Guo-Yue Niu

Interests

Teaching

Niu's teaching interests are hydrometeorology, ecohydrology, physical climatology, and physical hydrology, etc.

Research

Hydrometeorology; ecohydrology; land surface modeling; distributed hydrological modeling; global and regional climate modeling; the role of plant and microbial processes in climate change; application of remote sensing to modeling, etc

Courses

Scholarly Contributions

Chapters

• Volkmann, T. H., Sengupta, A., Pangle, L. A., ... Niu, G. .., & Troch, P. A. (2018). Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution Observatory: Toward Prediction of Coupled Hydrological, Biogeochemical, and Ecological Change. In Hydrology of Artificial and Controlled Experiments(pp 25-74). doi:http://dx.doi.org/10.5772/intechopen.72325
• Troch, P. A., Zeng, X., Van Haren, J. L., Tuller, M., Sibayan, M., Schaap, M. G., Saleska, S. R., Ruiz, J., Rasmussen, C., Pohlmann, M. A., Pelletier, J. D., Monson, R. K., Maier, R. M., Kim, M., Huxman, T. E., Ferre, P. A., Durcik, M., DeLong, S. B., Cueva, A., , Chorover, J. D., et al. (2017). Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution Observatory: Toward Prediction of Coupled Hydrological, Biogeochemical, and Ecological Changes. In Hydrology of Artificial and Controlled Experiments. Rijeka, Croatia: IN TECH d.o.o.
• Niu, G. (2012). Earth System Model, Modeling the Land Component of. In Climate Change Modeling Methodology(pp 139-168). New York: Springer.

