Olsson Hall 283
Link Lab (2nd floor of Olsson Hall) 151 Engineers Way
Google Scholar Research Gate Link Lab Hydroinformatics Group Center for Transportation Studies


Jonathan Goodall is a Professor in the Department of Civil and Environmental Engineering at the University of Virginia (UVA) and Director of the UVA Engineering Link Lab. He is a water resources engineer working to advance the field of hydroinformatics where data and computational sciences are used to improve the understanding, forecasting, and management of water systems. Much of his current work focuses on adapting techniques from cyber-physical systems for real-time flood mitigation in coastal urban communities experiencing sea level rise impacts. Professor Goodall leads the Hydroinformatics Research Group housed in the Link Lab, co-directs the UVA Public Interest Technology University Network (PIT-UN), is a member of UVA's Pan-University Environmental Resilience Institute steering committee, and is an affiliated faculty member of the Center for Transportation Studies. Professor Goodall is a registered Professional Engineer (PE), a Fellow of the American Society of Civil Engineers, and an elected member of the Virginia Academy of Science, Engineering, and Medicine. He earned his Ph.D. and M.S. in Civil Engineering from the University of Texas at Austin and his B.S. in Civil Engineering from the University of Virginia.


Ph.D., Civil Engineering, ​​University of Texas at Austin, 2005

M.S., Civil Engineering, ​University of Texas at Austin, 2003

B.S., Civil Engineering, University of Virginia, 2001

Research Interests

Water Resources Engineering
Smart Cities

Selected Publications

pystorms: A simulation sandbox for the development and evaluation of stormwater control algorithms Rimer, S.p., Mullapudi, a., Troutman, S.c., Ewing, G., Bowes, B.d., Akin, a.a., Sadler, J., Kertesz, R., Mcdonnell, B., Montestruque, L. And Hathaway, J., 2023. Environmental Modelling & Software, P.105635.
Predicting combined tidal and pluvial flood inundation using a machine learning surrogate model Zahura, F.t. And Goodall, J.l., 2022. Journal of Hydrology: Regional Studies, 41, P.101087.
Flood resilience through crowdsourced rainfall data collection: Growing engagement faces non-uniform spatial adoption Chen, a.b., Goodall, J.l., Chen, T.d. And Zhang, Z., 2022. Journal of Hydrology, 609, P.127724.
Reinforcement learning-based real-time control of coastal urban stormwater systems to mitigate flooding and improve water quality. Bowes, B.d., Wang, C., Ercan, M.b., Culver, T.b., Beling, P.a. And Goodall, J.l., 2022. Environmental Science: Water Research & Technology, 8(10), Pp.2065-2086.
Data-Driven Model Predictive Control For Real-Time Stormwater Management. Ning, J., Bowes, B.d., Goodall, J.l. And Behl, M., 2022, June. In 2022 American Control Conference (Acc) (Pp. 1438-1443). Ieee.

Courses Taught

CE 6230 Hydrology
CE 6500 Hydroinformatics


Elected Member, Virginia Academy of Science, Engineering, and Medicine 2021
Elected Fellow, American Society of Civil Engineering 2018
Early Career Research Excellence Award, International Environmental Modelling & Software Society (iEMSs) 2012
CAREER Award, National Science Foundation 2009