Development of Typhoon disaster risk evaluation and early warning system integrating real-time rainfall data from the satellite

2011 ◽  
Author(s):  
Liwei Xing ◽  
Deyong Hu ◽  
Lili Tang
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Early Warning System ◽  
Risk Evaluation ◽  
Warning System ◽  
Disaster Risk ◽  
Rainfall Data ◽  
Typhoon Disaster

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.

scholarly journals Technical Note: An operational landslide early warning system at regional scale based on space–time-variable rainfall thresholds

2015 ◽  
Vol 15 (4) ◽  
pp. 853-861 ◽  
Author(s):  
S. Segoni ◽  
A. Battistini ◽  
G. Rossi ◽  
A. Rosi ◽  
D. Lagomarsino ◽  
...  
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Rainfall Event ◽  
Rainfall Data ◽  
Limited Area ◽  
Rainfall Thresholds ◽  
Rain Gauges ◽  
Starting Time

Abstract. We set up an early warning system for rainfall-induced landslides in Tuscany (23 000 km2). The system is based on a set of state-of-the-art intensity–duration rainfall thresholds (Segoni et al., 2014b) and makes use of LAMI (Limited Area Model Italy) rainfall forecasts and real-time rainfall data provided by an automated network of more than 300 rain gauges. The system was implemented in a WebGIS to ease the operational use in civil protection procedures: it is simple and intuitive to consult, and it provides different outputs. When switching among different views, the system is able to focus both on monitoring of real-time data and on forecasting at different lead times up to 48 h. Moreover, the system can switch between a basic data view where a synoptic scenario of the hazard can be shown all over the region and a more in-depth view were the rainfall path of rain gauges can be displayed and constantly compared with rainfall thresholds. To better account for the variability of the geomorphological and meteorological settings encountered in Tuscany, the region is subdivided into 25 alert zones, each provided with a specific threshold. The warning system reflects this subdivision: using a network of more than 300 rain gauges, it allows for the monitoring of each alert zone separately so that warnings can be issued independently. An important feature of the warning system is that the visualization of the thresholds in the WebGIS interface may vary in time depending on when the starting time of the rainfall event is set. The starting time of the rainfall event is considered as a variable by the early warning system: whenever new rainfall data are available, a recursive algorithm identifies the starting time for which the rainfall path is closest to or overcomes the threshold. This is considered the most hazardous condition, and it is displayed by the WebGIS interface. The early warning system is used to forecast and monitor the landslide hazard in the whole region, providing specific alert levels for 25 distinct alert zones. In addition, the system can be used to gather, analyze, display, explore, interpret and store rainfall data, thus representing a potential support to both decision makers and scientists.

scholarly journals Technical Note: An operational landslide early warning system at regional scale based on space–time variable rainfall thresholds

2014 ◽  
Vol 2 (10) ◽  
pp. 6599-6622 ◽  
Author(s):  
S. Segoni ◽  
A. Battistini ◽  
G. Rossi ◽  
A. Rosi ◽  
D. Lagomarsino ◽  
...  
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Early Warning System ◽  
Recursive Algorithm ◽  
Regional Scale ◽  
Warning System ◽  
Rainfall Data ◽  
Critical Threshold ◽  
Rainfall Thresholds ◽  
Rain Gauges

Abstract. We set up an early warning system for rainfall-induced landslides in Tuscany (23 000 km2). The system is based on a set of state-of-the-art intensity-duration rainfall thresholds (Segoni et al., 2014b), makes use of LAMI rainfall forecasts and real-time rainfall data provided by an automated network of more than 300 rain-gauges. The system was implemented in a WebGIS to ease the operational use in civil protection procedures: it is simple and intuitive to consult and it provides different outputs. Switching among different views, the system is able to focus both on monitoring of real time data and on forecasting at different lead times up to 48 h. Moreover, the system can switch between a very straightforward view where a synoptic scenario of the hazard can be shown all over the region and a more in-depth view were the rainfall path of rain-gauges can be displayed and constantly compared with rainfall thresholds. To better account for the high spatial variability of the physical features, which affects the relationship between rainfall and landslides, the region is subdivided into 25 alert zones, each provided with a specific threshold. The warning system reflects this subdivision: using a network of 332 rain gauges, it allows monitoring each alert zone separately and warnings can be issued independently from an alert zone to another. An important feature of the warning system is the use of thresholds that may vary in time adapting at the conditions of the rainfall path recorded by the rain-gauges. Depending on when the starting time of the rainfall event is set, the comparison with the threshold may produce different outcomes. Therefore, a recursive algorithm was developed to check and compare with the thresholds all possible starting times, highlighting the worst scenario and showing in the WebGIS interface at what time and how much the rainfall path has exceeded or will exceed the most critical threshold. Besides forecasting and monitoring the hazard scenario over the whole region with hazard levels differentiated for 25 distinct alert zones, the system can be used to gather, analyze, visualize, explore, interpret and store rainfall data, thus representing a potential support to both decision makers and scientists.

