Analysis of the Spatio-Temporal Rainfall Variability in Cameroon over the Period 1950 to 2019

Ebodé, Valentin Brice

doi:10.3390/atmos13111769

Cited by 7 publications

(8 citation statements)

References 25 publications

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“…Using a the arithmetic mean of three different precipitation products, our analyses show, respectively, increasing and decreasing trends in annual precipitation in the southern and northern parts of the GGB. Annual precipitation decline in the northern part of the GGB is consistent with results from other studies in the region using precipitation estimates from CHIRPS (Bichet & Diedhiou, 2018; Nkiaka, 2022) and Climate Research Unit (Ebodé, 2022). Rainfall decline in Central Equatorial Africa has been attributed partly to sea surface temperature variations over the Indo‐Pacific linked with the enhanced and westward extended tropical Walker circulation (Hua et al, 2016).…”

Section: Discussionsupporting

confidence: 89%

Changes in climate, vegetation cover and vegetation composition affect runoff generation in the Gulf of Guinea Basin

Nkiaka,

Okafor

2024

Hydrological Processes

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Although considerable effort has been deployed to understand the impact of climate variability and vegetation change on runoff in major basins across Africa, such studies are scarce in the Gulf of Guinea Basin (GGB). This study combines the Budyko framework and elasticity concept along with geospatial data to fill this research gap in 44 nested sub‐basins in the GGB. Annual rainfall from 1982 to 2021 show significant decreasing and increasing trends in the northern and southern parts of the GGB, respectively. Annual potential evapotranspiration (PET) also shows significant increasing trends with higher magnitudes observed in the northern parts of the GGB. Changing trends in climate variables corroborates with shift to arid and wetter conditions in the north and south, respectively. From 2000 to 2020 vegetation cover estimated using enhanced vegetation index (EVI) shows significant increasing trends in all sub‐basins including those experiencing a decline in annual rainfall. Vegetation composition measured using vegetation continuous fields (VCFs) from 2000 to 2020 show an increase in tree canopy cover (TC), a decline in short vegetation cover and marginal changes in bare ground cover (BG). Elasticity coefficients show that a 10% increase in annual rainfall and PET may lead to a 33% increase and 24% decline in runoff, respectively. On the other hand, a 10% increase in EVI may lead to a 4% decline in runoff while a 10% increase in TC, SV and BG may reduce runoff by 4% and increase runoff by 3% and 2%, respectively. Even though changes are marginal, decomposing vegetation into different parameters using EVI and VCFs may lead to different hydrological effects on runoff which is one of the novelties of this study that may be used for implementing nature‐based solutions. The study also demonstrates that freely available geospatial data together with analytical methods are a promising approach for understanding the impact of climate variability and vegetation change on hydrology in data‐scarce regions.

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Section: Discussionsupporting

confidence: 89%

Changes in climate, vegetation cover and vegetation composition affect runoff generation in the Gulf of Guinea Basin

Nkiaka,

Okafor

2024

Hydrological Processes

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“…This allowed us to make much more precise supervised classi cations (close to reality). Their formulas are as follows (Ebodé, 2022):…”

Section: Discussionmentioning

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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“…This is data from the National Centers for Environmental Prediction (NCEP). It has been shown that these data could constitute a good alternative for rainfall study and modelling ows in ungauged regions (Nkiaka et al, 2017;Ebodé, 2022c). All the meteorological data used were collected over the period 1998-2008.…”

Section: Datamentioning

confidence: 99%

Effects of climate and anthropogenic changes on future variability in flows in the So’o River Basin (South of Cameroon)

Ebodé¹

2022

Preprint

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Due to climate and environmental changes, sub-Saharan Africa (SSA) has experienced several drought and flood events in recent decades with serious consequences on the economy of the sub-region. In this context, the region needs to enhance its capacity in water resources management, based on reliable forecasts. The objective of this article was to study the evolution future (near (2022-2060) and distant (2061-2100)) flows in the So’o River Basin (SRB) in Cameroon. The Cellular Automata (CA)-Markov was used to predict the future land cover evolution of the basin, and the outputs of two regional climate models-RCMs (RCA4 and CCCma) were used to predict the future climate in the basin. Distribution mapping was used for correcting precipitation and temperature biases in the outputs of the climate models used. The soil and water assessment tool (SWAT) model was used to simulate the future flows in the SRB. The results obtained show that a change in precipitation in line with the predictions of the CCCma model will lead to a decrease in river discharge in the basin, except under the RCP8.5 scenario during the second period (2061-2100), where will note an increase compared to the historical period of approximately +4%. It is projected that the decrease in precipitation and river discharge will occur mostly in the autumn months during 2020s, 2040s and 2070s. Results from the RCA4 model project an increase in precipitation which will lead to an increase in river discharge by more than +50%, regardless of the period and the scenario considered. In general, this increase will be greater during the dry seasons (winter and summer), while the decades at the end of the century (2080 to 2100) will be the wettest. An increase in discharges was noted in some cases despite a drop in rainfall, particularly in the case of discharges simulated for the second period (2061-2100) from the outputs of the CCCma model. This seems to be a consequence of the increase in impervious spaces, all the more the runoff increases during this period according to the model. Results from this study could be used to enhance water resources management in the basin investigated and the region.

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Analysis of the Spatio-Temporal Rainfall Variability in Cameroon over the Period 1950 to 2019

Cited by 7 publications

References 25 publications

Changes in climate, vegetation cover and vegetation composition affect runoff generation in the Gulf of Guinea Basin

Changes in climate, vegetation cover and vegetation composition affect runoff generation in the Gulf of Guinea Basin

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

Effects of climate and anthropogenic changes on future variability in flows in the So’o River Basin (South of Cameroon)

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