Application of geographical information system-based analytical hierarchy process modeling for flood susceptibility mapping of Krishna District in Andhra Pradesh

Abstract

Flooding is one of the most catastrophic natural disasters in terms of provoking socioeconomic losses.The current study is to foster a ood susceptibility map of Krishna District in Andhra Pradesh (AP) through integrating remote sensing data, geographical information system (GIS), and the Analytical hierarchy process (AHP). Eleven factors including elevation, slope, aspect, land-use/land-cover (LULC), drainage density, topographic wetness index, stream power index, lithology, soil, precipitation, distance from the streams, are considered for identifying and evaluating the spatial distribution of critical ood susceptible regions. Thematic maps of different factors were derived in GIS using remote sensing data obtained from Sentinel-2A (satellite sensor), shuttle radar topography mission digital elevation model (SRTM DEM -v3), and other scienti c data products. An analytical hierarchy process is a mathematical approach for decision support, primarily based on the weight and rank of different causative factors. AHP technique is implemented for ood hazard modeling and ascertaining the Flood Hazard Index (FHI) to produce a ood susceptibility map. Different thematic maps weighed with the AHP framework are combined using overlay analysis to produce the Flood Susceptibility map of the study region. The outcomes of the study demonstrate the potential of GIS and AHP in providing a premise to recognize the vulnerable areas that are susceptible to ood. According to the ndings, the Flood Hazard Index is 42% and the study region is classi ed into high, moderate, and low susceptible respectively. on. Furthermore, the lack of high-temporal-scale remote sensing data is a key impediment to ood mapping.The AHP model's ood vulnerability zone was classi ed into three groups (high, moderate, and low). The ndings clearly show that regions with low elevation and slope, high TWI, low SPI, high drainage density, and high precipitation are primarily risk-prone due to the high potential of ooding in such areas. The AHP technique used expert judgment and expertise to determine the best weights for the components that contribute to ood risk. The ease of handling, exibility, and low cost of the applicable technique make it possible to employ, particularly in such a location with relatively limited data and information. In the present preliminary assessment of ood hazards, the AHP technique serves its purpose.As, food risk management is a crucial segment of all social and environmental processes aimed at minimizing loss of life, injury, and property damage. The ndings of this research will assist decisionmakers in carrying out adequate ood management in future. Finally, the present study's maps may be utilized as a reference for ood prevention and preparedness by planners, developers, and the government. Knowledge of high-risk zones is essential for local governments to adequately control ooding and plan the execution of necessary ood prevention systems.

An Integrated GIS-AHP based Drought vulnerability Assessment for Kurnool district, Andhra Pradesh, India

“…To nd out the drought prone areas within the Kurnool region, it is to evaluate the harm incurred by droughts in agriculture, a drought vulnerability map must be prepared. The use of geographic information systems and multi-criteria decision models (AHP) can yield more realistic and accurate results in this regard (Penki et al, 2022a). Agricultural drought vulnerability is caused by a variety of factors.…”

“…Section 3.1 discusses how relevant data collected from different sources was utilized to produce maps derived from parameters other than landuse/landcover parameters. Multispectral classi cation techniques were used for the preparation of the landuse/landcover map derived from remotely sensed data (Penki et al, 2022a;Ramu et al, 2022). During this study, we used the supervised classi cation technique to classify multispectral lulc maps using the priori probabilities calculated from the ground data (Penki et al, 2022a;Ramu et al, 2022).…”

“…Such is a Drought assessment through Analytical Hierarchy Process (AHP). AHP is thought to be useful for ranking factors and criteria in a hierarchical order and analyzing data using pair-wise comparisons (Palchaudhuri and Biswas, 2016;Penki et al, 2022a;Ramu et al, 2022).…”

“…A vast area is subject to unpredictable drought, so the use of powerful technologies such as remote sensing is necessary in order to monitor and map droughts. Satellite image-based spatial monitoring of droughts can help reduce the impacts of drought (Penki et al, 2022a;Ramu et al, 2022Ramu et al, , 2022Savari et al, 2022). It has become more popular and widespread to monitor agricultural droughts using satellites in recent years (Kundu et al, 2021).…”

“…The multicriteria decision analysis technique (MCDA) offers a variety of techniques and procedures for analyzing and structuring decision problems, evaluating alternative decisions, and prioritizing them (Penki et al, 2022a(Penki et al, , 2022bRamu et al, 2022Ramu et al, , 2020Wijitkosum, 2018). The pair-wise comparison method created by Saaty (1990) in the framework of such decision-making procedure termed as the Analytic Hierarchy Process represents one of the collection's most promising strategies (AHP) (Saaty, 1990;Saaty and Vargas, 1991).…”