Profile of a typical mobile SMS user in emergency situations (empirical study in an urban flood prone area)

2016 ◽  
Author(s):  
Dinar Mutiara Kusumo Nugraheni ◽  
Denise de Vries
Keyword(s):  
Empirical Study ◽  
Urban Flood ◽  
Emergency Situations ◽  
Prone Area ◽  
Flood Prone Area

scholarly journals Urban Flood Control in Sringin Catchment, Semarang City, Central Java Province, Indonesia

2018 ◽  
Vol 4 (2) ◽  
pp. 191
Author(s):  
Ngo Pheaktra ◽  
Istiarto Istiarto ◽  
Rachmad Jayadi
Keyword(s):  
Return Period ◽  
Flood Control ◽  
Flow Analysis ◽  
Drainage System ◽  
Urban Flood ◽  
Central Java ◽  
Design Rainfall ◽  
Prone Area ◽  
Lowland Area ◽  
Flood Prone Area

Sringin is the lowland area located in Semarang city which has been vulnerable to rob flooding from the Java Sea along with flood triggered by the intense amount of rainfall. The case study will further discuss the hydrological analysis, transformation of rational method into flow hydrograph with the design rainfall of 25-year return period, and unsteady flow analysis by HEC-RAS 5.0.3 under existing condition and design condition. The result shows that the design rainfall of 25-year return period measures 173 mm in vertical length and data collected from the office of public work, Semarang city can be used to implement the design scenario with normalization of drainage system and the increase of levee with the freeboard up to 0.75 m is proved to be the solution to the flood inundation in that flood-prone area while the flood under existing condition has caused excessive discharge at downstream up to 9 hours.

Flood-prone area mapping using machine learning techniques: a case study of Quang Binh province, Vietnam

2021 ◽  
Author(s):  
Chinh Luu ◽  
Quynh Duy Bui ◽  
Romulus Costache ◽  
Luan Thanh Nguyen ◽  
Thu Thuy Nguyen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
Prone Area ◽  
Flood Prone Area

scholarly journals Factors that Influence Farmer’s Behavior Towards Risk

2021 ◽  
Vol 226 ◽  
pp. 00030
Author(s):  
Muhamad Nurdin Yusuf ◽  
Agus Yuniawan Isyanto ◽  
Sudradjat Sudradjat
Keyword(s):  
Logistic Regression ◽  
Paddy Fields ◽  
Price Risk ◽  
Land Area ◽  
Income Risk ◽  
Production Risk ◽  
Prone Area ◽  
Risk Takers ◽  
Paddy Farmers ◽  
Flood Prone Area

The research was carried out with the aim to find out the behavior of farmers towards risk and the factors that influence it. The research sample was 100 paddy farmers in flood-prone area paddy fields in Pangandaran District, West Java Province, Indonesia. Farmer’s behavior towards risk was analyzed using quadratic utility functions, while the factors that influence farmer’s behavior towards risk were analyzed using logistic regression. The results showed farmers 87 was risk neutral, while 13 farmer risk takers were farmers. Education, familys size and income significantly influence farmer’s behavior towards risk; while age, experience, land area, production risk, price risk, income risk and group did not significantly influence farmer’s behavior towards risk.

SISTEM INFORMASI GEOGRAFIS (SIG) DAERAH RAWAN BANJIR DI KOTA BENGKULU MENGGUNAKAN ARCVIEW

2016 ◽  
Vol 12 (1) ◽  
Author(s):  
Rahma Wayan Lestari ◽  
Indra Kanedi ◽  
Yode Arliando
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Geographic Information ◽  
The Body ◽  
Microsoft Excel ◽  
Microsoft Word ◽  
Prone Area ◽  
Flood Prone Area ◽  
The City ◽  
Flood Prone Areas

The purpose of this research is to create a geographic information system Bengkulu city flood-prone areas using ArcView. Apply the knowledge obtained during the lecture, especially relating to the development of Geographic Information Systems. To be able to produce a system that is accurate and useful information for the community. Where the research was conducted in the city of Bengkulu BASARNAS. Bengkulu BASARNAS office specializing in Search and Rescue (SAR), is the body that manage the flood of data that is still done manually, using Microsoft Word and Microsoft Excel. Thus experiencing problems in delivering information directly to the office because the SAR agencies require a long time.Keywords: Geographic Information System, Flood Prone Area

scholarly journals Assessment of vulnerability in agricultural sector in disaster prone areas of Bangladesh

2016 ◽  
Vol 28 (2) ◽  
pp. 91-101 ◽  
Author(s):  
TF Khan ◽  
MW Ullah ◽  
SM Imamul Huq
Keyword(s):  
Agricultural Production ◽  
Agricultural Development ◽  
Agricultural Sector ◽  
Flash Flood ◽  
Agricultural Practices ◽  
Cropping Pattern ◽  
River Flood ◽  
Prone Area ◽  
Flood Prone Area ◽  
Livelihood System

