1.731  Water Resource Systems
Spring 2003 Syllabus

Instructor:  Prof. Dennis McLaughlin Rm. 48-209 253-7176 dennism@mit.edu
This subject is concerned with quantitative methods for analyzing large-scale water resource problems.  Topics covered include the design and management of facilities such as irrigation areas, water treatment plants, and networks of reservoirs and associated canals.  Simulation models and optimization methods are often used to support analyses of water resource problems.   In this subject we will be constructing simulation models with the MATLAB programming language and solving numerical optimization problems  with the GAMS optimzation package.  It is desirable for students taking this subject to have some background in hydrology, linear algebra and programming, although these are not strict prerequisites. 

Class periods will generally be divided into 40 minutes of lecture and 40 minutes of related hands-on computer work using laptops available in the classroom.

There will be two in-class exams. Homework will vary in complexity from straightforward problem sets to mini-projects which resemble real-world applications. The grade will be based on exams (60%) and homework (40%).  A detailed schedule is provided below.

Introduction, Modeling, and Simulation
No. Date Topic and links for examples PS  PS links
1 Feb. 4 Case Study: Irrigation and Salination
PS1 out PS1&Solutions
Word    PDF
2 Feb. 6 Modeling in MATLAB
3 Feb. 11 Probability Review I
Random variables, probability distributions
cstr.minconc.dat  ;  runoff.mprecip.dat
4 Feb. 13 Probability Review II
Expectation; moments, derived distributions, Monte Carlo simulation
derived_dist1.m  ;  derived_dist2.m
PS1 in,
PS2 out
Word    PDF
5 Feb. 20 Time series, computing empirical event probabilities 

Optimization Concepts
No. Date Topic and links for examples PS PS links
6 Feb. 25 Formulation of Optimization Problems I
Introduction to GAMS
PS2 in,
PS3 out
Word    PDF
7 Feb. 27 Formulation of Optimization Problems II
8 Mar. 4 Optimality conditions I
Example applying optimality conditions
9 Mar. 6 Optimality conditions II
Continuation of example
10 Mar. 11 Quantifying optimization objectives; Present value and amortization, Multiobjective optimization, parametric analysis
PS3 in
PS4 out
Word    PDF
11 Mar. 13 Introduction to stochastic optimization; Incorporating uncertainty
12 Mar. 18 Expected utility and risk aversion, Utility and multiobjective optimization
Review for Quiz 1
PS4 in  
13 Mar. 20 Quiz 1    

Optimization Algorithms and Applications
No. Date Topic and links for examples PS PS links
14 April 1 Linear programming concepts and terminology
GAMS examples
PS5 out PS5&Solutions
Word    PDF
15 April 3 Solving linear programming problems
GAMS examples
16 April 8 Shadow prices and sensitivity analysis
GAMS examples
PS5 in
PS6 out
Word    PDF
17 April 10 Case Study: River Basin Planning    
18 April 15 Nonlinear programming
GAMS examples
19 April 17 Incorporating simulation models into optimization algorithms
MATLAB implementation
PS6 in
PS7 out
Word    PDF
20 April  24 Case Study: Optimal management of irrigated agriculture    
21 TBA Dynamic programming I
MATLAB implementation
22 May 1 Dynamic programming II
MATLAB implementation
PS7 in,
PS8 out 
Word     PDF
23 May 6 Case Study: Capacity expansion    
24 May 8 Stochastic dynamic programming    
25 May 13 Case Study: Evaluating infrastructure options in Thailand PS8 in  
26 May 15 Quiz 2    

 Copyright 2003 Massachusetts Institute of Technology
 Last modified Feb. 16, 2003   dennism