Journal of Environmental Protection, 2011, 2, 803-816
doi:10.4236/jep.2011.26092 Published Online August 2011 (http://www.SciRP.org/journal/jep)
Copyright © 2011 SciRes. JEP
803
The Spatio-Temporal-Severity Dynamics of
Drought in Botswana
Nnyaladzi Batisani
Department of Agricultural Engineering and Land Planning, University of Botswana, Gaborone, Botswana.
Email: nnyaladzi.batisani@gmail.com
Received March 22nd, 2011; revised May 7th, 2011; accepted June 18th, 2011.
ABSTRACT
Drought is a reoccurring natural hazard in semi-arid regions. However, despite its regular occurrence disaster man-
agers are still to develop concrete measures of mitigating and adapting to it. A fist step to the development of such
measures is the determination of the spatia l drought vulnerability variability. The goal of this pap er is to determine the
spatio-temporal severity drought occurrence, which is vital for drought mitigation planning and resources allocation
during responses. To reach this goal, th e pap er de termines th e p robab ilit y o f occurren ce of d ifferen t dro ugh t ca tego ries
based on the Standardized Precipitation Index. The analysis identifies areas vulnerable to agricultural and hydrologi-
cal droughts at various severity levels. The spatial variation in drought occurrence suggests that drought vulnerability
maps should be availed to disaster planners for efficient resource allocation during responses and mitigation and de-
velopment of ada pt ati o n measures.
Keywords: Drought, Vulnerability, Climate Change, Disaster Management , Standardized Precipitation Index
1. Introduction
Drought is one of the most devastating but least under-
stood weather phenomenons. Drought can erupt in a
matter of months or gradually creep up on an unsuspect-
ing society over several seasons. It is rarely forecasted
with any skill, and goes unobserved until its impacts
have already occurred. [1,2]]noted that drought is a com-
plex hydro meteorological phenomenon caused by mete-
orological anomalies that reduce precipitation. While [3]
observed that drought is a major climatic hazard and an
extreme meteorological event that originates from a defi-
ciency of precipitation leading to water shortage for
some activity or group. Drought is the world’s costliest
natural disasters causing an average of $6 - $8 billion in
global damages annually and collectively affects more
people than any other natural disaster [4]. [5] agreed and
noted that drought affects a large number of people
worldwide and cause tremendous economic losses, envi-
ronmental damage and social hardships. [6] described
drought, as one of the most damaging climate-related
hazards and also among the most multifaceted and least
understood natural hazards. [7] underscored this assertion
and noted that drought ranks high among natural disas-
ters based on the number of persons directly affected.
Drought has significant adverse effect on the socio-eco-
nomic, agricultural, and environment conditions [8]. Yet,
drought is one of the least understood of all weather
phenomena [9].
Drought is categorized into four types, namely mete-
orological, hydrological, agricultural, and socioeconomic
[10-12]. The latter form may be considered a conse-
quence of the other drought types. Unless societal de-
mand consistently exceeds natural supply, a socioeco-
nomic drought will not occur without one or more of the
other droughts [13]. A discussion of different types of
drought can be found in [10,14]. This paper considers
only the physical based forms of drought. Drought differs
from other natural hazards because its impacts may pro-
long for a long period of time even after the wet season
has commenced making the prediction of its onset and
termination difficult [10,15,16]. Therefore, timely infor-
mation on drought onset, its extent, and intensity is cru-
cial for the reduction of drought related losses and sub-
sequently the overall drought vulnerability of a commu-
nity or ecosystem.
