Gautam Bisht

Publications

In review
  • Liao, C., Zhou, T., Xu, D., Tan, Z., Bisht, G., Cooper, M., Engwirda, D., Li, H., and Leung, L. R., Topological relationship-based flow direction modeling stream burning and depression filling, in review, 2022.
2023
  • Sinha, E., Bond-Lamberty, B., Calvin, K. V., Drewniak, B. A., Bisht, G., Bernacchi, C., Blakely, B. J., and Moore, C. E., The Impact of Crop Rotation and Spatially Varying Crop Parameters in the E3SM Land Model (ELMv2), Journal of Geophysical Research: Biogeosciences, e2022JG007187, https://doi.org/10.1029/2022JG007187, 2023.
  • Hao, D., Bisht, G., Rittger, K., Stillinger, T., Bair, E., Gu, Y., and Leung, L. R.: Evaluation of E3SM land model snow simulations over the western United States, The Cryosphere, 17, 673–697, https://doi.org/10.5194/tc-17-673-2023, 2023.
  • Hao, D., Bisht, G., Rittger, K., Bair, E., He, C., Huang, H., Dang, C., Stillinger, T., Gu, Y., Wang, H., Qian, Y., and Leung, L. R.: Improving snow albedo modeling in the E3SM land model (version 2.0) and assessing its impacts on snow and surface fluxes over the Tibetan Plateau, Geosci. Model Dev., 16, 75–94, https://doi.org/10.5194/gmd-16-75-2023, 2023.
2022
  • Golaz, J.-C., Van Roekel, L. P., Zheng, X., Roberts, A. F., Wolfe, J. D., Lin, W., et al. (2022). The DOE E3SM Model version 2: Overview of the physical model and initial model evaluation. Journal of Advances in Modeling Earth Systems, 14, e2022MS003156. https://doi.org/10.1029/2022MS003156
  • Feng, D., Tan, Z., Engwirda, D., Liao, C., Xu, D., Bisht, G., Zhou, T., Li, H.-Y., and Leung, L. R.: Investigating coastal backwater effects and flooding in the coastal zone using a global river transport model on an unstructured mesh, Hydrol. Earth Syst. Sci., 26, 5473–5491, https://doi.org/10.5194/hess-26-5473-2022, 2022.
  • Fang, Y., Leung, L. R., Koven, C. D., Bisht, G., Detto, M., Cheng, Y., McDowell, N., Muller-Landau, H., Wright, S. J., and Chambers, J. Q.: Modeling the topographic influence on aboveground biomass using a coupled model of hillslope hydrology and ecosystem dynamics, Geosci. Model Dev., 15, 7879–7901, https://doi.org/10.5194/gmd-15-7879-2022, 2022
  • Huang, M., Ma, P.-L., Chaney, N. W., Hao, D., Bisht, G., Fowler, M. D., Larson, V. E., and Leung, L. R.: Representing surface heterogeneity in land–atmosphere coupling in E3SMv1 single-column model over ARM SGP during summertime, Geosci. Model Dev., 15, 6371–6384, https://doi.org/10.5194/gmd-15-6371-2022, 2022.
  • Xu, D., Bisht, G., Zhou, T., Leung, L. R., & Pan, M. (2022). Development of Land‐River Two‐Way Hydrologic Coupling for Floodplain Inundation in the Energy Exascale Earth System Model. Journal of Advances in Modeling Earth Systems, e2021MS002772, https://doi.org/10.1029/2021MS002772.