Journals/Publications

• Wang, W., He, C., Moore, J., Wang, G., & Niu, G. (2022). Physics-Based Narrowband Optical Parameters for Snow Albedo Simulation in Climate Models. Journal of Advances in Modeling Earth Systems, 14(1).
• Zhang, X., Jin, J., Zeng, X., Hawkins, C. P., Neto, A., & Niu, G. (2022). The Compensatory CO2 Fertilization and Stomatal Closure Effects on Runoff Projection From 2016–2099 in the Western United States. Water Resources Research, 58(1).
• Zhang, X., Xie, Z., Ma, Z., Barron-Gafford, G. A., Scott, R. L., & Niu, G. (2022). A Microbial-Explicit Soil Organic Carbon Decomposition Model (MESDM): Development and Testing at a Semiarid Grassland Site. Journal of Advances in Modeling Earth Systems, 14(1).
• Dwivedi, R., Eastoe, C., Knowles, J. F., Hamann, L., Meixner, T., “Ty”, F. P., Castro, C., Wright, W. E., Niu, G., Minor, R., Barron-Gafford, G. A., Abramson, N., Mitra, B., Papuga, S. A., Stanley, M., & Chorover, J. (2021). An improved practical approach for estimating catchment-scale response functions through wavelet analysis. Hydrological Processes, 35(3).
• Liu, J., Jin, J., & Niu, G. (2021). Effects of Irrigation on Seasonal and Annual Temperature and Precipitation over China Simulated by the WRF Model. Journal of Geophysical Research: Atmospheres, 126(10).
• Niu, G. (2021). Improved Runoff Simulations for a Highly Varying Soil Depth and Complex Terrain Watershed in the Loess Plateau with the Community Land Model. Geoscientific Model Development Discussions.
• Niu, G., Lai, J., Niu, G., & Sun, Y. (2021). Massive crop expansion threatens agriculture and water sustainability in Northwestern China. Environmental Research Letters.
• Wang, T., Wang, P., Wang, Z., Niu, G., Yu, J., Ma, N., Wu, Z., Pozdniakov, S. P., & Yan, D. (2021). Drought adaptability of phreatophytes: Insight from vertical root distribution in drylands of China. Journal of Plant Ecology, 14(6), 1128-1142.
• Wu, R., Chen, X., Hammond, G., Bisht, G., Song, X., Huang, M., Niu, G., & Ferre, T. (2021). Coupling surface flow with high-performance subsurface reactive flow and transport code PFLOTRAN. Environmental Modelling and Software, 137.
• Yuan, R., Chang, L., & Niu, G. (2021). Annual variations of T/ET in a semi-arid region: Implications of plant water use strategies. Journal of Hydrology, 603.
• Arevalo, J., Zeng, X., Durcik, M., Sibayan, M., Pangle, L., Abramson, N., Bugaj, A., Ng, W., Kim, M., Barron-Gafford, G. .., Haren, J., Niu, G., Adams, J., Ruiz, J., & Troch, P. A. (2020). Highly sampled measurements in a controlled atmosphere at the Biosphere 2 Landscape Evolution Observatory. Scientific Data, 7(1).
• Chang, L., Yuan, R., Gupta, H. V., Winter, C. L., & Niu, G. (2020). Why Is the Terrestrial Water Storage in Dryland Regions Declining? A Perspective Based on Gravity Recovery and Climate Experiment Satellite Observations and Noah Land Surface Model With Multiparameterization Schemes Model Simulations. Water Resources Research, 56(11).
• Dwivedi, R., Eastoe, C., Knowles, J. F., Wright, W. E., Hamann, L., Minor, R., Mitra, B., Meixner, T., McIntosh, J., Ty, F. P., Castro, C., Niu, G., Barron-Gafford, G. A., Abramson, N., Papuga, S. A., Stanley, M., Hu, J., & Chorover, J. (2020). Vegetation source water identification using isotopic and hydrometric observations from a subhumid mountain catchment. Ecohydrology, 13(1).
• Dwivedi, R., Knowles, J. F., Eastoe, C., Minor, R., Abramson, N., Mitra, B., Wright, W. E., McIntosh, J., Meixner, T., Ferre, P., Castro, C., Niu, G., Barron-Gafford, G. A., Stanley, M., & Chorover, J. (2020). Ubiquitous fractal scaling and filtering behavior of hydrologic fluxes and storages from a mountain headwater catchment. Water (Switzerland), 12(2).
• Niu, G., & Troch, P. (2020). Interactions between snow cover and evaporation lead to higher sensitivity of streamflow to temperature. Communications Earth & Environment, 1, 1-7.
• Niu, G., Fang, Y., Chang, L., Jin, J., Yuan, H., & Zeng, X. (2020). Enhancing the Noah-MP Ecosystem Response to Droughts With an Explicit Representation of Plant Water Storage Supplied by Dynamic Root Water Uptake. Journal of Advances in Modeling Earth Systems, 12(11).
• Tian, L., Jin, J., Wu, P., Niu, G., & Zhao, C. (2020). High-resolution simulations of mean and extreme precipitation with WRF for the soil-erosive Loess Plateau. Climate Dynamics, 54(7-8), 3489-3506.
• Dwivedi, R., Meixner, T., McIntosh, J. C., Ferré, P., Eastoe, C. J., Niu, G., Minor, R. L., Barron-Gafford, G. A., & Chorover, J. (2019). Hydrologic functioning of the deep critical zone and contributions to streamflow in a high-elevation catchment: Testing of multiple conceptual models. Hydrological Processes, 33(4), 476-494.
