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Papers published or in press (Google Scholar Profile):

  1. Olsoy, P. J., J. J. Mitchell, N. F. Glenn, and A. N. Flores, Assessing a multi-platform data fusion technique spatiotemporal in capturing dynamics of heterogeneous dryland ecosystems in topographically complex terrain, Remote Sensing, accepted.
  2. Zhou, Q., A. N. Flores, N. F. Glenn, R. D. Walters, and B. Han (2017), A machine learning approach to estimation of downward solar radiation from satellite-derived data products: an application over a semi-arid ecosystem in the U.S., PLoS ONE, 12(8): e0180239, doi:10.1371/journal.pone.0180239. [PDF – A machine learning approach…]
  3. Han, B., S. G. Benner, J. P. Bolte, K. B. Vache, and A. N. Flores (2017), Coupling biophysical processes and water rights to simulate spatially distributed water use and water scarcity in an intensively managed hydrologic system, Hydrology and Earth System Sciences, 21, 3671-3685, doi:10.5194/hess-21-3671-2017. [PDF – Coupling biophysical processes and water rights…]
  4. Chance, E., K. M. Cobourn, V. Thomas, B. C. Dawson, and A. N. Flores (2017), Normalized Difference Moisture Index Method for Identifying Irrigated Areas in the Snake River Plain, Idaho, Remote Sensing, 9(6), 546; doi:10.3390/rs9060546. [PDF – Normalized Difference Moisture Index Method…]
  5. Tappa, D. J., M. J. Kohn, J. P. McNamara, S. G. Benner, S. G., A. N. Flores (2016), Isotopic composition of precipitation in a topographically steep, seasonally snow-dominated watershed and implications of variations from the global meteoric water line, Hydrol. Process., 30: 45824592. doi: 10.1002/hyp.10940. [PDF – Isotopic composition…]
  6. Evans, S. L., A. N. Flores, A. Heilig, M. J. Kohn, and H.-P Marshall (2016), Isotopic evidence for lateral flow and diffusive transport, but not sublimation, in a sloped seasonal snowpack, Idaho, USA, Geophysical Research Letters43, doi:10.1002/2015GL067605. [PDF – Isotopic evidence…]
  7. Kormos, P. R., J. P. McNamara, M. S. Seyfried, H.-P. Marshall, D. Marks, and A. N. Flores (2015), Bedrock infiltration estimates from a catchment water storage-based modeling approach in the rain snow transition zone, Journal of Hydrology, 525, 231-248, doi:10.1016/j.jhydrol.2015.03.032. [PDF – Bedrock infiltration estimates…]
  8. Lin, L.-F., A. M. Ebtehaj, R. L. Bras, A. N. Flores, and J. Wang (2015), Dynamical downscaling of GPM precipitation observations for hydrologic applications via WRF 4D-Var assimilation of precipitation, Journal of Hydrometeorology, 16(2), 811-829, doi:10.1175/JHM-D-14-0042.1. [PDF – Dynamical downscaling…]
  9. Walters, R. D., K. A. Watson, H.-P. Marshall, J. P. McNamara, and A. N. Flores (2015), A physiographic approach to downscaling fractional snow cover data in mountainous regions, Remote Sensing of Environment, 152, 413-425, doi:10.1016/j.rse.2014.07.001. [PDF – A physiographic approach…]
  10. Kormos, P. R., D. Marks, J. P. McNamara, H.-P. Marshall, A. Winstral, and A. N. Flores (2014), Snow distribution, melt and surface water inputs to the soil in the mountain rain-snow transition zoneJ. of Hydrol., 519(A), 190-204, doi:10.1016/j.jhydrol.2014.06.051. [PDF – Snow distribution…]
  11. Anderson, B. T.J. P. McNamaraH.-P. Marshall, and A. N. Flores (2014), Insights into the physical processes controlling correlations between snow distribution and terrain properties, Water Resour. Res.50, doi:10.1002/2013WR013714. [PDF – Insights into the physical processes…]
  12. Flores, A. N., D. Entekhabi, and R. L. Bras (2014),  Application of a hillslope-scale soil moisture data assimilation system to military trafficability assessmentJ.  Terramechanics, 51, 53-66, doi: 10.1016/j.jterra.2013.11.004. [PDF – Application of hillslope-scale data assimilation to military trafficability…]
  13. Johnson, B., B. Malama, W. Barrash, and A. N. Flores (2013), Recognizing and modeling variable drawdown due to evapotranspiration in a semiarid riparian zone considering local differences in vegetation and distance from a river sourceWater Resour. Res., 49, doi:10.1002/wrcr.20122. [PDF – Application of a hillslope-scale…]
  14. Stanaway, D., R. Haggerty, S. G. Benner, A. N. Flores, and K. Feris (2012), Persistent metal contamination limits lotic ecosystem heterotrophic metabolism after more than 100 years of exposure: a novel application of the Resazurin Resorufin Smart TracerEnvironmental Science & Technology, 46 (18), pp 9862–9871, doi: 10.1021/es3015666. [PDF – Persistent metal contamination…]
  15. Flores, A. N., R. L. Bras, and D. Entekhabi (2012), Hydrologic data assimilation with a hillslope-scale resolving model and L-band radar observations: Synthetic experiments with the ensemble Kalman filterWater Resour. Res.48, W08509, doi:10.1029/2011WR011500. [PDF – Hydrologic data assimilation…]
  16. Poulos, M. J., J. L. Pierce, A. N. Flores, and S. G. Benner (2012), Hillslope asymmetry maps reveal widespread, multi-scale organizationGeophysical Research Letters39, L06406, doi:10.1029/2012GL051283. [PDF – Hillslope asymmetry maps…]
  17. Smith, T. J., J. P. McNamara, A. N. Flores, M. M. Gribb, P. S. Aishlin, and S. G. Benner (2011), Small soil storage capacity constrains upland benefits of winter snowpackHydrological Processes, 25(25), 3858-3865, doi:10.1002/hyp.8340. [PDF – Small soil storage capacity…]
  18. Kunkel, M. L.A. N. Flores, T. J. Smith, J. P. McNamara, and S. G. Benner (2011), A simplified approach for estimating soil carbon and nitrogen stocks in semi-arid complex terrainGeoderma, 165(1), 1-11, doi:10.1016/j.geoderma.2011.06.011. [PDF – A simplified approach…]
  19. Flores, A. N., D. Entekhabi, and R. L. Bras (2010), Reproducibility of soil moisture ensembles when representing soil parameter uncertainty and correlation using a Latin Hypercube-based approach, Water Resour. Res., 46, W04506, doi:10.1029/2009WR008155. [PDF – Reproducibility of soil moisture…]
  20. Flores, A. N., V. Y. Ivanov, D. Entekhabi, and R. L. Bras (2009), Impacts of hillslope-scale organization in topography, soil moisture, soil temperature, and vegetation on modeling surface microwave radiation emission, IEEE Trans. Geosci. Remote Sens., 47(8), 2557-2571. [PDF –
    Impacts of hillslope-scale organization…
  21. Flores, A. N., B. P. Bledsoe, C. O. Cuhaciyan, and E. E. Wohl (2006), Channel-reach morphology dependence on energy, scale, and hydroclimatic processes with implications for prediction using geospatial data, Water Resour. Res., 42, W06412, doi:10.1029/2005WR004226. [PDF – Channel-reach morphology dependence…]

