The Reynolds Creek Critical Zone Observatory and Boise State University is excited to announce a position for a funded postdoctoral researcher to examine relationships between Critical Zone moisture fluxes and soil carbon storage and ecosystem fluxes using models and data. Primary research advisor and collaborator is Dr. Lejo Flores (Boise State University, Geosciences). The successful candidate with collaborate closely with colleagues to leverage extensive soil, monitoring, and geophysical datasets to constrain subsurface Critical Zone properties required by a physics-based integrated hydrologic model. The postdoc will also have the support of the Reynolds Creek CZO team (principally at Boise State University, Idaho State University, and the Agricultural Research Service), who have interdisciplinary expertise in hydrologic modeling, landscape ecology, biogeochemistry, and soils science. The researcher will focus on the science questions, conduct the activities, and have at their disposal the unique resources described below.
Overarching science questions:
- What is the strength and significance of any relationship between the lateral soil moisture fluxes and soil organic carbon storage and how does this relationship (or lack thereof) depend on geomorphic, soil, ecologic, and hydrologic processes and/or properties?
- To what extent is the timing, rate, and distribution of moisture input to the critical zone sensitive to a transition from snow- to rain-dominated precipitation input?
- To what extent are the magnitude and direction of lateral fluxes of moisture in the subsurface sensitive to climate variability, as captured in the historical data record?
- Parameterize, calibrate, and verify a spatially distributed, process-based integrated hydrologic model (ParFlow) to simulate the distribution and redistribution,
- Leverage rich, extant datasets characterizing the Reynolds Creek CZO to prepare model inputs and forcings,
- Design and conduct a suite of numerical experiments to calibrate and validate key variables of the integrated hydrologic model, particularly soil moisture, snow water equivalent, and,
- Leverage independent datasets and observations of the spatiotemporal dynamics of snow cover, soil organic carbon storage, and soil moisture to answer the posed science questions and test associated hypotheses.
- A 31 year, 10-m spatial, and 1-hr temporal resolution dataset of distributed air temperature, humidity, precipitation amount and precipitation phase from the Reynolds Creek CZO (http://scholarworks.boisestate.edu/reynoldscreek/1/)
- Geospatial soil organic carbon storage in Reynolds Creek CZO derived from field observations, hyperspectral, lidar and other geospatial data using machine learning methods (http://scholarworks.boisestate.edu/reynoldscreek/2/)
- Detailed soil grain size analyses in the soil profile from more than 30 sites within the Reynolds Creek CZO.
- Unique geophysical datasets capturing key Critical Zone processes that include airborne transient electromagnetic, time-lapse electrical resistance tomography, and ground-penetrating radar measurements.
- Continuous eddy flux observations of H2O, CO2, and temperature at four sites along an elevation gradient from 2014 to present.
- Continuous measurements of soil moisture and temperature
- Additional data from a number of process studies related to litterfall, soil inorganic
If interested, you should send a (1) letter of interest specifically identifying skills and prior experience that make you a compelling candidate, (2) your current CV with three professional references, and (3) one published or submitted manuscript that best illustrates your skills and expertise that are relevant to the position to Professor Alejandro Flores (firstname.lastname@example.org).
At a minimum you should have: The researcher should have a Ph.D. in an appropriate field (Geosciences, Hydrology, Civil and Environmental Engineering) at the time of appointed. Preferred skills include: (1) prior experience with integrated hydrologic models, (2) use of high-performance computing environments, and (3) demonstrated skills in scientific programming.
Salary and benefits: $48,000 per year, plus an excellent benefits package is available for eligible employees, for more information visit: http://hrs.boisestate.edu/careers/benefits/.
See the full job position for more details: https://leaf.boisestate.edu/critical-zone-modeling-postdoctoral-opportunity/