PEER-REVIEWED | BOOKCHAPTER AND PROCEEDINGS | SELECTED PRESENTATIONS | INCITED TALKS

IDKey WordsCitation
108Precipitation extremesGazi Tawfiq Ezaz , Ke Zhang , Xin Li , Md Halim Shalehy , Mohammad Akram Hossain , Linxin Liu ,Spatiotemporal changes of precipitation extremes in Bangladesh during 1987–2017 and their connections with climate changes, climate, Global and Planetary Change oscillations, and monsoon dynamics
107hydrological-hydraulic model
Zhang, K; Shalehy, MH; Ezaz, GT; Chakraborty, A; Mohib, KM; Liu, LX;An integrated flood risk assessment approach based on coupled hydrological-hydraulic modeling and bottom-up hazard vulnerability analysis,Environmental Modelling and Software
106Flood forecastingZang, S., †Z. Li, †K. Zhang, C. Yao, Z. Liu, J. Wang, Y. Huang, and S. Wang (2021). Improving the flood prediction capability of the Xin’anjiang model by formulating a new physics-based routing framework and a key routing parameter estimation method, Journal of Hydrology, 603, 126867.
105Dry/wet conditionsChen, X., †Q. Quan, †K. Zhang, and J. Wei (2021). Spatiotemporal characteristics and attribution of dry/wet conditions in the Weihe River Basin within a typical monsoon transition zone of East Asia over the recent 547 years, Environmental Modelling and Software, 143, 105116.
104Water cycle曹易，†张珂，李致家，张维江，张菁 (2021). 宁夏三河源地区2000~2017 年水循环关键要素时空变化分析，水文，41(3), 88-94. [Cao, Y., †K. Zhang, Z. Li, W. Zhang, and J. Zhang (2021). Study on spatiotemporal variability and changes of key water cycle elements in the Three River Source Area of Ningxia from 2000 to 2017, Journal of China Hydrology, 41(3), 88-94].
103ETA comprehensive evaluation of five evapotranspiration datasets based on ground and GRACE satellite observations: implications for improvement of evapotranspiration retrieval algorithm, Remote Sensing, 13, 2414, doi:10.3390/rs13122414.
102Flood forecasting姚成，李致家，张珂，朱跃龙，刘志雨，黄迎春，龚珺夫，张锦堂，童冰星 (2021). 基于栅格型新安江模型的中小河流精细化洪水预报，河海大学学报（自然科学版）, 49(1), 19-25.
101Flood forecasting†李致家，朱跃龙，刘志雨，张珂，包红军，周国良，刘艳丽，何秉顺，万定生，李巧玲 (2021). 中小河流洪水防控与应急管理关键技术的思考，河海大学学报（自然科学版）, 49(1), 13-18.
100Flood forecasting†Sun, L., Z. Li, K. Zhang, and T. Jiang (2021). Impacts of precipitation and topographic conditions on the model simulation in the north of China, Water Science and Technology-Water Supply, 21 (3): 1025–1035.
99Precipitation张菁，†张珂，王晟，肖潺，陶然，鞠艳，李巧玲，李致家，阳辉，刘湘伟 (2021). 陕甘宁三河源区近50年极端降水时空变化分析，河海大学学报（自然科学版）, 49(3), 288-294
98ET†张珂，鞠艳，李致家 (2020). 金沙江流域实际蒸散发遥感重建及时空特征分析，水科学进展
97Water export范亚洲，†张珂，刘林鑫，晁丽君，姚 成 (2020). 水库水体的最大类间方差迭代遥感提取方法，水资源保护.
96Flood forecasting†张珂，牛杰帆，李曦，晁丽君 (2021). 洪水预报智能模型在中国半干旱半湿润区的应用对比，水资源保护，37(1), 28-35+60, doi:10.3880/j.issn.1004-6933.2021.01.005.
95PrecipitationLi, X., †K. Zhang, P. Gu, H. Feng, Y. Yin, W. Chen, and B. Cheng (2021). Changes in precipitation extremes in the Yangtze River Basin during 1960-2019 and the association with global warming, ENSO, and local effects, Science of the Total Environment, 757, 144244.
94WRF-Hydro-RAPID modeChao, L., †K. Zhang, Z.-L. Yang, J. Wang, P. Lin, J. Liang, Z. Li, and Z. Gu (2021). Improving flood simulation capability of the WRF-Hydro-RAPID model using a multi-source precipitation merging method, Journal of Hydrology, 592, 125814, doi:10.1016/j.jhydrol.2020.125814.
93Xin’anjiang ModelZang, S., †Z. Li, †C. Yao, K. Zhang, M. Sun, and X. Kong (2020). A new runoff routing scheme for Xin’anjiang Model and its routing parameters estimation based on geographical informaiton, Water, 12, 3429, doi:10.3390/w12123429.
92A hybrid runoff generation modelling frameworkLiu, Y., †K. Zhang, †Z. Li, Z. Liu, J. Wang, and P. Huang (2020). A hybrid runoff generation modelling framework based on spatial combination of three runoff generation schemes for semi-humid and semi-arid watersheds, Journal of Hydrology, 590, 125440.
91CA-Markov ModelRuben, Gebdang B., †K. Zhang, Z. Dong, and J. Xia (2020). Analysis and Projection of Land-Use/Land-Cover Dynamics through Scenario-Based Simulations Using the CA-Markov Model: A Case Study in Guanting Reservoir Basin, China, Sustainability, 12, 3747, doi:10.3390/su12093747.
90Green-Ampt rainfall-runoff modelHuo, W., †Z. Li, †K. Zhang, J. Wang, and C. Yao (2020). GA-PIC: an improved Green-Ampt rainfall-runoff model with a physically based infiltration distribution curve for semi-arid basins, Journal of Hydrology, 586, 124900, doi: 10.1016/j.jhydrol.2020.124900.
89Green-Ampt rainfall-runoff model†Li, Z., W. Huo, and K. Zhang (2020). Improvement and preliminary application of Green-Ampt rainfall-runoff model, Journal of Hohai University. Natural Sciences, 48(5), 385-391.
88Drought陶然，†张珂 (2020). 基于PDSI的中国近30年气象干旱特征及时空变化分析，水资源保护, 36(5), 78-85.
87Assessment framework†Zhang, K, G.B. Ruben, X. Li, Z. Li, Z. Yu, J. Xia, and Z. Dong (2020). A comprehensive assessment framework for quantifying climatic and anthropogenic contributions to streamflow changes: A case study in a typical semi-arid North China basin, Environmental Modelling & Software, 128, 104704, doi: 10.1016/j.envsoft.2020.104704.
