西北农林科技大学“生态过程与模拟”团队论文目录

学术期刊论文：

2020s: 2025 / 2024 / 2023 / 2022 / 2021 / 2020

2010s: 2019 / 2018 / 2017 / 2016 / 2015 / 2014 / 2013 / 2012 / 2011 / 2010

2000s: 2009 / 2008 / 2007 / 2006 / 2005 / 2004 / 2003 / 2002 / 2001 / 2000

1990s: 1990s

指导和培养的学生：博士后 / 博士 / 硕士 / 悉尼科技大学(UTS)

Book Chapter

学术期刊论文

2025

 

2024

  1. Chen, F.H., Yang, X.Y.*, Yu, Q., Han, B., 2024. Quantifying the effects of diffuse photosynthetically active radiation on water use efficiency in different ecosystems. Agricultural and Forest Meteorology, 356: 110191. Impact Factor: 5.6
  1. Chen, S., Feng, W.Z., He, L., Xiao, W., Feng, H., Yu, Q., Liu, J.D., He, J.Q.*, 2024. Parameterization of the Ångström–Prescott formula based on machine learning benefit estimation of reference crop evapotranspiration with missing solar radiation data. Hydrological Processes, 38(2): e15091. Impact Factor: 3.2
  1. Gong, K.Y., Huang, Z., Qu, M.Y., He, Z.H., Chen, J.Q., Wang, Z., Yu, Q., Feng, H., He, J.Q.*, 2024. Influences of climate change on carbon and water fluxes of the ecosystem in the Qinling Mountains of China. Ecological Indicators, 166: 112504. Impact Factor: 7.0
  1. He, Q.S., Liu, D.L.*, Wang, B.*, Wang, Z.K., Cowie, A., Simmons, A., Xu, Z.C., Li, L.C., Shi, Y., Liu, K., Harrison, M.T., Waters, C., Huete, A., Yu, Q.*, 2024. A food-energy-water-carbon nexus framework informs region-specific optimal strategies for agricultural sustainability. Resources, Conservation & Recycling, 203: 107428. Impact Factor: 13.2
  1. He, Z.H., Gong, K.Y., Qu, M.Y., Ru, X.Y., Chen, S., Jiang, T.C., Zhang, J., Feng, H., Yu, Q., He, L., He, J.Q.*, 2024. Clarifying the impacts of climatic coupling on plastic-mulching potato production in the loess plateau of China. Agricultural Systems, 221: 104140. Impact Factor: 6.1
  1. Hu, Z.H., Marcos Fernandez-Martinez, He, Q.S., Xu, Z.Y., Jiang, L., Zhou, G.Y., Chen, J., Nie, M., Yu, Q., Feng, H., Huang, Z.Q., Michaletz, S.T., 2024. Fungal composition associated with host tree identity mediates nutrient addition effects on wood microbial respiration. Ecology, 105(8): e4375. Impact Factor: 4.4
  1. Kang, X.F., Wu, D.R.*, Tan, J.J., Wang, P.J., Ma, Y.P., Yang, J.Y., Wang, C.Y., Huo, Z.G., Tian, Q., Yu, Q.*, 2024. Performance of nine maize phenology models in China under historical climate change conditions. Agricultural and Forest Meteorology. 358: 110234. Impact Factor: 5.6
  1. Li, C.C., Zhang, X.Z., Guo, J.P., Yu, Q.*, Zhang, Y.Q.*, 2024. Decadal variation and trend of boundary layer height and possible contribution factors in China. Agricultural and Forest Meteorology, 347: 109910. Impact Factor: 5.6
  1. Liang, C.T., Liu, X.Q., Feng, L., Jin, N., Lv, J.L., Yu, Q.*, 2024. Optimizing Phosphorus Fertilizer Use on the Loess Plateau Impact on Soil Properties and Crop Production Efficiency. Soil Systems. 8(1): 3. Impact Factor: 3.5
  1. Liang, C.T., Liu, X.Q., Lv, J.L., Zhao, F.L.*, Yu, Q.*, 2024. The impact of different phosphorus fertilizers varieties on yield under wheat-maize rotation coditions. Agronomy. 14(6): 1317. Impact Factor: 3.3
  1. Liu, J.C.*, Guo, Y.J., Yang, J.T., Zhu, N.N., Dai, W.X., Yu, Q., 2024. Forest point cloud registration: a review. Forestry Research, 4: e018.
  1. Liu, J.D., Du, J., Wang, F.*, Liu, D.L., Tang, J.H., Lin, D.W., Tang, Y.H., Shi, L.J., Yu, Q., 2024. Optimal methods for estimating shortwave and longwave radiation to accurately calculate reference crop evapotranspiration in the high-altitude of Central Tibet. Agronomy, 14(10): 2401. Impact Factor: 3.3
  1. Liu, Y.D., Li, H.M., Zhu, L., Chen, B., Li, M.R., He, H.J., Zhou, H., Wang, Z., Yu, Q.*, 2024. Revealing cropping intensity dynamics using high-resolution imagery: a case study in Shaanxi Province, China. Remote Sensing, 16(20): 3832. Impact Factor: 4.2
  1. Liu, Z.Q., Guo, C.H., Yu, Q., Zhu, P., Peng, X.B., Dong, M.Q., Cai, H.J., Lu, X.L.*, 2024. A SIF-based approach for quantifying canopy photosynthesis by simulating the fraction of open PSII reaction centers (qL). Remote Sensing of Environment, 305: 114111. Impact Factor: 13.5
  1. Niu, B., Li, Y.*, Liu, D.L., Xie, L.L., Wang, L., Jiang, X.H., Feng, H., Yu, Q., He, J.Q., Lin, H.X., 2024. Improved identification and monitoring of meteorological, agricultural, and hydrological droughts using the modified nonstationary drought indices in the Yellow River Basin of China. Journal of Hydrology, 643: 131788. Impact Factor: 5.9
  1. Qi, X.Y., Yang, G., Li, Y.*, Hou, Z.N., Shi, P.H., Wang, S.B., Wang, X.F., Liang, J.P., Sun, B.H., Siddique, K.H.M., Wu, S.F., Feng, H., Tian, X.H., Yu, Q., Xie, X.W., 2024. Optimizing biochar application rates for improved soil chemical environments in cotton and sugarbeet fields under trickle irrigation with plastic mulch. Soil and Tillage Research, 235: 105893. Impact Factor: 6.5
  1. Shi, Y., Li, L.C., Wu, B.Y., Zhang, Y.J., Wang, B., Niu, W.H., He, L., Jin, N., Pan, S.F., Tian, H.Q.*, Yu, Q.*, 2024. Predicting rice productivity for ground data-sparse regions: A transferable framework and its application to North Korea. Science of the Total Environment, 946: 174227. Impact Factor: 8.2
  1. Tan, J.J., Zhao, G.*, Tian, Q., Zheng, L., Kang, X.F., He, Q.S., Shi, Y., Chen, B., Wu, D.R., Yao, N., He, L., Srivastava, A.K., Li, Y., He, J.Q., Feng, H., Yu. Q.*, 2024. Overcoming mechanistic limitations of process-based phenological models: a data clustering method for large-scale applications. Agricultural and Forest Meteorology. 356: 110167. Impact Factor: 5.6
  1. Tian, Q., Zhao, G.*, Yan, C.Q., Yao, L.J., Qu, J.J., Yin, L., Feng, H., Yao, N., Yu, Q.*, 2024. Enhancing practicality of deep learning for crop disease identification under field conditions: Insights from model evaluation and crop-specific approaches. Pest Management Science, 80(11):5864-5875. Impact Factor: 3.8
  1. Wang, B.*, Jagermeyr, J., OLeary, G., Wallach, D., Ruane, A.C., Feng, P.Y., Li, L.C., Liu, D.L., Waters, C., Yu, Q., Asseng, S.*, Rosenzweig, C., 2024. Pathways to indentify and reduce uncertainties in agricultural climate impact assessments. Nature Food, 5(7):550-556. Impact Factor: 23.6
  1. Wang, B.*, Li, L.C., Feng, P.Y., Chen, C., Luo, J.J., Tascgetti, A.S., Harrison, M.T., Liu, K., Liu, D.L., Yu, Q., Guo, X.W.*, 2024. Probabilistic analysis of drought impact on wheat yield and climate change implications. Weather and Climate Extremes, 45: 100708. Impact Factor: 6.1
  1. Wang, X.F., Li, Y.*, Biswas, A., Sang, H.H., He, J.Q., Yu, Q., Feng, H., Siddique, K.H.M., 2024. Modeling soil water and salt dynamics in cotton-sugarbeet intercropping and their monocultures with biochar application. Soil & Tillage Research, 240: 106070. Impact Factor: 6.5
  1. Wu, D.R., Gao, J., Wang, P.J., Yang, J.Y., Ma, Y.P., Huo, Z.G., Yu, Q.*, 2024. The necessity of coupling the legacy effect with temperature response in crop phenology models. Global Planetary Change. 240: 104545. Impact Factor: 4.0
  1. Yan, C.Q., Liang, Z.Y., Yin, L., Wei, S.M., Tian, Q., Li, Y., Cheng, H., Liu, J.D., Yu, Q., Zhao, G.*, Qu, J.J.*, 2024. AFM-YOLOv8s: An accurate, fast and highly robust model for detection of sporangia of Plasmopara viticola with various morphological variants. Plant Phenomics, 6: 0246. Impact Factor: 7.6
  1. Yang, J.J., Lu, X.L., Liu, Z.Q., Tang, X.H., Yu, Q.*, Wang, Y.F.*, 2024. Atmospheric drought dominates changes in global water use efficiency. Science of the Total Environment, 934: 173084. Impact Factor: 9.8
  1. Yang, J.J., Liu, Z.Q., Yu, Q., Lu, X.L.*, 2024. Estimation of global transpiration from remotely sensed solar-induced chlorophyll fluorescence. Remote Sensing of Environment, 303: 113998. Impact Factor: 13.5
  1. You, S.Y., Shi, H.*, Lun, F., Bian, Z.H., Wang, S.Q., Yu, Z., Yu, Q., Yao, Y.Z., 2024. Evaluation of gridded cropland phosphorus budget and use efficiency in China. Journal of Environmental Management, 370: 122974. DOI:10.1016/j.jenvman.2024.122974. Impact Factor: 8.0
  1. 姚宁*, 蒋昆昊, 谢文馨, 张东彦, 杨晓娟, 于强. 气候变化背景下山西省气象干旱时空演变特征. 农业机械学报, 2024, 55(1): 270-281 Yao, N., Jiang, K.H., Xie, W.X., Zhang, D.Y., Yang, X.J., Yu, Q., Temporal and spatial evolution of drought disasters in Shaanxi Province under background of climate change. Transactions of the Chinese Society for Agricultural Machiner, 2024, 55(1): 270-281

 

 

2023

  1. Chai, C.Q., Zhang, B.B.*, Li, Y.Y., Niu, W.H., Zheng, W.W., Kong, X.B., Yu, Q., Zhao, M.J., Xia, X.L., 2023. A new multi-dimensional framework considering environmental impacts to assess green development level of cultivated land during 1990 to 2018 in China. Environmental Impact Assessment Review, 98: 106927. Impact Factor: 7.9
  1. Fang, N.F., Zeng, Y., Ran, L.S., Wang, Z., Lu, X.X.*, Wang, Z.G., Yang, X.K., Jian, J.S., Yu, Q., Ni, L.S., Liu, C., Yue, C., Shi, Z.H.*, 2023. Substantial role of check dams in sediment trapping and carbon sequestration on the Chinese Loess Plateau. Communications Earth & Environment, 4(1): 65. Impact Factor: 7.9
  1. Guo, L.*, Liu, X.W., Alatalo, J.M., Wang, C.Y., Xu, J.C., Yu, H.Y., Chen, J., Yu, Q.*, Peng, C.H.*, Dai, J.H.*, Luedeling, E., 2023. Climatic drivers and ecological implications of variation in the time interval between leaf-out and flowering. Current Biology, 33(6): 3338-3349. Impact Factor: 9.2
  1. Guo, Y.J., Liu, J.C.*, Yang, X., Gao, C., Yu, Q., 2023. A new decision-making method for the renewal of agricultural irrigation wells: a case study of Songzhuang town, Tongzhou District, Beijing. Ecological Informatics, 78: 102316. Impact Factor: 5.1
  1. He, Q.S., Liu, D.L.*, Wang, B.*, Cowie, A., Simmons, A., Waters, C., Li, L.C., Feng, P.Y., Li, Y., de Voil, P., Huete, A., Yu, Q.*, 2023. Modelling interactions between cowpea cover crops and residue retention in Australian dryland cropping systems under climate change. Agriculture, Ecosystems & Environment, 353: 108536. Impact Factor: 6.6
  1. Jia, Q.L., Liu, Z.Q., Guo, C.H., Wang, Y.K., Yang, J.J., Yu, Q., Wang, J., Zheng, F.L., Lu, X.L.*, 2023. Relationship between photosynthetic CO2 assimilation and chlorophyll fluorescence for winter wheat under water deficit. Plants, 12: 3365. Impact Factor: 4.5
  1. Jiang, T.C., Wang, B., Duan, X.N., Liu, D.L., He, J.Q., He, L., Jin, N., Feng, H., Yu, Q.*, 2023. Prioritizing agronomic practices and uncertainty assessment under climate change for winter wheat in the Loess Plateau, China. Agricultural Systems, 212: 103770. Impact Factor: 6.6
  1. Li, C.C., Yu, Q.*, Zhang, Y.Q.*, Ma, N., Tian, J., Zhang, X.Z., 2023. Dominant drivers for terrestrial water storage changes are different in northern and southern China. Journal of Geophysical Research – Atmospheres, 128: e2022JD038074. Impact Factor: 4.4
  1. Li, L.C., Wang, B.*, Feng, P.Y., Jagermeyr, J., Asseng, S., Muller, C., Macadam, I., Liu, D.L.*, Waters, C., Zhang, Y.J., He, Q.S., Shi, Y., Chen, S., Guo, X.W., Li, Y., He, J.Q., Feng, H., Yang, G.J., Tian, H.Q., Yu, Q.*, 2023. The optimizing of model ensemble composition and size can enhance the robustness of crop yield projections. Communications Earth & Environment, 4: 362. Impact Factor: 7.9
  1. Li, L.C.#, Zhang, Y.#, Wang, B., Feng, P.Y., He, Q.S., Shi, Y., Liu, K., Harrison, M.T., Liu, D.L.*, Yao, N., Li, Y., He, J.Q., Feng, H., Siddique, K.H.M., Yu, Q.*, 2023. Integrating machine learning and environmental variables to constrain uncertainty in crop yield change projections under climate change. European Journal of Agronomy, 149: 126917. Impact Factor: 5.2
  1. Li, S.Y., Wang, B.*, Liu, D.L.*, Chen, C., Feng, P.Y., Huang, M.X., Wang, X.F., Shi, L.J., Waters, C., Huete, A., Yu, Q., 2023. Can agronomic options alleviate the risk of compound drought-heat events during the wheat flowering period in Southeastern Australia? European Journal of Agronomy, 153: 127030. Impact Factor: 5.2
  1. Li, Y.*, Yao, N., Liang, J.P., Wang, X.F., Niu, B., Jia, Y.L., Jiang, F.C., Yu, Q., Liu, D.L., Feng, H., He, H.L., Yang, G., Pulatove, A., 2023. Rational biochar application rate for cotton nutrient uptake, growth, yields, productivity and economic benefits under file-mulched trickle irrigation. Agricultural Water Management, 276: 108079. Impact Factor: 6.7
  1. Liu, J.D., Shen, Y.B.*, Zhou, G.S, Liu, D.L.*, Yu, Q., Du, J., 2023. Calibrating the Ångström-Prescott model with solar radiation data collected over long and short periods of time over the Tibetan Plateau. Energies, 16: 7093. Impact Factor: 3.2
  1. Liu, X.W., Wang, Y.Q., Fu, W.H., Yuan, Z.Y., Yu, Q., Peng, C.H., Koerner, S., Guo, L.*, 2023. Growing season temperature and precipitation affect nutrient resorption in herbaceous species through foliar stoichiometric control strategies. Plant and Soil. 10.1007/s11104-023-06214-0 Impact Factor: 4.9
  1. Ru, X.Y., Zhou, J., Gong, K.Y., He, Z.H., Dai, Z.W., Li, M.R., Feng, X.X., Yu, Q., Feng, H., He, J.Q.*, 2023. Climate warming may accelerate apple phenology but lead to divergent dynamics in late-spring frost and poor pollination risks in main apple production regions of China. European Journal of Agronomy, 150: 126945. Impact Factor: 5.2
  1. Ru, X.Y., Huang, Z., Jiang, Y., Luo, Q., Feng, X.X., Wang, J.H., Wang, Z., Li, M.R., Qu, Z.J., Su, B.F., Feng, H., Zhang, D., Liu, D.L., Yu, Q., He, J.Q.*, 2023. Evaluating late spring frost risks of apple in the loess plateau of China under future climate change with phenological modelling approach. Scientia Horticulture, 308: 111604. Impact Factor: 4.3
  1. Shi, L.J., Wang, B.*, Liu, D.L.*, Feng, P.Y., James Cleverly, Li, L.C., Zhang, G.X., Yu, Q.*, 2023. Performance of potential evapotranspiration models across different climatic stations in New South Wales, Australia. Journal of Hydrology: Regional Studies, 50: 101573. Impact Factor: 4.7
  1. Wang, X.F., Li, Y.*, Feng, H., Yu, Q., Fan, X.Y., Liu, C.C., Chen, J.Y., Yang, Z., Biswas, A., 2023. Combined biochar with cotton-sugarbeet intercropping increased water-fertilizer productivity and economic benefits under plastic mulched drip irrigation in Xinjiang, China. Industrial Crops & Products, 192: 116060. Impact Factor: 5.9
  1. Xiang, K.Y., Wang, B.*, Liu, D.L.*, Chen, C., Waters, C., Huete A., Yu, Q., 2023. Probabilistic assessment of drought impacts on wheat yield in south-eastern Australia. Agricultural Water Management, 284: 108359. Impact Factor: 6.7
  1. Zhang, Y.Q.*#, Li, C.C.#, Chiew F.H.S., Post D.A., Zhang, X.Z., Ma, N., Tian, J., Kong, D.D., Leung, L.R., Yu, Q., Shi, J.C., Liu, C.M., 2023. Southern Hemisphere dominates recent decline in global water availability. Science, 382: 579-584. Impact Factor: 56.9
  1. 闫雨杏, 吕肖良, 王亚凯, 于强*. 日光诱导叶绿素荧光研究进展:基于文献计量分析. 中国农业气象, 2023, 44(2): 106-122. Yan, Y.X., Lu, X.L., Wang, Y.K., Yu, Q.*, Bibliometric analysis of research and application of solor-induced chlorophyll fluorescence. Chinese Journal of Agrometeorology, 2023, 44(2): 106-122.
  1. 赵成, 梁盈盈, 冯浩, 王钊, 于强, 何建强*. 基于Sentinel-2遥感影像的黄土高原覆膜农田识别. 农业机械学报, 2023, 54(8): 180-192. Zhao, C., Liang, Y.Y., Feng, H., Wang, Z., Yu, Q., He, J.Q.*, 2023. Plastic-mulched farmland recognition in Loess Plateau on Sentinel-2 remote-sensing images. Transactions of the Chinese Society for Agricultural Machiner, 54(8): 180-192.
  1. 罗琦, 茹晓雅, 姜元, 冯浩, 于强, 何建强*. 基于机器学习与气象灾害指标的苹果相对气象产量预测. 农业机械学报, 2023, 54(9): 352-364. Luo, Q., Ru, X.Y., Jiang, Y., Feng, H., Yu, Q., He, J.Q.*, Prediction of apple relative meteorological yields based on machine learning and meteorological disaster indices. Transactions of the Chinese Society for Agricultural Machiner, 2023, 54(9): 352-364.
  1. 张志良, 和志豪, 茹晓雅, 蒋腾聪, 何英彬, 冯浩, 于强, 何建强*. 未来气候变化对中国哦马铃薯种植气候适宜性的影响. 中国农业科学, 2023, 56(18): 3530-3542. Zhang, Z.L., He, Z.H., Ru, X.Y., Jiang, T.C., He, Y.B., Feng, H., Yu, Q., He, J.Q.*, Influence of future climate change on the climate suitability of potato cultivation in China. Scientia Agricultura Sinica, 2023, 56(18): 3530-3542.

