Paratanytarsus grimmii (Chironomidae) Larvae in Drinking Water Distribution Systems: Impairment or Disaster?

Christopher, Stefan; Michels, Ute; Gunkel, Günter

doi:10.3390/w15030377

Cited by 5 publications

(2 citation statements)

References 14 publications

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“…Notably, in Korean river ecosystems, the stonefly family, to which they belong, accounts for over 50% of invertebrates [10]. With the ability to achieve densities of 100,000 individuals per cubic meter of water, these larvae can thrive in depths of up to 1000 m and endure temperatures as low as minus 16 • C. Their life cycle encompasses four stages, spanning from egg to adulthood, with durations ranging from three weeks to several months [11]. The lifespans of larvae can range from two weeks to four years depending on the species [12].…”

Section: Chironomid Larvaementioning

confidence: 99%

RT-CLAD: Artificial Intelligence-Based Real-Time Chironomid Larva Detection in Drinking Water Treatment Plants

Jang,

Yeo,

Park

et al. 2023

Sensors

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The presence of chironomid larvae in tap water has sparked public concern regarding the water supply system in South Korea. Despite ongoing efforts to establish a safe water supply system, entirely preventing larval occurrences remains a significant challenge. Therefore, we developed a real-time chironomid larva detection system (RT-CLAD) based on deep learning technology, which was implemented in drinking water treatment plants. The acquisition of larval images was facilitated by a multi-spectral camera with a wide spectral range, enabling the capture of unique wavelet bands associated with larvae. Three state-of-the-art deep learning algorithms, namely the convolutional neural network (CNN), you only look once (YOLO), and residual neural network (ResNet), renowned for their exceptional performance in object detection tasks, were employed. Following a comparative analysis of these algorithms, the most accurate and rapid model was selected for RT-CLAD. To achieve the efficient and accurate detection of larvae, the original images were transformed into a specific wavelet format, followed by preprocessing to minimize data size. Consequently, the CNN, YOLO, and ResNet algorithms successfully detected larvae with 100% accuracy. In comparison to YOLO and ResNet, the CNN algorithm demonstrated greater efficiency because of its faster processing and simpler architecture. We anticipate that our RT-CLAD will address larva detection challenges in water treatment plants, thereby enhancing water supply security.

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Section: Chironomid Larvaementioning

confidence: 99%

RT-CLAD: Artificial Intelligence-Based Real-Time Chironomid Larva Detection in Drinking Water Treatment Plants

Jang,

Yeo,

Park

et al. 2023

Sensors

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show abstract

“…In 2000, the emergence of small larvae midges in water treatment plants and tap water worldwide became a growing concern, continuing into 2020 in Korean facilities [8]. The presence of Chironomidae larvae in tap water results from multiple factors, including accidental entry through intake pipes [9].…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Solutions to Prevent Larvae Breakout in Water Filtration Systems

Kwon,

Hidayaturrahman,

Koutavarapu

et al. 2023

Sustainability

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The presence of invertebrates in drinking water distribution systems, particularly Chironomidae larvae, has raised concerns among the general public. This study aimed to comprehensively address the issue of larvae breakout in water filtration systems and provide potential solutions to prevent their escape into the water supply. The research investigated various factors contributing to larvae breakout, including the type of filtration column, sand depth, pretreatment methods, and the effective size and uniformity coefficient of sand media. Experimental results revealed that the GAC column, primarily utilized for adsorption, was ineffective in retaining Chironomidae larvae, leading to their escape within a short period. Similarly, the sand filter column, with a design that is currently widely used with sand specifications of an effective size of 0.7 mm and a uniformity coefficient of 1.7, failed to act as a barrier for larvae. Increasing the height of the sand media and applying a pretreatment method, which was expected to prevent larvae from entering the treated water, yielded unsatisfactory results. Our research results show that reducing the uniformity coefficient to 1.5 while maintaining an effective size of 0.7 mm proved to be important in preventing the release of larvae into treated water. The Sand/GAC and Sand/Anthracite systems, by maintaining adjusted media sand specifications, also succeeded in retaining larvae in the filtration system. Additionally, this study emphasized the importance of following the recommended backwash procedure, consisting of specific steps involving air flow, a combination of air and water flow, and final water flow. This sequence effectively removed contaminants, turbidity, and Chironomidae larvae from the filtration media, ensuring improved water quality and system performance. The findings of this study provide valuable insights and recommendations for water treatment plants to address the issue of larvae breakout and enhance water quality.

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Zuckmückenlarven in Wasserversorgungssystemen

Scholz

2023

Wasser Abfall

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Paratanytarsus grimmii (Chironomidae) Larvae in Drinking Water Distribution Systems: Impairment or Disaster?

Cited by 5 publications

References 14 publications

RT-CLAD: Artificial Intelligence-Based Real-Time Chironomid Larva Detection in Drinking Water Treatment Plants

RT-CLAD: Artificial Intelligence-Based Real-Time Chironomid Larva Detection in Drinking Water Treatment Plants

Comprehensive Solutions to Prevent Larvae Breakout in Water Filtration Systems

Zuckmückenlarven in Wasserversorgungssystemen

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