Stochastic Hydrology
Stochastic Hydrology. Instructor: Prof. P. P. Mujumdar, Department of Civil Engineering, IISc Bangalore. The objective of this course is to introduce the concepts of probability theory and stochastic processes with applications in hydrologic analysis and design. Modeling of hydrologic time series with specific techniques for data generation and hydrologic forecasting will be dealt with. Case study applications will be discussed.
(from nptel.ac.in)
Introduction 
Lecture 01  Introduction 
Lecture 02  Bivariate Distributions 
Lecture 03  Independence; Functions of Random Variables 
Lecture 04  Moments of a Distribution 
Commonly used Probability Distributions 
Lecture 05  Normal Distribution 
Lecture 06  Other Continuous Distributions 
Data Generation 
Lecture 07  Parameter Estimation 
Lecture 08  Covariance and Correlation 
Lecture 09  Data Generation 
Time Series Analysis 
Lecture 10  Time Series Analysis, Part 1 
Lecture 11  Time Series Analysis, Part 2 
Lecture 12  Time Series Analysis, Part 3 
Lecture 13  Frequency Domain Analysis 
Lecture 14  Frequency Domain Analysis (cont.), ARIMA Models 
Lecture 15  ARIMA Models, Part 2 
Lecture 16  ARIMA Models, Part 3 
Lecture 17  ARIMA Models, Part 4 
Lecture 18  Case Studies, Part 1 
Lecture 19  Case Studies, Part 2 
Lecture 20  Case Studies, Part 3 
Lecture 21  Case Studies, Part 4 
Markov Chains 
Lecture 22  Markov Chains 
Lecture 23  Markov Chains (cont.) 
Frequency Analysis 
Lecture 24  Frequency Analysis 
Lecture 25  Frequency Analysis (cont.) 
Lecture 26  Frequency Analysis (cont.), Probability Plotting 
Lecture 27  Probability Plotting (cont.) 
Lecture 28  Goodness of Fit 
Lecture 29  IDF Relationships 
Multivariate Models 
Lecture 30  Multiple Linear Regression 
Lecture 31  Principal Component Analysis 
Lecture 32  Regression on Principal Components 
Lecture 33  Multivariate Stochastic Models, Part 1 
Lecture 34  Multivariate Stochastic Models, Part 2 
Lecture 35  Multivariate Stochastic Models, Part 3 
Data Consistency 
Lecture 36  Data Consistency, Part 1 
Lecture 37  Data Consistency, Part 2 
Lecture 38  Data Consistency, Part 3 
Applications and Summary 
Lecture 39  Recent Applications: Climate Change Impact Assessment 
Lecture 40  Summary 
References 
Stochastic Hydrology
Instructor: Prof. P. P. Mujumdar, Department of Civil Engineering, IISc Bangalore. The objective of this course is to introduce the concepts of probability theory and stochastic processes with applications in hydrologic analysis and design.
