Water Level Monitoring Research Articles

Intelligent system for measuring and monitoring water levels

Abstract Measuring and controlling water levels at water management facilities is one of the important tasks. In this research work, we, the authors, have studied the available means of measuring water level. Some of their drawbacks were brought to light throughout the investigation. For instance, if you take a water level control gauge, you have to keep an eye on it all the time, and automation is challenging. These water level measurement devices are not up to date with modern standards. At present, there is a need for systems for continuous monitoring of water resources, collection of necessary information and, if necessary, delivery of processed information to the user or decision-making in complex situations. Taking this into account, it was aimed to develop an intelligent system for measuring and controlling the water level that meets the requirements of the time. As the basis of the intelligent system, the JSN SR-04T ultrasound sensor, which is resistant to various aggressive conditions and has high measurement accuracy, and the Arduino Nano board were taken. This intelligent system was tested at the facility and the developed system performed all tasks reliably and qualitatively.

A Low-Cost Ultrasonic Sensor for Online Monitoring of Water Levels in Rivers and Channels

The measurement of flow parameters in rivers and channels is essential for anticipating floods, hydraulic modeling, and conducting water resource management studies. However, the high cost of existing equipment has resulted in a shortage of monitoring stations compared to actual requirements. This research focused on developing and validating a low-cost, highly accurate ultrasonic device that minimizes malfunctions for online monitoring of water levels in channels and streams. Considering the availability of components, cost, and the reported resolution of the product, the GY-Us42 sensor was selected for constructing the level gauge. The sensor operates within a range of 20 cm to 720 cm with a measurement accuracy of approximately 1 mm. The device integrates several error reduction mechanisms to enhance accuracy, including averaging multiple readings and temperature correction techniques. Laboratory data and field data gathered by both staff and shaft encoder were used for device validation. After constructing the main prototype and conducting various tests, multiple devices were installed in different locations within the Tehran rivers, and water depth data were collected over a specific period. Subsequently, data from other field sensors were also collected and used for device validation and accuracy assessment. The results indicate that the device's average error is below 3%, with a Root Mean Squared Error (RMSE) of 5.00 cm during field tests, demonstrates that the constructed device is an efficient tool for measuring water levels in streams, particularly during flood events.

Smart Sewage Management System

The Smart Sewage Management System introduces an innovative way to manage sewage flow on rural roads using IoT technology. It aims to detect excessive sewage discharge, which can harm the environment and public health. By focusing on monitoring drainage water levels in real-time, it addresses the common problem of drainage overflow in developing areas, where manual checks are slow and unreliable. The system uses a network of sensors that monitor water levels and send alerts to local authorities when levels get too high, allowing for quick action. Overall, this sewage management system not only helps protect the environment but also improves living conditions in rural communities.

IOT Based Waterproof System for Water Quality and Level Monitoring

Abstract: The Internet of Things (IoT) represents a significant advancement in the monitoring and management of environmental resources. This review explores the design and implementation of a waterproof IoT-based system for the remote monitoring of water quality and levels [2]. Water pollution, particularly in developing regions such as India, poses a substantial environmental threat, primarily driven by factors like untreated sewage, agricultural runoff, and industrial waste. Conventional approaches to monitoring water quality, which rely on physical sampling and laboratory testing, tend to be less efficient and often fail to deliver the prompt information required for effective resource management. To overcome these limitations, the proposed system utilizes waterproof IoT devices equipped with various sensors to continuously assess critical water quality parameters, including pH, turbidity [3], and pollutant levels. The collected data is transmitted in real time to a central monitoring unit, allowing for immediate assessment and timely interventions when quality thresholds are exceeded. This review emphasizes the innovations in sensor technology and communication protocols that enhance the efficiency and reliability of the monitoring system. Additionally, the paper addresses challenges such as sensor calibration, durability, and data transmission reliability in different environmental conditions. Solutions to these challenges are discussed to provide a comprehensive understanding of how to develop and maintain effective water quality monitoring systems. The review concludes by outlining future research directions aimed at improving system robustness and expanding its application across various water bodies, thereby contributing to enhanced water resource management and environmental sustainability [1].

