120. Zhang Y, Ye, A*., Analui, B.; Nguyen, P.; Sorooshian, S.; Hsu, K.; Wang Y. , 2023. Comparing quantile regression forest and mixture density long short-term memory models for probabilistic post-processing of satellite precipitation-driven streamflow simulations. Hydrology and Earth System Sciences, 27(24): 4529-4550.DOI: 10.5194/hess-27-4529-2023. PDF
119. Wang Y, Ye, A*., Zhang Y, Yang F, 2023. The quantitative attribution of climate change to runoff increase over the Qinghai-Tibetan Plateau. Science of The Total Environment, 897, 165326. DOI: 10.1016/j.scitotenv.2023.165326. PDF
118. [3]. Zhou J, Li Q*, Ye, A*., 2023. An improved methodology for quantifying the impact of human activities on hydrological drought change. Journal of Hydrology: Regional Studies, 50, 101603. DOI: 10.1016/j.ejrh.2023.101603. PDF
117. 杨帆，苗雨青， 叶爱中*., 2023. 巢湖水-气界面N2O通量排放特征及影响因素．湖泊科学，2023，35(6): 2000-2009. DOI: 10.18307/2023.0627. PDF
2022
116. Li Q, Ye, A*., Zhou J, Zhang Y, 2022. The peer-to-peer type propagation from meteorological drought to soil moisture drought occurs in areas with strong land-atmosphere interaction. Water Resources Research, 58, e2022WR032846. DOI: 10.1029/2022WR032846. PDF
115. Zhu Y, Ye, A*., Zhang, Yuhang. 2022. Changes of total and artificial Water bodies in mainland China over the past three decades. Journal of Hydrology, 613: 128344. DOI: 10.1016/j.jhydrol.2022.128344. PDF
114. Zhang Y, Ye, A*., 2022.Uncertainty analysis of multiple terrestrial gross primary productivity products. Global Ecology and Biogeography. DOI: 10.1111/geb.13578. PDF
113. Zhang Y, Ye, A*., Nguyen, P.; Analui, B.; Sorooshian, S.; Hsu, K. 2022.QRF4P-NRT: Probabilistic Post-processing of Near-real-time Satellite Precipitation Estimates using Quantile Regression Forests. Water Resources Research, e2022WR032117. DOI: 10.1029/2022WR032117. PDF
112. Zhang Y, Ye, A*., 2022. An improved global gross primary production dataset covering 1980–2018. Heliyon, 8(3): e09153. DOI: 10.1016/j.heliyon.2022.e09153. PDF
111. Wang Y, Ye, A*., Peng D, Miao C, Di Z, Gong W, 2022. Spatiotemporal variations in water conservation function of the Tibetan Plateau under climate change based on InVEST model. Journal of Hydrology: Regional Studies, 41, 101064. DOI: 10.1016/j.ejrh.2022.101064. PDF
2021
110. Zhang, Y, Ye, A*. 2021. Can machine learning improve short-term precipitation forecasts? — Multi-model comparison and experimental investigation. Journal of Hydrometeorology, DOI:10.1175/JHM-D-21-0096.1. PDF
109. Li H., Ye, A*., Zhang, Y.;Zhao W. 2021. Inter-comparison and evaluation of multi-source soil moisture products in China. Earth and Space Science，8, e2021EA001845 DOI: 10.1029/2021EA001845. PDF
108. Zhang, Y, Ye, A*., Nguyen, P.; Analui, B.; Sorooshian, S.; Hsu, K. 2021. New Insights Into Error Decomposition for Precipitation Products. Geophysical Research Letters, 48, e2021GL094092. DOI: 10.1029/2021GL094092. PDF
107. Zhang, Y, Ye, A*., Nguyen, P.; Analui, B.; Sorooshian, S.; Hsu, K. 2021. Error Characteristics and Scale Dependence of Current Satellite Precipitation Estimates Products in Hydrological Modeling. Remote Sens. 13, 3061. DOI: 10.3390/rs13163061. PDF
106. Zhang, Y, Ye, A*., You J, Jing X, 2021. Quantification of human and natural contributions to multi-dimensional hydrological alterations: A case study in the Upper Minjiang River, China. Journal of Geographical Science. 2021, 31(8): 1102-1122. DOI: 10.1007/s11442-021-1887-z. PDF
