Water Flow Monitoring Research Articles

Boosting performance of heat-source free water-floating thermoelectric generators by controlling wettability by mixing single-walled carbon nanotubes with α-cellulose

Thermoelectric generation (TEG) using single-walled carbon nanotubes (SWCNTs), which generate electricity simply by floating on the surface of water, is promising and has novel features that are not found in conventional TEG systems. However, water-floating SWCNT-TEGs generate only a small voltage owing to the hydrophobic nature of SWCNTs. In this study, to increase their output voltage, we added α-cellulose, which is hydrophilic in nature, to the SWCNT films for enhancing water evaporative thermal cooling, leading to an increase in the temperature gradient in the TEGs. When the TEGs were exposed to artificial sunlight, the TEG with SWCNT/α-cellulose (0.6 g) films exhibited the highest output voltage of 1.0 mV, which was more than three times higher than that exhibited for the SWCNT-TEG without α-cellulose. This phenomenon can be explained by the hydrophilic nature of the films, which increases the amount of water pumped to the film surface and enhances the evaporative cooling effect as this water evaporates, thereby creating a larger temperature difference within the TEGs. The results show their significant potential as a power source for sensors such as those monitoring water flow in water environments.

GraphSmart: a method for green and accurate IoT water monitoring

Water scarcity is nowadays a critical global concern and an efficient management of water resources is paramount. This paper presents an original approach for monitoring Water Distribution Systems (WDSs) through Internet of Things (IoT) that involves the integration of multiple sensors placed across the distribution network to accurately measure water flow. To enhance energy efficiency for green monitoring and communication process, we harness the power of graph theory and graph signal processing to represent in a tunable and accurate way the water flow and simultaneously minimize the number of IoT sensors communicating those measurements. We propose a graph model where water flow is represented as signal on graph and we introduce an algorithm, named GraphSmart, designed to reconstruct the graph signal when certain measurements are unknown or missing. Our framework is applied on synthetic realistic environment within the context of LoRaWAN (Long Range Wide Area Network), an infrastructure and protocol designed for ultra-low-power IoT devices. Our findings show that GraphSmart significantly reduces energy consumption while ensuring precise flow estimation. Our research demonstrates high potential for energy-efficient and accurate water flow monitoring, paving the way to improve the management of WDSs and enabling water operators to address water scarcity challenges.

Smart Irrigation Systems from Cyber–Physical Perspective: State of Art and Future Directions

Irrigation refers to supplying water to soil through pipes, pumps, and spraying systems to ensure even distribution across the field. In traditional farming or gardening, the setup and usage of an agricultural irrigation system solely rely on the personal experience of farmers. The Food and Agriculture Organization of the United Nations (UN) has projected that by 2030, developing countries will expand their irrigated areas by 34%, while water consumption will only be up 14%. This discrepancy highlights the importance of accurately monitoring water flow and volume rather than people’s rough estimations. The smart irrigation systems, a key subsystem of smart agriculture known as the cyber–physical system (CPS) in the agriculture domain, automate the administration of water flow, volume, and timing via using cutting-edge technologies, especially the Internet of Things (IoT) technology, to solve the challenges. This study explores a comprehensive three-dimensional problem space to thoroughly analyze the IoT’s applications in irrigation systems. Our framework encompasses several critical domains in smart irrigation systems. These domains include soil science, sensor technology, communication protocols, data analysis techniques, and the practical implementations of automated irrigation systems, such as remote monitoring, autonomous operation, and intelligent decision-making processes. Finally, we discuss a few challenges and outline future research directions in this promising field.

Long-Term Impacts of Glacier Retreat on Downstream Water Availability in Ethiopia

Purpose: The aim of the study was to examine Long-Term Impacts of Glacier Retreat on Downstream Water Availability in Ethiopia. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study revealed that as glaciers continue to shrink due to climate change, the hydrological systems in mountainous regions of Ethiopia, such as the Simien Mountains and Bale Mountains, face disruptions in water supply, affecting both local communities and downstream users. The reduction in glacial meltwater contributes to decreased streamflow, altered river regimes, and increased variability in water availability, exacerbating water stress in a country already prone to droughts and water scarcity. Moreover, glacier retreat affects ecosystems, biodiversity, and livelihoods dependent on freshwater resources, further amplifying socio-economic vulnerabilities in the region. Unique Contribution to Theory, Practice and Policy: Climate Change Theory, Hydrological Cycle Theory & Systems Theory may be used to anchor future studies on Long-Term Impacts of Glacier Retreat on Downstream Water Availability in Ethiopia. Implement cutting-edge technologies for real-time monitoring of glacier melt and downstream water flow. Use satellite imagery, remote sensing, and IoT sensors to gather data that can inform water management practices in real time. Develop and enforce policies that ensure sustainable water use and prioritize the maintenance of water quality and ecosystem health. This includes setting limits on water withdrawals based on sustainability criteria and enhancing the legal frameworks protecting water rights.