A Study of the Drainage Capacity, Flood Risks and Mitigation Measures for Selected Areas in Guyana’s Coastal and Riverine Regions: Williamsburg- Hampshire, Kilcoy-Chesney and Mabaruma-Kumaka-Barabina

This research investigates the drainage challenges and flood risks in three areas of Guyana: Williamsburg-Hampshire, Kilcoy-Chesney, and Mabaruma-Kumaka-Barabina. These drainage areas are characterised by low-lying terrain, proximity to waterways, and inadequate drainage infrastructure. The study identifies how these factors lead to frequent and sometimes costly flooding, especially during periods of peak rainfall and high tides that prevent the opening of drainage sluices. Using rainfall and runoff data, with the analysis of drainage coefficients and discharge capacities, the study examines the existing drainage systems in these regions. It highlights the inefficiencies of undersized drainage structures, inadequate maintenance, and the growing pressure from urbanisation, which has led to the expansion of impervious surfaces, thus increasing runoff. In the case of Mabaruma-Kumaka-Barabina, under- maintained sluices, narrow bridge culverts, and low earthen dams exacerbate the area’s flood vulnerabilities. To address these issues, the study recommends several key interventions. These include upgrading drainage infrastructure by widening internal drains, replacing narrow culverts, installing additional sluices, and using modern technologies like automated pumps and self-actuated sluices. The construction of higher, vegetated embankments and raising the earthen river dams are also recommended to prevent erosion and overtopping during high tides. Monitoring water levels and rainfall data regularly is proposed to inform drainage maintenance and flood prevention efforts. The findings underscore the need for public-private partnerships to maintain drainage systems while engaging the community in flood risk mitigation. By implementing these recommendations, these regions can better manage water flow, reduce the impact of flooding, and improve the quality of life for residents, particularly as climate change continues to pose greater challenges for water management in Guyana.

First results of the wavelet-analysis of karst water levels from the Bükk Mnts.

During our research, we used long-term data measured by the Bükki Karst Water Level Monitoring System to subject them to a periodicity test based on statistical methods. The goal was to search for cyclic components in the data of karst water levels, water temperature and conductivity measurements, using the methodology of wavelet analysis to supplement traditional deterministic procedures. Based on the calculations, it was possible to detect several periods in the data series, we also detected several properties that are only characteristic of hot or cold karst wells. Cycles with a period of 1 year, 3 years, or even longer were detected at several measurement sites, and with the help of the method, we were also able to determine which cycles appeared in the time series, and whether there was a period when it was not detectable in the data series. During the wavelet coherence tests, we determined to what extent these cycles move together in the data series of the measuring points of the Bükk Mountains, and whether there is a case where one measuring point "leads" the other time series.

Determination of Average Water Demand and Diurnal Consumption Pattern for a Multifamily Apartment Complex in Peshawar

Abstract: Accurately estimating and understanding domestic water demand and consumption patterns is essential for the efficient planning and management of drinking water supply systems. Traditional methods for estimating water demand are labor-intensive and often rely on assumptions. To overcome these limitations, this study employed a novel approach using highprecision data loggers to monitor water levels continuously in rooftop tanks at 5-minute intervals within a residential apartment complex in Peshawar, Pakistan. The findings indicate that per capita water consumption varies between 97 and 209 liters per capita per day (lpcd), with an average consumption of 173 lpcd. This methodology offers enhanced accuracy in quantifying water usage, providing a robust alternative to conventional estimation techniques.

