Analysis of drought conditions over major maize producing provinces of South Africa

Adisa, Omolola M.; Botai, Joel Ongego; Adeola, Abiodun M.; Botai, Christina M.; Hassen, Abubeker; Darkey, Daniel; Tesfamariam, Eyob Habte; Adisa, Abidemi T.; Adisa, A. F.

doi:10.2480/agrmet.d-18-00049

Cited by 16 publications

(6 citation statements)

References 36 publications

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“…In South Africa, the SPI drought index has been used to study drought characteristics at different timescales [13,15,16,[34][35][36][37] at national and regional level. Studies by [13,15] focused on drought characteristics in the Free State and North West as well as in the Western Cape provinces, respectively.…”

Section: Introductionmentioning

confidence: 99%

Drought Risk Analysis in the Eastern Cape Province of South Africa: The Copula Lens

Botai

Adeola

et al. 2020

Water

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This research study was carried out to investigate the characteristics of drought based on the joint distribution of two dependent variables, the duration and severity, in the Eastern Cape Province, South Africa. The drought variables were computed from the Standardized Precipitation Index for 6- and 12-month accumulation period (hereafter SPI-6 and SPI-12) time series calculated from the monthly rainfall data spanning the last five decades. In this context, the characteristics of climatological drought duration and severity were based on multivariate copula analysis. Five copula functions (from the Archimedean and Elliptical families) were selected and fitted to the drought duration and severity series in order to assess the dependency measure of the two variables. In addition, Joe and Gaussian copula functions were considered and fitted to the drought duration and severity to assess the joint return periods for the dual and cooperative cases. The results indicate that the dependency measure of drought duration and severity are best described by Tawn copula families. The dependence structure results suggest that the study area exhibited low probability of drought duration and high probability of drought severity. Furthermore, the multivariate return period for the dual case is found to be always longer across all the selected univariate return periods. Based on multivariate analysis, the study area (particularly Buffalo City, OR Tambo and Alfred Zoo regions) is determined to have higher/lower risks in terms of the conjunctive/cooperative multivariate drought risk (copula) probability index. The results of the present study could contribute towards policy and decision making through e.g., formulation of the forward-looking contingent plans for sustainable management of water resources and the consequent applications in the preparedness for and adaptation to the drought risks in the water-linked sectors of the economy.

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Section: Introductionmentioning

confidence: 99%

Drought Risk Analysis in the Eastern Cape Province of South Africa: The Copula Lens

Botai

Adeola

et al. 2020

Water

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“…It had been shown that the SPEI shown a consistent performance in drought monitoring in Pakistan compared to 15 various drought indices 35 . In a recent study by Omolola et al 36 for 4 major maize producing South African provinces (identical to the study area used in this study) discovered that the SPEI-3, calculated based on meteorological data from 27 ground stations, was significantly correlated with maize yield during the growing season from 1990 to 2015. Supported by this result, this study adopts drought analysis based on SPEI 3-month time scales.…”

Section: Introductionmentioning

confidence: 59%

“…The SPEI considers the effect of potential evapotranspiration (PET) using the FAO-56 Penman–Monteith equation, thereby representing a simple climatic water balance. In this study, we used the 3-month time scale SPEI data set (SPEI-3) 36 . The time window was set in parallel with the HMD time window (5-months) to capture the yield variability due to drought stress.…”

Section: Methodsmentioning

confidence: 99%

Impact of climate extreme events and their causality on maize yield in South Africa

