Natural Resources Management Integrated Water Resources Management

ILO-1_Matlab practice and time-series analysis

Spring semester 2015

Andrea Cominola

General info Contacts Andrea Cominola (andrea.cominola@polimi.it) Meeting by appointment on Tuesday morning and available during work time hour.

Lab info  _ All the official communications and the additional material can be found in

the Beep portal: https://beep.metid.polimi.it _ The material for the laboratory is available in the following directory:

P: Natural Resources Management

_ The day before each laboratory, the material (presentations, MatLab code and data) will be also uploaded in the Beep portal.

Lab schedule Tuesday afternoon 14.15 – 18.15 + work time 18.15 – 19.15. Room 3.3 10 Mar 2015 ILO-1 – Matlab Practice and Time Series Analysis 17 Mar 2015 ILO-2 – Lake Maggiore flood indicators / Groups for term project 24 Mar 2015 ILO-3 – Irrigania game 31 Mar 2015 ILO-4 – WEAP modeling of the Lower Bear River (Utah) 14 Apr 2015 ILO-5 – Multi-objective visualizations 21 Apr 2015 ILO-6 – Near-optimal management 28 Apr 2015 GROUP PROJECT – interim presentation on user group and

performance metrics 5 May 2015 GROUP PROJECT - Grandi Laghi Lombardi in WEAP 12 May 2015 GROUP PROJECT - Grandi Laghi Lombardi in WEAP 19 May 2015 GROUP PROJECT – Work time 26 May 2015 FINAL GROUP PRESENTATIONS

Matlab information

MatLab http://www.mathworks.com http://www.math.ufl.edu/help/matlab-tutorial/ http://www.math.utah.edu/lab/ms/matlab/matlab.html How to get the 2014b version provided by Polimi: http://www.software.polimi.it/en/software-download/students/matlab/ Alternative software - octave http://www.octave.org/

Case study Lake Maggiore

Lake Como

Lake Iseo

Basic statistics

min

max

std mean

Basic statistics A statistic is a syntehetic index (scalar variable) characterizing our data series. Typical statistics are: and the maximum and minimum extreme values of the data series.

M

x

=1

N

NX

i=1

x

i

S

2x

=1

N � 1

NX

i=1

(xi

�Mx

)2

S

x

=p

S

2x

=

vuut 1N � 1

NX

i=1

(xi

�Mx

)2

mean

variance

standard deviation