2022

  1. Chen, S.#, He, C.#, Huang, Z., Xu, X.J., Jiang, T.C., He, Z.H., Liu, J.D., Su, B.F.*, Feng, H., Yu, Q., He, J.Q.* 2022. Using support vector machine to deal with the missing of solar radiation data in daily reference evapotranspiration estimation in China. Agricultural and Forest Meteorology, 316: 108864. Impact Factor: 6.424
  1. Chen, S., He, L.*, Dong, W.B., Li, R.T., Jiang, T.C., Li, L.C., Feng, H., Zhao, K.F., Yu, Q., He, J.Q.*, 2022. Weather records from recent years performed better than analogue years when merging with real-time weather measurements for dynamic within-season predictions of rainfed maize yield. Agricultural and Forest Meteorology, 315: 108810. Impact Factor: 6.424
  1. Cheng, G., Harmel, R.D.*, Ma, L.W., Derner, J.D., Augustine, D.J., Bartling, P.N.S., Fang, Q.X., Williams, J.R., Zilverberg, C.J., Boone, R.B., Yu, Q.*, 2022. Evaluation of the APEX cattle weight gain component for grazing decision-support in the Western Great Plains. Rangeland Ecology & Management, 82: 1-11. Impact Factor: 2.398
  1. Cheng, H.Y., Yuan, M.S., Tang, L., Shen, Y.F.*, Yu, Q., Li, S.Q., 2022. Integrated microbiology and metabolomics analysis reveal responses of soil microorganisms and metabolic functions to phosphorus fertilizer on semiarid farm. Science of the Total Environment, 817: 152878. Impact Factor: 10.753
  1. Chu, X.S., Flerchinger, G.N., Ma, L.W., Fang, Q.X., Malone, R.W., Yu, Q., He, J.Q., Wang, N.J., Feng, H.*, Zou, Y.F., 2022. Development of RZ-SHAW for simulating plastic mulch effects on soil water, soil temperature, and surface energy balance in a maize field. Agricultural Water Management, 269: 107666. Impact Factor: 6.611
  1. Dong, J.Q., Li, L.H.*, Li, Y.Z, Yu, Q.*, 2022. Inter-comparisons of mean, trend and interannual variability of global terrestrial gross primary production retrieved from remote sensing approach. Science of the Total Environment, 822: 153343. Impact Factor: 10.753
  1. Feng, P.Y.*, Wang, B., Harrison, M., Wang, J., Liu, K., Huang, M.X., Liu, D.L., Yu, Q., Hu, K.L.*, 2022. Soil properties resulting in superior maize yields upon climate warming. Agronomy for Sustainable Development, 42(5): 85. Impact Factor: 7.832
  1. Feng, P.Y.*, Wang, B.*, Macadam, I., Taschetto, A.S., Abram, N.J., Luo, J.J., King, A.D., Chen, Y., Li, Y., Liu, D.L., Yu, Q., Hu, K.M.*, 2022. Increasing dominance of Indian ocean variability impacts Australian wheat yields. Nature Food, 3(10): 862-870. Impact Factor: 20.430
  1. He, J., Feng, P.Y., Wang, B., Zhuang, W., Zhang, Y.Q., Liu, D.L., Cleverly, J., Huete, A., Yu, Q.*, 2022. Centennial annual rainfall pattern changes show an increasing trend with higher variation over Northern Australia. Journal of Hydrometeorology, 23(8): 1333-1349. Impact Factor: 4.871
  1. He, Q.S., Liu, D.L.*, Wang, B.*, Li, L.C., Cowie, A., Simmons, A., Zhou, H.X., Tian, Q., Li, S.E., Li, Y., Liu, K., Yan, H.L., Harrison, M.T., Feng, P.Y., Waters, C., Li, G.D., de Voil, P., Yu, Q.*, 2022. Identifying effective agricultural management practices for climate change adaptation and mitigation: A win-win strategy in South-Eastern Australia. Agricultural Systems, 202: 103527. Impact Factor: 6.756
  1. He, Z.H., Gong, K.Y., Zhang, Z.L., Dong, W.B., Feng, H., Yu, Q., He, J.Q.*, 2022. What is the past, present, and future of scientific research on the Yellow River Basin? —A bibliometric analysis. Agricultural Water Management, 262: 107404. Impact Factor: 6.611
  1. He, Z.H., Jiang, T.C., Jiang, Y., Luo, Q., Chen, S., Gong, K.Y., He, L., Feng, H., Yu, Q., Tan, F.Y.*, He, J.Q.*, 2022. Gated recurrent unit models outperform other Machine learning models in prediction of minimum temperature in greenhouse Based on local weather data. Computers and Electronics in Agriculture, 202: 107416. Impact Factor: 6.757
  1. Hu, Z.H., Song, X., Wang, M.H., Ma, J., Zhang, Y.L., Xu, H.J., Hu, Z.M., Zhu, X.Y., Liu, H.L., Ma, J., Yu, Q., Ostle, N.J., Li, Y.T.*, Yue, C.*, 2022. Aridity influences root versus shoot contributions to steppe grassland soil carbon stock and its stability. Geoderma, 413: 115744. Impact Factor: 7.422
  1. Huang, M.X., Wang, J.*, Wang, B.*, Liu, D.L., Feng, P.Y., Yu, Q., Pan, X.B., Li, S.Y., Jiang, T.C., 2022. Dominant sources of uncertainty in simulating maize adaptation under future climate scenarios in China. Agricultural Systems, 199: 103411. Impact Factor: 6.765
  1. Jiang, T.C., Wang, B., Xu, X.J., Cao, Y.X., Liu, D.L., He, L., Jin, N., Ma, H.J., Chen, S., Zhao, K.F., Feng, H., Yu, Q., He, Y.B.*, He, J.Q.*, 2022. Identifying Sources of Uncertainty in Wheat Production Projections with Consideration of Crop Climatic Suitability under Future Climate. Agricultural and Forest Meteorology, 319: 108933. Impact Factor: 6.424
  1. Jin, N., Tao, B., Ren, W., He, L.*, Zhang, D.Y.*, Wang, D.C., Yu, Q., 2022. Assimilating remote sensing data into a crop model improves winter wheat yield estimation based on regional irrigation data. Agricultural Water Management, 266: 107583. Impact Factor: 6.611
  1. Leng, S., Huete, A.R., Cleverly, J., Gao, S.C., Yu, Q., Meng, X.Y., Qi, J.Y., Zhang, R.R., Wang, Q.F.*, 2022. Assessing the Impact of Extreme Droughts on Dryland Vegetation by Multi-satellite Solar-induced Chlorophyll Fluorescence. Remote Sensing, 14(7): 1581. Impact Factor: 5.349
  1. Leng, S., Huete, A.R., Cleverly, J., Yu, Q., Zhang, R.R., Wang, Q.F.*, 2022. Spatiotemporal variations of dryland vegetation phenology revealed by satellite-observed fluorescence and greenness across the North Australian Tropical Transect. Remote Sensing, 14(13): 2985. Impact Factor: 5.349
  1. Leng, S., Huete, A.R.*, Cleverly, J., Lu, X.L., Ma, X.L., Gao, S.C., Yu, Q., 2022. Response of dryland vegetation under extreme wet events with satellite measures of greenness and fluorescence. Science of the Total Environment, 842: 156860. Impact Factor: 10.753
  1. Li, L.C., Wang, B.*, Feng, P.Y., Liu, D.L., He, Q.S., Zhang, Y.J., Wang, Y.K., Li, S.Y., Lu, X.L., Yue, C., Li, Y., He, J.Q., Feng, H., Yang, G.J.*, Yu, Q., 2022. Developing machine learning models with multi-source environmental data to predict wheat yield in China. Computers and Electronics in Agriculture, 194: 106790. Impact Factor: 6.757
  1. Li, J.G., Xie, Z.Y.*, Qiu, X.C., Yu, Q., Bu, J.W., Sun, Z.Y., Long, R.J., Brandis, K.J., He, J., Feng, Q., Ramp, D., 2022. Heavy metal habitat: a novel framework for mapping heavy metal contamination over large-scale catchment with a species distribution model. Water Research, 226: 119310. Impact Factor: 13.400
  1. Li, S.Y., Wang, B.*, Feng, P.Y., Liu, D.L.*, Li, L.C., Shi, L.J., Yu, Q.*, 2022. Assessing climate vulnerability of historical wheat yield in south-eastern Australia's wheat belt. Agricultural Systems, 196: 103340. Impact Factor: 6.765
  1. Li, Y., Tang, J.Z., Wang, J.*, Zhao, G., Yu, Q., Wang, Y.X., Hu, Q., Zhang, J., Pan, Z.H., Pan, X.B., Xiao, D.P., 2022. Diverging water-saving potential across China's potato planting regions. European Journal of Agronomy, 134: 126450. Impact Factor: 5.722
  1. Li, Y., Wang, J.*, Chen, R.W., Wang, E.L., Wang, B., Yu, Q., Hu, Q., Pan, Z.H., Pan, X.B., 2022. Climate-smart planting for potato to balance economic return and environmental impact across China. Science of the Total Environment, 850: 158013. Impact Factor: 10.753
  1. Liu, J.D., Du, J.*, Liu, D.L., Linderholm, H.W., Zhou, G.S.*, Song, Y.L., Shen, Y.B., Yu, Q., 2022. Spatial and temporal variations in potential yields of highland barley in relation to climate change in tree rivers region of Tibetan Plateau from 1961 to 2020. Sustainability, 14: 7719. Impact Factor: 3.889
  1. Liu, Z.Q., Zhao, F., Liu, X.J., Yu, Q., Wang, Y.F., Peng, X.B., Cai, H.J., Lu, X.L.*, 2022. Direct estimation of photosynthetic CO2 assimilation from solar-induced chlorophyll fluorescence (SIF). Remote Sensing of Environment, 271: 112893. Impact Factor: 13.850
  1. Shi, L.J., Feng, P.Y., Wang, B.*, Liu, D.L., Zhang, H., Liu, J.D.*, Yu, Q.*, 2022. Assessing future runoff changes with different potential evapotranspiration inputs based on multi-model ensemble of CMIP5 projections. Journal of Hydrology, 612: 128042. Impact Factor: 6.708
  1. Shi, Y., Zhang, Y.J., Wu, B.Y., Wang, B., Li, L.C., Shi, H., Jin, N., Liu, D.L., Miao, R.Q., Lu, X.L., Geng, Q.L., Lu, C.Q., He, L., Fang, N.F., Yue, C., He, J.Q., Feng, H., Pan, S.F., Tian, H.Q.*, Yu, Q.*, 2022. Building social resilience in North Korea can mitigate the impacts of climate change on food security. Nature Food, 3(7): 499-511. Impact Factor: 20.430
  1. Wang, B.*, Spessa, A., Feng, P.Y., Hou, X., Yue, C., Luo, J.J.*, Ciais, P., Waters, C., Cowie, A., Nolan, R., Nikonovas, T., Jin, H.D., Walshaw, H., Wei, J.H., Liu, D.L., Yu, Q.*, 2022. Extreme fire weather is the major driver of severe bushfires in southeast Australia. Science Bulletin, 67(6): 655-664. Impact Factor: 20.557
  1. Wang, T.X., Li, N., Li, Y.*, Lin, H.X., Yao, N., Chen, X.G., Liu, D.L., Yu, Q., Feng, H., 2022. Impact of climate variability on grain yields of spring and summer maize. Computers and Electronics in Agriculture, 199: 107101. Impact Factor: 6.757
  1. Wang, Y.F.#, Zou, Y.F.#, Cai, H.J.*, Zeng, Y.J., He, J.Q., Yu, L.Y., Zhang, C., Saddique, Q., Peng, X.B., Siddique, K.H.M., Yu, Q., Su, Z.B., 2022. Seasonal variation and controlling factors of the evapotranspiration over a dry semi-humid cropland in the Guanzhong Plain, China. Agricultural Water Management, 259: 107242. Impact Factor: 6.611
  1. Wang, Y.K., Liu, Z.Q., Yu, Q., Liu, L.Y., Liu, X.J., Li, L.C., Jia, Q.L., Guo, C.H., Lu, X.L.*, 2022. Simulations of solar-induced chlorophyll fluorescence over crop canopies using the integrated APSIM model. Computers and Electronics in Agriculture. 203: 107494. Impact Factor: 6.757
  1. You, Y.F., Tian, H.Q.*, Pan, SF, Shi, H., Bian, ZH, Gurgel, A., Huang, YW, Kicklighter, D., Liang, X.Z., Lu, C.Q., Melillo, J., Miao, R.Q., Pan, N.Q., Reilly, J., Ren, W., Xu, R.T., Yang, J., Yu, Q., Zhang, J.T., 2022. Incorporating dynamic crop growth processes and management practices into a terrestrial biosphere model for simulating crop production in US: toward a scalable agricultural modelling framework. Agricultural and Forest Meteorology. 325: 109144. Impact Factor: 6.424
  1. Zhang, B.B., Li, X., Chen, H.B.*, Niu, W.H.*, Kong, X.B.*, Yu, Q., Zhao, M.J., Xia, X.L., 2022. Identifying opportunities to close yield gaps in China by use of certificated cultivars to estimate potential productivity. Land Use Policy, 117: 106080. Impact Factor: 6.189
  1. Zhang, H., Wang, B., Liu, D.L.*, Leslie, L.M., Shi, L.J., Zhang, M.X., Yu, Q.*, 2022. Individual and coupled effects of future climate and land use scenarios on water balance components in an Australian catchment. Atmosphere, 13(9): 1428. Impact Factor: 3.110
  1. Zhang, M.X., Rossel, R.A.V., Zhuqing, G.Z., Leys, J., Gray, J.M., Yu, Q., Yang, X.H.*, 2022. Dynamic modelling of water and wind erosion in Australia over the past two decades. Remote Sensing, 14(21): 5437. Impact Factor: 5.349
  1. Zhang, M.X., Yang, X.H., Cleverly, J., Huete, A., Zhang, H., Yu, Q.*, 2022. Heat wave tracker: a multi-method, multi-source heat wave measurement toolkit based on Google Earth Engine. Environmental Modelling & Software, 147: 105255. Impact Factor: 5.471
  1. Zhang, Q.Y., Jia, X.X., Li, T.C., Shao, M.A., Yu, Q., Wei, X.R.*, 2022. Intensification of water storage deficit in topsoil but not deep soil in a semi-humid forest after excluding precipitation for two years. Journal of Hydrology. 605: 127374. Impact Factor: 6.708
  1. Zeng, Y., Ran, L.S., Fang, N.F.*, Wang, Z., Xu, Z.C., Lu, X.X., Yu, Q., Wang, L., Yu, S.X., Shi, Z.H.*, 2022. How to balance green and grain in marginal mountainous areas? Earth's Future, 10(5): e2021EF002552. Impact Factor: 8.852
  1. 曹银轩, 黄卓, 徐喜娟, 陈上, 王钊, 冯浩, 于强, 何建强*. 黄土高原植被日光诱导叶绿素荧光对气象干旱的响应. 应用生态学报, 2022, 33(2): 457-466. Cao, Y.X., Huang, Z., Xu, X.J., Chen, S., Wang, Z., Feng, H., Yu, Q., He, J.Q.*, 2022. Response of vegetation photosynthesis to meteorological drought in loess Plateau based on SIF and SPEI. Chinese Journal of Applied Ecology, 33(2): 457-466.
  1. 康晓凤, 邬定荣*, 田琪, 谭姣姣, 马玉平, 于强*. 玉米发育模式在我国主要产区的适用性比较研究. 中国生态农业学报, 2022, 30(9): 1477-1489. Kang, X.F., Wu, D.R.*, Tian, Q., Tan, J.J., Ma, Y.P., Yu, Q.*, 2022. Comparison of applicability of phenological models in the main maize production areas of China. Chinese Journal of Eco-Agriculture, 30(9): 1477-1489.
  1. 徐芳, 何建强*, 朱晓华, 徐喜娟, 冯浩, 于强. 利用APSIM模型评估播期和种植密度对关中玉米气候生产力的影响. 陕西气象, 2022, 1: 59-65.
  1. 黄卓, 曹银轩, 徐喜娟, 陈上, 冯浩, 王钊, 于强, 何建强*. 基于多源GPP和ET产品的秦岭生态系统水分利用效率研究. 水土保持学报, 2022, 36(05): 181-194. Huang, Z., Cao, Y.X., Xu, X.J., Chen, S., Feng, H., Wang, Z., Yu, Q., He, J.Q.*, 2022. Study on the ecosystem water use efficiency of the Qinling Mountains with multi-source GPP and RT products. Journal of Soil and Water Conservation, 36(05): 181-194.
  1. 孙欣琪, 张蚌蚌, 柴朝卿, 牛文浩, 于强*. 沙地整治下榆林土地利用及土壤有机质时空分异特征. 农业工程学报, 2022, 38(24): 207-217. Sun, X.Q., Zhang, B.B., Chai, C.Q., Niu, W.H., Yu, Q.*, 2022. Spatial-temporal and characteristics of land use and soil organic matter under sandy land remediation in Yulin City of China. Transactions of the Chinese Society of Agricultural Engineering, 38(24): 207-217.
  1. 姜元, 茹晓雅, 罗琦, 李美荣, 王钊, 王景红, 冯浩, 张东, 苏宝峰, 于强, 何建强*, 基于Copula函数的陕西苹果晚霜冻特征分析. 农业工程学报, 2022, 38(23): 170-180. Jiang, Y., Ru, X.Y., Luo, Q., Li, M.R., Wang, Z., Wang, J.H., Feng, H., Zhang, D., Su, B.F., Yu, Q., He, J.Q.*, Analysis of the characteristics of apple later frost risks in Shaanix Province based on Copula functions. Transactions of the Chinese Society of Agricultural Engineering, 2022, 38(23): 170-180.

