scholarly journals Flood susceptibility assessment for ungauged sites in urban areas using spatial modeling

2021 ◽  
Author(s):  
Zohreh Masoumi
Keyword(s):  
Spatial Modeling ◽  
Urban Areas ◽  
Susceptibility Assessment ◽  
Ungauged Sites ◽  
Flood Susceptibility

scholarly journals Use of Mamdani Fuzzy Algorithm for Multi-Hazard Susceptibility Assessment in a Developing Urban Settlement (Mamak, Ankara, Turkey)

2020 ◽  
Vol 9 (2) ◽  
pp. 114 ◽  
Author(s):  
Tugce Yanar ◽  
Sultan Kocaman ◽  
Candan Gokceoglu
Keyword(s):  
High Resolution ◽  
Landslide Susceptibility ◽  
Urban Areas ◽  
Susceptibility Map ◽  
Susceptibility Assessment ◽  
Urban Settlement ◽  
Fuzzy Algorithm ◽  
Flood Susceptibility ◽  
Susceptibility Maps ◽  
Integrated Hazard

Urban areas may be affected by multiple hazards, and integrated hazard susceptibility maps are needed for suitable site selection and planning. Furthermore, geological–geotechnical parameters, construction costs, and the spatial distribution of existing infrastructure should be taken into account for this purpose. Up-to-date land-use and land-cover (LULC) maps, as well as natural hazard susceptibility maps, can be frequently obtained from high-resolution satellite sensors. In this study, an integrated hazard susceptibility assessment was performed for a developing urban settlement (Mamak District of Ankara City, Turkey) considering landslide and flood potential. The flood susceptibility map of Ankara City was produced in a previous study using modified analytical hierarchical process (M-AHP) approach. The landslide susceptibility map was produced using the logistic regression technique in this study. Sentinel-2 images were employed for generating LULC data with the random forest classification method. Topographical derivatives obtained from a high-resolution digital elevation model and lithological parameters were employed for the production of landslide susceptibility maps. For the integrated hazard susceptibility assessment, the Mamdani fuzzy algorithm was considered, and the results are discussed in the present study. The results demonstrate that multi-hazard susceptibility assessment maps for urban planning can be obtained by combining a set of expert-based and ensemble learning methods.

Climate and land use change induced future flood susceptibility assessment in a sub-tropical region of India

2021 ◽  
Author(s):  
Paramita Roy ◽  
Subodh Chandra Pal ◽  
Alireza Arabameri ◽  
Fatemeh Rezaie ◽  
Rabin Chakrabortty ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Tropical Region ◽  
Susceptibility Assessment ◽  
Flood Susceptibility

scholarly journals Flash Flood Susceptibility Assessment Based on Geodetector, Certainty Factor, and Logistic Regression Analyses in Fujian Province, China

2020 ◽  
Vol 9 (12) ◽  
pp. 748
Author(s):  
Yifan Cao ◽  
Hongliang Jia ◽  
Junnan Xiong ◽  
Weiming Cheng ◽  
Kun Li ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Flash Flood ◽  
Pearson Correlation ◽  
Flash Floods ◽  
Ensemble Model ◽  
Susceptibility Assessment ◽  
Certainty Factor ◽  
Fujian Province ◽  
Flood Susceptibility ◽  
Susceptibility Maps

Flash floods are one of the most frequent natural disasters in Fujian Province, China, and they seriously threaten the safety of infrastructure, natural ecosystems, and human life. Thus, recognition of possible flash flood locations and exploitation of more precise flash flood susceptibility maps are crucial to appropriate flash flood management in Fujian. Based on this objective, in this study, we developed a new method of flash flood susceptibility assessment. First, we utilized double standards, including the Pearson correlation coefficient (PCC) and Geodetector to screen the assessment indicator. Second, in order to consider the weight of each classification of indicator and the weights of the indicators simultaneously, we used the ensemble model of the certainty factor (CF) and logistic regression (LR) to establish a frame for the flash flood susceptibility assessment. Ultimately, we used this ensemble model (CF-LR), the standalone CF model, and the standalone LR model to prepare flash flood susceptibility maps for Fujian Province and compared their prediction performance. The results revealed the following. (1) Land use, topographic relief, and 24 h precipitation (H24_100) within a 100-year return period were the three main factors causing flash floods in Fujian Province. (2) The area under the curve (AUC) results showed that the CF-LR model had the best precision in terms of both the success rate (0.860) and the prediction rate (0.882). (3) The assessment results of all three models showed that between 22.27% and 29.35% of the study area have high and very high susceptibility levels, and these areas are mainly located in the east, south, and southeast coastal areas, and the north and west low mountain areas. The results of this study provide a scientific basis and support for flash flood prevention in Fujian Province. The proposed susceptibility assessment framework may also be helpful for other natural disaster susceptibility analyses.

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>

Sign in / Sign up

Export Citation Format

Share Document