Environmental Engineering Reference
In-Depth Information
Chapter 4
Time Series Modeling
Abstract When in surface water such as rivers, ponds and lakes detailed charac-
teristic are not available, especially in developing countries, application of deter-
ministic model are not applicable. In this regards, stochastic modeling are applied
for estimating the future value of water quality parameters. There has been much
effort in developing this technique for solving other engineering matters. Time
series modeling as a stochastic model is trying to make probabilistic statements
about the relation between system components and their future values and is used
frequently in water quality management. In this chapter, after a preliminary
explaining historical background of the method and introducing of time series
modeling, the various methods such as Box-Jenkins methodology including sta-
tionary and non-stationary models and seasonal and non-seasonal models, expo-
nential smoothing methods and Winter
s method, was stated and described in
detail. Finally the application of time series modeling on Latian Dam, which located
in the southeastern part of Tehran province in Iran, was discussed.
'
4.1 Introduction
Planning a water pollution control program in rivers requires the following steps:
The design of an experimental program and analyzing the water quality parameters,
The study of mathematical methods for
fitting equations to the parameters,
Forecasting the future values of the parameters, and
The development of appropriate control strategies.
Mathematical modeling plays a major part in formulating control strategies.
Building mathematical models require special techniques, whereby one can express
the natural phenomenon by mathematical equations. In general, there are two
approaches to mathematical modeling, as stated below:
1. Deterministic, and
2. Stochastic.
Search WWH ::
Custom Search