🙋♀️ 1. Forecasting daily and hourly dam inflow using various Deep Learning approaches in neuralhydrology
🌈 2. Forecaseting daily and hourly dam downstream streaflow and waterlevel using various Deep Learning approaches in neuralhydrology
👩💻 3. Application of MC-LSTM to
🍿 4. Application of Differentiable Modeling to analyze streamflow using Muskingum-Cunge
🧙 5. Data Assimilation for Real-time AI Tool Operation
Forked from mhpi/dMC-Juniata-hydroDL2
A novel differentiable modeling framework to perform routing and to learn a “parameterization scheme” (a systematic way of inferring parameters from more rudimentary information) for routing flows …
Python
Forked from HIPS/autograd
Efficiently computes derivatives of NumPy code.
Python
Forked from uihilab/HydroLang
Web-based Hydrologic Programming Framework
JavaScript
The RAS-Commander library provides a python API for automating HEC-RAS 6.x and accessing HDF data using Python, built with and driven by large language models.
Reference implementation for PyTorch research workflows using MLflow. Features automated experiment tracking, model registry management, production aliasing, and custom authentication handling for internal MLflow servers.
Routing Application for Programmed Integration of Discharge
Pipes • Filters • Tools for Open WebUI
Python library to train neural networks with a strong focus on hydrological applications.
Water management model for the Delaware River Basin, based on the pywr simulation framework
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