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Effect of climate variability and climate change
on crop production and water resources in Cyprus
Adriana Bruggeman1, Christos Zoumides
2, Stelios Pashiardis
3,
Panos Hadjinicolaou1, Manfred A. Lange
1and Theodoros Zachariadis
2
1
The Cyprus Institute,2
Cyprus University of Technology,3Cyprus Meteorological Service
Nicosia, Cyprus, June 2011
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ii
Contents . . . . . . . . . 1
Executive summary . . . . . . . . 3
Acknowledgements . . . . . . . . 4
1. Introduction . . . . . . . . . 52. Methods . . . . . . . . . 7
2.1 Description of the Green-Blue Water Model . . . . . 7
2.2 Data Sources . . . . . . . . . 10
2.2.1 Climate . . . . . . . . . 10
2.2.2 Land Use and Production . . . . . . . 12
2.2.3 Soils . . . . . . . . . 14
2.2.4 Agricultural Management . . . . . . . 14
2.3 Analysis of Climate Variability and Climate Change . . . . 17
3. Results and Discussion . . . . . . . 19
3.1 Climate Variability and Climate Change . . . . . 19
3.2 Effect of Climate Variability on Crop Production . . . . 23
3.3 Effect of Climate Change and Reduced Irrigation Water Supply on Crop Production 30
4. Conclusion . . . . . . . . . 32
References . . . . . . . . . 33
Appendix 1 Effect of Climate Variability on Crop Production
Appendix 2 Effect of Climate Change on Crop Production, Scenario 1
Appendix 3 Effect of Climate Change on Crop Production, Scenario 2
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1
H ,
. ,
, .
()
30 , ()
,
()
(2013/14-2019/20),
.
,
, Green-Blue
(FAO).
( ) ( ).
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34 70
.
(, , ),
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( ) ( ).
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, .
2005
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2008, 70,9103.
, 40%
, 62,2103 1980 38,410
3 2009.
, 34,3103 8,310
3
, 5,3103
13,3103 , 5,7103 12,0103
.
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2
1980/81-2008/09 , ,
( ).
8% 5%
,
. ,
190106../ ' 1980/81-2009/10,
2% 2%
. 1989/90 (219106..),
150106..
2007/08. 135106..
2007/08 368106.. 2003/04.
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. 27310
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,
2013/14-2019/20.
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. ,
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, 25%
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2013/14-2019/20 41%
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. ,
. ,
,
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.
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3
Executive Summary
Crop production in Cyprus is constrained by a highly variable climate, limited precipitation and high
temperatures. In addition, global climate change and water management policies that support the
sustainable use of water resources are also reducing irrigation water supply. The main aims of thisstudy were (i) to assess trends in climate parameters during the past 30 years; (ii) to assess the effect
of climate variability on changes in agricultural land use, production and irrigation water demand;
and (iii) to assess the effect of possible climate change scenarios and reduced irrigation water supply
on crop production for the last seven seasons of this decade (2013/14-2019/20).
A daily soil water balance model, based on the FAO dual crop coefficient approach, referred to as
the Green-Blue Water Model, was developed to compute the crop soil water use, originating from
precipitation (green water) and from irrigation (blue water). Crop area and production data for 30
seasons (1979/80-2008/09), 87 different crops and 431 communities were obtained from the
Agricultural Statistics and Censuses. Crop areas registered by the Cyprus Agricultural Payment
Organisation (CAPO) in 2010 were used to simulate future scenarios. Daily climate data from 34
stations and precipitation data from 70 gauges were used for the water balance computations.
The monthly averages of the daily minimum temperatures were found to have statistically significant
upward trends, at the 5% significance level, for the summer months at all four stations that were
analyzed for trends (Larnaca, Kornos, Platania and Prodromos). The monthly averages of the daily
maximum temperatures were also found to have statistically significant positive trends at
Prodromos in the Troodos mountains (five months), Kornos in the eastern foot hills of the mountains
(seven months), and Larnaca at the coast (nine months). Precipitation was highly variable and the
only statistically significant trend was a downward trend for March at Kornos.
The total harvested area of temporary (annual) crops peaked at 101.9103
ha in 2005, after a
sequence of three wet seasons, and dwindled to 70.9103
ha during the 2008 drought year. The
harvested permanent crop area decreased by nearly 40%, from 62.2103
ha in 1980 to 38.4103
ha
in 2009. The main loss was for the vine growing area, which decreased from 34.3 to 8.3103
ha, and
for the areas planted with nut trees, which shrank from 13.3 to 5.3103
ha, while the olive area
increased from 5.7 to 12.0103
ha.