2021

  1. Chen, S., He, L., Cao, Y.X, Wang, R.H., Wu, L.H., Wang, Z, Zou, Y.F., Siddique, K.H.M., Xiong, W., Feng, H., Yu, Q., Wang, X.M.*, He, J.Q.*, 2021. Comparisons among four different upscaling strategies for cultivar genetic parameters in spring wheat phenology simulations with the DSSAT-CERES-Wheat model. Agricultural Water Management, 258: 107181. Impact Factor: 4.516
  1. Cheng, G., Harmel, R.D.*, Ma, L.W., Derner, J.D., Augustine, D.J., Bartling, P.N.S., Fang, Q.X., Williams, J.R., Zilverberg, C.J., Boone, R.B., Hoover, D., Yu, Q.*, 2021. Evaluation of APEX modifications to simulate forage production for grazing management decision-support in the Western US Great Plains. Agricultural Systems, 191: 103139. Impact Factor: 5.370
  1. Gan, R., Zhang, L., Yang, Y.T., Wang, E.L., Woodgate, W., Zhang, Y.Q.*, Haverd, V., Kong, D.D., Fischer, T., Chiew, F., Yu, Q.*, 2021. Estimating ecosystem maximum light use efficiency based on the water use efficiency principle. Environmental Research Letters, 16: 104032. Impact Factor: 6.793
  1. Gu, C.J., Tang, Q.H.*, Zhu, G.F., Ma, J.Z., Gu, C.L., Zhang, K., Sun, S., Yu, Q., Niu, S.L., 2021. Discrepant responses between evapotranspiration- and transpiration-based ecosystem water use efficiency to interannual precipitation fluctuations. Agricultural and Forest Meteorology, 303: 108385. Impact Factor: 5.734
  1. Huang, M.X., Wang, J.*, Wang, B., Liu, D.L., Feng, P.Y., Yu, Q., Pan, X.B., Waters, C., 2021. Assessing maize potential to mitigate the adverse effects of future rising temperature and heat stress in China. Agricultural and Forest Meteorology, 311: 108673. Impact Factor: 5.734
  1. Li, L.C., Wang, B., Feng, P.Y., Wang, H.H., He, Q.S., Wang, Y.K., Liu, D.L., Li, Y., He, J.Q., Feng, H., Yang, G.J.*, Yu, Q.*, 2021. Crop yield forecasting and associated optimum lead time analysis based on multi-source environmental data across China. Agricultural and Forest Meteorology, 308-309: 108558. Impact Factor: 5.734
  1. Li, Y.Y., Dan, L.*, Peng, J., Wang, J.B., Yang, F.Q., Gao, D.D., Yang, X.J. and Yu, Q.*, 2021. Response of growing season gross primary production to El Niño in different phases of the pacific decadal oscillation over eastern China based on bayesian model averaging. Advances in Atmospheric Sciences, 38(9): 1580-1595. Impact Factor: 3.158
  1. Liu, J.C., Khan, T.U., Nie, Z.G., Yu, Q.*, Feng, Z.K.*, 2021. Calibration and precise orientation determination of a gun barrel for agriculture and forestry work using a high-precision total station. Measurement, 173: 108494. Impact Factor: 3.927
  1. Liu, J.L., Li, S.Q., Yue, S.C., Tian, J.Q., Chen, H.*, Jiang, H.B., Siddique, K.H.M., Zhan, A.*, Fang, Q.X., Yu, Q., 2021. Soil microbial community and network changes after long-term use of plastic mulch and nitrogen fertilization on semiarid farmland. Geoderma, 396: 115086. Impact Factor: 6.114
  1. Liu, Z.Q., Guo, C.H., Bai, Y.W., Zhang, N.N., Yu, Q., Zhao, F., Lu, X.L.*, 2021. Far-red chlorophyll fluorescence radiance tracks photosynthetic carbon assimilation efficiency of dark reactions. Applied Sciences, 11(22): 10821. Impact Factor: 2.679
  1. Ma, Q., Li, Y.*, Feng, H., Yu, Q., Zou, Y.F., Liu, F.G., Pulatov, B., 2021. Performance evaluation and correction of precipitation data using the 20-year IMERG and TMPA precipitation products in diverse subregions of China. Atmospheric Research, 249: 105304. Impact Factor: 5.369
  1. Ning, J.C., Zhang, D.J.*, Yu, Q., 2021. Quantifying the efficiency of soil conservation and optimized strategies: A case study in a hotspot of afforestation in the Loess Plateau. Land Degradation & Development, 32(3): 1114-1126. Impact Factor: 4.977
  1. Rong, L.B., Gong, K.Y., Duan, F.Y., Li, S.K., Zhao, M., He, J.Q., Zhou, W.B.*, Yu, Q.*, 2021. Yield gap and resource utilization efficiency of three major food crops in the world - a review. Journal of Integrative Agriculture, 20(2): 349-362. Impact Factor: 2.848
  1. Wang, Y.F., Zeng, Y.J., Yu, L.Y., Yang, P.Q., der Tol, C.V., Yu, Q., Lu, X.L., Cai, H.J.*, Su, Z.B.*, 2021. Integrated modeling of canopy photosynthesis, fluorescence, and the transfer of energy, mass, and momentum in the soil–plant–atmosphere continuum (STEMMUS–SCOPE v1.0.0). Geoscientific Model Development, 14: 1379-1407. Impact Factor: 6.135
  1. Xu, F.#, Wang, B.#, He, C., Liu, D.L., Feng, P.Y., Yao, N., Zhang, R.H., Xu, S.T., Xue, J.Q., Feng, H., Yu, Q., He, J.Q.*, 2021. Optimizing sowing date and planting density can mitigate the impacts of future climate on maize yield: a case study in the Guanzhong Plain of China. Agronomy, 11(8): 1452. Impact Factor: 2.259
  1. Zhang, Q.Y., Jia, X.X., Li, T.C., Shao, M.A., Yu, Q., Wei, X.R.*, 2021. Decreased soil total phosphorus following artificial plantation in the Loess Plateau of China. Geoderma, 385(1): 114882. Impact Factor: 6.114
  1. Zhang, W.J., Zhang, B.P., Zhu, W.B.*, Tang, X.L., Li, F.J., Liu, X.S., Yu, Q., 2021. Comprehensive assessment of MOD07-derived near-surface air temperature using wide elevation-spanned measurements in China. Science of the Total Environment, 800: 149535. Impact Factor: 7.963
  1. Zhang, Y.J.*, Niu, H.S., Yu, Q., 2021. Impacts of climate change and increasing carbon dioxide levels on yield changes of major crops in suitable planting areas in China by the 2050s. Ecological Indicators, 125: 107588. Impact Factor: 4.958
  1. Zhang, Y.J.*, Yu, Q., 2021. Does agroecosystem model improvement increase simulation accuracy for agricultural N2O emissions? Agricultural and Forest Meteorology, 297: 108281. Impact Factor: 5.734
  1. Zhang, Y.J., Yu, Q.*, Li, J.*, 2021. Bioenergy research under climate change: a bibliometric analysis from a country perspective. Environmental Science and Pollution Research, 28(21): 26427-26440. Impact Factor: 4.223
  1. Zhang, Y.J.*, Zhao, J., Yan, Y.X., Shi, Y., Yu, Q.*, 2021. Relationship of population migration, crop production pattern, and socioeconomic development: Evidence from the early 21st century. Environmental Research Letters, 16(7): 074045. Impact Factor: 6.793
  1. Zhao, C.S., Pan, X., Yang, S.T.*, Xiang, H., Zhao, J., Gan, X.J., Ding, S.Y., Yu, Q., Yang, Y., 2021. Standards for environmental flow verification. Ecohydrology, 14(1): e2252. Impact Factor: 2.843
  1. Zhao, C.S., Pan, X., Yang, S.T.*, Xiang, H., Zhao, J., Gan, X.J., Ding, S.Y., Yu, Q., 2021. Effects and prediction of nonpoint source pollution on the structure of aquatic food webs. Ecohydrology, 14(1): e2257. Impact Factor: 2.843
  1. Zhao, J., Wang, L.*, Hou, X., Li, G.Y., Tian, Q., Chan, E., Ciais, P., Yu, Q., Yue, C.*, 2021. Fire regime impacts on post-fire diurnal land surface temperature change over North American boreal forest. Journal of Geophysical Research – Atmospheres, 126(23): e2021JD035589. Impact Factor: 4.261
  1. Zhu, T.T., Li, J.*, He, L., Wu, D.R., Tong, X.J., Mu, Q.Y., Yu, Q., 2021. The improvement and comparison of diffuse radiation models in different climatic zones of China. Atmospheric Research, 254: 105505. Impact Factor: 5.369
  1. 穆青云, 李俊*, 何亮, 邬定荣, 朱婷婷, 吕昌河, 于强. 青藏高原冬小麦生产潜力及其对气候变化的响应. 干旱区资源与环境, 2021, 35(7):92-99. Mu, Q.Y., Li, J.*, He, L., Wu, D.R., Zhu, T.T., Lu, C.H., Yu, Q., 2021. Potential yield of winter wheat in Qinghai-Tibet Plateau an its response to climate change. Journal of Arid Land Resources and Environment, 35(7):92-99.
  1. 孙梦华, 牛文浩, 张蚌蚌, 耿庆玲, 于强*. 黄河流域土地利用变化下生态服务价值时空演变及其响应—以陕甘宁地区为例. 应用生态学报, 2021, 32(11): 3913-3922. Sun, M.H., Niu, W.H., Zhang, B.B., Geng, Q.L., Yu, Q.*, 2021. Spatial-temporal evolution pattern and response of ecosystem service value under land use change in the Yellow River Basin: A case study of Shaanxi-Gansu-Ningxia region, Northwest China. Chinese Journal of Applied Ecology, 32(11): 3913-3922.
  1. 王欢欢, 赵杰, 岳超, 于强*. 黄土高原植被恢复对地表的冷却作用及变化规律. 水土保持学报, 2021, 35(3): 214-220. Wang, H.H., Zhao, J., Yue, C., Yu, Q.*, 2021. Cooling effect induced by afforestation on the Loess Plateau and its change law. Journal of Soil and Water Conservation, 35(3): 214-220.
  1. 王润红, 茹小雅, 蒋腾冲, 王景红, 王钊, 苏宝峰, 张东, 于强, 冯浩, 何建强*. 基于物候模型研究未来气候情景下陕西苹果花期的可能变化. 中国农业气象, 2021, 42(9): 729-745. Wang, R.H., Ru, X.Y., Jiang, T.C., Wang, J.H., Wang, Z., Su, B.F., Zhang, D., Yu, Q., Feng, H., He, J.Q.*, 2021. Based on the Phenological Model to Study the Possible Changes of Apple Flowering Dates under Future Climate Scenarios in Shaanxi Province. Chinese Journal of Agrometeorology, 42(9): 729-745.