Intelligent IoT-Based Flood Monitoring and Alerting System using Raspberry Pi

Abstract: Floods are one of the most destructive natural disasters, causing significant loss of life and property. Early detection and timely intervention are crucial in mitigating the impacts of floods. The "Intelligent IoT-Based Flood Monitoring and Alerting System" is an innovative solution that leverages the power of the Internet of Things (IoT) to monitor water levels and predict potential flooding events. This system uses low-cost and easily accessible hardware such as a Raspberry Pi, sensors, LCD, buzzer and a cloud-based platform to provide real-time flood monitoring. The system continuously collects data on water levels, environmental conditions, and other relevant metrics, and processes this data to issue early warnings and alerts to local authorities and residents. Through an intuitive web interface, users can monitor flood-prone areas and receive notifications when water levels reach dangerous thresholds. The system aims to enhance disaster preparedness, reduce human and material losses, and improve the efficiency of flood management

Spatiotemporal variation of water level in wetlands based on multi-source remote sensing data and responses to changing environments

Under changing environmental conditions, water level is a crucial indicator for assessing the wetland hydrological cycle. However, due to some wetlands being located in remote and widely dispersed areas, acquiring data on wetland water level changes presents significant challenges, making wetland water level monitoring exceptionally difficult. Wetlands are extensively distributed in western Jilin Province, China, and are experiencing significant degradation due to various factors including natural conditions, agricultural activities, and social development. To address this challenge, this study proposes a monitoring method that combines Sentinel-3 radar altimetry satellites with optical remote sensing images to obtain wetland water level data. Additionally, the study takes into account the Chinese government's Interconnected River System Network Project (IRSNP), classifying wetlands in western Jilin Province into three different water recharge scenarios: direct recharge through main and branch canals, indirect recharge through ditches, and no recharge to isolated wetlands. This study analyses the relationship between wetland water level changes and climatic factors, and assesses how IRSNP can mitigate the negative impacts of climate factors on wetland water levels across different recharge scenarios. The results show that: (1) the wetland water level monitoring method, has high accuracy and feasibility. The average difference between the in-situ measured and satellite-monitored water levels was 0.254 m. (2) There was an overall increasing trend in wetland water levels directly influenced by IRSNP, an insignificant decreasing trend in wetland water levels indirectly influenced by IRSNP. (3) Increased precipitation and decreased evaporation are the predominant climatic factors contributing to rising wetland water levels. Conversely, lower relative humidity and higher temperatures primarily lead to declining water levels. The construction of IRSNP can mitigate the impact of climate change on water levels. Thus, under changing environmental conditions, the implementation of IRSNP has positively impacted wetland protection and provides valuable insights for understanding wetland water level changes and managing water resources effectively.

Design and Development of a Prototype Water Level Control System for Early Flood Detection Based on The Internet of Things: a Case Study of Kambaniru Dam

Flooding can occur due to overflowing water during the rainy season, therefore early detection of the water level in dams as water runoff processing structures is needed. When heavy rain occurs it can result in flood disasters that are detrimental to communities, dam infrastructure and agricultural land. This research aims to monitor water levels online as initial information about impending flood disasters. Monitoring using Internet of Things (IoT) based technology is intended to obtain water level information in real time. In this device the HC-SR04 ultrasonic sensor is used as a water level reader, a waterflow sensor as a water discharge reader and a servo motor as a sluice gate controller. The results of this research are a prototype of a water level detection device that can provide water level information and can control sluice gates. automatically and can be controlled manually or remotely via the latest notifications in the Blynk application using the MQTT protocol. This research was carried out by taking information based on the results of direct observations and interviews with officers at Kambaniru Dam, Lambanapu Village, Kambera District. In this way, the prototype of this detection tool will be easy to use as initial information about the possibility of flooding.