Bionic Fish-Shaped Triboelectric-Electromagnetic Hybrid Generator via a Two-Stage Swing Mechanism for Water Flow Energy Harvesting and Condition Monitoring.

The water flow energy of rivers is an important renewable and clean energy that plays a vital role in human life but is challenging to harvest at low flow velocity. This work proposes a bionic fish-shaped triboelectric-electromagnetic hybrid generator (BF-TEHG) via a two-stage swing mechanism for harvesting water flow energy. It is designed to simulate the shape of fish, effectively improving its ability to utilize low-velocity water flow energy and enabling it to operate at a minimum flow rate of 0.24 m/s. Furthermore, the impact of motion parameters on electrical performance is studied. The triboelectric and electromagnetic power-generation units can generate peak powers of 0.55 and 0.34 mW in the simulated river environments with a flow velocity of 0.98 m/s. In applications, after being immersed in water for 40 days, the BF-TEHG maintains its electrical performance without reduction, indicating excellent water immersion durability. Therefore, this work proposes an efficient strategy to harvest low-velocity water flow energy and provides an acceptable candidate for monitoring water flow conditions.

3D-Printed Artificial Cilia Arrays: A Versatile Tool for Customizable Mechanosensing.

Bio-inspired cilium-based mechanosensors offer a high level of responsiveness, making them suitable for a wide range of industrial, environmental, and biomedical applications. Despite great promise, the development of sensors with multifunctionality, scalability, customizability, and sensing linearity presents challenges due to the complex sensing mechanisms and fabrication methods involved. To this end, high-aspect-ratio polycaprolactone/graphene cilia structures with high conductivity, and facile fabrication are employed to address these challenges. For these 3D-printed structures, an "inter-cilium contact" sensing mechanism that enables the sensor to function akin to an on-off switch, significantly enhancing sensitivity and reducing ambiguity in detection, is proposed. The cilia structures exhibit high levels of customizability, including thickness, height, spacing, and arrangement, while maintaining mechanical robustness. The simplicity of the sensor design enables highly sensitive detection in diverse applications, encompassing airflow and water flow monitoring, braille detection, and debris recognition. Overall, the unique conductive cilia-based sensing mechanism that is proposed brings several advantages, advancing the development of multi-sensing capabilities and flexible electronic skin applications in smart robotics and human prosthetics.

Linking the uptake of best management practices on dairy farms to catchment water quality improvement over a 20-year period

Intensive land use, such as dairying, can impair water quality. Although many guidelines exist on how to mitigate the loss of dairy-associated contaminants from land to water through best management practices (BMPs), few datasets exist on the success of implementation on-farm. Five dairy-dominated catchments (from 598 to 2480 ha) in New Zealand were studied from 2001 to 2020. The first period, from 2001 to 2010, involved comprehensive “extension” advice to farmers consisting of workshops, stream water quality and flow monitoring, farm practice surveys, and identified solutions to address site-specific contaminant losses. In the second period (2011−2020), termed “post-extension”, only water quality monitoring and farm practice surveys were continued. Of the water quality contaminants (including dissolved reactive phosphorus (DRP), total phosphorus (TP), ammoniacal-nitrogen, nitrate-nitrite-nitrogen [NNN], suspended sediment and E. coli), 83 % of water quality trend directions were either improving (n = 16) or showed no change (n = 9) during the extension period. Over the 20-year dataset, which included the post-extension period, 20 out of 30 contaminant-catchment combinations (67 %) were improving, but nine were degrading, dominated by NNN (n = 4), DRP (n = 2) and E. coli (n = 2). Abrupt decreases in contaminant concentrations, were correlated with on-farm practice changes mainly associated with transition from direct discharge of farm dairy shed effluent to waterways to land application, and the capture of effluent from off-paddock facilities (like stand off or feed pads). Best management practices reduced phosphorus (P) forms, E. coli and sediment concentrations. Increase in NNN concentrations was caused by transitioning from flood to spray irrigation and a commensurate increase in cow numbers and NNN leaching. These data indicate that extension advice and on-farm practice change have helped to improve overall water quality over time. Nevertheless, recent regulatory threshold values for some contaminant concentrations are not being met, meaning that more actions are required, over and above the BMPs implemented.