Simanjuntak,

Gaiser,

Ahrends

et al. 2023

Sci Rep

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Extreme climate events can have a significant negative impact on maize productivity, resulting in food scarcity and socioeconomic losses. Thus, quantifying their effect is needed for developing future adaptation and mitigation strategies, especially for countries relying on maize as a staple crop, such as South Africa. While several studies have analyzed the impact of climate extremes on maize yields in South Africa, little is known on the quantitative contribution of combined extreme events to maize yield variability and the causality link of extreme events. This study uses existing stress indices to investigate temporal and spatial patterns of heatwaves, drought, and extreme precipitation during maize growing season between 1986/87 and 2015/16 for South Africa provinces and at national level and quantifies their contribution to yield variability. A causal discovery algorithm was applied to investigate the causal relationship among extreme events. At the province and national levels, heatwaves and extreme precipitation showed no significant trend. However, drought severity increased in several provinces. The modified Combined Stress Index (CSIm) model showed that the maize yield nationwide was associated with drought events (explaining 25% of maize yield variability). Heatwaves has significant influence on maize yield variability (35%) in Free State. In North West province, the maize yield variability (46%) was sensitive to the combination of drought and extreme precipitation. The causal analysis suggests that the occurrence of heatwaves intensified drought, while a causal link between heatwaves and extreme precipitation was not detected. The presented findings provide a deeper insight into the sensitivity of yield data to climate extremes and serve as a basis for future studies on maize yield anomalies.

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“…While these indices have been extensively employed in various studies, our approach diverges significantly in its utilization of these indices. Contrary to the conventional use of default timescales in previous studies [19,35], this research strategically categorizes these timescales (3 and 6-month timescales) into specific seasons. This categorization is carefully aligned with the various stages of the maize growing season-computing, identifying, monitoring and characterizing droughts aids in developing and implementing drought management and mitigation strategies.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Impact of Agricultural Drought on Yield over Maize Growing Areas, Free State Province, South Africa, Using the SPI and SPEI

Makuya,

Tesfuhuney,

Moeletsi

et al. 2024

Sustainability

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Maize (Zea mays L.) is an essential crop in South Africa serving as a staple food; however, agricultural drought threatens its production, resulting in lower yields. This study aimed to assess the impact of agricultural drought on maize yield in the major areas (Bethlehem, Bloemfontein, and Bothaville) that produce maize in the Free State Province from 1990 to 2020. The study used the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) to examine drought occurrences and severity during the maize growing season (October–March). The Standardized Yield Residuals Series (SYRS), Crop Drought Resilient Factor (CDRF), Spearman’s Rank Correlation (rs), and yield loss rate were employed to emphasize agricultural drought impact on maize yield. The results based on the SPI and SPEI show that drought frequently occurred in Bethlehem, followed by Bloemfontein and Bothaville. Drought severity indicated that moderate droughts were prevalent in Bethlehem, while severe droughts were in all areas (Bethlehem, Bloemfontein, and Bothaville) and extreme droughts in Bloemfontein. The agricultural drought’s impact on maize varied across growth seasons and areas. Notably, the lowest SYRS value of −2.38 (1991/92) was observed in Bethlehem. An extremely strong significant correlation (rsSPEI-6 vs SYRS = 0.83, p = 1.07 × 10−8) was observed between the SPEI and SYRS in Bloemfontein during the October–November–December–January–February–March (ONDJFM) season. The CDRF indicated that maize yield was severely non-resilient (CDRF < 0.8) to drought in Bethlehem (CDRF = 0.27) and Bloemfontein (CDRF = 0.33) and resilient (CDRF = 1.16) in Bothaville. The highest maize yield loss of −88.62% was observed in Bethlehem due to extreme agricultural drought. The results suggest that, historically, agricultural drought was a threat to maize production in the studied areas, particularly in Bethlehem and Bloemfontein. This underscores the implementation of sustainable agricultural practices, such as drought-resistant varieties in these areas, to mitigate the impacts of climate change, especially drought, and ensure food security. This is a step toward achieving Sustainable Development Goal 2 (Zero Hunger).

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Analysis of drought conditions over major maize producing provinces of South Africa

Cited by 16 publications

References 36 publications

Drought Risk Analysis in the Eastern Cape Province of South Africa: The Copula Lens

Drought Risk Analysis in the Eastern Cape Province of South Africa: The Copula Lens

Impact of climate extreme events and their causality on maize yield in South Africa

Assessing the Impact of Agricultural Drought on Yield over Maize Growing Areas, Free State Province, South Africa, Using the SPI and SPEI

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