  • Li, L., Bisht, G., and Leung, L. R.: Spatial heterogeneity effects on land surface modeling of water and energy partitioning, Geosci. Model Dev., 15, 5489–5510, https://doi.org/10.5194/gmd-15-5489-2022, 2022
  • Xu, D., Bisht, G., Sargsyan, K., Liao, C., and Leung, L. R.: Using a surrogate-assisted Bayesian framework to calibrate the runoff-generation scheme in the Energy Exascale Earth System Model (E3SM) v1, Geosci. Model Dev., 15, 5021–5043, https://doi.org/10.5194/gmd-15-5021-2022, 2022
  • Cheng, Y., Leung, L.R., Huang, M., Koven, C., Detto, M., Knox, R., Bisht, G., Bretfeld, M. and Fisher, R.A., 2022. Modeling the joint effects of vegetation characteristics and soil properties on ecosystem dynamics in a Panama tropical forest. Journal of Advances in Modeling Earth Systems, 14(1), p.e2021MS002603. https://doi.org/10.1029/2021MS002603
  • Hao, D., Bisht, G., Huang, M., Ma, P.L., Tesfa, T., Lee, W.L., Gu, Y. and Leung, L.R., 2022. Impacts of sub‐grid topographic representations on surface energy balance and boundary conditions in the E3SM Land Model: A case study in Sierra Nevada. Journal of Advances in Modeling Earth Systems, p.e2021MS002862. https://doi.org/10.1029/2021MS002862
  • Liao, C., Zhou, T., Xu, D., Barnes, R., Bisht, G., Li, H.Y., Tan, Z., Tesfa, T., Duan, Z., Engwirda, D. and Leung, L.R., 2022. Advances in hexagon mesh-based flow direction modeling. Advances in Water Resources, p.104099. https://doi.org/10.1016/j.advwatres.2021.104099
2021
  • Hao, D., Bisht, G., Gu, Y., Lee, W.L., Liou, K.N. and Leung, L.R., 2021. A parameterization of sub-grid topographical effects on solar radiation in the E3SM Land Model (version 1.0): implementation and evaluation over the Tibetan Plateau. Geoscientific Model Development, 14(10), pp.6273-6289. https://doi.org/10.5194/gmd-14-6273-2021
  • Ivanov, V.Y., Xu, D., Dwelle, M.C., Sargsyan, K., Wright, D.B., Katopodes, N., Kim, J., Tran, V.N., Warnock, A., Fatichi, S., Burlando, P., Enrica Caporali, E., Restrepo, P., Sanders, B. F., Chaney, M. M., Nunes, A. M. B., Nardi, F., Vivoni, E. R., Istanbulluoglu, E., Bisht, G., and Bras, R. L. (2021). Breaking Down the Computational Barriers to Real‐Time Urban Flood Forecasting. Geophysical Research Letters, 48(20), e2021GL093585. https://doi.org/10.1029/2021GL093585
  • Agee, E., He, L., Bisht, G., Couvreur, V., Shahbaz, P., Meunier, F., Gough, C.M., Matheny, A.M., Bohrer, G. and Ivanov, V., 2021. Root lateral interactions drive water uptake patterns under water limitation. Advances in Water Resources, 151, p.103896. https://doi.org/10.1016/j.advwatres.2021.103896
  • Cheng, Y., Huang, M., Zhu, B., Bisht, G., Zhou, T., Liu, Y., Song, F. and He, X., 2021. Validation of the Community Land Model version 5 over the contiguous United States (CONUS) using in situ and remote sensing data sets. Journal of Geophysical Research: Atmospheres, 126(5), p.e2020JD033539. https://doi.org/10.1029/2020JD033539
  • Zhu, B., Huang, M., Cheng, Y., Xie, X., Liu, Y., Bisht, G. and Chen, X., 2021. Impact of Vegetation Physiology and Phenology on Watershed Hydrology in a Semiarid Watershed in the Pacific Northwest in a Changing Climate. Water Resources Research, 57(3), p.e2020WR028394. https://doi.org/10.1029/2020WR028394
  • Wu, R., Chen, X., Hammond, G., Bisht, G., Song, X., Huang, M., Niu, G.Y. and Ferre, T., 2021. Coupling surface flow with high-performance subsurface reactive flow and transport code PFLOTRAN. Environmental Modelling & Software, 137, p.104959. https://doi.org/10.1016/j.envsoft.2021.104959
2020