Vulnerability is generally defined as the susceptibility
of a society or system to damage and is characterized in
terms of one or more of the sensitivity or exposure of a
system (people or place) to shocks, stresses or distur-
bances, the state of the system relative to a threshold of
The Spatio-Temporal-Severity Dynamics of Drought in Botswana
804
damage, and the system’s ability to adapt to changing
conditions [17-23]. The terms “shocks,” “disturbances,”
“stresses” and “perturbations” are often used to refer to
exogenous forces that have the potential of creating an
adverse impact [24,25]. A force is seen to be “exoge-
nous” if its occurrence is beyond the power of the unit of
analysis such as the individual or household [25]. These
forces include phenomena such as drought, climate vari-
ability and change, floods, hurricanes and market fluc-
tuations. [26] underscored that vulnerability plays a
critical role in the relationship between a hazard and so-
ciety. While [27] noted that the magnitude of a disaster is
a function of its magnitude and also of the society’s vul-
nerability.
Vulnerability has emerged as one of the central orga-
nizing concepts on global environmental change research
[28-32]. Vulnerability assessment is a significant aspect
of climate variability and change impacts and adaptation
research [33]. It is referred to in the United Nations
Framework Convention on Climate Change where com-
mitments are made to address vulnerable regions and
peoples [34,35]. [36,37] observed that climate change is
expected to increase the frequency and also the severity
of extreme events such as droughts and floods. [3] agreed
with this contention and noted that changes in drought
frequency could be used as an indicator of climate change.
Observations of long-term and widespread changes in
wind patterns and aspects of extreme weather, including
droughts, heavy precipitation, heat waves, and the inten-
sity of tropical cyclones, are increasingly linked with
climate change [38]. Accordingly, the impending increase
in drought vulnerability due to climate change has ampli-
fied the need for drought vulnerability assessment [39-
42]. Recent drought losses such as the 1987-89 drought
in the USA [43,44] and the Sahel droughts of the 1980’s
[45] further illustrate this vulnerability.
Numerous conceptual frameworks have been proposed
for examining the causal structure of the vulnerability of
people and places to environmental and social forces
[21,32,46-49]. Vulnerability assessment provides a frame-
work for identifying the social, economic and environ-
mental causes of drought impacts [50]. [41] stated that
vulnerability is a relative measure, and hence the need to
always define its critical levels. [26] agreed with this
assertion and pointed out that factors influencing drought
vulnerability are numerous and their inclusion in assess-
ments depends on data availability. The need for vulner-
ability assessment is further noted in [7,51]. [50] high-
lighted the lack of robust and credible measures for
drought vulnerability assessment as major research chal-
lenge.
A common theme in climate change impacts and vul-
nerability literature is that regions, countries, economic
sectors and social groups differ in their degree of vul-
nerability [24,52] noted that developing countries are
often considered more vulnerable to the effects of cli-
mate change than developed ones. [18,53] concurred and
noted that the differential vulnerability between devel-
oped and developing countries is due to the high reliance
on natural resources, lack of insufficient safety nets and
also lack of educational progress by the developing
countries. Africa has been portrayed as being vulnerable
to the impacts of global change because of its low human
adaptive capacity to anticipated increases in extreme
events [54,55]. Africa has suffered the most dramatic
impacts from droughts during the last several decades. In
addition, within country drought vulnerability variation,
impacts, and adaptive capacity to drought also exists and
will increase with climate change [18]. Thus the need to
assess vulnerability at both country and local levels. In-
formation on differential drought vulnerability across
space could aid decision makers in identifying appropri-
ate mitigation actions before the next drought event and
subsequently lessening its impacts. Understanding peo-
ple’s vulnerability to drought is complex, yet essential
for designing drought preparedness, mitigation and relief
policies and programmes. [56] highlighted that drought
vulnerability maps can be overlaid with population and
other baseline information such as infrastructure to assess
risks and design adaptive measures. With a map of
drought vulnerability, decision makers could visualize
the hazard and allocate resources accordingly.