105. Zhang, Y, Ye, A*., 2021. Would the obtainable gross primary productivity (GPP) products stand up? A critical assessment of 45 global GPP products. Science of the Total Environment, 783: 146965 DOI: 10.1016/j.scitotenv.2021.146965. PDF
102. Zhang, Y, Ye, A*., 2021. Quantitatively distinguishing the impact of climate change and human activities on vegetation in Mainland China with the improved residual method. Giscience & Remote Sensing. DOI: 10.1080/15481603.2021.1872244. PDF
2020
101. Jiang S, Ye, A*., Xiao, C., 2020. The temperature increase in Greenland has accelerated in the past five years. Global and planetary change, 194, 103297. DOI: 10.1016/j.gloplacha.2020.103297. PDF
100. Zhang Y, Ye, A*.. 2020. Spatial and temporal variation in vegetation coverage using AVHRR GIMMS and Terra MODIS data in the Mainland of China. International Journal of Remote Sensing 41:11, 4238-4268, DOI:10.1080/01431161.2020.1714781 . PDF
99. Huang L, Ye, A*., Tang C, Duan Q, Zhang Y. 2020. Impact of rural depopulation and climate change on vegetation, runoff and sediment load in the Gan River basin, China. Hydrology Research, 51(4), 768 - 780. doi: 10.2166/nh.2020.120 . PDF
98. Lang Y, Luo L*， Ye, A., Duan Q. 2020. Do CFSv2 Seasonal Forecasts Help Improve the Forecast of Meteorological Drought over Mainland China? Water 2020, 12(7), 2010, doi: 10.3390/w12072010 . PDF
2019
97. Ma, F., Ye, A*., Duan, Q,. 2019. Seasonal drought ensemble predictions based on multiple climate models in the upper Han River Basin, China, Climate Dynamics, 53(12), 7447-7460. doi: 10.1007/s00382-017-3577-1. PDF
96. Ma F, Luo L., Ye, A*., Duan, Q,. 2019.Drought characteristics and propagation in the semi-arid Heihe River basin in Northwestern China. J. Hydrometeor. 20(1), 59-77. DOI: 10.1175/JHM-D-18-0129.1. PDF
95. Di Z*, Ye, A., Duan, Q,. et al. 2019.Assessment of Parametric Sensitivity Analysis Methods Based on A Quasi Two-Dimensional Groundwater Model. Journal of environmental informatics. doi:10.3808/jei.201900413. PDF
94. Li, W., Duan, Q., Ye, A., and Miao, C. 2019. An improved meta-Gaussian distribution model for post-processing of precipitation forecasts by censored maximum likelihood estimation. Journal of Hydrology 574, 801-810. PDF
93. 黄李东, 叶爱中*., 张疋亥, 汤崇军. 近30年中国典型区域水体面积变化与归因[J]. 南水北调与水利科技, 17(6):138-147. PDF
2018
92. Ma F, Luo L., Ye, A*., Duan, Q,. 2018.Seasonal drought predictability and forecast skill in the semi-arid endorheic Heihe River basin in Northwestern China. Hydrol. Earth Syst. Sci. ., 22, 5697–5709. DOI: 10.5194/hess-22-5697-2018. PDF
91. Hou, J., Ye, A*., You J, Ma, F and Duan, Q,. 2018. An estimate of human and natural contributions to changes in water resources in the upper reaches of the Mingjiang River. Science of the Total Environment. 635: 901-912. DOI: 10.1016/j.scitotenv.2018.04.163. PDF
90. Ma, F., Ye, A*., You J, Duan, Q,. 2018. 2015-16 floods and droughts in China, and its response to the strong El Niño. Science of the Total Environment. 627, 1473-1484, doi:https://doi.org/10.1016/j.scitotenv.2018.01.280. PDF
89. Ye, A*.,Zhou Z, You J, Ma, F, Duan, Q., 2018.Dynamic Manning's Roughness Coefficients for Hydrological Modelling in Basins. Hydrology Research xx, xxx-xxx. DOI: 10.2166/nh.2018.175. PDF
88. Gan Y*,Liang X, Duan Q, Ye, A.,Di Z, Hong Y. 2018. A systematic assessment and reduction of parametric uncertainties for a distributed hydrological model. Journal of Hydrology.564:697-711. DOI: 10.1016/j.jhydrol.2018.07.055 PDF
