Trend Analysis on Water Quality Index Using the Least Squares Regression Models

Zawawi, Iskandar Shah Mohd; Haniffah, Mohd Ridza Mohd; Aris, Hazleen

doi:10.13189/eer.2022.100504

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…The author uses the regression method to model local rainfall based on climate change and ENSO variables. The general formula for regression [11] is as…”

Section: Modellingmentioning

confidence: 99%

Impact of Climate Change and the El Niño – Southern Oscillation on Extreme Rainfall

Sulistiyono¹,

Yasa²,

Saidah³

et al. 2023

eer

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Some information states that the world is currently experiencing climate change. Many scientists have researched the relationship between climate change and various natural events. Still, there has been no research on the relationship between climate change and extreme rainfall events. The relationship between climate change and extreme rainfall events needs to be clearly understood, as extreme wet events can cause losses such as landslides in hilly areas, submerged agricultural areas, and damaged residential facilities due to flooding. Meanwhile, extreme dry events can lead to droughts and forest fires. The authors have proposed a procedure to utilize the upper and lower threshold values to determine the extreme rainfall. The proposed procedure uses correlation coefficient and regression modeling. The authors hope that engineers can estimate the extreme rainfall after understanding the relationship between climate change variables and the El-Nino Southern Oscillation (ENSO) on local rainfall. This study applied monthly rainfall data from the Alas Rainfall Station in Indonesia, climate change data, and ENSO from 1992 to 2021 to demonstrate the proposed procedure. The results showed that climate change affects the occurrence of Extreme Rainfall at the Alas Rainfall Station. The predicted extreme wet was 118.11%, and the predicted extreme dry was 72.12%. Extreme wet events are becoming more frequent, while extreme dry events are decreasing. The ENSO has no significant relationship to the extreme rainfall at several stations.

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“…The author uses the regression method to model local rainfall based on climate change and ENSO variables. The general formula for regression [11] is as…”

Section: Modellingmentioning

confidence: 99%

Impact of Climate Change and the El Niño – Southern Oscillation on Extreme Rainfall

Sulistiyono¹,

Yasa²,

Saidah³

et al. 2023

eer

View full text Add to dashboard Cite

show abstract

“…Usually, selecting a suitable numerical model to solve a practical water quality problem is a highly specialised task, requiring detailed knowledge on the application and limitation of models [7]. Therefore, evaluating the surface-water quality and the associated hydrochemical characteristics is essential for managing water resources in arid and semi-arid environments [15]. DISCUSSIONS In employing a basic polynomial regression method for our water quality predictive modeling, we acknowledge its sim-plicity and effectiveness using the available dataset.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence for Water Quality

Vaivude

2023

IJRASET

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This study delves into how AI can be applied within water and environmental engineering research, particu- larly emphasizing the utilization of machine learning models to advance the accuracy of water quality predictions in the Delaware River. Through an analysis of time series data spanning from 2020 to 2022 and the utilization of exploratory data analysis methods, this investigation scrutinizes various elements influenc- ing the dynamics of water quality. For water quality time series analysis, identifying changes in long-term trends is important, yet identifying specific change-points is also important[3]. A strong correlation is notably detected between levels of dissolved oxygen and recorded temperatures. Leveraging this correlation, an intricate polynomial regression model is crafted to forecast dissolved oxygen concentrations based on expected temperature values. This predictive model not only clarifies the inherent link between dissolved oxygen and temperature but also offers insights into projecting future dissolved oxygen levels in the Delaware River, considering anticipated temperature fluctuations. These findings hold significant promise, potentially enhancing ecologi- cal evaluations and the development of impactful management strategies, specifically designed for water quality monitoring and conservation efforts within the Delaware River basin. Hence, eval- uation of water quality of groundwater is extremely important to prepare for remedial measures[1].

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Trend Analysis on Water Quality Index Using the Least Squares Regression Models

Cited by 2 publications

References 14 publications

Impact of Climate Change and the El Niño – Southern Oscillation on Extreme Rainfall

Impact of Climate Change and the El Niño – Southern Oscillation on Extreme Rainfall

Artificial Intelligence for Water Quality

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