The Seasonal Characteristics of the Wind Conditions and Turbidity for Lake-Type Raw Water and the Development of a Turbidity Prediction Model

Shallow lakes are important drinking water sources, but are easily affected by wind. Turbidity is an indicator that fluctuates dramatically with changes in wind and is affected not only by the instantaneous wind speed but also by the wind direction, duration, etc. The Weibull distribution was introduced to describe the distributions of the wind conditions and turbidity during a seasonal period. The relationship between the mean wind-power density and the corresponding turbidity reached 0.8, which showed a relatively strong correlation. A turbidity prediction model was built by the random forest algorithm and was fed with the mean wind-power density and temperature. The results indicated that nearly half of the test samples had REs less than 20%, which was enough for waterworks to adjust the dosage in advance. The findings can be used to develop turbidity prediction models using meteorological forecast data and provide a reference for waterworks with shallow lakes as sources.

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Publication Details

Journal
Sustainability
Published
2025-02-21
DOI
https://doi.org/10.3390/su17051835
Citations
1
Primary Topic
Hydrology and Watershed Management Studies
Type
article
Field-Weighted Citation Impact
0.82
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article

The Seasonal Characteristics of the Wind Conditions and Turbidity for Lake-Type Raw Water and the Development of a Turbidity Prediction Model

Yiping Zhang, Xiaolin Yao
1 citations
Sustainability
Hydrology and Watershed Management Studies
0.82
article

The Seasonal Characteristics of the Wind Conditions and Turbidity for Lake-Type Raw Water and the Development of a Turbidity Prediction Model

Yiping Zhang, Xiaolin Yao
article en
1 citations

Abstract

Shallow lakes are important drinking water sources, but are easily affected by wind. Turbidity is an indicator that fluctuates dramatically with changes in wind and is affected not only by the instantaneous wind speed but also by the wind direction, duration, etc. The Weibull distribution was introduced to describe the distributions of the wind conditions and turbidity during a seasonal period. The relationship between the mean wind-power density and the corresponding turbidity reached 0.8, which showed a relatively strong correlation. A turbidity prediction model was built by the random forest algorithm and was fed with the mean wind-power density and temperature. The results indicated that nearly half of the test samples had REs less than 20%, which was enough for waterworks to adjust the dosage in advance. The findings can be used to develop turbidity prediction models using meteorological forecast data and provide a reference for waterworks with shallow lakes as sources.

SustainabilityVol. 17(5)
Hangzhou Wanxiang Polytechnic (CN), Zhejiang University (CN)
Openalex Percentile: Top 29%
Hydrology and Watershed Management Studies
0.82
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