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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » People & Locations » Xuesong Zhang

Xuesong Zhang
Research Physical Scientist


Publications (Clicking on the reprint icon Reprint Icon will take you to the publication reprint.)
Advancing the SWAT model to simulate perennial bioenergy crops: A case study on switchgrass growth - (Peer Reviewed Journal)
Large-scale urban building function mapping by integrating multi-source web-based geospatial data - (Peer Reviewed Journal)
Nitrous oxide emissions from multiple agroecosystems in the U.S. Corn Belt simulated using the modified SWAT-C model - (Peer Reviewed Journal)
Liang, K., Zhang, X., Qi, J., Emmett, B.D., Johnson, J.M., Malone, R.W., Moglen, G.E., Venterea, R.T. 2023. Nitrous oxide emissions from multiple agroecosystems in the U.S. Corn Belt simulated using the modified SWAT-C model . Environmental Pollution. 337 (2023). https://doi.org/10.1016/j.envpol.2023.122537.
Watershed scale modeling of dissolved organic carbon export from variable source areas - (Peer Reviewed Journal)
Multivariate calibration of the SWAT model using remotely sensed datasets - (Peer Reviewed Journal)
Dangol, S., Zhang, X., Liang, X., Anderson, M.C., Crow, W.T., Lee, S., Moglen, G.E., McCarty, G.W. 2023. Multivariate calibration of the SWAT model using remotely sensed datasets. Remote Sensing. 15(9):2417. https://doi.org/10.3390/rs15092417.
Crop yield prediction via explainable AI and interpretable machine learning: Dangers of black box models for evaluating climate change impacts on crop yield - (Peer Reviewed Journal)
Hu, T., Zhao, K., Zhou, Y., Liu, Y., Bohrer, G., Martin, J., Li, Y., Zhang, X. 2023. Crop yield prediction via explainable AI and interpretable machine learning: Dangers of black box models for evaluating climate change impacts on crop yield. Agricultural and Forest Meteorology. 336:109458. https://doi.org/10.1016/j.agrformet.2023.109458.
SWAT-3PG: Improving forest growth simulation with a process-based forest model in SWAT - (Peer Reviewed Journal)
Karki, R., Qi, J., Gonzales-Benecke, C., Zhang, X., Martin, T., Arnold, J.G. 2023. SWAT-3PG: Improving forest growth simulation with a process-based forest model in SWAT. Journal of Environmental Modeling and Software. 164. Article 105705. https://doi.org/10.1016/j.envsoft.2023.105705.
Simulating agroecosystem soil inorganic nitrogen dynamics under long-term management with an improved SWAT-C model - (Peer Reviewed Journal)
Liang, K., Zhang, X., Liang, X., Jin, V.L., Birru, G.A., Schmer, M.R., Robertson, P.G., McCarty, G.W., Moglen, G.E. 2023. Simulating agroecosystem soil inorganic nitrogen dynamics under long-term management with an improved SWAT-C model. Science of the Total Environment. 879. Article 162906. https://doi.org/10.1016/j.scitotenv.2023.162906.
Estimation of base and surface flow using deep neural networks and a hydrologic model in two watersheds of the Chesapeake Bay - (Peer Reviewed Journal)
Lee, J., Abbas, A., McCarty, G.W., Zhang, X., Lee, S., Cho, K. 2022. Estimation of base and surface flow using deep neural networks and a hydrologic model in two watersheds of the Chesapeake Bay. Journal of Hydrology. 617. Article 128916. https://doi.org/10.1016/j.jhydrol.2022.128916.
Global and northern-high-latitude terrestrial carbon sinks in the 21st century from CMIP6 experiments - (Peer Reviewed Journal)
Qui, H., Hao, D., Zeng, Y., Zhang, X., Chen, M. 2023. Global and northern-high-latitude terrestrial carbon sinks in the 21st century from CMIP6 experiments. Science of the Total Environment. 14(1):1-16. https://doi.org/10.5194/esd-14-1-2023.
Integrating vegetation phenology and SWAT model for improved modeling of ecohydrological processes - (Peer Reviewed Journal)
Chen, S., Fu, Y., Wu, Z., Hao, F., Hao, Z., Guo, Y., Geng, X., Li, X., Zhang, X., Tang, J., Singh, V.P., Zhang, X. 2022. Integrating vegetation phenology and SWAT model for improved modeling of ecohydrological processes. Remote Sensing. 616:128817. https://doi.org/10.1016/j.jhydrol.2022.128817.
