Articles from the center, those using its research, and faculty associated with the center.
Dunn, F. E., S. E. Darby, R. J. Nicholls, S. Cohen, C. Zarfl, B.M. Fekete, (2019). Projections of declining fluvial sediment delivery to major deltas worldwide in response to climate change and anthropogenic stress. Environmental Research Letters, 14 (8), 084034. https://doi.org/10.1088/1748-9326/ab304e
Syvitski, J.P., S. Cohen, A. Miara, J. Best, (2019). River temperature and the thermal-dynamic transport of sediment. Global and Planetary Change, 178,168-183. c
B. Seyednasrollah* and M. Kumar, How Surface Radiation on Forested Snowpack Changes across a Latitudinal Gradient, Hydrology, 2019
Magliocca, N.R., Khuc, Q.V., de Bremond, A., Ellicott, E. (2019). Archetypical pathways of direct and indirect land-use change caused by Cambodia’s large-scale land acquisitions. Ecology & Society, 24(2): 25. [online] URL: https://www.ecologyandsociety.org/vol24/iss2/art25/.
C. Krapu*, M. Borsuk, and M. Kumar, Gradient‐Based Inverse Estimation for a Rainfall‐ Runoff Model, Water Resources Research, 2019
Chen, Z., Yu, B., Zhou, Y., Liu, H., Yang, C., Shi, K., & Wu, J. (2019). Mapping global urban areas from 2000 to 2012 using time-series nighttime light data and MODIS products. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(4), 1143-1153.
Sun, H., Zhou, B., & Liu, H. (2019). Spatial Evaluation of Soil Moisture (SM), Land Surface Temperature (LST), and LST-Derived SM Indexes Dynamics during SMAPVEX12. Sensors, 19(5), 1247.
Beck, R., Xu, M., Zhan, S., Johansen, R., Liu, H., Tong, S., … & Berling, K. (2019). Comparison of satellite reflectance algorithms for estimating turbidity and cyanobacterial concentrations in productive freshwaters using hyperspectral aircraft imagery and dense coincident surface observations. Journal of Great Lakes Research, 45(3), 413-433.
Oubeidillah, A., G. Tootle and T. Piechota, 2019. Incorporating Antecedent Soil Moisture into Streamflow Forecasting. Hydrology, 6(2), 50; https://doi.org/10.3390/hydrology6020050.
Moftakhari, H. R., Schubert, J., AghaKouchak, A., Matthew, R. A., & Sanders, B. F. (2019). Linking Statistical and Hydrodynamic Modeling for Compound Flood Hazard Assessment in Tidal Channels and Estuaries. Advances in Water Resources 128, 28-38, https://doi.org/10.1016/j.advwatres.2019.04.009.
Sun, H., Cai, C., Liu, H., & Yang, B. (2019). Microwave and Meteorological Fusion: A method of Spatial Downscaling of Remotely Sensed Soil Moisture. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(4), 1107-1119.
Magliocca, N.R., McSweeney, K. Sesnie, S.E., Tellman, E., Devine, J.A., Nielsen, E.A., Pearson, Z. Wrathall, D.J., Dávila, A. (2019). Modeling cocaine traffickers and counterdrug interdiction forces as a complex adaptive system. Proceedings of the National Academy of Sciences USA, 116 (16): 7784-7792. DOI: https://doi.org/10.1073/pnas.1812459116.
Wu, Q., Lane, C. R., Wang, L., Vanderhoof, M. K., Christensen, J. R., & Liu, H. (2019). Efficient delineation of nested depression hierarchy in digital elevation models for hydrological analysis using level‐set method. JAWRA Journal of the American Water Resources Association, 55(2), 354-368.
Schelf K.E., H. Moradkhani, and U. Lall (2019), Atmospheric Circulation Patterns Associated with extreme United States Floods Identified via Machine Learning, Scientific Reports, doi:10.1038/s41598-019-43496-w.
Anderson, S., R. Ogle, G. Tootle and A. Oubeidillah, 2019. Tree-Ring Reconstructions of Streamflow for the Tennessee Valley. Hydrology, 6(2), 34; https://doi.org/10.3390/hydrology6020034.