• Elshall, A. S., Ye, M., Niu, G., & Barron-Gafford, G. A. (2019). Bayesian inference and predictive performance of soil respiration models in the presence of model discrepancy. Geoscientific Model Development, 12(5), 2009-2032.
• Huo, X., Gupta, H., Niu, G., Gong, W., & Duan, Q. (2019). Parameter Sensitivity Analysis for Computationally Intensive Spatially Distributed Dynamical Environmental Systems Models. Journal of Advances in Modeling Earth Systems, 11(9), 2896-2909.
• Ma, X., Jin, J., Liu, J., & Niu, G. (2019). An improved vegetation emissivity scheme for land surface modeling and its impact on snow cover simulations. Climate Dynamics, 53(9-10), 6215-6226.
• Wang, Y., Broxton, P., Fang, Y., Behrangi, A., Barlage, M., Zeng, X., & Niu, G. (2019). A Wet-Bulb Temperature-Based Rain-Snow Partitioning Scheme Improves Snowpack Prediction Over the Drier Western United States. Geophysical Research Letters, 46(23), 13825-13835.
• Yuan, R., Chang, L., Gupta, H., & Niu, G. (2019). Climatic forcing for recent significant terrestrial drying and wetting. Advances in Water Resources, 133.
• Chang, L., Dwivedi, R., Knowles, J. F., Fang, Y., Niu, G., Pelletier, J. D., Rasmussen, C., Durcik, M., Barron-Gafford, G. A., & Meixner, T. (2018). Why Do Large-Scale Land Surface Models Produce a Low Ratio of Transpiration to Evapotranspiration?. Journal of Geophysical Research: Atmospheres, 123(17), 9109-9130.
• Elshall, A. S., Ye, M., Pei, Y., Zhang, F., Niu, G., & Barron-Gafford, G. A. (2018). Relative model score: a scoring rule for evaluating ensemble simulations with application to microbial soil respiration modeling. Stochastic Environmental Research and Risk Assessment, 32(10), 2809-2819.
• Heuvel, D. B., Troch, P. A., Booij, M. J., Niu, G., Volkmann, T., & Pangle, L. A. (2018). Effects of differential hillslope-scale water retention characteristics on rainfall–runoff response at the Landscape Evolution Observatory. Hydrological Processes, 32(13), 2118-2127.
• Pelletier, J. D., Barron-Gafford, G. A., Gutiérrez-Jurado, H., Hinckley, E., Istanbulluoglu, E., McGuire, L. A., Niu, G., Poulos, M. J., Rasmussen, C., Richardson, P., Swetnam, T. L., & Tucker, G. E. (2018). Which way do you lean? Using slope aspect variations to understand Critical Zone processes and feedbacks. Earth Surface Processes and Landforms, 43(5), 1133-1154.
• Tian, L., Jin, J., Wu, P., & Niu, G. (2018). Assessment of the effects of climate change on evapotranspiration with an improved elasticity method in a Nonhumid Area. Sustainability (Switzerland), 10(12).
• Tian, L., Jin, J., Wu, P., & Niu, G. (2018). Quantifying the impact of climate change and human activities on streamflow in a Semi-Arid Watershed with the Budyko Equation incorporating dynamic vegetation information. Water (Switzerland), 10(12).
• Wang, P., Niu, G., Fang, Y., Wu, R., Yu, J., Yuan, G., Pozdniakov, S. P., & Scott, R. L. (2018). Implementing Dynamic Root Optimization in Noah-MP for Simulating Phreatophytic Root Water Uptake. Water Resources Research, 54(3), 1560-1575.
• Fang, Y., Zhang, X., Corbari, C., Mancini, M., Niu, G., & Zeng, W. (2017). Improving the Xin'anjiang hydrological model based on mass-energy balance. Hydrology and Earth System Sciences, 21(7), 3359-3375.
• Fang, Y., Zhang, X., Niu, G., Zeng, W., Zhu, J., & Zhang, T. (2017). Study of the spatiotemporal characteristics of meltwater contribution to the total runoffin the Upper Changjiang River Basin. Water (Switzerland), 9(3).
• Ma, N., Niu, G., Xia, Y., Cai, X., Zhang, Y., Ma, Y., & Fang, Y. (2017). A Systematic Evaluation of Noah-MP in Simulating Land-Atmosphere Energy, Water, and Carbon Exchanges Over the Continental United States. Journal of Geophysical Research: Atmospheres, 122(22), 12,245-12,268.
• Brunke, M. A., Broxton, P., Pelletier, J., Gochis, D., Hazenberg, P., Lawrence, D. M., Leung, L. R., Niu, G., Troch, P. A., & Zeng, X. (2016). Implementing and evaluating variable soil thickness in the Community Land Model, version 4.5 (CLM4.5). Journal of Climate, 29(9), 3441-3461.
• Hazenberg, P., Broxton, P., Gochis, D., Niu, G., Pangle, L. A., Pelletier, J. D., Troch, P. A., & Zeng, X. (2016). Testing the hybrid-3-D hillslope hydrological model in a controlled environment. Water Resources Research, 52(2), 1089-1107.
• Ma, N., Szilagyi, J., Niu, G., Zhang, Y., Zhang, T., Wang, B., & Wu, Y. (2016). Evaporation variability of Nam Co Lake in the Tibetan Plateau and its role in recent rapid lake expansion. Journal of Hydrology, 537, 27-35.
• Pelletier, J. D., Broxton, P. D., Hazenberg, P., Zeng, X., Troch, P. A., Niu, G., Williams, Z., Brunke, M. A., & Gochis, D. (2016). A gridded global data set of soil, intact regolith, and sedimentary deposit thicknesses for regional and global land surface modeling. Journal of Advances in Modeling Earth Systems, 8(1), 41-65.
