Publications
2024
Chen, H., Niu, Q., McNamara, J. P., & Flores, A. N. (2024). Influence of subsurface critical zone structure on hydrological partitioning in mountainous headwater catchments. Geophysical Research Letters, 51(6). https://doi.org/10.1029/2023gl106964
Jarecke, K. M., Zhang, X., Keen, R. M., Dumont, M., Li, B., Sadayappan, K., Moreno, V., Ajami, H., Billings, S. A., & Flores, A. N. (2024). Woody Encroachment Modifies Subsurface Structure and Hydrological Function. Ecohydrology, e2731. https://doi.org/10.1002/eco.2731
Mach, K. J., Jagannathan, K., Shi, L., Turek-Hankins, L. L., Arnold, J. R., Brelsford, C., Flores, A. N., Gao, J., Martín, C. E., McCollum, D. L., Moss, R., Niemann, J., Rashleigh, B., & Reed, P. M. (2024). Research to confront climate change complexity: Intersectionality, integration, and innovative governance. Earth’s Future, 12(6), 1–17. https://doi.org/10.1029/2023ef004392
Ragab, D., Kaiser, K. E., Niu, Q., Attwa, M., & Flores, A. N. (2024). A case study of canal seepage quantification using gain/loss method and electrical resistivity tomography in an intensively managed water resource system in the Treasure Valley, Idaho, United States. Journal of Hydrology, 645, 132251. https://doi.org/10.1016/j.jhydrol.2024.132251
Rudisill, W. J., Flores, A. N., Marshall, H. P., Siirila-Woodburn, E., Feldman, D. R., Rhoades, A. M., Xu, Z., & Morales, A. (2024). Cold-Season Precipitation Sensitivity to Microphysical Parameterizations: Hydrologic Evaluations Leveraging Snow Lidar Datasets. Journal of Hydrometeorology, 1(aop). https://doi.org/10.1175/JHM-D-22-0217.1
2023
Feldman, D. R., Aiken, A. C., Boos, W. R., Carroll, R. W. H., Chandrasekar, V., Collis, S., Creamean, J. M., de Boer, G., Deems, J., DeMott, P. J., Fan, J., Flores, A. N., Gochis, D., Grover, M., Hill, T. C. J., Hodshire, A., Hulm, E., Hume, C. C., Jackson, R., … Xu, Z. (2023). The Surface Atmosphere Integrated Field Laboratory (SAIL) Campaign. Bulletin of the American Meteorological Society, 1(aop). https://doi.org/10.1175/BAMS-D-22-0049.1
Duro, A. M., Hirmas, D., Ajami, H., Billings, S. A., Zhang, X., Li, L., Flores, A., Moreno, V., Cao, X., Guilinger, J., Oleghe, E., Giménez, D., Gray, A., & Sullivan, P. L. (2023). Topographic correction of visible near‐infrared reflectance spectra for horizon‐scale soil organic carbon mapping. Soil Science Society of America Journal. https://doi.org/10.1002/saj2.20612
Koop, A. N., Hirmas, D. R., Billings, S. A., Li, L., Cueva, A., Ajami, H., Flores, A., et al. (2023). Is macroporosity controlled by complexed clay and soil organic carbon? Geoderma. https://www.sciencedirect.com/science/article/pii/S0016706123002422
Rudisill, W., Flores, A., & Carroll, R. (2023). Evaluating 3 decades of precipitation in the Upper Colorado River basin from a high-resolution regional climate model. Geoscientific Model Development, 16(22), 6531–6552. https://doi.org/10.5194/gmd-16-6531-2023
National Academies of Sciences, Engineering, and Medicine, Division on Earth and Life Studies, Water Science and Technology Board, & Committee on the Future of Water Quality in Coeur d’Alene Lake. (2023). The future of water quality in Coeur d’Alene lake. National Academies Press. https://doi.org/10.17226/26620 (A.N. Flores, contributing author)
2022
CUAHSI Board of Directors & Officers. (2022). COVID‐19 Impacts Highlight the Need for Holistic Evaluation of Research in the Hydrologic Sciences. Water Resources Research, 58(2), e2021WR030930. https://doi.org/10.1029/2021WR030930 (A.N. Flores, contributing author)
