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Water Supply

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Development of a Soft Sensor for Flow Estimation in Water Supply Systems Using Artificial Neural Networks.

Sensors (Basel, Switzerland)
A water supply system is considered an essential service to the population as it is about providing an essential good for life. This system typically consists of several sensors, transducers, pumps, etc., and some of these elements have high costs an...

Investigation of intra - event variations of total, dissolved and truly dissolved metal concentrations in highway runoff and a gross pollutant trap - bioretention stormwater treatment train.

Water research
Metals in stormwater can be toxic to organisms, particularly when occurring in truly dissolved form (fraction <3 kDa). Here, using 153 samples collected during six rains, we investigated intra-events variations of total, dissolved and truly dissolved...

Improving the leak detection efficiency in water distribution networks using noise loggers.

The Science of the total environment
Leak detection techniques are effective ways of controlling water leakage in real water distribution networks (WDNs). Nevertheless, developing detection techniques for real WDNs has received little attention compared to the detection models developed...

Multivariate Streamflow Simulation Using Hybrid Deep Learning Models.

Computational intelligence and neuroscience
Reliable and accurate streamflow simulation has a vital role in water resource development, mainly in agriculture, environment, domestic water supply, hydropower generation, flood control, and early warning systems. In this context, these days, deep ...

Occurrence and concentration of 20-100 μm sized microplastic in highway runoff and its removal in a gross pollutant trap - Bioretention and sand filter stormwater treatment train.

The Science of the total environment
Microplastic pollution of stormwater can be a serious threat to the environment. Gross pollutant trap (GPT) - bioretention treatment trains have been shown previously to treat (inter alia) particulate stormwater pollutants including microplastic part...

A stochastic modeling approach for analyzing water resources systems.

Journal of contaminant hydrology
Many uncertain factors exist in the water resource systems, leading to dynamic characteristics of the water distribution process. Especially for the watershed including irrigation area with multiple water sources and water users, it is complicated th...

Spectrophotometric Online Detection of Drinking Water Disinfectant: A Machine Learning Approach.

Sensors (Basel, Switzerland)
The spectra fingerprint of drinking water from a water treatment plant (WTP) is characterised by a number of light-absorbing substances, including organic, nitrate, disinfectant, and particle or turbidity. Detection of disinfectant (monochloramine) c...

Contamination source identification in water distribution networks using convolutional neural network.

Environmental science and pollution research international
Contamination source identification (CSI) is significant for water quality security and social stability when a contamination intrusion event occurs in water distribution systems (WDSs). However, in research, this is an extremely challenging task for...

Risk assessment of hybrid rain harvesting system and other small drinking water supply systems by game theory and fuzzy logic modeling.

The Science of the total environment
The complexity and uncertainties affecting drinking water supply systems and threatening hazards require a comprehensive and effective risk assessment to increase the reliability of drinking water safety, especially for small or household systems. Th...

Deep learning identifies accurate burst locations in water distribution networks.

Water research
Pipe bursts in water distribution networks lead to considerable water loss and pose risks of bacteria and pollutant contamination. Pipe burst localisation methods help water service providers repair the burst pipes and restore water supply timely and...