A Reliability-Based Early Warning System for Real-Time Monitoring on RC Buildings

2012 ◽  
Vol 446-449 ◽  
pp. 3422-3427
Author(s):  
Wang Sheng Liu ◽  
Ming Zhao
Keyword(s):  
Probability Distribution ◽  
Real Time ◽  
Early Warning ◽  
Early Warning System ◽  
Limit State ◽  
Warning System ◽  
State Function ◽  
Real Time Monitoring ◽  
Rc Buildings ◽  
Load Effect

Today there is an urgent need for effective monitoring whether for old buildings or new ones. While conventional early warning system for real-time monitoring is based on safety factor, this paper proposes a new reliability-based framework to monitor the safety of RC buildings probabilistically. The framework includes modeling resistance, predicting probability distribution of load effect, calculating reliability and setting reliability index threshold. The in-situ test data enables to update the resistance model through a Bayesian process. Meanwhile, the observed monitoring data predicts the probability distribution of load effect. FORM is used to calculate the reliability because the limit state function for real-time monitoring is linear and simple. This study shows that the reliability-based early warning system is of more scientific sense in quantifying the safety and may be applied to many engineering fields.

scholarly journals Design of Early Warning System Based on Wireless Sensor Network

2018 ◽  
Vol 14 (01) ◽  
pp. 66
Author(s):  
Gan Bo ◽  
Jin Shan
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Monitoring System ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Sensor Data ◽  
Landslide Monitoring ◽  
Remote Transmission ◽  
Sensor Data Acquisition

In order to solve the shortcomings of the landslide monitoring technology method, a set of landslides monitoring and early warning system is designed. It can achieve real-time sensor data acquisition, remote transmission and query display. In addition, aiming at the harsh environment of landslide monitoring and the performance requirements of the monitoring system, an improved minimum hop routing protocol is proposed. It can reduce network energy consumption, enhance network robustness, and improve node layout and networking flexibility. In order to realize the remote transmission of data, GPRS wireless communication is used to transmit monitoring data. Combined with remote monitoring center, real-time data display, query, preservation and landslide warning and prediction are realized. The results show that the sensor data acquisition system is accurate, the system is stable, and the node network is flexible. Therefore, the monitoring system has a good use value.

scholarly journals RISIKO KAWASAN LONGSOR DALAM UPAYA MITIGASI BENCANA MENGGUNAKAN SISTEM INFORMASI GEOGRAFIS

Pondasi ◽  
2019 ◽  
Vol 24 (1) ◽  
pp. 67
Author(s):  
Fakhryza Nabila Hamida ◽  
Hasti Widyasamratri
Keyword(s):  
Land Use ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Disaster Risk ◽  
Risk Mapping ◽  
Disaster Mitigation ◽  
Accurate Information ◽  
Loss Of Life ◽  
Landslide Disaster

ABSTRACTIndonesia is an area prone to landslides. The occurrence of this landslide disaster can cause a large impact such as damage and loss both material and non-material. The availability of complete and accurate information in controlling land use in landslide prone areas in the development of an area becomes very important in minimizing the loss of life and losses, both physical, social and economic. This information must be disseminated to the community as an early warning system in disaster mitigation efforts. Identification of the characteristics of landslide prone areas requires a risk mapping of landslide prone areas in efforts to mitigate disasters can be done using Geographic Information Systems (GIS). The results in this study indicate the need to identify disaster risk in detail because basically, an area threatened by disaster does not necessarily mean that each community has the same level of disaster risk. Mapping can be done by clustering or by identifying each building in a vulnerable area based on the level of risk of landslides. Keywords: risk analysis, landslides, disaster mitigation, GIS ABSTRAKIndonesia merupakan wilayah yang rawan terhadap bencana longsor. Terjadinya bencana longsor ini dapat menyebabkan dampak yang besar seperti kerusakan dan kerugian baik materiil maupun non materiil. Tersedianya informasi yang lengkap dan akurat dalam pengendalian pemanfaatan lahan di kawasan rawan bencana longsor dalam pengembangan suatu wilayah menjadi hal yang sangat penting dalam meminimalisir adanya korban jiwa dan kerugian-kerugian baik fisik, sosial maupun ekonomi. Informasi tersebut harus disebarkan kepada masyarakat sebagai sistem peringatan dini dalam upaya mitigasi bencana. Identifikasi karakteristik daerah rawan longsor diperlukan sebuah pemetaan risiko kawasan rawan longsor dalam upaya mitigasi bencana dapat dilakukan menggunakan Sistem Informasi Geografis (SIG). Hasil dalam penelitian ini menunjukkan perlunya identifikasi risiko bencana secara detail karena pada dasarnya, suatu kawasan yang terancam bencana belum tentu tiap masyarakatnya mempunyai tingkat risiko bencana yang sama. Pemetaan dapat dilakukan dengan pengklusteran maupun dengan identifikasi setiap bangunan dalam kawasan rawan berdasarkan tingkat risiko terhadap bencana tanah longsor.Kata Kunci: analisis risiko, tanah longsor, mitigasi bencana, GIS

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