Hauser, E., Sullivan, P. L., Flores, A. N., Hirmas, D., & Billings, S. A. (2022). Global‐scale shifts in rooting depths due to anthropocene land cover changes pose unexamined consequences for critical zone functioning. Earth’s Future, 10(11). https://doi.org/10.1029/2022ef002897
Pereira, C. O., Escanilla-Minchel, R., González, A. C., Alcayaga, H., Aguayo, M., Arias, M. A., & Flores, A. N. (2022). Assessment of Future Land Use/Land Cover Scenarios on the Hydrology of a Coastal Basin in South-Central Chile. Sustainability: Science Practice and Policy, 14(24), 16363. https://doi.org/10.3390/su142416363
Rudisill, W., Kaiser, K. E., & Flores, A. N. (2022). Evaluating long‐term One‐Way Atmosphere‐Hydrology simulations and the impacts of Two‐Way coupling in four mountain watersheds. Hydrological Processes, 36(5). https://doi.org/10.1002/hyp.14578
Sullivan, P. L., Billings, S. A., Hirmas, D., Li, L., Zhang, X., Ziegler, S., Murenbeeld, K., Ajami, H., Guthrie, A., Singha, K., Giménez, D., Duro, A., Moreno, V., Flores, A., Cueva, A., Koop, Aronson, E. L., Barnard, H. R., Banwart, S. A., … Wen, H. (2022). Embracing the dynamic nature of soil structure: A paradigm illuminating the role of life in critical zones of the Anthropocene. Earth-Science Reviews, 225, 103873. https://doi.org/10.1016/j.earscirev.2021.103873
Wen, H., Sullivan, P. L., Billings, S. A., Ajami, H., Flores, A.N., et al. (2022). From soils to streams: Connecting terrestrial carbon transformation, chemical weathering, and solute export across hydrological regimes. Water Resources Research. https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2022WR032314
2021
Dashti, H., Pandit, K., Glenn, N. F., Shinneman, D. J., Flerchinger, G. N., Hudak, A. T., de Graaf, M. A., Flores, A., Ustin, S., & Ilangakoon, N. (2021). Performance of the ecosystem demography model (EDv2. 2) in simulating gross primary production capacity and activity in a dryland study area. Agricultural and Forest Meteorology, 297, 108270. https://doi.org/10.1016/j.agrformet.2020.108270
Feldman, D., Aiken, A., Boos, W., Carroll, R., Chandrasekar, V., Collins, W., Collis, S., Deems, J., DeMott, P., Fan, J., Flores, A., et al. (2021). Surface atmosphere integrated field laboratory (SAIL) science plan. Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). ARM. https://www.arm.gov/publications/programdocs/doe-sc-arm-21-004.pdf
Pandit, K., Dashti, H., Hudak, A. T., Glenn, N. F., Flores, A. N., & Shinneman, D. J. (2021). Understanding the effect of fire on vegetation composition and gross primary production in a semi-arid shrubland ecosystem using the Ecosystem Demography (EDv2. 2) model. Biogeosciences, 18(6), 2027–2045. https://doi.org/10.5194/bg-18-2027-2021
Poulos, M. J., Smith, T. J., Benner, S. G., Pierce, J. L., Flores, A. N., Seyfried, M. S., & McNamara, J. P. (2021). Topographically moderated soil water seasons impact vegetation dynamics in semiarid mountain catchments: Illustrations from the Dry Creek Experimental Watershed, Idaho, USA. Hydrological Processes, 35(12), e14421. https://doi.org/10.1002/hyp.14421
Rudisill, W., & Flores, A. (2021). The Impact of Initial Snow Conditions on the Numerical Weather Simulation of a Northern Rockies Atmospheric River. Journal of Hydrometeorology. https://journals.ametsoc.org/view/journals/hydr/22/1/jhm-d-20-0018.1.xml
2020
Kaiser, K. E., Flores, A. N., & Vernon, C. R. (2020). Janus: a Python package for agent-based modeling of land use and land cover change. Journal of Open Research Software, 8(PNNL-SA-148545). https://doi.org/10.5334/jors.306
Kaiser, K. E., Flores, A. N., & Hillis, V. (2020). Identifying emergent agent types and effective practices for portability, scalability, and intercomparison in water resource agent-based models. Environmental Modelling & Software, 127, 104671. https://doi.org/10.1016/j.envsoft.2020.104671
