Sergio E. Serrano, Ph.D.Sergio E. Serrano, Ph.D.
ENGINEERING UNCERTAINTY AND RISK ANALYSISPublished by HydroScience Inc. , Lexington, Kentucky, 2001. ISBN: 0-9655643-8-X, softcover, 472 pages, 151 solved examples, 50 short computer programs in Maple, 136 figures, 51 data and statistical tables, 152 proposed problems, 145 answers to problems, index, references. For textbook examination copies, please contact the publisher FREE OVERHEAD TRANSPARENCIES AVAILABLE TO FACULTY.
A book that combines water quantity with water quality:
Published by HydroScience Inc. , Lexington, Kentucky, 1997. ISBN: 0-9655643-9-8, Hardcover, 470 pages, includes an educational version of the KYSPILL groundwater pollution software, over 70 solved examples, over 150 illustrations, index, references. For textbooks examination copies, please contact the publisher. FREE OVERHEAD TRANSPARENCIES AVAILABLE TO FACULTY.
EDUCATION
HONORS AND AWARDS
AREA OF SPECIALIZATION
SELECTED PUBLICATIONS IN REFEREED JOURNALS
35. Serrano, S.E., and Workman, S.R., 1998. Analytical Solution of the Non-Linear Transient Groundwater Flow Equation Subject to Time Variable River Boundaries. Journal of Hydrology, 206:245-255.
23. Serrano, S.E., 1995(1)*. Analytical Solutions of the Non-Linear Groundwater Flow Equation in Unconfined Aquifers and the Effect of Heterogeneity. Water Resources Research, American Geophysical Union, 31(11):2733-2742
COURSES
CE461G Hydrology (Spring and Fall, every year)
The fundamentals of physical and contaminant hydrology of small watersheds. Hydrologic systems, precipitation, frequency analysis, evaporation and transpiration, infiltration and recharge, groundwater flow, surface runoff and streamflow, hydrograph analysis, the hydrology of extreme events, design of urban storm sewers, flood frequency analysis, hydrologic aspects of water quality, the hydrology of river contamination, the hydrology of lake contamination, soil and groundwater pollution. This course includes 3 hours per week of lecture and a computer laboratory using the KYSPILL groundwater pollution software, which was written by Dr. Serrano. The laboratory illustrates in graphical form the propagation of contaminants in soils and aquifers, the effects of recharge, reactive contaminants, non-point sources, and contaminant biodegradation. In response to the need for an undergraduate course that integrates surface, subsurface and contaminant hydrology, Dr. Serrano published the textbook Hydrology for Engineers, Geologists, and Environmental Professionals (listed in the books section). The course, the textbook, and the software gives the necessary analytical skills and prepares the student to solve today's water resources and environmental problems.
CE660 Groundwater Hydrology (Fall, every year)
The laws and models that govern the flow of water and the transport of contaminants in subsurface environments. Physical and mathematical preliminaries. Review of linear systems theory, vector calculus, and the divergence theorem. The equations of saturated groundwater flow, the formulation of boundary value problems, and some analytical methods of solution. Derivation of the partial differential equations using the divergence theorem, solutions using Fourier series, solutions involving the Fourier transform and the Fourier sine and cosine transforms, examples of applications to the calculation of infiltration and groundwater potential. The equations of unsaturated groundwater flow and some analytical methods of solution. Derivation of the onedimensional and threedimensional nonlinear partial differential equation, the Boltzman transformation, development of the Philip solution for horizontal and vertical flow, applications to the calculation of the soilwater diffusivity (the inverse problem) and the calculation of the evolution of the water content. Mathematical statement of the saturated and unsaturated groundwater pollution problem and some analytical methods of solution. Use of the divergence theorem in the development of the advectivedispersive equation in porous media, the semigroup solution of the resulting evolution equation, examples of solutions using the Laplace transform and the Fourier transform, more complex solutions in twodimensional and threedimensional domains, solutions for distributed sources in time and in space, solutions for timevaried boundary conditions. The approximate solution of boundary value problems and modeling of groundwater systems. Development of fundamental finite differences equations using the divergence theorem, some applications to the solution of steady and unsteady regional flow problems. Other models: single cell and multicell models, solution of problems involving fluid interfaces
