Selection of Water Quality Monitoring Stations - Water Quality Management: Assessment and Interpretation - page 4

Chapter 2
Selection of Water Quality Monitoring
Stations

Abstract Due to financial constraints and improper selection of water quality sta-

tions considering the objective of water uses, water quality monitoring network
design is an ef

nd
appropriate locations for monitoring stations. In the past, most of water quality
selection stations were subjective and the designs on the network had some human
error. However, now there are several mathematical methods using experimental data
for assessment of existing monitoring stations or designing new network such as
Sanders method, multiple criteria decision making (MCDM) and dynamic pro-
gramming approach (DPA) that developed by researchers. In the following chapter,
after reviewing the historical background of developing and application of the
methods, the theory of these methods was described in details. Finally, the application
of the Sanders Method to design number of water quality monitoring stations in the
K

cient method to manage water quality. The most crucial part is to

ā r ū in River which located in the south west of Iran was studied.

2.1 Historical Background

Allocation of the water quality monitoring site is the cant step in the

design of the water quality network. The importance of water quality network control
concerning pollution causes creation of water quality stations in the network. How-
ever,

first and the signi

finical constraints causes to decrease the number of water quality station in the
network. Regarding optimizations of a number of monitoring stations some tech-
niques were developed such as Sanders method, arti

cial neural network, Multi-
Criteria Decision Method (MCDM) and Dynamic Program Approach (DPA). Some
researches were carried out by Sharp ( 1970 , 1971 ); Dandy ( 1976 ); Sanders ( 1983 );
Schilperoort and Groot ( 1983 ); Ward and Loftis ( 1986 ); MacKenzie et al. ( 1987 );
Woldt and Bogardi ( 1992 ); Harmancioglu and Alpaslan ( 1992 ); Hudak and Loaiciga
( 1993 ); Karemi ( 2002 ); Ozkul et al. ( 2003 ); Khalil and Quarda ( 2009 ); Noori et al.
( 2007 ); Karamouz et al. ( 2009 ); Khalil et al. ( 2011 ); Asadollahfardi et al. ( 2011 ).
The DPA technique, which is a general method for maximizing and minimizing
mathematical functions for solving a problem together with Multi-Criteria Decision,