Nutrient retention in tile‐fed and non‐tile reconstructed oxbows in north central Iowa

AbstractNutrient export from the agricultural Midwest threatens the Gulf of Mexico and new conservation practices are needed to reduce the loss of nutrient from subsurface tile drainage systems. Oxbows are natural waterbodies formed when a river cuts off a meander loop and water quality benefits of reconstructed oxbows are being increasingly recognized. In this study, we monitored four reconstructed oxbow sites (two tile‐fed, two non‐tile) over a 2‐year period in north‐central Iowa and assessed their capacity for NO3‐N and dissolved reactive phosphorus (DRP) reductions. Water flow and quality monitoring of tiles, shallow groundwater, oxbow and receiving streams documented that the oxbows were dominated by tile drainage inputs. NO3‐N concentrations were highest in the drainage tiles flowing into the tile‐fed oxbows (mean 8–10 mg/L) and much lower in floodplain groundwater (<1–2 mg/L). Annual NO3‐N loads into the tile‐fed oxbows were substantially larger than input loads into the non‐tiled oxbows. For the two tile‐fed oxbows, the 2‐year NO3‐N retention efficiencies were very similar (0.76–0.77) and on a monthly basis, greater retention efficiencies were measured in summer and fall. DRP concentrations and loads into the tile‐fed oxbows were too low to allow for meaningful estimates of retention. Reconstructing oxbows to receive tile drainage water should be considered a sustainable conservation practice for tile drainage treatment in agricultural areas.

Designing smart pulse flow meters using diversion analysis

<span lang="EN-US">The operation of modern housing infrastructure is characterized by a constant increase in the cost of the limited resources used. This necessitates the priority implementation in the concept of a smart home of elements aimed at resource saving and their rational management. The study provides an overview of the implementation architectures of the internet of things (IoT) concept in the construction of home automation systems and the requirements they impose on the implementation of smart primary meters of controlled physical quantities. Based on a diversion analysis, a promising smart water meter was developed. The prototype is ergonomic and has a structural form factor convenient for further integration. The designed model of the electronic module of the water flow monitoring system implements, in addition to typical tasks, additional functionality: transfer of recorded indicators and technical information to the cloud storage, warning the user about an emergency situation, accumulation of current data in non-volatile memory. It is possible to use the accumulated statistics for training the predictive analysis module. The proposed architecture option will allow creating energy-efficient elements of home automation systems in the future.</span>

Liquid‐Metal‐Based Stretchable Triboelectric Nanogenerators for Flowing‐Liquid‐Based Energy Harvesting and Self‐Powered Sensor Applications

AbstractIn this paper, a liquid‐metal‐based triboelectric nanogenerator (LM‐TENG) is proposed for harvesting energy from flowing water and self‐powered flow sensor applications. The proposed LM‐TENG mainly consists of a Galinstan working electrode that is encapsulated in a polydimethylsiloxane friction layer. The triboelectric performance of the LM‐TENG is optimized as a function of flow rate and frictional layer thickness. The output performance of the optimized LM‐TENG (6.2 V and 3.6 µA) is superior to that of the copper‐electrode‐based TENG (C‐TENG, 2.4 V and 0.8 µA) at the flow rate of 2.5 L min−1. This is because the stretchability of the optimized LM‐TENG is three times higher than that of the C‐TENG, which increases the contact area and enhances the output performance. The optimized LM‐TENG is successfully demonstrated as a self‐powered flow sensor for remote monitoring of water flow in pipelines. In addition, the LM‐TENG is a capable of powering more than 30 LEDs and directly powering low‐power electronics (LCDs).

Design and Fabrication of a Four-Electrodes PVDF Fiber for a Flow Sensor

Inspired by seal vibrissa, an ingenious bionic flow sensor, that had four electrodes and dual-sensing circuits, was designed and fabricated using polyvinylidene fluoride (PVDF) and optical fiber. Based on the piezoelectric equation, the sensing model of this bionic vibrissa sensor (BVS) was deduced. The BVS was thoroughly investigated for airflow and oscillatory water flow monitoring applications. The results indicated that the BVS had a faster response to airflow compared with the anemometer, and it could sense the direction and the magnitude of the airflow simultaneously. The BVS could recognize the frequencies, phases, and waveforms of the oscillatory water flow. The unique dual-sensing circuit and flexible characteristics endowed the BVS with excellent underwater sensing abilities. It exhibited a very low-velocity detection threshold (0.15 mm/s). It could accurately sense the flow speed and direction at the same time by measuring only once. The success of this study paves the way for extending this technology to many applications, such as underwater detection, water leak monitoring, and blood/urine flow monitoring.