• Scudeler, C., Pangle, L., Pasetto, D., Niu, G., Volkmann, T., Paniconi, C., Putti, M., & Troch, P. (2016). Multiresponse modeling of variably saturated flow and isotope tracer transport for a hillslope experiment at the Landscape Evolution Observatory. Hydrology and Earth System Sciences, 20(10), 4061-4078.
• Barlage, M., Tewari, M., Chen, F., Miguez-Macho, G. .., Yang, Z., & Niu, G. (2015). The effect of groundwater interaction in North American regional climate simulations with WRF/Noah-MP. Climatic Change, 129(3-4), 485-498.
• Field, J. P., Breshears, D. D., Law, D. J., Villegas, J. C., Lopez-Hoffman, L. .., Brooks, P. D., Chorover, J., Barron-Gafford, G. A., Gallery, R. E., Litvak, M. E., Lybrand, R. A., McIntosh, J. C., Meixner, T., Niu, G., Papuga, S. A., Pelletier, J. D., Rasmussen, C. R., & Troch, P. A. (2015). Critical zone services: Expanding context, constraints, and currency beyond ecosystem services. Vadose Zone Journal, 14(1).
• Hazenberg, P., Fang, Y., Broxton, P., Gochis, D., Niu, G., Pelletier, J. D., Troch, P. A., & Zeng, X. (2015). A hybrid-3D hillslope hydrological model for use in Earth system models. Water Resources Research, 51(10), 8218-8239.
• Pangle, L. A., DeLong, S. B., Abramson, N., Adams, J., Barron-Gafford, G. A., Breshears, D. D., Brooks, P. D., Chorover, J., Dietrich, W. E., Dontsova, K., Durcik, M., Espeleta, J., Ferre, T., Ferriere, R., Henderson, W., Hunt, E. A., Huxman, T. E., Millar, D., Murphy, B., , Niu, G., et al. (2015). The Landscape Evolution Observatory: A large-scale controllable infrastructure to study coupled Earth-surface processes. Geomorphology, 244, 190-203.
• Pasetto, D., Niu, G., Pangle, L., Paniconi, C., Putti, M., & Troch, P. A. (2015). Impact of sensor failure on the observability of flow dynamics at the Biosphere 2 LEO hillslopes. Advances in Water Resources, 86, 327-339.
• Shao, A., Qiu, C., & Niu, G. (2015). A piecewise modeling approach for climate sensitivity studies: Tests with a shallow-water model. Journal of Meteorological Research, 29(5), 735-746.
• Cai, X., Yang, Z., David, C. H., Niu, G., & Rodell, M. (2014). Hydrological evaluation of the noah-MP land surface model for the Mississippi River Basin. Journal of Geophysical Research, 119(1), 23-38.
• Chen, F., Barlage, M., Tewari, M., Rasmussen, R., Jin, J., Lettenmaier, D., Livneh, B., Lin, C., Miguez-Macho, G. .., Niu, G., Wen, L., & Yang, Z. (2014). Modeling seasonal snowpack evolution in the complex terrain and forested colorado headwaters region: A model intercomparison study. Journal of Geophysical Research, 119(22), 13795-13819.
• Fehmi, J. S., Niu, G., Scott, R. L., & Mathias, A. (2014). Evaluating the effect of rainfall variability on vegetation establishment in a semidesert grassland. Environmental Monitoring and Assessment, 186(1), 395-406.
• Niu, G., Paniconi, C., Troch, P. A., Scott, R. L., Durcik, M., Zeng, X., Huxman, T., & Goodrich, D. C. (2014). An integrated modelling framework of catchment-scale ecohydrological processes: 1. Model description and tests over an energy-limited watershed. Ecohydrology, 7(2), 427-439.
• Niu, G., Pasetto, D., Scudeler, C., Paniconi, C., Putti, M., Troch, P. A., Delong, S. B., Dontsova, K., Pangle, L., Breshears, D. D., Chorover, J., Huxman, T. E., Pelletier, J., Saleska, S. R., & Zeng, X. (2014). Incipient subsurface heterogeneity and its effect on overland flow generation - Insight from a modeling study of the first experiment at the Biosphere 2 Landscape Evolution Observatory. Hydrology and Earth System Sciences, 18(5), 1873-1883.
• Niu, G., Troch, P. A., Paniconi, C., Scott, R. L., Durcik, M., Zeng, X., Huxman, T., Goodrich, D., & Pelletier, J. (2014). An integrated modelling framework of catchment-scale ecohydrological processes: 2. The role of water subsidy by overland flow on vegetation dynamics in a semi-arid catchment. Ecohydrology, 7(2), 815-827.
• Zhang, X., Niu, G., Elshall, A. S., Ye, M., Barron-Gafford, G. A., & Pavao-Zuckerman, M. .. (2014). Assessing five evolving microbial enzyme models against field measurements from a semiarid savannah - What are the mechanisms of soil respiration pulses?. Geophysical Research Letters, 41(18), 6428-6434.
• Dai, Y., Shangguan, W., Duan, Q., Liu, B., Fu, S., & Niu, G. (2013). Development of a china dataset of soil hydraulic parameters using pedotransfer functions for land surface modeling. Journal of Hydrometeorology, 14(3), 869-887.
• David, C. H., Maidment, D. R., Niu, G., Yang, Z., Habets, F., & Eijkhout, V. (2011). River network routing on the NHDPlus dataset. Journal of Hydrometeorology, 12(5), 913-934.
