scholarly journals HOUSEHOLD PREPAREDNESS FOR FLOOD DISASTER IN SURAKARTA CITY 2017

GeoEco ◽  
2018 ◽  
Vol 4 (2) ◽  
pp. 192
Author(s):  
Ika Rahmawati ◽  
Chatarina Muryani ◽  
Setya Nugraha
Keyword(s):  
Flood Control ◽  
Sampling Technique ◽  
Flood Disaster ◽  
Disaster Mitigation ◽  
Basic Material ◽  
Measurement Framework ◽  
Administrative Unit ◽  
Western City ◽  
Household Preparedness ◽  
Flood Characteristics

<p>This research case aims to determine (1) The spread of floods in the city of Surakarta in 2016; (2) Uncertainty factors that causing floods based on community perception in Surakarta City; (3) Individual and household preparedness levels in dealing with flood disaster in Surakarta City; (4) Implementation of science as a teaching material of geography in grade XI Senior High School on basic material of natural disaster mitigation.</p><p>The research was conducted in Western City of Surakarta. The area assumed in Western City of Surakarta are Banjarsari district, Laweyan District, and Serengan District. Eligible samples consisted of 11 villages affected by flood in 2016, sampling of administrative unit using purposive sampling technique. The sample has been taken is the number of individuals / households in each ‘RW’ affected by floods in each villages, the number of samples is using snowball sampling technique. Data collection was done by documentation study, interview, questionnaire, and interview. Data validity test is done by data triangulation method. Data analysis is using Likert approach and LIPI preparedness measurement framework - UNESCO / ISDR.</p>The results of the research are as follows: (1) flooding spread in eleven sub-districts in West Surakarta City which is divided into 3 regions based on administrative unit of analysis. Banjarsari District having local flood characteristics and submissions with elevation and duration of time falling into the low category. Laweyan District areas have local flood characteristics and postings with elevation and duration of time that falling into the low category. Serengan District has local flood characteristics and post with elevation and duration falling into the medium category; (2). Factors causing high flooding, garbage disposal, and flood control building conditions; (3) Individual and household preparedness studies in all villages are in a ready category;

scholarly journals Household Preparedness to Reducing Landslide Disaster Risk in Sepakung Village

2021 ◽  
Vol 8 (8) ◽  
pp. 618-627
Author(s):  
Yohanes Dwi Anugrahanto ◽  
Dewi Liesnoor Setyowati ◽  
Erni Suharini
Keyword(s):  
Sampling Technique ◽  
Early Warning Systems ◽  
Disaster Risk ◽  
Disaster Mitigation ◽  
Central Java ◽  
The People ◽  
Analysis Technique ◽  
Prone Area ◽  
Household Preparedness ◽  
Evacuation Routes

Landslides are one of the natural disasters that often occur in Indonesia. Throughout 2019, Indonesia experienced 1483 landslides. Indonesian people need to have preparedness in dealing with disasters. Sepakung village is included in a landslide-prone area in Semarang regency, Central Java. This study aims to analyze the preparedness of the people of Sepakung village who live around landslide-prone points. The research method used is quantitative with a descriptive percentage analysis technique. The population of this research is the residents of Sepakung village. The sampling technique used is purposive sampling. Data collection techniques using observation, questionnaires, and documentation. The data processing results show that the experience of dealing with landslides for the residents of Sepakung village is quite good. This is shown from the average descriptive percentage score reaching 65.909091. The attitude of the respondent's vigilance is included in the very good category, with a descriptive score of the percentage getting 85%. All respondents in this study agreed that awareness of landslides needs to be increased during the rainy season. Knowledge of landslides that are owned needs to be increased again, especially for knowledge about the signs of landslides, disaster mitigation, early warning systems, and evacuation routes. Keywords: disaster, disaster risk reduction, preparedness, landslide.

scholarly journals A Case Study of Flood Risk Evaluation Based on Emergy Theory and Cloud Model in Anyang Region, China

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 420
Author(s):  
Zening Wu ◽  
Yuhai Cui ◽  
Yuan Guo
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Flood Control ◽  
Flood Hazard ◽  
Cloud Model ◽  
Flood Disaster ◽  
Assessment System ◽  
Assessment Model ◽  
Flood Risk Assessment ◽  
Emergy Theory

With the progression of climate change, the intensity and frequency of extreme rainfall have increased in many parts of the world, while the continuous acceleration of urbanization has made cities more vulnerable to floods. In order to effectively estimate and assess the risks brought by flood disasters, this paper proposes a regional flood disaster risk assessment model combining emergy theory and the cloud model. The emergy theory can measure many kinds of hazardous factor and convert them into unified solar emergy (sej) for quantification. The cloud model can transform the uncertainty in flood risk assessment into certainty in an appropriate way, making the urban flood risk assessment more accurate and effective. In this study, the flood risk assessment model combines the advantages of the two research methods to establish a natural and social dual flood risk assessment system. Based on this, the risk assessment system of the flood hazard cloud model is established. This model was used in a flood disaster risk assessment, and the risk level was divided into five levels: very low risk, low risk, medium risk, high risk, and very high risk. Flood hazard risk results were obtained by using the entropy weight method and fuzzy transformation method. As an example for the application of this model, this paper focuses on the Anyang region which has a typical continental monsoon climate. The results show that the Anyang region has a serious flood disaster threat. Within this region, Linzhou County and Anyang County have very high levels of risk for flood disaster, while Hua County, Neihuang County, Wenfeng District and Beiguan District have high levels of risk for flood disaster. These areas are the core urban areas and the economic center of local administrative regions, with 70% of the industrial clusters being situated in these regions. Only with the coordinated development of regional flood control planning, economy, and population, and reductions in the uncertainty of existing flood control and drainage facilities can the sustainable, healthy and stable development of the region be maintained.

