Jump to navigation
MIT Center for Global Change Science affiliates include: the MIT School of Science; MIT School of Engineering; Earth, Atmospheric & Planetary Sciences (EAPS); Civil & Evironmental Engineering (CEE);Electrical Engineering & Computer Science (EECS); Engineering Systems Division (ESD), and Biology.
Events CalendarKendall Memorial Lecture
My enduring research interest is to design methods to describe the behaviour of Stochastic Fields and Processes better. I broadly study Estimation, Control...
Research Interests: Estimation and control, data assimilation; Surface and groundwater hydrology; Water resources systems
D McLaughlin, W Kinzelbach, 2015: Food security and sustainable resource management, Water Resources Research 51 (7), 4966-4985
N Li, D McLaughlin, W Kinzelbach, WP Li, XG Dong, Using an ensemble smoother to evaluate parameter uncertainty of an integrated hydrological model of Yanqi basin, 2015: Journal of Hydrology 529, 146-158
B Lin, D McLaughlin, 2014: Efficient characterization of uncertain model parameters with a reduced-order ensemble Kalman filter, SIAM Journal on Scientific Computing 36 (2), B198-B224
Ng, G.-H. C., D. McLaughlin, D. Entekhabi and A. Ahanin, 2011: The role of model dynamics in ensemble Kalman filter performance for chaotic systems, Tellus A, 63(5): 958-77McLaughlin, D. and E.F. Wood, 1988: A distributed parameter approach for evaluating the accuracy of groundwater model predictions: 1. Theory, Water Resources Research, 24(7): 1037-47McLaughlin, D. and W. Johnson, 1987: Comparison of Three Groundwater Modeling Studies, ASCE Journal of Water Resources Planning and Management, 113(3): 405-21Moughamian, M., D. McLaughlin, and R.L. Bras, 1987: Estimation of flood frequency: An evaluation of two derived distribution procedures, Water Resources Research, 23(7): 1309-19
B.S.E.E. 1966, Purdue UniversityM.S.E. 1967, Princeton UniversityPh.D. 1985, Princeton University