Grey S Nearing

Assistant Professor

  • gsnearing@ua.edu
  • (205) 348-6268
  • Bevill 1036

Education

BS, Purdue University, 2006

MS, University of Arizona, 2009

PhD, University of Arizona, 2013

Courses Taught

GEO 105

Curriculum Vitae

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Research Interests

My research focuses on large-scale hydrological modeling for flood forecasting, agricultural monitoring, and weather and climate forecasting. In particular, I am interested in model/data fusion, and how to use remote sensing and other types of hydrologic observations to improve hydrology models. This work largely relies on information-theoretic, machine learning, and data assimilation techniques. I am also interested in the application of emerging computational technologies for Earth Science applications.

Research Group Members

I am currently accepting applications for both PhD and MS candidates to work on developing and applying machine learning techniques for data assimilation, parameter estimation, and uncertainty quantification in agricultural and flood forecasting models.

Representative Publications

1. G.S. Nearing, S. Yatheendradas, W.T. Crow, D.D. Bosch, M.H. Cosh, D.C. Goodrich, P.J. Starks, M.S. Seyfried; Nonparametric Triple Collocation; Water Resources Research, May, 2017.
2. G.S. Nearing, Y. Tian, H.V. Gupta, M.P. Clark, S.V. Weijs, K.W. Harrison; A philosophical basis for hydrologic uncertainty. Hydrological Sciences Journal, Jul 2016.
3. G.S. Nearing, D.M. Mocko, C.D. Peters-Lidard, S.V. Kumar, Y. Xia; Benchmarking NLDAS-2 soil moisture and evapotranspiration to separate uncertainty contributions. Journal of Hydrometeorology, Mar 2016.
4. M.J. Best, et al.; The plumbing of land surface models. Journal of Hydrometeorology, Jun 2015.
5. G.S. Nearing, H.V. Gupta; The quantity and quality of information in hydrologic models. Water Resources Research, Jan 2015.
6. H.V. Gupta, G.S. Nearing; Debates on water resources: Using models and data to learn – a systems theoretic perspective on the future of hydrological science. Water Resources Research, Jun 2014.
7. G.S. Nearing, H.V. Gupta, W.T. Crow, W. Gong; An approach to quantifying the efficiency of a Bayesian filter. Water Resources Research, Apr 2013.
8. G.S. Nearing, M. Tuller, S.B. Jones, R. Heinse, M.S. Meding; Electromagnetic induction for mapping physical and chemical properties of mine tailings deposits. Journal of Applied Geophysics, Feb 2013.
9. G.S. Nearing, W.T. Crow, K.R. Thorp, M.S. Moran, R.R. Reichle, H.V. Gupta; Assimilating remote sensing observations of leaf area index and soil moisture for wheat yield estimates: an observing system simulation experiment. Water Resources Research, May 2012.
10. G.S. Nearing, M.S. Moran, R.L. Scott, G.E. Ponce-Campos; Coupling diffusion and maximum entropy models to estimate thermal inertia and soil moisture. Remote Sensing of Environment, Apr 2012.