Abstract:
Droughts pose a significant challenge to water resources, causing several socio-economic
consequences. The growing economy requires improved assessments of drought-related
impacts in the water sector, particularly under semi-arid environments where its climate is
getting drier and warmer. This study proposes a probabilistic model (copula approach) that
is intended to contribute to the drought risk assessment by providing an essential information
in drought prediction, decision making and management of the limited water resources
available during drought events. The three key pillars (i. Drought monitoring and early
warning systems, ii.vulnerability, and impact assessments, and iii. mitigation and response
measures) are recommended as the basis of national drought policy and management plans,
providing a practical way to organize multiple actions and activities that the country need to
implement to better prepare and respond to drought. In the study, drought events are
characterized by duration, severity and intensity, and the Standardized Precipitation Index
(SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) were used to
analyse hydrological drought based on gridded rain gauge and potential evapotranspiration
data referred to as Climatic Research Unit (CRU) covering a period of 1901-2018 at a time
scale of 12 months. Both SPI and SPEI were able to detect the spatial and temporal variation
of drought. But SPEI was able to identify more droughts in the severe to moderate categories
over wider areas in the country than SPI did. A set of seven homogeneous drought regimes
based on spatial characteristics of SPEI were obtained. Region 1 and 7 are relatively wet
regions, followed by region 2 and 6, while region 2 and 4 are relatively dry regions which
borders the Kgalagadi Basin. The optimal marginal distribution for drought duration,
severity and intensity were identified by employing the Akaike Information Criterion (AIC).
The drought duration was best described by the Generalized Extreme Value distribution
while the drought severity and intensity were both found to optimally fit with Weibull
distribution. Nine copula distributions, namely-Normal, Student’s t, Gumbel-Hougaard,
Rotated Gumbel, Clayton, Rotated Clayton, Joe Clayton, Frank, and Plackett copula
distributions were applied to construct the bivariate and trivariate distributions. The most
appropriate copula functions were determined also based on AIC. The joint distribution of
the best marginal cumulative density functions of duration and severity is found to optimally
fit Normal copula while Clayton copula distribution is the best copula function that describes
joint distribution of duration and intensity as well as the joint distribution of severity and
intensity over most grids in Botswana. The trivariate distribution of the univariate marginals
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of duration, severity and intensity is best fitted by Normal copula. The conditional return
period of drought of different categories was also determined in a multivariate context by
coupling duration, severity, intensity of drought based on copula distribution and cumulative
density functions. Most of the historical drought events over homogenous drought regimes
in Botswana have short duration, low severity, low intensity and short return period, with
drought regimes 1, 3, 4 and 7 having longer drought return periods than the other three zones
(2, 5 and 6). The risk of having long and severe droughts within the 10-year design lifetime
of any hydrological system was low in drought events with longer duration and high severity
across all the regions in Botswana. Improved information on drought characterization can
be useful in evaluating the water-supply capability and the needed supplementary water
resources during severe drought conditions for a specific water-supply system.