Raspy-cal: A genetic algorithm-based automatic calibration tool for hec-ras hydraulic models

Abstract

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