86WRF-Hydro ModelSun, M., Z. Li, C. Yao, Z. Liu, J. Wang, A. Hou, K. Zhang, W. Huo, and M. Liu (2020). Evaluation of Flood Prediction Capability of the WRF-Hydro Model Based on Multiple Forcing Scenarios, Water, 12, 874, doi:10.3390/212030874.
85Global terrestrial energy fluxesForzieri, G., D.G. Miralles, P. Ciais, R. Alkama, Y. Ryu, G. Duveiller, K. Zhang, E. Robertson, M. Kautz, B. Martens, C. Jiang, A. Arneth, G. Georgievski, W. Li, G. Ceccherini, P. Anthoni, P. Lawrence, A. Wiltshire, J. Pongratz, S. Piao, S. Sitch, D.S. Goll, V.K. Arora1, S. Lienert, D. Lombardozzi, E. Kato, J.E.M.S. Nabel, H. Tian, P. Friedlingstein, and A. Cescatti (2020). Increased control of vegetation on global terrestrial energy fluxes. Nature Climate Change, 10, https://doi.org/10.1038/s41558-020-0717-0
84Ecohydrological responseLiao, S., L. Xue, Z. Dong, B. Zhu, K. Zhang, Q. Wei, F. Fu, and G. Wei (2020). Cumulative ecohydrological response to hydrological processes in arid basins. Ecological Indicators, 111, 106005.
83LandslideWang, S, †K. Zhang, L.P.H. van Beek, X. Tian, and T.A. Bogaard (2020). Physically-based landslide prediction over a large region: Scaling low-resolution hydrological model results for high-resolution slope stability assessment. Environmental Modelling and Software, 124, 104607, https://doi.org/10.1016/j.envsoft.2019.104607.
82ETWang Jingfeng, 刘元波，张珂 (2019). 最大熵增地表蒸散模型：原理及应用综述. 地球科学进展, 6, 596-605.
81Flood hazardKhaing ZM, †K. Zhang, H. Sawano, B.B. Shrestha, T. Sayama, K. Nakamura (2019). Flood hazard mapping and assessment in data-scarce Nyaungdon area, Myanmar. PLoS ONE 14(11): e0224558. https://doi.org/10.1371/journal.pone.0224558
80Climate change†Li, X., †K. Zhang, and V. Babovic (2019). Projections of future climate change in Singapore based on a multi-site multivariate downscaling approach, Water, 11, 2300, doi:10.3390/w11112300.
79Ecosystem Demography Model, version 2.2Longo, M., R. G. Knox, N. M. Levine, A. L. S. Swann, D. M. Medvigy, M. C. Dietze, Y. Kim, K. Zhang, D. Bonal, B. Burban, P.B. Camargo, M.N. Hayek, S.R. Saleska, R. da Silva, R.L. Bras, S.C. Wofsy, and P. R. Moorcroft (2019). The biophysics, ecology, and biogeochemistry of functionally diverse, vertically- and horizontally-heterogeneous ecosystems: the Ecosystem Demography Model, version 2.2 — Part 2: Model evaluation for tropical South America, Geoscientific Model Development, 12, 4347–4374.
78Ecosystem Demography Model, version 2.2Longo, M., R. G. Knox, D. M. Medvigy, N. M. Levine, M. C. Dietze, Y. Kim, A. L. S. Swann, K. Zhang, C. R. Rollinson, R.L. Bras, S.C. Wofsy, and P. R. Moorcroft (2019). The biophysics, ecology, and biogeochemistry of functionally diverse, vertically- and horizontally-heterogeneous ecosystems: the Ecosystem Demography Model, version 2.2 — Part 1: Model description, Geoscientific Model Development, 12, 4309–4346.
77Distributed Grid-Xinanjiang mode†Yao, C., J. Ye, Z. He, S. Bastola, †K. Zhang, and Z. Li (2019). Evaluation of flood prediction capability of the distributed Grid-Xinanjiang model driven by WRF precipitation, Journal of Flood Risk Management, 2019, 12(S1), e12544, doi: 10.1111/jfr3.12544.
76Soil moisture†Zhang, K., A. Ali, A. Antonarakis, M. Moghaddam, S. Saatchi, A. Tabatabaeenejad, R. Chen, S. Jaruwatanadilok, R. Cuenca, W.T. Crow, and †P. Moorcroft (2019). The Sensitivity of North American Terrestrial Carbon Fluxes to Spatial and Temporal Variation in Soil Moisture: An Analysis Using Radar-Derived Estimates of Root Zone Soil Moisture, Journal of Geophysical Research-Biogeosciences, 124, 3208-3231, doi: 10.1029/2018JG004589.
75Hydrological model†Huang, Y., A. Bardossy, and †K. Zhang (2019). Sensitivity of hydrological model to temporal and spatial resolutions of rainfall data, Hydrology and Earth System Sciences, 23, 1-17.
74Soil moisture†Zhang, K., L. Chao, Q. Wang, Y. Huang, R. Liu, Y. Hong, Y. Tu , W. Qu, and J. Ye (2019). Using multi-satellite microwave remote sensing observations for retrieval of daily surface soil moisture across China, Water Science and Engineering, 12(2): 85-97.
73Water use efficiencyZhang, K., Liu, L., Chao, L., et al., (2019). Spatiotemporal variations of terrestrial ecosystem water use efficiency in Yunnan Province from 2000 to 2014, Water Resources Protection, 35(5), 1–5, doi:10.3880/j.issn.1004-6933.2019.05.001.
72Soil moisture†Zhang, K., Q. Wang, L. Chao, J. Ye, Z. Li, Z. Yu, T. Yang, and Q. Ju (2019). Ground observation-based analysis of soil moisture spatiotemporal variability across a humid to semi-humid transitional zone in China, Journal of Hydrology, 574, 903-914.
71Soil moisture王青青，†张珂，叶金印，李致家（2019）.安徽省土壤湿度时空变化规律分析及遥感反演，河海大学学报（自然科学版），47(2), 114-118.
70Distributed hydrological modelChao, L, †K. Zhang, Z. Li, J. Wang, C. Yao, Q. Li (2019). Applicability assessment of the CASCade Two Dimensional SEDiment (CASC2D-SED) distributed hydrological model for flood forecasting across four typical medium and small watersheds in China, Journal of Flood Risk Management, 12(S1), e12518, doi:10.1111/jfr3.12518.
