scholarly journals Modelling Of Food Hazard Susceptibility in Komatipoort, South Africa

2018 ◽  
Vol 37 (1) ◽  
pp. 47-71
Author(s):  
Nomcebo Khumalo ◽  
Aloyce W. Mayo ◽  
Subira Munishi
Keyword(s):  
Hydrological Modeling ◽  
Small Town ◽  
Flood Hazard ◽  
Central Business District ◽  
Hydraulic Modeling ◽  
Susceptibility Mapping ◽  
Flood Susceptibility ◽  
Flood Susceptibility Mapping ◽  
Using Data ◽  
Business District

Komatipoort, a small town located at the confluence of Komati and Krokodil rivers, is constantly being hit by floods which affect the residents of this small town as well as the farmers settling along the rivers. This study aimed at mapping the flood hazard and susceptibility through the integration of GIS techniques and hydraulic modeling. Due to inconsistency in the length of streamflow data in the different gauging stations, a Hydrological modeling HBV model, was utilized for modelling runoff in order to extend flow records at station X2HO32 for Komati River. Calibration was conducted using observed data from 1982 to 1993, giving an efficiency value of 65% and validation was done using data from 1993 to 1999, giving an efficiency value of 53%. Flood frequencies were analyzed and flood quantiles were determined at different return periods. HEC-RAS was utilized to simulate the hydraulic parameters of Komati and Krokodil rivers to obtain flood hazard maps. GIS-based multi-criteria analysis techniques were incorporated for flood susceptibility mapping. Hydraulic analysis showed that the floods mostly affect the farms and settlements along the rivers and a small part of the central business district is affected. Flood susceptibility mapping showed that the area is generally highly susceptible to flooding because of a combination of anthropogenic and natural factors.

scholarly journals PRELIMINARY INVESTIGATIONS ON FLOOD SUSCEPTIBILITY MAPPING IN ANKARA (TURKEY) USING MODIFIED ANALYTICAL HIERARCHY PROCESS (M-AHP)

2018 ◽  
Vol XLII-5 ◽  
pp. 361-365 ◽  
Author(s):  
B. Sozer ◽  
S. Kocaman ◽  
H. A. Nefeslioglu ◽  
O. Firat ◽  
C. Gokceoglu
Keyword(s):  
Urban Areas ◽  
Flood Hazard ◽  
Analytic Solutions ◽  
Drainage Density ◽  
Susceptibility Mapping ◽  
Topographic Wetness Index ◽  
Flood Susceptibility ◽  
Spatial Datasets ◽  
Flood Susceptibility Mapping ◽  
Hierarchy Process

<p><strong>Abstract.</strong> Susceptibility mapping for disasters is very important and provides the necessary means for efficient urban planning, such as site selection and the determination of the regulations, risk assessment and the planning of the post-disaster stage, such as emergency plans and activities. The main purpose of the present study is to introduce the preliminary results of an expert based flood susceptibility mapping approach applied in urban areas in case of Ankara, Turkey. The proposed approach is based on Modified Analytic Hierarchy Process (M-AHP), which is an expert-based algorithm and provides data based modeling. The existing spatial datasets are evaluated in the decision process and the specified number of decision points according to the degree desired can be formed. The parameter priorities can be identified at the beginning of the modeling with this approach by the responsible expert. The spatial datasets used in the modeling and mapping process have been provided by the General Directorate of Mapping (HGM). Additionally, the slope gradient of topography, drainage density, and topographic wetness index of the site being one of the second derivatives of topography have been evaluated to identify the main conditioning factors controlling water accumulation on ground. Considering the uncertainties in flood hazard assessment and limitations in sophisticated analytic solutions, the proposed methodology could be evaluated to be an efficient tool to detect the most influential parameters representing the flood vulnerability and assessing the mitigation applications in urban environment.</p>

scholarly journals Application of a Novel Hybrid Method for Flood Susceptibility Mapping with Satellite Images: A Case Study of Seoul, Korea

2021 ◽  
Vol 13 (14) ◽  
pp. 2786
Author(s):  
Roya Narimani ◽  
Changhyun Jun ◽  
Saqib Shahzad ◽  
Jeill Oh ◽  
Kyoohong Park
Keyword(s):  
High Risk ◽  
Hybrid Method ◽  
Satellite Images ◽  
Controlling Factors ◽  
Susceptibility Mapping ◽  
Low Risk ◽  
Flood Susceptibility ◽  
Flood Susceptibility Mapping ◽  
Flood Maps

