Shu, Song

Contact Information

Education

Current Research

Dr. Song Shu’s research centers on advancing hydrologic understanding and engineering applications in the context of climate-driven change across the Earth’s water cycle. He focuses on water resources, lake and river hydrology, and bathymetric and geomorphologic evolution, with particular emphasis on how these processes affect infrastructure resilience and water management. Multi-platform remote sensing (satellite altimetry, multispectral, SAR, and LiDAR observations), and UAV-based measurements are integrated with GIS advanced computational approaches, including deep learning and artificial intelligence to address these challenges. This computing-driven framework enables the quantification and prediction of spatiotemporal variability in key hydrologic variables at scales ranging from individual watersheds to global systems. Specifically, Dr. Shu investigates the dynamics of lake water levels, surface water storage, water quality, snow accumulation, and erosion processes under a changing climate.

Selected Publications

Shu, S., Liu, H., Wang, L., Seo, J., Tian, D., Beck, R., Su, H., & Wang, S. (2026).
GLWaterlevel-analyst: An open-source remote sensing toolbox in QGIS for global lake
water level analysis and prediction. Remote Sensing Applications: Society and
Environment, 43, 102144, https://doi.org/10.1016/j.rsase.2026.102144
Shu, S., Liu, H., Beck, R., Wang, L., Tian, D., & Seo, J. (2026). Mapping near-daily
large lake water surface topography by integrating SWOT swath observations with
multi-mission satellite radar altimetry. Journal of Hydrology, 676,
https://doi.org/10.1016/j.jhydrol.2026.135724
Shu, S., Yu, O.-Y., Schoonover, C., Liu, H., & Yang, B. (2023). Unmanned Aerial
Vehicle-Based Structure from Motion Technique for Precise Snow Depth Retrieval –
Implication for Optimal Ground Control Point Deployment Strategy. Remote Sensing,
15, 2297 (IF: 5.0) https://doi.org/10.3390/rs15092297
Shu, S., Liu, H., Beck, R.A., Frappart, F., Korhonen, J., Lan, M., Xu, M., Yang, B., &
Huang, Y. (2021). Evaluation of historic and operational satellite radar altimetry missions
for constructing consistent long-term lake water level records. Hydrology and Earth
System Science, 25, 1643-1670 (IF: 6.9) https://doi.org/10.5194/hess-25-1643-2021
Shu, S., Liu, H., Beck, R.A., Frappart, F., Korhonen, J., Xu, M., Yang, B., Hinkel, K.M.,
Huang, Y., and Yu, B., (2020). "Analysis of Sentinel-3 SAR altimetry waveform
retracking algorithms for deriving temporally consistent water levels over ice-covered
lakes." Remote Sensing of Environment, 239: 111643 (IF: 13.5).
https://doi.org/10.1016/j.rse.2020.111643

Instruction

Short Biographical Sketch

I am an Associate Professor at Kansas State University and Director of the Geographic Information Systems Spatial Analysis Lab (GISSAL) in the School of Earth and Environment. My research focuses on hydrology and water resources, particularly lakes, rivers, reservoirs, snow, and soil erosion. I use satellite remote sensing, drones, field observations, GIS, and machine learning to better understand water systems and develop practical tools for water resources management. I am especially interested in combining geospatial data and computational methods to monitor and predict changes in water resources at different scales. I enjoy teaching GIS, remote sensing, spatial analysis, and programming, with an emphasis on hands-on learning and real-world water and environmental problems. I also work closely with students through research, mentoring, and graduate advising. Beyond research and teaching, I am active in professional service, scientific collaboration, and community outreach. Through GISSAL, I look forward to building interdisciplinary collaborations and advancing the use of geospatial technologies to address water resources challenges in Kansas and beyond.

More information about Dr. Song Shu’s research, teaching, and service is available here.