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S.S. Papadopulos & Associates, Inc. and Watermark Numerical Computing
(the developers of PEST) are pleased to provide consultancy services in
model calibration and predictive uncertainty analysis.
Please
contact us if
you need help with any of the following:
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Use of PEST in the calibration of complex environmental models, including
groundwater flow and transport models, surface water quality and quantity
models, and any other kind of model.
Using
the latest technology ( such as
SVD-Assist
), we
can show you how to apply regularized inversion to the calibration of
complex models. With regularized inversion model-to-measurement fits are
better, and model predictive error variance is smaller than using
traditional zone-based techniques.
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Software development.
No graphical user interface or simulation program provides solutions for
all modeling applications. We have developed programs to support the
modeling process in a wide variety of settings. We can write custom
software to enhance your modeling in specific application areas; assist
you in processing environmental data; and allow you to most efficiently
and effectively incorporate data into the model calibration and predictive
analysis processes.
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Quantification of model predictive uncertainty.
Where the cost of being wrong
is high, model predictive uncertainty analysis is an essential component
of model deployment. Using PEST and ancillary software we can help you
understand potential errors associated with critical model predictions
through comprehensive analysis of uncertainty. This includes innate
parameter variability, constraints on this variability imposed by model
calibration, and the possible contribution from complexity that is beyond
the reach of the calibration process.
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Parallelization of the model calibration and predictive uncertainty
analysis process.
Once
an inversion problem has been properly posed and a PEST dataset created
for your model, we can help you calibrate that model faster using Parallel
PEST on a network of fast computers.
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Optimization of data acquisition.
Data acquisition is expensive yet sound environmental management
necessitates it. What is the best data to gather? It is that which reduces
the uncertainty of a key model prediction the most. The extent to which
the acquisition of data can reduce model prediction uncertainty can be
quantified using PEST in regularization mode together with ancillary
software. Hence, different data-gathering strategies can be evaluated
using sound scientific bases.
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Models or mediation and negotiation.
PEST
enables the quantification of the predictive limits of available data and
modeling software, leading to understanding of the limits of the model as
deployed. This quantification of uncertainty allows models to be deployed
to support negations between stakeholder groups, and as a basis for
dispute resolution.
We can provide these services
tailored to your modeling requirements.
One
option is a 40-hour “PEST Immersion” which includes:
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8 hours for us to
review your modeling needs and prepare specific materials
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A 12-hour in-house
PEST course introducing basic aspects of non-linear parameter
estimation, and the advanced aspects that are relevant to your modeling
context
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A 12-hour period of
collaboration to set up your model for non-linear parameter estimation,
regularized inversion, or predictive analysis
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8 hours of follow-up
technical support, to help you continue developing PEST skills
Please
contact us if you would like to discuss a PEST
emersion similar to that described above, tailored to your specific
needs.
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