Applications Of Statistical Analyses On Water Quality Data And Its Recent
Research Trends
Dr. Nancy Agnes, Head,
Technical Operations, Tutorsindia
info@ tutorsindia.com
Keywords:
Regression analysis, Testing Statistical
Hypothesis, Statistical Modelling, Data
collection, statistical analysis
I. INTRODUCTION
II. STATISTICAL TECHNIQUES
The common statistical analysis or
techniques to handle water quality data is
as follows:
Statistical
Commonly
Analysing water quality data entails
Technique
applied to
reviewing and assessing the data to see if
Trend analysis
Rainfall
any errors were made during the sampling
Correlation
Flowing quality of
or analysis of the water quality sample or
water
data entry. To detect any issues regarding
surface,
data, a series of data checks should be
water quality
performed. It includes data checking in the
Regression analysis
on
any
drinking
Sanitary
water
quality
first stage, i.e. data entry, whether the data
is within the range of parameters, data is
Autocorrelation
Water
within the detection limits, etc. However,
analysis
measured
quality
at
there are different aspects of water quality,
several point of
and the techniques suitable for each field
time
are tabulated in the following subsection.
Testing
One way to analyse the water quality data
Hypothesis
Statistical Comparing
the
water quality of
is using graphical techniques. The benefits
two or more rivers
of graphical representation of data
or regions
include finding the data trend, finding
outliers in the data, etc.
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Statistical Modeling
Predicting
outcome
future
like
1
rainfall prediction,
etc.
Control Charts
Quality of water is
under
control
limits or not.
1. Trend analysis:
It acts as an important factor for
water quality analysis since it
helps the researcher understand the
data's variability. Wang et al.
2. Correlation:
(2020) proposed an innovative
trend analysis to detect or identify
the annual and seasonal rainfall
pattern.
Data
collection
from
different meteorological stations
and compare the proposed method
with
Theil-Sen
trend
method
The result revealed a strong trend
associated with flood and drought
during extreme rainfall. These
methods' validity showed that the
seasonal
method
trend
the relationship between two or
more variables. It helps to identify
the variables which control the
variability in water quality data.
For example, consider a study on
water flowing quality on land, i.e.
Mann-Kendall test.
proposed
Correlation is basically to identify
detects
the
accurately than
water quality in the rivers. One can
take different research problem
based on the river data. However,
suppose our interest is to find the
seasonality of water quality in
selected areas and the land usage.
using the other two test methods.
Then common statistical technique
Our Data collection service help in
to analyse the data is using
collect clean data and maximize
Spearman's
your impact.
coefficients. It can identify the
rank
correlation
relationship between the water
quality parameters and the various
land usage at different times. The
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2
correlation matrix will look like the
However, selecting a suitable statistical
following table 1.
analysis
A
1.00
B
0.34
1.00
water
quality
analysis
technique depends on the data and the
Table 1: Sample Correlation Matrix
X/Y
A
B
C
or
research question. The choice of suitable
C
0.72
0.80
1.00
analytical technique is based on detection
limits, i.e. range of concentration of the
chemical component in the water, how
much accuracy and precision are needed
3. Regression analysis: Regression
for the research problem. The most
analysis helps find the average
important
relationship between the variables
Statswork
and is useful to predict future
statistical analysis service to get high
outcomes.
quality data.
is
the
provide
sampling
strategy.
suitable
online
4. Autocorrelation analysis: If we
III. FUTURE SCOPE
want to understand the relationship
between two or more similar
There are numerous statistical procedures
attributes measured at different
or techniques to analyse the water quality
time points, then autocorrelation
data. Since water scarcity is increasing due
analysis can be used.
to lack of rainfall in many regions, finding
5. Testing statistical hypothesis
the water quality for the recycled water,
6. Statistical modelling: It is used to
research related to turning the hard water
identify the behaviour and predict
to soft water, etc. are considered future
future
research scope.
outcomes
through
a
mathematical formulation.
7. Control Charts: It is used to
monitor the process and detect the
data variability using control limits.
The most popular is the mean chart
REFERENCES:
1.
Al
Saad
Z.A.A.,
Hamdan
A.N.
(2020)
and range chart. If any data points
Evaluation of Water Treatment Plants Quality
are scattered away from the limits,
in Basrah Province, by Factor and Cluster
Analysis.
they can be considered defective
and treated as an outlier(s).
Journal
of
Water
and
Land
Development. 46 (VII–IX) pp. 10–19.
2.
Yuefeng Wang, Youpeng Xu, Hossein Tabari,
Jie Wang, Qiang Wang, Song Song, Zunle Hu.
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3
(2020). Innovative Trend Analysis of Annual
and Seasonal Rainfall in the Yangtze River
Delta, Eastern China, Atmospheric Research,
231, 104673.
3.
Tommaso Caloiero (2020). Evaluation of
Rainfall Trends in the South Island of New
Zealand
through the Innovative Trend Analysis (ITA).
Theoretical and Applied Climatology, 139, pp.
493–504.
4.
Fikret Ustaoğlu, Yalçın Tepe, Beyhan Taş,
(2020). Assessment of stream quality and
health risk in a subtropical Turkey river
system: A combined approach using statistical
analysis and water quality index, Ecological
Indicators, 113, pp. 1 – 12.
5.
Emma R. Kelly, Ryan Cronk, Emily Kumpel,
Guy Howard, Jamie Bartram, (2020). How we
assess water safety: A critical review of
sanitary inspection and water quality analysis,
Science of The Total Environment, 718, pp. 1 –
9.
.
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