical Zone Observatories to scale up their
 
 
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