2020

  1. Cheng, H.Y., Zhu, X.Z., Sun, R.X., Niu, Y.N, Yu, Q.*, Shen, Y.F.*, Li, S.Q., 2020. Effects of different mulching and fertilization on phosphorus transformation in upland farmland. Journal of Environmental Management, 253: 109717. Impact Factor: 5.647
  1. Cheng, H.Y., Yuan, M.S., Duan, Q.Y., Sun, R.X., Shen, Y.F.*, Yu, Q., Li, S.Q., 2020. Influence of phosphorus fertilization patterns on the bacterial community in upland farmland. Industrial Crops & Products, 155: 112761. Impact Factor: 4.244
  1. Chen, S., Jiang, T.C., Ma, H.J., He, C., Xu, F., Malone, R.W., Feng, H., Yu, Q., Siddique, K.H.M., Dong, Q.G., He, J.Q.*, 2020. Dynamic within-season irrigation scheduling for maize production in Northwest China: a method based on weather data fusion and yield prediction by DSSAT. Agricultural and Forest Meteorology, 285-286: 107928. Impact Factor: 4.651
  1. Cleverly, J.*, Vote, C., Isaac, P., Ewenz, C., Harahap, M., Beringer, J., David I. Campbell, D.I., Daly, E., Eamus, D., He, L., Hunt, J., Grace, P., Hutley, L.B., Laubach, J., McCaskill, M., Rowlings, D., Jonker, S.R., Schipper, L.A., Schroder, I., Teodosio, B., Yu, Q., Ward, P.R., Walker, J.P., Webb J.A., Grover, S.P.P., 2020. Carbon, water and energy fluxes in agricultural systems of Australia and New Zealand. Agricultural and Forest Meteorology, 287: 107934. Impact Factor: 4.651
  1. Ding, W.B., Wang, F.*, Jin, K., Han, J.Q., Yu, Q., Ren, Q.F., Shi, S.Y., 2020. Individual rainfall change based on observed hourly precipitation records on the Chinese Loess Plateau from 1983 to 2012. Water, 12: 2268. Impact Factor: 2.544
  1. Feng, P.Y., Wang, B.*, Liu, D.L.*, Waters, C., Xiao, D.P., Shi, L.J., Yu, Q.*, 2020. Dynamic wheat yield forecasts are improved by a hybrid approach using a biophysical model and machine learning technique. Agricultural and Forest Meteorology, 285-286: 107922. Impact Factor: 4.651
  1. Feng, P.Y., Wang, B.*, Liu, D.L.*, Ji, F., Niu, X.L., Ruan, H.Y., Shi, L.J., Yu, Q.*, 2020. Machine learning-based integration of large-scale climate drivers can improve the forecast of seasonal rainfall probability in Australia. Environmental Research Letters, 15(8): 084051. Impact Factor: 6.096
  1. Feng, P.Y., Wang, B.*, Luo, J.J., Liu, D.L., Water, C., Ji, F., Ruan, H.Y., Xiao, D.P., Shi, L.J., Yu, Q.*, 2020. Using large-scale climate drivers to forecast meteorological drought condition in growing season across the Australian wheatbelt. Science of the Total Environment, 724: 138162. Impact Factor: 6.551
  1. Geng, Q.L., Ren, Q.F., Yan, H.M., Nolan, R.H., Li, L.H., Zhao, X.N., Mu, X.M., Wu, P.T., Yu, Q.*, 2020. Target areas for harmonizing the Grain for Green programme in China's Loess Plateau. Land Degradation & Development, 31(3): 325-333. Impact Factor: 3.775
  1. He, C., Liu, J.D., Xu, F., Zhang, T., Chen, S., Sun, Z., Zheng, W.H., Wang, R.H., He, L., Feng, H., Yu, Q., He, J.Q.*, 2020. Improving solar radiation estimation in China base regional optimal combination of meteorological factors with machine learning methods. Energy Conversion and Management, 220: 113111. Impact Factor: 8.208
  1. He, L.*, Jin, N., Yu, Q., 2020. Impacts of climate change and crop management practices on soybean phenology changes in China. Science of the Total Environment, 707: 135638. Impact Factor: 6.551
  1. Huang, M.X., Wang, J.*, Wang, B., Liu, D.L., Yu, Q., He, D., Wang, N., Pan, X.B., 2020. Optimizing sowing window and cultivar choice can boost China’s maize yield under 1.5 °C and 2 °C global warming. Environmental Research Letters, 15: 024015. Impact Factor: 6.096
  1. Jiang, T.C.#, Liu, J.#, Gao, Y.J.#, Sun, Z., Chen, S., Yao, N., Ma, H.J., Feng, H., Yu, Q., He, J.Q.*, 2020. Simulation of plant height of winter wheat under soil water stress using modified growth function. Agricultural Water Management, 232: 106066. Impact Factor: 4.021
  1. Jiang, T.C.#, Dou, Z.H.#, Liu, J.#, Gao, Y.J., Malone, R.W., Chen, S., Feng, H., Yu, Q., Xue, G.N, He, J.Q.*, 2020. Simulating the influences of soil water stress on leaf expansion and senescence of winter wheat. Agricultural and Forest Meteorology, 291: 108061. Impact Factor: 4.651
  1. Jin, N., He, J.Q., Fang, Q.X., Chen, C., Ren, Q.F., He, L., Yao, N., Song, L.B., Yu, Q.*, 2020. The responses of maize yield and water use to growth stage-based irrigation on the Loess Plateau in China. International Journal of Plant Production, 14(4): 621-633. Impact Factor: 1.169
  1. Li, J.G., Li, Z.X.*, Brandis, K.J., Bu, J.W., Sun, Z.Y., Yu, Q., Ramp, D., 2020. Tracing geochemical pollutants in stream water and soil from mining activity in an alpine catchment. Chemosphere, 242: 125167. Impact Factor: 5.778
  1. Li, C.C., Zhang, Y.Q.*, Shen, Y.J., Yu, Q., 2020. Decadal water storage decrease driven by vegetation changes in the Yellow River Basin. Science Bulletin, 65(22): 1859-1861. Impact Factor: 9.511
  1. Liang, W.*, Zhang, W.B., Jin, Z., Yan, J.W., Lu, Y.H., Li, S., Yu, Q., 2020. Rapid urbanization and agricultural intensification increase regional evaporative water consumption of the Loess Plateau. Journal of Geophysical Research - Atmospheres, 125(23): e2020JD033380. Impact Factor: 3.820
  1. Liu, Y.Y., Li, J.*, Liu, S.C., Yu, Q., Tong, X.J., Zhu, T.T., Gao, X.X., Yu, L.X., 2020. Sugarcane leaf photosynthetic light responses and their difference between varieties under high temperature stress. Photosynthetica, 58(4): 1009-1018. Impact Factor: 2.562
  1. Ma, H.J., Malone, R.W., Jiang, T.C., Yao, N., Chen, S., Song, L.B., Feng, H., Yu, Q., He, J.Q.*, 2020. Estimating Crop Genetic Parameters for DSSAT with Modified PEST Software. European Journal of Agronomy, 115: 126017. Impact Factor: 3.726
  1. Ma, X.L.*, Huete, A., Moore, C.E., Cleverly, J., Hutley, L.B., Beringer, J., Leng, S., Xie, Z.Y., Yu, Q., Eamus, D., 2020. Spatiotemporal partitioning of savanna plant functional type productivity along NATT. Remote Sensing of Environment, 246: 111855. Impact Factor: 9.085
  1. Saddique, Q., Cai, H.J.*, Xu, J.T., Ajaz, A., He, J.Q., Yu, Q., Wang, Y.F., Chen, H., Khan, M.I., Liu, D.L., He, L., 2020. Analyzing adaptation strategies for maize production under future climate change in Guanzhong Plain, China. Mitigation and Adaptation Strategies for Global Change, 25: 1523-1543. Impact Factor: 3.230
  1. Shen, J.X.*, Huete, A., Ma, X.L., Tran, N.N., Joiner, J., Beringer, J., Eamus, D., Yu, Q., 2020. Spatial pattern and seasonal dynamics of photosynthesis activity across Australian rainfed croplands. Ecological Indicators, 108: 105669. Impact Factor: 4.229
  1. Shi, L.J., Feng, P.Y., Wang, B.*, Liu, D.L.*, Cleverly, J., Fang, Q.X., Yu, Q.*, 2020. Projecting potential evapotranspiration change and quantifying its uncertainty under future climate scenarios: a case study in south-eastern Australia. Journal of Hydrology, 584: 124756. Impact Factor: 4.500
  1. Shi, L.J., Feng, P.Y., Wang, B.*, Liu, D.L.*, Yu, Q.*, 2020. Quantifying future drought change and associated uncertainty in southeastern Australia with multiple potential evapotranspiration models. Journal of Hydrology,590: 125394. Impact Factor: 4.500
  1. Shi, Y., Jin, N.*, Ma, X.L., Wu, B.Y, He, Q.S., Yue, C., Yu, Q.*, 2020. Attribution of climate and human activities to vegetation change in China using machine learning techniques. Agricultural and Forest Meteorology, 294: 108146. Impact Factor: 4.651
  1. Sima, M., Fang, Q.X.*, Qi, Z.M., Yu, Q., 2020. Direct assimilation of measured soil water content in Root Zone Water Quality Model calibration for deficit-irrigated maize. Agronomy Journal, 112: 844-860. Impact Factor: 1.683
  1. Song, Y., Wang, J.*, Yu, Q., Huang, J.X., 2020. Using MODIS LAI data to monitor spatio-temporal change of winter wheat phenology in response to climate warming. Remote Sensing, 12(5): 786. Impact Factor: 4.509
  1. Wang, B.#, Feng, P.Y.#, Water, C., Cleverly, J., Liu, D.L., Yu, Q.*, 2020. Quantifying the impacts of pre-occurred ENSO signals on wheat yield variation using machine learning in Australia. Agricultural and Forest Meteorology, 291: 108043. Impact Factor: 4.651
  1. Wang, B.*, Feng, P.Y., Liu, D.L.*, O’leary G.J., Macadam, I., Waters, C., Asseng, S., Cowie, A.L., Jiang, T.C., Xiao, D.P., Ruan, H.Y., He, J.Q., Yu, Q.*, 2020. Sources of uncertainty for wheat yield projections under future climate are site-specific. Nature Food, 1(11): 720-728
  1. Wang, H.H., Yue, C.*, Mao, Q.Q., Zhao, J., Ciais, P., Li, W., Yu, Q., Mu, X.M., 2020. Vegetation and species impacts on soil organic carbon sequestration following ecological restoration over the Loess Plateau, China. Geoderma, 371: 114389. Impact Factor: 4.848
  1. Wu, D.R., Wang, P.J., Jiang, Z.Y., Huo, Z.G., Shi, K.Q., Yang, Y., Yu, Q.*, 2020. Use of a plastic temperature response function reduces simulation error of crop maturity date by half. Agricultural and Forest Meteorology, 280: 107770. Impact Factor: 4.651
  1. Wu, D.R., Huo, Z.G., Wang, P.J., Song, Y.L., Yang, J.Y., Zhao, H.R., Yang, Y., Yu, Q.*, 2020. Plastic temperature response function accurately simulates crop flowering/heading date in a simple and effective way. Agronomy Journal, 112(5): 3832-3846. Impact Factor: 1.683
  1. Yang, X.H., Zhang, X.P.*, Lu, D., Yin, S.Q., Zhang, M.X., Zhuqing, G.Z., Yu, Q., 2020. Remote sensing estimation of the soil erosion cover-management factor over China’s Loess Plateau. Land Degradation & Development, 31(5): 1942-1955. Impact Factor: 3.775
  1. Yao, N., Li, Y., Xu, F., Liu, J., Chen, S., Ma, H.J., Chau, H.W., Liu, D.L., Li, M., Feng, H., Yu, Q., He, J.Q.*, 2020. Permanent wilting point plays an important role in simulating winter wheat growth under water deficit conditions. Agricultural Water Management, 229: 105954. Impact Factor: 4.021
  1. Ye, Z.P., Ling, Y., Yu, Q., Duan, H.L., Kang, H.J., Huang, G.M., Duan, S.H., Chen, X.M., Liu, Y.G.*, Zhou, S.X.*, 2020. Quantifying light response of leaf-scale water-use efficiency and its interrelationships with photosynthesis and stomatall conductance in C3 and C4 species. Frontiers in Plant Science-Plant Physiology, 11: 374. Impact Factor: 4.402
  1. Zhang, H., Wang, B.*, Liu, D.L.*, Zhang, M.X., Leslie, L.M.M, Yu, Q.*, 2020. Using an improved SWAT model to simulate hydrological responses to land use change: a case study of a catchment in tropical Australia. Journal of Hydrology, 585: 124822. Impact Factor: 4.500
  1. Zhang, M.X., Wang, B., Cleverly, J., Liu, D.L., Feng, P.Y., Zhang, H., Huete, A., Yang, X.H.*, Yu, Q., 2020. Creating new near-surface air temperature datasets to understand elevation-dependent warming in the Tibetan Plateau. Remote Sensing, 12: 1722. Impact Factor: 4.509
  1. Zhang, M.X., Wang, B., Liu, D.L., Liu, J.D., Zhang, H., Feng, P.Y., Kong, D.D., Cleverly, J., Yang, X.H., Yu, Q.*, 2020. Incorporating dynamic factors for improving a GIS-based solar radiation model. Transactions in GIS, 24(2): 423-441. Impact Factor: 2.119
  1. Zhang, Q.Y., Jia, X.X., Wei, X.R., Shao, M.A., Li, T.C., Yu, Q.*, 2020. Total soil organic carbon increases but becomes more labile after afforestation in China’s Loess Plateau. Forest Ecology and Management, 461: 117911. Impact Factor: 3.170
  1. Zhang, Y.J.* and Yu, Q., 2020. What is the best article publishing strategy for early career scientists? Scientometrics, 122: 397-408. Impact Factor: 2.867
  1. Zhang, Y.J.* and Yu, Q.*, 2020. Characteristics of high-impact agronomic journals. Agronomy Journal, 112(5): 3878-3890. Impact Factor: 1.683
  1. Zhang, Y.J.* and Yu, Q., 2020. Identification of current research intensity and influence factors of agricultural nitrogen loss from cropping systems. Journal of Cleaner Production, 276: 123308. Impact Factor: 7.246
  1. Zhao, C.S., Yang, Y., Yang, S.T.*, Xiang, H., Ge, Y.R., Zhang, Z.S., Zhao, Y., Yu, Q., 2020. Effects of spatial variation in water quality and hydrological factors on environmental flows . Science of the Total Environment, 728: 138695. Impact Factor: 6.551
  1. Zhao, F.N., Zhou, S., Wang, R.Y., Zhang, K., Wang, H., Yu, Q.*, 2020. Quantifying key model parameters for wheat leaf gas exchange under different environmental conditions. Journal of Integrative Agriculture, 19(9): 2188-2205. Impact Factor: 1.984
  1. Zhu, T.T., Li, J.*, Liu, Y.Y., Tong, X.J., Yu, Q., 2020. Leaf photosynthetic light response of summer maize: comparison of models and analysis of parameters. Photosynthetica, 58(1): 19-28. Impact Factor: 2.562
  1. Zhuang, W., Shi, H., Ma, X.L., Cleverly, J., Beringer, J., Zhang, Y., He, J., Eamus, D., Yu, Q.*, 2020. Improving estimation of seasonal evapotranspiration in Australian tropical savannas using a Flexible Drought Index. Agricultural and Forest Meteorology, 295: 108203. Impact Factor: 4.651
  1. ZhuQing, G.Z., Yang, X.H.*, Fei, J., Liu, D.L., Yu, Q., 2020. Extreme rainfall, rainfall erosivity and hillslope erosion in Australian Alpine region and their future changes. International Journal of Climatology, 40(2): 1213-1227. Impact Factor: 3.928
  1. 弓开元, 何亮, 邬定荣, 吕昌河, 李俊, 周文彬, 杜军, 于强*. 青藏高原高寒区青稞光温潜力和产量差时空分布特征及其对气候变化的响应. 中国农业科学, 2020, 53(4): 720-733. Gong, K.Y., He, L., Wu, D.R., Lu, C.H., Li, J., Zhou, W.B., Du, J., Yu, Q.*, 2020. Spatial-Temporal variations of photo-temperature productivity and yield gap of highland barley and its response to climate change in the cold regions of the Tibetan Plateau. Scientia Agricultura SINICA, 53(4): 720-733.
  1. 李凤, 李毅*, 于强, 彭艳, 姚宁, 冯浩, 宋小燕．1961-2019年陕西省极端旱涝事件的时空演变规律．陕西气象, 2020, 6: 23-29.
  1. Yue, C.*, Ciais, P., Houghton, R.A., Nassikas, A.A., 2020. Contribution of use to the interannual variability of the land carbon cycle. Nature Communications, 11: 3170. Impact Factor: 12.121
  1. Lu, X.L., Liu, Z.Q., Zhao, F., Tang, J.W.*, 2020. Comparison of total emitted solar-induced chlorophyll fluorescence (SIF) and top-of-canopy (TOC) SIF in estimating photosynthesis. Remote Sensing of Environment, 251: 112083. Impact Factor: 9.085
  1. Hu, Z.H., Chen, H.Y.H., Yue, C., Gong, X.Y., Shao, J.J., Zhou, G.Y., Wang, J.W., Wang, M.H., Xia, J.Y., Li, Y.T.*, Zhou, X.H.*, Michaletz, S.T., 2020. Traits mediate drought effects on wood carbon fluxes. Global Change Biology, 26: 3429-3442. Impact Factor: 8.997

2019

  1. Bai, J., Shi, H.*, Yu, Q., Xie, Z.Y., Li, L.H., Luo, G.P., Jin, N., Li, J., 2019. Satellite-observed vegetation stability in response to changes in climate and total water storage in Central Asia. Science of the Total Environment, 659: 862-871. Impact Factor: 4.610
  1. Fang,Q.X.*, Ma, L.W., Harmel, R.D., Yu, Q., Sima, M.W., Bartling, P.N.S., Malone, R.W., Nolan, B.T.., Doherty, J., 2019. Uncertainty of Model Calibration with Irrigation Treatments Using Pest Optimization Algorithm. Agronomy, 9: 241. Impact Factor: 1.419
  1. Feng, P.Y.*, Liu, D.L., Wang, B., Waters, C., Zhang, M.X., Yu, Q., 2019. Projected changes in drought across the wheat belt of south-eastern Australia using a downscaled climate ensemble. International Journal of Climatology, 39(2): 1041-1053. Impact Factor: 3.100
  1. Feng, P.Y., Wang, B., Liu, D.L., Waters, C., Yu, Q.*, 2019. Incorporating machine learning with biophysical model can improve the evaluation of climate extremes impacts on wheat yield in south-eastern Australia. Agricultural and Forest Meteorology, 275: 100-113. Impact Factor: 4.039
  1. Feng, P.Y., Wang, B., Liu, D.L., Yu, Q.*, 2019. Machine learning-based integration of remotely-sensed drought factors can improve the estimation of agricultural drought in south-eastern Australia. Agricultural Systems, 173: 303-316. Impact Factor: 3.004
  1. Geng, Q.L., Ren, Q.F., Nolan, R.H., Wu, P.T., Yu, Q.*, 2019. Assessing China’s agricultural water use efficiency in a green-blue water perspective: a study based on data envelopment analysis. Ecological Indicators, 96: 329-335. Impact Factor: 3.983
  1. Gu, C.J., Mu, X.M., Gao, P.*, Zhao, G.J., Sun, W.Y., Yu, Q., 2019. Rainfall erosivity and sediment load over the Poyang Lake Basin under variable climate and human activities since the 1960s. Theoretical and Applied Climatology, 136(1-2): 15-30. Impact Factor: 2.321
  1. Guo, L., Wang, J.H., Li, M.J., Xu, J.C., Cheng, J.M., Gang, C.C., Yu, Q., Chen, J., Peng, C.H.*, Luedeling, E., 2018. Distribution margins as natural laboratories to infer species’s flowering response to climate warming and implications for frost risk. Agricultural and Forest Meteorology, 268: 299-307. Impact Factor: 4.039
  1. Guo, L.P., Mu, X.M.*, Hu, J.M.*, Gao, P.*, Zhang, Y.F., Liao, K.T., Bai, H., Chen, X.L., Song, Y.J., Jin, N., Yu, Q., 2019. Assessing Impacts of climate change and human activities on streamflow and sediment discharge in the Ganjiang River Basin (1964-2013). Water, 11(8): 1679
  1. Tang, J.Z., Wang, J.*, Fang, Q.X., Dayananda, B., Yu, Q., Zhao, P.Y., Yin, H., Pan, X.B., 2019. Identifying agronomic options for potato production and conserving water resources in the agro-pastoral ecotone in North China Plain. Agricultural and Forest Meteorology, 272-273: 91-101. Impact Factor: 4.039
  1. Wang, B.*, Feng, P.Y., Chen, C., Liu, D.L., Waters, C., Yu, Q., 2019. Designing wheat ideotypes to cope with future changing climate in south-eastern Australia. Agricultural Systems, 170: 9-18. Impact Factor: 3.004
  1. Wang, B.R., Zhao, X.D., Liu, Y., Fang, Y., Ma, R.T., Yu, Q., An, S.S.*, 2019. Using soil aggregate stability and erodibility to evaluate the sustainability of large-scale afforestation of Robinia pseudoacacia and Caragana korshinskii in the Loess Plateau. Forest Ecology and Management, 450: 117491. Impact Factor: 3.126
  1. Wu, D.R., Wang, P.J., Jiang, C.Y., Yang, J.Y., Huo, Z.G., Yu, Q.*, 2019. Measured phenology response of unchanged crop varieties to long-term historical climate change. International Journal of Plant Production, 13(1): 47-58. Impact Factor: 0.886
  1. Yang, X.Y.*, Li, J., Yu, Q., Ma, Y.C., Tong, X.J., Feng, Y., Tong, Y.X., 2019. Impacts of diffuse radiation fraction on light use efficiency and gross primary production of winter wheat in the North China Plan. Agricultural and Forest Meteorology, 275: 233-242. Impact Factor: 4.039
  1. Zhang, H., Wang, B., Liu, D.L.*, Zhang, M.X., Feng, P.Y., Cheng, L., Yu, Q.*, Eamus, D., 2019. Impacts of future climate change on water resource availability of eastern Australia: a case study of Manning River Basin. Journal of Hydrology, 573: 49-59. Impact Factor: 3.727
  1. Zhao, C.S., Yang, Y., Yang, S.T.*, Xiang, H., Wang, F., Chen, X., Zhang, H.M., Yu, Q., 2019. Impact of spatial variations in water quality and hydrological factors on the food-web structure in urban aquatic environments. Water Research, 153: 121-133. Impact Factor: 7.051
  1. Zhao, F.N.*, Wang, R.Y., Zhang, K., Lei, J., Yu, Q.*, 2019. Predicting spring wheat yields based on water use-yield production function in a semi-arid climate. Spanish Journal of Agricultural Research, 17(2): e1201. Impact Factor: 1.035
  1. ZhuQing, G.Z.*, Yang, X.H., Yu, B.F., Tulau, M., Mclnnes-Clarke, S., Nolan, R.H., Du, Z.Y., Yu, Q., 2019. Estimation of event-based rainfall erosivity from radar after wildfire. Land Degradation & Development, 30: 33-48. Impact Factor: 7.270
  1. 何亮*, 钱者东, 靳宁, 于强, 侯英雨. 格点天气预报数据与机理模型耦合的冬小麦干旱预警方法. 农业机械学报, 2019, 50(9): 170-176. He, L.*, Qian, Z.D., Jin, N., Yu, Q., Hou, Y.Y., 2019. Drought early warning of winter wheat based on soil water dynamic model coupled with grid weather forecast data. Transactions of the Chinese Society for Agricultural Machiner, 50(9): 170-176.
  1. 刘杨杨, 李俊*, 于强, 刘少春, 同小娟, 余凌翔. 甘蔗叶片光合CO2响应参数分析及其品种间差异. 中国农业气象, 2019, 40(10): 637-646. Liu, Y.Y., Li, J.*, Yu, Q., Liu, S.C., Tong, X.J., Yu, L.X., 2019. Sugarcane leaf photosynthetic responses parameters and their difference among varieties. Chinese Journal of Agrometeorology, 40(10): 637-646.
  1. 汤秋鸿*, 刘星才, 李哲, 运晓博, 张学君, 于强, 李俊, 张永勇, 崔慧娟, 孙思奥, 张弛, 唐寅, 冷国勇. 陆地水循环过程的综合集成与模拟. 地理科学进展, 2019, 34(2): 115-123. Tang, Q.H.*, Liu, X.C., Li, Z., Yun, X.B., Zhang, X.J., Yu, Q., Li, J., Zhang, Y.Y., Cui, H.J., Sun, S.A., Zhang, C., Tang, Y., Leng, G.Y., Integrated water systems model for terrestrial water cycle simulation. Advances in Earth Science, 34(2): 115-123

