Browsing by Author "Kenabatho, Piet K."

Now showing 1 - 7 of 7
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    Analysis of Long Term Drought Severity Characteristics and Trends across Semiarid Botswana using Two Drought Indices
    (Atmospheric research, 2018) Byakatonda, Jimmy; Parida, B.P.; Moalafhi, D.B.; Kenabatho, Piet K.
    Semiarid areas exhibit high climate variability whose frequency has increased in the recent past. This variability ultimately influences the spatial and temporal characteristics of droughts which in turn require a reliable drought index that can adequately characterize drought both in time and space. This study applied two drought indices viz.: Standardized precipitation index (SPI) and Standardized precipitation and evapotranspiration index (SPEI) at timescales of 1-, 3-, 6-, 12-, 18- and 24-months for a period of 1960–2016. The monotonic changes in drought severity were studied using Mann-Kendall Z-statistic and Sen's slope estimator. Both drought indices were able to detect the historical drought events of 1961/62–1965/66, 1980/81–1986/87, 1991/92, 2001/02–2005/06, 2009/10–2012/13 and 2014/15–2015/16. These events mainly coincided with El Niño years, hence the influence of El Niño southern oscillation (ENSO) on drought occurrence could not be ruled out. The drought evolutions were characterized by low frequency and longer durations at timescales of 12-, 18-, and 24-months. It was also observed that SPI overestimated drought severity during dry winter months while SPEI showed higher spatial coverage of drought vulnerability compared to SPI. Spatial and temporal trends of droughts showed significant wetting trends during the period 1960–1979 while during the entire period it was mostly drying tendencies after 1979/80. Pandamatenga and Shakawe showed higher vulnerability towards drying conditions during the period of analysis. The association between SPI and SPEI was also investigated using Spearman's rank correlation. Results from this analysis indicate that SPI accounts for >50% of the variations in SPEI and the association was strongest (96%) at 12-months timescale. The influence of temperature on drought evolutions was demonstrated at Francistown with SPI recording positive trends and SPEI negative ones. This study concludes that with the ongoing global warming, SPEI proves more robust in characterizing droughts in semiarid areas. It is hoped that findings from this study will augment ongoing efforts of mitigating negative impacts of increased incidences of climate variability especially in areas of agriculture and water resource management.
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    Analysis of Rainfall and Temperature Time Series to Detect long-term Climatic Trends and Variability over Semi-arid Botswana
    (Journal of Earth System Science, 2018) Byakatonda, Jimmy; Parida, B. P.; Kenabatho, Piet K.; Moalafhi, D. B.
    Arid and semi-arid environments have been identified with locations prone to impacts of climate variability and change. Investigating long-term trends is one way of tracing climate change impacts. This study investigates variability through annual and seasonal meteorological time series. Possible inhomogeneities and years of intervention are analysed using four absolute homogeneity tests. Trends in the climatic variables were determined using Mann–Kendall and Sen’s Slope estimator statistics. Association of El Niño Southern Oscillation (ENSO) with local climate is also investigated through multivariate analysis. Results from the study show that rainfall time series are fully homogeneous with 78.6 and 50% of the stations for maximum and minimum temperature, respectively, showing homogeneity. Trends also indicate a general decrease of 5.8, 7.4 and 18.1% in annual, summer and winter rainfall, respectively. Warming trends are observed in annual and winter temperature at 0.3 and 1.5% for maximum temperature and 1.7 and 6.5% for minimum temperature, respectively. Rainfall reported a positive correlation with Southern Oscillation Index (SOI) and at the same time negative association with Sea Surface Temperatures (SSTs). Strong relationships between SSTs and maximum temperature are observed during the El Niño and La Niña years. These study findings could facilitate planning and management of agricultural and water resources in Botswana.
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    Construction of 3D drought structures of meteorological drought events and their spatio-temporal evolution characteristics
    (Journal of Earth System Science, 2018) Byakatonda, Jimmy; Parida, B. P.; Kenabatho, Piet K.; Moalafhi, D. B.