87. Yuan, X., Ji, P., Wang, L., Liang, X.-Z., Yang, K., Ye, A.,Su, Z. and Wen, J. 2018. High resolution land surface modeling of hydrological changes over the Sanjiangyuan region in the eastern Tibetan Plateau: 1. Model development and evaluation, Journal of Advances in Modeling Earth Systems, 0(ja), doi:10.1029/2018MS001412 PDF
86. Di, Z., Duan, Q., Wang, C., Ye, A., Miao, C., & Gong, W., 2017. Assessing the applicability of WRF optimal parameters under the different precipitation simulations in the Greater Beijing Area. Climate Dynamics, 1-22. doi:10.1007/s00382-017-3729-3 PDF
84. Ye A*, Deng X, Ma F, Duan Q, Zhou Z, Du C. 2017. Integrating weather and climate predictions for seamless hydrologic ensemble forecasting: A case study in the Yalong River basin. Journal of Hydrology.547:196-207. DOI: 10.1016/j.jhydrol.2017.01.053 PDF
83. Xu, J., Ye, A*., Duan, Q., Ma, F., Deng, X., Zhou, Z. 2017. Improvement of rank histograms for verifying reliability of extreme events ensemble forecasts [J]. Environmental Modelling & Software. doi: 10.1016/j.envsoft.2017.02.024. PDF
82. Du C., Ye, A*., Gan, Y, You, J, Duan, Q, Ma, F and Hou, J. 2017. Drainage network extraction from a high-resolution DEM using parallel programming in the .NET Framework, Journal of Hydrology, 555, 506-517, DOI: https://doi.org/10.1016/j.jhydrol.2017.10.034. PDF
81. Duan Q, Di Z, Quan J, Wang C, Gong W, Gan Y., Ye, A.,Miao C, Miao S, Liang X, Fan S. 2017. Automatic Model Calibration: A New Way to Improve Numerical Weather Forecasting. Bulletin of the American Meteorological Society 98:959-970. doi:10.1175/BAMS-D-15-00104.1. PDF
80. Li, W., Duan Q., Miao C., Ye, A.,Gong W., and Di Z., 2017. A review on statistical postprocessing methods for hydrometeorological ensemble forecasting, Wiley Interdisciplinary Reviews: Water, n/a-n/a, doi:10.1002/wat2.1246. PDF
79. Di, Z., Duan, Q., Gong, W.,Ye, A., Miao, C., 2017 Parametric sensitivity analysis of precipitation and temperature based on multi-uncertainty quantification methods in the Weather Research and Forecasting model. Science China Earth Sciences, 60(5), 876-898.doi:https://doi.org/10.1007/s11430-016-9021-6. PDF
78. 周正, 叶爱中*,马凤, 杜超. 基于贝叶斯理论的亚博网APP最新版本手机版多yobo体育官网登录入口预报[J]. 南水北调与水利科技, 2017, (01):1-6. PDF
2016
77. Ma, F, Ye A*, Deng, X, Zhou, Z, Liu, X, Duan, Q, Xu, J, Miao, C, Di, Z. and Gong, W. (2016), Evaluating the skill of NMME seasonal precipitation ensemble predictions for 17 hydroclimatic regions in continental China, International Journal of Climatology, , 36: 132–144. doi:10.1002/joc.4333. PDF
76. Mao Y, Ye A*, Liu, X,, Ma F et al. , 2016. High-resolution simulation of the spatial pattern of water use in continental China. Hydrological Sciences Journal, DOI:10.1080/02626667.2016.1153102 PDF
75. Duan, Q., Di, Z., Quan, J., Wang, C., Gong, W., Gan, Y., Ye, A., Miao, C., Miao, S., Liang, X. and Fan, S. Automatic model calibration - a new way to improve numerical weather forecasting. Bulletin of the American Meteorological Society, doi:doi:10.1175/BAMS-D-15-00104.1. PDF
74. Gong, W., Duan, Q., Li, J., Wang, C., Di, Z., Ye, A., et al.. (2016). Multiobjective adaptive surrogate modeling-based optimization for parameter estimation of large, complex geophysical models. Water Resources Research, n/a-n/a. doi: 10.1002/2015WR018230 PDF