2018

  1. Feng, P.Y., Wang, B., Liu, D.L., Xing, H.T., Ji, F., Macadam, I., Ruan, H.Y., Yu, Q.*, 2018. Impacts of rainfall extremes on wheat yield in semi-arid cropping systems in eastern Australia. Climatic Change, 147(3-4): 555-569. Impact Factor: 3.537
  2. Gan, R., Zhang, Y.Q.*, Shi, H., Yang Y.T., Eamus, D., Cheng, L., Chiew, F.H.S., Yu, Q., 2018. Use of satellite leaf area index estimating evapotranspiration and gross assimilation for Australian ecosystems. Ecohydrology, 11(5): e1974. Impact Factor: 2.755
  3. Guo, L.P., Yu, Q., Gao, P., Nie, X.F., Liao, K.T., Chen, X.L., Hu, J.M.*, Mu, X.M.*, 2018. Trend and change-point analysis of streamflow and sediment discharge of the Gongshui River in China during the last 60 years. Water, 10(9): 1273. Impact Factor: 2.069
  4. He, L.*, Cleverly, J., Wang, B., Jin, N., Mi, C.R., Liu, D.L., Yu, Q., 2018. Multi-model Ensemble Projections of Future Extreme Heat Stress on Rice across Southern China. Theoretical and Applied Climatology, 133(3-4): 1107-1118. Impact Factor: 2.321
  5. He, L.*, Li, J., Harahap, M., Yu, Q., 2018. Scale-specific controller of carbon and water exchanges over wheat field identified by Ensemble Empirical Mode Decomposition. International Journal of Plant Production, 12(1): 43-52. Impact Factor: 0.886
  6. Hu, Z.M.*, Shi, H.*, Cheng, K.L., Wang, Y.P., Piao, S.L., Li, Y., Zhang, L., Xia, J.Y., Zhou, L., Yuan, W.P., Running, S.W., Li, L.H., Hao, Y.B., He, N.P., Yu, Q., Yu, G.R., 2018. Joint structural and physiological control on the interannual variation in productivity in a temperate grassland: a data-model comparison. Global Change Biology, 24: 2965-2979. Impact Factor: 8.997
  7. Jin, K., Wang, F.*, Yu, Q., Gou, J.J., Liu, H.H., 2018. Varied degrees of urbanization effects on observed surface air temperature trends in China. Climate Research, 76(2): 131-143. Impact Factor: 1.954
  8. Jin, N., Ren, W., Tao, B., He, L., Ren, Q.F., Li, S.Q., Yu, Q.*, 2018. Effects of water stress on water use efficiency of irrigated and rainfed wheat in the Loess Plateau, China. Science of the Total Environment, 642: 1-11. Impact Factor: 4.610
  9. Li, L.H.*, Wang, Y.P., Arora, V.K., Eamus, D., Shi, H., Li, J., Cheng, L., Cleverly, J., Hajima, T., Ji, D.Y., Jones, C., Kawamiya, M., Li, W.P., Tjiputra, J., Wiltshire, A., Zhang, L., Yu, Q., 2018. Evaluating global land surface models in CMIP5: analysis of ecosystem water- and light-use efficiency, and rainfall partitioning. Journal of Climate, 31: 2995-3008. Impact Factor: 4.661
  10. Li, Y., Shi, H.*, Zhou, L., Eamus, D., Huete, A., Li, L.H., Cleverly, J., Hu, Z.M., Harahap, M., Yu, Q., He, L., Wang, S.Q.*, 2018. Disentangling climate and LAI effects on seasonal variability in water use efficiency across terrestrial ecosystems in China. Journal of Geophysical Research – Biogeosciences, 123(8): 2429-2443. Impact Factor: 3.484
  11. Shen, J.X.*, Huete, A., Tran, N.N., Devadas, R., Ma, X.L., Eamus, D., Yu, Q., 2018. Diverse sensitivity of winter crops over the growing season to climate and land surface temperature across the rainfed cropland-belt of eastern Australian. Agriculture Ecosystems & Environment, 254: 99-110. Impact Factor: 3.541
  12. Tang, J.Z., Wang, J.*., Wang, E.L., Yu, Q., Yin, H., He, D., Pan X.B., 2018. Identifying key meteorological factors to yield variation of potato and the optimal planting date in the agro-pastoral ecotone in North China. Agricultural and Forest Meteorology, 256-257: 283-291. Impact Factor: 4.039
  13. Tian, H.Q., Lu, C.Q., Pan, S.F., Yang, J., Miao, R.Q., Ren, W., Yu, Q., Fu, B.J., Jin, F.F., Lu, Y.L., Melillo, J., Ouyang, Z.Y., Palm, C., Reilly, J., 2018. Optimizing resource use efficiencies in the food-energy-water nexus for sustainable agriculture: from conceptual model to decision support system. Current Opinion in Environmental Sustainability, 33: 104-113. Impact Factor: 4.186
  14. Wang, B.*, Zheng, L.H., Liu, D.L., Ji, F., Clark, A., Yu, Q., 2018. Using multi-model ensembles of CMIP5 global climate models to reproduce observed monthly rainfall and temperature with machine learning methods in Australia. International Journal of Climatology, 38(13): 4891-4902. Impact Factor: 3.100
  15. Wang, B.*, Liu, D.L., O’Leary, S.J., Asseng, S., Macadam, I., Lines-Kelly, R., Yang, X.H., Clark, A., Crean, J., Sides, T., Xing, H.T., Mi, C.R., Yu, Q. 2018. Australian wheat production expected to decrease by the late 21st century. Global Change Biology, 24: 2403-2415. Impact Factor: 8.997
  16. Wang, B.*, Liu, D.L., Waters, C., Yu, Q., 2018. Quantifying sources of uncertainty in projected wheat yield changes under climate change in eastern Australia. Climatic Change, 151: 259-273. Impact Factor: 3.537
  17. Yang, X.Y., Gregory S. McMaster, G.S., Yu, Q.*, 2018. Spatial patterns of relationship between wheat yield and yield components in China. International Journal of Plant Production, 12(1): 61-71. Impact Factor: 0.886
  18. Zhao, C.S., Shao, N.F., Yang, S.T.*, Xiang, H., Lou, H.Z., Sun, Y., Yang, Z.Y., Zhang, Y., Yu, X.Y., Zhang, C.B., Yu, Q., 2018. Identifying the principal driving factors of water ecosystem dependence and the corresponding indicator species in a pilot City, China. Journal of Hydrology, 556: 488-499. Impact Factor: 3.727
  19. Zhao, C.S., Zhang, Y., Yang, S.T.*, Xiang, H., Sun, Y., Yang, Z.Y., Yu, Q. and Lim, R.P., 2018. Quantifying effects of hydrological and water quality disturbances on fish with food-web modeling. Journal of Hydrology, 560: 1-10. Impact Factor: 3.727
  20. Zhao, F.N.*, Lei, J., Wang, R.Y., Wang, H.L., Zhang, K., Yu, Q., 2018. Determining agricultural drought for spring wheat with statistical models in a semi-arid climate. Journal of Agricultural Meteorology, 74(4): 162-172. Impact Factor: 1.037
  21. Zhu, Q.*, Mi, C.R., Liu, D.L., He, L., Kuang, Z.M., Fang, Q.X., Ramp, D., Li, L., Wang, B., Chen, Y.L., Li, J., Jin. N., Yu, Q.*, 2018. Spatio-temporal distribution of sugarcane potential yields and yield gaps in Southern China. European Journal of Agronomy, 92: 72-83 Impact Factor: 3.192
  22. 何亮*, 侯英雨, 于强, 靳宁. 不同空间分辨率驱动数据对作物模型区域模拟的影响研究. 农业机械学报, 2018, 49(2): 241-251. He, L.*, Hou, Y.Y., Yu, Q., Jin, N., 2018. Influence of different resolutions data on regional simulation of crop model. Transactions of the Chinese Society for Agricultural Machiner. 49(2): 241-251.
  23. 何亮*, 吴门新, 侯英雨, 赵刚, 靳宁, 于强. 基于极值概率分布函数的中国早稻高温热害时空分布统计特征. 中国生态农业学报, 2018, 26(11): 1601-1612. He, L.*, Wu, M.X., Hou, Y.Y., Zhao, G., Jin, N., Yu, Q., 2018. Statistical characteristics of heat stress on early rice based on the extreme values distribution in China. Chinese Journal of Eco-Agriculture, 26(11): 1601-1612.
  24. 蒋腾冲, 窦子荷, 姚宁, 冯浩, 于强, 何建强*. 不同水分胁迫情景下冬小麦生长发育的RZWQM2模拟. 农业机械学报, 2018, 49(7): 205-216. Jiang, T.C., Dou, Z.H., Yao, N., Feng, H., Yu, Q., He, J.Q.*, 2018. Simulation of winter wheat growth under different scenarios of water stress with RZWQM2 model. Transactions of the Chinese Society for Agricultural Machiner. 49(7): 205-216.
  25. 李华龙, 窦子荷, 蒋腾冲, 冯浩, 于强, 何建强*. 水分胁迫对冬小麦冠层辐射截获率和利用效率的影响. 农业机械学报, 2018, 49(9): 226-237. Li, H.L., Dou, Z.H., Jiang, T.C., Feng, H., Yu, Q., He, J.Q.*, 2018. Influences of soil water stress on solar radiation interception and use efficiency of winter wheat canopy. Transactions of the Chinese Society for Agricultural Machiner, 49(9): 226-237.
  26. 杨晓亚*, 李俊, 江晓东, 同小娟, 于强. 散射辐射比例与冬小麦光能利用率和总初级生产力的关系. 中国农业气象, 2018, 39(7): 462-467. Yang, X.Y.*, Li, J., Jiang, X.D., Tong, X.J., Yu, Q., 2018. Relationship between diffuse radiation fraction and light use efficiency and gross primary productivity of winter wheat. Chinese Journal of Agrometeorology, 39(7): 462-467.

2017

  1. Dong, J.Q., Li, L.H.*, Shi, H., Chen, X., Luo, G.P., Yu, Q., 2017. Robustness and uncertainties of the “temperature and greenness” model for estimating terrestrial gross primary production. Scientific Reports, 7: 44046. Impact Factor: 4.122
  2. Fang, Q.X.*, Ma, L.W., Qi, Z., Shen, Y.J., He, L., Xu, S.H., Kisekka, I., Sima, M.W., Malone, R.W., Yu, Q., 2017. Optimizing ET-based irrigation scheduling for wheat and maize rotation with water constraints. Transactions of theASABE, 60(6): 2053-2065. Impact Factor: 1.118
  3. Fang, Q.X.*, Ma, L.W., Ahuja, L.R., Trout, T.J., Malone, R.W., Zhang, H.H., Gui, D.W., Yu, Q., 2017. Long-term simulation of growth stage-based irrigation scheduling in maize under various water constraints in Colorado, USA. Frontiers of Agricultural Science and Engineering, 4(2): 172-184. Impact Factor: 1.716
  4. Li, L.H.*, Wang, Y.P., Beringer, J., Shi, H., Cleverly, J., Cheng, L., Eamus, D., Huete, A., Hutley, L., Lu, X.J., Piao, S.L., Zhang, L., Zhang, Y.Q., Yu, Q., 2017. Responses of LAI to rainfall explain contrasting sensitivities to carbon uptake between forest and non-forest ecosystems in Australia. Scientific Reports, 7: 11720. Impact Factor: 4.122
  5. Liu, J.D., Pan, T.*, Chen, D.L., Zhou, X.J., Yu, Q., Flerchinger, G.N., Liu, D.L., Zou, X.T., Linderholm, H.W., Du, J., Wu, D.R., Shen, Y.B., 2017. An improved Angstrom-Type model for estimating solar radiation over the Tibetan Plateau. Energies, 10(7): 892. Impact Factor: 2.676
  6. Shi, H., Li, L.H.*, Eamus, D., Huete, A., Cleverly, J., Tian, X., Yu, Q., Wang, S.Q., Montagnani, L., Magliulo, V., Rotenberg, E., Pavelka, M., Carrara, A., 2017. Assessing the ability of MODIS EVI to estimate terrestrial ecosystem gross primary production of multiple land cover types. Ecological Indicators, 72: 153-164. Impact factor: 3.983
  7. Tong, X.J.*, Li, J.*, Nolan, R.H., Yu, Q., 2017. Biophysical controls of soil respiration in a wheat-maize rotation system in the North China Plain. Agricultural and Forest Meteorology, 246: 231-240. Impact Factor: 4.039
  8. Wang, B.*, Liu, D.L., Asseng, S., Macadam, I., Yang, X.H., Yu, Q., 2017. Spatiotemporal changes in wheat phenology, yield and water use efficiency under the CMIP5 multimodel ensemble projections in eastern Australia. Climate Research, 72(2): 83-98. Impact factor: 1.859
  9. Wang, B.*, Liu, D.L., Asseng, S., Macadam, I., Yu, Q., 2017. Modelling wheat yield change under CO2 increase, heat and water stress in relation to plant available water capacity in eastern Australia. European Journal of Agronomy, 90: 152-161. Impact Factor: 3.192
  10. Whitley, R.*, Beringer, J., Hutley, L.B., Abramowitz, G., De Kauwe, M.G., Evans, B., Haverd, V., Li, L.H., Ryu, Y., Smith, B., Schymanski, S., Wang, Y.P., Williams, M., Yu, Q., 2017. Challenges and opportunities in land surface modelling of savanna ecosystems. Biogeosciences, 14: 4711-4732. Impact Factor: 3.441
  11. Xie, X.J., Zhang, Y.H., Wang, L., Yang, X.H., Yu, Q., Bao, Y.X.*, 2017. Effect of asymmetric warming on rice (Oryza sativa) growth characteristics and yield components under a free air temperature increase apparatus. Indian Journal of Agricultural Sciences, 87(10): 1384-1390. Impact Factor: 0.231
  12. Xing, H.T.*, Liu, D.L., Li, G.D., Wang, B., Anwar, M.R., Crean, J., Lines-Kelly, R., Yu, Q., 2017. Incorporating grain legumes in cereal-based cropping systems to improve profitability in Southern New South Wales, Australia. Agricultural Systems, 154: 112-123. Impact factor: 3.004
  13. Zhao, C.S., Zhang, C.B., Yang, S.T.*, Liu, C.M., Xiang, H., Sun, Y., Yang, Z.Y., Zhang, Y., Yu, X.Y., Shao, N.F., Yu, Q., 2017. Calculating e-flow using UVA and ground monitoring. Journal of Hydrology, 552: 351-365. Impact Factor: 3.727
  14. Zhang, Y.Y.*, Gao, Y., Yu, Q., 2017. Diffuse nitrogen loss simulation and impact assessment of stereoscopic agriculture pattern by integrated water system model and consideration of multiple existence forms. Journal of Hydrology, 552: 660-673. Impact Factor: 3.727
  15. 陈上, 窦子荷, 蒋腾聪, 李华龙, 马海姣, 冯浩, 于强, 何建强*. 基于聚类法筛选历史相似气象数据的玉米产量DSSAT-CERES-Maize预测. 农业工程学报, 2017, 33(19): 147-155. Chen, S., Dou, Z.H., Jiang, T.C., Li, H.L., Ma, H.J., Feng, H., Yu, Q., He, J.Q.*, Maize yield forecast with DASST-CERES-Maize model driven by historical meteorological data of analogue years by clustering algorithm. Transactions of the Chinese Society of Agricultural Engineering, 2017, 33(19): 147-155.

2016

  1. Chen, C.*, Cleverly, J., Zhang, L., Yu, Q., Eamus, D., 2016. Modelling seasonal and inter-annual variations in carbon and water fluxes in an arid-zone Acacia savanna woodland, 1981-2012. Ecosystems, 19(4): 625-644. Impact Factor: 4.030
  2. Cleverly, J.*, Eamus, D., Luo, Q.Y., Coupe, N.R., Kljun, N., Ma, X.L., Ewenz, C., Li, L.H., Yu, Q., Huete, A., 2016. The importance of interacting climate modes on Australia’s contribution to global carbon cycle extremes. Scientific Reports, 6: 23113. Impact Factor: 4.122
  3. Cleverly, J.*, Eamus, D., Van Gorsel, E., Chen, C., Rumman, R., Luo, Q.Y., Coupe, N.R., Li, L.H., Kljun, N., Faux, R., Yu, Q., Huete, A., 2016. Productivity and evaporanspiration of two contrasting semiarid ecosystems following the 2011 global carbon land risk anomaly. Agricultural and Forest Meteorology, 220: 151-159. Impact Factor: 4.039
  4. Cleverly, J.*, Eamus, D., Restrepo-Coupe, N., Chen, C., Maes, W.H., Li, L.H., Faux, R., Santini, N.S., Rumman, R., Yu, Q., Huete, A., 2016. Soil moisture controls on phenology, productivity and evapotranspiration in a semi-arid critical zone. Science of the Total Environment, 568: 1227-1237. Impact factor: 4.610
  5. Gu, C.J., Mu, X.M., Zhao, G.J.*, Gao, P., Sun, W.Y., Yu, Q., 2016. Changes in stream flow and their relationships with climatic variations and anthropogenic activities in the Poyang Lake Basin, China. Water, 8(12): 564. Impact Factor: 2.069
  6. Jin, N., Tao, B., Ren, W., Feng, M.C., Sun, R., He, L., Zhuang, W., Yu, Q.*, 2016. Mapping irrigated and rainfed wheat areas using multi-temporal satellite data. Remote Sensing, 8(3): 207. Impact Factor: 3.406
  7. Li, X.L., Joshua Philp, Roger Cremades, Anna Roberts, He, L., Li, L.H., Yu, Q.*, 2016. Agricultural vulnerability over the Chinese Loess Plateau in response to climate change: exposure, sensitivity and adaptive capacity. AMBIO, 45(3): 350-360. Impact Factor: 3.616
  8. Wang, B., Liu, D.L.*, Macadam, I., Alexander, L.V., Abramowitzc, G., Yu, Q., 2016. Multi-model ensemble projections of future extreme temperature change using a statistical downscaling method in south eastern Australia. Climatic Change, 138(1): 85-98. Impact Factor: 3.537
  9. Whitley, R.*, Beringer, J., Hutley, L.B., Abramowitz, G., De Kauwe, M.G., Duursma, R., Evans, B., Haverd, V., Li, L.H., Ryu, Y., Smith, B., Wang, Y.P., Williams, M., Yu, Q., 2016. A model inter-comparison study to examine limiting factors in modelling Australian tropical savannas. Biogeosciences, 13(11): 3245-3265. Impact Factor: 3.441
  10. Xu, B.D., Li, J.*, Liu, Q.H.*, Huete, A.R., Yu, Q., Zeng, Y.L., Yin, G.F., Zhao, J., Yang, L., 2016. Evaluating Spatial Representativeness of Station Observations for Remotely Sensed Leaf Area Index Products. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(7): 3267-3282. Impact Factor: 2.777
  11. Zhuang W., Cheng, L., Rhys Whitley, Shi, H., Beringer, J., Hutley, L.B., Wang, Y.P., He, L., Ckeverly, J., Eamus, D., Yu, Q.*, 2016. How energy and water availability constrain vegetation water-use along the North Australian tropical transect. International Journal of Plant Production, 10(3): 403-423. Impact Factor: 0.886
  12. 黄明霞, 王靖*, 唐建昭, 于强, 张君, 薛庆禹, 常清, 谈美秀. 气孔导度模型在北方农牧交错带的适用性评价: 以马铃薯和油葵为例. 应用生态学报，2016, 27(11): 3585-3592. Huang, M.X., Wang, J.*, Tang, J.Z., Yu, Q., Zhang, J., Xue, Q.Y., Chang, Q., Tan, M.X., 2016. Suitability of four stomatal conductance models in agro-pastoral ecotone in North China: A case study for potato and oil sunflower. Chinese Journal of Applied Ecology, 27(11): 3585-3592.
  13. 何亮*, 侯英雨, 赵刚, 邬定荣, 于强. 基于全局敏感性分析和贝叶斯方法的WOFOST作物模型参数优化. 农业工程学报, 2016, 32(2): 169-179. He, L.*, Hou, Y.Y., Zhao, G., Wu, D.R., Yu, Q., 2016. Parameters optimization of WOFOST model by integration of global sensitivity analysis and Bayesian calibration method. Transactions of the Chinese Society of Agricultural Engineering, 32(2): 169-179.

