Evaluation of the impact of climate change on the characteristics of drought in Sahel Region of Nigeria: 1971–2060

Ogunrinde, Akinwale T.; Oguntunde, Phillip G.; Akinwumiju, Akinola S.; Fasinmirin, Johnson Toyin

doi:10.1080/19376812.2020.1814826

Cited by 10 publications

(6 citation statements)

References 36 publications

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“…llnl.gov/cmip5/. RCP 8.5 was used for the study because its underlying assumptions are similar to the prevailing conditions in Sub-Saharan Africa, where Nigeria is located (Ogunrinde et al 2020). These assumptions are: high population growth, slow rate of economic development, and relatively slow tempo of technological change, coupled with increased greenhouse gas emission, moderate improvement rates of energy intensity and a dearth of good climate change policies (Riahi et al 2011;Ogunrinde et al 2020).…”

Section: Methodsmentioning

confidence: 99%

“…RCP 8.5 was used for the study because its underlying assumptions are similar to the prevailing conditions in Sub-Saharan Africa, where Nigeria is located (Ogunrinde et al 2020). These assumptions are: high population growth, slow rate of economic development, and relatively slow tempo of technological change, coupled with increased greenhouse gas emission, moderate improvement rates of energy intensity and a dearth of good climate change policies (Riahi et al 2011;Ogunrinde et al 2020). HadGEM2-ES and IPSL-CM5A models were selected for use because they have been shown to simulate the observed climate of Nigeria well (Third National Communication of the Federal Republic of Nigeria under the UNFCC), while ICHEC-EC-EARTH was used because it is not a widely used model for climate change studies in Nigeria.…”

Section: Methodsmentioning

confidence: 99%

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Rainfall dynamics in the Sudano-Sahelian zone of Nigeria under RCP 8.5

Adegun¹,

Odunuga²

2022

BOGPGS

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The study analysed the historical (1961–90) and projected rainfall variability for the rainy season expected in the near future (2021–50) at selected locations within the Komadugu-Yobe and Sokoto-Rima River Basins in the Sudano-Sahelian zone of northern Nigeria. Three models were utilised, and analyses were based on Representative Concentration Pathway (RCP) 8.5. Projected changes in mean, level of variability and distribution of rainfall were analysed using the Relative Percentage Change Method and the Precipitation Concentration Index (PCI), while the performance of the models was evaluated using the Nash–Sutcliffe Efficiency (NSE) index. The results show that changes in mean rainfall will be predominantly negative, with a minimum and maximum level of change of ˗1.02 per cent at Nguru, and ˗70.4 per cent at Jos, based on the IPSL-CM5A and HadGEM2-ES models, respectively. The rainy season of the baseline period varied between low and moderate variability, while the near future ranges between low and high levels of variability. The validation indicates acceptable levels of performance, with most values ranging between 0.0 and 1.0. The PCI for the near future suggests that the rainy season will be mainly characterised by uniform and near-uniform rainfall distribution. Hence, the projected negative changes and high variability of rainfall at some locations call for the development of an Adaptive Benefit Mechanism that will minimise future natural resource conflicts.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Rainfall dynamics in the Sudano-Sahelian zone of Nigeria under RCP 8.5

Adegun¹,

Odunuga²

2022

BOGPGS

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“…Previous studies found divergence in trends of drought characteristics between SPI and SPEI in observations (Stagge et al, 2017;Karimi et al, 2020;Ionita and Nagavciuc, 2021), historical climate simulations (Chiang et al, 2021) and future climate projections (e.g. Arnell and Freeman, 2021;García-Valdecasas Ojeda et al, 2021;Wang et al, 2021;Ogunrinde et al, 2021), with SPEI indicating increased drying compared to SPI. Increases in PET under a changing climate, combined with the high sensitivity of SPEI to PET changes, cause amplified projections of climatological drying and even a reversal of wetting trends in some parts of the world compared to when only changes in precipitation are considered (Cook et al, 2014).…”

Section: Differences Between Spi and Spei Projectionsmentioning

confidence: 95%

Projected changes in droughts and extreme droughts in Great Britain strongly influenced by the choice of drought index

