Originally published in our April 2022 newsletter (Issue 14)
In his ICoM- sponsored work, Sanjib collaborates with Earth scientists, engineers, social scientists, and decision makers to design new risk management strategies that have potential to enable infrastructure robustness against deep uncertainties.
Sanjib Sharma is an assistant research professor in the Earth and Environmental Systems Institute at Penn State. He graduated from Penn State with a Ph.D. in Civil and Environmental Engineering. Sharma received a master’s degree from Southern Illinois University and a bachelor’s degree in civil engineering from Tribhuvan University in Nepal. His research focuses on advancing the fundamental understanding of the interactions and nonlinear feedbacks between water and other systems (such as climate, urban, and infrastructure). He integrates methods from Earth science, engineering, and data science to inform decisions addressing critical environmental challenges. Example applications include water resources planning, flood risk management, and critical infrastructure design.
One key challenge Sharma tackles is the deep and dynamic uncertainties surrounding projected flood risks. These deep uncertainties can stem, for example, from choice of model structures, model parameters, and unresolved processes related to human decisions and biophysical processes. Neglecting deep uncertainties can drastically underestimate the tails of hazard probability distribution and can result in poor decisions as well as outcomes. Sharma integrates land surface models with methods for Bayesian data-model fusion and model diagnostics to better understand multi-sector dynamics and to inform the design of risk management strategies. As part of the U. S. Department of Energy (DOE) supported multi-institutional effort on Integrated Coastal Modeling (ICoM), Sharma is collaborating with hydrologists from Pacific Northwest National Laboratory to apply novel methods for urban flood hazard characterizations. These new methods can improve (i) the diagnosis of the underlying hydrodynamic models, (ii) the uncertainty characterization, and (iii) the understanding of the multisector dynamics.
Sharma explores new approaches to designing urban infrastructure in a changing climate. Traditional strategies for flood-sensitive infrastructure design typically assume a stationary rainfall distribution and neglect the deep uncertainties surrounding projections of the coupled natural-human systems. Designing infrastructure in the face of dynamic climate, land-use and socioeconomic uncertainties poses highly complex decision problems. Sharma studies robust decision-making and infrastructure design under deep uncertainty approaches that have potential to enable infrastructure robustness under dynamic conditions.
Highlighted Articles:
Cooper C.M., S. Sharma, R. Nicholas, K. Keller, 2022. Trade-offs in the design and communication of flood-risk information. Under Review. Preprint available: arXiv:2201.01254
Sharma, S., B.S. Lee, R. Nicholas, and K. Keller, 2021. A safety factor approach to designing urban infrastructure for dynamic conditions. Earth’s Future, 9, e2021EF002118. https://doi.org/10.1029/2021EF002118.
Sharma, S., B. S. Lee, H. S. Iman, M. Haran, and K. Keller, 2022. Neglecting uncertainties surrounding model parameters can drastically underestimate flood risks. Under Review. Preprint available: https://doi.org/10.1002/essoar.10510275.1[4] Sharma, S., M. Gomez, K. Keller, R.
Nicholas, and A. Mejia, 2021. Regional flood risk projections under climate change. Journal of Hydrometeorology, 22(9), pp.2259-2274, https://doi.org/10.1175/JHM-D-20-0238.1