Natural disaster management has largely been geared
towards response and recovery with little attention to
mitigation, preparedness, prediction and monitoring [57,
58]. Nevertheless, there has been a shift in drought man-
agement from a reactive, crisis management approach to
a proactive, risk management approach, which requires
planning between periods of drought [59]. Integrated
disaster risk management (IDRiM) is a process for com-
prehensively and credibly estimating and managing risks
from multiple synergistic sources, and, as such, presents
a challenge to science and policy communities. The pro-
active approach to drought management is based on
measures devised and implemented before the initiation
of a drought event [2]. Thus a major aspect of the proac-
tive approach in drought mitigation is vulnerability as-
sessment for the identifying the most vulnerable areas for
efficient resource allocation [40,42,60]. Integrated disas-
ter risk management calls for rigorous risk analyses that
integrate multiple hazards and their drivers for estimating
potential human, economic and environmental losses. An
integrated assessment of disaster risk not only takes ac-
count of the potential losses, but also of how they are
distributed among communities and regions, and how
they may differentially affect the poor or. Accordingly,
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The Spatio-Temporal-Severity Dynamics of Drought in Botswana805
drought vulnerability mapping has direct implications for
drought planning and response [40,42]. An understand-
ing and awareness of the characteristics of drought by
scientists and policy makers is crucial for the establish-
ment of policies and plans for drought vulnerability re-
duction and stabilization [40]. Drought mitigation meas-
ures are expensive and therefore cannot be adopted in a
whole jurisdiction (country or province) affected by
drought. Therefore it is necessary to determine where, in
what form, with what intensity and with what probability
the arid conditions exist, and to determine their durations
and geographical distributions. In particular, the analysis
of their temporal distribution could have great implica-
tions with respect to improving probabilistic techniques
used for hazard analysis [61,62] noted that defining
drought vulnerability of an area involves knowledge of
its strength over an area and how it is related to other
areas. By knowing these characteristics, it is possible to
develop prototype mitigation strategies that are compati-
ble with the biophysical and socioeconomic context of a
particular area.
2. Materials and Methods
2.1. Study Area
Botswana is a land-locked country in southern Africa
lying approximately between latitudes 18 and 27˚S and
longitudes 20 and 29˚E with a land area of approximately
582,000 square kilometers and a population of 1.7 mil-
lion people. Two important features controlling the cli-
mate of southern Africa are the semi permanent sub-
tropical high pressure systems located in the southeast
Atlantic (St. Helena anticyclone) and southwest Indian
ocean [Mascarene high]. These subtropical high pressure
systems are associated with widespread and persistent
subsidence [63]. Much of southern Africa is therefore
semi-arid and/or prone to drought. The rainy season span
the months of October through April with January and
February being the peak rainfall months [64].
2.2. Rainfall Data
In this study, the homogeneous monthly rainfall data of 8
meteorological stations of Francistown, Gantsi, Kasane,
Lobatse, Maun, Molepolole, Serowe, Tsabong for the
period 1974-2005 obtained from the Department of Me-
teorological Services formed the basis of the analysis.
3. Analysis
3.1. Estimation of SPI
[65] proposed Standardized Precipitation Index (SPI) to
assess anomalous and extreme precipitation. Because
precipitation data are mostly skewed, in order to compute
SPI, precipitation data are normalized using gamma
function. SPI is based on the probability of precipitation
for any desired time scale and spatially invariant indica-
tor of drought. It involves fitting a gamma probability
density function to a given frequency distribution of pre-
cipitation totals for a given station [66]. The SPI compu-
tation is based on the long-term precipitation record for
the desired time scale. The long-term record is fitted to a
gamma probability distribution that is then transformed
into a normal distribution, with zero mean and unit vari-
ence. Hence the SPI indicates the number of standard
deviations that a particular rainfall event deviates from
normal conditions. Because the SPI is normalized, wetter
and drier climates can be monitored in the same way and
comparisons between different locations can also be
made.
A drought event occurs if the SPI is –1 or less and the
event ends when the index becomes positive. Drought is
defined by the precipitation deficiency at a specific time
scale but also consecutive occurrences of deficiencies.