2015

  1. Guo, L.P., Kang, H.J., Ouyang, Z., Zhuang, W., Yu, Q.*, 2015. Photosynthetic parameter estimations by considering interactive effects of light, temperature and CO2 concentration. International Journal of Plant Production, 9(3): 321-345. Impact Factor: 0.886
  2. He, L.*, Asseng, S., Wu, D.R., Yang, X.Y., Zhuang, W., Jin, N., Yu, Q., 2015. Impacts of recent climate warming, cultivar changes, and crop management on winter wheat phenology across the Loess Plateau of China. Agricultural and Forest Meteorology, 200: 135-143. Impact Factor: 4.039
  3. Jiang, B., Yang, S.Y.*, Yang, X.B., Ma, Y.H., Chen, X.L., Zuo, H.F., Fan, D.F., Gao, L., Yu, Q., Yang, W., 2015. Effect of controlled drainage in the wheat season on soil CH4 and N2O emissions during the rice season. International Journal of Plant Production, 9(2): 273-290. Impact Factor: 0.886
  4. Jiang, C., Wu, Z.F.*, Cheng, J., Yu, Q., Rao, X.Q., 2015. Impacts of urbanization on net primary productivity in the Pearl River Delta, China. International Journal of Plant Production, 9(4): 581-598. Impact Factor: 0.886
  5. Liu, J.D.*, Linderholm, H., Chen, D.L., Zhou, X.J., Flerchinger, G.N., Yu, Q., Du, J., Wu, D.R., Shen, Y.B., Yang, Z.B., 2015. Changes in the relationship between solar radiation and sunshine duration in large cities of China. Energy, 82: 589-600. Impact Factor: 4.968
  6. Wang, B.*, Asseng, S., Yu, Q., Yang, X.H., 2015. Effects of climate trend and variability on wheat yields variability in eastern Australia. Climate Research, 64(2): 173-186. Impact Factor: 1.859
  7. Wang, B.*, Liu, D.L., Asseng, S., Macadam, I., Yu, Q., 2015. Impact of climate change on wheat flowering time in eastern Australia. Agricultural and Forest Meteorology, 209-210: 11-21. Impact Factor: 4.039
  8. Wang, N., Wang, J.*, Wang, E.L.*, Yu, Q., Shi, Y., He, D., 2015. Increased uncertainty in simulated maize phenology with more frequent supra-optimal temperature under climate warming. European Journal of Agronomy, 71: 19-33. Impact Factor: 3.192
  9. Zhao, C.S., Yang, S.T.*, Xiang, H., Liu, C.M., Zhang, H.T., Yang, Z.L., Zhang, Y., Sun, Y., Mitrovic, S.M., Yu, Q., Lim, R.P., 2015. Hydrologic and water-quality rehabilitation of environments for suitable fish habitat. Journal of Hydrology, 530: 799-814. Impact Factor: 3.727
  10. Zhao, C.S., Yang, S.T.*, Liu, C.M., Dou, T.W., Yang, Z.L., Yang, Z.Y., Liu, X.L., Xiang, H., Nie, S.Y., Zhang, J.L., Mitrovic, S.M., Yu, Q., Lim, R.P., 2015. Linking hydrologic, physical and chemical habitat environments for the potential assessment of fish community rehabilitation in a developing city. Journal of Hydrology, 523: 384-397. Impact Factor: 3.727
  11. Zhao, G.*, Bryan, B.A., King, D., Luo, Z.K., Wang, E.L., Yu, Q., 2015. Sustainable limits to crop residue harvest for bioenergy: maintaining soil carbon in Australia’s agricultural lands. Global Change Biology – Bioenergy, 7(3): 479-487. Impact Factor: 5.415
  12. 何亮*, 赵刚, 靳宁, 庄伟, 于强. 不同气候区和不同产量水平下APSIM-Wheat模型的参数全局敏感性分析. 农业工程学报, 2015, 31(4): 148-157. He, L.*, Zhao, G., Jin, N., Zhuang, W., Yu, Q., 2015. Global sensitivity analysis of APSIM-Wheat parameters in different climate zones and yield levels. Transactions of the Chinese Society of Agricultural Engineering, 31(14): 148-157.
  13. 李璐, 李俊*, 同小娟, 杨永民, 于强. 不同冠层阻力公式在玉米田蒸散模拟中的应用. 中国生态农业学报, 2015, 23(8): 1026-1034. Li, L., Li, J.*, Tong, X.J., Yang, Y.M., Yu, Q., 2015. Application of different canopy resistance models in summer maize evapotranspiration Simulation. Chinese Journal of Eco-Agriculture, 23(8): 1026-1034.
  14. 邬定荣, 刘建栋*, 刘玲, 姜朝阳, 于强. 基于作物生长模型及CAST分类的华北夏玉米生产力区划研究. 气象科学, 2015, 35(1): 66-70. Wu, D.R., Liu, J.D.*, Liu, L., Jiang, Z.Y., Yu, Q., 2015. Regionalization of summer maize productivity in North China based on crop growth model and CAST method. Journal of the Meteorological Sciences, 35(1): 66-70.

2014

  1. Bai, J., Chen, X., Li, L.H.*, Luo, G., Yu, Q., 2014. Quantifying the contributions of agricultural oasis expansion, management practices and climate change to net primary production and evapotranspiration in croplands in arid northwest China. Journal of Arid Environments, 100-101: 31-41. Impact Factor: 1.989
  2. Chen, C.*, Eamus, D., Cleverly, J., Boulain, N., Cook, P., Zhang, L., Cheng, L., Yu, Q., 2014. Modelling vegetation water-use and groundwater recharge as affected by climate variability in an arid-zone Acacia savanna woodland. Journal of Hydrology, 519: 1084-1096. Impact Factor: 3.727
  3. Chen, X.*, Su, Z., Ma, Y., Liu, S., Yu, Q., Xu, Z., 2014. Development of a 10 year (2001–2010) 0.1° dataset of land-surface energy balance for mainland China. Atmospheric Chemistry and Physics, 14: 13097-13117. Impact Factor: 5.509
  4. Cheng, L., Zhang, L.*, Wang, Y.P., Yu, Q., Eamus, D., 2014. Quantifying the effects of elevated CO2 on water budgets by combining FACE data with an ecohydrological model. Ecohydrology, 7(6): 1574-1588. Impact Factor: 2.755
  5. Cheng, L., Zhang, L.*, Wang, Y.P., Yu, Q., Eamus, D., O'Grady, A., 2014. Impacts of elevated CO2, climate change and their interactions on water budgets in four different catchments in Australia. Journal of Hydrology, 519: 1350-1361. Impact Factor: 3.727
  6. Fang, Q.X., Ma, L.W.*, Flerchinger, G.N., Qi, Z., Ahuja, L.R., Xing, H.T., Li, J., Yu, Q., 2014. Modelling evapotranspiration and energy balance in a wheat-maize cropping system using the revised RZ-SHAW model. Agricultural and Forest Meteorology, 195: 218-229. Impact Factor: 4.039
  7. He, L., Cleverly, J., Chen, C., Yang, X.Y., Li, J., Liu, W.Z., Yu, Q.*, 2014. Diverse responses of winter wheat yield and water use to climate change and variability over the semi-arid Loess Plateau in China. Agronomy Journal, 106(4): 1169-1178. Impact Factor: 1.897
  8. Li, X.W., Zhao, G., Yu, X.B., Yu, Q.*, 2014. A comparison of forest fire indices for predicting fire risk in contrasting climates in China. Natural Hazards, 70: 1339-1356. Impact Factor: 1.901
  9. Ma, X.L., Huete, A.*, Yu, Q., Restrepo-Coupe, N., Beringer, J., Hutley, L.B., Kanniah, K.D., Cleverly, J., Eamus, D., 2014. Parameterization of an ecosystem light use-efficiency model for predicting savanna GPP using MODIS EVI. Remote Sensing of Environment, 154: 253-271. Impact Factor: 6.457
  10. Shi, H., Li, L.H.*, Eamus, D., Cleverly, J., Huete, A., Beringer, J., Yu, Q., Gorsel, E., Hutley, L.B., 2014. Intrinsic climate dependency of ecosystem light and water-use-efficiencies across Australian biomes. Environmental Research Letters, 9(10): 104002. Impact Factor: 4.541
  11. Tong, X.J.*, Li, J.*, Yu, Q., Lin, Z.H., 2014. Biophysical controls on light response of net CO2 exchange in a winter wheat field in the North China Plain. PLoS ONE, 9(2): e89469. Impact Factor: 2.766
  12. Yu, Q.*, Li, L., Luo, Q.Y., Derek, E., Xu, S.H., Chen, C., Wang, E.L., Liu, J.D., Nielsen, D.C., 2014. Year patterns of climate impact on wheat yields. International Journal of Climatology, 34: 518-528. Impact Factor: 3.100
  13. Zhu, J.T., Yu, J.J.*, Wang, P., Yu, Q., Eamus, D., 2014. Variability in groundwater depth and composition and their impacts on vegetation succession in the lower Heihe Basin, north-western China. Marine and Freshwater Research, 65(3): 206-217. Impact Factor: 1.674
  14. 李俊*, 韩凤明, 同小娟, 于强*. 麦田蒸散模型的改进及其对阻力参数的敏感性分析. 中国农业气象, 2014, 35(6): 635-643. Li, J.*, Han, F.M., Tong, X.J., Yu, Q., Evapotranspiration models for a winter wheat field: the improvements and analyses on their sensitivities to the resistance parameters. Chinese Journal of Agrometeorology, 35(6): 635-643.

2013

  1. Cleverly, J.*, Boulain, N., Villalobos-Vega, R., Grant, N., Faux, R., Wood, C., Cook, P.G., Yu, Q., Leigh, A., Eamus, D., 2013. Dynamics of component carbon fluxes in a semi-arid Acacia woodland, central Australia. Journal of Geophysical Research - Biogeosciences, 118: 1168-1185. Impact Factor: 3.484
  2. Cleverly, J.*, Chen, C., Boulain, N., Villalobos-Vega, R., Faux, R., Grant, N., Yu, Q., Eamus, D., 2013. Aerodynamic resistance and Penman-Monteith evapotranspiration over a seasonally two-layered canopy in semi-arid central Australia. Journal of Hydrometeorology, 14(5): 1562-1570. Impact Factor: 3.790
  3. Fang, Q.X.*, Ma, L.W.*, Yu, Q., Hu, C.S., Li, X.X., Malone, R.W., Ahuja, L.R., 2013. Quantifying climate and management effects on regional crop yield and nitrogen leaching in the North China Plain. Journal of Environmental Quality, 42: 1466-1479. Impact Factor: 2.405
  4. Ma, X.L., Huete, A.*, Yu, Q., Natalia, R.C., Davies, K., Broich, M., Ratana, P., Beringer, J., Lindsay, B.H., Cleverly, J., Boulain, N., Eamus, D., 2013. Spatial patterns and temporal dynamics in savanna vegetation phenology across the North Australian Tropical Transect. Remote Sensing of Environment, 139: 97-115. Impact Factor: 6.457
  5. Yang, X.Y.*, Asseng, S., Wong, M.T.F., Yu, Q., Li, J., Liu, E.M., 2013. Quantifying the interactive impacts of global dimming and warming on wheat yield and water use in China. Agricultural and Forest Meteorology, 182-183: 342-351. Impact Factor: 4.039
  6. Zhao, C.S.*, Liu, C.M., Zhao, Z.J., Xia, J., Yu, Q.*, Eamus, D., 2013. Zooplankton in hightly regulated rivers: Changing with water environment. Ecological Engineering, 58: 323-334. Impact Factor: 3.023
  7. Zhao, G.*, Bryan, B.A., King, D., Luo, Z.K., Wang, E.L., Bende-Michl, U., Song, X.D., Yu, Q., 2013. Large-scale, high-resolution agricultural systems modeling using a hybrid approach combining grid computing and parallel processing. Environmental Modelling & Software, 41: 231-238. Impact Factor: 4.177
  8. Zhao, G.*, Bryan, B.A., King, D., Luo, Z.K., Wang, E.L., Song, X.D., Yu, Q., 2013. Impact of agricultural management practices on soil organic carbon: simulation of Australian wheat systems. Global Change Biology, 19(5): 1585-1597. Impact Factor: 8.997
  9. Zhao, Z.J., Shen, G.Z., Tan, L.Y., Kang, D.W., Wang, M.J., Kang, W., Guo, W.X., Zeppel, M.J.B., Yu, Q., Li, J.Q.*, 2013. Treelines dynamics in response to climate change in the Min Mountains, southwestern China. Botanical Studies, 54: 15. Impact Factor: 1.411
  10. Zhu, J.T., Yu, J.J.*, Wang, P., Yu, Q., Eamus, D., 2013. Distribution patterns of groundwater-dependent vegetation species diversity and their relationship to groundwater attributes in northwestern China. Ecohydrology, 6(2): 191-200. Impact Factor: 2.755
  11. 李晓炜, 赵刚, 于秀波, 于强*. 不同区域森林火灾对生态因子的响应及其概率模型. 生态学报, 2013, 33(4): 1219-1229. Li, X.W., Zhao, G., Yu, X. B., Yu, Q.*, 2013. Probability models of forest fire risk based on ecology factors in different vegetation regions over China. ACTA Ecologica SINICA, 33(4): 1219-1229.
  12. 梅旭荣*, 康绍忠, 于强, 黄元仿, 钟秀丽, 龚道枝, 霍再林, 刘恩科, 协同提升黄淮海平原作物生产力与农田水分利用效率途径. 中国农业科学, 2013, 46(6): 1149-1157. Mei, X.R.*, Kang, S.Z., Yu, Q., Huang, Y.F., Zhong, X.L., Gong, D.Z., Liu, E.K., 2013. Pathways to Synchronously Improving Crop Productivity and Field Water Use Efficiency in the North China Plain. Scientia Agricultura SINICA, 46(6): 1149-1157.

2012

  1. Chew, K.L.*, Langtry, T., Zinder, Y., Yu, Q., Li, L.H., 2012. Estimation of biochemical parameters from leaf photosynthesis. ANZIAM Journal, 53(EMAC2011): C218-C235. Impact Factor: 0.554
  2. Li, L.H.*, Wang, Y.P., Yu, Q., Pak, B., Eamus, D., Yan, J.H., van Gorsel, E., Baker, I.T., 2012. Improving the responses of the Australian community land surface model (CABLE) to seasonal drought. Journal of Geophysical Research - Biogeosciences, 117: G04002. Impact Factor: 3.484
  3. Liu, J.D., Liu, J.M., Linderholm, H.W.*, Chen, D.L., Yu, Q., Wu, D.R., Haginoya, S., 2012. Observation and calculation of the solar radiation on the Tibetan Plateau. Energy Conversion and Management, 57: 23-32. Impact Factor: 6.377
  4. Luo, Q.Y.*, Yu, Q., 2012. Developing higher resolution climate change scenarios for agricultural risk assessment: progress, challenges and prospects. International Journal of Biometeorology, 56(4): 557-568. Impact Factor: 2.577
  5. Ye, Z.P.*, Yu, Q., Kang, H.J., 2012. Evaluation of photosynthetic electron flow using simultaneous measurements of gas exchange and chlorophyll fluorescence under photorespiratory conditions. Photosynthetica, 50(3): 472-476. Impact Factor: 1.740
  6. Zhao, C.S.*, Liu, C.M., Xia, J., Zhang, Y.Y., Yu, Q.*, Eamus, D., 2012. Recognition of key regions for restoration of phytoplankton communities in the Huai River basin, China. Journal of Hydrology, 420: 292-300. Impact Factor: 3.727
  7. Zhao, G.*, Bryan, B.A., King, D., Song, X.D., Yu, Q., 2012. Parallelization and optimization of spatial analysis for large scale environmental model data assembly. Computers and Electronics in Agriculture, 89: 94-99. Impact Factor: 2.427
  8. Zhao, Z.J., Eamus, D., Yu, Q., Li, Y., Yang, H.W., Li, J.Q.*, 2012. Climate constraints on growth and recruitment patterns of Abies faxoniana over altitudinal gradients in the Wanglang Natural Reserve, eastern Tibetan Plateau. Australian Journal of Botany, 60(7): 602-614. Impact Factor: 0.903
  9. Zhu, J.T., Li, X.Y.*, Zhang, X.M., Yu, Q., Lin, L.S., 2012. Leaf nitrogen allocation and partitioning in three groundwater-dependent herbaceous species in a hyper-arid desert region of north-western China. Australian Journal of Botany, 60(1): 61-67. Impact Factor: 0.903
  10. Zhu, J.T., Yu, J.J.*, Wang, P., Zhang, Y.C., Yu, Q., 2012. Interpreting the groundwater attributes influencing the distribution patterns of groundwater-dependent vegetation in northwestern China. Ecohydrology, 5(5): 628-636. Impact Factor: 2.755
  11. Li X.W., Fu G.B., Zeppel M.J.B., Zhao G., Eamus D., Yu Q.*, 2012. Probability models of risk based on forest fire indices in contrasting climates over China. Journal of Resources and Ecology. 3(2): 105-117.
  12. 刘渡, 李俊, 同小娟, 于强. 华北平原冬小麦/夏玉米田能量闭合状况分析. 中国农业气象, 2012, 33(4): 493-499. Liu, D., Li, J.*, Tong X.J., Yu, Q., 2012. Analysis of the energy balance closure in a winter wheat/summer maize double cropping system in the North China Plain. Chinese Journal of Agrometeorology, 33(4):493-499.
  13. 刘渡, 李俊*, 于强, 同小娟, 欧阳竹. 涡度相关观测的能量闭合状况及其对农田蒸散测定的影响. 生态学报, 2012, 32(17): 5309-5317. Liu, D., Li, J.*, Yu, Q., Tong, X.J., Ouyang, Z., 2012. Energy balance closure and its effects on evapotranspiration measurements with the eddy covariance technique in a cropland. ACTA Ecologica SINICA, 32(17): 5309-5317.
  14. 邬定荣*, 刘健栋, 刘玲, 姜朝阳, 于强. 华北地区冬小麦生产潜力数值模拟. 干旱地区农业研究. 2012, 30(5): 7-14. Wu, D.R., Liu, J.D.*, Liu, L., Jiang, Z.Y., Yu, Q., 2012. Yield potential of winter wheat in the North China and its EOF analysis. Agricultural Research in the Arid Areas, 30(5): 7-14.