The 1980/81-2008/09 seasons were divided in seven dry years, fifteen average and seven wet years,based on their aridity ratio (precipitation over reference evapotranspiration). Average annual crop
production was 8% lower during the dry years and 5% higher during the wet years, relative to the
production during the fifteen average years. Model computations indicated that total blue water use
averaged 190106
m3/yr during the 1980/81-2008/09 seasons and was only 2% higher during the dry
years and 2% lower during the wet years. Blue water was computed to have peaked at 219106
m3
in 1989/90, while it fell to a record low (150106
m3) during the 2007/08 drought year. Total green
water use ranged between 135106
m3
in 2007/08 and 368106
m3
in 2003/04.
The irrigated areas occupied 23% of the cropland, but were responsible for 65% of the total national
crop production, while consuming 48% of the blue and green water used by crops. The rain-fed
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areas produced on average 273103
ton/yr, fueled by 277106
m3/yr green water. This water may
otherwise have returned back to the atmosphere without much local benefit.
Climate change projections for Cyprus from an ensemble of six Regional Climate Models, under the
medium A1B emission scenario of the UN Intergovernmental Panel on Climate Change (IPCC-SRES),
indicated an increase in temperatures and highly variable but slightly lower precipitation amounts
for the 2013/14-2019/20 seasons. Two climate scenarios were simulated: (1) a worst case scenario,
represented by the seven dry years from the 1980/81-2008/09 record; and (2) a medium scenario
made up of three dry years, two average years and two wet years, each with the highest
evapotranspiration rates within their class. For both scenarios, irrigation water demand was reduced
to 129106
m3/yr, as recommended by recent national water management policies, which was
achieved by reducing all irrigated crop areas of the 2010 CAPO crop areas by 25%. The computed
annual national crop production for 2013/14-2019/2020 was reduced by 41%, on average, under
scenario 1 and by 43% under scenario 2, relative to 1980/81-2008/09. The average loss of irrigated
production was 193103
ton/yr under scenario 1 and 216103
ton/yr under scenario 2, whereas theaverage rain-fed production loss was 13210
3ton/yr (scenario 1) and 12510
3ton/yr (scenario 2).
These results indicated that within the near future water management policies could be critical for
agriculture. Of course, irrigation water supply is likely to be reduced even further by climate change.
The modeling analysis also showed high variability in water use for the different crops, communities
and years, indicating that there are various options for climate change adaptation.
Acknowledgements
This research was conducted within the framework of a study on the economic impact of climate
change on Cypriot agriculture, funded by the Ministry of Agriculture, Natural Resources and
Environment, and led by the Agricultural Research Institute of Cyprus. The authors would like to
acknowledge the support of Marinos Markou of the Agricultural Research Institute, Christos
Hadjiantonis and George Nicolaou of the Department of Agriculture, Silas Michaelides, Anastasia
Onoufriou, Andri Georgiou and Elenitsa Ioannou of the Cyprus Meteorological Service, Zomenia
Zomeni from the Cyprus Geological Survey, Daniel Karageorgis, Haris Chimonides and Demetris
Papadopoulos from the Cyprus Agricultural Payment Organization, and Damianos Pitiris and Loukia
Alexandrou from the Cyprus Statistical Service. Theodoros Zachariadis acknowledges also the
financial contribution of the European Commission under Marie Curie Reintegration Grant No.
PERG03-GA-2008-230595Assessment of Economic Impacts of Climate Change in Cyprus in the
framework of the 7th European Community Framework Programme.
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1.IntroductionAgriculture in the Mediterranean region is constrained by the limited and highly variable rainfall and
high temperatures. The often shallow and stony soils and the low soil organic carbon contents (Lal,
2009) are additional factors that limit root zone soil water storage and affect agricultural production
in this region. A recent study found that in the Mediterranean European countries, the modeled,
non-water limited potential yields were lower, and the gaps between modeled yields and reported
average national yields were higher than in the European countries at higher latitudes (Supit et al.,
2010). For example, modeled potential barley yields during the period 1976-2005 reached 9.5
ton/ha in The Netherlands and 7.5 ton/ha in Greece, whereas the reported average national yields
were 5.5 and 2.4 ton/ha, respectively. In Cyprus, which was not included in this study, the reported
average national barley yields during this period were even lower (2.0 ton/ha). It may be good to put
the word potential, as used in yield gap modeling studies, in perspective. Unless the arid and semi-
arid regions of the Mediterranean receive water resources from outside the region, such as the Nile
River in Egypt, or mine their non-renewable groundwater resources, such as the famous man-made
river in Libya, they will only be able to achieve these non-water limiting potential yields on a very
small fraction of their agricultural land.