Ledford, S. H., Monteagudo, M. M., Flores, A. N., Glass, J. B., & Cobb, K. M. (2020). GeoGRExit: why geosciences programs are dropping the GRE. Eos, 101. https://doi.org/10.1029/2020EO145223
National Academies of Sciences, Life Studies, Board on Earth Sciences, Committee on Catalyzing Opportunities for Research in the Earth Sciences (CORES), & A Decadal Survey for NSF’s Division of Earth Sciences. (2020). A vision for NSF Earth sciences 2020-2030: Earth in time. National Academies Press. https://doi.org/10.17226/25761 (A.N. Flores, contributing author)
2019
Dashti, H., Glenn, N. F., Ustin, S., Mitchell, J. J., Qi, Y., Ilangakoon, N. T., Flores, A. N., Silván-Cárdenas, J. L., Zhao, K., & Spaete, L. P. (2019). Empirical methods for remote sensing of nitrogen in drylands may lead to unreliable interpretation of ecosystem function. IEEE Transactions on Geoscience and Remote Sensing, 57(6), 3993–4004. https://doi.org/10.1109/TGRS.2018.2889318
Dashti, H., Poley, A., F. Glenn, N., Ilangakoon, N., Spaete, L., Roberts, D., Enterkine, J., N. Flores, A., L. Ustin, S., & J. Mitchell, J. (2019). Regional scale dryland vegetation classification with an integrated lidar-hyperspectral approach. Remote Sensing, 11(18), 2141. https://doi.org/10.3390/rs11182141
Fan, Y., Clark, M., Lawrence, D. M., Swenson, S., Band, L. E., Brantley, S. L., Brooks, P. D., Dietrich, W. E., Flores, A., Grant, G., Kirchner, J. W., Mackay, D. S., McDonnell, J. J., Milly, P. C. D., Sullivan, P. L., Tague, C., Ajami, H., Chaney, N., Hartmann, A., … Yamazaki, D. (2019). Hillslope hydrology in global change research and earth system modeling. Water Resources Research, 55(2), 1737–1772. https://doi.org/10.1029/2018wr023903
Han, B., Benner, S. G., & Flores, A. N. (2019). Including Variability across Climate Change Projections in Assessing Impacts on Water Resources in an Intensively Managed Landscape. Water, 11(2), 286. https://doi.org/10.3390/w11020286
Havens, S., Marks, D., FitzGerald, K., Masarik, M., Flores, A.N., Kormos, P. & Hedrick, A. (2019). Approximating input data to a snowmelt model using weather research and forecasting model outputs in lieu of meteorological measurements. Journal Of. https://journals.ametsoc.org/view/journals/hydr/20/5/jhm-d-18-0146_1.xml
Pandit, K., Dashti, H., Glenn, N. F., Flores, A. N., Maguire, K. C., Shinneman, D. J., Flerchinger, G. N., & Fellows, A. W. (2019). Developing and optimizing shrub parameters representing sagebrush (Artemisia spp.) ecosystems in the northern Great Basin using the Ecosystem Demography (EDv2. 2) model. Geoscientific Model Development, 12(11), 4585–4601. https://gmd.copernicus.org/articles/12/4585/2019/
Sadegh, M., AghaKouchak, A., Flores, A., Mallakpour, I., & Nikoo, M. R. (2019). A multi-model nonstationary rainfall-runoff modeling framework: analysis and toolbox. Water Resources Management, 33, 3011–3024. https://doi.org/10.1007/s11269-019-02283-y
Weintraub, S. R., Flores, A. N., Wieder, W. R., Sihi, D., Cagnarini, C., Gonçalves, D. R. P., Young, M. H., Li, L., Olshansky, Y., & Baatz, R. (2019). Leveraging environmental research and observation networks to advance soil carbon science. Journal of Geophysical Research. Biogeosciences, 124(5), 1047–1055. https://doi.org/10.1029/2018JG004956
Zhou, Q., Fellows, A., Flerchinger, G. N., & Flores, A. N. (2019). Examining interactions between and among predictors of net ecosystem exchange: A machine learning approach in a semi-arid landscape. Scientific Reports, 9(1), 2222. https://doi.org/10.1038/s41598-019-38639-y
