Most rivers have no gauges, which makes it hard to forecast floods and manage water. Researchers have a new approach: A machine learning model that estimates upstream river flow using downstream data, even without sensors.
Read more here: https://t.co/RSVQVa3kmP
📊 Big boost for the National Water Model! UA Ph.D. student Savalan Naser Neisary and advisor Steve Burian of @UA_CIROH have developed a machine learning framework that slashes bias and boosts streamflow forecast accuracy by up to... More https://t.co/yacpHY3R6C #WaterForecasting
UA Ph.D. student Savalan Naser Neisary and advisor Steven Burian have developed a machine learning framework that slashes bias and boosts streamflow forecast accuracy by up to 65% in drought-prone, reservoir-heavy regions like the Western U.S.
🔗 https://t.co/1FL72BjYsR
Excited to share our new publication on improving the National Water Model streamflow predictions using a post-processing machine learning-based framework. Huge thanks to my co-authors, my advisor Dr. Steven Burian, and CIROH for supporting this work!
https://t.co/Bx4RgkThBM
Finally, I presented my poster on "ML Post-Processing Enhances NWM Accuracy by 30% in Watersheds with Extensive Water Infrastructure" at CIROH DevCon, discussing the usage of XGBoost for post-processing NWM data. Thanks to Ryan Johnson, Mohammad Shahabul Alam, and Steve Burian.
I had the pleasure of leading a second workshop at the CIROH Developer's Conference on how to use Machine Learning to post-process and improve the accuracy of the NWM by 30% in drought-prone watersheds. Thanks to Ryan Johnson and all participants for the valuable feedback!
I had a great experience leading two workshops and presenting a poster on ML post-processing of NWM data using Amazon SageMaker at CIROH DevCon. The first workshop was about leveraging SageMaker to develop LSTMs. Thanks to @arpita0911patel , James Halgren, and Scott Hendrickson.
Excited to present at the EWRI event tomorrow! I'll discuss the spatiotemporal patterns of multi-year hydrological droughts and their impact on the Great Salt Lake. Join for insights and networking. See you there!
#EWRI2024#ASCE#DroughtAnalysis#GreatSaltLake#CIROH
If you are interested in ML applications in operational hydrological prediction and the National Water Model (NWM) and would like to discuss potential collaborations or learn more about our research, please feel free to contact us.
Honored to receive the Presentation Award Runner Up – Graduate for the best graduate student presentation at the AWRA Spring 2024 Conference for our work on “Improving NWM Predictions in Watersheds with Extensive Water Resources Infrastructure.”
#AWRA#CIROH#ML#NWM
A special thanks to my advisor, Dr. Steven Bruian, and our team, Ryan Johnson and Mohammad Shahabul Alam, PhD, for their incredible support and insights.
Also, a special shout-out to the @UA_CIROH and @AlabamaWater