Machine Learning Based Prediction of Urban Flood Susceptibility from Selected Rivers in a Tropical Catchment Area

Ekwueme, Benjamin Nnamdi

doi:10.28991/cej-2022-08-09-08

Cited by 22 publications

(5 citation statements)

References 46 publications

(65 reference statements)

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“…Water resources management and related risks are increasingly becoming an important concern of contemporary society (Ebodé et Ebodé et al, 2024c). Among the wide range of existing hydrological risks, ooding appears to be one of the most devastating, considering the enormous damage it often causes (Samanta et al, 2018;Krisnayanti et al 2022;Ekwueme, 2022;Manzoor et al, 2022). Between the 1990s and 2010s, oods caused the deaths of more than 158,000 people around the world (CRED, 2018).…”

Section: Introductionmentioning

confidence: 99%

Flood susceptibility mapping in the Tongo Bassa watershed through GIS, remote sensing and frequency ratio model

Ebodé

2024

Preprint

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Flooding constitutes a major problem for the inhabitants of Douala City in general and those of the Tongo Bassa watershed (TBW) in particular. Faced with this situation, public authorities need to put in place measures to mitigate the vulnerability of populations to these disasters. This article aims to map flooding risk areas in the TBW using geographic information system (GIS), field data (historical flood points), remote sensing data (Sentinel II image) and frequency ratio (FR) model. Six independent variables linked to floods were considered (land use and land cover patterns, altitudes, slopes, drainage densities, distances from watercourses and soil types). The map of land use patterns was obtained following the supervised classification of a Landsat 8 image using ENVI 5.2 software. The other five (05) variables were automatically generated from a digital terrain model using ArcGIS 10.2 software. The map produced shows that 1.41%, 8.88%, 28.51%, 33.86% and 27.33% of the basin area are respectively delimited into very low, low, medium, high and very high flood vulnerability classes. High and very high flooding risk areas (those where flooding is most likely to occur) occupy more than half of the basin (61.19%). These areas are characterized by significant imperviousness, low altitudes, weak slopes, significant proximity to watercourses and clayey soils. Most of the houses in the basin (66.92%) are located in areas affected by these two levels of exposure (high and very high). With respective success and prediction accuracy rates of 89% and 96.78%, a certain confidence deserves to be placed on the map of flooding risk areas produced. The results of this study could serve as decision-support tools in the context of the various developments undertaken by the public authorities, to fight against flooding in this basin.

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Section: Introductionmentioning

confidence: 99%

Flood susceptibility mapping in the Tongo Bassa watershed through GIS, remote sensing and frequency ratio model

Ebodé

2024

Preprint

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“…Mapping of glaciers regularly using conventional methods of surveying is difficult due to the high altitude, inaccessibility, ruggedness, and harsh climatic conditions of the mountainous terrain. Remote sensing (Ekwueme (2022), Mann and Gupta (2022) and Jabal et al (2022), Dibs et al 2023a, Kanmani et al 2023) provides an alternative for mapping and monitoring of glaciers in mountainous terrain (Hall et al 2003). Numerous satellites have been successfully used for mapping and monitoring glaciers' facies and features.…”

Section: Introductionmentioning

confidence: 99%

Monitoring of spatio-temporal glaciers dynamics in Bhagirathi Basin, Gharhwal Himalayas using remote sensing data