69Landslide and debris†Zhang, K., S. Wang, H. Bao, and X. Zhao (2019). Characteristics and influencing factors of rainfall-induced landslide and debris flow hazards in Shaanxi Province, China, Natural Hazards and Earth System Sciences, 19, 93-105.
68DroughtMohmmed, A., †K. Zhang, M. Kabenge, S. Keesstra, A. Cerda, M. Reuben, M. Elbashier, T. Dalson, and A. Ali (2018). Analysis of Drought and Vulnerability in the North Darfur Region of Sudan, Land Degradation & Development, 29, 4424-4438, doi:10.1002/ldr.3180.
67Distributed hydrological models包红军, 王凯, 张少杰, 王莉莉，刘敦龙, 张珂（2018）. 耦合分布式水文模型的泥石流物理模型预报试验，暴雨灾害，37（4），303-310.
66RunoffWu, X., Z. Zhang, X. Xiang, K. Zhang, H. Jin, X. Chen, C. Wang, Q. Shao, and W. Hua (2018). Changing runoff generation in the source area of the Yellow River: Mechanisms, seasonal patterns and trends, Cold Regions Science and Technology, 155, 58-68.
65ETXu, S., Z. Yu, C. Yang, X. Ji, and K. Zhang (2018). Trends in evapotranspiration and their responses to climate change and vegetation greening over the upper reaches of the Yellow River Basin, Agricultural and Forest Meteorology, 263, 118-129.
64Hydrological modelsHuo, W., †Z. Li, J. Wang, C. Yao, †K. Zhang, and Y. Huang (2018). Multiple hydrological models comparison and an improved Bayesian model averaging approach for ensemble prediction over semi-humid regions, Stochastic Environmental Research and Risk Assessment, doi:10.1007/s00477-018-1600-7.
63Amazon forestLongo, M., R.G. Knox, N.M. Levine, L.F. Alves, D. Bonal, P.B. Camargo, D.R. Fitzjarrald, M.N. Hayek, N. Restrepo-Coupe, S.R. Saleska, R. da Silva, S.C. Stark, R.P. Tapajos, K.T. Wiedemann, K. Zhang, S.C. Wofsy, P.R. Moorcroft (2018). Ecosystem heterogeneity and diversity mitigate Amazon forest resilience to frequent extreme droughts, New Phytologist, 219(3), 914-931, doi: 0.1111/nph.15185.
62Land cover changeLee, E., A. Livino, S.C. Han, K. Zhang, J. Briscoe, J. Kelman, and P. Moorcroft (2018). Land cover change explains the increasing discharge of the Parana River, Regional Environmental Change, 18(6), 1871-1881, doi:10.1007/s10113-018-1321-y.
61Flood forecastRen, W., T. Yang, P. Shi, C. Xu, K. Zhang, X. Zhou, Q. Shao, and P. Ciais (2018). A probabilistic method for streamflow projection and associated uncertainty analysis in a data sparse alpine region, Global and Planetary Change, 165, 100-113.
60Flash floodGuo, L., B. He, M. Ma, Q. Chang, Q. Li, K. Zhang, and Y. Hong (2018). A comprehensive flash flood defense system in China: overview, achievements, and outlook, Natural Hazards, 92(2), 727-740, doi: 10.1007/s11069-018-3221-3.
59PrecipitationChao, L., †K. Zhang, Z. Li , Y. Zhu, J. Wang, and Z. Yu (2018). Geographically Weighted Regression Based Methods For Merging Satellite and Gauge Precipitation, Journal of Hydrology, 558, 275-289.
58Canopy conductanceXu, S., Z. Yu, K. Zhang, X. Ji, C. Yang, and E.A. Sudicky (2018). Simulating canopy conductance of the Haloxylon ammodendron shrubland in an arid inland river basin of northwest China, Agricultural and Forest Meteorology, 249, 22-34.
57Flash FloodMa, M., H. Yu, H. Wang, F. Kong, K. Zhang, H. Yang, C. Liu, and Q. Liu (2018). Characteristics of Urban Waterlogging and Flash Flood Hazards and Their Integrated Preventive Measures: Case Study in Fuzhou, China, Journal of Sustainable Water in the Built Environment, 4(1): 05017007.
56Chemical Oxygen DemandRuben, G.B., †K. Zhang, H. Bao, and X. Ma (2018). Application and Sensitivity Analysis of Artificial Neural Network for Prediction of Chemical Oxygen Demand, Water Resources Management, 32(1), 273-283, doi:10.1007/s11269-017-1809-0.
55Flash floodHe, B., X. Huang, M. Ma, Q. Chang, Y. Tu, Q. Li, K. Zhang, and Y. Hong (2017). Analysis of flash flood disaster characteristics in China from 2011 to 2015, Natural Hazards, 90(1), 407-429, doi:10.1007/s11069-017-305207.
54Flood forecast李致家，姚成，张珂，朱跃龙，刘志雨，李巧玲，童冰星，黄小祥，黄鹏年 (2017). 基于网格的精细化降雨径流水文模型及其在洪水预报中的应用, 河海大学学报（自然科学版），45(6): 471-480.
53Soil moisture刘荣华，†张珂，晁丽君，王青青，洪阳，涂勇，曲伟 (2017). 基于多源卫星观测的中国土壤湿度时空特征分析，水科学进展，28(4), 479-487.
52Landslide包红军，†张珂，晁丽君，赵晓萌，刘艳辉，王晟，刘凑华 (2017). 基于水土耦合机制的流域滑坡预报研究，气象，43(9), 1138-1150.
51Flood forecast包红军，张珂，魏丽，李致家，宗志平，谌芸，狄靖月，栾承梅，刘开磊，曹勇 (2017). 淮河流域２０１６年汛期洪水预报试验，气象，43(7), 831-844.
50Hydrometeorological ApplicationsQi, Y., Q. Cao, B. Yong, K. Zhang, and Z. Li (2017). Hydrometeorological Applications: Severe Weather Precipitation Detection, Estimation, and Forecast, Advances in Meteorology, 8365319, doi:10.1155/2017/8365319.
49Distributed hydrological modelBao, H., K. Zhang, L. Wang, Z. Li, and C. Yao (2017). Application of a developed distributed hydrological model based on the mixed runoff generation model and 2-D kinematic wave flow routing model for better flood forecasting, Atmospheric Science Letters, 18, 284-293, doi:10.1002/asl.754.
48Recession flow analysis†Li, W., †K. Zhang, Y. Long, and L. Feng (2017). Estimation of active stream network length in a hilly headwater catchment using recession flow analysis, Water, 9 (5), 348, doi:10.3390/w9050348.