Reyniers

Osborn

Addor

et al. 2022

Preprint

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Abstract. Droughts cause enormous ecological, economical and societal damage, and are already undergoing changes due to anthropogenic climate change. Understanding, anticipating and communicating these changes is essential to a wide range of stakeholders. In this study, the projected impacts of climate change on future atmospheric droughts in Great Britain were assessed for two warming levels (2 °C and 4 °C above pre-industrial levels) using the UKCP18 regional climate projections. As projected changes can be very sensitive to the choice of drought index, two indices were compared: the Standardized Precipitation Index (SPI), and the Standardized Precipitation Evapotranspiration Index (SPEI, which unlike the SPI, accounts for increasing potential evapotranspiration). The SPI and SPEI were used to quantify drought frequency, extent and duration of all droughts and of only extreme droughts. To provide context, aridity and seasonal precipitation and potential evapotranspiration changes were also assessed, as well as seasonal contributions to dryness at a yearly time scale. The UKCP18 regional simulations project (strongly) increasing drought frequency and extent due to climate change based on the SP(E)I almost everywhere in Great Britain. Importantly, the relative increase in frequency and extent is much more pronounced for extreme droughts than for more moderate droughts. Increasing longer-term dry conditions can be attributed mostly to more frequent dry and extremely dry summers, for which normal to wet winters are decreasingly able to compensate (even where winters are projected to become wetter). In general, using the SPEI results in far greater increases in drought frequency and extent than using the SPI. These differences are so substantive that at +2 °C the SPEI6-based projected changes reach a similar magnitude to the SPI6-based changes at +4 °C. Finally, projected changes in the distribution of drought durations depend on the drought index, region and warming level. These results illustrate that the choice of atmospheric drought index can have a decisive influence on changes in projected drought characteristics, and therefore users of these indices should be aware of the importance of potential evapotranspiration in their intended context when choosing a drought index. The stark differences between SPI- and SPEI-based projections highlight the need to understand the interplay between increasing atmospheric evaporative demand and moisture availability under a changing climate.

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“…The SPI allows monitoring and analysis of meteorological drought through the transformation of aggregated rainfall data at different time scales [34]. SPI is a statistical monthly indicator (e.g., 3, 6, 12, and 24 months) that is fitted to a long-term precipitation time series using a gamma distribution function, as given by the following equation [35,36]:…”

Section: Drought Indicesmentioning

confidence: 99%

Assessment of Meteorological and Agricultural Drought Indices under Climate Change Scenarios in the South Saskatchewan River Basin, Canada

et al. 2023

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Climate change has amplified the severity of droughts with potentially adverse impacts on agriculture in western Canada. This study assessed meteorological and agricultural drought in the Southern Saskatchewan River Basin (SSRB) using an array of drought indices, including the Standardized Precipitation Index (SPI), the Standardized Precipitation-Evapotranspiration Index (SPEI), the Self-Calibrated Palmer Drought Severity Index (scPDSI), the Soil Moisture Deficit Index (SMDI), and the Evapotranspiration Deficit Index (ETDI). These indices were evaluated using multiple regional climate model (RCM) projections assuming 1.5, 2.0, and 3.0 °C thresholds of global warming. A modified Soil and Water Assessment Tool (SWAT-M) was used to simulate the soil water content (SWC), actual evapotranspiration (AET), and potential evapotranspiration. The results of a sensitivity analysis using the SUFI-2 method in SWAT-CUP showed that the model performed well with BIAS lower than 10% and NSE and R higher than 0.7, and the range of SWC output closely matched the observed SWC. According to the RCM projections, the annual precipitation increases for all three global temperature thresholds while the annual mean temperature increases at a greater rate than the rise in global mean temperature. The projected PDSI and the SPEI suggest that drought duration and severity will exceed historical values while SPI will remain largely unchanged. Furthermore, severe drought conditions (SMDI < 2.0) are more frequent under the 3.0 °C global temperature scenario. The mean ETDI was historically 0.58 while the projected value is 0.2, 0.1, and −0.2 for the first to third scenarios, respectively. Simulated values, spatial maps, and heat maps of SMDI and ETDI illustrated that Canesm2.CRCM5 projects the driest conditions among all the RCMs. Agricultural drought indices, which incorporate SWC data, show more significant effects than meteorological drought indices. The increasing dryness will potentially impact agricultural crop production, particularly under the third scenario (3 °C) in the SSRB.

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Evaluation of the impact of climate change on the characteristics of drought in Sahel Region of Nigeria: 1971–2060

Cited by 10 publications

References 36 publications

Rainfall dynamics in the Sudano-Sahelian zone of Nigeria under RCP 8.5

Rainfall dynamics in the Sudano-Sahelian zone of Nigeria under RCP 8.5

Projected changes in droughts and extreme droughts in Great Britain strongly influenced by the choice of drought index

Assessment of Meteorological and Agricultural Drought Indices under Climate Change Scenarios in the South Saskatchewan River Basin, Canada

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