• Li, M. X., Ma, Z. G., & Niu, G. (2011). Modeling spatial and temporal variations in soil moisture in China. Chinese Science Bulletin, 56(17), 1809-1820.
• Niu, G., Yang, Z., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M., Kumar, A., Manning, K., Niyogi, D., Rosero, E., Tewari, M., & Xia, Y. (2011). The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 116.
• Rosero, E., Gulden, L. E., Yang, Z., Goncalves, L. G., Niu, G., & Kaheil, Y. H. (2011). Ensemble evaluation of hydrologically enhanced Noah-LSM: Partitioning of the water balance in high-resolution simulations over the little washita river experimental watershed. Journal of Hydrometeorology, 12(1), 45-64.
• Su, H., Yang, Z., Niu, G., & Wilson, C. R. (2011). Parameter estimation in ensemble based snow data assimilation: A synthetic study. Advances in Water Resources, 34(3), 407-416.
• Yang, Z., Niu, G., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M., Longuevergne, L., Manning, K., Niyogi, D., Tewari, M., & Xia, Y. (2011). The community Noah land surface model with multiparameterization options (Noah-MP): 2. Evaluation over global river basins. Journal of Geophysical Research Atmospheres, 116(12).
• Rosero, E., Yang, Z., Wagener, T., Gulden, L. E., Yatheendradas, S., & Niu, G. (2010). Quantifying parameter sensitivity, interaction, and transferability in hydrologically enhanced versions of the noah land surface model over transition zones during the warm season. Journal of Geophysical Research Atmospheres, 115(3).
• Su, H., Yang, Z., Dickinson, R. E., Wilson, C. R., & Niu, G. (2010). Multisensor snow data assimilation at the continental scale: The value of Gravity Recovery and Climate Experiment terrestrial water storage information. Journal of Geophysical Research Atmospheres, 115(10).
• Chen, J. L., Wilson, C. R., Tapley, B. D., Yang, Z. L., & Niu, G. Y. (2009). 2005 drought event in the Amazon River basin as measured by GRACE and estimated by climate models. Journal of Geophysical Research: Solid Earth, 114(5).
• Jiang, X., Niu, G., & Yang, Z. (2009). Impacts of vegetation and groundwater dynamics on warm season precipitation over the Central United States. Journal of Geophysical Research Atmospheres, 114(6).
• Rosero, E., Yang, Z., Gulden, L. E., Niu, G., & Gochis, D. J. (2009). Evaluating enhanced hydrological representations in Noah LSM over transition zones: Implications for model development. Journal of Hydrometeorology, 10(3), 600-622.
• Yong, B., Ren, L., Chen, X., Zhang, Y., Zhang, W., Fu, C., & Niu, G. (2009). Development of a large-scale hydrological model TOPX and its coupling with regional integrated environment modeling system RIEMS. Acta Geophysica Sinica, 52(8), 1954-1965.
• Yong, B., Zhang, W., Niu, G., Ren, L., & Qin, C. (2009). Spatial statistical properties and scale transform analyses on the topographic index derived from DEMs in China. Computers and Geosciences, 35(3), 592-602.
• Zhang, X., Wang, X., Yang, Z., Niu, G., & Xie, Z. (2009). Simulations of seasonal variations of stable water isotopes in land surface process model CLM. Chinese Science Bulletin, 54(10), 1765-1772.
• Zhang, X., Yang, Z., Niu, G., & Wang, X. (2009). Stable water isotope simulation in different reservoirs of Manaus, Brazil, by community land model incorporating stable isotopic effect. International Journal of Climatology, 29(5), 619-628.
• Gulden, L. E., Rosero, E., Yang, Z., Wagener, T., & Niu, G. (2008). Model performance, model robustness, and model fitness scores: A new method for identifying good land-surface models. Geophysical Research Letters, 35(11).
• Gulden, L. E., Yang, Z., & Niu, G. (2008). Sensitivity of biogenic emissions simulated by a land-surface model to land-cover representations. Atmospheric Environment, 42(18), 4185-4197.
• Oleson, K. W., Niu, G., Yang, Z., Lawrence, D. M., Thornton, P. E., Lawrence, P. J., Stöckli, R., Dickinson, R. E., Bonan, G. B., Levis, S., Dai, A., & Qian, T. (2008). Improvements to the community land model and their impact on the hydrological cycle. Journal of Geophysical Research: Biogeosciences, 113(1).
• Stöckli, R., Lawrence, D. M., Niu, G., Oleson, K. W., Thornton, P. E., Yang, Z., Bonan, G. B., Denning, A. S., & Running, S. W. (2008). Use of FLUXNEt in the community land model development. Journal of Geophysical Research: Biogeosciences, 113(1).
• Su, H., Yang, Z., Niu, G., & Dickinson, R. E. (2008). Enhancing the estimation of continental-scale snow water equivalent by assimilating MODIS snow cover with the ensemble Kalman filter. Journal of Geophysical Research Atmospheres, 113(8).
• Gulden, L. E., Rosero, E., Yang, Z., Rodell, M., Jackson, C. S., Niu, G., Yeh, P., & Famiglietti, J. (2007). Improving land-surface model hydrology: Is an explicit aquifer model better than a deeper soil profile?. Geophysical Research Letters, 34(9).