    Arid and semi-arid environments have been identified with locations prone to impacts of climate variability and change. Investigating long-term trends is one way of tracing climate change impacts. This study investigates variability through annual and seasonal meteorological time series. Possible inhomogeneities and years of intervention are analysed using four absolute homogeneity tests. Trends in the climatic variables were determined using Mann–Kendall and Sen’s Slope estimator statistics. Association of El Niño Southern Oscillation (ENSO) with local climate is also investigated through multivariate analysis. Results from the study show that rainfall time series are fully homogeneous with 78.6 and 50% of the stations for maximum and minimum temperature, respectively, showing homogeneity. Trends also indicate a general decrease of 5.8, 7.4 and 18.1% in annual, summer and winter rainfall, respectively. Warming trends are observed in annual and winter temperature at 0.3 and 1.5% for maximum temperature and 1.7 and 6.5% for minimum temperature, respectively. Rainfall reported a positive correlation with Southern Oscillation Index (SOI) and at the same time negative association with Sea Surface Temperatures (SSTs). Strong relationships between SSTs and maximum temperature are observed during the El Niño and La Niña years. These study findings could facilitate planning and management of agricultural and water resources in Botswana.
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    Influence of climate variability and length of rainy season on crop yields in semiarid Botswana
    (Agricultural and Forest Meteorology, 2018) Byakatonda, Jimmy; Parida, B.P.; Kenabatho, Piet K.; Moalafhi, D.B.
    Climate variability and change is expected to affect agricultural productivity among other sectors. Studying the influence of this variability on crop production is one measure of generating climate change resilience strategies. In this study, the influence of climate variability on crop yield is investigated by determining the degree of association between climatic indices and crop yields of maize and sorghum using spearman’s rank correlation. The climatic indices used in this study are aridity index (AI), standardised precipitation evapotranspiration index (SPEI) at timescales of 1, 3, 6 and 12 months and southern oscillation index (SOI) representing El Niño southern oscillation (ENSO) influence on local climate. Local rainfall characteristics are expressed through length of the rainy season (LRS). Results reveal that ENSO influence is the most dominant across Botswana accounting for 85% and 78% variations in maize and sorghum yields respectively. Whereas AI and SPEI accounts for 70% and 65% variations in maize and sorghum respectively, LRS accounts for only 50% and 62% respectively. To facilitate agricultural planning, crop yield projections have been made using artificial neural network (ANN) models. The ANN projections indicate a likelihood of maize and sorghum yields declining by 51% and 70% respectively in the next 5 years. The high association between ENSO and crop yields in Botswana could further facilitate yield projections. Information generated from this study is useful in agricultural planning and hence strengthens farmers’ strategies in mitigating impacts of climate variability and change in semiarid areas.
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    Investigating Relationship between Drought Severity in Botswana and ENSO
    (Natural Hazards, 2020) Byakatonda, Jimmy; Parida, B. P.; Moalafhi, Ditiro B.; Kenabatho, Piet K.; Lesolle, David
    Influences of El Niño southern oscillation (ENSO) on weather systems have increased the frequency and amplitude of extreme events over the last century. This even continues to exacerbate the already warming earth, with 2014–2016 which coincided with the strongest El Niño years observed as the warmest period in recent past. This study presents an approach of characterizing droughts at various timescales and establishes teleconnections between ENSO and drought severity in Botswana. The study uses Standardized Precipitation Evaporation Index (SPEI) at timescales of 1, 3, 6, 12 and 24 month to characterize droughts and Pearson’s correlations to study the teleconnections between SPEIs and ENSO. Results from the study reveal that extreme droughts are a rare occurrence in Botswana though it is more prone to moderate droughts at 12 month SPEI with a probability of 19% in the north. The highest severe drought probability was 7% recorded in the east. Linear trends indicate increasing dryness of around 0.8% per decade. These results have demonstrated that warm sea surface temperatures combined with negative Southern Oscillation Index correspond to persistent negative SPEI values and thus are likely to result in dry conditions. Significant correlations were observed in the mid austral summer in December and January. Due to this relationship, the drought early warning systems could use ENSO as one of the instruments for predicting drought over the study area and hence in its management.