47Hydrological ModelWang, L., D. Chen, H. Bao, and K. Zhang (2017). On Simulation Improvement of the Noah_LSM by Coupling with a Hydrological Model Using a “Double-Excess” Runoff-production Scheme in GRAPES_Meso model, Meteorological Applications, 24, 512-520.
46Water Resources Management†Yang, N., †K. Zhang, Y. Hong, Q. Zhao, Q. Huang, Y. Xu, X. Xue, and S. Chen (2016). Evaluation of the TRMM Multisatellite Precipitation Analysis and Its Applicability in Supporting Reservoir Operation and Water Resources Management in Hanjiang basin, China, Journal of Hydrology, 549, 313-325.
45Runoff sensitivityLiu, D., A.K. Mishra, and K. Zhang (2017). Runoff sensitivity over Asia: Role of climate variables and initial soil conditions, Journal of Geophysical Research-Atmospheres, 122, 2218-2238, doi:10.1002/2016JD025694.
44Amazon forestGuimberteau, M., P. Ciais, A. Ducharne, J.P. Boisier, A.P.D. Aguiar, H. Biemans, H. D. Deurwaerder, D. Galbraith, B. Kruijt, F. Langerwisch, G. Poveda, A. Rammig, D. A. Rodriguez, G. Tejada, K. Thonicke, C. Von Randow, R.C. S. Von Randow, K. Zhang, and H.Verbeeck (2017). Impacts of future deforestation and climate change on the hydrology of the Amazon basin: a multi-model analysis with a new set of land-cover change scenarios, Hydrology and Earth System Sciences, 21, 1455-1475.
43CREST ModelShen, X., Y. Hong, K. Zhang, and Z. Hao (2017). Refine a Distributed Linear Reservoir Routing Method to Improve Performance of the CREST Model, Journal of Hydrologic Engineering, doi:10.1061/(ASCE)HE.1943-5584.0001442.
42Amazon forestMoghim, S., S. McKnight, K. Zhang, A. M. Ebtehaj, R.C. Knox, R.L. Bras, P.R. Moorcroft, and J. Wang (2016). Bias-corrected data sets of climate model outputs at uniform space-time resolution for land surface modelling over Amazonia, International Journal of Climatology, 37, 621-636, doi:10.1002/joc.4728.
41LandslidesHe, X., Y. Hong, H. Vergara, K. Zhang, P.E. Kirstetter, J.J. Gourley, Y. Zhang, G. Qiao, and C. Liu (2016). Development of a coupled hydrological-geotechnical framework for rainfall-induced landslides prediction, Journal of Hydrology, 543, 395-405.
40StreamflowLi, S., Y. Chen, Z. Li, and K. Zhang (2016). Applying a statistical method to streamflow reduction caused by underground mining for coal in the Kuye River basin, Science China Technological Sciences, 59(12), 1911-1920, doi: 10.1007/s11431-016-0393-4.
39Xinanjiang modelLi, Z., K. Liang, G. Kan, Q. Li, C. Yao, K. Zhang (2016). A method for deriving the river network flow concentration parameter Cs of the Xinanjiang model, Advances in Water Science, 27(5), 652-661.
38Landslide. †Zhang, K., X. Xue, Y. Hong, J. J. Gourley, N. Lu, Z. Wan, Z. Hong, and R. Wooten (2016). iCRESTRIGRS: A coupled modeling system for cascading flood-landslide disaster forecasting, Hydrology and Earth System Sciences, 20, 5035-5048, doi:10.5194/hess-20-5035-2016.
37Amazonian forestsJohnson, M.O., D. Galbraith, E. Gloor, H. De Deurwaerder, M. Guimberteau, A. Rammig, K. Thonicke, H. Verbeeck, C. von Randow, R.J.W. Brienen, T.R. Feldpausch, G. Lopez Gonzalez, A. Monteagudo, O.L. Phillips, C.A. Quesada, B. Christoffersen, P. Ciais, S. Gilvan, B. Kruijt, P. Meir, P. Moorcroft, K. Zhang, E.A. Alvarez, A Alves de Oliveira, I Amaral, A Andrade, L.E.O. C Aragao, A Araujo-Murakami, E.J.M. M Arets, L Arroyo, G. A Aymard, C Baraloto, J Barroso, D Bonal, R Boot, J Camargo, J Chave, A Cogollo, F Valverde Cornejo, L da Costa, A di Fiore, L Ferreira, N Higuchi, E Honorio, T J Killeen, S. G Laurance, W. F Laurance, J Licona, T Lovejoy, Y Malhi, B Marimon, B. H Junior Marimon, D.C. L Matos, C Mendoza, D. A Neill, G Pardo, M Peña-Claros, N.C. A Pitman, L Poorter, A Prieto, H Ramirez-Angulo, A Roopsind, A Rudas, R. P Salomao, M Silveira, J Stropp, H ter Steege, J Terborgh, R Thomas, M Toledo, A Torres-Lezama, G.M.F van der Heijden, R Vasquez, I Vieira, E Vilanova, V. A Vos and T. R Baker (2016). Variation in stem mortality rates determines patterns of aboveground biomass in Amazonian forests: implications for dynamic global vegetation models, Global Change Biology, 22, 3996-4013, doi:10.1111/gcb.13315.
36ET†Zhang, K., J.S. Kimball and S.W. Running (2016). A review of remote sensing based actual evapotranspiration estimation, Wiley Interdisciplinary Reviews: Water, 3, 834-853, doi: 10.1002/wat2.1168.
35Remote sensing and modeling†Zhang, K., J. Wang, I. Ahmed, and P.H. Gowda (2016). Advances in remote sensing and modeling of terrestrial hydrometeorological processes and extremes, Advances in Meteorology, 2016, 4371840, doi: 10.1155/2016/5173984.
34Hydrological modelBao, H., L. Wang, Z. Li, C. Yao, and K. Zhang (2016). Grid-based distributed hydrological model with mixed runoff model and two-dimensional kinematic wave flow model, Water Resources and Power, 34(11), 1-4+21
33Hydrological modelHuang, P., Z. Li, Q. Li, K. Zhang, and H. Zhang (2016). Application and comparison of coaxial correlation diagram and hydrological model for reconstructing flood series under human disturbance, Journal of Mountain Science, 13(7), 1245-1264.
32Hydraulic modelLiu, K., Z. Li, C. Yao, J. Chen, K. Zhang, and M. Saifullah (2016). Coupling the k-nearest neighbor procedure with the Kalman filter for real-time updating of the hydraulic model in flood forecasting, International Journal of Sediment Research, 31(2), 149-158.
