- Impacts of weather events on microbial mediated reactions in the subsurface
- Interactions of microbial mediated reactions in the subsurface with above ground processes
- Contribution of microbial mediated reactions to catchment scale, ecosystem scale and global scale C-N turnovers
- Using machine learning to optimize computational efforts to parameterize and simulate reactive transport
I am modeling microbial mediated reactions and the environmental factors affecting biogeochemical dynamics in the subsurface at the small scale (sub-meter). This knowledge can be applied at the catchment scale by using appropriate upscaling methodologies and coupling the up-scaled biogeochemical model with robust surface water and groundwater flow models. I shall employ this flow and reactive transport model to predict solute discharge in the catchment. This project contributes substantially to identification of environmental drivers and relevant parameters influencing biogeochemical dynamics in the critical zone. This will result in focused parameterization of models in regions where one might not have access to resources to conduct detailed studies using state-of-the-art equipment.
Haritash, A.K., Mittal, N., Aggarwal, R., and Khurana, S. (2017) Stabilisation of wastewater by Lemna minor: A microcosm study. Indian Journal of Waste Management 1: 35-38.
Khurana, S., Heße, F, Thullner, M. (2020). Reactive Transport Simulations Reveal the Influence of Spatio-Temporal Heterogeneities on Biogeochemical Cycling in the Subsurface. CMWR 2020, online event.
Khurana, S., Heße, F, Thullner, M. (2020). Influence of Spatio-Temporal Heterogeneity on Biogeochemical Cycling in the Subsurface using a Numerical Modeling Approach. Goldschmidt 2020, online event.
Bhatia, A., Agarwal, S., and Khurana, S. (2010) Optimal use of waste heat of condenser of thermal
power plant. International conference on fluid dynamics and thermodynamics technologies (FDTT), Singapore.
Khurana, S., Heße, F, Thullner, M. (2020). Predicting microbial redox dynamics in spatially heterogeneous and dynamic conditions using a numerical modelling approach. AGU General Assembly 2020, online event.
Khurana, S., Heße, F, Thullner, M. (2020). Influence of spatio-temporal heterogeneities on microbial redox dynamics and nutrient cycling in the vadose zone. EGU General Assembly 2020, online event.
Khurana, S., Heße, F, Thullner, M. (2019). Influence of spatio-temporal heterogeneities on microbial redox dynamics and nutrient cycling in the vadose zone. EGU General Assembly 2019, Vienna
Young Hydrologic Society. Board Member.
Machine Learning Café. Chair: Timo Houben, Co-Chair: Lennart Schmidt, Swamini Khurana.
PhD-Team Data Science. Chair: Swamini Khurana, Co-Chair: Timo Houben