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Haruko Murakami Wainwright is currently a tenure-track research scientist at Lawrence Berkeley National Laboratory. After graduating with BS in engineering from Kyoto University in Japan, she earned MS in nuclear engineering (2006), MA in statistics (2010), and PhD in nuclear engineering (2010) at University of California, Berkeley. Her dissertation focused on Bayesian geostatistical inverse modeling for subsurface characterization at the uranium-contaminated DOE Hanford site. Her research has been focused on parameter estimation (PE) and uncertainty quantification (UQ) related to various environmental systems and problems such as Arctic terrestrial ecosystems, groundwater contamination, and deep-subsurface CO2 storage. In particular, she applies Bayesian geostatistical methods to integrate hydrological, geophysical and remote sensing datasets in multiple scales for estimating spatially heterogeneous hydrological, geochemical and ecosystem properties. She also develops and applies global sensitivity analysis methods to various hydrogeological and geochemical models for quantifying the uncertainty in future responses, identifying key controls and processes, and prioritizing the site characterization. She has played a key role in many DOE-sponsored large multidisciplinary projects; the DOE’s Integrated Field Research Challenge (IFRC) project, Sustainable Systems Science Focus Area (SFA), National Risk Assessment Partnership (NRAP), the Advanced Simulation Capability for Environmental Management (ASCEM), and Next Generation Ecosystem Experiment in Arctic (NGEE-Arctic). She is currently a deputy lead of the site application thrust in the ASCEM project to develop comprehensive software to address groundwater contamination and environmental remediation, and she is leading the site application effort of this software at the Savannah River Site F-Area.
Haruko's research can be categorized in the following areas:
(1) Environmental remediation: Integration of datasets with various types (e.g. cores, hydraulic tests, borehole/crosshole/surface geophysical measurements) and scales (several inches to several hundred meters) for plume-scale flow-and-transport simulations, using Bayesian geostatistical methods (as a part of Sustainable Systems Scientific Focus Area); Stochastic flow-and-transport simulations in high-performance computating platforms (as a part of Advanced Simulation Capability for Environmental Management),
(2) CO2 sequesteration: Uncertainty and sensitivity analaysis of CO2 plume migration and pressure build-up (as a part of National Risk Assessment Partnership),
(3) Arctic hydrology: Subsurface characterization at the Arctic tundra site for characterizing permafrost dynamics and hydrology, using various datasets such as core/probe measurements and geophysical and remote sensing data (as a part of Next Generation Ecosystem Experiment-Arctic.)