Computer Vision Approach for Tile Drain Outflow Rate Estimation

HighlightsVision-based approach for detecting outlet flow of tile drains in a laboratory environment.Method accurately detects and estimates flow within 12% or less of ground truth flow rate.A real-time application was developed that provides estimated flow rates from collected video.Abstract. This article presents a computer vision-based approach for monitoring water flow at outlet points of a tile drain system. The approach relies only on video capture of events at outlet points, thus a camera can be installed remotely and without contact with water. The algorithm detects, identifies, and tracks flows by motion, shape, and color features and measures flow rate based on a proposed model and two provided dimensions. The software was tested in a laboratory environment with three different target flow rate conditions: 0.312, 0.946, and 1.58 L/s (5, 15, and 25 gal/min). Flow rates reported by the computer vision approach are within 12% of the ground-truth flow rate baseline. The results of this work show that computer vision can be used as a reliable method for monitoring outlet flows from free-standing outlet structures under laboratory conditions. This work opens the possibility of applying computer vision techniques in tile drain monitoring from outlet points with mobile video recording devices in the field. Keywords: Keywords., Morphological transformations, Outflow detection, Outlet flow, Real-time application.

A unified model for the permeability, electrical conductivity and streaming potential coupling coefficient in variably saturated fractured media

ABSTRACTWe present a new unified model for the permeability, electrical conductivity and streaming potential coupling coefficient in variably saturated fractured media. For those, we conceptualize the fractured medium as a partially saturated bundle of parallel capillary slits with varying sizes. We assume that the fracture size distribution of the corresponding medium follows a fractal scaling law, which allows us to establish a pressure head‐saturation relationship based on the Laplace equation. We first describe the flow rate, the conduction current and the electrokinetic streaming current within a single fracture. Then, we upscale these properties at the scale of an equivalent fractured media partially saturated in order to obtain the relative permeability, the electrical conductivity and the streaming potential coupling coefficient. The newly proposed model explicitly depends on pore water chemistry, interface properties, microstructural parameters of fractured media and water saturation. Model predictions are in good agreement with both experimental and simulated data and with another model from the literature. The results of this work constitute a useful framework to estimate hydraulic properties and monitor water flow in fractured media.

Breeding and conservation of Luciola cruciata Motschulsky, 1854 (Coleoptera: Lampyridae) larvae in forests near chemical factories

The number of fireflies in Japan has decreased with the development of cities and industries. As a first step toward the regeneration of an environment for fireflies, we report an attempt to breed aquatic firefly larvae. Focusing on the operational stability of equipment used, we use a safety evaluation method like that employed in petrochemical plants. The death of larvae is a major risk in the operational safety of firefly larvae breeding. The larval death scenario is analyzed and clarified using fault tree analysis, demonstrating that reducing operational mistakes in monitoring water flow and temperature conditions contribute most to the reduction of the probability of larval death. An experiment simulating water supply stoppage to estimate the permissible time for a response once the water temperature rose is reported. A firefly larval breeding system equipped with an alarm function for prompting emergency responses is constructed. Fireflies, including mature larvae, are successfully bred and the effectiveness of this system is demonstrated by comparing it with a conventional system. The superiority of the breeding system of this study is indicated by a twofold increase in the yield of mature larvae and the lower expenses related to this strategy.

A Low-Cost, Low-Power Water Velocity Sensor Utilizing Acoustic Doppler Measurement.

Current commercial sensors to monitor water flow velocities are expensive, bulky, and require significant effort to install. Low-cost sensors open the possibility of monitoring storm and waste water systems at a much greater spatial and temporal resolution without prohibitive costs and resource investment. To aid in this, this work developed a low-cost, low-power velocity sensor based on acoustic Doppler velocimetry. The sensor, costing less than 50 USD is open-source, open-hardware, compact, and easily interfaceable to a wide range of data-logging systems. A freely available sensor design at this price point does not currently exist, and its novelty is in enabling high-resolution real-time monitoring schemes. The design is capable of measuring water velocities up to 1200 mm/s. The sensor is characterised and then verified in an in-field long-term test. Finally, the data from this test are then used to evaluate the performance of the sensor in a real-world scenario. The analysis concludes that the sensor is capable of effectively measuring water velocity.