• Gulden, L. E., Yang, Z., & Niu, G. (2007). Interannual variation in biogenic emissions on a regional scale. Journal of Geophysical Research Atmospheres, 112(14).
• Li, W., Dickinson, R. E., Fu, R., Niu, G., Yang, Z., & Canadell, J. G. (2007). Future precipitation changes and their implications for tropical peatlands. Geophysical Research Letters, 34(1).
• Niu, G., & Yang, Z. (2007). An observation-based formulation of snow cover fraction and its evaluation over large North American river basins. Journal of Geophysical Research Atmospheres, 112(21).
• Niu, G., Seo, K., Yang, Z., Wilson, C., Su, H., Chen, J., & Rodell, M. (2007). Retrieving snow mass from GRACE terrestrial water storage change with a land surface model. Geophysical Research Letters, 34(15).
• Niu, G., Yang, Z., Dickinson, R. E., Gulden, L. E., & Su, H. (2007). Development of a simple groundwater model for use in climate models and evaluation with Gravity Recovery and Climate Experiment data. Journal of Geophysical Research Atmospheres, 112(7).
• Niu, G., & Yang, Z. (2006). Assessing a land surface model's improvements with GRACE estimates. Geophysical Research Letters, 33(7).
• Niu, G., & Yang, Z. (2006). Effects of frozen soil on snowmelt runoff and soil water storage at a continental scale. Journal of Hydrometeorology, 7(5), 937-952.
• Niu, G., Yang, Z., Dickinson, R. E., & Gulden, L. E. (2005). A simple TOPMODEL-based runoff parameterization (SIMTOP) for use in global climate models. Journal of Geophysical Research Atmospheres, 110(21), 1-15.
• Boone, A. A., Habets, F., Noilhan, J., Clark, D., Dirmeyer, P., Fox, S., Gusev, Y., Haddeland, I., Koster, R., Lohmann, D., Mahanama, S., Mitchell, K., Nasonova, O., Niu, G., Pitman, A., Polcher, J., Shmakin, A. B., Tanaka, K., Van, D., , Vérant, S., et al. (2004). The Rho̊ne-aggregation land surface scheme intercomparison project: An overview. Journal of Climate, 17(1), 187-208.
• Niu, G., & Yang, Z. (2004). Effects of vegetation canopy processes on snow surface energy and mass balances. Journal of Geophysical Research D: Atmospheres, 109(23), 1-15.
• Bowling, L. C., Lettenmaier, D. P., Nijssen, B., Graham, L. P., Clark, D. B., El Maayar, M., Essery, R., Goers, S., Gusev, Y. M., Habets, F., Van, D., Jin, J., Kahan, D., Lohmann, D., Ma, X., Mahanama, S., Mocko, D., Nasonova, O., Niu, G., , Samuelsson, P., et al. (2003). Simulation of high-latitude hydrological processes in the Torne-Kalix basin: PILPS Phase 2(e) 1: Experiment description and summary intercomparisons. Global and Planetary Change, 38(1-2), 1-30.
• Dai, Y., Zeng, X., Dickinson, R. E., Baker, I., Bonan, G. B., Bosilovich, M. G., Denning, A. S., Dirmeyer, P. A., Houser, P. R., Niu, G., Oleson, K. W., Schlosser, C. A., & Yang, Z. (2003). The common land model. Bulletin of the American Meteorological Society, 84(8), 1013-1023.
• Nijssen, B., Bowling, L. C., Lettenmaier, D. P., Clark, D. B., El Maayar, M., Essery, R., Goers, S., Gusev, Y. M., Habets, F., Van, D., Jin, J., Kahan, D., Lohmann, D., Ma, X., Mahanama, S., Mocko, D., Nasonova, O., Niu, G., Samuelsson, P., , Shmakin, A. B., et al. (2003). Simulation of high latitude hydrological processes in the Torne-Kalix basin: PILPS Phase 2(e) 2: Comparison of model results with observations. Global and Planetary Change, 38(1-2), 31-53.
• Niu, G., & Yang, Z. (2003). The versatile integrator of surface atmospheric processes part 2: Evaluation of three topography-based runoff schemes. Global and Planetary Change, 38(1-2), 191-208.
• Yang, Z., & Niu, G. (2003). The versatile integrator of surface and atmosphere processes part 1. Model description. Global and Planetary Change, 38(1-2), 175-189.
• Yang, Z., Gochis, D., Shuttleworth, W. J., & Niu, G. (2003). The impact of sea surface temperature on the North American monsoon: A GCM study. Geophysical Research Letters, 30(2), 5-1 - 5-4.
• Cassardo, C., Loglisci, N., Gandini, D., Qian, M. W., Niu, G. Y., Ramieri, P., Pelosini, R., & Longhetto, A. (2002). The flood of November 1994 in Piedmont, Italy: A quantitative analysis and simulation. Hydrological Processes, 16(6), 1275-1299.
• Yang, Z., Dickinson, R. E., Hahmann, A. N., Niu, G., Shaikh, M., Gao, X., Bales, R. C., Sorooshian, S., & Jin, J. (1999). Simulation of snow mass and extent in general circulation models. Hydrological Processes, 13(12-13), 2097-2113.
• Guoyue, N., Carssardo, C., Zhongxiang, H., & Longhetto, A. (1998). Numerical simulation on the response of land surface to severe weather. Acta Meteorologica Sinica, 12(4), 410-424.
• Niu, G., Sun, S., & Hong, Z. (1997). Water and heat transport in the desert soil and atmospheric boundary layer in western China. Boundary-Layer Meteorology, 85(2), 179-195.

