Welcome to Doug Baldwin’s personal website. Here, you will find examples of my past work during my Masters and PhD programs. I am currently wrapping up dissertation revisions after successfully defending last December.
Brief Research Statement
Mathematical models are used prolifically in the environmental sciences to simulate the behavior of real-world systems or predict future states of interest, such as ecosystem biomass or soil wetness. Controlled laboratory or field experiments inform the development of equations that make up these physically-based models. Applying these equations, or mechanisms, to accurately simulate natural processes in ‘real-world’ environments is challenging, since many of the assumptions that may be appropriate for laboratory settings do not hold in the complex, thermodynamically open Earth system.
Soil moisture is a state that ‘connects’ multiple earth system cycles, which include the water cycle, nutrient cycle, and the carbon cycle. Our understanding of these cycles is crucial for many aspects of our modern civilization, such as agricultural planning, natural disaster forecasting, resource management, drought adaptation, and stormwater control. Satellites can indirectly observe the amount of moisture in the first 0-2 cm of Earth’s surface across the world, but this depth is inadequate for most applications requiring plant water availability or soil water storage estimates. An accurate understanding of ‘root zone soil moisture’, or moisture content of the top 1 meter of soil, would greatly improve the performance of hydrologic and climate models. The behavior of root zone soil moisture can differ significantly from near-surface moisture, since it can be influenced by rising groundwater, impermeable soil layers, plant root water uptake, and lateral underground drainage from nearby hillslopes.
A major outcome of my research will be an operational model system that can estimate daily root zone soil moisture across broad (i.e., regional to continental) extents using a newly developed hydrologic model called the Soil Moisture Analytical Relationship (SMAR; see Manfreda et al, 2014), data assimilation techniques, and satellite soil moisture from NASA (see https://www.nasa.gov/smap for information about the new SMAP soil moisture product).
Reference: Manfreda, S., Brocca, L., Moramarco, T., Melone, F., and Sheffield, J., 2014. A physically based approach for the estimation of root-zone soil moisture from surface measurements. Hydrology and Earth System Sciences 18, 1199-1212. (link to journal article)