Dr. Xudong Zhou is now a Research Professor in the Institute of Hydraulics and Ocean Engineering in Ningbo University, China. His research interest is Monitoring, Modelling and Modulating River Flow Dynamics. Dr. Zhou is a strong advocate of open science and collaborative research. He founded the Hydro90 Research platform, with more than 45,000 followers (as of Aug, 2024).
[Aug. 2024] 2024年8月17-18日,CYWater夏季会议将在西安举行,欢迎报名参加。
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(48) Guo, Q., Mistry, M. N., Zhou, X., Zhao, G., Kino, K., Wen, B., Yoshimura, K., Satoh, Y., Cvijanovic, I., Kim, Y., Ng, C. F. S., Vicedo-Cabrera, A. M., Armstrong, B., Urban, A., Katsouyanni, K., Masselot, P., Tong, S., Sera, F., Huber, V., … Oki, T. (2024). Regional variation in the role of humidity on city-level heat-related mortality. PNAS Nexus. https://doi.org/10.1093/pnasnexus/pgae290
(47) Wu, S., Zhou, X., Reyns, J., Yamazaki, D., Yin, J., & Li, X. (2024). Climate change and urban sprawl: Unveiling the escalating flood risks in river deltas with a deep dive into the GBM river delta. Science of The Total Environment, 947, 174703. https://doi.org/10.1016/j.scitotenv.2024.174703
(46) Xie, X., Lin, K., Xiao, M., Zhou, X., Zhao, G., & Yamazaki, D. (2024). How Does Heavy Precipitation of Varying Durations Respond to Urbanization in China? Earth’s Future, 12(7). https://doi.org/10.1029/2023EF004412
(45) Zhao, Q., Cui, S., Zhu, Y., Li, R., & Zhou, X. (2024). A Novel Online Hydrological Data Quality Control Approach Based on Adaptive Differential Evolution. Mathematics, 12(12), 1821. https://doi.org/10.3390/math12121821
(44) Hu, Y., Zhou, X., Yamazaki, D., & Chen, J. (2024). A self-adjusting method to generate daily consistent nighttime light data for the detection of short-term rapid human activities. Remote Sensing of Environment, 304, 114077. https://doi.org/10.1016/j.rse.2024.114077
(43) Lin, J., Wang, P., Wang, J., Zhou, Y., Zhou, X., Yang, P., Zhang, H., Cai, Y., & Yang, Z. (2024). An extensive spatiotemporal water quality dataset covering four decades (1980–2022) in China. Earth System Science Data, 16(2), 1137–1149. https://doi.org/10.5194/essd-16-1137-2024
(42) Li, S., Yamazaki, D., Zhou, X., & Zhao, G. (2024). Where in the World Are Vegetation Patterns Controlled by Hillslope Water Dynamics? Water Resources Research, 60(4). https://doi.org/10.1029/2023WR036214
(41) Revel, M., Zhou, X., Modi, P., Cretaux, J. F., Calmant, S., & Yamazaki, D. (2024). AltiMaP: altimetry mapping procedure for hydrography data. Earth System Science Data, 16(1), 75-88. https://doi.org/10.5194/essd-16-75-2024
(40) Ding, M., Lin, P., Gao, S., Wang, J., Zeng, Z., Zheng, K., Zhou, X., Yamazaki, D., Gao, Y., & Liu, Y. (2023). Reversal of the levee effect towards sustainable floodplain management. Nature Sustainability. https://doi.org/10.1038/s41893-023-01202-9
(39) Polcher, J., Schrapffer, A., Dupont, E., Rinchiuso, L., Zhou, X., Boucher, O., Mouche, E., Ottlé, C., & Servonnat, J. (2023). Hydrological modelling on atmospheric grids: using graphs of sub-grid elements to transport energy and water. Geoscientific Model Development, 16(9), 2583–2606. https://doi.org/10.5194/gmd-16-2583-2023
(38) Kimura, Y., Hirabayashi, Y., Kita, Y., Zhou, X., & Yamazaki, D. (2023). Methodology for constructing a flood-hazard map for a future climate. Hydrology and Earth System Sciences, 27, 1627–1644. https://doi.org/10.5194/egusphere-2022-1343