Proceedings Publications

• Niu, G., & Yang, Z. (2004). Modeling the Continental Hydrology: The Interplay between Canopy Interception and Hill-Slope Runoff.
• Yang, Z., Niu, G., & Zeng, Q. (2004). Impacts of Fractional Snow Cover on Surface Air Temperature in the NCAR Community Atmosphere Model (NCAR-CAM2).

Presentations

• Niu, G., Zeng, X., Gupta, H. V., & Wang, Y. H. (2021). Developing Regional Snow Model Using Long Short-Term Memory Networks Applied to Large Pixel-Scale Datasets. El Dia Del Agua y Atmosphera, Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, Mar 31/April 1. Online: Department of Hydrology and Atmospheric Sciences, The University of Arizona,.
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  Wang YH, H Gupta, X Zeng and GY Niu (2021), Developing Regional Snow Model Using Long Short-Term Memory Networks Applied to Large Pixel-Scale Datasets, presented at El Dia Del Agua y Atmosphera, Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, Mar 31/April 1
• Niu, G., Zeng, X., Gupta, H. V., & Wang, Y. H. (2021). Hypothesis Testing Using Long Short-Term Memory Networks for Improving Understanding of Continental- and Regional-Scale Snowpack Dynamics. 2021 Fall Meeting of the American Geophysical Union, Online, Dec 13-17. Online: AGU.
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  Wang YH, HV Gupta , X Zeng and GY Niu (2021), Hypothesis Testing Using Long Short-Term Memory Networks for Improving Understanding of Continental- and Regional-Scale Snowpack Dynamics, Session H081: Physics-informed Machine Learning in Hydrology, presented at 2021 Fall Meeting of the American Geophysical Union, Online, Dec 13-17.
• Niu, G. (2020, 11). Noah-MP and Recent New Developments in Plant Hydraulics. Invited SeminarNASA Hydrological Sciences Laboratory.
• Niu, G., Fang, Y., Zeng, X., Behrangi, A., Broxton, P. D., Gupta, H. V., & Wang, Y. H. (2020, Spring). Developing the Snow Cover Fraction Schemes using Machine Learning Approach for Hydrological Predictions. 2020 Meeting of the American Meteorological Society, Phoenix Arizona, Jan 12-16.. Boston, MA: AMS.
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  Wang YH, HV Gupta, PD Broxton, A Behrangi, X Zeng, Y Fang, Guo-Yue Niu (2020), Developing the Snow Cover Fraction Schemes using Machine Learning Approach for Hydrological Predictions, Session on Applications of Machine Learning in Earth System Modeling, presented at 2020 Annual Meeting of the American Meteorological Society, Boston MA, Jan 12–16.
• Niu, G., Zeng, X., Behrangi, A., Fang, Y., Broxton, P. D., Gupta, H. V., & Wang, Y. H. (2020, Spring). Toward Improving Snowpack Prediction and its Parameterization in Land Surface Models. El Dia Del Agua y Atmosphera, Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, April. Tucson AZ: Department of Hydrology and Atmospheric Sciences, The University of Arizona.
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  YH Wang, HV Gupta, P Broxton, Y Fang, A Behrangi, X Zeng, GYue Niu (2020), Toward Improving Snowpack Prediction and its Parameterization in Land Surface Models, presented at El Dia Del Agua y Atmosphera, Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, April
• Niu, G., Zeng, X., Behrangi, A., Fang, Y., Broxton, P. D., Wang, Y. H., & Gupta, H. V. (2020, Fall). Toward Improving Snowpack Prediction and Snow Cover Fraction Parameterization in Land Surface Models. 2020 Fall Meeting of the American Geophysical Union, Online, Dec 7-11. Online: American Geophysical Union.
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  H Gupta, YH Wang , PD Broxton, Y Fang, A Behrangi, X Zeng and GY Niu (2020), Toward Improving Snowpack Prediction and Snow Cover Fraction Parameterization in Land Surface Models, Session C029: Quantifying Spatial and Temporal Variability of Snow and Snow Processes, presented at 2020 Fall Meeting of the American Geophysical Union, Online, Dec 1-17.
• Niu, G., Zeng, X., Nearing, G. S., Gupta, H. V., & Wang, Y. H. (2020, Fall). Hypothesis Testing using Long Short-Term Memory Networks Applied to Large Pixel-Scale Datasets. 2020 Fall Meeting of the American Geophysical Union, Online, Dec 7-11. Online: American Geophysical Union.
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  YH Wang, H Gupta, GS Nearing, X Zeng and GYue Niu (2020), Hypothesis Testing using Long Short-Term Memory Networks Applied to Large Pixel-Scale Datasets, Session H224: Machine Learning in Hydrological Modeling, presented at 2020 Fall Meeting of the American Geophysical Union, Online, Dec 1-17.
• Niu, G., Fang, Y., Zeng, X., Behrangi, A., Broxton, P. D., Gupta, H. V., & Wang, Y. H. (2019, Fall). Investigation of Constructing a Snow Cover Fraction Scheme for Land Surface Model. 2019 Annual Meeting of the Arizona Hydrological Society, Casino del Sol, Tucson AZ, Sept 25–27. Tucson AZ: AHS.
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  Wang YH, HV Gupta, PD Broxton, A Behrangi, X Zeng, Y Fang, Guo-Yue Niu (2019), Investigation of Constructing a Snow Cover Fraction Scheme for Land Surface Model, presented at 2019 Annual Meeting of the Arizona Hydrological Society, Casino del Sol, Tucson AZ, Sept 25–27.
• Niu, G., Gupta, H. V., Zeng, X., Behrangi, A., Broxton, P. D., Fang, Y., & Wang, Y. H. (2019, Fall). Developing a New Snow Cover Fraction Scheme for Hydrological Predictions. 2019 Fall Meeting of the American Geophysical Union. San Francisco, CA: AGU.
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  Wang YH, Y Fang, PD Broxton, A Behrangi, X Zeng, HV Gupta, Guo-Yue Niu (2019), Developing a New Snow Cover Fraction Scheme for Hydrological Predictions, Session H025 - Applications in Snow Hydrology: Linking Seasonal Snow to Natural Processes and Society, presented at 2019 Fall Meeting of the American Geophysical Union, San Francisco CA, Dec 9-13.
• Gong, W., Duan, Q., Gupta, H. V., Niu, G., & Huo, X. (2018, Fall 2018). Investigation of the Robustness of Parameter Sensitivity Estimates from Different Spatial Samples. 2018 Fall Meeting of the American Geophysical Union. Washington DC: American Geophysical Union.
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  Huo X, GY Niu, H Gupta, Q Duan and W Gong (2018), Investigation of the Robustness of Parameter Sensitivity Estimates from Different Spatial Samples, session H044 – Data integration, inverse methods, and data valuation across a range of scales in hydrogeophysics, presented at 2018 Fall Meeting of the American Geophysical Union, Washington DC, Dec 10-14.
• Elshall, A., Ye, M., Niu, G., & Barron-Gafford, G. A. (2015, December). Bayesian multimodel inference of soil microbial respiration models: Theory, application and future prospective. American Geophysical Union Annual Meeting. San Francisco, CA.
• Chang, H. I., Castro, C. L., & Niu, G. (2013, December). Impact of dynamic vegetation on evolution of the North American Monsoon region in a regional climate model.. 46th American Geophysical Union Fall Meeting. San Francisco, CA: American Geophysical Union.