  • Zhu, B., Huang, M., Cheng, Y., Xie, X., Liu, Y., Zhang, X., Bisht, G., Chen, X., Missik, J. and Liu, H., 2020. Effects of irrigation on water, carbon, and nitrogen budgets in a semiarid watershed in the Pacific northwest: A modeling study. Journal of Advances in Modeling Earth Systems, 12(9), p.e2019MS001953. https://doi.org/10.1029/2019MS001953
  • Burrows, S. M., Maltrud, M., Yang, X., Zhu, Q., Jeffery, N., Shi, X., ... & Leung, L. R. (2020). The DOE E3SM v1. 1 biogeochemistry configuration: Description and simulated ecosystem‐climate responses to historical changes in forcing. Journal of Advances in Modeling Earth Systems, 12(9), e2019MS001766.  https://doi.org/10.1029/2019MS001766
2019
  • Lawrence, D. M., Fisher, R. A., Koven, C. D., Oleson, K. W., Swenson, S. C., Bonan, G., ... & Zeng, X. (2019). The Community Land Model version 5: Description of new features, benchmarking, and impact of forcing uncertainty. Journal of Advances in Modeling Earth Systems, 11(12), 4245-4287. https://doi.org/10.1029/2018MS001583
  • Cai, X., Riley, W.J., Zhu, Q., Tang, J., Zeng, Z., Bisht, G. and Randerson, J.T., 2019. Improving representation of deforestation effects on evapotranspiration in the E3SM land model. Journal of Advances in Modeling Earth Systems, 11(8), pp.2412-2427. https://doi.org/10.1029/2018MS001551
  • Zhu, Q., Riley, W.J., Tang, J., Collier, N., Hoffman, F.M., Yang, X. and Bisht, G., 2019. Representing nitrogen, phosphorus, and carbon interactions in the E3SM land model: Development and global benchmarking. Journal of Advances in Modeling Earth Systems, 11(7), pp.2238-2258. https://doi.org/10.1029/2018MS001571
  • Bisht, G. and Riley, W.J., 2019. Development and verification of a numerical library for solving global terrestrial multiphysics problems. Journal of Advances in Modeling Earth Systems, 11(6), pp.1516-1542. https://doi.org/10.1029/2018MS001560
  • Golaz, J. C., Caldwell, P. M., Van Roekel, L. P., Petersen, M. R., Tang, Q., Wolfe, J. D., ... & Zhu, Q. (2019). The DOE E3SM coupled model version 1: Overview and evaluation at standard resolution. Journal of Advances in Modeling Earth Systems, 11(7), 2089-2129. https://doi.org/10.1029/2018MS001603
2018
  • Bisht, G., Riley, W.J., Hammond, G.E. and Lorenzetti, D.M., 2018. Development and evaluation of a variably saturated flow model in the global E3SM Land Model (ELM) version 1.0. Geoscientific Model Development, 11(10), pp.4085-4102. https://doi.org/10.5194/gmd-11-4085-2018
  • Tran, A.P., Dafflon, B., Bisht, G. and Hubbard, S.S., 2018. Spatial and temporal variations of thaw layer thickness and its controlling factors identified using time-lapse electrical resistivity tomography and hydro-thermal modeling. Journal of Hydrology, 561, pp.751-763. https://doi.org/10.1016/j.jhydrol.2018.04.028
  • Bisht, G., Riley, W.J., Wainwright, H.M., Dafflon, B., Yuan, F. and Romanovsky, V.E., 2018. Impacts of microtopographic snow redistribution and lateral subsurface processes on hydrologic and thermal states in an Arctic polygonal ground ecosystem: a case study using ELM-3D v1. 0. Geoscientific Model Development, 11(1), pp.61-76. https://doi.org/10.5194/gmd-11-61-2018
2017
  • Bisht, G., Huang, M., Zhou, T., Chen, X., Dai, H., Hammond, G.E., Riley, W.J., Downs, J.L., Liu, Y. and Zachara, J.M., 2017. Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream–aquifer–land interactions (CP v1. 0). Geoscientific Model Development, 10(12), pp.4539-4562. https://doi.org/10.5194/gmd-10-4539-2017
  • Dwivedi, D., Steefel, I.C., Arora, B. and Bisht, G., 2017. Impact of intra-meander hyporheic flow on nitrogen cycling. Procedia Earth and Planetary Science, 17, pp.404-407. https://doi.org/10.1016/j.proeps.2016.12.102
2016
  • Liu, Y., Bisht, G., Subin, Z.M., Riley, W.J. and Pau, G.S.H., 2016. A hybrid reduced-order model of fine-resolution hydrologic simulations at a polygonal tundra site. Vadose Zone Journal, 15(2). https://doi.org/10.2136/vzj2015.05.0068
