Parameter Optimization for the HYPE model with Shuffled Frog Leaping Algorithm (SFLA)

Python scripts for controlling parameter optimization for the hydrological model HYPE. The scripts can be used to optimize model parameters with the Shuffled Frog Leaping Algorithm (SFLA). Additionally, there is a modification of the Differential Evolution Markov Chain (DEMC) algorithm, which has been previously applied for HYPE. In this first version, all parameters of SFLA as well as of HYPE are hard coded within one script. HYPE version 5.8.0 was used without modifications of the code. At the end of each simulation, HYPE opens a window and asks for a confirmation to exit this window. We have used an auto-clicker to overcome that step. However, modifying the HYPE code would be a better solution for future releases.

Data and Resources

Cite this as

Prajna Kasargodu Anebagilu, Xinyu Li (2022). Dataset: Parameter Optimization for the HYPE model with Shuffled Frog Leaping Algorithm (SFLA). https://doi.org/10.25835/u0wna7hm

Retrieved: July 4, 2022, 13:12 (+0200)

Additional Info

Field Value
Author Prajna Kasargodu Anebagilu, Xinyu Li
Maintainer Jörg Dietrich
Version 0.8
Last Updated April 28, 2022, 11:36 (+0200)
Created April 27, 2022, 21:27 (+0200)
License Creative Commons Attribution 3.0
Dataset Size 16.2 KByte