Poster Presentations

• Troch, P. A., Zeng, X., Wang, Y., Van Haren, J. L., Tuller, M., Sibayan, M., Schaap, M. G., Saleska, S. R., Ruiz, J., Rasmussen, C., Pelletier, J. D., Niu, G., Monson, R. K., Meredith, L., Alves Meira Neto, A., Matos, K. A., Maier, R. M., Kim, M., Hunt, E. A., , Harman, C. J., et al. (2017, December). Controlled Experiments of Hillslope Co-evolution at the Biosphere 2 Landscape Evolution Observatory: Toward Prediction of Coupled Hydrological, Biogeochemical, and Ecological change. 2017 AGU Fall Meeting, Abstract B43A-2105. New Orleans, LA: American Geophysical Union (AGU).
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  Understanding the process interactions and feedbacks among water, microbes, plants, and porous geological media is crucial for improving predictions of the response of Earth’s critical zone to future climatic conditions. However, the integrated co-evolution of landscapes under change is notoriously difficult to investigate. Laboratory studies are typically limited in spatial and temporal scale, while field studies lack observational density and control. To bridge the gap between controlled lab and uncontrolled field studies, the University of Arizona – Biosphere 2 built a macrocosm experiment of unprecedented scale: the Landscape Evolution Observatory (LEO). LEO consists of three replicated, 330-m2 hillslope landscapes inside a 5000-m2 environmentally controlled facility. The engineered landscapes contain 1-m depth of basaltic tephra ground to homogenous loamy sand that will undergo physical, chemical, and mineralogical changes over many years. Each landscape contains a dense sensor network capable of resolving water, carbon, and energy cycling processes at sub-meter to whole-landscape scale. Embedded sampling devices allow for quantification of biogeochemical processes, and facilitate the use of chemical tracers applied with the artificial rainfall. LEO is now fully operational and intensive forcing experiments have been launched. While operating the massive infrastructure poses significant challenges, LEO has demonstrated the capacity of tracking multi-scale matter and energy fluxes at a level of detail impossible in field experiments. Initial sensor, sampler, and restricted soil coring data are already providing insights into the tight linkages between water flow, weathering, and (micro-) biological community development during incipient landscape evolution. Over the years to come, these interacting processes are anticipated to drive the model systems to increasingly complex states, potentially perturbed by changes in climatic forcing. By intensively monitoring the evolutionary trajectory, integrating data with models, and fostering community-wide collaborations, we envision that emergent landscape structures and functions can be linked and significant progress can be made toward predicting the coupled hydro-biogeochemical and ecological responses to global change.