A study was carried out in 24 Upazillas of 12 districts of Bangladesh with a view to identifying risks, vulnerabilities and impacts of different types of natural disasters commonly occurring in Bangladesh with respect to agricultural production and sustainable agricultural development. Three districts were selected from each category of the disaster viz., drought, saline, river flood and flash flood prone. Two Upazillas were selected randomly from each district by considering the homogeneity (climate, agricultural practices, agricultural production, disaster risks, livelihood system, population, etc.) of the particular disaster affected areas. Of the four disasters, drought prone area covers the highest net cultivable area (NCA) measuring about 121 ha. Flash flood, salinity and river flood prone area covers approximately 115, 60 and 30 ha, respectively. The dominant cropping pattern in drought areas is Fallow-T.Aman-Wheat. In saline areas, it is Fallow-T. Aman- Pulse while in flood areas, it is Fallow-T.Aman- HYV Boro. Trend analysis shows that overall cropped area decreased by 1% in all disaster prone areas from 1984 - 2013. The highest decrease in cropped area was found for pulse in both drought (13%) and river flood (14%) areas. In saline and flash flood areas, it was for spice and potato, respectively. Among 72 farmers, 85% is vulnerable to drought, 90% to salinity, 69% to river flood and 95% to flash flood. Medium high land was found to be the most vulnerable for agricultural production in all disaster prone areas. Due to vulnerability to disasters, medium high land remains fallow in saline (83%), river flood (51%) and flash flood (31%) areas. In case of drought regions, medium low land (37%) remains fallow.Bangladesh J. Sci. Res. 28(2): 91-101, Dec-2015

scholarly journals Identification of naturally available forage species and their feeding effect on dairy cows in different climatic vulnerable areas of Bangladesh

2017 ◽  
Vol 46 (2) ◽  
pp. 150-158
Author(s):  
SMR Rahman ◽  
NR Sarker ◽  
MR Amin ◽  
M Kamruzzaman ◽  
MR Haque
Keyword(s):  
Milk Production ◽  
Methane Emission ◽  
Methane Production ◽  
Check List ◽  
Climatic Zones ◽  
Forage Species ◽  
Different Types ◽  
Prone Area ◽  
Flood Prone Area ◽  
Drought Prone Area

An investigation was carried out with the objectives to identify the naturally occurring forage species, seasonal availability, production patterns under different climatic zones and production performance and methane emission from dairy cow under existing feeding systems. For this purpose, three different agro-climatic zones of Bangladesh, namely saline prone area (Satkhira), flood plain/river basin areas (Pabna), semi-arid/drought prone areas (Chapainobabgonj) were selected. To achieve the objectives, three Focus Group Discussions (FGD) were conducted in each location to obtain more information from different age groups of farmers. A total of 9 FDGs were conducted under three selected locations and twelve participants were attended in each FGD. During FDGs, information was collected through participatory discussions through check list and also discussion was recorded to verify the information gathered as per check list.  After collection of information in each side, all the data were checked and analyzed. The results indicated that in saline area, farmers reported that different types of local grass e.g. Tale Shapna,Durba,Nona Shapna, Khud Gate/ KhudKhachra, Shama, Full Paira, Bass Pata, Math Pora/KhataShak, GhimeeShak and Baksha etc were available round the year but according to their observation Nona Shapna, Tale Shapna and Baksha were more available compared to other species of the natural grasses and these three natural forages are more suitable in this area. In the drought prone area, different types of native grasses e.g. Durba,Shama, Mutha,Katla,Kausha/Kannar, Binna, Datuloka,Shanchi, Shunshue, Bash Batari, Ulo and Binna Pati were identified and utilized by the farmers in different seasons but Durba,Katla and Mutha were found more drought tolerant compared to other species. In flood prone area, Kolmi, Shanti, Baksha, Arail, Dubla, Bokma, Vadail and Bolenga etc were found and Kolmi, Baksha and Arail are more suitable in this area. Farmers were also reported that fodder tree like Dumur/khoksha also is survive in water logging situation and or flood prone area. The study revealed that calculated total DMI (Kg/h/day) was the highest (14.14±1.06) in flood prone  followed by drought (13.80±1.30) and saline areas (4.43±0.20),  respectively. Similarly, the milk production was also higher (12.06±1.19 litre/h/day) in flood prone area followed by drought (4.47±0.60 litre/h/day) and saline (1.83±0.11 litre/h/day) areas, respectively. The calculated total methane emission (g/h/d) was significantly higher in flood prone (478.31±36.36) and the lowest in saline (153.35±7.14) prone areas. Whereas, methane production per unit of milk yield, was the lowest in flood prone (46.55±6.78) and the highest (110.48±21.69) in drought prone area and the difference was statistically significant (p<0.05).  Therefore, it may be concluded that farmers’ rearing animals under climate vulnerable areas utilizing natural grasses are more prone to higher methane production compared to animals rearing better feed resources though their availability was varied with the seasons and locations.  Hence, further research is needed to explore more suitable natural grasses in addition to introduction of high yielding fodder with higher biomass and nutritive values based on the existing cropping systems in those climate vulnerable areas for higher milk production and low enteric methane emission in the country.Bang. J. Anim. Sci. 2017. 46 (2): 150-158

scholarly journals Flood Evacuation Routes Based on Spatiotemporal Inundation Risk Assessment

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2271
Author(s):  
Yoon Ha Lee ◽  
Hyun Il Kim ◽  
Kun Yeun Han ◽  
Won Hwa Hong
Keyword(s):  
Neural Network ◽  
Risk Assessment ◽  
Flood Risk Assessment ◽  
Flood Prediction ◽  
Prone Area ◽  
Auto Regressive ◽  
Flood Prone Area ◽  
Hazard Level ◽  
Evacuation Routes ◽  
Evacuation Route

For flood risk assessment, it is necessary to quantify the uncertainty of spatiotemporal changes in floods by analyzing space and time simultaneously. This study designed and tested a methodology for the designation of evacuation routes that takes into account spatial and temporal inundation and tested the methodology by applying it to a flood-prone area of Seoul, Korea. For flood prediction, the non-linear auto-regressive with exogenous inputs neural network was utilized, and the geographic information system was utilized to classify evacuations by walking hazard level as well as to designate evacuation routes. The results of this study show that the artificial neural network can be used to shorten the flood prediction process. The results demonstrate that adaptability and safety have to be ensured in a flood by planning the evacuation route in a flexible manner based on the occurrence of, and change in, evacuation possibilities according to walking hazard regions.

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