(37) Lin, J., Bryan, B. A., Zhou, X., Lin, P., Do, H. X., Gao, L., Gu, X., Liu, Z., Wan, L., Tong, S., Huang, J., Wang, Q., Zhang, Y., Gao, H., Yin, J., Chen, Z., Duan, W., Xie, Z., Cui, T., … Yang, Z. (2023). Making China’s water data accessible , usable and shareable. Nature Water, 1, 1–8. https://doi.org/10.1038/s44221-023-00039-y
(36) Revel, M., Zhou, X., Yamazaki, D., & Kanae, S. (2023). Assimilation of Transformed Water Surface Elevation to Improve River Discharge Estimation in a Continental-Scale River. Hydrology and Earth System Sciences, 27, 647–671. https://doi.org/10.5194/hess-27-647-2023
(35) Shi, P., Yang, T., Yong, B., Xu, C.-Y., Li, Z., Wang, X., Qin, Y. & Zhou, X. (2023). Some statistical inferences of parameter in MCMC approach and the application in uncertainty analysis of hydrological simulation. Journal of Hydrology. 617(Part A), 128767. https://doi.org/10.1016/j.jhydrol.2022.128767
(34#) Liang, H., & Zhou, X. (2022). Impact of Tides and Surges on Fluvial Floods in Coastal Regions. Remote Sensing, 14, 5779. https://doi.org/10.3390/rs14225779
(33#) Zhou, X., Revel, M., Modi, P., Shiozawa, T., & Yamazaki, D. (2022). Correction of river bathymetry parameters using the stage-discharge rating curve. Water Resources Research, 58, e2021WR031226.
https://doi.org/10.1029/2021WR031226
[This paper describes a rubost and reliable method to correct river bathymetry (river depth) using remote sensed water altimetry data and in-situ river discharge measurement. Correction using rating-curve method can eliminate impact of errors in forcing inputs and attribute all errors/biases to model correction.]
(32) Pellet, V., Aires, F., Yamazaki, D., Zhou, X., & Paris, A. (2022). A first continuous and distributed satellite-based mapping of river discharge over the Amazon. Journal of Hydrology. 614 (Part A), 128481. https://doi.org/10.1016/j.jhydrol.2022.128481
(301) Guo, Q., Zhou, X., Satoh, Y., & Oki, T. (2022). Irrigated cropland expansion exacerbates the urban moist heat stress in northern India. Environmental Research Letters, 17(5). https://doi.org/10.1088/1748-9326/ac64b6
(30#) Zhou, X., Prigent, C., & Yamazaki, D. (2021). Toward Improved Comparisons Between Land‐Surface‐Water‐Area Estimates From a Global River Model and Satellite Observations. Water Resources Research, 57(5), e2020WR029256. https://doi.org/10.1029/2020WR029256
(29#) Zhou, X., Polcher, J., & Dumas, P. (2021). Representing human water management in a land surface model using a supply/demand approach. Water Resources Research, 57, e2020WR028133. https://doi.org/10.1029/2020WR028133
(28#) Zhou, X., Ma, W., Echizenya, W., & Yamazaki, D. (2021). The uncertainty of flood frequency analyses in hydrodynamic model simulations. Natural Hazards and Earth System Sciences, 21, 1071–1085. https://doi.org/10.5194/nhess-21-1071-2021
(27) Zheng, X., Yang, T., Cui, T., Xu, C., Zhou, X., Li, Z., ... & Qin, Y. (2021). A revised range of variability approach considering the morphological alteration of hydrological indicators. Stochastic Environmental Research and Risk Assessment, 35(9), 1783-1803. https://doi.org/10.1007/s00477-020-01926-6
(26) Kitajima, N., Seto, R., Yamazaki, D., Zhou, X., Ma, W., & Kanae S. (2021). Potential of a SAR Small-Satellite Constellation for Rapid Monitoring of Flood Extent. Remote Sensing, 13(10), 1959. https://doi.org/10.3390/rs13101959
(25) Huang, Y., Tokuda, D., Zhou, X., & Oki, T. (2021). Global integrated modeling framework of riverine dissolved inorganic nitrogen with seasonal variation. Hydrological Research Letters, 15(3), 50-57. https://doi.org/10.3178/hrl.15.50
