3359 Mississauga Road
Mississauga ON L5L 1C6
Water Resources, Remote sensing, Data Assimilation, Climate Change
Changes in the spatial and temporal characteristics of hydrological conditions (precipitation, surface water, soil moisture, groundwater, snow/ice, etc.) play a significant role in driving the impacts of climate change on human settlements and infrastructure. In particular, extreme hydro-climatological events (e.g. flood and drought) could cause severely adverse socio-economic impacts. Our research aims to make high quality scientific contributions towards a better understanding of spatiotemporal changes in hydro-climatological conditions and interactions of atmospheric, terrestrial and hydrological processes. The research themes mainly involve integration of remotely sensed hydrologic products with hydrological/hydrogeological modeling, ensemble methods for quantifying the uncertainties pertaining to water resources modeling and prediction, and development of theoretical framework and modeling system that integrate different processes and disciplines across the earth’s climate system for quantifying the water cycle-climate-human interactions. The outcomes will improve our skill to monitor and forecast water resources variability and extreme hydro-climatological events, in support of water resources management and water security.
Zhu, Y., S. W. Myint, D. Schaffer-Smith, D. J. Sauchyn, X. Xu, J. M. Piwowar, and Y. Li (2022), Examining ground and surface water changes in response to environmental variables, land use dynamics, and social economic changes in Canada, Journal of Environmental Management, 322, 115875, doi:10.1016/j.jenvman.2022.115875.
Xu, X., Frey, S.K., and Ma, D. (2022). Hydrological performance of ERA5 and MERRA-2 precipitation products over the Great Lakes basin, Journal of Hydrology: Regional Studies, 39, 100982. Doi: 10.1016/j.ejrh.2021.100982.
De Benedetti, M., G.W.K. Moore, and X. Xu. (2022). Representation of spatial variability of the water fluxes over the Congo Basin region, Sensors, 22, 84. doi:10.3390/s22010088.
Xu, X., and Frey, S.K. (2021). Validation of SMOS, SMAP, and ESA CCI soil moisture over a humid region, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 10786-10793, doi: 10.1109/JSTARS.2021.3122068.
Frey, S.K., K. Miller, O. Khader, A. Taylor, D. Morrison, X. Xu, S.J. Berg, H.T. Hwang, E.A. Sudicky, D.R. Lapen (2021), Evaluating landscape influences on hydrologic behavior with a fully-integrated groundwater-surface water model. Journal of Hydrology, 602, 126758.
Moore, G. W. K., Howell, S. E. L., Brady, M., Xu, X., & McNeil, K. (2021). Anomalous collapses of Nares Strait ice arches leads to enhanced export of Arctic sea ice. Nature Communications, 12(1), 1-8.
Moore, K., Howell, S., Brady, M., McNeil, K., & Xu, X. (2020). Recent behavior of the Nares Strait ice arches: anomalous collapses and enhanced transport of multi-year ice from the Arctic Ocean. In Ocean Sciences Meeting 2020. Agu.
Xu, X., Shew, B., Zaman, S., Lee, J. & Zhi, Y. (2020). Assessment of SMAP and ESA CCI Soil Moisture Over the Great Lakes Basin. IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA, 2020, pp. 4590-4593, doi: 10.1109/IGARSS39084.2020.9323638.
Xu, X. (2020). Evaluation of SMAP Level 2, 3, and 4 Soil Moisture Datasets over the Great Lakes Region. Remote Sensing, 12(22), 3785.
Xu, X., Frey, S. K., Boluwade, A., Erler, A. R., Khader, O., Lapen, D. R., & Sudicky, E. (2019). Evaluation of variability among different precipitation products in the Northern Great Plains. Journal of Hydrology: Regional Studies, 24, 100608.
Gaborit, É., Fortin, V., Xu, X., Seglenieks, F., Tolson, B., Fry, L. M., ... & Gronewold, A. D. (2017). A hydrological prediction system based on the SVS land-surface scheme: efficient calibration of GEM-Hydro for streamflow simulation over the Lake Ontario basin. Hydrology and Earth System Sciences, 21(9), 4825-4839.
Xu, X., B. A. Tolson, J. Li, and B. Davison (2017), Comparison of X-band and L-band soil moisture retrievals for land data assimilation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(9), 3850-3860, doi: 10.1109/JSTARS.2017.2703988.
Xu, X., B. A. Tolson, J. Li, and B. Davison (2017), Assimilation of synthetic remotely-sensed soil moisture in Environment Canada's MESH model. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(4), 1317-1327, doi: 10.1109/JSTARS.2016.2626256.