Fuzzy Logic Approach to Complex Assessment of Drought Vulnerability

Nikolova, Nina; Златева, Пламена; Todorov, Leonid

doi:10.1007/978-3-030-81469-4_24

Cited by 2 publications

(3 citation statements)

References 24 publications

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“…As an alternative methodology, the fuzzy theory introduced by Zadeh (1965) provides a logical approach that is capable of dealing with complex systems, such as those observed in forest fire events that have spatial and temporal variability, as well as subjectivity, and providing an adequate mathematical treatment (Zadeh 1965;Araya-Muñoz et al 2017;Bressane et al 2020;Fernandes et al 2023). Recent environmental applications that use the fuzzy approach integrated with GIS have shown advantages over traditional techniques in evaluating several phenomena, such as susceptibility to flooding (Sahana and Patel, 2019), landslides (Nwazelibe et al 2023), drought (Nikolova et al 2021), and soil erosion (Souza et al 2019), and anthropic impact on watersheds (Lopes et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Inference System For Mapping Forest Fire Susceptibility In Northern Rondônia, Brazil

Duarte,

Acácio da Silva,

Paixão de Sousa

et al. 2024

GES

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Forest fires are global phenomena that pose an accelerating threat to ecosystems, affect the population life quality and contribute to climate change. The mapping of fire susceptibility provides proper direction for mitigating measures for these events. However, predicting their occurrence and scope is complicated since many of their causes are related to human practices and climatological variations. To predict fire occurrences, this study applies a fuzzy inference system methodology implemented in R software and using triangular and trapezoidal functions that comprise four input parameters (temperature, rainfall, distance from highways, and land use and occupation) obtained from remote sensing data and processed through GIS environment. The fuzzy system classified 63.27% of the study area as having high and very high fire susceptibility. The high density of fire occurrences in these classes shows the high precision of the proposed model, which was confirmed by the area under the curve (AUC) value of 0.879. The application of the fuzzy system using two extreme climate events (rainy summer and dry summer) showed that the model is highly responsive to temperature and rainfall variations, which was verified by the sensitivity analysis. The results obtained with the system can assist in decision-making for appropriate firefighting actions in the region.

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Section: Introductionmentioning

confidence: 99%

Fuzzy Inference System For Mapping Forest Fire Susceptibility In Northern Rondônia, Brazil

Duarte,

Acácio da Silva,

Paixão de Sousa

et al. 2024

GES

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“…They are beneficial for drought assessment because drought conditions are often complex and challenging to define, and uncertainty is often associated with the data used to assess drought conditions. Fuzzy logic-based methods can help overcome these challenges by providing a more flexible and adaptable approach to drought assessment (Nikolova et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

“…These models are essential hazard assessment tools (Hoque et al, 2021;Nikolova et al, 2021). However, when using fuzzy logic, multicriteria decision-making is considered more accurate (Chen et al, 2020) and less subjective (Mahjouri et al, 2017), as it reduces imprecision and subjectivity (Kahraman, 2008).…”

Section: Introductionmentioning

confidence: 99%

State-Level Multidimensional Agricultural Drought Susceptibility and Risk Assessment for Agriculturally Prominent Areas

Islam¹,

Yeșilköy²,

Baydaroğlu³

et al. 2023

Preprint

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Due to the shifting climate, extreme events are being observed more frequently globally. Drought is one of the most common natural hazards that severely impacts communities in terms of economic losses and agricultural production disruption. Considering global trade, drought in an agricultural region affects the food security in other regions because of disrupted supply. Decision-makers often consult susceptibility maps when preparing mitigation plans so that the adverse impacts of a drought event can be reduced. Creating drought susceptibility maps can be demanding, requiring a lot of data (i.e., hydrological and land use), expertise, and thorough assessment to accurately picture a vulnerable region’s condition. The process also relies on complex hydrological and hydrometeorological models. The objective of this investigation is to examine the vulnerability and impact of drought and formulate maps of drought susceptibility, exposure, and risk by considering a multitude of atmospheric, physical and social indicators. Subsequent to this notion, a fuzzy logic algorithm has been devised by assigning a comprehensive array of weights to each parameter derived from an exhaustive literature review and used for a preliminary investigation for the state of Iowa. This state is located in the Corn Belt region, and its primary economic activity is agriculture. Drought susceptibility maps for the state of Iowa have been generated for the period spanning from 2015 to 2021 and validated using the Kappa coefficient. The produced drought susceptibility maps can support drought mitigation plans and decisions for communities in Iowa.

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Fuzzy Logic Approach to Complex Assessment of Drought Vulnerability

Cited by 2 publications

References 24 publications

Fuzzy Inference System For Mapping Forest Fire Susceptibility In Northern Rondônia, Brazil

Fuzzy Inference System For Mapping Forest Fire Susceptibility In Northern Rondônia, Brazil

State-Level Multidimensional Agricultural Drought Susceptibility and Risk Assessment for Agriculturally Prominent Areas

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