Model code for Wollheim, W. M., T. K. Harms, A. L. Robison, L. E. Koenig, A. M. Helton, C. Song, W. B. Bowden, and J. C. Finlay. 2022. Superlinear scaling of riverine biogeochemical function with watershed size. Nature Communications 13:1230 https://doi.org/10.1038/s41467-022-28630-z

MATLAB simulation modeling drone mesh networks to meet <4% packet loss. Features interference zone analysis (bridges/rivers), and statistical reliability reporting. Validated 92% link stability in 3.65km² areas. Designed for emergency response systems needing mission-critical uptime.

This contains python codes for a probabilistic model developed for explaining statistical organization in river networks. Please refer research article to understand the model details and algorithm.

This repository includes Python and MATLAB scripts developed for a study assessing flood hydrology in the Black River Watershed. MATLAB was utilized for statistical analysis and HBV hydrological modeling, while Python was employed for machine learning and hybrid modeling using Random Forest and Artificial Neural Networks (ANNs).