In review:

  1. Lin, L.-F., A. M. Ebtehaj, A. N. Flores, S. Bastola, and R. L. Bras, Joint Variational Data Assimilation of Satellite Precipitation and Soil Moisture: A Case Study Using TRMM and SMOS Data, Monthly Weather Review, in review.
  2. Sadegh, M., A. AghaKouchak, and A. N. Flores, A Multi-Model Nonstationary Rainfall-Runoff Modeling Framework: Analysis and Toolbox, Environmental Modelling and Software, in review.
  3. McNamara, J. P., S. G. Benner, M. J. Poulos, D. Chandler, H.-P. Marshall, A. N. Flores, M. Seyfried, and N. F. Glenn, Form and function relationships revealed by long-term research in a semiarid mountain catchment, WIREs Water, in review.

Publications (non-peer reviewed):

  1. Flores, A. N., M. Durand, S. Steele-Dunne, and B. F. Zaitchik (2011), Platforms for change: The increasing importance of sustained satellite observation for global hydrologic change monitoring, AGU Hydrology Section Newsletter, July 2011, 29-32.
  2. Flores, A.N., D. Entekhabi, and R. L. Bras (2010), A data assimilation approach for the prediction of soil moisture at tactical scales fusing multiple scale data sources and models, OP-010, Proceedings of the 27th Army Science Conference, 29 November-2 December 2010, Orlando, FL.
  3. Flores, A. N., V. Y. Ivanov, D. Entekhabi, and R. L. Bras (2008), Hillslope-scale controls on remote sensing of soil moisture with microwave radiometry, Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International, vol.2, no., pp. II-695-II-698, 7-11 July 2008, doi: 10.1109/IGARSS.2008.4779088.
  4. Flores A. N., E. Istanbulluoglu, R.L. Bras, and D. Entekhabi (2004). A framework for the prediction of soil moisture, Proceedings of the 24th Army Science Conference, 29 November -2 December 2004, Orlando FL.

Conference Papers and Presentations

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