World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
52
Citations
9099
World Ranking
4522
National Ranking
1682

Overview

Xuesong Zhang is affiliated with the Agricultural Research Service in the United States. Their research primarily focuses on environmental science, with contributions spanning several interconnected subfields including global and planetary change, water science and technology, environmental engineering, environmental chemistry, and ecology.

The scientist's work covers multiple main topics that include hydrology and watershed management studies, soil and water nutrient dynamics, plant water relations and carbon dynamics, land use and ecosystem services, environmental impact and sustainability, climate variability and models, and flood risk assessment and management.

Xuesong Zhang has coauthored publications frequently with several researchers, indicating collaborative work in diverse areas. The most common coauthors are Junyu Qi, Gregory W. McCarty, Glenn E. Moglen, Hongjie Peng, and Yuyu Zhou.

They have published in various scientific journals with repeated contributions in key venues such as the Journal of Hydrology, The Science of The Total Environment, Environmental Modelling & Software, Environmental Research Letters, and Environmental Science & Technology.

Significant recent publications by Xuesong Zhang include:

  • "Urban land use change simulation and spatial responses of ecosystem service value under multiple scenarios: A case study of Wuhan, China" (2022) in Ecological Indicators
  • "A multi-scale daily SPEI dataset for drought characterization at observation stations over mainland China from 1961 to 2018" (2021) in Earth System Science Data
  • "The spatial spillover effect and nonlinear relationship analysis between land resource misallocation and environmental pollution: Evidence from China" (2022) in Journal of Environmental Management
  • "Understanding climate change impacts on drought in China over the 21st century: a multi-model assessment from CMIP6" (2024) in npj Climate and Atmospheric Science
  • "Freeze-Thaw cycle representation alters response of watershed hydrology to future climate change" (2020) in CATENA

Best Publications

  • Sustainable bioenergy production from marginal lands in the US Midwest.

    Ilya Gelfand;Ilya Gelfand;Ritvik Sahajpal;Ritvik Sahajpal;Ritvik Sahajpal;Xuesong Zhang;Xuesong Zhang;R. César Izaurralde;R. César Izaurralde;R. César Izaurralde

  • SWAT Ungauged: Hydrological Budget and Crop Yield Predictions in the Upper Mississippi River Basin

    R. Srinivasan;X. Zhang;J. Arnold

  • Detecting change-point, trend, and seasonality in satellite time series data to track abrupt changes and nonlinear dynamics: A Bayesian ensemble algorithm

    Kaiguang Zhao;Kaiguang Zhao;Michael A. Wulder;Tongxi Hu;Ryan Bright

  • A global map of urban extent from nightlights

    Yuyu Zhou;Steven J. Smith;Kaiguang Zhao;Marc L. Imhoff

  • Modeling urban building energy use: A review of modeling approaches and procedures

    Wenliang Li;Yuyu Zhou;Kristen Cetin;Jiyong Eom

  • Calibration and uncertainty analysis of the SWAT model using Genetic Algorithms and Bayesian Model Averaging

    Xuesong Zhang;Raghavan Srinivasan;David Bosch

  • Predicting hydrologic response to climate change in the Luohe River Basin using the SWAT model

    X. Zhang;R. Srinivasan;F. Hao

  • A multi-scale daily SPEI dataset for drought characterization at observation stations over mainland China from 1961 to 2018

    Qianfeng Wang;Qianfeng Wang;Jingyu Zeng;Junyu Qi;Xuesong Zhang;Xuesong Zhang

  • Evaluation of global optimization algorithms for parameter calibration of a computationally intensive hydrologic model

    Xuesong Zhang;Raghavan Srinivasan;Kaiguang Zhao;Mike Van Liew

  • Multi-Site Calibration of the SWAT Model for Hydrologic Modeling

    X. Zhang;R. Srinivasan;M. Van Liew

  • Runoff Simulation of the Headwaters of the Yellow River Using The SWAT Model With Three Snowmelt Algorithms1

    Xuesong Zhang;Raghavan Srinivasan;Bekele Debele;Fanghua Hao

  • On the use of multi-algorithm, genetically adaptive multi-objective method for multi-site calibration of the SWAT model

    Xuesong Zhang;Raghavan Srinivasan;Michael Van Liew

  • Hyperspectral remote sensing of plant biochemistry using Bayesian model averaging with variable and band selection

    Kaiguang Zhao;Denis Valle;Sorin Popescu;Xuesong Zhang

  • Approximating SWAT model using Artificial Neural Network and support vector machine.

    Xuesong Zhang;Raghavan Srinivasan;Michael Van Liew

  • An integrative modeling framework to evaluate the productivity and sustainability of biofuel crop production systems

    Xuesong Zhang;Roberto C. Izaurralde;David H. Manowitz;T. O. West

  • Evaluating the SWAT Model for Hydrological Modeling in the Xixian Watershed and a Comparison with the XAJ Model

    Peng Shi;Peng Shi;Chao Chen;Ragahavan Srinivasan;Xuesong Zhang

  • GIS-based spatial precipitation estimation: a comparison of geostatistical approaches.

    Xuesong Zhang;Raghavan Srinivasan

  • Bioenergy crop models: descriptions, data requirements, and future challenges

    Sujithkumar Surendran Nair;Shujiang Kang;Xuesong Zhang;Fernando E. Miguez

  • Terrestrial lidar remote sensing of forests: Maximum likelihood estimates of canopy profile, leaf area index, and leaf angle distribution

    Kaiguang Zhao;Mariano García;Shu Liu;Qinghua Guo

  • Using NEXRAD and rain gauge precipitation data for hydrologic calibration of SWAT in a Northeastern watershed.

    A. M. Sexton;A. M. Sadeghi;X. Zhang;R. Srinivasan

  • Efficient multi-objective calibration of a computationally intensive hydrologic model with parallel computing software in Python

    Xuesong Zhang;Peter Beeson;Robert Link;David Manowitz

Frequent Co-Authors

R. Cesar Izaurralde
R. Cesar Izaurralde University of Maryland, College Park
Roberto C. Izaurralde
Roberto C. Izaurralde University of Maryland, College Park
Raghavan Srinivasan
Raghavan Srinivasan Texas A&M University
Kaiguang Zhao
Kaiguang Zhao The Ohio State University
Maoyi Huang
Maoyi Huang Pacific Northwest National Laboratory
Allison M. Thomson
Allison M. Thomson University of Maryland, College Park
Guoyong Leng
Guoyong Leng Chinese Academy of Sciences
Gregory W. McCarty
Gregory W. McCarty Agricultural Research Service
Yuyu Zhou
Yuyu Zhou Iowa State University
Bruce E. Dale
Bruce E. Dale Michigan State University

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