SPLIT DUCT AC LEAKAGE MONITORING SYSTEM VIA GOOGLE SHEETS

General Background: Split duct air conditioners are prone to leaks, often resulting from corrosion in water catchment systems, which can lead to significant operational hazards such as electrical fires. Specific Background: Given the prevalence of these issues, there is an urgent need for effective monitoring solutions to maintain optimal air conditioner performance and prevent leaks. Knowledge Gap: Current monitoring systems lack integration with real-time data reporting mechanisms that can alert users promptly to potential issues. Aims: This research aims to develop a monitoring device utilizing NodeMCU ESP8266, water level sensors, and Google Sheets to enable real-time monitoring and management of water levels in split duct air conditioners. Results: The device successfully operates by turning on the fan when water levels are below 2 cm and activating the pump when levels exceed this threshold. The data is continuously sent to Google Sheets, allowing for easy monitoring and management. Novelty: This study presents a novel approach to air conditioner leak monitoring by integrating IoT technology, offering an efficient and user-friendly solution for residents. Implications: The developed monitoring tool significantly enhances the ability to detect and manage potential leaks in real time, thereby improving safety and operational efficiency. Future research should focus on enhancing sensor accuracy through specialized equipment and exploring alternative IoT platforms for improved data visualization, thereby providing users with an even more effective monitoring experience.

Design and Implementation of an IoT-Based Water Level Monitoring System with Automated Pump Control and Real-Time Notifications

Design and Implementation of an IoT-Based Water Level Monitoring System with Automated Pump Control and Real-Time Notifications

Cloud computing and spatial hydrology for monitoring the Buyo and Kossou reservoirs in Côte d'Ivoire

The Buyo and Kossou reservoirs are crucial for water supply, agricultural irrigation, and hydroelectric power generation in Côte d'Ivoire. However, climate change threatens the stability and availability of these water resources by increasing rainfall variability, extending drought periods, and intensifying extreme weather events. These challenges underscore the need for precise and continuous monitoring of water levels and surface areas to ensure sustainable management. Due to the scarcity of gauging stations, the objective of this study is to leverage cloud computing technologies along with altimetric and satellite data, for effective reservoir monitoring. Tools like the EO-Africa program's Innovation Lab and Google Earth Engine (GEE), along with advanced image processing software such as PyGEE-SWToolbox and AlTis, were used to process large datasets from the Sentinel-1, Sentinel-2, and Sentinel-3 satellites. These satellites delivered extensive, high-resolution imagery and altimetric data, crucial for monitoring changes in the reservoirs. The processed data were validated with in-situ measurements, yielding a Root Mean Square Error (RMSE) of less than 0.4 m and a correlation coefficient exceeding 0.90. The results highlighted water surface and level changes from 2016 to 2022, with downward trends and seasonal variations closely aligning with in-situ measurements. The study also revealed that the relationship between water levels and surface areas is influenced by both precipitation and the hydrological regimes of the Bandama and Sassandra rivers, demonstrating the complexity of water dynamics in these reservoirs. This research emphasizes the effectiveness of integrating spatial hydrology with cloud computing tools for fast and accurate monitoring of large reservoir. The use of these advanced technologies provides near real-time, reliable, and easily accessible data, offering a significant advantage for water resource management in Côte d'Ivoire.

418 Evaluation of an automated system for measuring individual animal water consumption

Abstract SmartWater is an automatic watering station that measures the volume of water consumed by individual animals when visiting the system. The self-contained, portable system is constructed of a steel frame, two load cells, and a stainless-steel water trough that measures 0.1 m3 with a water capacity of 113 L. SmartWater refills automatically when the water mass is below 55 L, refilling for 120 s, or until the water mass reaches 70 L. The flow rate of water entering the system and the weight of the bin are measured every second in L/s and L, respectively. When the bin is being refilled, animals are still able to drink from the system. Animal water intake during a visit is measured by summing the amount of water dispensed into the bin and the difference in bin weight at the start and end of the visit. Water intake days are considered valid if the unknown percentage is less than 5% of the total daily water intake, where unknown intake is defined as feed mass disappearance that cannot be assigned to an EID. Invalid days are excluded from final datasets. System performance was evaluated using 17 Angus heifers (body weight = 248 ± 37 kg) in a 55-d trial period. Animals were given ad libitum access to two SmartWater systems, and all animals successfully adapted to the system. Mean daily visitation was 2.7 ± 0.4 and average visit length was 87 ± 175 s. Mean water consumption over the trial period was 13.7 ± 1.8 L. The coefficient of variance of water consumption between animals was 12.8%. The average standard deviation water consumption within animals between days was 5.9%. SmartWater provides an accurate and efficient way to measure water intake of animals in extensive and intensive systems, eliminating the need to manually monitor water levels and refill watering stations.