[67,68] noted that small time scales of SPI are used to
detect agricultural drought while large time scales deter-
mine hydrological drought such as underground waters,
river flows and dam levels. [69] concurred by noting that
crop stress is often among the earliest indicators of a de-
veloping drought situation because plants rely on fre-
quent rainfall. The SPI is computed by dividing the dif-
ference between the normalized seasonal precipitation
and its long-term seasonal mean by the standard devia-
tion. Thus,
ij ij
X
X
SPI
(1)
where Xij is the seasonal precipitation at the ith synoptic
station and jth observation, Xim the long-term seasonal
mean and
is its standard deviation. See appendix 1
for detailed SPI analysis. Four classes of SPI as shown in
Table 1 are used in this study.
3.2. Drought Occurrences and Analysis
Drought occurrences were investigated on the bases of
frequency of the events for each drought category by
taking ratio of drought occurrences in each time step to
the total drought occurrences in the same time step and
Table 1. Drought categories defined for SPI values [6].
SPI values Drought category
0 to –0.99 Mild drought
–1.00 to –1.49 Moderate drought
–1.50 to –1.99 Severe drought
–2.0 Extreme drought
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The Spatio-Temporal-Severity Dynamics of Drought in Botswana
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drought category.
3.3. Mapping Meteorological Drought with SPI
The resulting SPI values at corresponding drought cate-
gories and time scale at each synoptic station were inter-
polated at country extent using spline interpolation tech-
nique in ArcGIS 9.2 GIS package.
4. Results
4.1. Drought Severity Temporal Dynamics
Mild droughts are the most prevalent at Francistown sta-
tion with 6 and 9 month steps having the highest fre-
quencies. The 3 month time step has the highest frequen-
cies for the moderate and very severe drought categories
(Table 2).
Table 3 shows the occurrence varies drought catego-
ries for the different time steps for Gantsi station. The
station has high frequency of mild droughts with the 12
month time step being the highest at 88 percent. Moder-
ate and severe drought categories have the highest fre-
quencies at 3 month timescale of 33 and 13 percent re-
spectively and the frequency of very severe drought is
highest at 12 months.
Mild droughts are the most frequent at Kasane station
with 6 and 9 months categories having the highest oc-
currences. Moderate drought occurs mostly at 3 and 12
months. While very severe drought occurs mostly at 6
months (Table 4).
Lobatse experiences relatively low drought frequencies
for all drought categories with mild drought being rela-
tively constant across the time scales while moderate
drought is also constant across time scales except at 3
months where it is higher. The frequency of severe and
very severe categories is about 6 percent for all the cate-
gories except at 12 month where there is no occurrence
(Table 5).
Maun experiences almost constant mild drought ac-
currences at all time steps of about 60 percent while that
of moderate drought is between 22 and 35 percent with 6
month time step having the lowest occurrence while 12
month have the highest. The occurrence for severe
drought is below 6 percent except at 6 months where it is
22 percent. There is no occurrence of very severe
drought except 5 percent at 9 month (Table 6).
Mild droughts at Molepolole station occur about 60
percent of the time while the occurrences of mild drought
is between 26 and 31 percent. Severe drought occurs 6
percent of the time for all the time steps and there is no
occurrence of very severe drought except 6 percent at 12
months (Table 7).
Drought occurrence at Serowe ranges between 0 and
71 percent with 12 month mild drought having the high-
est occurrence while there is no very severe drought
(Table 8).
Tsabong has high occurrences of mild drought with 12
month timescale having the highest at 82 percent. While
the occurrence of moderate drought is 17 percent at all
time steps but 12 months where it is 6 percent. The oc-
currence of severe drought at Tsabong is 6 percent for all
time steps and there is no occurrence of very severe
drought except 6 percent at 12 months (Table 9 ).
Table 2. Drought occurrence at Francistown (northeast) and corresponding drought categories and time steps.