(24) Hirabayashi, Y., Tanoue, M., Sasaki, O., Zhou, X., & Yamazaki, D. (2021). Global exposure to flooding from the new CMIP6 climate model projections. Scientific Reports, 11(0123456789), 3740–3746. https://doi.org/10.1038/s41598-021-83279-w [News]
(23) Yin, Z., Ottlé, C., Ciais, P., Zhou, F., Wang, X., Jan, P., Dumas, P., Peng, S., Li, L., Zhou, X., & Piao, S. (2021). Irrigation, damming, and streamflow fluctuations of the Yellow River. Hydrology and Earth System Sciences, 25(April), 1133–1150. https://doi.org/10.5194/hess-25-1133-2021
(22#) Zhou, X., Wang, Q., & Yang, T. (2020). Decreases in days with sudden day-to-day temperature change in the warming world. Global and Planetary Change, 192(May), 103239. https://doi.org/10.1016/j.gloplacha.2020.103239
(21#) Zhou X., Polcher, J., Yang, T., & Huang, C.-S. (2020). A new uncertainty estimation approach with multiple datasets and implementation for various precipitation products. Hydrology and Earth System Sciences, 24, 2061–2081. https://doi.org/10.5194/hess-24-2061-2020
(20) Kitajima, N., Seto, R., Yamazaki, D., Zhou, X., Ma, W., & Kanae, S. (2020). Possibility of High-frequency Observation of Inundation Area by Small SAR Satellites Constellation. Journal of Japan Society of Civil Engineers Ser B1 (Hydraulic Engineering), 76(2), 535–540. https://doi.org/10.1007/s00477-020-01926-6
(19) Zhao, Q., Zhu, Y., Shu, K., Wan, D., Yu, Y., Zhou, X., & Liu, H. (2020). Joint spatial and temporal modeling for hydrological prediction. IEEE Access, 8, 78492–78503. https://doi.org/10.1109/ACCESS.2020.2990181
(18) Yin, Z., Wang, X. H., Otté, C., Zhou, F., Guimberteau, M., Polcher, J., Peng, S. S., Piao, S. L., Li, L., Bo, Y., Chen, X. L., Zhou, X. D., Kim, H., & Ciais, P. (2020). Improvement of the irrigation scheme in the ORCHIDEE land surface model and impacts of irrigation on regional water budgets over China. Journal of Advances in Modeling Earth Systems, 12, e2019MS001770.https://doi.org/10.1029/2019ms001770
(17) Gao, Y., Zhou, F., Ciais, P., Miao, C., Yang, T., Jia, Y., Zhou, X., Klaus, B., Yang, T. Yu, G.(2020). Human activities aggravate nitrogen deposition pollution to inland water over china. National Science Review, 7(2), 430–440. https://doi.org/10.1093/nsr/nwz073
(16) Shi, P., Yang, T., Yong, B., Li, Z., Xu, C. Y., Shao, Q., Wang, X., Zhou, X., Qin, Y. (2019). A new uncertainty measure for assessing the uncertainty existing in hydrological simulation. Water (Switzerland), 11(4). https://doi.org/10.3390/w11040812
(15) Shi, P., Yang, T., Xu, C.-Y., Yong, B., Huang, C.-S., Li, Z., Qin, Y., Wang, X., Zhou, X.,Li, S. (2019). Rainfall–Runoff Processes and Modelling in Regions Characterized by Deficiency in Soil Water Storage. Water, 11(9), 1858. https://doi.org/10.3390/w11091858
(14#) Zhou, X., Polcher, J., Yang, T., Hirabayashi, Y., & Nguyen-Quang, T. (2018). Understanding the water cycle over the upper Tarim Basin: retrospecting the estimated discharge bias to atmospheric variables and model structure. Hydrology and Earth System Sciences, 22, 6087–6108. https://doi.org/10.5194/hess-22-6087-2018
(13) Ren, W., Yang, T., Shi, P., Xu, C. yu, Zhang, K., Zhou, X., Shao, Q., & Ciais, P. (2018). A probabilistic method for streamflow projection and associated uncertainty analysis in a data sparse alpine region. Global and Planetary Change, 165, 100–113. https://doi.org/10.1016/j.gloplacha.2018.03.011