73. Yuan, X., Ma, F., Wang, L., Zheng, Z., Ma, Z., Ye, A., Peng, S., 2016. An experimental seasonal hydrological forecasting system over the Yellow River basin - Part I: Understanding the role of initial hydrological conditions, Hydrol. Earth Syst. Sci.. 20, 2437–2451. doi:10.5194/hess-20-2437-2016 PDF
72. Quan J, Di Z, Duan Q, Gong W, Wang C, Gan Y, Ye A, Miao C. 2016. An Evaluation of Parametric Sensitivities of Different Meteorological Variables Simulated by the WRF Model. Quarterly Journal of the Royal Meteorological Society:n/a-n/a. DOI: 10.1002/qj.2885 PDF
71. Zhang Y, Shao Q, Ye A, Xing H, Xia J. 2016. Integrated water system simulation by considering hydrological and biogeochemical processes: model development, with parameter sensitivity and autocalibration. Hydrol. Earth Syst. Sci. 20:529-5. PDF
2015
70. Ye A*, Duan Q, Schaake J, Xu J, Deng X, Di Z, Miao C and Gong W, 2015. Post-processing of Ensemble Low Flow Forecasts. Hydrological Processes, 29, 2438–2453. (SCI) DOI: 10.1002/hyp.10374 Published: 2015.4.20, online 6 2014.11.6 PDF
69. Ma, F, Ye A*, Deng, X, Zhou, Z, Liu, X, Duan, Q, Xu, J, Miao, C, Di, Z. and Gong, W. (2015), Evaluating the skill of NMME seasonal precipitation ensemble predictions for 17 hydroclimatic regions in continental China, International Journal of Climatology, n/a-n/a, doi:10.1002/joc.4333. (SCI) Published: 2015.4.10 on linePDF
68. Mao Y, Ye A*, Liu, X,, Ma F et al. , 2015. High-resolution simulation of the spatial pattern of water use in continental China. Hydrological Sciences Journal (SCI) Published: 2015.11.10PDF
67. Ma F, Yuan X*, and Ye A, 2015. Seasonal Drought Predictability and Forecast Skill over China. Journal of Geophysical Research,120,8264-8275. (SCI)PDF
66. Kong, D., Miao, C., Borthwick, A.G.L., Duan, Q., Liu, H., Sun, Q., Ye, A., Di, Z. and Gong, W. (2015) Evolution of the Yellow River Delta and its relationship with runoff and sediment load from 1983 to 2011. Journal of Hydrology 520(0), 157-167. (SCI) Published: 2015.1.16PDF
65. Kong, D., Miao, C., Wu, J., Duan, Q., Sun, Q., Ye, A., Di, Z. and Gong, W. (2015) The hydro-environmental response on the lower Yellow River to the water–sediment regulation scheme. Ecological Engineering 79, 69-79. (SCI) Published: 2015.3.9PDF
64. Di, Z., Duan, Q., Gong, W., Wang, C., Gan, Y., Quan, J., Li, J., Miao, C., Ye, A. and Tong, C. (2015), Assessing WRF model parameter sensitivity: A case study with 5 day summer precipitation forecasting in the Greater Beijing Area, Geophys. Res. Lett., 42, 579–587, doi:10.1002/2014GL061623. (SCI) Published: 2015.1.22PDF
63. Gong, W., Duan, Q., Li, J., Wang, C., Di, Z., Dai, Y., Ye, A., and Miao, C. , 2015. Multi-objective parameter optimization of common land model using adaptive surrogate modeling, Hydrol. Earth Syst. Sci., 19, 2409-2425, doi:10.5194/hess-19-2409-2015. (SCI) Published: 2015.5.21PDF
62. Chen, Y., Yuan, W., Xia, J., Fisher, J.B., Dong, W., Zhang, X., Liang, S., Ye, A., Cai, W. and Feng, J. (2015) Using Bayesian Model Averaging to Estimate Terrestrial Evapotranspiration in China. Journal of Hydrology (doi:10.1016/j.jhydrol.2015.06.059). (SCI) Published: 2015.6.16PDF
61. Gong, W., Duan, Q., Li, J., Wang, C., Di, Z., Ye, A., Miao, C. , and Dai, Y., 2015. An Intercomparison of Sampling Methods for Uncertainty Quantification of Environmental Dynamic Models. Journal of Environmental Informatics (DOI: 10.3808/jei.201500310) (SCI) Published: 2015.7.13PDF