SPI Drought category Time (%) 3 months Time (%) 6 months Time (%) 9 months Time (%) 12 months
0 to –0.99 Mild drought 68.75 78.9 80.0 75.0
–1.00 to –1.49 Moderate drought 18.75 15.8 15.0 12.5
–1.50 to –1.99 Severe drought 0 5.26 5.0 6.25
–2.0 Very severe drought 12.5 0 0 6.25
Table 3. Drought occurrence at Gantsi (west) and corresponding drought categories and time steps.
SPI Drought category Time (%) 3 months Time (%) 6 months Time (%) 9 months Time (%) 12 months
0 to –0.99 Mild drought 53.33 64.7 64.7 87.5
–1.00 to –1.49 Moderate drought 33.33 23.53 23.53 0
–1.50 to –1.99 Severe drought 13.33 11.8 11.8 0
–2.0 Very severe drought 0 0 0 12.5
The Spatio-Temporal-Severity Dynamics of Drought in Botswana807
Table 4. Drought occurrence at Kasane (north) and corresponding drought categories and time steps.
SPI Drought category Time (%) 3 months Time (%) 6 months Time (%) 9 months Time (%) 12 months
0 to –0.99 Mild drought 64.3 71.4 76.9 60.0
–1.00 to –1.49 Moderate drought 28.6 14.3 7.69 33.3
–1.50 to –1.99 Severe drought 0 0 7.69 6.7
–2.0 Very severe drought 7.14 14.3 7.69 0
Table 5. Drought occurrence at Lobatse (south) and corresponding drought categories and time steps.
SPI Drought category Time (%) 3 months Time (%) 6 months Time (%) 9 months Time (%) 12 months
0 to –0.99 Mild Drought 66.7 62.5 60.0 60.0
–1.00 to –1.49 Moderate drought 22.2 25.0 26.7 33.3
–1.50 to –1.99 Severe drought 5.56 6.25 6.67 6.67
–2.0 Very severe drought 5.56 6.25 6.67 0
Table 6. Drought occurrence at Maun (northwest) and corresponding drought categories and time steps.
SPI Drought category Time (%) 3 months Time (%) 6 months Time (%) 9 months Time (%) 12 months
0 to –0.99 Mild Drought 68.4 66.7 66.7 58.8
–1.00 to –1.49 Moderate drought 26.3 22.2 27.8 35.3
–1.50 to –1.99 Severe drought 5.26 22.0 0 5.88
–2.0 Very severe drought 0 0 5.57 0
Table 7. Drought occurrence at Molepolole (southcentral) and corresponding drought categories and time steps.
SPI Drought category Time (%) 3 months Time (%) 6 months Time (%) 9 months Time (%) 12 months
0 to –0.99 Mild Drought 64.7 62.5 64.7 60.0
–1.00 to –1.49 Moderate drought 29.4 31.3 29.4 26.7
–1.50 to –1.99 Severe drought 5.88 6.25 5.88 6.67
–2.0 Very severe drought 0 0 0 6.67
Table 8. Drought occurrence at Serowe (central) and corresponding drought categories and time steps.
SPI Drought category Time (%) 3-months Time (%) 6-months Time (%) 9-months Time (%) 12-months
0 to –0.99 Mild Drought 64.7 70.6 70.6 71.4
–1.00 to –1.49 Moderate drought 29.4 29.4 29.4 21.4
–1.50 to –1.99 Severe drought 5.88 0 0 7.14
–2.0 Very severe drought 0 0 0 0
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The Spatio-Temporal-Severity Dynamics of Drought in Botswana
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Table 9. Drought occurrence at Tsabong (southwest) and corresponding drought categories and time steps.