2018
Baatz, R., Sullivan, P. L., Li, L., Weintraub, S. R., Loescher, H. W., Mirtl, M., Groffman, P. M., Wall, D. H., Young, M., White, T., Wen, H., Zacharias, S., Kühn, I., Tang, J., Gaillardet, J., Braud, I., Flores, A. N., Kumar, P., Lin, H., Ghezzehei, T., Jones, J., Gholz, H. L., Vereecken, H., & van Looy, K. (2018). Steering operational synergies in terrestrial observation networks: Opportunity for advancing Earth system dynamics modelling. Earth System Dynamics, 9(2), 593–609. https://doi.org/10.5194/esd-9-593-2018
McNamara, J. P., Benner, S. G., Poulos, M. J., Pierce, J. L., Chandler, D. G., Kormos, P. R., Marshall, H.-P., Flores, A. N., Seyfried, M., Glenn, N. F., & Aishlin, P. (2018). Form and function relationships revealed by long‐term research in a semiarid mountain catchment. WIREs. Water, 5(2), e1267. https://doi.org/10.1002/wat2.1267
Steimke, A. L., Han, B., Brandt, J. S., & Flores, A. N. (2018). Climate change and curtailment: Evaluating water management practices in the context of changing runoff regimes in a snowmelt-dominated basin. Water, 10(10), 1490. https://doi.org/10.3390/w10101490
2017
Chance, E. W., Cobourn, K. M., Thomas, V. A., Dawson, B. C., & Flores, A. N. (2017). Identifying irrigated areas in the Snake River Plain, Idaho: Evaluating performance across compositing algorithms, spectral indices, and sensors. Remote Sensing, 9(6), 546. https://doi.org/10.3390/rs9060546
Han, B., Benner, S. G., Bolte, J. P., Vache, K. B., & Flores, A. N. (2017). Coupling biophysical processes and water rights to simulate spatially distributed water use in an intensively managed hydrologic system. Hydrology and Earth System Sciences, 21(7), 3671–3685. https://doi.org/10.5194/hess-21-3671-2017
Lin, L.-F., Ebtehaj, A. M., Flores, A. N., Bastola, S., & Bras, R. L. (2017). Combined assimilation of satellite precipitation and soil moisture: A case study using TRMM and SMOS data. Monthly Weather Review, 145(12), 4997–5014. https://doi.org/10.1175/MWR-D-17-0125.1
Olsoy, P. J., Mitchell, J., Glenn, N. F., & Flores, A. N. (2017). Assessing a multi-platform data fusion technique in capturing spatiotemporal dynamics of heterogeneous dryland ecosystems in topographically complex terrain. Remote Sensing, 9(10), 981. https://doi.org/10.3390/rs9100981
Zhou, Q., Flores, A., Glenn, N. F., Walters, R., & Han, B. (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 US. PloS One, 12(8), e0180239. https://doi.org/10.1371/journal.pone.0180239
2016
Evans, S. L., Flores, A. N., Heilig, A., Kohn, M. J., Marshall, H., & McNamara, J. P. (2016). Isotopic evidence for lateral flow and diffusive transport, but not sublimation, in a sloped seasonal snowpack, Idaho, USA. Geophysical Research Letters, 43(7), 3298–3306. https://doi.org/10.1002/2015GL067605
Tappa, D. J., Kohn, M. J., McNamara, J. P., Benner, S. G., & Flores, A. N. (2016). Isotopic composition of precipitation in a topographically steep, seasonally snow‐dominated watershed and implications of variations from the global meteoric water line. Hydrological Processes, 30(24), 4582–4592. https://doi.org/10.1002/hyp.10940
2015
Kormos, P. R., McNamara, J. P., Seyfried, M. S., Marshall, H. P., Marks, D., & Flores, A. N. (2015). Bedrock infiltration estimates from a catchment water storage-based modeling approach in the rain snow transition zone. Journal of Hydrology, 525, 231–248. https://doi.org/10.1016/j.jhydrol.2015.03.032
Lin, L.-F., Ebtehaj, A. M., Bras, R. L., Flores, A. N., & Wang, J. (2015). Dynamical precipitation downscaling for hydrologic applications using WRF 4D-Var data assimilation: Implications for GPM era. Journal of Hydrometeorology, 16(2), 811–829. https://doi.org/10.1175/JHM-D-14-0042.1