Monitoring of Water Flow in the Springs of the Golesh Massif, Kosovo

Monitoring of Water Flow in the Springs of the Golesh Massif, Kosovo

Application of critical path analysis to streaming potential coupling coefficient in porous media

Streaming potential is a passive hydrogeophysical method that can be used to monitor water flow in porous media. However, a quantitative use of this method requires a good understanding of the streaming potential generation in water saturated porous media. In this work, we used the Critical Path Analysis (CPA) method to propose a new model to estimate the streaming potential coupling coefficient (SPCC) in porous media. By comparing the proposed model with 109 experimental data points for both unconsolidated samples such as uniform glass bead and sand packs and consolidated samples such as sandstones, carbonates and with 36 simulated data points, we demonstrated that the CPA is applicable to model the SPCC for porous media with both narrow and broad pore size distributions. Additionally, from the obtained result for the uniform grain packings, we found the rc–d relationship between the critical pore radius rc and grain diameter d that was validated by using 70 experimental data points available in literature. The obtained rc–d relationship may be helpful for applications of CPA-based models for uniform grain packings. We believe that the CPA-based model is an useful alternative approach for modeling the streaming potential coupling coefficient in porous media along with two other models available in literature.

Intelligent water flow monitoring system based on internet of things for residential pipeline

Providing sustainable water supply is a huge challenge for Malaysia whereby the residential areas are still equipped with the conventional water meter with lack of monitoring options. In order to detect the locations of internal leakage, the process requires costly plumber service while manual comparison may be inaccurate and time-consuming. Therefore, digitalization transformation aligned with the industrial revolution IR 5.0 is crucial especially with the recent occurrences of high water bills reports during the movement control order (MCO). The objectives of this project is to develop an intelligent water flow monitoring system using Arduino as a microcontroller and to construct a system that can monitor the water usage behaviour at any distant with internet of thing (IoT). It can be installed anywhere in a pipeline whereby the water flow sensor measures the real-time water parameters. The data transferred to the cloud are sent to the homeowner to display the accuracy and availability of their water system via Blynk, a mobile-compatible and user-friendly application that generates clear data visualization. The key goal of this project is to provide a wireless, mobile, economical and systematic solution for residents to self-monitor their water consumption as compared to the conventional manual monitoring.

Measurement of the hydraulic properties of chalk using centrifuge permeameter; the study of chalk hydraulic properties under accelerated gravitational force

In this study, a geotechnical centrifuge has been used to study the unsaturated hydraulic properties of rock samples from the chalk aquifer, SE England. This method allows rapid measurement of hydraulic properties in a controlled environment, in contrast to previous studies on the chalk unsaturated zone, which required either an extended period (years) of data monitoring in the field or extended experimental periods (weeks) in the laboratory. Three types of specially built sensors were used to monitor water flow through chalk samples: a water pressure transducer to measure matric potential, frequency domain reflectometry probes to measure the volumetric water content and pressure transducers to measure the volume of water passing through the sample. Chalk samples were tested during wetting and draining processes to understand any hysteresis occurring during periodic recharge of the aquifer. Before undertaking physical tests of chalk samples in the centrifuge, a theoretical model of chalk hydraulic behaviour under centrifugal force was developed. This model was used to define and justify the instrumentation plan of the physical model and predict the shape of the soil moisture characteristic (SMC) curve and unsaturated hydraulic conductivity ( K u ) function. The results were then evaluated and compared with the experimental results. These results show that chalk samples can be successfully tested under centrifuge conditions and hydraulic properties can be measured, including soil moisture characteristic curves and hydraulic conductivity. Supplementary material: Calculation spread sheets are available at https://doi.org/10.17033/DATA.00000283

Dynamic Data-Driven Modelling of Water Allocation for the Internet of Things

The allocation of water resources is an important aspect of maintaining public security, but there are still many problems in water resources management. The application of IoT technology in water resources management mainly focuses on water quality detection and water flow monitoring. For the allocation of water resources, the application of the Internet of things technology is not deep and sufficient, and the advantages of the Internet of things technology in water resources management are not fully utilized. In view of the above problems in the current situation, this paper proposes solutions for smart water resources. Smart water resources combine geographic information technology and Internet of things technology to visualize a map of water resources and realize the whole process management from the source to the end user and automatic data collection and analysis. Therefore, an intelligent system with remote control function is constructed, which can be applied to the practice of water resources allocation and realize the full utilization of water resources.