Journal of Water and Land Development

Konin, N’Da Jean Claude; N’go, Yao Alexis; Soro, Gneneyougo Emile; Goula, Bi Tié Albert

doi:10.24425/jwld.2021.139938

2021

DOI: 10.24425/jwld.2021.139938

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Journal of Water and Land Development

N’Da Jean Claude Konin,

Yao Alexis N’go,

Gneneyougo Emile Soro

et al.

Abstract: The aim of this study is to analyse the spatio-temporal evolution of hydro-rainfall variables in the Agnéby watershed in a disturbed climatic context. Rainfall data from the stations of Arrah,

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2023

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Run-off modelling of pervious and impervious areas using couple SWAT and a novel machine learning model in cross-rivers state Nigeria

Salele,

Dodo,

Sani

et al. 2023

Water Science &Amp; Technology

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Using the soil and water assessment tool (SWAT), runoff in pervious and impervious urban areas was simulated in this study. In the meantime, as a novel application of machine learning, the emotional artificial neural network (EANN) model was employed to enhance the SWAT obtained for this study. As a result of the EANN model's capabilities in rainfall–runoff phenomena, the SWAT-EANN couple model has been used to assess urban flooding. The pervious, impervious, and water body areas of the study area were classified and mapped to estimate the cover change over three epochs. Land use map, precipitation data, temperature (minimum and maximum) data, wind speed, relative humidity, soil map, solar radiation, and digital elevation model were used as inputs for modelling rainfall–runoff of the study area in the ArcGIS environment. The accuracy assessment of this study was excellent (root-mean-square error 1 mm of precipitation). It also revealed that (a) a land use map illustrating changes in impervious, pervious surface, and water body for 1998, 2008, and 2018; (b) runoff modelling using a historical pattern of rainfall–runoff changes (1998–2018); and (c) descriptive statistical analysis of the runoff results of the research. This research will aid in urban planning, administration, and development. Specifically, it will prevent flooding and environmental problems.

show abstract

Run-off modelling of pervious and impervious areas using couple SWAT and a novel machine learning model in cross-rivers state Nigeria

Salele,

Dodo,

Sani

et al. 2023

Water Science &Amp; Technology

View full text Add to dashboard Cite

show abstract

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Journal of Water and Land Development

Abstract: The aim of this study is to analyse the spatio-temporal evolution of hydro-rainfall variables in the Agnéby watershed in a disturbed climatic context. Rainfall data from the stations of Arrah,

Cited by 1 publication

References 12 publications

Run-off modelling of pervious and impervious areas using couple SWAT and a novel machine learning model in cross-rivers state Nigeria

Run-off modelling of pervious and impervious areas using couple SWAT and a novel machine learning model in cross-rivers state Nigeria

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