Flash Flood Early Warning System Using Mini PC Case Study: Mount Nago Water Reservoir

Author(s):  
Dodon Yendri ◽  
Angga Septiawan ◽  
Zaini
2018 ◽  
Vol 92 (2) ◽  
pp. 619-634 ◽  
Author(s):  
Changjun Liu ◽  
Liang Guo ◽  
Lei Ye ◽  
Shunfu Zhang ◽  
Yanzeng Zhao ◽  
...  

2017 ◽  
Author(s):  
M. M. Farid ◽  
Prawito ◽  
I. P. Susila ◽  
A. Yuniarto

2018 ◽  
Vol 7 (4.38) ◽  
pp. 1310
Author(s):  
Prof. Dr. Ir Vinesh Thiruchelvam ◽  
Mbau Stella Nyambura

The cost of climate change has increased phenomenally in recent years. Therefore, understanding climate change and its impacts, that are likely to get worse and worse into the future, gives us the ability to predict scenarios and plan for them. Flash floods, which are a common result of climate change, follow increased precipitation which then increases risk and associated vulnerability due to the unpredictable rainfall patterns. Developing countries suffer grave consequences in the event that weather disasters strike because they have the least adaptive capacity. At the equator where the hot days are hotter and winds carrying rainfall move faster, Kenya’s Tana River County is noted for its vulnerability towards flash floods. Additionally, this county and others that are classified as rural areas in Kenya do not receive short term early warnings for floods. This county was therefore selected as the study area for its vulnerability. The aim of the study is therefore to propose a flash flood early warning system framework that delivers short term early warnings. Using questionnaires, information about the existing warning system will be collected and analyzed using SPSS. The results will be used to interpret the relationships between variables of the study, with a particular interest in the moderation effect in order to confirm that the existing system can be modified; that is, if the moderation effect is confirmed.       


2021 ◽  
pp. 209-223
Author(s):  
Ekkehard Holzbecher ◽  
Ahmed Hadidi ◽  
Nicolette Volp ◽  
Jeroen de Koning ◽  
Humaid Al Badi ◽  
...  

AbstractTechnologies concerning integrated water resources management, in general, and flood management, in particular, have recently undergone rapid developments. New smart technologies have been implemented in every relevant sector and include hydrological sensors, remote sensing, sensor networks, data integration, hydrodynamic simulation and visualization, decision support and early warning systems as well as the dissemination of information to decision-makers and the public. After providing a rough review of current developments, we demonstrate the operation of an advanced system with a special focus on an early warning system. Two case studies are covered in this chapter: one specific urban case located in the city of Parrametta in Australia in an area that shows similar flood characteristics to those found in arid or semiarid regions and one case regarding the countrywide Flash Flood Guidance System in Oman (OmanFFGS).


2018 ◽  
Vol 7 (4.38) ◽  
pp. 810
Author(s):  
Prof. Dr. Ir Vinesh Thiruchelvam ◽  
Mbau Stella Nyambura

The cost of climate change has increased phenomenally in recent years. Therefore, understanding climate change and its impacts, that are likely to get worse and worse into the future, gives us the ability to predict scenarios and plan for them. Flash floods, which are a common result of climate change, follow increased precipitation which then increases risk and associated vulnerability due to the unpredictable rainfall patterns. Developing countries suffer grave consequences in the event that weather disasters strike because they have the least adaptive capacity. At the equator where the hot days are hotter and winds carrying rainfall move faster, Kenya’s Tana River County is noted for its vulnerability towards flash floods. Additionally, this county and others that are classified as rural areas in Kenya do not receive short term early warnings for floods. This county was therefore selected as the study area for its vulnerability. The aim of the study is therefore to propose a flash flood early warning system framework that delivers short term early warnings. Using questionnaires, information about the existing warning system will be collected and analyzed using SPSS. The results will be used to interpret the relationships between variables of the study, with a particular interest in the moderation effect in order to confirm that the existing system can be modified; that is, if the moderation effect is confirmed.   


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