31GDBCShen, X., H.J. Vergera, E.I. Nikolopoulos, E.N. Anagnostou, Y. Hong, Z. Hao, K. Zhang, and K. Mao (2016). GDBC: A tool for generating global-scale distributed basin morphometry, Environmental Modelling and Software, 83, 212-223.
30PrecipitationShi, P., T. Yang, K. Zhang, Q. Tang, Z. Yu, and X. Zhou (2016). Large-scale climate patterns and precipitation in an arid endorheic region: linkage and underlying mechanism, Environmental Research Letters, 11, 044006, doi:10.1088/1748-9326/11/4/044006.
29Hydrological Models:Xue, X., K. Zhang, Y. Hong, J.J. Gourley, W. Kellogg, R.A. McPherson, and Z. Wan (2016). New Multisite Cascading Calibration Approach for Hydrological Models: Case Study in the Red River Basin Using the VIC Model, Journal of Hydrologic Engineering, 21(2), 05015019, doi:10.1061/(ASCE)HE.1943-5584.0001282.
28AmazonLevine, N., K. Zhang, M. Longo, A. Baccini, O. Phillips, S.L. Lewis, E. Alvarez, A.C.S. de Andrade, R.J.W. Brienen, T. Erwin, T.R. Feldpausch, A. Mendo, P.N. Vargas, A. Prieto, J.E.S. Espejo, Y. Malhi, and P. Moorcroft (2016). Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change, PNAS, 113(3), 793-797, doi: 10.1073.pnas.1511344112.
27Amazon biomassCastanho, A., D. Galbraith, K. Zhang, M. Coe, M.H. Costa, and P. Moorcroft (2016). Changing Amazon biomass and the role of atmospheric CO2 concentration, climate and land use, Global Biogeochemical Cycles, 30(1), 18-39, doi:10.1002/2015GB005135.
26ET†Zhang, K., J.S. Kimball, R.R. Nemani, S.W. Running, Y. Hong, J.J. Gourley, and Z. Yu (2015). Vegetation Greening and Climate Change Promote Multidecadal Rises of Global Land Evapotranspiration, Scientific Reports, 5, 15956; doi: 10.1038/srep15956.
25ET#Wan, Z., #†K. Zhang, X. Xue, Z. Hong, †Y. Hong, and J.J. Gourley (2015). Water balance-based actual evapotranspiration reconstruction from ground and satellite observations over the conterminous United States, Water Resources Research, 51, 6485–6499, doi:10.1002/2015WR017311.
24Amazonian ecosystemsZhang, K., A. Castanho, D. Galbraith, S. Moghim, N. Levine, R. Bras, M. Coe, M.H. Costa, Y. Malhi, M. Longo, R.G. Knox, S. McKnight, J. Wang, and †P.R. Moorcroft (2015). The fate of Amazonian ecosystems over the coming century arising from changes in climate, atmospheric CO2 and land-use, Global Change Biology, 21, 2569-2587.
23Ecosystem-atmosphere modelR.G. Knox, M. Longo, A.L.S. Swann, K. Zhang, N.M. Levine, P.R. Moorcroft, and R.L. Bras (2015). Hydrometeorological effects of historical land-conversion in an ecosystem-atmosphere model of northern South America, Hydrology and Earth System Sciences, 19, 241-273.
22Xinanjiang modelYao, C., K. Zhang, Z. Yu, Z. Li and Q. Li (2014). Improving the flood prediction capability of the Xinanjiang model in ungauged nested catchments by coupling it with the geomorphologic instantaneous unit hydrograph, Journal of Hydrology, 517, 1035-1048.
21Non-frozen seasonsKim, Y., J.S. Kimball, K. Zhang, K. Didan, I. Velicogna, and K.C. McDonald (2013). Attribution of divergent northern vegetation growth responses to lengthening non-frozen seasons using satellite optical-NIR and microwave remote sensing, International Journal of Remote Sensing, 35(10), 3700-3721.
20Inferred climate modelSchwalm, C. R., D.N. Huntinzger, A.M. Michalak, J.B. Fisher, J.S. Kimball, B. Mueller, K. Zhang and Y. Zhang (2013). Sensitivity of inferred climate model skill to evaluation decisions: A case study using CMIP5 evapotranspiration, Environmental Research Letters, 8, 024028, doi:10.1088.
19Non-frozen seasonsKim, Y., J.S. Kimball, K. Zhang and K.C. McDonald (2012). Satellite detection of increasing Northern Hemisphere non-frozen seasons from 1979 to 2008: Implications for regional vegetation growth, Remote Sensing of Environment, 121, 472-487.
18Distributed grid-based XinanjiangYao, C., Z. Li, Z. Yu and K. Zhang (2012). A priori parameter estimates for a distributed, grid-based Xinanjiang model using geographically based information, Journal of Hydrology, 468-469, 47-62.
17Freeze-thaw†Zhang, K., J.S. Kimball, Y. Kim and K.C. McDonald (2011). Changing freeze-thaw seasons in northern high latitudes and associated influences on evapotranspiration, Hydrological Processes, 25, 4142-4151, doi:10.1002/hyp.8350.
16ETJung, M., M. Reichstein, P. Ciais, S. Seneviratne, J. Sheffield, M. Goulden, G. Bonan, A. Cescatti, J. Chen, R. de Jeu, H. Dolman, W. Eugster, D. Gerten, D. Gianelle, N. Gobron, J. Heinke, J. Kimball, B. Law, L. Montagnani, Q. Mu, B. Mueller, K. Oleson, D. Papale, A. Richardson, O. Roupsard, S. Running, E. Tomelleri, N. Viovy, U. Weber, C. Williams, E. Wood, S. Zaehle, and K. Zhang (2010). Recent decline in the global land evapotranspiration trend due to limited moisture supply, Nature, 467, 951-954.
15ET†Zhang, K., J.S. Kimball, R.R. Nemani and S.W. Running (2010). A continuous satellite-derived global record of land surface evapotranspiration from 1983-2006, Water Resources Research, W09522, 10.1029/2009WR008800.
14Arctic SystemRawlins, M.A., M. Steele, M.M. Holland, J.C. Adam, J.E. Cherry, J.A. Francis, P.Y. Groisman, L.D. Hinzman, T.G. Huntington, D. L. Kane, J.S. Kimball, R. Kwok, R.B. Lammers, C.M. Lee, D.P. Letternmaier, K.C. McDonald, E. Podest, J. W. Pundsack, B. Rudels, M.C Serreze, A. Shiklomanov, Q. Skagseth, T.J. Troy, C.J. Vorosmarty, M. Wensnahan, E.F. Wood, R. Woodgate, D. Yang, K. Zhang and T. Zhang (2010), Analysis of the Arctic System for freshwater cycle intensification: Observations and expectations, Journal of Climate, 23, 5717-5737.
