| Modeling and simulating of reservoir operation using the artificial neural network, support vector regression, deep learning algorithm D Zhang, J Lin, Q Peng, D Wang, T Yang, S Sorooshian, X Liu, J Zhuang Journal of Hydrology 565, 720-736, 2018 | 265 | 2018 |
| Developing reservoir monthly inflow forecasts using artificial intelligence and climate phenomenon information T Yang, AA Asanjan, E Welles, X Gao, S Sorooshian, X Liu Water Resources Research 53 (4), 2786-2812, 2017 | 263 | 2017 |
| Assessment of CMIP5 climate models and projected temperature changes over Northern Eurasia C Miao, Q Duan, Q Sun, Y Huang, D Kong, T Yang, A Ye, Z Di, W Gong Environmental Research Letters 9 (5), 055007, 2014 | 227 | 2014 |
| Detecting the quantitative hydrological response to changes in climate and human activities J Wu, C Miao, X Zhang, T Yang, Q Duan Science of the Total Environment 586, 328-337, 2017 | 199 | 2017 |
| Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau X Liu, T Yang, K Hsu, C Liu, S Sorooshian Hydrology and Earth System Sciences 21 (1), 169-181, 2017 | 191 | 2017 |
| Shortterm precipitation forecast based on the PERSIANN system and LSTM recurrent neural networks A Akbari Asanjan, T Yang, K Hsu, S Sorooshian, J Lin, Q Peng Journal of Geophysical Research: Atmospheres 123 (22), 12,543-12,563, 2018 | 164 | 2018 |
| Simulating California reservoir operation using the classification and regressiontree algorithm combined with a shuffled crossvalidation scheme T Yang, X Gao, S Sorooshian, X Li Water Resources Research 52 (3), 1626-1651, 2016 | 160 | 2016 |
| Drought evolution and its impact on the crop yield in the North China Plain X Liu, Y Pan, X Zhu, T Yang, J Bai, Z Sun Journal of hydrology 564, 984-996, 2018 | 139 | 2018 |
| Improving the multi-objective evolutionary optimization algorithm for hydropower reservoir operations in the California Oroville–Thermalito complex T Yang, X Gao, SL Sellars, S Sorooshian Environmental Modelling & Software 69, 262-279, 2015 | 112 | 2015 |
| Human activities aggravate nitrogen-deposition pollution to inland water over China Y Gao, F Zhou, P Ciais, C Miao, T Yang, Y Jia, X Zhou, BB Klaus, T Yang, ... National Science Review 7 (2), 430-440, 2020 | 96 | 2020 |
| An enhanced artificial neural network with a shuffled complex evolutionary global optimization with principal component analysis T Yang, AA Asanjan, M Faridzad, N Hayatbini, X Gao, S Sorooshian Information Sciences 418, 302-316, 2017 | 95 | 2017 |
| A remote sensing and artificial neural network-based integrated agricultural drought index: Index development and applications X Liu, X Zhu, Q Zhang, T Yang, Y Pan, P Sun Catena 186, 104394, 2020 | 91 | 2020 |
| Impacts of rainfall and inflow on rill formation and erosion processes on steep hillslopes P Tian, X Xu, C Pan, K Hsu, T Yang Journal of Hydrology 548, 24-39, 2017 | 84 | 2017 |
| Evaluation of typical methods for baseflow separation in the contiguous United States J Xie, X Liu, K Wang, T Yang, K Liang, C Liu Journal of Hydrology 583, 124628, 2020 | 77 | 2020 |
| Genome-wide association mapping of starch pasting properties in maize using single-locus and multi-locus models Y Xu, T Yang, Y Zhou, S Yin, P Li, J Liu, S Xu, Z Yang, C Xu Frontiers in plant science 9, 1311, 2018 | 75 | 2018 |
| Applying the water footprint and dynamic structural decomposition analysis on the growing water use in China during 1997–2007 Z Yang, H Liu, X Xu, T Yang Ecological indicators 60, 634-643, 2016 | 75 | 2016 |
| Investigation of the probability of concurrent drought events between the water source and destination regions of China's water diversion project X Liu, Y Luo, T Yang, K Liang, M Zhang, C Liu Geophysical Research Letters 42 (20), 8424-8431, 2015 | 75 | 2015 |
| New insight into global blue carbon estimation under human activity in land-sea interaction area: A case study of China Y Gao, G Yu, T Yang, Y Jia, N He, J Zhuang Earth-Science Reviews 159, 36-46, 2016 | 72 | 2016 |
| Can artificial intelligence and data-driven machine learning models match or even replace process-driven hydrologic models for streamflow simulation?: A case study of four … T Kim, T Yang, S Gao, L Zhang, Z Ding, X Wen, JJ Gourley, Y Hong Journal of Hydrology 598, 126423, 2021 | 71 | 2021 |
| Assessment of the influences of different potential evapotranspiration inputs on the performance of monthly hydrological models under different climatic conditions P Bai, X Liu, T Yang, F Li, K Liang, S Hu, C Liu Journal of Hydrometeorology 17 (8), 2259-2274, 2016 | 65 | 2016 |
