A Geospatial Expose of Flood-Risk and Vulnerable Areas in Nigeria

Njoku, Chukwudi Gbadebo; Efiong, Joel; Ayara, Nse-Abasi Ndiyo

doi:10.4018/ijagr.20200701.oa1

Cited by 9 publications

(6 citation statements)

References 44 publications

(42 reference statements)

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“…Flood vulnerability zone map yielded an outcome that was classified into five zones such as very low (2.02 km 2 ), low (2.45 km 2 ), moderately low (2.44 km 2 ), highly vulnerable (2.26 km 2 ) and very highly vulnerable (1.21 km 2 ) areas. Njoku, Efiong, and Ayara (2020), studied local government areas (LGAs) in Nigeria that are at risk and vulnerable to flooding. The study incorporated multi-criteria approach and geospatial techniques.…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of Flood Susceptibility in Northern Anambra State, Nigeria Using Geospatial Technology.

Igboanugo,

Iheukwumere,

Obikwelu

et al. 2023

ijaser

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The vulnerability of the Northern region in Anambra was modelled using Analytical Hierarchical Process (AHP,) Best Worst Method (BWM) and Criteria Importance Through Intercriteria Correlation Method (CRITIC Method) by performing a pairwise comparison matrix of the nine flood influential factors with the aid of GIS. This was modelled with the aid of Geographic Information System (GIS). GIS, is a veritable software for modelling and predicting spatial aspects of the real world. Nine flood conditioning factors were used to model the flood susceptibility of Northern Anambra region. The conditioning factors for the analysis were rainfall, slope, aspect, lithology, LULC, elevation, SPI, NDVI, and drainage density. The value obtained from AHP, BWM and CRITIC method analysis indicated that 73%, 72% and 78% of the land area were susceptible to flooding, and thus implied that about 1197.89km 2 out of the 1794km 2 are liable to experience frequent flooding events. These values were validated with AUC curve, with AHP, BWM and CRITIC method having an accuracy prediction of 74%, 73% and 78% respectively at 95% level of confidence. According to the flood inventory and the modelled map, flooding is evident in the southwest, west, and southeastern parts of the study area. Rainfall is weighted as the highest influencing factor for AHP and BWM but Aspect weighted the highest influencing factor for CRITIC method. We thus recommend that effort for provision of advanced drainage system, which will enable water to make its path to the river in the rainy season, as this will mitigate dry land being submerged in water at every rainy season.

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Section: Literature Reviewmentioning

confidence: 99%

Analysis of Flood Susceptibility in Northern Anambra State, Nigeria Using Geospatial Technology.

Igboanugo,

Iheukwumere,

Obikwelu

et al. 2023

ijaser

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“…Slope of an area determine the intensity of flash flood but the fatalities increase with steepness [30]. In general, flash flood risk increases on flat slope [31], this is because, flat terrain allows rainwater to accumulate. Google Earth digital terrain model (GEDEM) was used to produce slope model in ESRI's ArcGIS.…”

Section: Slope Modelmentioning

confidence: 99%

Analyzing flash flood risk in a section of ntawogba creek, Port Harcourt city, Rivers State

JU¹,

Abah²,

BA³

2022

Int. J. Frontline Res. Eng. Technol.

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Flood is a natural disaster and occurred in different forms. It is also a factor of climate change. Flash flood is a type of flood that occurs within few hours of intensive precipitation. It poses serious threat to urban areas, particularly in less developed countries. Geospatial technology has been very useful in mapping spatial extent and quantified damages associated with flash flood events. Proximity analysis and AHP has been widely utilized in modeling flash flood vulnerable zones. Little was known about MCA ranking method which is considered appropriate for few parameters in making complex decisions. This study utilized MCA ranking method to analyzed flash flood risk within Ntawogba Creek, Port Harcourt, Rivers State. Rainfall, slope model, impervious surface and distance to river were used in the decision making. The datasets were processed into common spatial referenced system. Each criterion was scaled from 5 to 1, with 5 being very high risk and 1 very low risk area. Weights were assigned to the criteria based on the importance, with higher weight to criterion that is more important in the decision making process. The weights are; distance to water channel 48, impervious surface 25, slope 22 and rainfall 5. The results obtained showed area of 93.0ha as very high flash flood risk representing 6% of the area. This zone was located along Ntawogba Creek and on major roads. Total area of high risk zone was 864.1ha representing 56%, moderate risk and low risk zone was 452.2ha and 134.7ha with 29.3 5 and 8.7% respectively. For further study, drainage density and soil infiltration should be included in the flash flood risk analysis.

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“…Rising river levels and ocean surges have frequently submerged towns and villages in parts of the Niger Delta, Lagos State, Imo State, Anambra State, Kogi State, and many other States in southern Nigeria (Anabaraonye et al, 2018). In the past three decades, temperature has increased approximately 0.2 to 0.3°C per decade, with similar variability in wind direction and intensity in various parts of southern Nigeria (Njoku et al, 2020). These have had significant impacts on the rainfall pattern with the attendant consequences of flooding (Umar and Gray, 2023).…”

Section: Introductionmentioning

confidence: 99%

Effects of Climatic Variations and Changing Land Use/Land Cover on Flooding in Southern Nigeria

Chidiebere,

Godswill,

Anthony

et al. 2024

indones. j. env. man. sus.

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The prevalence of flooding in Nigeria in the past few years (with its devastating consequences) has become a source of concern for policymakers and researchers alike. Scholars have attributed the high frequency of flooding, particularly in the southern region of Nigeria, to several factors; climatic variation and land use/land cover changes are themes that fall under the domain of natural and anthropogenic causes of flooding, respectively. This study examined climatic variations and changing land use/land cover in southern Nigeria with the view of determining their synergistic effects on flooding. We adopted a mixed approach for data collection with the use of Geographic Information System (GIS), retrieval of primary data from meteorological stations in the region, and field surveys. Findings show a significant decrease in rural land uses like arable lands, wetlands, and undisturbed forests; while there was a corresponding increase in urban/peri-urban land uses like settlements and tree-crop plantations over the period from 1999 to 2019. The land use/land cover changes have manifested in the destabilization of the microclimate, distortion of the carbon circle, loss of biodiversity, reduction of ecosystem services of the natural areas, and flooding. The decadal rainfall trends over the past three decades show consistent extremities with mean rainfall duration decreasing while the mean intensity increases; aggravating soil erosion, urban runoff challenges, and flooding. Climatic variations (mainly extreme rainfall patterns) synergize with inefficient land use management to exacerbate flooding in southern Nigeria. While policymakers in this region may not have the standalone capacity to significantly control climate change and the consequential variations in the local microclimate, they can re engineer land use policies to eliminate or substantially degrade anthropogenic factors that exacerbate flooding.

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A Geospatial Expose of Flood-Risk and Vulnerable Areas in Nigeria

Cited by 9 publications

References 44 publications

Analysis of Flood Susceptibility in Northern Anambra State, Nigeria Using Geospatial Technology.

Analysis of Flood Susceptibility in Northern Anambra State, Nigeria Using Geospatial Technology.

Analyzing flash flood risk in a section of ntawogba creek, Port Harcourt city, Rivers State

Effects of Climatic Variations and Changing Land Use/Land Cover on Flooding in Southern Nigeria

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