60. Zhang, Y., Shao, Q. , Ye, A. , Xing, H., & Xia, J. (2015). Integrated water system simulation by considering hydrological and biogeochemical processes: model development, parameter sensitivity and autocalibration. Hydrol. Earth Syst. Sci. Discuss., 12(5), 4997-5053. doi: 10.5194/hessd-12-4997-2015PDF
56. Ye A, Duan Q, Chu W, Xu J, Mao Y, 2014. The impact of the South–North Water Transfer Project (CTP)'s central route on groundwater table in the Hai River basin, North China. Hydrological Processes 28, 5755–5768, DOI: 10.1002/hyp.10081. (SCI) Published: 2014.10.14PDF
55. Ma F, Ye A*, Gong W, Mao Y, Miao C, Di Z, 2014. An estimate of human and natural contributions to flood changes of the Huai River. Global and Planetary Change 119, 39-50. (SCI) Published: 2014.5.20 online 2014.8.1 pressPDF
54. Ye A, Duan Q, Yuan X, Wood EF, Schaake J, 2014. Hydrologic post-processing of MOPEX streamflow simulations. Journal of Hydrology 508, 147-56. (SCI) Published: 2014.1.16PDF
53. Lang Y., Ye A., Gong W., Miao C., Di Z., Xu J., Liu Y., Luo L. and Duan Q, 2014: Evaluating Skill of Seasonal Precipitation and Temperature Predictions of NCEP CFSv2 Forecasts over 17 Hydroclimatic Regions in China. J. Hydrometeor, 15, 1546–1559. doi: http://dx.doi.org/10.1175/JHM-D-13-0208.1 Published: 2014.8.1PDF
52. Zhang, H., Liu, S., Yuan, W., Dong, W., Ye, A., Xie, X., Chen, Y., Liu, D., Cai, W. and Mao, Y, 2014. Inclusion of soil carbon lateral movement alters terrestrial carbon budget in China. Sci. Rep. 4. doi: 10.1038/srep07247 (SCI) Published: 2014.11.28PDF
51. Mao Y, Ye A*, Xu J, Ma F et al., 2014. An advanced distributed automated extraction of drainage network model on high-resolution DEM. Hydrol. Earth Syst. Sci. Discuss. 11, 7441-67. doi:10.5194/hessd-11-7441-2014.PDF
50. Zhang, Y., Shao, Q., Ye, A. and Xing, H. (2014) An integrated water system model considering hydrological and biogeochemical processes at basin scale: model construction and application. Hydrol. Earth Syst. Sci. Discuss. 11(8), 9219-9279.PDF
49. Wang C, Duan Q, Gong W, Ye A, Di Z, Miao C, 2014. An evaluation of adaptive surrogate modeling based optimization with two benchmark problems. Environmental Modelling & Software 60, 167-79. (SCI) Published: 2014.10.1PDF
48. Tao Y, Duan Q, Ye A, Gong W, Di Z, Xiao M and Hsu K, 2014. An evaluation of post-processed TIGGE multimodel ensemble precipitation forecast in the Huai river basin, Journal of Hydrology, 519, Part D(0), 2890-2905, doi:http://dx.doi.org/10.1016/j.jhydrol. 2014.04.040. (SCI) Published:2014.11.1PDF
47. Gan Y, Duan Q, Gong W, Tong C, Sun Y, Chu W, Ye A, Miao C, Di Z, 2014. A comprehensive evaluation of various sensitivity analysis methods: A case study with a hydrological model. Environmental Modelling & Software 51, 269-85. (SCI) Published: 2014.1.1PDF
46. Sun Q, Miao C, Duan Q, Kong D, Ye A, Di Z, Gong W, 2014. Would the ‘real’ observed dataset stand up? A critical examination of eight observed gridded climate datasets for China. Environmental Research Letters 9, 015001. (SCI) Published: 2014.1.15PDF
45. Sun Q, Kong D, Miao C, Duan Q, Yang T, Ye A, Di Z and Gong W, 2014 Variations in global temperature and precipitation for the period of 1948 to 2010. Environmental monitoring and assessment, 186(9):5663-79. doi: 10.1007/s10661-014-3811-9 (SCI) Published: 2014.9.1PDF
44. Miao, C., Duan Q., Sun Q., Huang Y., Kong D., Yang T., Ye A., Di Z., and Gong W., 2014. Assessment of CMIP5 climate models and projected temperature changes over Northern Eurasia, Environmental Research Letters, 9(5), 055007. (SCI) Published: 2014.5.28PDF
