Morpho-lithostructural analysis of Ala River basin for flood risk assessment: geospatial techniques intervention

Olabode, Oluwaseun Franklin; Oluwaniyi, Olaoluwa Emmanuel; Adebayo, Quadri Akolade; Asiwaju-Bello, Yinusa Ayodele

doi:10.1007/s12145-020-00457-6

Cited by 7 publications

(2 citation statements)

References 56 publications

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“…It is one of the most commonly used morphometric features of watersheds in flooding studies. When the values of Cc tend to be close to one, it means the shape of the watershed is closer to a circle, and, therefore, it has the lowest infiltration capacity and the highest sensitivity to flooding [32,33].…”

Section: Methodsmentioning

confidence: 99%

“…and 0 < 𝜇 (𝑢) + 𝐼 (𝑢) + 𝜈 (𝑢) < 1 ∀𝑢 ∈ 𝑈 (33) where 𝜇 (𝑢) is the degree of membership; 𝐼 (𝑢) is the degree of non-membership, and 𝜈 (𝑢) is the indeterminacy of 𝑢 to 𝐴̃ , respectively. Additionally, the degree of refusal of 𝑢 can be defined as follows: 𝜒 ̃ = 1 − 𝜇 (𝑢) + 𝐼 (𝑢) + 𝜈 (𝑢) .…”

Section: Definition 1: the Single-valued Pfs Of ãU Of The Universe Of...mentioning

confidence: 99%

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Ranking Sub-Watersheds for Flood Hazard Mapping: A Multi-Criteria Decision-Making Approach

Nguyen

Bahramloo

Sadeghian

et al. 2023

Water

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The aim of this paper is to assess the extent to which the Sad-Kalan watershed in Iran participates in floods and rank the Sad-Kalan sub-watersheds in terms of flooding potential by utilizing multi-criteria decision-making approaches. We employed the entropy of a drainage network, stream power index (SPI), slope, topographic control index (TCI), and compactness coefficient (Cc) in this investigation. After forming a decision matrix with 25 possibilities (sub-watersheds) and 5 evaluation indices, we used four MCDM approaches, including the analytic hierarchy process (AHP), best–worst method (BWM), interval rough numbers AHP (IRNAHP), picture fuzzy with AHP (PF-AHP), and picture fuzzy with linear assignment model (PF-LAM, hereafter PICALAM) algorithms, to rank the sub-watersheds. The study results demonstrated that PICALAM exhibited superior performance compared to the other methods due to its consideration of both local and global weights for each criterion. Additionally, among the methods used (AHP, BWM, and IRNAHP) that showed similar performances in ranking the sub-watersheds, the BWM method proved to be more time-efficient in the ranking process.

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Section: Methodsmentioning

confidence: 99%

Section: Definition 1: the Single-valued Pfs Of ãU Of The Universe Of...mentioning

confidence: 99%

Ranking Sub-Watersheds for Flood Hazard Mapping: A Multi-Criteria Decision-Making Approach

Nguyen

Bahramloo

Sadeghian

et al. 2023

Water

View full text Add to dashboard Cite

show abstract

Developing a new multi-criteria decision-making for flood prioritization of sub-watersheds using concept of D numbers

Sepehri,

Linh,

Pouya

et al. 2023

Acta Geophys.

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Geochemical processes influencing stream water chemistry: a case study of Ala River, Akure, Southwestern Nigeria

Oluwaniyi

Asiwaju-Bello

2020

Sustain. Water Resour. Manag.

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Morpho-lithostructural analysis of Ala River basin for flood risk assessment: geospatial techniques intervention

Cited by 7 publications

References 56 publications

Ranking Sub-Watersheds for Flood Hazard Mapping: A Multi-Criteria Decision-Making Approach

Ranking Sub-Watersheds for Flood Hazard Mapping: A Multi-Criteria Decision-Making Approach

Developing a new multi-criteria decision-making for flood prioritization of sub-watersheds using concept of D numbers

Geochemical processes influencing stream water chemistry: a case study of Ala River, Akure, Southwestern Nigeria

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