SPI Drought category Time (%) 3 months Time (%) 6 months Time (%) 9 months Time (%) 12 months
0 to –0.99 Mild Drought 76.5 76.5 77.8 82.4
–1.00 to –1.49 Moderate drought 17.6 17.6 16.7 5.88
–1.50 to –1.99 Severe drought 5.88 5.88 5.56 5.88
–2.0 Very severe drought 0 0 0 5.88
4.2. Drought Severity Spatial Dynamics
The eastern, southeast, extreme north, and the northeast
parts of the country are most vulnerable to 3 month mild
drought while the south central and the southwest are
moderately vulnerable. The northwest and western parts
are the least vulnerable. These results imply that the east-
ern, southeast, extreme north, and the northeast parts of
the country, the arable agricultural regions of the country,
are vulnerable to agricultural drought (Figure 1).
The extreme north, northeast and southwest are also
most vulnerable to 6 months mild drought and the central
is moderately vulnerable. The western and northwestern
parts are again least vulnerable to 6 months moderate
drought. (Figure 2).
Some areas in the west and the central are most vul-
nerable to 9 month mild drought while the south central
is moderately vulnerable. The northern, western, north-
east and southwestern are less vulnerable to 9 month mild
drought (Figure 3).
The west and the central are most vulnerable to
12-month mild drought while the south central is moder-
ately vulnerable. The north, northeast and southwest are
less vulnerable to 12 month mild drought (Figure 4).
The extreme north and extreme southwest are most
vulnerable to 3 month moderate drought while the west;
south central and extreme northwest are moderately vul-
nerable The northeast and central are less vulnerable to 3
month moderate drought (Figure 5).
The western, northwestern, southwestern, southern and
some parts of the northeast are most vulnerable to 6
month moderate drought while the central and northern
parts are less vulnerable (Figure 6).
The northeast, central and south central are most vul-
nerable to 9 month moderate drought whilst the west, and
southwest t are moderately vulnerable. The north and
northwest are less vulnerable (Figure 7).
The northeast, central and the north are most vulner-
able to 12 month moderate drought. While the northwest
is moderately vulnerable and the west, south central,
southern and south western are less vulnerable to 12
month moderate drought (Figure 8).
The north, northwest, south, south central and some
areas in the northeast are most vulnerable to 3 month
severe drought. While the northeast and southwest are
moderately vulnerable and the western and central are
less vulnerable (Figure 9).
Most parts of the country are vulnerable to 6 months
severe drought with the north being most vulnerable and
the central least vulnerable (Fi gure 1 0 ).
The north and southwest are most vulnerable to 9
months severe drought and the northwest, west southern
are moderately vulnerable while the south central is less
vulnerable (Figure 11).
The southwest, southern and the north are most vul-
nerable to 12 month severe drought while the western and
south central are moderately vulnerable (Figure 12).
Generally the country is less vulnerable to 3 month very
severe drought except some areas in the west and central
parts (Figure 13).
The country is less vulnerable to very severe drought at
6 months although the north and northwest are moder-
ately vulnerable and the southern is vulnerable (Figure
14).
The northeast is most vulnerable to 9 month very se-
vere drought while the west, northwest and west are
moderately vulnerable and the southwest, southern and
south central are less vulnerable (Figure 15).
The northeast is most vulnerable to 12 month very se-
vere drought and the southwest, southern and south cen-
tral are less vulnerable (Figure 16).
5. Discussion
The results demonstrate that mild droughts are the most
prevalent in Botswana followed by moderate ones while
the frequency of severe and very severe droughts is low
with a frequency of about 6 percent in most regions. This
finding agrees with the assertion by [65] that mild
drought occur more frequently than other drought catego-
ries.
Most parts of the country are vulnerable to mild and
moderate agricultural drought (3 and 6 months). While
the vulnerability of severe and very severe agricultural
drought is low. Mild and moderate droughts depict high
frequency of occurrence throughout the country implying
The Spatio-Temporal-Severity Dynamics of Drought in Botswana809
Figure 1. 3 months mild drought spatial occurrence.
Figure 2. 6 months mild drought spatial occurrence.
Figure 3. 9 months mild drought spatial occurrence.
Figure 4. 12 months mild drought spatial occurrence.
