Yaoping Wang Email & Phone Number

Co-organizer of a Soil Moisture Working Group under the Reducing Uncertainty in Biogeochemical Interactions through Synthesis and Computation (RUBISCO) Scientific Focus Area (SFA).Discovered significant urban-rural difference in vegetation resilience to heat waves via statistical analysis of remote sensing imagery and identified the main underlying drivers via explanatory machine learning.Improving the carbon cycle modeling in a land surface model (E3SM Land Model, in Fortran) via the addition of new functionalities and modules. Implemented and tested alternative machine learning methods to approximate the E3SM Land Model, as part of the process of performing rapid Bayesian inversion for parameter calibration (https://github.com/ypwong22/OLMT).Incorporated soil moisture assessment capabilities into a climate model performance benchmarking package (https://github.com/ypwong22/ILAMB).

Knoxville, Tennessee Area

Faculty of record for Applied Data Science (IE 465/565), which introduced students to machine learning methods and their applications for engineering problems (https://github.com/ypwong22/IE465_jupyter_notebooks/).Instructed and provided oversight to a PhD colleague on setting up and running a hydrological model (CWatM, in Python), and on using principal component analysis to develop composite water scarcity indicators for the State of Tennessee.Designed novel procedure for correcting bias in the signal extracted by formal statistical detection and attribution analysis to demonstrate that human forcings had significant impacts on long-term soil moisture changes.Created a global, multi-depth, gap-free soil moisture dataset by developing a framework to merge a wide range of site-measured, remote sensing and modeled soil moisture data using multiple statistical methods. Applied Random Forest to create a soil moisture map for Texas by upscaling site-measured soil moisture data using soil properties, topography, vegetation indices, and weather.Co-organizer of a stakeholder meeting on sustainability and food-energy-water nexus issues in the U.S.-China soybean supply chainCo-lead in linking an optimization model to an integrated assessment model (Global Change Assessment Model, in C++) to inform business decision making in the U.S.-China soybean supply chain

Scraped power plant emissions data from the APIs of the U.S. and Taiwan Environmental Protection Agencies using the Python requests, sqlachemy, and geopandas packages, and archived data in a google cloud database.

Calibrated and performed simulations with the CWatM hydrological model in the Indus River Basin

Developed hourly electricity load forecast models for two transmission zones in the U.S. with improved definitions of heating and cooling degree days and segmented autoregressive-moving average regression. Demonstrated flaws in two popular statistical methods for downscaling precipitation by implementing and testing the methods on weather stations data and climate model outputs in the eastern U.S.Graded homework, held office hours, and provided some classroom teaching for the following classes:- CIVILEN 5130 Applied Hydrology- CIVILEN 3080 Economic Evaluation and Optimization in Civil and Environmental Engineering- CIVILEN 2060 Numerical Analysis Methods for Civil and Environmental Engineering Applications- CIVILEN 2050 Probabilistic Applications and Data Interpretation in Civil and Environmental Engineering

Quantified the future water scarcity risk to coal-fired power plants in developing Asia by connecting climate model projections, hydrological simulation outcomes, and an energy-and-heat balance model.

Doctor Of Philosophy - Phd

Bachelor'S Degree, Environmental Science