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Data · dataset · 2026

Raspy-Cal: A genetic algorithm-based automatic calibration tool for HEC-RAS hydraulic models

Listed in National Center for Atmospheric Research

While automatic calibration programs exist for many hydraulic models, no user-friendly and broadly reusable automatic calibration system currently exists for steady-state HEC-RAS models.

Description

This study highlights development of Raspy-Cal, an automatic HEC-RAS calibration program based on a genetic algorithm and implemented in Python. It includes a graphical user interface and an interactive command-line interface, as well as libraries readily usable by other programs.

As a case study, Raspy-Cal was used to calibrate a model of the Los Angeles River in California and its two major tributaries. We found that Raspy-Cal matched the accuracy of manual calibrations in much less time and without manual intervention, producing a Nash-Sutcliffe Efficiency of 0.89 or greater within several hours when run for 100 iterations. Our analysis showed that the open-source freeware facilitates fast and precise calibration of HEC-RAS models and could serve as a basis for future software development.

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Raspy-Cal is available online in source and executable form as well as through the Python Package Index.

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Provenance · 1 source records, 7 field assertions
SourceKeyLast seenRaw
National Center for Atmospheric Research04a0f63d-6818-4a8e-bb04-e4e5f58b9d3510 d agoJSON v1
FieldAssertionExtractorEvidence
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concepts[field].local:field:ocean-atmosphericmapping · data ucar educonnector:data_ucar_edu@1.0.0
created_datesource · data ucar educonnector:data_ucar_edu@1.0.0
descriptionsource · data ucar educonnector:data_ucar_edu@1.0.0/notes
publication_datesource · data ucar educonnector:data_ucar_edu@1.0.0
titlesource · data ucar educonnector:data_ucar_edu@1.0.0/title
updated_datesource · data ucar educonnector:data_ucar_edu@1.0.0