This paper proposes a novel hybrid method for flood susceptibility mapping using a geographic information system (ArcGIS) and satellite images based on the analytical hierarchy process (AHP). Here, the following nine multisource environmental controlling factors influencing flood susceptibility were considered for relative weight estimation in AHP: elevation, land use, slope, topographic wetness index, curvature, river distance, flow accumulation, drainage density, and rainfall. The weight for each factor was determined from AHP and analyzed to investigate critical regions that are more vulnerable to floods using the overlay weighted sum technique to integrate the nine layers. As a case study, the ArcGIS-based framework was applied in Seoul to obtain a flood susceptibility map, which was categorized into six regions (very high risk, high risk, medium risk, low risk, very low risk, and out of risk). Finally, the flood map was verified using real flood maps from the previous five years to test the model’s effectiveness. The flood map indicated that 40% of the area shows high flood risk and thus requires urgent attention, which was confirmed by the validation results. Planners and regulatory bodies can use flood maps to control and mitigate flood incidents along rivers. Even though the methodology used in this study is simple, it has a high level of accuracy and can be applied for flood mapping in most regions where the required datasets are available. This is the first study to apply high-resolution basic maps (12.5 m) to extract the nine controlling factors using only satellite images and ArcGIS to produce a suitable flood map in Seoul for better management in the near future.

Swarm‐based optimizer for convolutional neural network: An application for flood susceptibility mapping

2020 ◽  
Author(s):  
Tien‐Yin Chou ◽  
Thanh‐Van Hoang ◽  
Yao‐Min Fang ◽  
Quoc‐Huy Nguyen ◽  
Tuan Anh Lai ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Susceptibility Mapping ◽  
Flood Susceptibility ◽  
Flood Susceptibility Mapping

scholarly journals A Hybrid GIS Multi-Criteria Decision-Making Method for Flood Susceptibility Mapping at Shangyou, China

2018 ◽  
Vol 11 (1) ◽  
pp. 62 ◽  
Author(s):  
Yi Wang ◽  
Haoyuan Hong ◽  
Wei Chen ◽  
Shaojun Li ◽  
Dragan Pamučar ◽  
...  
Keyword(s):  
Decision Making ◽  
Area Under The Curve ◽  
Analytic Network Process ◽  
Susceptibility Mapping ◽  
Collective Decision ◽  
Susceptibility Map ◽  
Hybrid Technique ◽  
Collective Decision Making ◽  
Flood Susceptibility ◽  
Flood Susceptibility Mapping

Floods are considered one of the most disastrous hazards all over the world and cause serious casualties and property damage. Therefore, the assessment and regionalization of flood disasters are becoming increasingly important and urgent. To predict the probability of a flood, an essential step is to map flood susceptibility. The main objective of this work is to investigate the use a novel hybrid technique by integrating multi-criteria decision analysis and geographic information system to evaluate flood susceptibility mapping (FSM), which is constructed by ensemble of decision making trial and evaluation laboratory (DEMATEL), analytic network process, weighted linear combinations (WLC) and interval rough numbers (IRN) techniques in the case study at Shangyou County, China. Specifically, we improve the DEMATEL method by applying IRN to determine connections in the network structure based on criteria and to accept imprecisions during collective decision making. The application of IRN can eliminate the necessity of additional information to define uncertain number intervals. Therefore, the quality of the existing data during collective decision making and experts’ perceptions that are expressed through an aggregation matrix can be retained. In this work, eleven conditioning factors associated with flooding were considered and historical flood locations were randomly divided into the training (70% of the total) and validation (30%) sets. The flood susceptibility map validates a satisfactory consistency between the flood-susceptible areas and the spatial distribution of the previous flood events. The accuracy of the map was evaluated by using objective measures of receiver operating characteristic (ROC) curve and area under the curve (AUC). The AUC values of the proposed method coupling with the WLC fuzzy technique for aggregation and flood susceptibility index are 0.988 and 0.964, respectively, which proves that the WLC fuzzy method is more effective for FSM in the study area. The proposed method can be helpful in predicting accurate flood occurrence locations with similar geographic environments and can be effectively used for flood management and prevention.

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