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Unformatted text preview: Florida International University Department of Civil and Environmental Engineering CWR6117 Statistical Hydrology Course Outline Catalog Description (NEW): Quantitative description and estimation of surface water and groundwater hydrology variables from a statistical approach. Course Objectives: This course emphasizes the use of statistical methods to quantify the different components of the hydrologic cycle. Focus is placed on the development and use of stochastic approaches to treat naturally occurring spatial and temporal variability in hydrologic variables. Students will learn about the fundamental processes triggering uncertainty of the components of the hydrologic cycle, and the quantitative tools that are being used and in development to provide estimates of water budget and statistical variability at the site, regional and global scales. Learning Outcomes: Understand the statistical variability of components of the components of the hydrologic cycle at the site, regional and global scales Apply quantitative approaches to provide estimates of water stocks and fluxes through the hydrosphere, as well as estimates of uncertainty Understand the limits of predictability of hydrologic variables in urban and natural settings Course Topics: Introduction: overview of the hydrologic cycle; atmospheric, surface and subsurface water; water balance concepts; natural variability of hydrologic cycle processes. Probability Theory: random events, random variables and statistical distributions, moments of a random variable, sequences of random variables. Probabilistic Models and Observed Data: models from discrete random trials, models from random occurrences, limiting cases, multivariate models and Markov chains; hypothesis testing. Stochastic Processes: stationarity and ergodicity, spectral analysis of hydrologic data. Univariate and Multivariate Times Series Analysis of Hydrologic Data: stationary and non‐stationary models, streamflow forecasting. Frequency Domain Analysis of Hydrologic Processes: applications to rainfall data time series, seasonality and detection of trends. Multidimensional Hydrologic Processes: correlation and spectrum, application to hydrologic data generation (rainfall, runoff). Hydrologic Estimation in Linear and Non‐linear Systems: optimal estimation (kriging) methods, detrending approaches, Kalman filtering, applications to hydrologic monitoring network design. Stochastic Modeling of the Water Balance: probabilistic solution to the water balance equation in time, stochastic approach to spatial variability and solution approaches. Instructor Fernando Miralles‐Wilhelm Office EC‐3607 Tel: 305‐3483653 Fax: 305‐5135799 Email: [email protected] Bibliography There will be no recommended textbook for this class. Reading materials (excerpts from several books, journal articles and other materials) will be distributed electronically throughout the semester. Course Schedule TBA Prerequisite Coursework Undergraduate fluid mechanics (CWR3201 or equivalent) and water resources engineering (CWR3103 or equivalent), familiarity with differential equations helpful. Grading This course will be graded through a number of homework assignments and a term paper with an oral presentation at the end of the course. ...
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This note was uploaded on 07/09/2011 for the course CWR 6117 taught by Professor Miralles during the Spring '09 term at FIU.
- Spring '09