Effects of climate change and drought attributes in Nigeria based on RCP 8.5 climate scenario

Ogunrinde, Akinwale T.; Oguntunde, Phillip G.; Akinwumiju, Akinola S.; Fasinmirin, Johnson Toyin; Adawa, Ifeoluwa S.; Ajayi, Taiwo Adedayo

doi:10.1016/j.pce.2022.103339

Cited by 9 publications

(2 citation statements)

References 31 publications

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“…1). Benin is a tropical country, made up of three climatic Zones(Toko Imorou, 2020), Zone 1 which constitutes the Guinean region located in the south of the country and comprises eight (08) meteorological stations, has an equatorial climate with two rainy seasons and two dry seasons (Adam and Boko 1993); then Zone 2 which is the Sudano-Guinean region located in the center of Benin and contains seventeen (17) meteorological stations, with a slightly shorter rainy season (April to October); and nally the Sudanian region Zone 3 located in the north of the country, which is characterized by a wet season and a dry season and comprises dix(10) meteorological stations. We have carefully chosen 35 meteorological stations in this study.…”

Section: Study Areamentioning

confidence: 99%

Comparative analysis of meteorological drought based on the SPI and SPEI Indices in Benin

BOUKO,

Gao,

Mutelo

et al. 2024

Preprint

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In Benin, drought refers to a meteorological disaster that causes insufficient soil moisture and has adverse consequences on agriculture, the environment, and food security. However, to better understand the evolution of drought, the Mann–Kendall trend test, and comparative statistical evaluation of drought indices were applied in this paper. To achieve this objective, firstly, this article used daily precipitation, temperature, and relative humidity data from the National Meteorological Agency of Benin (NMAB) to calculate the standardized precipitation index (SPI), the standardized evapotranspiration of precipitation (SPEI), and used the Mann-Kendall trend test to quantify the importance of characteristic drought trends in the three (03) zones of Benin at different time scales. Then, we performed a statistical and comparative evaluation of SPI and SPEI based on Pearson's correlation coefficient, and cross-wavelet transform, to identify the strengths of SPI and SPEI. The results showed that (1) as the time scale increased, the temporal variations of the SPI and SPEI were increasingly consistent across all 3 areas of Benin; but there remains a difference between SPI and SPEI; (2) the drought trends identified by the SPI and the SPEI in certain areas of Benin were quite different. In Zone 2 (Central Benin), SPI showed an insignificant decreasing trend (P > 0.05), while SPEI showed a significant decreasing trend (P < 0.05) on all time scales. In Zone 3 (northern Benin), SPI showed a significantly increasing trend (P < 0.05) except for SPI-1, while SPEI showed a significantly decreasing trend except for SPEI-12. (3) the two indices (SPI/SPEI) show a strong correlation with each other; (4) Compared to the drought index (SPI/SPEI) and the standard relative humidity indices (SRHI), the SRHI-3 and SPEI-3 gave the largest correlation coefficient (r = 0.5), The SPEI could be more appropriate than SPI for monitoring drought in Benin. It should be noted that the adaptability of SPI and SPEI may be different across periods and regions.

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Section: Study Areamentioning

confidence: 99%

Comparative analysis of meteorological drought based on the SPI and SPEI Indices in Benin

BOUKO,

Gao,

Mutelo

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Recent flash floods in many countries showcase the direct impact of climate change on the hydrological cycle. Some countries are experiencing having higher and more intensified rainfalls [50][51][52][53] while some other countries are experiencing droughts [54][55][56][57] due to ongoing climate change. Each scenario is harmful or causes many adverse impacts on livelihood.…”

Section: Climate Change and Importance Of Flood Modelingmentioning

confidence: 99%

Evaluating the Efficacy of Different DEMs for Application in Flood Frequency and Risk Mapping of the Indian Coastal River Basin

Gangani,

Mangukiya,

Mehta

et al. 2023

Climate

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Floods are among the most occurring natural hazards that cause severe damage to infrastructure and loss of life. In India, southern Gujarat is affected during the monsoon season, facing multiple flood events in the Damanganga basin. As the basin is one of the data-scarce regions, evaluating the globally available dataset for flood risk mitigation studies in the Damanganga basin is crucial. In the present study, we compared four open-source digital elevation models (DEMs) (SRTM, Cartosat-1, ALOS-PALSAR, and TanDEMX) for hydrodynamic (HD) modeling and flood risk mapping. The simulated HD models for multiple flood events using HEC-RAS v6.3 were calibrated by adopting different roughness coefficients based on land-use land cover, observed water levels at gauge sites, and peak flood depths in the flood plain. In contrast to the previous studies on the Purna river basin (the neighboring basin of Damanganga), the present study shows that Cartosat-1 DEM provides reliable results with the observed flood depth. Furthermore, the calibrated HD model was used to determine the flood risk corresponding to 10, 25, 50, and 100-year return period floods calculated using Gumbel’s extreme value (GEV) and log-Pearson type III (LP-III) distribution techniques. Comparing the obtained peak floods corresponding to different return periods with the observed peak floods revealed that the LP-III method gives more reliable estimates of flood peaks for lower return periods, while the GEV method gives comparatively more reliable estimates for higher return period floods. The study shows that evaluating different open-source data and techniques is crucial for developing reliable flood mitigation plans with practical implications.

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A novel self-adjusting weight approximation procedure to minimize non-identical seasonal effects in multimodel ensemble for accurate twenty-first century drought assessment

Naz,

Ali

2024

Stoch Environ Res Risk Assess

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Effects of climate change and drought attributes in Nigeria based on RCP 8.5 climate scenario

Cited by 9 publications

References 31 publications

Comparative analysis of meteorological drought based on the SPI and SPEI Indices in Benin

Comparative analysis of meteorological drought based on the SPI and SPEI Indices in Benin

Evaluating the Efficacy of Different DEMs for Application in Flood Frequency and Risk Mapping of the Indian Coastal River Basin

A novel self-adjusting weight approximation procedure to minimize non-identical seasonal effects in multimodel ensemble for accurate twenty-first century drought assessment

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