13Land surface air temperatureJones, L.A., C.R. Ferguson, J.S. Kimball, K. Zhang (2010), S.T.K. Chan, K.C. McDonald, E.G. Njoku and E.F. Wood. Satellite microwave remote sensing of daily land surface air temperature minima and maxima from AMSR-E, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 3, 111-123.
12ET†Zhang, K., J.S. Kimball, Q. Mu, L.A. Jones, S.J. Goetz and S.W. Running (2009). Satellite based analysis of northern ET trends and associated changes in the regional water balance from 1983 to 2005, Journal of Hydrology, 379, 92-110.
11CO2 exchangeKimball, J.S., L.A. Jones, K. Zhang, F.A. Heinsch, K.C. McDonald and W.C. Oechel (2009). A satellite approach to estimate land-atmosphere CO2 exchange for boreal and Arctic biomes using MODIS and AMSR-E, IEEE Transactions on Geoscience and Remote Sensing, 47(2), 569-587.
10NPP†Zhang, K., J.S. Kimball, E.H. Hogg, M. Zhao, W.C. Oechel, J.J. Cassano and S.W. Running (2008). Satellite-based model detection of recent climate-driven changes in northern high latitude vegetation productivity, Journal of Geophysical Research-Biogeosciences, 113, G03033, doi:10.1029/2007JG000621.
9GIS-based hydrological modelsLi, Z. and K. Zhang (2008). Comparison of three GIS-based hydrological models, Journal of Hydrologic Engineering, 13(5), 364-370.
8NPP†Zhang, K., J.S. Kimball, K.C. McDonald, J.J. Cassano and S.W. Running (2007). Impacts of large-scale oscillations on pan-Arctic terrestrial net primary production, Geophysical Research Letters, 34, L21403, doi:10.1029/2007GL031605.
7Climate ChangeBunn, A.G., S.J. Goetz, J.S. Kimball and K. Zhang (2007). Northern high latitude ecosystems respond to recent climate change, EOS, Transactions, American Geophysical Union, 88 (34), 333-340.
6NPP†Zhang, K., J.S. Kimball, M. Zhao, W.C. Oechel, J. Cassano and S.W. Running (2007). Sensitivity of pan-Arctic terrestrial net primary productivity simulations to daily surface meteorology from NCEP-NCAR and ERA-40 reanalyses, Journal of Geophysical Research-Biogeosciences, 112, G01011, doi: 10.1029/2006JG000249.
5Distributed geological modelsLi, Z., K. Zhang and C. Yao (2006). Comparison of distributed geological models based on GIS technology and DEM, Journal of Hydraulic Engineering, Chinese Hydraulic Engineering Society, 37(8), 1022-1028.
4Isoline MappingLiu, J., Y. Zhao and K. Zhang (2006). MapX-based isoline mapping for hydrologic data, Advances in Science and Technology of Water Resources, 26(1), 70-72.
3GTOPMODELZhang, K., Z. Li and H. Bao (2005). Comparison between GTOPMODEL and TOPMODEL, Journal of Hohai University (Natural Sciences), 33(5), 509-512.
2WatershedZhang, K., Y. Guo, Z. Li and J. Liu (2005). DEM-based watershed information extracting method and its application, Water Power, 31(2), 18-21.
1Flood ForecastingZhang, K., and Z. Li (2003), Real-time Flood Forecasting and Flood Regulation System, Journal of Hohai University (Natural Science), 31(Supplement), 150-154.

IDKey WordsCitation
6Environmental Remote SensingZhang, K. and Yang Hong (2015), in Environmental Remote Sensing for Hydrologic Building and Societal Resilience, edited by Y. Hong, Y. Zhang, and S. Khan, Taylor & Francis Group, in press.
5Ecohydrological processes Zhang, K., and Z. Yu (2015), Ecohydrological processes in river ecosystems, in Advances in Ecohydrology, edited by X. Yu, Science Press, China Science Publishing & Media Ltd, pp.70-90.
4LandslideHong, Y., Xiaogang He, Amy Cerato, Ke Zhang, Zhen Hong, Zonghu Liao (2014), Predictability of a Physically-based Model for Rainfall-induced Shallow Landslides: Model Development and Case Studies, in Technologies for Landslide Investigations, edited by M. Scaioni, Springer Verlag Press, pp.165-178.
3Hydrological Modeling and ForecastingZhang, K. (2010). Ecohydrological modelling, in Modern Technologies in Hydrological Modeling and Forecasting, edited by Z. Li et al., Hohai University Press, Nanjing, China, pp. 306-320 (in Chinese).
2ETZhang, K., J.S. Kimball, L.A. Jones, Q. Mu, and S.W. Running (2009). Analysis of northern ET trends and associated regional water balance changes using satellite inputs and meteorology reanalysis from 1983 to 2005, Proceeding s of the 30th Canadian Symposium on Remote Sensing, Canadian Remote Sensing Society, 797-809.
1Hydrological modelsLi, Z., C. Yao and K. Zhang (2008). Grid-based hydrological models, in Application and Research of Hydrological Modelling, edited by Z. Li, pp. 148-207, Hohai University Press, Nanjing, China (in Chinese).

IDKey WordsCitation
36Flash FloodZhang, K., Y. Hong, J. J. Gourley, H.J. Vergara, X. Xue, N. Lu, and R. Wooten (2014). Build an Ensemble-based Remote-Sensing Driven Coupled Flash Flood and Landslide Warning System and Its Evaluation Across the United States. 2014 AGU Fall Meeting, San Francisco (Invited).
35AmazoniaP. Moorcroft, K. Zhang, A. Castanho, D. Galbraith, S. Moghim, N. Levine, R. Bras, M. Coe, M. Costa, Y. Malhi, M. Longo, R. Knox, S. McKnight, and J. Wang (2014). The Fate of Amazonian Ecosystems over the Coming Century Arising from Changes in Climate, Atmospheric CO2 and land-use. 2014 AGU Fall Meeting, San Francisco.
34Amazonia Castanho, A.D.A., D. Galbraith, K. Zhang, M. Coe, M. Costa, and P. Moorcroft (2014). The Influence of Atmospheric CO2 Concentration and Climate Variability on Amazon Tropical Forest. 2014 AGU Fall Meeting, San Francisco.
