Software Tool Development to Generate Stochastic Hydraulic Simulations using HEC-RAS
Can VBA tools be used to create a robust and powerful software tool that can be utilized to perform Monte Carlo simulation methods in hydraulic modeling to represent probabilistic model results in order to better inform decisions.
Need and Benefit
Hydraulic modeling is an essential part of many aspects of achieving the mission of Reclamation. Hydraulic models
are used to answer many questions about current and future hydraulic and geomorphic conditions and trends, as well
as anticipated effects of projects and infrastructure on hydraulic conditions. Currently, hydrologic models are
deterministic, where model inputs are used to derive a single result. Most rivers are very dynamic in nature, adjusting
their geometry to ever changing inputs in real time. In addition, hydraulic models rely on relatively simple expressions
that integrate over various spatial scales, in order to produce a result. Hydraulic modelers do their best to optimize
model results through rigorous calibration/validation procedures. However, due to large uncertainties in model input
parameters, the cumulative impact of various calibration parameters, and geometric heterogeneities, deterministic
model results convey a confidence in those results that is not consistent with the known uncertainties within the
modeling effort (Bates et. al., 2004).
Reclamation staff have advanced knowledge of hydraulic models and their capabilities. Reclamation staff are involved
in both the development of improved hydraulic modeling capabilities, as well as implementation of existing hydraulic
models in completing their mission. However, assessment of uncertainties within any particular model is beyond the
scope of most projects. Uncertainty assessments currently require significant manual efforts to vary selected input
parameters and compile multiple results into meaningful insights. For this reason, currently few if any modeling efforts
take the extra step to represent the probabilities of different outcomes.
Implementation of this project will facilitate implementation of probabilistic modeling and reduce time required to
implement them, by several orders of magnitude. Stochastic simulation and representation of modeling results as
probabilistic is a growing field and identified as an important and valuable effort in many fields of science and
engineering (Romanowicz & Beven,1996, 1998, 2003; Aronica et. al., 1998, 2002; Bates et. al., 2004; Hall et. al.,
2005; Pappenberger et. al., 2005, 2006). Probabilistic modeling is required for most risk analyses associated with
large infrastructure projects. Development of this tool will allow HEC-RAS modelers from the most sophisticated
regional efforts to the most simple project implemented at the most local level to enter their calibrated and validated
model into this software tool and produce probabilistic results, by doing nothing more than putting in the location of
their model program file. This tool could save on the order of weeks of time for any project to develop probabilistic
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