❄️🌡️ New paper on #SnowDroughts by
our colleague David Gampe et al: "The emergence of snow droughts as drivers of negative extremes in plant productivity over the past decades" in 𝗘𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁𝗮𝗹 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗟𝗲𝘁𝘁𝗲𝗿𝘀.

🔗 Learn more: https://www.geo.lmu.de/geographie/en/latest-news/news-overview/news/new-publication-in-environmental-research-b72db7cd.html

#geography #research #science #sustainability #climatechange #environmentalmodeling

🌊 Hydrological patterns in the Inhulets River Basin

I’m working on a large-scale study of the technogenic impact on the Inhulets River system (Ukraine).
The workflow combines R + SAGA GIS + QGIS for geomorphometric and hydrological analysis.

Over the past week, I’ve been refining digital elevation models and tracing surface runoff connectivity — not an easy task in a region reshaped by century of mining.

The map below shows one of the calmest and most “well-behaved” areas, far from the mining zone.
As for the drainage network over the mining areas… let’s just say it’s geological chaos down there 😄

🛰️ Data: Copernicus DEM (GLO-30)
🧭 Tools: SAGA GIS (Terrain Analysis), R, QGIS

#Hydrology #Geomorphometry #SAGAGIS #QGIS #RStats #DEM #GIScience #EnvironmentalModeling #MiningImpact #Geodata #InhuletsRiver #Ukraine #KryvyiRih #Copernicus #CopernicusDem

#TBT to the inspiring Lightning Talks at the Center for Geospatial Analytics during the GRASS Developer Summit in Raleigh! ⚡️🌍

We heard rapid-fire insights on a wide range of geospatial innovations!
https://grass.osgeo.org/news/2025_05_27_grass_dev_summit_report/

Big thanks to everyone who shared their work and ideas!

📺 Stay tuned — videos coming soon!

#FOSS4G #OpenSource #Geospatial #RemoteSensing #Hydrology #UrbanPlanning #EnvironmentalModeling

Exciting News from the #AI and #freshwater Modelling project at the University of Auckland! 🎓

Master’s student Nicolas Samelson, supervised by Dr. Jörg Wicker and Dr. Katharina Dost, is breaking new ground in #environmentalmodeling. His thesis leverages #machinelearning to enhance process-based models, especially in scenarios with limited data.

Learn more about this pioneering work on our website!

https://freshwater.blogs.auckland.ac.nz/research-project-machine-learning-for-process-based-environmental-modelling-in-data-limited-scenarios/