A review of
water
quality
index models and their use for assessing surface
water
quality
ABCD PBi
A review of
water
quality
index models and their use for assessing surface
water
quality
Autor:
Uddin, Md. Galal
;
Nash, Stephen
;
Olbert, Agnieszka I.
Assuntos:
Aggregation function
;
Model uncertainty and sensitivity
;
Sub-index
;
Surface
water
quality
;
water
quality
index (WQI)
;
Water
quality
parameters
É parte de:
Ecological indicators, 2021-03, Vol.122, p.107218, Article 107218
Descrição:
•Twenty-one different WQI models were identified and reviewed.•Rivers are by far the most common application of WQI models.•Most models comprised of four key components, the specifics of which varied significantly.•Uncertainty and eclipsing problems are key issues affecting model accuracy. The
water
quality
index (WQI) model is a popular tool for evaluating surface
water
quality
. It uses aggregation techniques that allow conversion of extensive
water
quality
data into a single value or index. Globally, the WQI model has been applied to evaluate
water
quality
(surface
water
and groundwater) based on local
water
quality
criteria. Since its development in the 1960s, it has become a popular tool due to its generalised structure and ease-of-use. Commonly, WQI models involve four consecutive stages; these are (1) selection of the
water
quality
parameters, (2) generation of sub-indices for each parameter (3) calculation of the parameter weighting values, and (4) aggregation of sub-indices to compute the overall water quality index. Several researchers have utilized a range of applications of WQI models to evaluate the water quality of rivers, lakes, reservoirs, and estuaries. Some problems of the WQI model are that they are usually developed based on site-specific guidelines for a particular region, and are therefore not generic. Moreover, they produce uncertainty in the conversion of large amounts of water quality data into a single index. This paper presents a comparative discussion of the most commonly used WQI models, including the different model structures, components, and applications. Particular focus is placed on parameterization of the models, the techniques used to determine the sub-indices, parameter weighting values, index aggregation functions and the sources of uncertainty. Issues affecting model accuracy are also discussed.
Editor:
Elsevier Ltd
Idioma:
Inglês