CE661 Advanced Hydrology (on demand)
Study of the mathematical models of hydrologic processes taking place in a watershed. Precipitation models. Evaporation and evapotranspiration. Infiltration equations. Theory of flood wave propagation in stream channels. Theory of overland flow and its kinematic wave approximations. Equations of saturated and saturated subsurface flow on a hillside. Numerical solutions. Computer simulation
CE662 Stochastic Hydrology (on demand)
Probabilistic, statistic, and uncertainty analysis of hydrologic phenomena. Sources of hydrologic uncertainty and environmental climatic fluctuations. Hydrologic random variables and probability distributions. Statistical measures, parameter estimation procedures, discrete and continuous probability laws commonly used in hydrology, development and use of Montecarlo simulations in the generation of precipitation fields. Statistical tests of hydrologic data. Point frequency and regional frequency analysis. Stochastic processes in hydrology. Basic concepts, moments. Some useful random processes: Random walk, white noise, Brownian Motion. Stochastic differential equations in hydrology. Review of some differential equations relevant to hydrologic modeling and their solutions. Solution of hydrologic differential equations subject to stochastic parameters, stochastic boundary conditions or stochastic source terms. Moments of the solution and computational aspects. Examples: saturated groundwater flow, unsaturated groundwater flow, groundwater pollution. Analysis of hydrologic time series. Longterm trend, harmonic analysis of periodicity, autocorrelation, spectral analysis. Correlation and regression analysis. Simple regression of two hydrologic variables, multiple regression analysis. Linear stochastic models. Theory and applications of autoregressive models, the AR(1), AR(2), MA(q), ARMA(1,1), ARMA(p,q) and ARIMA(p,d,q) models, seasonal models, parameter estimation
CE561 Groundwater Modeling (Spring, every year; in compressed video, on demand)
An introduction to the practical aspects of numerical modeling techniques as applied to the solution of groundwater flow and groundwater pollution problems is given. A review of elementary finite differences, finite elements, and computeroriented analytical methods will be provided along with the opportunity to test and modify several example microcomputer programs. Mathematical models in groundwater. Finite difference methods for steady state flow problems. Finite difference methods for transient flow problems. Finite element methods for steady state flow problems. Finite element methods for transient flow problems. Various approaches to groundwater pollution modeling
EGR680 Engineering Applications of Stochastic Differential Equations (on demand)
This is an advanced-level course for students with previous exposure to probability and/or statistics and with a good working knowledge of ordinary and partial (deterministic) differential equations. It is intended for research-oriented students in all the engineering fields, physics, chemistry, earth sciences, biology, biomedicine, and applied mathematics. This course attempts to combine a solid background in probability with a series of systematic methods to solve random differential equations appearing in engineering. Physical, chemical and biological processes are usually subject to a variety of uncertain conditions which are best described in probabilistic terms. These uncertain conditions come from errors in measurement of the input variables, random environmental fluctuations, errors due to simplifying model assumptions, and our inability to accurately predict future realizations of natural phenomena. Stochastic methods are concerned with the development of mathematical procedures to correctly represent the behavior of engineering systems under uncertainty. Uncertainty Analysis of physical and natural phenomena. Review of probability, random variables and stochastic processes. Review of the theory of linear systems and the theory of deterministic ordinary and partial differential equations. Stochastic Calculus: Stochastic continuity, stochastic differentiation, stochastic integration. Systems Governed by Random Ordinary Differential Equations: Solution processes for random initial conditions, random forcing terms and random parameters, examples. Systems governed by partial differential equations: random steady equations and random evolution equations; solutions for random initial conditions, random boundary conditions random forcing terms and random parameters
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