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Course Description

Hydrologic models are simplified, conceptual representations of a part of the hydrologic cycle.

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Course Syllabus
  • Mod-01 Lec-01 Introduction
  • Mod-01 Lec-02 Bivariate Distributions
  • Mod-01 Lec-03 Independence ; Functios of Random Variables
  • Mod-01 Lec-04 Moments of a Distribution
  • Mod-02 Lec-05 Normal Distribution
  • Mod-02 Lec-06 Other Continuous Distributions
  • Mod-03 Lec-07 Parameter Estimation
  • Mod-03 Lec-08 Covariance and Correlation
  • Mod-03 Lec-09 Data Generation
  • Mod-04 Lec-10 Time Series Analysis - I
  • Mod-04 Lec-11 Time Series Analysis - II
  • Mod-04 Lec-12 Time Series Analysis-III
  • Mod-04 Lec-13 Frequency Domain Analysis - I
  • Mod-04 Lec-14 Frequency Domain Analysis - II and ARIMA Models - I
  • Mod-04 Lec-15 ARIMA Models-II
  • Mod-04 Lec-16 ARIMA Models - III
  • Mod-04 Lec-17 ARIMA Models-IV
  • Mod-04 Lec-18 Case Studies - I
  • Mod-04 Lec-19 Case Studies - II
  • Mod-04 Lec-20 Case Studies -III
  • Mod-04 Lec-21 Case Studies- IV
  • Mod-05 Lec-22 Markov Chains - I
  • Mod-05 Lec-23 Markov Chains-II
  • Mod-06 Lec-24 Frequency Analysis - I
  • Mod-06 Lec-25 Frequency Analysis-I
  • Mod-06 Lec-26 Frequency Analysis - III and Probability Plotting - I
  • Mod-06 Lec-27 Probability Plotting - II
  • Mod-06 Lec-28 Goodness of Fit
  • Mod-06 Lec-29 IDF Relationships
  • Mod-07 Lec-30 Multiple Linear Regression
  • Mod-07 Lec-31 Principal Component Analysis
  • Mod-07 Lec-32 Regression on Principal Components
  • Mod-07 Lec-33 Multivariate Stochastic Models - I
  • Mod-07 Lec-34 Multivariate Stochastic Models - II
  • Mod-07 Lec-35 Multivariate Stochastic Models - III
  • Mod-08 Lec-36 Data Consistency Checks -I
  • Mod-08 Lec-37 Data Consistency Checks - II
  • Mod-08 Lec-38 Data Consistency Checks - III
  • Mod-09 Lec-39 Recent Applications: ClimateChange Impact Assessment
  • Mod-09 Lec-40 Summary of the Course

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