33AmazoniaMoghim, S., S. McKnight, K. Zhang, A. Ebtehaj, R. Knox, R. Bras, P. Moorcroft, and J. Wang (2014). A Space-Time Unified Data Set of General Circulation Model Outputs for Land Surface Modeling over Amazonia. 2014 AGU Fall Meeting, San Francisco.
32CREST v2.1X. Shen, Y. Hong, K. Zhang, Z. Hao, and D. Wang (2014). CREST v2.1 Refined by a Distributed Linear Reservoir Routing Scheme. 2014 AGU Fall Meeting, San Francisco.
31Freeze-thaw Kimball, J.S., Y. Kim, K. Zhang, K. Didan, I. Velicogna, and K. McDonald (2013). Satellite detection and attribution of divergent northern vegetation growth responses to lengthening non-frozen seasons. 2013 AGU Fall Meeting, San Francisco.
30Terrestrial Biosphere ModelZhang, K., et al. (2013). Using Airborne Microwave Remotely Sensed Root-Zone Soil Moisture and Flux Measurements to Improve Regional Predictions of Carbon Fluxes in a Terrestrial Biosphere Model. 2013 AGU Fall Meeting, San Francisco.
29Freeze-thaw Zhang, K., J.S. Kimball, Y. Kim and K.C. McDonald (2012). Influences of changing freeze-thaw seasons on evapotranspiration in northern high latitudes and associated uncertainty analysis. 2012 AGU Fall Meeting, San Francisco (Invited).
28Amazonia Zhang, K., A. Castanho, S. Moghim, et al. (2012). Exploring eco-hydrological consequences of the Amazonian ecosystems under climate and land-use changes in the 21st century. 2012 AGU Fall Meeting, San Francisco.
27Vegetation canopy Kim, Y., J.S. Kimball, K. Zhang and K.C. McDonald (2012). The effect of winter frozen season changes on Northern Hemisphere vegetation canopy growth determined from satellite microwave and optical remote sensing. 2012 AGU Fall Meeting, San Francisco.
26Amazonia Castanho, A.D.A., K. Zhang, M.T. Coe, M. Costa and P. Moorcroft (2012). The impact of CO2 fertilization effect associated with land use change on the total biomass in Amazonian tropical forest in the last decades. 2012 AGU Fall Meeting, San Francisco.
25ET Schwalm, C.R., D.N. Huntinzger, A.M. Michalak, J.B. Fisher, J.S. Kimball, B. Mueller, K. Zhang and Y. Zhang (2012). On the effects of evaluation decisions in model-data intercomparisons: An example using CMIP5 evapotranspiration. 2012 AGU Fall Meeting, San Francisco.
24Model parameter optimization.Zhang, K., A. Antonarakis and P. Moorcroft (2012). L4A NEE: model parameter optimization. AirMOSS Science Team Meeting, Pasadena, California.
23Amazonia Zhang, K., N.M. Levine, M. Longo and P.R. Moorcroft (2011). Recent and future impacts of climate and land-use changes on the Amazonian ecosystems inferred from an ecosystem model. 2011 AGU Fall Meeting, San Francisco.
22AmazoniaKnox, R.G., M. Longo, K. Zhang, N.M. Levine and P.R. Moorcroft (2011). Regional eco-hydrologic sensitivity to projected Amazonia land use scenarios. 2011 AGU Fall Meeting, San Francisco.
21NPP Kim, Y., J.S. Kimball, K. Zhang and K.C. McDonald. Satellite detection of Northern Hemisphere no-frozen season changes and associated impacts to vegetation growing seasons. 2011 AGU Fall Meeting, San Francisco.
20Climate changeMoorcroft, P.R., D. Medvigy, M.C. Dietz, N.M. Levine, Y. Kim and K. Zhang (2011). The significance of plant canopy demography for predicting terrestrial ecosystem responses to climate change. 2011 AGU Fall Meeting, San Francisco.
19GPP Zhang, K., J.S. Kimball and S. Goetz (2010). Diagnosis and attribution of recent changes in vegetation productivity and the regional water balance for the pan-Arctic basin and Alaska. 2010 NASA Terrestrial Ecology Science Team Meeting, La Jolla, California.
18ETQ. Mu, M. Zhao, K. Zhang and S.W. Running (2010). Applications of the newly improved global MOD16 evapotranspiration algorithm at Ameriflux tower site and global scale. 2010 NASA Terrestrial Ecology Science Team Meeting, La Jolla, California.
17ET Zhang, K. and J.S. Kimball (2009). Satellite-based global long-term terrestrial evapotranspiration estimates and trend analysis. Eos Trans. AGU, 90(52), Fall Meet. Suppl., Abstract H21A-0820.
16ETZhang, K., J.S. Kimball, L.A. Jones, Q. Mu and S.W. Running (2009). Analysis of northern ET trends and associated regional water balance changes using satellite inputs and meteorology reanalysis from 1983 to 2005. 30th Canadian Symposium on Remote Sensing, Lethbridge, Alberta, Canada.
15Carbon algorithmsJones, L.A., J.S. Kimball, K. Zhang and K.C. McDonald (2009). Developing future carbon algorithms for SMAP. 30th Canadian Symposium on Remote Sensing, Lethbridge, Alberta, Canada.
14ET Zhang, K., J.S. Kimball, Q. Mu and S.W. Running (2009). Satellite-derived global long-term terrestrial evapotranspiration estimates. 4th Global Vegetation Workshop, Missoula, Montana.
13Carbon algorithmsJones, L.A., J.S. Kimball, K. Zhang and K.C. McDonald (2009). Satellite based modeling of net CO2 exchange and uncertainty analysis using MODIS and AMSR-E: Developing future carbon algorithms for SMAP. 4th Global Vegetation Workshop, Missoula, Montana.
12Freeze-thawKim, Y., J.S. Kimball, K.C. McDonald, K. Zhang and J. Lucotch (2009). Terrestrial freeze-thaw monitoring in the Northern Hemisphere using satellite active and passive microwave remote sensing. 4th Global Vegetation Workshop, Missoula, Montana.
11ET11. Zhang, K., J.S. Kimball, E.H. Hogg, K.C. McDonald and W.C. Oechel (2009). Satellite based analysis of recent changes in ET and the terrestrial water balance over Canada and Alaska: Implications for vegetation productivity and the northern carbon cycle. 2nd NACP All-Investigators Meeting, San Diego, California.