IoT based Smart Weather Monitoring with Flood and Earthquake Detection

Weather monitoring is essential for understanding the changing climatic conditions. Traditional weather monitoring system are slow, labor intensive, and outdated, often prone to error and inaccurate predictions. To overcome these challenges and provide an up-to date weather information, the IoT (Internet of Things) has been implemented in weather monitoring. This research presents an IoT-based weather monitoring system integrated with sensors to ensure accurate weather monitoring, including flood and earth quake detection. The collected data, such as temperature, humidity, atmospheric pressure, rainfall, flood levels, and seismic activity, is transmitted through IoT protocols to a centralized repository (Cloud) and visualized in the Blynk App. Flood sensors are strategically positioned in flood-prone areas, continuously monitoring water levels to detect abnormal rises indicative of potential floods. Similarly, seismic sensors detect ground vibrations and seismic activity, providing early alerts for earthquakes. The proposed system offers a comprehensive approach to monitor the weather, contributing to enhanced preparedness and mitigation strategies for natural disasters.

Internet of Things (IoT) Driven Water Management System for Efficient Level Control

Water is an essential and valuable resource in daily life, making its conservation crucial to prevent adverse effects. Storing water for domestic, industrial, agricultural, and other purposes is particularly important. Safe drinking water is increasingly becoming polluted due to the growing population and their demands for urbanization and industrialization. At the household level, some people leave electric water pumps running and either go to work or sleep, forgetting to turn off the pumps when the water container is full. This highlights the need for a reliable and continuous water supply. IoT plays a significant role in environmental monitoring, particularly in disaster management, early warning systems, and environmental data analytics. One major challenge in urban cities is water management, especially with the rapid growth of urbanization, necessitating sustainable urban development plans. To address these issues, we propose a "Water Level Monitoring System" solution. This paper presents an IoT-based water monitoring system for real-time applications. The system's sensors measure the water level in the tank, and the data is sent to a cloud server, allowing users to view it on a remote dashboard. This system can be used efficiently by both homeowners and industrial users, as well as other water utilities.

Coupled and radiated microwave sensors for vital signs and lung water level monitoring

This paper presents a novel approach for non-invasive monitoring of vital signs (heart rate (HR), respiration rate (RR)) and lung water levels using ultra-wideband (UWB) microwave sensors. The primary contribution of this study is the development and testing of two different sensor technologies to enhance the penetration and monitoring capabilities of electromagnetic waves within the human body. The first sensor technology employs a radiated UWB microwave that can be integrated into textiles, operating within a frequency range of 1.5 to 10 GHz, providing flexibility and comfort for wearable health monitoring. The second sensor technology involves using body-coupled UWB non-radiating sensors with a wide operational bandwidth from 1.3 to 10 GHz and a stable feeding structure, ensuring efficient reflection and transmission of waves for accurate monitoring. The shapes of flexible and textile UWB electromagnetic microwave sensor radiators and couplers, along with the measurement procedure, are tested in human clinical studies. The sensor-specific absorption rate (SAR) is evaluated at two distinct resonant frequencies on tissue masses of 1 g and 10 g, aligning with the IEEE C95.3 standard to ensure adherence to standard thresholds of 1.6 W/kg and 2 W/kg, respectively. Additionally, a denoising scheme utilizing deep learning techniques is proposed to filter Base Line Wander (BLW) noise attributable to misplaced electrodes, skin impedance, poor skin preparation, patient movement, and breathing within the frequency range of 0.05 to 3 Hz. The postprocessing outcome demonstrates the superiority of couplers over radiating sensors.

