Author: hcho

I am invited to deliver a research talk “Parallel Processing Methods for Big Data in Hydrology” for the Kyungpook National University (KNU) Global Seminar Series (translated).

A new paper on the Memory-Efficient Watershed Delineation (MESHED) parallel algorithm “Avoid backtracking and burn your inputs: CONUS-scale watershed delineation using OpenMP” is just published in Environmental Modelling & Software. Check its author’s version and source repository. The final version of the paper will freely be available for the next 50 days through this link.

I am invited to give a seminar “Memory-Efficient Flow Accumulation Computing Using GRASS GIS” for the Osaka Metropolitan University (OMU) Science Frontier Geoscience Seminar Series (translated) and a workshop “Physically-Based Hydrologic Modeling Using GRASS GIS” at the OMU Graduate School of Science.

I presented the “Evolution of GRASS GIS” and “An OpenMP Algorithm for Delineating a Large Number of Watersheds” at the Free and Open Source Software for Geospatial North America (FOSS4G NA) 2024 Conference.

The Memory-Efficient Watershed Delineation (MESHED) OpenMP parallel algorithm is released under GPL v3 as part of the Memory-Efficient I/O-Improved Drainage Analysis System (MIDAS).

This is the objective function surface of an unsteady 2D HEC-RAS model that minimizes the volume error and maximizes the NSE by trying 10,000 different combinations of the curve number and Manning’s n. That best model (still with a 5.75% volume error) is very hard to find on a relatively flat valley. Calibrating the RAS…

I presented “Memory Efficiency in Parallel Computation of Continental-Scale Hydrologic Parameters” and “Open-Source Hydrology Using GRASS GIS” at the 2024 Cooperative Institute for Research to Operations in Hydrology (CIROH) Developers Conference (DevCon) on May 29, 2024.

I’m introducing the Memory-Efficient I/O-Improved Drainage Analysis System (MIDAS). It consists of various modules for hydrologic parameter calculations including flow accumulation, watershed delineation, longest flow path, and flow length. More modules will be added later. Please try its early release of Windows binaries at https://github.com/HuidaeCho/midas.

I just started this GIS algorithm research for fast memory-efficient flow length calculation using OpenMP. Try it yourself: https://github.com/HuidaeCho/midas.