2011

  1. Chen, C.*, Baethgen, W.E., Wang, E.L., Yu, Q., 2011. Characterizing spatial and temporal variability of crop yield caused by climate and irrigation in the North China Plain. Theoretical and Applied Climatology, 106(3-4): 365-381. Impact Factor: 2.321
  2. Pan, G.Y., Ouyang, Z., Luo, Q.Y., Yu, Q., Wang, J.S., 2011. Water consumption of seven forage cultivars under different climatic condition in the North China Plain. Journal of Resources and Ecology. 2(1): 74-82.
  3. Pan, G.Y., Ouyang, Z.*, Luo, Q., Yu, Q., Wang, J., 2011. Water use patterns of forage cultivars in the North China Plain. International Journal of Plant Production, 5(2): 181-194. Impact Factor: 0.886
  4. Xing, H.T., Wang, E.L.*, Smith, C.J., Rolston, D., Yu, Q., 2011. Modelling nitrous oxide and carbon dioxide emission from soil in an incubation experiment. Geoderma, 167-68: 328-339. Impact Factor: 3.740
  5. Yang, X., Chen, C., Luo, Q., Li, L., Yu, Q.*, 2011. Climate change effects on wheat yield and water use in oasis cropland. International Journal of Plant Production, 5(1): 83-94. Impact Factor: 0.886

2010

  1. Chen, C., Wang, E.L.*, Yu, Q., 2010. Modeling wheat and maize productivity as affected by climate variation and irrigation supply in North China Plain. Agronomy Journal, 102(3): 1037-1049. Impact Factor: 1.897
  2. Chen, C., Wang, E.L.*, Yu, Q., Zhang, Y.Q., 2010. Quantifying the effects of climate trends in the past 43 years (1961-2003) on crop growth and water demand in the North China Plain. Climatic Change, 100(3-4): 559-578. Impact Factor: 3.537
  3. Chen, C., Wang, E.L.*, Yu, Q., 2010. Modelling the effects of climate variability and water management on crop water productivity and water balance in the North China Plain. Agricultural Water Management, 97(8): 1175-1184. Impact Factor: 3.182
  4. Fang, Q.X., Ma, L.W.*, Yu, Q., Ahuja, L.R., Malone, R.W., Hoogenboom, G., 2010. Irrigation strategies to improve the water use efficiency of wheat-maize double cropping systems in North China Plain. Agricultural Water Management, 97(8): 1165-1174. Impact Factor: 3.182
  5. Fang, Q.X.*, Ma, L., Green, T.R., Yu, Q., Wang, T.D., Ahuja, L.R., 2010. Water resources and water use efficiency in the North China Plain: Current status and agronomic management options. Agricultural Water Management, 97(8): 1102-1116. Impact Factor: 3.182
  6. Flerchinger, G.N.*, Marks, D., Reba, M.L., Yu, Q., Seyfried, M.S., 2010. Surface fluxes and water balance of spatially varying vegetation within a small mountainous headwater catchment. Hydrology and Earth System Sciences, 14(6): 965-978. Impact Factor: 4.256
  7. Li, L., Nielsen, D.C.*, Yu, Q., Ma, L., Ahuja, L.R., 2010. Evaluating the Crop Water Stress Index and its correlation with latent heat and CO2 fluxes over winter wheat and maize in the North China plain. Agricultural Water Management, 97(8): 1146-1155. Impact Factor: 3.182
  8. Qin, Z., Su, G.L., Zhang, J.E., Ouyang, Y.*, Yu, Q.*, Li, J., 2010. Identification of important factors for water vapor flux and CO2 exchange in a cropland. Ecological Modelling, 221(4): 575-581. Impact Factor: 2.507
  9. Sun, H.Y., Shen, Y.J.*, Yu, Q., Flerchinger, G.N., Zhang, Y.Q., Liu, C.M., Zhang, X.Y., 2010. Effect of precipitation change on water balance and WUE of the winter wheat-summer maize rotation in the North China Plain. Agricultural Water Management, 97(8): 1139-1145. Impact Factor: 3.182
  10. Wang, J.*, Zhao, T.B., Wang, E.L., Yu, Q., Yang, X.G., Feng, L.P., Pan, X.B., 2010. Measurement and simulation of diurnal variations in water use efficiency and radiation use efficiency in an irrigated wheat-maize field in the North China Plain. New Zealand Journal of Crop and Horticultural Science, 38(2): 119-135. Impact Factor: 0.647
  11. Xiao, W., Lee, X.H.*, Griffis, T.J., Kim, K., Welp, L.R., Yu, Q., 2010. A modeling investigation of canopy-air oxygen isotopic exchange of water vapor and carbon dioxide in a soybean field. Journal of Geophysical Research - Biogeosciences, 115: G01004. Impact Factor: 3.484
  12. 叶子飘, 康华靖, 陶月良*, 于强. 以光和助手计算光合参数的一些问题. 植物生理学通讯, 2010, 46(1): 67-70. Ye, Z.P., Kang, H.J., Tao, Y.L.*, Yu, Q., 2010. Some problems on photosynthetic parameters calculated by photosynthesis assistant. Plant Physiology Communications, 46(1): 67-70.
  13. 谢莹莹, 陆佩玲, 于强*. 中国东部季风气候区木本植物展叶期对春季温度变化的敏感性. 中国农业气象, 2010, 31(44): 495-500. Xie, Y.Y., Lu, P.L., Yu, Q.*, 2010. Sensitivity of leaf unfolding date for woody plant to temperature variability in spring in China’s Eastern monsoonal region. Chinese Journal of Agrometeorology, 31(44): 495-500.

2009

  1. Flerchinger, G.N.*, Xaio, W., Marks, D., Sauer, T.J., Yu, Q., 2009. Comparison of algorithms for incoming atmospheric long-wave radiation. Water Resources Research, 45. Impact Factor: 4.361
  2. Flerchinger, G.N.*, Xiao, W., Sauer, T.J., Yu, Q., 2009. Simulation of within-canopy radiation exchange. NJAS-Wageningen Journal of Life Sciences, 57(1): 5-15. Impact Factor: 1.585
  3. Li, L.*, Yu, Q., Su, Z., van der Tol, C., 2009. A simple method using climatic variables to estimate canopy temperature, sensible and latent heat fluxes in a winter wheat field on the North China Plain. Hydrological Processes, 23(5): 665-674. Impact Factor: 3.181
  4. Tong, X.J., Li, J.*, Yu, Q., Qin, Z., 2009. Ecosystem water use efficiency in an irrigated cropland in the North China Plain. Journal of Hydrology, 374(3-4): 329-337. Impact Factor: 3.727
  5. 陈超, 于强*, 王恩利, 夏军. 华北平原作物水分生产力区域分异规律模拟. 资源科学. 2009, 31(9): 1477-1485. Chen, C., Yu, Q.*, Wang, E.L., Xia, J., 2009. Modeling the spatial distribution of crop water productivity in the North China Plain. Resources Science, 31(9): 1477-1485.
  6. 房全孝*, 于强, 王建林. 利用RZWQM-CERES模拟华北平原农田土壤水分动态及其作物产量的影响. 作物学报, 2009, 35(6): 1122-1130. Fang, Q.X.*, Yu, Q., Wang, J.L., 2009. Simulating soil water dynamics and its effects on crop yield using RZWQM-CERES in the North China Plain. ACTA Agronomica SINICA, 35(6): 1122-1130.
  7. 孙善彬, 李俊*, 陆佩玲, 于强, 姚玉刚, 孙艳丽. 小麦植株在麦田CH4交换中的作用及光照的影响. 中国生态农业学报, 2009, 17(3): 495-499. Sun, S.B., Li, J.*, Lu, P.L., Yu, Q., Yao, Y.G., Sun, Y.L., 2009. Effect of plant light on CH4 exchange in the soil-plant system of wheat fields. Chinese Journal of Eco-Agriculture, 17(3): 495-499.
  8. 同小娟, 李俊*, 于强. 农田生态系统光能利用效率及其影响因子分析. 自然资源学报, 2009, 24(8): 1393-1401. Tong, X.J., Li, J.*, Yu, Q., 2009. Analysis of biophysical controls on light use efficiency in a farm land ecosystem. Journal of Natural Resources, 24(8): 1393-1401.
  9. 叶子飘*, 于强. 光合作用对胞间和大气CO2响应曲线的比较. 生态学杂志. 2009, 28(11): 2233-2238. Ye, Z.P.*, Yu, Q., 2009. A comparison of response curves of winter wheat photosynthesis to flag leaf intercellular and air CO2 concentrations. Chinese Journal of Ecology, 28(11): 2233-2238.
  10. 叶子飘*, 于强. 植物气孔导度的机理模型. 植物生态学报. 2009, 33(4): 772-782. Ye, Z.P.*, Yu, Q., 2009. Mechanism model of stomatal conductance. Chinese Journal of Plant Ecology, 33(4): 772-782.

2008

  1. Fang, Q., Ma, L.*, Yu, Q., Malone, R.W., Saseendran, S.A., Ahuja, L.R., 2008. Modeling Nitrogen and Water Management Effects in a Wheat-Maize Double-Cropping System. Journal of Environmental Quality, 37(6): 2232-2242. Impact Factor: 2.405
  2. Jiang, J., Zhang, Y.*, Wegehenkel, M., Yu, Q., Xia, J., 2008. Estimation of soil water content and evapotranspiration from irrigated cropland on the North China Plain. Journal of Plant Nutrition and Soil Science, 171(5): 751-761. Impact Factor: 2.163
  3. Li, J.*, Tong, X.J., Yu, Q., Dong, Y.S., Peng, C.H., 2008. Micrometeorological measurements of nitrous oxide exchange above a cropland. Atmospheric Environment, 42(29): 6992-7001. Impact Factor: 3.708
  4. Li, L.H., Malone, R.W.*, Ma, L., Kaspar, T.C., Jaynes, D.B., Saseendran, S.A., Thorp, K.R., Yu, Q., Ahuja, L.R., 2008. Winter cover crop effects on nitrate leaching in subsuface drainage as simulated by by RZWQM-DSSAT. Transactions of the ASABE, 51(5): 1575-1583. Impact Factor: 1.118
  5. Li, L.H.*, McMaster, G.S., Yu, Q., Du, J., 2008. Simulating winter wheat development response to temperature: Modifying Malo's exponential sine equation. Computers and Electronics in Agriculture, 63(2): 274-281. Impact Factor: 2.427
  6. Lu, P.L., Yu, Q.*, Wang, E., Liu, J.D., Xu, S.H., 2008. Effects of climatic variation and warming on rice development across South China. Climate Research, 36(1): 79-88. Impact Factor: 1.859
  7. Qin, Z., Ouyang, Y., Su, G.L., Yu, Q.*, Li, J., Zhang, J.E., Wu, Z.Y., 2008. Characterization of CO2 and water vapor fluxes in a summer maize field with wavelet analysis. Ecological Informatics, 3(6): 397-409. Impact Factor: 1.820
  8. Wang, E.L.*, Cresswell, H., Yu, Q., Verburg, K., 2008. Summer forage cropping as an effective way to control deep drainage in south-eastern Australia - A simulation study. Agriculture Ecosystems & Environment, 125(1-4): 127-136. Impact Factor: 3.402
  9. Wang, E.L.*, Yu, Q., Wu, D.R., Xia, J., 2008. Climate, agricultural production and hydrological balance in the North China Plain. International Journal of Climatology, 28(14): 1959-1970. Impact Factor: 3.100
  10. Wu, D.R., Yu, Q.*, Wang, E.L., Hengsdijk, H., 2008. Impact of spatial-temporal variations of climatic variables on summer maize yield in North China Plain. International Journal of Plant Production, 2(1): 71-88. Impact Factor: 0.886
  11. Ye, Z.P.* and Yu, Q., 2008. A coupled model of stomatal conductance and photosynthesis for winter wheat. Photosynthetica, 46(4): 637-640. Impact Factor: 1.740
  12. Yu, Q.*, Wang, E.L., Smith, C.J., 2008. A modelling investigation into the economic and environmental values of 'perfect' climate forecasts for wheat production under contrasting rainfall conditions. International Journal of Climatology, 28(2): 255-266. Impact Factor: 3.100
  13. Zhang, Y.Q.*, Yu, Q., Jiang, J., Tang, Y.H., 2008. Calibration of Terra/MODIS gross primary production over an irrigated cropland on the North China Plain and an alpine meadow on the Tibetan Plateau. Global Change Biology, 14(4): 757-767. Impact Factor: 8.997
  14. 叶子飘, 于强. 合作用光响应模型的比较. 植物生态学报. 2008, 32(6)：1356-1361. Ye, Z.P., Yu, Q., 2008. Comparison of new and several classical models of photosynthesis in response to irradiance, Journal of Plant Ecology, 32(6): 1356-1361.
  15. 叶子飘, 于强. 冬小麦旗叶页光合速率对光强和CO2浓度的响应. 扬州大学学报, 2008, 29(3): 33-37. Ye, Z.P., Yu, Q., 2008. Photosynthetic response to irradiance and CO2 concentration for flag leaves of winter wheat. Journal of Yangzhou University, 29(3): 33-37.
  16. 王靖, 于强, 潘学标, 尹红, 张永强. 土壤-植被-大气连续体水热, CO2通量估算模型研究进展. 生态学报. 2008, 28(6): 1-11. Wang, J., Yu, Q., Pan, X.B., Yin, H., Zhang, Y.Q., 2008. A review on water, heat and CO2 fluxes simulation models. ACTA Ecologica SINICA, 28(6): 1-11.

2007

  1. Fang, Q.X.*, Chen, Y.H., Yu, Q., Ouyang, Z., Li, Q.Q., Yu, S.Z., 2007. Much improved irrigation wheat-maize double use efficiency in an intensive cropping system in the north China plain. Journal of Integrative Plant Biology, 49(10): 1517-1526. Impact Factor: 3.129
  2. Flerchinger, G.N.* and Yu, Q., 2007. Simplified expressions for radiation scattering in canopies with ellipsoidal leaf angle distributions. Agricultural and Forest Meteorology, 144(3-4): 230-235. Impact Factor: 4.039
  3. Li, L.H.* and Yu, Q., 2007. Quantifying the effects of advection on canopy energy budgets and water use efficiency in an irrigated wheat field in the North China Plain. Agricultural Water Management, 89(1-2): 116-122. Impact Factor: 3.182
  4. Peng, C.H.*, Ouyang, H., Gao, Q., Jiang, Y., Zhang, F., Li, J., Yu, Q., 2007. Environment - Building a "green" railway in China. Science, 316(5824): 546-547. Impact Factor: 41.058
  5. Tong, X.J., Li, J.*, Zhang, X.S., Yu, Q., Qin, Z., Zhu, Z.L., 2007. Mechanism and bio-environmental controls of ecosystem respiration in a cropland in the North China Plains. New Zealand Journal of Agricultural Research, 50(5): 1347-1358. Impact Factor: 1.149
  6. Wang, J., Yu, Q.*, Lee, X.H., 2007. Simulation of crop growth and energy and carbon dioxide fluxes at different time steps from hourly to daily. Hydrological Processes, 21(18): 2474-2492. Impact Factor: 3.181
  7. Yu, Q.*, Flerchinger, G.N., Xu, S., Kozak, J., Ma, L., Ahuja, L., 2007. Energy balance simulation of a wheat canopy using the RZ-SHAW (RZWQM-SHAW)model. Transactions of the ASABE, 50(5): 1507-1516. Impact Factor: 1.118
  8. Yu, Q.*, Xu, S.H., Wang, J., Lee, X.H., 2007. Influence of leaf water potential on diurnal changes in CO2 and water vapour fluxes. Boundary-Layer Meteorology, 124(2): 161-181. Impact Factor: 2.607
  9. Yue, T.X.*, Wang, W., Yu, Q., Zhu, Z., Zhang, S., Zhang, R., Du, Z., 2007. Simulation of vertical wind profile under neutral conditions. International Journal of Remote Sensing, 28(10): 2207-2219. Impact Factor: 1.782
  10. 叶子飘, 于强. 一个光合作用响应新模型与传统模型的比较. 沈阳农业大学学报, 2007, 38(6): 771-775. Ye, Z.P., Yu, Q., 2007. Comparison of a new model of light response of photosynthesis with traditional models. Journal of Shenyang Agricultural University, 38(6): 771-775.
  11. 王琳, 郑有飞, 于强. APSIM模型对华北平原小麦-玉米轮作系统的适应性. 应用生态学报, 2007, 18(11): 2480-2486. Wang, L., Zeng, Y.F., Yu, Q., 2007. Applicability of agricultural production systems simulator (APSIM) in simulating the production and water use of wheat-maize continuous cropping system in North China Plain. Chinese Journal of Applied Ecology. 18(11): 2480-2486.

2006

  1. Fang, Q.X., Yu, Q.*, Wang, E.L., Chen, Y.H., Zhang, G.L., Wang, J., Li, L.H., 2006. Soil nitrate accumulation, leaching and crop nitrogen use as influenced by fertilization and irrigation in an intensive wheat-maize double cropping system in the North China Plain. Plant and Soil, 284(1-2): 335-350. Impact Factor: 3.306
  2. Jiang, Z.Y., Yu, Q.*, Lei, S., Wang, T.D., Sun, X.M., Zhang, R.H., 2006. Comparative analysis of temperature and CO2 fluxes for winter wheat in Tibetan Plain and North China Plain using the EMD method. Progress in Natural Science-Materials International, 16(10): 1066-1071. Impact Factor: 2.572
  3. Jiang, Z.Y,*, Yu, Q., Wang, T.D., Sun, X.M., Zhang, R.H., 2006. Continuous wavelet transform and discrete multi-resolution analysis of surface fluxes and atmospheric stability. Progress in Natural Science-Materials International, 16(4): 403-409. Impact Factor: 2.572
  4. Li, J.*, Yu, Q., Sun, X.M., Tong, X.J., Ren, C.Y., Wang, J., Liu, E.M., Zhu, Z.L., Yu, G.R., 2006. Carbon dioxide exchange and the mechanism of environmental control in a farmland ecosystem in North China Plain. Science China-Earth Sciences, 49: 226-240. Impact Factor: 2.058
  5. Li, L.H., Yu, Q.*, Zheng, Y.F., Wang, J., Fang, Q.X., 2006. Simulating the response of photosynthate partitioning during vegetative growth in winter wheat to environmental factors. Field Crops Research, 96(1): 133-141. Impact Factor: 2.976
  6. Lu, P.L., Yu, Q.*, Liu, H.D., He, Q.T., 2006. Effects of changes in spring temperature on flowering dates of woody plants across China. Botanical Studies, 47(2): 153-161. Impact Factor: 1.411
  7. Lu, P.L., Yu, Q.*, Liu, J.D., Lee, X.H., 2006. Advance of tree-flowering dates in response to urban climate change. Agricultural and Forest Meteorology, 138(1-4): 120-131. Impact Factor: 4.039
  8. Wang, J., Yu, Q.*, Li, J., Li, L.H., Li, X.G., Yu, G.R., Sun, X.M., 2006. Simulation of diurnal variations of CO2, water and heat fluxes over winter wheat with a model coupled photosynthesis and transpiration. Agricultural and Forest Meteorology, 137(3-4): 194-219. Impact Factor: 4.039
  9. Wu, D.R., Yu, Q.*, Lu, C.H., Hengsdijk, H., 2006. Quantifying production potentials of winter wheat in the North China Plain. European Journal of Agronomy, 24(3): 226-235. Impact Factor: 3.192
  10. Xiao, W., Flerchinger, G.N., Yu, Q.*, Zheng, Y.F., 2006. Evaluation of the SHAW model in simulating the components of net all-wave radiation. Transactions of the ASABE, 49(5): 1351-1360. Impact Factor: 1.118
  11. Xiao, W., Yu, Q., Flerchinger, G.N.*, Zheng, Y.F., 2006. Evaluation of SHAW model in simulating energy balance, leaf temperature, micrometeorological variables within a maize canopy. Agronomy Journal, 98(3): 722-729. Impact Factor: 1.897
  12. Yu, Q.*, Saseendran, S.A., Ma, L., Flerchinger, G.N., Green, T.R., Ahuja, L.R., 2006. Modeling a wheat-maize double cropping system in China using two plant growth modules in RZWQM. Agricultural Systems, 89(2-3): 457-477. Impact Factor: 3.004
  13. Zhang, Y.Q.*, Liu, C., Lei, Y., Tang, Y., Yu, Q., Shen, Y., Sun, H., 2006. An integrated algorithm for estimating regional latent heat flux and daily evapotranspiration. International Journal of Remote Sensing, 27(1): 129-152. Impact Factor: 1.782
  14. 房全孝, 陈雨海, 李全起, 于舜章, 罗毅, 于强, 欧阳竹. 土壤水分对冬小麦生长后期光能利用及水分利用效率的影响. 作物学报, 2006, 32(6): 861-866. Fang, Q.X., Chen, Y.H., Li, Q.Q., Yu, S.Z., Luo, Y., Yu, Q., Ouyang, Z., 2006. Effects of soil moisture on radiation utilization during late growth stages and water use efficiency of winter wheat. ACTA Agrinomica SINICA, 32(6): 861-866.
  15. 陆佩玲, 贺庆棠, 于强. 植物物候对气候变化的响应. 生态学报, 2006, 26(3): 923-929. Lu, Peiling, Yu, Q., 2006. Responses of plant phenology to climatic change. ACTA Ecologica SINICA, 26(3): 923-929.