10Freeze-thawMcDonald, K.C., J.S. Kimball, K. Zhang, Y. Kim, D. Ganem and E. Podest (2009). Monitoring of landscape freeze-thaw in the terrestrial high latitudes with satellite microwave remote sensing: Relationships with growing season and land-atmosphere CO2 exchange. 2nd NACP All-Investigators Meeting, San Diego, California.
9ET Zhang, K., J.S. Kimball, Q. Mu, L.A. Jones, S. J. Goetz and S.W. Running (2008). Satellite based analysis of northern ET trends and associated changes in regional water balance from 1983 to 2005. Eos Trans. AGU, 89(52), Fall Meet. Suppl., Abstract H43G-1096.
8AMSR-EJones, L.A., J.S. Kimball, K. Zhang, S.K. Chan, C. Ferguson and E.F. Wood (2008). Daily land surface air temperature and vapor pressure deficit derived from AMSR-E: Comparison with AIRS and Northern Hemisphere WMO stations. Eos Trans. AGU, 89(52), Fall Meet. Suppl., Abstract H41B-0865.
7NPPZhang, K., J.S. Kimball, K.C. McDonald, J.J. Cassano and S.W. Running (2008). Teleconnection between large-scale oscillations and northern high-latitude terrestrial net primary production. 2008 Carbon Cycle and Ecosystems Joint Science Workshop, Adelphi, Maryland.
6NPP Zhang, K., J.S. Kimball, K.C. McDonald, J.J. Cassano and S.W. Running (2007). Impacts of large-scale oscillations on northern high-latitude terrestrial net primary production. Eos Trans. AGU, 88(52), Fall Meet. Suppl., Abstract U31C-0501.
5Drought Kimball, J.S., K. Zhang, T. Hogg, K.C. McDonald and W.C. Oechel (2007). Satellite Detection of Recent Drought-Induced Decline in Vegetation Productivity for the Pan-Arctic Basin and Alaska. NASA SMAP Science Workshop, Arlington, Virginia.
4NPP Zhang, K., J.S. Kimball, T. Hogg, M. Zhao, W.C. Oechel and S.W. Running (2006). Remotely Sensed Variations of Pan-Arctic Terrestrial Vegetation Productivity from 1982-2005. Eos Trans. AGU, 87(52), Fall Meet. Suppl., Abstract U33A-0007.
3NPP Zhang, K., J.S. Kimball, T. Hogg, M. Zhao, W.C. Oechel and S.W. Running (2006). Satellite observations of pan-Arctic terrestrial net primary productivity from 1982-2005. Joint Workshop on NASA Biodiversity, Terrestrial Ecology, and Related Applied Sciences, Adelphi, Maryland.
2NPP Zhang, K., J.S. Kimball, M. Zhao, W.C. Oechel and S.W. Running (2006). Analysis of Pan-Arctic Terrestrial Net Primary Productivity from 1982-2005 by Combining AVHRR and MODIS Products. Global Vegetation Workshop 2006, Missoula, Montana.
1ArcticKimball, J.S. and K. Zhang (2006). Multi-scale Assessment of Arctic Terrestrial-Atmosphere Carbon and Water Cycle Interactions. NSF ARCSS Workshop, Seattle, Washington.

IDKeywordsCitation
15Hydroclimatic ZonesKe Zhang and Xinzheng Tang (2017). Recent Multi-decadal Changes of Hydroclimatic Zones in China Inferred from Ground and Satellite Observations. The 2nd International Top-Level Forum on Engineering Science and Technology Development Strategy, October 18-20, 2017, Nanjing, Jiangsu, China.
14Soil moisture张珂 (2017).基于多源卫星的中国地表土壤湿度遥感反演研究 . 第34届中国气象学会年会S7分会，郑州。
13ET张珂 (2016). 基于卫星遥感和地面观测的全球陆地蒸散发和水量平衡变化趋势研究. 第33届中国气象学会年会S9分会，西安。
12Free-thaw张珂 (2016). 基于卫星观测的高纬度地区冻融过程与水循环变化关联分析. 清华大学首届“全球遥感水文与水利大数据论坛”，清华大学，北京。
11Flash flood and LandslideZhang, K., Y. Hong, J. J. Gourley, H.J. Vergara, X. Xue, N. Lu, and R. Wooten (2014). Build an Ensemble-based Remote-Sensing Driven Coupled Flash Flood and Landslide Warning System and Its Evaluation Across the United States. 2014 AGU Fall Meeting, San Francisco (Invited).
10Eco-hydrological consequencesZhang, K. (2013). The fate of Amazonian ecosystems and eco-hydrological consequences under climate and land-use changes. Atmospheric Sciences Research Center Seminar, SUNY, Albany, New York.
9Free-thawZhang, K., J.S. Kimball, Y. Kim and K.C. McDonald (2012). Influences of changing freeze-thaw seasons on evapotranspiration in northern high latitudes and associated uncertainty analysis. 2012 AGU Fall Meeting, San Francisco.
8Amazonian ecosystemsZhang, K. (2012). Exploring eco-hydrological consequences of Amazonian ecosystems under climate and land-use changes. Department of Civil & Environmental Engineering & Earth Sciences, University of Notre Dame, Notre Dame, Indiana.
7ETZhang, K. (2011). Development of a satellite-derived global land evapotranspiration record and analysis of changes in the global water cycle from 1983 to 2006. NOAA CREST Seminar, The City College of New York, New York City, New York.
6Hydrological processesZhang, K. (2010). Integrating satellite remote sensing and modeling to study ecological and hydrological processes. Moorcroft Laboratory, Harvard University, Cambridge, Massachusetts.
5ETZhang, K. (2009). Satellite based analysis of recent changes in ET and the terrestrial water balance over the pan-Arctic region. Organismal Biology and Ecology Seminar, Division of Biological Sciences, The University of Montana, Missoula, Montana.
4NPPZhang, K. (2008). Impacts of large-scale atmospheric oscillations on pan-arctic terrestrial net primary production. Organismal Biology and Ecology Seminar, Division of Biological Sciences, The University of Montana, Missoula, Montana.
3NPP Zhang, K. and J.S. Kimball (2007). Summer drought induced NPP decline for the Alaska North Slope. SNACS Team Meeting, San Francisco, California.
2NPPZhang, K. (2007). Satellite detection of a recent decline in northern high latitude terrestrial vegetation productivity with regional warming and drying. Organismal Biology and Ecology Seminar, Division of Biological Sciences, The University of Montana, Missoula, Montana.
1Arctic Kimball, J.S. and K. Zhang (2006). Multi-scale assessment of Arctic terrestrial-atmosphere carbon and water cycle interactions. NSF ARCSS Workshop, Seattle, Washington.