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 
irrigation.m

PS1 out

PS1&Solutions
Word    PDF

2

Feb. 6

Modeling in MATLAB 
irrigation.m

 

 

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

PS2&Solutions
Word    PDF

5

Feb. 20

Time series, computing empirical event probabilities  
runoff_monte.m

 

 


 

Optimization Concepts

No.

Date

Topic and links for examples

PS

PS links

6

Feb. 25

Formulation of Optimization Problems I 
Introduction to GAMS 
transprt.gms

PS2 in, 
PS3 out

PS3&Solutions
Word    PDF

7

Feb. 27

Formulation of Optimization Problems II 
convexity.m

 

 

8

Mar. 4

Optimality conditions I 
Example applying optimality conditions 
optimality.gms

 

 

9

Mar. 6

Optimality conditions II 
Continuation of example 
yield.gms

 

 

10

Mar. 11

Quantifying optimization objectives; Present value and amortization, Multiobjective optimization, parametric analysis 
pareto.gms

PS3 in 
PS4 out

PS4&Solutions
Word    PDF

11

Mar. 13

Introduction to stochastic optimization; Incorporating uncertainty 
pareto.gms

 

 

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

PS6&Solutions
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

PS7&Solutions
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 

PS8&Solutions
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