2005

  1. Qin, Z., Yu, Q.*, Xu, S.H., Hu, B.M., Sun, X.M., Liu, E.M., Wang, J.S., Yu, G.R., Zhu, Z.L., 2005. Water, heat fluxes and water use efficiency measurement and modeling above a farmland in the North China Plain. Science China-Earth Sciences, 48(S1): 207-217. Impact Factor: 2.058
  2. Zhang, Y.Q.*, Yu, Q., Liu, C.M., Wang, J., 2005. Simulation of CO2 and latent heat fluxes in the North China Plain. Science China-Earth Sciences, 48(S1): 172-181. Impact Factor: 2.058
  3. Qin, Z.*, Su, G.L., Yu, Q., Hu, B.M., Li, J., 2005. Modeling water and carbon fluxes above summer maize field in North China Plain with Back-Propagation neural networks. Journal of Zhejiang University Science (Life Science), 6B(5): 418-426
  4. Qin, Z.*, Yu, Q., Li, J., Wu, Z.Y., Hu, B.M.*, 2005. Application of Least Squares Vector Machines in Modelling Water Vapor and Carbon Dioxide Fluxes over a Cropland. Journal of Zhejiang University Science (Life Science). 6B(6): 491-495.
  5. 王兴武, 于强*, 张国梁. 鲁西北玉米产量与氮淋失研究. 地理研究, 2005, 24(1): 140-150. Wang, X.W., Yu, Q., Zhang, G.L., 2005. The yield and dynamics of soil nitrate for summer maize on the plain of northwest Shandong province. Geographical Research, 24(1): 140-150.
  6. 肖薇, 郑有飞, 于强. 基于SHAW模型对农田小气候要素的模拟. 生态学报, 2005, 25(7): 1626-1634. Xiao, W., Zeng, Y.F., Yu, Q., 2005. Evaluation of SHAW model in simulating energy balance, leaf temperature and micrometeorological variables within a maize canopy. ACTA Ecologica SINICA, 25(7): 1626-1634.
  7. 徐雨晴, 陆佩玲, 于强. 近50 年北京树木物候对气候变化的响应. 地理研究, 2005, 24(3): 412-420. Xu, Y.Q., Lu, P.L., Yu, Q., 2005. Response of tree phenology to climate change for recent 50 years in Beijing. Geographical Research, 24(3): 412-420.

2004

  1. Lee, X.H.*, Yu, Q., Sun, X., Liu, J., Min, Q., Liu, Y., Zhang, X., 2004. Micrometeorological fluxes under the influence of regional and local advection: a revisit. Agricultural and Forest Meteorology, 122(1-2): 111-124. Impact Factor: 4.039
  2. Qiu, X.F.*, Zeng, Y., Miao, Q., Yu, Q., 2004. Estimation of annual actual evapotranspiration from nonsaturated land surfaces with conventional meteorological data. Science China-Earth Sciences, 47(3): 239-246. Impact Factor: 2.058
  3. Yu, Q.*, Zhang, Y.G., Liu, Y.F., Shi, P.L., 2004. Simulation of the stomatal conductance of winter wheat in response to light, temperature and CO2 changes. Annals of Botany, 93(4): 435-441. Impact Factor: 3.646
  4. Zhang, Y.Q.*, Kendy, E., Yu, Q., Liu, C.M., Shen, Y.J., Sun, H.Y., 2004. Effect of soil water deficit on evapotranspiration, crop yield, and water use efficiency in the North China Plain. Agricultural Water Management, 64(2): 107-122. Impact Factor: 3.182
  5. Zhang, Y.Q.*, Liu, C.M., Yu, Q., Shen, Y.J., Kendy, E., Kondoh, A., Tang, C.Y., Sun, H.Y., 2004. Energy fluxes and the Priestley-Taylor parameter over winter wheat and maize in the North China Plain. Hydrological Processes, 18(12): 2235-2246. Impact Factor: 3.181
  6. Zhang, Y.Q.*, Yu, Q., Liu, C.M., Jiang, J., Zhang, X.Y., 2004. Estimation of winter wheat evapotranspiration under water stress with two semiempirical approaches. Agronomy Journal, 96(1): 159-168. Impact Factor: 1.897
  7. 房全孝, 陈雨海, 李全起, 于舜章, 罗毅, 于强, 欧阳竹. 灌溉对冬小麦水分利用效率的影响研究. 农业工程学报, 2004, 4: 34-39. Fang, Q.X., Chen, Y.H., Li, Q.Q., Yu, S.Z., Luo, Y., Yu, Q., Ouyang, Z., 2004. Effect of irrigation on water use efficiency of winter wheat. Transactions of the CSAE, 20(4): 34-39.
  8. 李龙辉, 郑有飞, 于强*. 冬小麦同化物生产与分配对水分胁迫响应的模拟模型研究. 中国生态农业学报, 2004, 12(3): 51-54. Li, L.H., Zeng, Y.F., Yu, Q., 2004. Winter wheat photosynthesis and biomass accumulation model under water stress conditions. Chinese Journal of Eco-Agriculture, 12(3): 51-54.
  9. 秦钟, 于强*, 许守华, 胡秉民, 孙晓敏, 刘恩民, 王吉顺, 于贵瑞, 朱治林. 华北平原玉米田水热通量及作物水分利用效率特征和模拟. 中国科学D辑, 2004, 34(s2): 183-192.
  10. 王靖, 于强, 李湘阁, 孙晓敏, 朱治林. 用光合-蒸腾耦合模型模拟CO2通量的日变化. 生态学报, 2004, 24(12): 2782-2788. Wang, J., Yu, Q., Li, X.G., Sun, X.M., Zhu, Z.L., 2004. Modeling diurnal variations of CO2 flux over winter wheat with a coupled model of photosynthesis and evapotranspiration. ACTA Ecologica SINICA, 24(12): 2782-2788.
  11. 王靖, 于强, 李湘阁, 孙晓敏. 用光合-蒸腾耦合模型模拟水热通量的日变化. 应用生态学报, 2004, 15(11): 2077-2082. Wang, J., Yu, Q., Li, X.G., Sun, X.M., 2004. Diurnal variation of winter wheat water and heat fluxes of a simulation with photosynthesis evapotranspiration couple model. Chinese Journal of Applied Ecology, 15(11): 2077-2082.
  12. 徐雨晴, 陆佩玲, 于强, 气候变化对植物物候影响的研究进展. 资源科学, 2004, 26(1): 129-136. Xu, Y.Q., Lu, P.L., Yu, Q., 2004. Review and prospect in the researches of influence of climate change on plant phenology. 26(1): 129-136.
  13. 徐雨晴, 陆佩玲, 于强. 气候变化对我国刺槐、紫丁香始花期的影响. 北京林业大学学报, 2004, 26(6): 94-97. Xu, Y.Q., Lu, P.L., Yu, Q., 2004. Impacts of climate change on first-flowering dates of Robinica pseudoacacia L. and Syringa amurensis Rupr. in China. Journal of Beijing Forestry University, 26(4): 94-97.
  14. 杨彦武, 于强*, 王靖. 近40年华北及华东局部主要气候资源要素的时空变异性. 资源科学, 2004, 26(4): 45-50. Yang, Y.W., Yu, Q., Wang, J., 2004. Spatio-temporal variations of principal climatic factors in North China and part of East China within past 40 years. Resources Science, 26(4):45-50.
  15. 於莉, 于强, 罗毅, 刘敏华, 水分胁迫对冬小麦物质分配及产量构成的影响. 地理科学进展, 2004, 23(1): 105-112. Yu, L., Yu, Q., Luo, Y., Liu, M.H., 2004. Effect of water stress on dry-matter partition and yield constitution of winter wheat. Progress in Geography, 23(1): 105-112.
  16. Zhang, Y.Q., Liu, C.M., Yu, Q., 2004. Water nd heat transfer mechanics in the soil-plant-atmosphere continuum and regional evapotranspiration model. Journal of Graduate School of the Chinese Academy of Sciences, 21(4): 562-567.
  17. 张永强, 于强, 刘昌明, 王靖, 植被光合、冠层导度和蒸散的耦合模拟. 中国科学D辑, 2004, 34(s2): 152-160.

2003

  1. Liu, J.D.*, Zhou, X., Yu, Q., 2003. Numerical analysis of the source-sink alternation of composite global warming potential of the paddy ecosystem in the Yangtze Delta. Science China-Earth Sciences, 46(4): 385-396. Impact Factor: 2.058
  2. 任巍, 姚克敏, 于强*, 欧阳竹, 王菱. 水分调控对冬小麦同化物分配与水分利用效率的影响研究. 中国生态农业研究, 2003, 11(4): 92-94. Ren, W., Yao, K.M., Yu, Q., Ouyang, Z., Wang, L., 2003. Effect of water control in combination of dry matter partition and water use efficiency of winter wheat. Chinese Journal of Eco-Agriculture, 11(4): 92-94.
  3. 王靖, 李湘阁, 刘恩民, 于强*. 华北平原冬小麦相对蒸散与叶面积指数及表层土壤含水量的关系. 中国生态农业学报, 2003, 11(2): 32-34. Wang, J., Li, X.G., Liu, E.M., Yu, Q.*, 2003. The relationship between relative evaportransiration and leaf area index and surface soil water content in winter wheat field of North China Plain. Chinese Journal of Eco-Agriculture, 11(2): 32-34.
  4. 邬定荣, 欧阳竹, 赵小敏, 于强*, 作物生长模型WOFOST在华北平原的适用性研究. 植物生态学报, 2003, 27(5): 594-602. Wu, D.R., Ouyang, Z., Zhao, X.M., Yu, Q.*, 2003. The applicability research of WOFST model in North China Plain. ACTA Phytoecologica SINICA, 27(5): 594-602.

2002

  1. Yu, Q.*, Liu, J.D., Zhang, Y.Q., Li, J., 2002. Simulation of rice biomass accumulation by an extended logistic model including influence of meteorological factors. International Journal of Biometeorology, 46(4): 185-191. Impact Factor: 2.577
  2. Yu, Q.*, Liu, Y.F., Liu, J.D., Wang, T.D., 2002. Simulation of leaf photosynthesis of winter wheat on Tibetan Plateau and in North China Plain. Ecological Modelling, 155(2-3): 205-216. Impact Factor: 2.507
  3. Zhang Y.Q., Sheng Y.J., Yu Q., Liu, C.M., 2002. Variation of Fluxes of Water Vapor, Sensible Heat and Carbon Dioxide above Winter Wheat and Maize Canopies. Journal of Geographical Sciences, 12(3): 295-300.
  4. 张永强, 沈彦俊, 刘昌明, 于强, 孙宏勇, 贾金生, Kondoh, A., 华北平原典型农田水、热与CO2通量的测定. 地理学报, 2002, 57: 333-342. Zhang, Y.Q., Shen, Y.J., Liu, C.M., Yu, Q., Sun, H.Y., Jia, J.S., Kondoh, A., 2002. Measurement and analysis of water, heat and CO2 flux from a farmland in the North China Plain. ACTA Geographica SINICA, 57: 333-342.

2001

  1. Yu, Q.*, Goudriaan, J., Wang, T.D., 2001. Modelling diurnal courses of photosynthesis and transpiration of leaves on the basis of stomatal and non-stomatal responses, including photoinhibition. Photosynthetica, 39(1): 43-51. Impact Factor: 1.740
  2. Yu, Q.*, Hengsdijk, H., Liu, J.D., 2001. Application of a progressive-difference method to identify climatic factors causing variation in the rice yield in the Yangtze Delta, China. International Journal of Biometeorology, 45(2): 53-58. Impact Factor: 2.577
  3. 于强*, 王天铎, 农田生态系统模型与农业资源高效利用, 世界科技研究与发展. 2001, 23(5): 22-27. Yu, Q.*, Wang, T.D., 2001. Agricultural Ecosystem Model and High Efficient Utilization of Resource. World SCI-Tech R&D, 23(5): 22-27.
  4. 陆佩玲, 于强, 罗毅, 刘建栋. 冬小麦光合作用的光响应曲线的拟合. 中国农业气象, 2001, 22(2): 12-14. Lu, P.L., Yu, Q., Luo, Y., Liu, J.D., 2001. Fitting light response curves of photosynthesis of winter wheat. Chinese Journal of Agrometeorology, 22(2): 12-14.

2000

  1. Yu, Q.*, Liu, J.D., Luo, Y., 2000. Applicability of some stomatal models to natural conditions. Journal of Integrative Plant Biology, 42(2): 203-206. Impact Factor: 3.129
  2. 陆佩玲, 罗毅, 刘建栋, 于强. 华北地区冬小麦光合作用的光响应曲线的特征参数. 应用气象学报. 2000, 11(2): 234-241. Lu, P.L., Luo, Y., Liu, J.D., Yu, Q., 2000. Character is tic parameters of light response curves of photosynthesis of winter wheat in North China. Quarterly Journal of Applied Meteorology, 11(2): 234-241.
  3. 陆佩玲, 于强, 罗毅. 华北地区冬小麦田辐射过程和热量过程的基本特征. 生态农业研究, 2000, 8(1): 10-13. Lu, P.L., Yu, Q., Luo, Y., 2000. Characteristics of radiation and heat processes over wheat field in North China Plain. Eco-agriculture Research, 8(1): 10-13.

1990s

  1. Yu, Q.* and Wang, T.D., 1998. Simulation of the physiological responses of C3 plant leaves to environmental factors by a model which combines stomatal conductance, photosynthesis and transpiration. Journal of Integrative Plant Biology, 40(8): 740-754. Impact Factor: 3.129
  2. 于强*, 陆佩玲, 刘建栋, 傅抱璞, 姚克敏, 作物光温生产力模型和南方水稻适宜生长期的数值分析. 自然资源学报, 1999, 14(2): 163-168. Yu, Q.*, Lu, P.L., Liu, J.D., Fu, B.P., Yao, K.M., 1999. Crop Photo-temperature Productivity Model and Numerical Analysis of Suitable Growth Season of Rice in Southern China. Journal of Natural Resources,1999, 14(2): 163-168.
  3. 于强*, 谢贤群, 孙淑芬, 王天铎, 陆佩玲, 植物光合生产力和冠层蒸散的模拟研究进展. 生态学报, 1999, 19(5): 744-753. Yu, Q.*, Xie, X.Q., Sun, S.F., Wang, T.D., Lu, P.L., 1999. Advances in Simulation of Plant Photosynthetic Productivity and Canopy Evapotranspiration. ACTA Ecologica SINICA, 19(5): 744-753.
  4. 陆佩玲, 任保华, 于强. 玉米冠层凝露的观测与模拟. 生态学报, 1998, 18(6): 615-620. Lu, Peiling, Ren, B.H., Yu, Q.. The observation and simulation of dew form ation over maize canopy. ACTA Ecologica SINICA, 1998, 18(6): 615-620.
  5. 于强*, 任保华, 王天铎, 孙淑芬. C3植物光合作用日变化的模拟. 大气科学, 1998, 22(6): 865-880. Yu, Q.*, Ren, B.H., Wang, T.D., Sun, S.F., 1998. A Simulation of Diurnal Variations of Photosynthesis of C3 Plant Leaves. Scientia Atmospherica SINICA, 22(6): 865-880.
  6. 于强*, 王天铎, 刘建栋, 孙淑芳, 玉米株型与冠层光合作用的数学模型研究 I. 模型与验证. 作物学报, 1998, 24(1): 7-15. Yu, Q.*, Wang, T.D., Liu, J.D., Sun, S.F., 1998. A Mathematical Study on Crop Architecture and Canopy Photosynthesis I: Model. ACTA Agronomica SINICA, 24(1): 7-15.
  7. 于强*, 王天铎, 孙淑芬, 任保华, 玉米株型与冠层光合作用的数学模型研究 II. 数值分析. 作物学报, 1998, 24(3): 272-279. Yu, Q.*, Wang, T.D., Sun, S.F., Ren, B.H., 1998. A Mathematical Study on Crop Architecture and Canopy Photosynthesis II: Numerical Study. ACTA Agronomica SINICA, 24(3): 272-279.
  8. 于强*, 彭乃志, 傅抱璞, 三峡气候的基本特征和成因的初步研究, 湖泊科学, 1996, 8(4): 324-330. Yu, Q.*, Peng, N.Z., Fu, B.F., 1996. A Preliminary Study on Climatic Characteristics and Cause of Formation in Three Gorges. Journal of Lake Sciences. 8(4): 324-330.
  9. 于强*, 傅抱璞, 姚克敏, 包容生态因子的广义Logistic模型, 生态学报, 1996, 16(3): 289-294. Yu, Q.*, Fu, B.P., Yao, K.M., 1996. An Augmented Logistic Model Taking Account of Ecological Factors. ACTA Ecologica SINICA, 16(3): 289-294.
  10. 于强*, 陆佩玲, 巢湖对冬季陆面辐射过程和热量过程的影响, 湖泊科学, 1996, 8(1): 8-15. Yu, Q.*, Lu, P.L., 1996. Influence of Chaohu Lake on Radiation and Heat Processes over Land Surface in Water. Journal of Lake Sciences. 8(1): 8-15.
  11. 于强*, 傅抱璞, 姚克敏, 水稻叶面积指数的普适增长模型, 中国农业气象, 1995, 16(2): 6-8. Yu, Q.*, Fu, B.P., Yao, K.M., 1995. A Universal Development Model of Leaf Area Index of Rice. Chinese Journal of Agrometeorology, 16(2): 6-8.
  12. 于强*, 傅抱璞, 彭乃志, 陈明, 辐射日总量的最热坡度解析模式及其全球分布规律, 地理学报, 1994, 49(6): 526-532. Yu, Q.*, Fu, B.P., Peng, N.Z., Chen, M., 1994. Analytic models for warmest slope calculated according to the solar radiation and its global distribution. ACTA Geographica SINICA. 49(6): 526-532.
  13. 于强*, 安徽大别山南麓柑桔冻害分布模式的研究, 地理研究, 1992, 11(3): 95-97. Yu, Q., 1992. A Study of Topography-Low Temperature Model on the South Slope MT. Dabie In Anhui Province, Geographical Research, 11(3): 95-97.

指导和培养的学生

博士后

博士生

硕士生

悉尼科技大学（UTS）

 

学术专著（Book Chapter）