Flood Disaster and Flood Control Measurements in Shanghai

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Zhengzheng Zhou ◽  
Shuguang Liu ◽  
Guihui Zhong ◽  
Yi Cai
Keyword(s):  
Flood Control ◽  
Flood Disaster

scholarly journals Analysis of the Losses Due to Flood and Waterlogging Disasters in China during 2006 to 2017

Proceedings ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 25
Author(s):  
Weiwei Shao ◽  
Yuanfei Li ◽  
Dianyi Yan ◽  
Jiahong Liu ◽  
Zhiyong Yang ◽  
...  
Keyword(s):  
Flood Disaster ◽  
Disaster Mitigation ◽  
High Concentration ◽  
Rapid Urbanization ◽  
Analysis And Evaluation ◽  
Flood Disasters ◽  
Disaster Losses ◽  
Disaster Control ◽  
The Impact ◽  
The Relationship

China is in a period of rapid urbanization. Due to the high concentration of population and industries, the loss due to flood and waterlogging is becoming more and more serious. Therefore, it is of great significance to strengthen the analysis and evaluation of the losses due to flood and waterlogging disasters in China for the recent years. This study analyzed the losses caused by flood and waterlogging disasters in China from 2006 to 2017. The results showed that the most serious year affected by floods and waterlogging was 2010. However, the relationship between rainfall and flood disaster losses was not significant, which may be because the occurrence of flood disasters is caused by many factors. The spatial distribution showed that the eastern and southern parts of China suffered greater losses from the flood and waterlogging disasters because these areas are more vulnerable to floods and waterlogging disasters under the impact of both monsoons and typhoons. This study hopes to provide some reference for flood disaster control and disaster mitigation in the future.

scholarly journals Implementation Flood Disaster Policy base Community in Cilacap Regency, Central Java Province, Indonesia

2019 ◽  
Vol 3 (2) ◽  
pp. 50
Author(s):  
Rudi SUBIYAKTO ◽  
Sri SUWITRI ◽  
Endang LARASATI ◽  
Prayitno PRAYITNO
Keyword(s):  
Research Method ◽  
Risk Index ◽  
Disaster Risk ◽  
Flood Disaster ◽  
Disaster Mitigation ◽  
Infrastructure Development ◽  
Mitigation Policy ◽  
Central Java ◽  
The Impact ◽  
Central Java Province

Cilacap Regency is the region that has the highest Disaster Risk Index in the Central Java Province, this area has the risk of floods, water robes, landslides, droughts, tornadoes, earthquakes, and tsunamis. Data from the Indonesian Disaster Risk Index (IRBI) in 2016 shows the level of disaster risk in Cilacap Regency occupying the 17th position nationally and first from 35 regencies/cities in the Central Java Province with a score of 132 (high hazard class). Under these conditions, a Disaster Mitigation Policy is needed. Legally, the Mitigation Policy in Cilacap Regency has been regulated in Regional Regulation Number 1 of 2012 concerning Violation of disaster management, especially in article 43 which includes several activities, namely: (1) Spatial planning implementation (2) Arrangement of infrastructure development, governance buildings, (3) Organizing education, counseling, and training, both conventional and modern, so that regional governments are expected to be able to develop disaster information, disaster databases, and maps in order to minimize the impact of disasters. Therefore, in this study, trying to describe the analysis of the implementation of disaster mitigation policies in Cilacap Regency. The research method used is a qualitative research method by looking at phenomena in the implementation of disaster mitigation and the factors that support and inhibit them. The community plays a role according to the direction of the BPBD. The community continues to coordinate, communicate and cooperate in carrying out its role. The non-technical role is carried out through socialization, education, advocacy to the community in the flood disaster area. Key words: Disaster Mitigation, Policy Implementation, Disaster Impact, Cilacap Regency, Policy Environment

scholarly journals Research on Monthly Precipitation Prediction Based on the Least Square Support Vector Machine with Multi-Factor Integration

Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1076
Author(s):  
Jingchun Lei ◽  
Quan Quan ◽  
Pingzhi Li ◽  
Denghua Yan
Keyword(s):  
Support Vector Machine ◽  
Prediction Model ◽  
Flood Control ◽  
Historical Data ◽  
Yellow River ◽  
Least Square ◽  
Disaster Mitigation ◽  
Support Vector ◽  
Monthly Precipitation ◽  
Precipitation Prediction

Accurate precipitation prediction is of great significance for regional flood control and disaster mitigation. This study introduced a prediction model based on the least square support vector machine (LSSVM) optimized by the genetic algorithm (GA). The model was used to estimate the precipitation of each meteorological station over the source region of the Yellow River (SRYE) in China for 12 months. The Ensemble empirical mode decomposition (EEMD) method was used to select meteorological factors and realize precipitation prediction, without dependence on historical data as a training set. The prediction results were compared with each other, according to the determination coefficient (R2), mean absolute errors (MAE), and root mean square error (RMSE). The results show that sea surface temperature (SST) in the Niño 1 + 2 region exerts the largest influence on accuracy of the prediction model for precipitation in the SRYE (RSST2= 0.856, RMSESST= 19.648, MAESST= 14.363). It is followed by the potential energy of gravity waves (Ep) and temperature (T) that have similar effects on precipitation prediction. The prediction accuracy is sensitive to altitude influences and accurate prediction results are easily obtained at high altitudes. This model provides a new and reliable research method for precipitation prediction in regions without historical data.

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