43. She D, Xia J, Zhang D, Ye A, Sood A, 2014. Regional extreme-dry-spell frequency analysis using the L-moments method in the middle reaches of the Yellow River Basin, China. Hydrological Processes 28(17), 4694-4707. (SCI) Published: 2014.8.15PDF
40. Ye A, Duan Q, Zhan C, Liu Z, Mao Y, 2013. Improving kinematic wave routing scheme in Community Land Model. Hydrology Research 44, 886-903. (SCI) Published: 2013.10.8PDF
39. Li J, Duan QY, Gong W, Ye A, et al., 2013. Assessing parameter importance of the Common Land Model based on qualitative and quantitative sensitivity analysis. Hydrol. Earth Syst. Sci. 17, 3279-93. (SCI) Published：2013.8.21PDF
38. Shangguan W, Dai Y, Liu B, Zhu A, Duan Q, Wu L, Ji D, Ye A, et al., 2013. A China data set of soil properties for land surface modeling. Journal of Advances in Modeling Earth Systems 5, 212-24. (SCI) Published：2013.6.21PDF
37. Liu, Y., Q. Duan, L. Zhao, A. Ye, Y. Tao, C. Miao, X. Mu, and J. C. Schaake (2013), Evaluating the predictive skill of post-processed NCEP GFS ensemble precipitation forecasts in China's Huai river basin, Hydrological Processes, 27(1), 57-74. (SCI)PDF
33. Mao Y, Ye A, Xu J, 2012. Using Land Use Data to Estimate the Population Distribution of China in 2000. Giscience & Remote Sensing 49, 822-53. (SCI)PDF
32. Wei Shangguan, Yongjiu Dai, Baoyuan Liu, Aizhong Ye, Hua Yuan. 2012. A soil particle-size distribution dataset for regional land and climate modelling in China. Geoderma, 171-172: 85-91, doi:10.1016/j.geoderma.01.013. (SCI)PDF
27. Xia J, Zhang Y, Zhan C, Ye A, 2011. Water Quality Management in China: The Case of the Huai River Basin. International Journal of Water Resources Development 27, 167-80. (SCI)PDF
26. Zhao, L., Duan, Q., Schaake, J., Ye, A., and Xia, J. A hydrologic post-processor for ensemble streamflow predictions, Adv. Geosci., 2011, 29, 51-59.PDF
25. Zhan C, Xu Z, Ye A, et al. 2011. LUCC and its impact on runoff yield in the Bai river catchment, upstream of the Miyun reservoir basin. J Plant Ecol;4:61-66. (SCI)PDF
2010
24. Ye A, Duan Q, Zeng H, Li L, Wang C, 2010. A Distributed Time—Variant Gain Hydrological Model Based on Remote Sensing. Journal of Resources and Ecology 1, 222-30.PDF
22. Chen Xiangdong, Xia Jun, Ye Aizhong, Zhang Yongyong, "A Retrospective Temporal Integration Method for Richards' Equation," csie, vol. 2, pp.591-595, 2009 WRI World Congress on Computer Science and Information Engineering, 2009 (EI)PDF
17. Xia J, Ye A, Wang L, etc.. Water cycle mechanisms on the Loess Plateau, China: the Chabagou catchment case study. Methodology in Hydrology (Proceedings of the Second International Symposium on Methodology in Hydrology held in Nanjing, China, October–November 2005). IAHS Publ. 311, 2007. (EI)PDF
8. XIA Jun, WANG Gangsheng, YE Aizhong and NIU Cun-Wen. A Distributed Monthly Water Balance Model for Analyzing Impacts of Land Cover Change on Flow Regimes[J]. Pedosphere 2005, 15(6):761-767. (SCI)PDF
7. XIA Jun, WANG Gangsheng, TAN Ge, YE Aizhong & G.H. Huang. Development of distributed time-variant gain model for nonlinear hydrological systems[J]. Science in china series d:earth sciences, 2005, 48(6): 713-723 (SCI)PDF
6. YE Aizhong , XIA Jun, WANG Gangsheng. A Distributed Time-Variant Gain Model Applied to the Yellow River . Proceedings of the 2nd International Yellow River Forum(I). 2005, 10. (ISTP)PDF