Texas Hill Country Flood
Displacement‑corrected rainfall improved peak timing by 6–8 hours and RMSE by 23% across 4 gauges.
HydroSky transfers cutting-edge hydrometeorological technology to support climate change resilience for future hydrological extremes and water resources sustainability. We bridge advanced research and practical applications, delivering innovative solutions for climate resilience and water security.
Basins Modeled (HUC8)
Event Match for Top‑3 Peaks
Lead Time for Early Warning
Faster Scenario Exploration
From real‑time warnings to long‑term planning, HydroSky adapts to your data and decisions.
High‑resolution rainfall ingestion (MRMS/HRRR), hydrologic routing with CREST/EF5, probabilistic peaks, and push alerts with explainable drivers.
Soil‑moisture deficits, runoff efficiency, and snowmelt diagnostics for seasonal allocation, resilience, and supply risk planning.
What‑if storm tracks, displacement correction, reservoir rules, and land‑use change—compare impacts in minutes, not weeks.
Map tiles, time‑series, exceedance curves, and API endpoints for enterprise integration.
Hybrid physics‑ML stack: physical consistency meets data‑driven speed.
HRRR/MRMS/GraphCast/GFS ingestion, bias & displacement correction, and automated basin tiling.
CREST/EF5 routing with calibrated parameters; AI‑assisted guidance for robust generalization.
Attribution of peaks to upstream basins, snowmelt vs. rainfall shares, and sensitivity to storm shifts.
Zero‑ops static frontends (GitHub Pages) plus optional cloud backends for on‑demand heavy runs.
Illustrative results. Replace with your own projects and images when ready.
Displacement‑corrected rainfall improved peak timing by 6–8 hours and RMSE by 23% across 4 gauges.
Combined snowmelt diagnostics and runoff thresholds to quantify reservoir drawdown risks under El Niño.
HUC8 contribution tree reveals upstream drivers of compound events and flash‑to‑flood transition windows.
Clear steps, measurable outcomes.
Use cases, basins, data access, KPIs. We align on scope and timeline.
Spin up a pilot basin with baseline datasets and dashboards.
Hybrid guidance + targeted runs for robust generalization—not just a single “best fit”.
Web delivery, training, and integration. Optional SLA for ops and updates.
Meet the researchers, scientists, and collaborators driving innovation in hydrological remote sensing.
Professor, CEES / SoM
yanghong@ou.edu
Adj. Associate Professor, SoM / NOAA NSSL
jj.gourley@noaa.gov
Research Scientist, Adj. Faculty, ARRC / CEES
pierre.kirstetter@noaa.gov
Research Scientist
kezhang@ou.edu
Research Scientist, CIMMS
humber@ou.edu
Assistant Professor
tiantian.yang@ou.edu
CEES Graduate Student
mchen15@ou.edu
COE/CEES
li1995@ou.edu
Geoinformatics
Zhen.Hong-1@ou.edu
Post-doc, COE/CEES
xyluo@ou.edu
Post-doc, CEES
Liang.Gao-1@ou.edu
Post-doc, CEES
jiaqi.zhang@ou.edu
Senior Research Fellow, IFPRI
l.you@cgiar.org
Assistant Professor, CEES
naiyu.wang@ou.edu
Professor, University of Connecticut
manos@engr.uconn.edu
Senior Research Scientist, University of Maryland
radler@umd.edu
Research Scientist, National Water Center
sadiq@ou.edu
Postdoc Research Fellow, CEES
chenshengou@ou.edu
Tell us about your basins and decisions. We’ll tailor a demo to your data.
GitHub Pages is static—use the email link below or connect a form service later.