Enhancing Rice Cultivation Efficiency in Tidal Lowland of Delta Saleh, Indonesia: Precision Farming Practices for Water Management and Soil Health Improvement

Tidal lowland is a marginal land characterized by low pH, deficient nutrients, and salinity. Despite these challenges, El Niño phenomenon often occurs during the second planting season, resulting in long droughts. However, tidal lowland must be used for cultivation due to the need for rice and the land should be treated accurately. Therefore, this research aimed to address the issues by improving the efficiency of rice cultivation on tidal lowland through precision farming practices. A survey and land analysis were conducted in tidal lowland of B typology in Delta Saleh, Indonesia, from March 2023 to June 2023. In this precision farming practice, water management was highly prioritized, starting from tertiary channels such as optimizing sluice gate operations and monitoring water levels in channels and groundwater. Additionally, pH, CEC, and C-Organic analysis were also carried out in rice cultivation, as showed by the equation Y = 0.15 - 0.001 pH + 0.000 CEC + 0.000 C-Organic. The highest production yield was 2.05 tons/ha in P5, with the SEW-10 value during cultivation activities being 778 cm and the number of days above -10 reaching 84. Moreover, the efficiency of rice cultivation was improved through precision agricultural practices by using valve sluices and levees.

Enhancing Rice Cultivation Efficiency in Tidal Lowland of Delta Saleh, Indonesia: Precision Farming Practices for Water Management and Soil Health Improvement

Tidal lowland is a marginal land characterized by low pH, deficient nutrients, and salinity. Despite these challenges, El Niño phenomenon often occurs during the second planting season, resulting in long droughts. However, tidal lowland must be used for cultivation due to the need for rice and the land should be treated accurately. Therefore, this research aimed to address the issues by improving the efficiency of rice cultivation on tidal lowland through precision farming practices. A survey and land analysis were conducted in tidal lowland of B typology in Delta Saleh, Indonesia, from March 2023 to June 2023. In this precision farming practice, water management was highly prioritized, starting from tertiary channels such as optimizing sluice gate operations and monitoring water levels in channels and groundwater. Additionally, pH, CEC, and C-Organic analysis were also carried out in rice cultivation, as showed by the equation Y = 0.15 - 0.001 pH + 0.000 CEC + 0.000 C-Organic. The highest production yield was 2.05 tons/ha in P5, with the SEW-10 value during cultivation activities being 778 cm and the number of days above -10 reaching 84. Moreover, the efficiency of rice cultivation was improved through precision agricultural practices by using valve sluices and levees.

Perbandingan Metode Kalibrasi Sistem Celup Dan Chamber Untuk Vibrating Wire Piezometer In Situ

Piezometers are geotechnical monitoring instruments commonly used to obtain pore water pressure or groundwater level values. The most popular piezometer is the electric type (vibrating wire). The way this type of piezometer works is that the pore water pressure acting on the diaphragm causes a change in voltage and resonance on the vibrating wire. From the resonance of the vibrating wire will issue a frequency that will be recorded by the reading unit. This change in water force will affect the magnitude of the frequency read in the reading unit. In addition, seepage patterns, possible piping zones, and the effectiveness of seepage control used can be evaluated with the help of this tool. Currently piezometers are widely used for Monitoring embankment stability and safety, Measuring water load behind retaining walls, Assessing soil consolidation, Measurement of uplift pressure acting on structural foundations, Verification of seepage patterns and models, Monitoring slope stability, Monitoring water levels for environmental control, Assessment of tidal influence, Pump testing. Due to the importance of these instruments and their high sensitivity, it is necessary to calibrate them before installation to ensure that the equipment functions properly and accurately. Some methods of conducting in-situ calibration that are often used are the dip method and the pressurized chamber or cell method. This study will compare the two methods to determine the accuracy of the calibration implementation that can be used as a consideration for the acceptance of instruments from certain manufacturers. Based on the research that has been done, calibration with the chamber method is more accurate and acceptable after analysis. Because in its implementation it can be more thorough and there is not much external disturbance as in the dip method calibration method carried out in lakes or reservoirs where there is a lot of external disturbance.