2014
Anderson, B. T., McNamara, J. P., Marshall, H.-P., & Flores, A. N. (2014). Insights into the physical processes controlling correlations between snow distribution and terrain properties. Water Resources Research, 50(6), 4545–4563. https://doi.org/10.1002/2013wr013714
Flores, A. N., Entekhabi, D., & Bras, R. L. (2014). Application of a hillslope-scale soil moisture data assimilation system to military trafficability assessment. Journal of Terramechanics, 51, 53–66. https://doi.org/10.1016/j.jterra.2013.11.004
Kormos, P. R., Marks, D., McNamara, J. P., Marshall, H. P., Winstral, A., & Flores, A. N. (2014). Snow distribution, melt and surface water inputs to the soil in the mountain rain–snow transition zone. Journal of Hydrology, 519, 190–204. https://doi.org/10.1016/j.jhydrol.2014.06.051
Walters, R. D., Watson, K. A., Marshall, H.-P., McNamara, J. P., & Flores, A. N. (2014). A physiographic approach to downscaling fractional snow cover data in mountainous regions. Remote Sensing of Environment, 152, 413–425. https://doi.org/10.1016/j.rse.2014.07.001
2006-2013
Johnson, B., Malama, B., Barrash, W., & Flores, A. N. (2013). Recognizing and modeling variable drawdown due to evapotranspiration in a semi‐arid riparian zone considering local differences in vegetation and distance from a river source. Water Resources Research, 49. https://doi.org/10.1002/wrcr.20122
Flores, A. N., Bras, R. L., & Entekhabi, D. (2012). Hydrologic data assimilation with a hillslope‐scale‐resolving model and L band radar observations: Synthetic experiments with the ensemble Kalman filter. Water Resources Research, 48(8). https://doi.org/10.1029/2011WR011500
Poulos, M. J., Pierce, J. L., & Flores, A. N. (2012). Hillslope asymmetry maps reveal widespread, multi‐scale organization. Geophysical Research Letters. https://doi.org/10.1029/2012GL051283
Stanaway, D., Haggerty, R., Benner, S., Flores, A., & Feris, K. (2012). Persistent metal contamination limits lotic ecosystem heterotrophic metabolism after more than 100 years of exposure: a novel application of the resazurin resorufin smart tracer. Environmental Science & Technology, 46(18), 9862–9871. https://doi.org/10.1021/es3015666
Kunkel, M. L., Flores, A. N., Smith, T. J., McNamara, J. P., & Benner, S. G. (2011). A simplified approach for estimating soil carbon and nitrogen stocks in semi-arid complex terrain. Geoderma, 165(1), 1–11. https://doi.org/10.1016/j.geoderma.2011.06.011
Smith, T. J., McNamara, J. P., Flores, A. N., Gribb, M. M., Aishlin, P. S., & Benner, S. G. (2011). Small soil storage capacity limits benefit of winter snowpack to upland vegetation. Hydrological Processes, 25(25), 3858–3865. https://doi.org/10.1002/hyp.8340
Flores, A. N., Entekhabi, D., & Bras, R. L. (2010). Reproducibility of soil moisture ensembles when representing soil parameter uncertainty using a Latin Hypercube–based approach with correlation control. Water Resources Research, 46(4). https://doi.org/10.1029/2009WR008155
Flores, A. N., Ivanov, V. Y., Entekhabi, D., & Bras, R. L. (2009). Impact of hillslope-scale organization of topography, soil moisture, soil temperature, and vegetation on modeling surface microwave radiation emission. IEEE Transactions on Geoscience and Remote Sensing, 47(8), 2557–2571. https://doi.org/10.1109/TGRS.2009.2014743
Flores, A. N., Bledsoe, B. P., Cuhaciyan, C. O., & Wohl, E. E. (2006). Channel‐reach morphology dependence on energy, scale, and hydroclimatic processes with implications for prediction using geospatial data. Water Resources Research, 42(6). https://doi.org/10.1029/2005WR004226