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Related Experiment Video

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Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Published on: September 26, 2017

Rainfall Threshold Assessment Corresponding to the Maximum Allowable Turbidity for Source Water.

Shu-Kai S Fan¹, Wen-Hui Kuan, Chihhao Fan

¹Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei City, Taiwan, 10608.

Water Environment Research : a Research Publication of the Water Environment Federation

|March 11, 2016

Summary

This study identifies critical upstream rainfall thresholds to manage source water turbidity. Artificial neural networks predict turbidity, aiding water resource management in the Taipei Water Source Domain.

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Area of Science:

Environmental Science
Hydrology
Water Resource Management

Background:

Source water turbidity is a critical water quality parameter.
Effective management requires understanding the relationship between rainfall and turbidity.
Predictive models are essential for proactive water quality control.

Purpose of the Study:

To determine upstream rainfall thresholds linked to maximum allowable source water turbidity.
To develop a predictive model for downstream turbidity using artificial neural networks.
To establish rainfall thresholds for specific rain gauge stations in the Taipei Water Source Domain.

Main Methods:

Collected upstream rainfall data and source water turbidity monitoring data.
Employed Analysis of Variance (ANOVA) to identify significant rainfall parameters.
Developed and utilized an artificial neural network (ANN) model for turbidity prediction.

Main Results:

Identified five key cumulative rainfall parameters (e.g., one-day Ping-lin, two-day Tong-hou) influencing turbidity.
Constructed an ANN model capable of predicting downstream turbidity.
Calculated specific upstream rainfall thresholds based on preselected turbidity criteria.

Conclusions:

Upstream rainfall significantly impacts source water turbidity.
ANN models provide a reliable method for predicting turbidity and assessing rainfall thresholds.
The findings support proactive water resource management strategies to ensure water quality.