<i>Anticipatory defence for agricultural drought forecasting and warning system using a real time water-level</i>

2019 ◽  
Author(s):  
Jong-Won Do ◽  
Bo-Sung Koh ◽  
Kwang-Ya Lee ◽  
Tae-Hyun Ha ◽  
Seung-Yong Lee ◽  
...  
Keyword(s):  
Water Level ◽  
Real Time ◽  
Warning System ◽  
Agricultural Drought ◽  
Drought Forecasting ◽  
Forecasting And Warning

scholarly journals Flood Forecasting and Warning System Structures: Procedure and Application to a Small Urban Stream in South Korea

Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1571 ◽  
Author(s):  
Song ◽  
Park ◽  
Lee ◽  
Park ◽  
Song
Keyword(s):  
Decision Making ◽  
Water Level ◽  
Real Time ◽  
Lead Time ◽  
Flash Flood ◽  
Warning System ◽  
Flood Forecasting ◽  
Urban Stream ◽  
Forecasting And Warning ◽  
Flood Warnings

The runoff from heavy rainfall reaches urban streams quickly, causing them to rise rapidly. It is therefore of great importance to provide sufficient lead time for evacuation planning and decision making. An efficient flood forecasting and warning method is crucial for ensuring adequate lead time. With this objective, this paper proposes an analysis method for a flood forecasting and warning system, and establishes the criteria for issuing urban-stream flash flood warnings based on the amount of rainfall to allow sufficient lead time. The proposed methodology is a nonstructural approach to flood prediction and risk reduction. It considers water level fluctuations during a rainfall event and estimates the upstream (alert point) and downstream (confluence) water levels for water level analysis based on the rainfall intensity and duration. We also investigate the rainfall/runoff and flow rate/water level relationships using the Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) and the HEC’s River Analysis System (HEC-RAS) models, respectively, and estimate the rainfall threshold for issuing flash flood warnings depending on the backwater state based on actual watershed conditions. We present a methodology for issuing flash flood warnings at a critical point by considering the effects of fluctuations in various backwater conditions in real time, which will provide practical support for decision making by disaster protection workers. The results are compared with real-time water level observations of the Dorim Stream. Finally, we verify the validity of the flash flood warning criteria by comparing the predicted values with the observed values and performing validity analysis.

scholarly journals Design and Implementation of Real-Time Flood Early Warning System (FEWS) Based on IoT Blynk Application

ELKHA ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 113
Author(s):  
Hasbi Nur Prasetyo Wisudawan
Keyword(s):  
Water Level ◽  
Real Time ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Disaster Risk ◽  
Disaster Mitigation ◽  
Average Temperature ◽  
Flood Warning ◽  
Flood Warning System

Disaster occurrence in Indonesia needs attention and role from all parties including the community to reduce the risks.  Disaster mitigation is one of the ways to reduce the disaster risk through awareness, capacity building, and the development of physical facilities, for example by applying disaster mitigation technology (early warning system, EWS). EWS is one of the effective methods to minimize losses due to disasters by providing warning based on certain parameters for disasters which usually occur such as floods. This research promotes a real-time IoT-based EWS flood warning system (Flood Early Warning System, FEWS) using Arduino and Blynk as well as Global System for Mobile Communication network (GSM) as the communication medium. The steps for implementing FEWS system in real locations are also discussed in this paper. Parameters such as water level, temperature, and humidity as well as rain conditions that are read by the EWS sensor can be accessed in real-time by using android based Blynk application that has been created. The result of the measurement of average temperature, humidity, and water level were 28.6 oC, 63.7 %, and 54.5 cm. Based on this analysis, the parameters indicated that the water level is in normal condition and there are no signs indicating that there will be flooding in the 30 days observation.  Based on the data collected by the sensor, FEWS can report four conditions, namely Normal, Waspada Banjir (Advisory), Siaga Banjir (Watch), and Awas Banjir (Warning) that will be sent immediately to the Blynk FEWS application user that has been created.

Development and Testing of a Low-cost Water Level Sensor and a Mobile based Real-time Flood Warning System for the Flash Flood Prone North Eastern part of Bangladesh

2020 ◽  
Vol 10 ◽  
Author(s):  
Nova Ahmed ◽  
Md. Sirajul Islam ◽  
Sifat Kalam ◽  
Farzana Islam ◽  
Nabila Chowdhury ◽  
...  
Keyword(s):  
Water Level ◽  
Real Time ◽  
Flash Flood ◽  
Low Cost ◽  
Warning System ◽  
Outdoor Environment ◽  
Flood Warning ◽  
North Eastern ◽  
Flood Warning System ◽  
North Eastern Part

Background: The North-Eastern part of Bangladesh is suffering from flash flood very frequently, causing colossal damage to life and properties, especially the vast croplands. A distributed sensing system can monitor the water level on a continuous basis to warn people near the riverbank beforehand and reduce the damage largely. However, the required communication infrastructure is not available in most of the remote rural areas in a developing country like Bangladesh. Objective: This study intends to develop a low-cost sensor based warning system, customizing to the Bangladesh context. Method: The system utilizes a low-cost ultrasound based sensor device, a lightweight mobile phone based server, low-cost IoT sensing nodes, and a central server for continuous monitoring of river stage data along with the provision of storage and long-term data analytics. Results: A flash flood warning system developed afterward with the sensors, mobile-based server, and appropriate webbased interfaces. The device was tested for some environmental conditions in the lab and deployed it later in the outdoor conditions for short-term periods. Conclusion: Overall, the warning system performed well in the lab as well as the outdoor environment, with the ability to detect water level at reasonable accuracy and transmit data to the server in real time. Some minor shortcomings still noted with the scope for improvements, which are in the way to improve further.