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The Spatio-Temporal-Severity Dynamics of Drought in Botswana
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Figure 5. 3 months moderate drought spatial occurrence.
Figure 6. 6 months moderate drought spatial occurrence.
Figure 7. 9 months moderate drought spatial occurrence.
Figure 8. 12 months moderate drought spatial occurrence.
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The Spatio-Temporal-Severity Dynamics of Drought in Botswana811
Figure 9. 3 months severe drought spatial occurrence.
Figure 10. 6 months severe drought spatial occurrence.
Figure 11. 9 months severe drought spatial occurrence.
Figure 12. 12 months severe drought spatial occurrence.
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The Spatio-Temporal-Severity Dynamics of Drought in Botswana
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Figure 13. 3 months very severe drought spatial occurrence.
Figure 14. 6 months very severe drought spatial occurrence.
Figure 15. 9 months very severe drought spatial occurrence.
Figure 16. 12 months very severe drought sp atial occurren ce.
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The Spatio-Temporal-Severity Dynamics of Drought in Botswana813
that communities have high exposure of this drought
category and likely to have developed some resilience
and adaptation measures over time such as planting early
maturing crop varieties and also applying drought escap-
ing mechanism such as planting early or late when the
chances or reoccurring drought within a season is low.
Nevertheless, the high spatial and temporal rainfall vari-
ability in arid regions like Botswana makes the develop-
ment of resilience difficult because communities have to
adjust to the ever changing conditions. [70] noted that
rainfall variability in space and time is a characteristic of
climatology in arid and semi-arid regions while [71]
agreed with this assertion and noted that semi-arid re-
gions are subjected to inter-annual and seasonal rainfall
variability.
Most parts of the country are vulnerable to hydrologi-
cal droughts (9 and 12 moths) at all severity levels. This
information is vital because it helps in identifying areas at
risk of water deficit, the likely impacts of such deficit and
hence likely mitigation measures that can either be tacti-
cal or strategic. Tactical measures are reactive-type, or
emergency response, or crisis management in nature and
usually instituted once drought has already started and it
is too late to build new water facilities [72,73]. While
strategic measures are proactive and consist of measures
that are planned in advance, as a strategy to prepare for
drought and to mitigate its effects. These measures in-
clude construction of new dams, water reticulation and
conveying to areas at drought risk and water safe meas-
ures. The planning process should take place before the
onset of drought whereas its implementation is parti-
tioned over a long period of time, from way before
drought starts until some time after it has passed. The
planning process should never end in drought prone
countries, but be continuous through evaluation of the
plan and its amendments to adapt it to the dynamic
changes [74].
6. Conclusions
In conclusion, the purpose of this paper was to determine
the spatio-temporal dynamics of drought in Botswana
using the Standardized Precipitation index. Although the
occurrences of different drought categories and severity
levels do not show any distinct spatial patterns, the anal-
ysis was able to determine areas vulnerable to agricul-
tural drought and those vulnerable to hydrological
drought at differing severity levels and time scales. From
a planning perspective, knowledge of the spatial occur-
rence of the different drought categories is indispensable
because from food security point of view it is essential
that policy makers know the probability that drought may
simultaneously affect all or several major agricultural
regions or watersheds of major dams within its boarders
and subsequently develop contingencies if such an event
were to occur.
Likewise, it is important to know the chances of a re-
gional drought simultaneously affecting agricultural pro-
ductivity in their country as well as adjacent or nearby
nations on whom they are dependent for food supplies
because in some instances, a nation’s primary drought
mitigation strategy may be to import food from nearby
nations, hence ignoring the likelihood that a drought may
occur in the region could have severe consequences on
food security. Similarly, the occurrence of drought
worldwide or in the principal grain exporting nations may
significantly alter a developing country’s access to food
from donor government. In this respect, the study was
able to lay a foundation on which an all encompassing
drought vulnerability assessment can be built on.
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