Author: hcho

I have been elected as an OSGeo Charter Member. OSGeo Charter Members serve as the formal voting body of the Open Source Geospatial Foundation (OSGeo) and help guide the direction of major open-source geospatial projects worldwide. I am grateful to the community for the nomination and recognition, and I look forward to contributing to the…

I presented AI for Large-Scale Hydrologic Modeling at the NMSU Engineering Advisory Council Meeting. My talk highlighted the lab’s recent and ongoing research that bridges AI and hydrologic modeling. I covered: and introduced our new pursuit on differentiable deep learning for a New Mexico county.

Abdullah Azzam has published three GRASS addons for hydrologic analysis: r.curvenumber, r.runoff, and r.timeofconcentration.

Madan Pokhrel was awarded an NM WRRI student grant for his project “Remote Sensing-Based Assessment of Groundwater-Induced Subsidence in the Mesilla Aquifer System in New Mexico.” Dung Ho was awarded an NM WRRI student grant for his project “Development of a Machine Learning Approach for Detecting Culvert Linear Features to Support Statewide Hydrologic and Hydraulic…

The Memory-Efficient I/O-Improved Drainage Analysis System (MIDAS) is now available as a C library, and as Python and R packages, as well as a QGIS plugin.

I’ll present a keynote speech “GRASS, Rebuilt – Toward Scalable Cyberinfrastructure for a New Era of Hydrologic Modeling” at FOSS4G 2025 Kansai on July 5, 2025 at 10:45am JST.

I’ll be presenting “A Coupled Hydrologic Modeling Framework for Drought Evaluation in New Mexico” at GEOINFORUM-2025, the 36th General Meeting and Lecture of the Japanese Society for Geoinformatics, at Osaka Metropolitan University. The talk is scheduled for June 27, 2025 at 10:45am JST. See the agenda.