(12) Nguyen-Quang, T., Polcher, J., Ducharne, A., Arsouze, T., Zhou, X., Schneider, A., & Fita, L. (2018). ORCHIDEE-ROUTING: revising the river routing scheme using a high-resolution hydrological database. Geoscientific Model Development, 11, 4965–4985. https://doi.org/10.5194/gmd-11-4965-2018
(11) Wang, X., Yang, T., Yong, B., Krysanova, V., Shi, P., Li, Z., & Zhou, X. (2018). Impacts of climate change on flow regime and sequential threats to riverine ecosystem in the source region of the Yellow River. Environmental Earth Sciences, 77(485). https://doi.org/10.1007/s12665-018-7628-7
(10#) Zhou, X., Yang, T., Shi, P., Yu, Z., Wang, X., & Li, Z. (2017). Prospective scenarios of the saltwater intrusion in an estuary under climate change context using Bayesian neural networks. Stochastic Environmental Research and Risk Assessment, 31(4), 981–991. https://doi.org/10.1007/s00477-017-1399-7
(9) Wang, X., Yang, T., Li, X., Shi, P., & Zhou, X. (2017). Spatio-temporal changes of precipitation and temperature over the Pearl River basin based on CMIP5 multi-model ensemble. Stochastic Environmental Research and Risk Assessment, 31(5), 1077–1089. https://doi.org/10.1007/s00477-016-1286-7
(8) Shi, P., Yang, T., Xu, C. Y., Yong, B., Shao, Q., Li, Z., Wang, X., Zhou, X., Li, S. (2017). How do the multiple large-scale climate oscillations trigger extreme precipitation? Global and Planetary Change, 157(September), 48–58. https://doi.org/10.1016/j.gloplacha.2017.08.014
(7) Zhang, H. W., Sun, Y. Q., Li, Y., Zhou, X. D., Tang, X. Z., Yi, P., … Mugwaneza, V. P. (2017). Quality assessment of groundwater from the south-eastern Arabian Peninsula. Environmental Monitoring and Assessment, 189(411). https://doi.org/10.1007/s10661-017-6092-2
(6) Yang, T., Shi, P., Yu, Z., Li, Z., Wang, X., & Zhou, X. (2016). Probabilistic modeling and uncertainty estimation of urban water consumption under an incompletely informational circumstance. Stochastic Environmental Research and Risk Assessment, 30(2), 725–736. https://doi.org/10.1007/s00477-015-1081-x
(5) Shi, P., Yang, T., Zhang, K., Tang, Q., Yu, Z., & Zhou, X. (2016). Large-scale climate patterns and precipitation in an arid endorheic region: Linkage and underlying mechanism. Environmental Research Letters, 11(4). https://doi.org/10.1088/1748-9326/11/4/044006/
(4) Zheng, M. J., Murad, A., Zhou, X. D., Yi, P., Alshamsi, D., Hussein, S., … Yu, Z. B. (2016). Distribution and sources of 226Ra in groundwater of arid region. Journal of Radioanalytical and Nuclear Chemistry, 309(2), 667–675. https://doi.org/10.1007/s10967-015-4632-1
(3) Zheng, M., Wan, C., Du, M., Zhou, X., Yi, P., Aldahan, A., … Gong, M. (2016). Application of Rn-222 isotope for the interaction between surface water and groundwater in the Source Area of the Yellow River. Hydrology Research, 47(6), 1253–1262. https://doi.org/10.2166/nh.2016.070
(2) Yang, T., Zhou, X., Yu, Z., Krysanova, V., & Wang, B. (2015). Drought projection based on a hybrid drought index using Artificial Neural Networks. Hydrological Processes, 29(11), 2635–2648. https://doi.org/10.1002/hyp.10394
(1) Murad, A., Zhou, X. D., Yi, P., Alshamsi, D., Aldahan, A., Hou, X. L., & Yu, Z. B. (2014). Natural radioactivity in groundwater from the south-eastern Arabian Peninsula and environmental implications. Environmental Monitoring and Assessment, 186(10), 6157–6167. https://doi.org/10.1007/s10661-014-3846-y
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