U.S. flagAn official website of the United States government
                    Here's how you know **Official websites use .gov**
                            
                            A **.gov** website belongs to an official government organization in the United States.
 **Secure .gov websites use HTTPS**
                            
                            A **lock** (                            
                              A locked padlock                                                      
                            
                            ) or **https://** means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.


Menu Agricultural Research Service
						
                    U.S. DEPARTMENT OF AGRICULTURE
 Hydrology and Remote Sensing Laboratory: Beltsville, MD
 close



    Research

                    Research Projects
                                    Publications
                                    Collaborations
                                    News
                                    Software
                People

                    Staff Listing
                                    CareersSearch small
                    Search
            
            ARS Home
                                About ARS
                                Contact Us




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





- Find a person
- Find a location
- ARS Organizational Chart
- People
- Research
- Joseph Alfieri
- Martha Anderson
- Michael Cosh
- Octavia Crompton
- Wade Crow
- Feng Gao
- Cathleen Hapeman
- Simon Kraatz
- William Kustas
- Gregory McCarty
- Xuesong Zhang
- Alexia Bertholon
- Wayne Dulaney
- Sanam Izadidehkordi
- Lynn McKee
- Robert Parry
- Aquena Perry
- Andrew Russ
- Zacharias Smith
- Alan Stern
- William (Alex) White
- Uvirkaa Akumaga
- Nishan Bhattarai
- Richard Cirone
- Ling Du
- Maryam Foroughi
- Audra Hinson
- Wells (Dean) Hively
- Victoria Walker
- Yiming Wang
- Yun Yang
- Haoteng Zhao

Xuesong  Zhang
                     

                     Research Physical Scientist

                     


                        **Publications**
                                    (Clicking on the reprint icon
                                       Reprint Icon
                                       will take you to the publication reprint.)Modeling lateral carbon fluxes for agroecosystems in the Mid-Atlantic region: Control factors and importance for carbon budget

                                       -
(Peer Reviewed Journal)Luo, X., Risal, A., Qi, J., Lee, S., Zhang, X., Alfieri, J.G., Mccarty, G.W. 2023. Modeling lateral carbon fluxes for agroecosystems in the Mid-Atlantic region: Control factors and importance for carbon budget. Science of the Total Environment. 912:169128. https://doi.org/10.1016/j.scitotenv.2023.169128.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). Article 122537. 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.


Return to top


Connect with ARS Sign up


ARS Home
                            USDA.gov
                            Plain Writing
                            Policies & Links
                            Civil Rights Statements
                            FOIA
                            Accessibility Statement
                            Privacy Policy
                            Non-Discrimination Statement
                            Quality of Information
                            USA.gov
                            WhiteHouse.gov