  • Kumar, J., Collier, N., Bisht, G., Mills, R.T., Thornton, P.E., Iversen, C.M. and Romanovsky, V., 2016. Modeling the spatiotemporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape. The Cryosphere, 10(5), pp.2241-2274. https://doi.org/10.5194/tc-10-2241-2016
  • Tang, G., Yuan, F., Bisht, G., Hammond, G.E., Lichtner, P.C., Kumar, J., Mills, R.T., Xu, X., Andre, B., Hoffman, F.M. and Painter, S.L., 2016. Addressing numerical challenges in introducing a reactive transport code into a land surface model: a biogeochemical modeling proof-of-concept with CLM–PFLOTRAN 1.0. Geoscientific Model Development, 9(3), pp.927-946. https://doi.org/10.5194/gmd-9-927-2016
2015
  • Shi, X., Thornton, P.E., Ricciuto, D.M., Hanson, P.J., Mao, J., Sebestyen, S.D., Griffiths, N.A. and Bisht, G., 2015. Representing northern peatland microtopography and hydrology within the Community Land Model. Biogeosciences, 12(21), pp.6463-6477. https://doi.org/10.5194/bg-12-6463-2015
2014
  • Pau, G.S.H., Bisht, G. and Riley, W.J., 2014. A reduced-order modeling approach to represent subgrid-scale hydrological dynamics for land-surface simulations: application in a polygonal tundra landscape. Geoscientific Model Development, 7(5), pp.2091-2105. https://doi.org/10.5194/gmd-7-2091-2014
2011
  • Bisht, G. and Bras, R.L., 2011. Estimation of net radiation from the Moderate Resolution Imaging Spectroradiometer over the continental United States. IEEE Transactions on Geoscience and Remote Sensing, 49(6), pp.2448-2462. https://doi.org/10.1109/TGRS.2010.2096227
  • Knox, R., Bisht, G., Wang, J. and Bras, R., 2011. Precipitation variability over the forest-to-nonforest transition in southwestern Amazonia. Journal of Climate, 24(9), pp.2368-2377. https://doi.org/10.1175/2010JCLI3815.1
2010
  • Bisht, G. and Bras, R.L., 2010. Estimation of net radiation from the MODIS data under all sky conditions: Southern Great Plains case study. Remote Sensing of Environment, 114(7), pp.1522-1534. https://doi.org/10.1016/j.rse.2010.02.007
2009
  • Wang, J., Chagnon, F.J., Williams, E.R., Betts, A.K., Renno, N.O., Machado, L.A., Bisht, G., Knox, R. and Bras, R.L., 2009. Impact of deforestation in the Amazon basin on cloud climatology. Proceedings of the National Academy of Sciences, 106(10), pp.3670-3674. https://doi.org/10.1073/pnas.0810156106
2008
  • Vivoni, E.R., Rinehart, A.J., Méndez‐Barroso, L.A., Aragón, C.A., Bisht, G., Cardenas, M.B., Engle, E., Forman, B.A., Frisbee, M.D., Gutiérrez‐Jurado, H.A. and Hong, S.H., 2008. Vegetation controls on soil moisture distribution in the Valles Caldera, New Mexico, during the North American monsoon. Ecohydrology: Ecosystems, Land and Water Process Interactions, Ecohydrogeomorphology, 1(3), pp.225-238. https://doi.org/10.1002/eco.11
2006
  • Batra, N., Islam, S., Venturini, V., Bisht, G. and Jiang, L.E., 2006. Estimation and comparison of evapotranspiration from MODIS and AVHRR sensors for clear sky days over the Southern Great Plains. Remote Sensing of Environment, 103(1), pp.1-15. ttps://doi.org/10.1016/j.rse.2006.02.019
2005
  • Bisht, G., Venturini, V., Islam, S. and Jiang, L.E., 2005. Estimation of the net radiation using MODIS (Moderate Resolution Imaging Spectroradiometer) data for clear sky days. Remote sensing of environment, 97(1), pp.52-67. https://doi.org/10.1016/j.rse.2005.03.014
2004
  • Venturini, V., Bisht, G., Islam, S. and Jiang, L., 2004. Comparison of evaporative fractions estimated from AVHRR and MODIS sensors over South Florida. Remote Sensing of Environment, 93(1-2), pp.77-86. https://doi.org/10.1016/j.rse.2004.06.020
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