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    Prediction of Onset and Cessation of Austral Summer Rainfall and Dry Spell Frequency Analysis in Semiarid Botswana
    (Theoretical and Applied Climatology, 2019) Byakatonda, Jimmy; Parida, B. P.; Kenabatho, Piet K.; Moalafhi, D. B.
    Uncertainties in rainfall have increased in the recent past exacerbating climate risks which are projected to be higher in semiarid environments. This study investigates the associated features of rainfall such as rain onset, cessation, length of the rain season (LRS), and dry spell frequency (DSF) as part of climate risk management in Botswana. Their trends were analysed using Mann-Kendall test statistic and Sen’s Slope estimator. The rainfall-evapotranspiration relationships were used in formulating the rain onset and cessation criteria. To understand some of the complexities arising from such uncertainties, artificial neural network (ANN) is used to predict onset and cessation of rain. Results reveal higher coefficients of variation in onset dates as compared to cessation of rain. Pandamatenga experiences the earliest onset on 28th of November while Tsabong the latest on 14th of January. Likewise, earliest cessation is observed at Tshane on 22nd of February and the latest on 30th of March at Shakawe. The shortest LRS of 45 days is registered at Tsabong whereas the northern locations show LRS greater than 100 days. Stations across the country experience strong negative correlation between onset and LRS of − 0.9. DSF shows increasing trends in 50% of the stations but only significant at Mahalapye, Pandamatenga, and Shakawe. Combining the LRS criteria and DSF, Kasane, Pandamatenga, and Shakawe were identified to be suitable for rainfed agriculture in Botswana especially for short to medium maturing cereal varieties. Predictions of onset and cessation indicate the possibility of delayed onset by 2–5 weeks in the next 5 years. Information generated from this study could help Botswana in climate risk management in the context of rainfed farming.
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    Relating the dynamics of climatological and hydrological droughts in semiarid Botswana
    (Physics and Chemistry of the Earth, Parts A/B/C, 2018) Byakatonda, Jimmy; Parida, B.P.; Kenabatho, Piet K.
    Dynamics of droughts have been an associated feature of climate variability particularly in semiarid regions which impact on the response of hydrological systems. This study attempts to determine drought timescale that is suitable for monitoring the effects of drought on hydrological systems which can then be used to assess the long term persistence or reversion and forecasts of the dynamics. Based on this, climatological and hydrological drought indices characterized by Standardized precipitation evapotranspiration index (SPEI) and Standardized flow index (SFI) respectively have been determined using monthly rainfall, temperature and flow data from two major river systems. The association between climatological and hydrological droughts in Botswana has been investigated using these river systems namely: Okavango that is predominantly a storage type and Limpopo which is non-storage for a period of 1975–2014. Dynamics of climatological and hydrological droughts are showing trends towards drying conditions at both river systems. It was also observed that hydrological droughts lag climatological droughts by 7 months in Limpopo and 6 months in Okavango river systems respectively. Analyses of the association between climatic and flow indices indicate that the degree of association becomes stronger with increasing timescale at the Okavango river system. However in the Limpopo river system, it was observed that high timescales of 18- and 24-months were not useful in drought monitoring. 15-months timescale was identified to best monitor drought dynamics at both locations. Therefore SPEIs and SFIs computed at 15-months timescale have been used to assess the variability and long term persistence in drought dynamics through rescaled range analysis (R/S). H-coefficients of 0.06 and 0.08 resulted for Limpopo and Okavango respectively. These H-coefficients being significantly less than 0.5 is an indication of high variability and suggests a change in dynamics from the existing conditions in these river systems. To forecast possible changes, the nonlinear autoregressive with exogenous input (NARX) artificial neural network model has been used. Results from this model agree with those of the R/S and projects generally dry conditions for the next 40 months. Results from this study are helpful not only in choosing a proper timescale but also in evaluating the futuristic drought dynamics necessary for water resources planning and management.