Sandhu,

Gusain,

Arora

et al. 2024

Environ Earth Sci

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Glacier retreat represents a highly sensitive indicator of climate change and global warming. Therefore, timely mapping and monitoring of glacier dynamics is strategic for water budget forecasting and sustainable management of water resources. In this study, Landsat satellite images of 2000 and 2015 have been used to estimate area extent variations in 29 glaciers of the Bhagirathi basin, Garhwali Himalayas. ASTER DEM has been used for extraction of glacier terrain features, such as elevation, slope, area, etc. It is observed from the analysis that Bhagirathi sub-basin has a maximum glaciated area of ~ 35% and Pilang has the least with ~ 3.2%, whereas Kaldi sub-basin has no glacier. In this region, out of 29 glaciers, 25 glaciers have shown retreat, while only 4 glaciers have shown advancement resulting in a total glacier area loss of ~ 0.5%, while the retreat rate varies from ~ 0.06 m/yr to ~ 19.4 m/yr. Dokarni glacier has maximum retreat rate (~ 19.4 m/yr), whereas Dehigad has maximum advancing rate (~ 10.1 m/yr). Glaciers retreat and advance have also been analyzed based on terrain parameters and observed that northern and southern orientations have shown retreat, whereas the area change is highly correlated with glacier length. The study covers more than 65% of the total glaciated area and based on the existing literature represents one of the most exhaustive studies to cover the highest number of glaciers in all sub-basins of the Bhagirathi basin.

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“…Currently, much research considers the impacts of natural disasters on socioeconomic factors (Ekwueme, 2022;Mann and Gupta, 2022) and food security (Jabal et al, 2022) or the impacts of extreme disasters on sustainable business development (Habib and Mourad, 2023). While these studies can help readers understand climate change in depth, they neglect to consider livestock factors.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the coupling coordination of livestock production, residential consumption, and resource and environmental carrying capacity in China

Zhou,

Wu,

et al. 2024

Front. Sustain. Food Syst.

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Increasing demands for livestock products have stimulated rapid increases in the number of livestock and the scale of farming, thus increasing pressure on resources and the environment. Coordinating the development of livestock production (LP) with residential consumption (RC), resources and the environmental carrying capacity (RECC) is important to ensure sustainable development. In this study, the entropy weight method and the improved-coupling coordination degree (CCD) model were used to identify the spatial–temporal coordination development characteristics of livestock production-residential consumption-resource and environmental carrying capacity (LRRE). Furthermore, the spatial autocorrelation model (SAM) and gray model (GM) were used to analyze the spatial aggregation characteristics and future development trends of the CCDs of the LRRE in China. The findings show that the CCDs of the LRRE values in 31 Chinese provinces increased from 2005 to 2020, but no provinces reached a high coordination level. Specifically, the coordinated development level of LRRE is relatively high in the central, eastern and northeastern regions and relatively low in the western region. The spatial autocorrelation analysis confirmed that the high-high (H-H) aggregation areas were mainly distributed in the northeastern, eastern, and central regions, while low-high (L-H) agglomeration was distributed in the western region. This phenomenon is mainly attributed to the continuous expansion of the scale of livestock production in western China. Regions with relatively developed economies have more funds to invest in environmental protection projects. Using GM method, we find that the CCDs of LRRE in 31 provinces in China will increase from 2021 to 2030, and all provinces will reach the basic coordination level. However, most of the western regions will barely reach the basic coordination level. This result indicates that the low level of LRRE development in western China may be difficult to change in the short term. The level of coordinated LRRE development in the relatively developed eastern region is increasing. The spatial layout of China’s livestock industry should be appropriately adjusted, its expansion rate in the western region should be decreased, and the ecological environment of the areas bordering the western and central regions should be improved. These findings have practical implications for other large livestock production countries. Promoting the coordinated development of LRRE is also an important condition for agricultural transformation in developing countries, especially for improving the environment in key areas of the livestock industry.

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Machine Learning Based Prediction of Urban Flood Susceptibility from Selected Rivers in a Tropical Catchment Area

Cited by 22 publications

References 46 publications

Flood susceptibility mapping in the Tongo Bassa watershed through GIS, remote sensing and frequency ratio model

Flood susceptibility mapping in the Tongo Bassa watershed through GIS, remote sensing and frequency ratio model

Monitoring of spatio-temporal glaciers dynamics in Bhagirathi Basin, Gharhwal Himalayas using remote sensing data

Analysis of the coupling coordination of livestock production, residential consumption, and resource and environmental carrying capacity in China

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