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dc.contributorSingh, Vijay P.
dc.creatorHao, Zengchao
dc.date.accessioned2014-09-16T07:28:20Z
dc.date.accessioned2017-04-07T20:00:15Z
dc.date.available2014-09-16T07:28:20Z
dc.date.available2017-04-07T20:00:15Z
dc.date.created2012-05
dc.date.issued2012-07-16
dc.identifier.urihttp://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10828
dc.description.abstractThe dissertation focuses on the application of entropy theory in hydrologic analysis and simulation, namely, rainfall analysis, streamflow simulation and drought analysis. The extreme value distribution has been employed for modeling extreme rainfall values. Based on the analysis of changes in the frequency distribution of annual rainfall maxima in Texas with the changes in duration, climate zone and distance from the sea, an entropy-based distribution is proposed as an alternative distribution for modeling extreme rainfall values. The performance of the entropy based distribution is validated by comparing with the commonly used generalized extreme value (GEV) distribution based on synthetic and observed data and is shown to be preferable for extreme rainfall values with high skewness. An entropy based method is proposed for single-site monthly streamflow simulation. An entropy-copula method is also proposed to simplify the entropy based method and preserve the inter-annual dependence of monthly streamflow. Both methods are shown to preserve statistics, such as mean, standard deviation, skenwess and lag-one correlation, well for monthly streamflow in the Colorado River basin. The entropy and entropy-copula methods are also extended for multi-site annual streamflow simulation at four stations in the Colorado River basin. Simulation results show that both methods preserve the mean, standard deviation and skewness equally well but differ in preserving the dependence structure (e.g., Pearson linear correlation). An entropy based method is proposed for constructing the joint distribution of drought variables with different marginal distributions and is applied for drought analysis based on monthly streamflow of Brazos River at Waco, Texas. Coupling the entropy theory and copula theory, an entropy-copula method is also proposed for constructing the joint distribution for drought analysis, which is illustrated with a case study based on the Parmer drought severity index (PDSI) data in Climate Division 5 in Texas.
dc.language.isoen_US
dc.subjectrainfall analysis
dc.subjectstreamflow simulation
dc.subjectdrought analysis
dc.subjectmaximum entropy
dc.subjectcopula
dc.subjectjoint distribution
dc.titleApplication of Entropy Theory in Hydrologic Analysis and Simulation
dc.typeThesis


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