主要学术论文： [第一/通讯作者SCI/EI论文] [1] Soil physicochemical properties explain land use/cover histories in the last sixty years in China, Geoderma, 2024. https://doi.org/10.1016/j.geoderma.2024.116908 [2] Toward an improved ensemble of multi-source daily precipitation via joint machine learning classification and regression, Atmospheric Research, 2024. https://doi.org/10.1016/j.atmosres.2024.107385 [3] Evaluating data-driven and hybrid modeling of terrestrial actual evapotranspiration based on an automatic machine learning approach, Journal of Hydrology, 2024. https://doi.org/10.1016/j.jhydrol.2023.130594 [4] Dynamically weighted ensemble of geoscientific models via automated machine-learning-based classification, Geoscientific Model Development, 2023. https://doi.org/10.5194/gmd-16-5685-2023 [5] Impacts of seasonally frozen soil hydrothermal dynamics on the watershed hydrological processes inferred from a spatially distributed numerical modelling approach, Journal of Hydrology, 2023. https://doi.org/10.1016/j.jhydrol.2023.129947 [6] Discrimination and mapping ground surface freeze and thaw states over Northeastern China based on the improved dual-index algorithm, Cold Regions Science and Technology, 2023. https://doi.org/10.1016/j.coldregions.2023.103963 [7] Combining sparse observations and reanalysis data for refining spatiotemporal variability in near-surface air temperature lapse rates over China, International Journal of Climatology, 2021. https://doi.org/10.1002/joc.7226 [8] Long-term groundwater storage variations estimated in the Songhua River Basin by using GRACE products, land surface models, and in-situ observations, Science of The Total Environment, 2019. https://doi.org/10.1016/j.scitotenv.2018.08.352 [9] Remote detection of human-induced evapotranspiration in a regional system experiencing increased anthropogenic demands and extreme climatic variability, International Journal of Remote Sensing, 2019. https://doi.org/10.1080/01431161.2018.1523590 [10] Climate Change and Anthropogenic Impacts on Wetland and Agriculture in the Songnen and Sanjiang Plain, Northeast China, Remote Sensing, 2018. https://doi.org/10.3390/rs10030356 [11] Coupling physically-based modeling and deep learning for long-term global freshwater availability monitoring and prediction, Proceedings Volume 11856, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIII, 2021. https://doi.org/10.1117/12.2600200 [12] Variations of simulated water use efficiency over 2000-2016 and its driving forces in Northeast China, Proceedings Volume 11149, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI, 2019. https://doi.org/10.1117/12.2533127 [13] Modelling spatial and temporal variability of hydrologic impacts under climate changes over the Nenjiang River Basin, China, Proceedings Volume 10421, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX, 2017. https://doi.org/10.1117/12.2278357 [14] Volunteered Geographic Information for Disaster Management with Application to Earthquake Disaster Databank & Sharing Platform, IOP Conference Series: Earth and Environmental Science, 2017. https://doi.org/10.1088/1755-1315/57/1/012015 [合作作者SCI论文] [1] Soil Moisture Memory: State-Of-The-Art and the Way Forward, Reviews of Geophysics, 2024. https://doi.org/10.1029/2023RG000828 [2] Modeling hydrological consequences of 21st-Century climate and land use/land cover changes in a mid-high latitude watershed, Geoscience Frontiers, 2024. https://doi.org/10.1016/j.gsf.2024.101819 [3] Impacts of Climatic Fluctuations and Vegetation Greening on Regional Hydrological Processes: A Case Study in the Xiaoxinganling Mountains–Sanjiang Plain Region, Northeastern China, Remote Sensing, 2024. https://doi.org/10.3390/rs16152709 [4] Spatiotemporal green water dynamics and their responses to variations of climatic and underlying surface factors: A case study in the Sanjiang Plain, China, Journal of Hydrology: Regional Studies, 2023. https://doi.org/10.1016/j.ejrh.2022.101303 [5] Human-Induced water loss from closed inland Lakes: Hydrological simulations in China’s Daihai lake, Journal of Hydrology, 2022. https://doi.org/10.1016/j.jhydrol.2022.127552 [6] A new method for surface water extraction using multi-temporal Landsat 8 images based on maximum entropy model, European Journal of Remote Sensing, 2022. https://doi.org/10.1080/17538947.2020.1812740 [7] Evaluating global ecosystem water use efficiency response to drought based on multi-model analysis, Science of The Total Environment, 2021. https://doi.org/10.1016/j.scitotenv.2021.146356 [8] Spatial Downscaling Based on Spectrum Analysis for Soil Freeze/Thaw Status Retrieved From Passive Microwave, IEEE Transactions on Geoscience and Remote Sensing, 2021. https://doi.org/10.1109/TGRS.2021.3051683 [9] Monitoring the spatial distribution and changes in permafrost with passive microwave remote sensing, ISPRS Journal of Photogrammetry and Remote Sensing, 2020. https://doi.org/10.1016/j.isprsjprs.2020.10.011 [10] Separating the impacts of climate variability, land-use change and large reservoir operations on streamflow in the Yangtze River basin, China, using a hydrological modeling approach, International Journal of Digital Earth, 2020. https://doi.org/10.1080/17538947.2020.1812740 [11] A Global Hydrological Drought Index Dataset Based on Gravity Recovery and Climate Experiment (GRACE) Data, Water Resources Management, 2018. https://doi.org/10.1007/s11269-017-1869-1 [12] An Improved Algorithm for Discriminating Soil Freezing and Thawing Using AMSR-E and AMSR2 Soil Moisture Products, Remote Sensing, 2018. https://doi.org/10.3390/rs10111697 |
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