Flood Susceptibility Analysis (FSAn) Using Multi-Criteria Evaluation (MCE) Technique for Landuse Planning: A Case from Penampang, Sabah, Malaysia

This study area is part of the Kadamaian watershed and is located on the North-West flank of Mount Kinabalu, composed of sedimentary rock from the Crocker Formation and the Mt. Kinabalu granitic pluton. Many loose seismic materials were found on the slopes during the 2015 Sabah Earthquake with a moment magnitude of 6.0. These materials later served as the source material for rainfall-induced debris flows or shallow landslides. The community closest to the Panataran river in the Kg Melangkap area is the most affected. Therefore, the objective of this study is to study the debris flow susceptibility analysis using a bivariate statistical analysis approach, namely the Frequency Ratio (FR) model. Forty-eight landslides were identified using remote sensing interpretation. Characteristics of the research area, such as slope gradient, elevation, slope aspect, lithology, slope curvature, and topographic wetness index, were selected as the factors to evaluate the debris flow susceptibility analysis. The correlations between these factors and the occurrence of landslides were established, and the results were assessed and validated based on those results. Validation findings demonstrate that this technique provides high accuracy, with an AUC of 81.8 for success rate. As a result, it can be stated that this model accurately predicted landslide susceptibility in the research area, and that it can help local authority with future land-use planning, as well as give tools for hazard mitigation.

Section: Resultsmentioning

confidence: 99%

Debris flow susceptibility analysis using a bivariate statistical analysis in the Panataran River, Kg Melangkap, Sabah, Malaysia

Sharir

Lai

Simon

et al. 2022

“…Soils with a texture consisting of sand and dust will tend to form a rusty and rough soil surface to reduce the infiltration rate [35]. In addition, soil infiltration capacity affects the state of soil texture due to a decrease in infiltration capacity so that there is an increase in surface runoff [61].…”

Section: Frequency Ratio Calculationmentioning

confidence: 99%

Flood vulnerability analysis using the frequency ratio method with the watershed ecosystem in Bulukumba Regency, South Sulawesi Indonesia

Soma,

Arsyad,

Nursaputra

et al. 2023

Bulukumba Regency is located in the Province of South Sulawesi. It is one of the main tourist destinations and phinisi boat industry that provides much economic added value for the community and local government. Apart from these advantages, the problem of flooding is an obstacle and has a detrimental impact on the regional economy. Drainage problems, weather anomalies, and land function experts in the upstream area are factors in the occurrence of floods in Bulukumba Regency. This study used remote sensing and geographic information systems (GIS) combined with the Frequency Ratio (F.R.) method to create flood vulnerability maps. The parameters in this study are based on literature studies, data availability, and research site conditions such as rainfall, earth curvature, river distance, marbles, altitude, topographic wetness index (TWI), stream power index (SPI), soil texture, soil permeability, geology, and land use/land cover (LULC). The results of the identification of flood events obtained a total area of flood events, namely 6,345 ha, which was identified with the highest F.R. value in the closure of pond land and coastal sand beds, sand soil texture, and lithology, namely alluvium rocks. Validation was obtained for the success rate with a value of 0.895 and the prediction rate with a value of 0.887. It shows the weight that falls into the good category. The area of insecurity has a high of 7.20% and high of 1.69%.

“…The pair-wise comparison is more acceptable if accuracy and theory are the main concern [13]. The process consists of contrasting the criteria and evaluating the relevance of two parameters at a time [14][15][16][17]. The criterion pair-wise comparison matrix takes the pair-wise comparisons as an input and produces the relative weights as output.…”

Section: 𝐹𝑆𝐼 = (∑ 𝑊𝑝𝑎𝑟𝑎𝑚𝑒𝑡𝑒𝑟 𝑋 𝑊𝑠𝑢𝑏𝑝𝑎𝑟𝑎𝑚𝑒𝑡𝑒𝑟)mentioning

confidence: 99%

Assessment of Flood Susceptibility Analysis Using Analytical Hierarchy Process (AHP) in Kota Belud Area, Sabah, Malaysia

Sharir

Lai

Simon

et al. 2022

This study aims to assess the flood susceptibility analysis using a Geographical Information System (GIS) based-heuristic analysis, namely the Analytical Hierarchy Process (AHP) model. Eight relevant physical parameters have been selected, namely, drainage density, drainage proximity, elevation, slope angle, slope curvature, land use, soil type, and topography wetness index. The relative importance of these factors has been compared in the pairwise matrix to gain weight values during the process of the Analytical Hierarchy Process (AHP). The flood susceptibility zones have been mapped according to their weightage value. Finally, the flood susceptibility map was prepared and classified into six classes as very low, low, moderate, high, and very high susceptibility using the natural break classification method. The accuracy of the flood susceptibility model was validated using the Area Under the Curve (AUC) analysis. The AUC for success rate was estimated at 82.13%.7.