scholarly journals A Wireless Smart Sensor Network for Flood Management Optimization

2017 ◽  
Vol 4 (1) ◽  
pp. 36-42
Author(s):  
Hossam Adden Alfarra ◽  
Mohammed Hayyan Alsibai
Keyword(s):  
Water Level ◽  
Real Time ◽  
Sensor Network ◽  
Warning System ◽  
Flood Management ◽  
Base Station ◽  
Risk Level ◽  
Size Analysis ◽  
Smart Sensor ◽  
Flood Warning

Recent development in the sensing technologies and wireless sensor networks has encouraged many innovative applications in disaster management and forecasting. Flood is one of the most dangerous natural disasters that occurs frequently in south Asia. Therefore, water level monitoring and flood early prediction, play an important role in lives and properties saving. In this paper, an optimized Flood Warning System (FWS) is presented. The system is based on multi parameters Wireless Smart Sensor Network (WSSN) for early flood warning. WSSN performs pre-processing procedures at sensor level before sending the data to a base data analyzing station. This pre-processing step is to improve the reliability, data quality and transmission quality. For the purpose of validation, the proposed method is applied using two parameters: The water level (L) and streamflow of water (R) in rivers. The proposed system provides early flood detection by continuously measuring R and L in real-time. The collected data is to be used to predict flood time and place. Data is exchanged among sensors in real-time. Pre-analyzing is performed and reports are sent to the base station only if the analysis gave a high risk level. The main purpose is to cut down the data size. Analysis and simulation showed that the data size is improved significantly using this method. Calculations considers real cases on a part of Pahang River (Sungai Pahang).

Web-Based Surface Level Measuring System Employing Ultrasonic Sensors and GSM/GPRS-Based Communication

2015 ◽  
Vol 771 ◽  
pp. 92-95 ◽  
Author(s):  
Muhammad Miftahul Munir ◽  
Rahmat Awaludin Salam ◽  
Eko Widiatmoko ◽  
Yundi Supriadani ◽  
Andri Rahmadhani ◽  
...  
Keyword(s):  
Water Level ◽  
Real Time ◽  
Early Warning ◽  
Early Warning System ◽  
Water Surface ◽  
Warning System ◽  
Water Levels ◽  
Measuring System ◽  
Web Based ◽  
Surface Level

Water surface level should get special attention as water can cause disasters such as flood when its surface exceeds a certain level. A real time early warning system to monitor water surface level is necessary for avoiding severe effects of flood to human life. A web-based water level measuring system using an ultrasonic sensor can be an alternative choice for developing the early warning system. It is known that the system has advantages in the installation and maintenance compared to other systems. This paper discusses the design of a water level measuring system integrated with an internet web server. Ultrasonic sensors are used to measure the water surface level. A GSM / GPRS-based communication system is applied for sending measured water levels to a web server. The results indicate that the measurement data are in accordance with the water levels manually obtained. The results also show that the system works real time.

scholarly journals Integrated Flood Forecasting and Warning System against Flash Rainfall in the Small-Scaled Urban Stream

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 971
Author(s):  
Jung Hwan Lee ◽  
Gi Moon Yuk ◽  
Hyeon Tae Moon ◽  
Young-Il Moon
Keyword(s):  
Water Level ◽  
Urban Areas ◽  
Warning System ◽  
Flood Forecasting ◽  
Urban Stream ◽  
Lead Times ◽  
Short Term ◽  
Inland River ◽  
Prediction Module ◽  
Forecasting And Warning

The flood forecasting and warning system enable an advanced warning of flash floods and inundation depths for disseminating alarms in urban areas. Therefore, in this study, we developed an integrated flood forecasting and warning system combined inland-river that systematized technology to quantify flood risk and flood forecasting in urban areas. LSTM was used to predict the stream depth in the short-term inundation prediction. Moreover, rainfall prediction by radar data, a rainfall-runoff model combined inland-river by coupled SWMM and HEC-RAS, automatic simplification module of drainage networks, automatic calibration module of SWMM parameter by Dynamically Dimensioned Search (DDS) algorithm, and 2-dimension inundation database were used in very short-term inundation prediction to warn and convey the flood-related data and information to communities. The proposed system presented better forecasting results compared to the Seoul integrated disaster prevention system. It can provide an accurate water level for 30 min to 90 min lead times in the short-term inundation prediction module. And the very short-term inundation prediction module can provide water level across a stream for 10 min to 60 min lead times using forecasting rainfall by radar as well as inundation risk areas. In conclusion, the proposed modules were expected to be useful to support inundation forecasting and warning systems.

AUTOMATIC WATER LEVEL MONITORING WITH IOT AND LPWAN

2019 ◽  
pp. 95-103
Author(s):  
Krum Videnov ◽  
Vanya Stoykova
Keyword(s):  
Water Level ◽  
Real Time ◽  
Early Warning ◽  
Water Sources ◽  
Water Levels ◽  
Water Level Fluctuations ◽  
Level Monitoring ◽  
Water Level Monitoring

Monitoring water levels of lakes, streams, rivers and other water basins is of essential importance and is a popular measurement for a number of different industries and organisations. Remote water level monitoring helps to provide an early warning feature by sending advance alerts when the water level is increased (reaches a certain threshold). The purpose of this report is to present an affordable solution for measuring water levels in water sources using IoT and LPWAN. The assembled system enables recording of water level fluctuations in real time and storing the collected data on a remote database through LoRaWAN for further processing and analysis.

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