Effects of temporal resolution of river routing on hydrologic modeling and aquatic ecosystem health assessment with the SWAT model - (Peer Reviewed Journal)
Qui, H., Qi, J., Lee, S., Moglen, G.E., Mccarty, G.W., Chen, M., Zhang, X. 2022. Effects of temporal resolution of river routing on hydrologic modeling and aquatic ecosystem health assessment with the SWAT model. Environmental Modelling & Software. 145:105232. https://doi.org/10.1016/j.envsoft.2021.105232.
Replicating measured site-scale soil organic carbon dynamics in the U.S. corn belt using the SWAT-C model - (Peer Reviewed Journal)
Liang, K., Qi, J., Zhang, X. 2022. Replicating measured site-scale soil organic carbon dynamics in the U.S. corn belt using the SWAT-C model. Environmental Modelling & Software. 158. Article 105553. https://doi.org/10.1016/j.envsoft.2022.105553.
Irrigation plays significantly different roles in influencing hydrological processes in two breadbasket regions - (Peer Reviewed Journal)
Wang, Y., Zhou, Y., Franz, K., Zhang, X., Qi, J., Jia, G., Yang, Y. 2022. Irrigation plays significantly different roles in influencing hydrological processes in two breadbasket regions. Science of the Total Environment. 844:157253. https://doi.org/10.1016/j.scitotenv.2022.157253.
Agricultural irrigation effects on hydrological processes in the northern high plains simulated by the coupled SWAT-MODFLOW system - (Peer Reviewed Journal)
Dangol, S., Zhang, X., Lang, X., Miralles-Wilhelm, F. 2022. Agricultural irrigation effects on hydrological processes in the northern high plains simulated by the coupled SWAT-MODFLOW system. Water. 14(12):1938. https://doi.org/10.3390/w14121938.
Inductive predictions of hydrologic events using a Long Short-Term Memory Network and the Soil and Water Assessment Tool - (Peer Reviewed Journal)
Majeske, N., Zhang, X., Gong, L., Zhu, C., Azad, A. 2022. Inductive predictions of hydrologic events using a Long Short-Term Memory Network and the Soil and Water Assessment Tool. Environmental Modelling & Software. 152:105400. https://doi.org/10.1016/j.envsoft.2022.105400.
Combined use of crop yield statistics and remotely sensed products for enhanced simulations of evapotranspiration within an agricultural watershed - (Peer Reviewed Journal)
Lee, S., Qi, J., McCarty, G.W., Anderson, M.C., Yang, Y., Zhang, X., Moglen, G.E., Kwak, D., Kim, H., Lakshmi, V. 2022. Combined use of crop yield statistics and remotely sensed products for enhanced simulations of evapotranspiration within an agricultural watershed. Agricultural Water Management. 264:107503. https://doi.org/10.1016/j.agwat.2022.107503.
A review of carbon monitoring in wet carbon systems using remote sensing. - (Peer Reviewed Journal)
Campbell, A.D., Bourgeau-Chavez, L., Charles, S.P., Goes, J., Gomes, H., Halabisky, M., Holmquist, J., Lagomasino, D., Lohrenz, S., Mitchell, C., Moskai, M., Poulter, B., Qui, H., Resende De Sousa, C.H., Sayers, M., Simard, M., Stewart, A.J., Singh, D., Trettin, C., Wu, J., Zhang, X., Fatoyinbo, T. 2022. A review of carbon monitoring in wet carbon systems using remote sensing.. Environmental Research Letters. 17:025009. https://doi.org/10.1088/1748-9326/ac4d4d.
Coupling terrestrial and aquatic thermal processes for improving stream temperature modeling at watershed scale - (Peer Reviewed Journal)
Qi, Y., Lee, S., Du, X., Ficklin, D., Wang, Q., Myers, D., Singh, D., Moglen, G.E., Mccarty, G.W., Zhou, Y., Zhang, X. 2021. Coupling terrestrial and aquatic thermal processes for improving stream temperature modeling at watershed scale. Journal of Hydrology. 603. Article 126983. https://doi.org/10.1016/j.jhydrol.2021.126983.