The Intergovernmental Panel on Climate Change identified the Mediterranean as one of the regions
that is likely to experience a decrease in water resources due to climate change (Kundzewicz, 2007).
Giorgi (2006) also showed that the Mediterranean region is a hotspot of climate change. Similar to
many Sahel countries (Kevane and Grey, 2008), Cyprus has already experienced a decrease in
precipitation in the recent past. A regional analysis of the changes in precipitation found a
statistically significant step change in the 1916-2000 annual precipitation time series between the
hydrologic years 1968/69 and 1971/72, with a 15-25% reduction in precipitation for the last 30 yearsof the 20th century (Rossel, 2001). Data from the Cyprus Meteorological Service (CMS, 2010; 2011)
give an average annual precipitation over the government controlled area of Cyprus of 541 mm for
1901/02-1969/70 and 466 mm for the 1970/71-2009/10 period. This decrease in precipitation has
resulted in an even greater decrease in the countrys water resources. Considering that the majority
of Cyprus dams and irrigation projects have been designed on the basis of precipitation data from a
wetter past, they have not always lived up to the expectations they raised.
A recent study by the Ministry of Agriculture, Natural Resources and Environment (Vakakis and
Associates, 2010), which addressed the future of agriculture in Cyprus, indicated that climate change
is likely to increase irrigation water demands, reduce yields and increase soil degradation. On theother hand, the Water Development Departments (WDD) review of the countrys water policy for
the implementation of articles 11, 13, and 15 of the European Water Framework Directive (WFD)
recommended a 15% reduction in irrigation water demand (Karavokyris et al., 2010). Considering
their estimated irrigation water demand of 152 Mm3/yr, this would bring the irrigation water supply
down to 129.2 Mm3/yr. But not only is there expected to be less water for agriculture, this water will
also come at a higher price. The proposed new water pricing policy of the WDD, which is supposed
to bring Cyprus in line with the cost recovery principles of the European WFD, and include financial,
environmental and economic costs, proposed an increase from 0.17 to 0.24 /m3
for government
supplied irrigation water and an associated increase in the fixed charge from 1.71 to 6.61 /decare
(WDD, 2010). Farmers are also expected to start paying for the water they pump from streams or
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aquifers at a rate of 0.11 /m3. The pricing framework did take the social importance and financial
viability of the agricultural sector into consideration and the cost recovery of irrigation water supply
will still be fairly low (54%).
Although there is a critical need for a more sustainable use of the water resources in Cyprus (e.g.,
Karavokyris et al., 2010), crop farmers, who have always struggled in this marginal environment,
seem now to be hit by both climate change and policy changes. This phenomenon where certain
sectors or groups are affected by changes related to both global warming and economic
globalization has been referred to as double exposure in the socio-climate literature (OBrien and
Leichenko, 2000).
The main goal of this study is to obtain a better understanding of the effect of climate variability and
climate change on crop production in Cyprus. The specific objectives of this study are:
to assess trends in climate parameters during the past 30 years (1980-2010)
to assess changes in agricultural land use during the past 29 crop seasons (1980/81-2008/09) to asses variability and changes in agricultural production during 1980/81-2008/09; to assess variability and changes in irrigation water demand in Cyprus during 1980/81-
2009/10;
to assess the effect of potential climate change scenarios and reduced irrigation watersupply on water use and agricultural production under the new CAP (2013/14-2019/20).
This research builds on the work of Zoumides and Bruggeman (2010), who developed a monthly
water balance model to assess blue and green water use of all crop areas in all communities in
Cyprus and analyzed the agro-meteorological seasons 1996/97-2007/08. The terms green and blue
water have been recently introduced in global water research to shift our thinking from a supply-
driven focus on water resources that can be pumped from streams and aquifers (blue water) to a
more holistic thinking about precipitation as the primary water source, with both green water (soil
moisture) and blue water (rivers and groundwater) providing society with the necessary resources
and ecosystems services (e.g., Falkenmark and Rockstrom, 2010).
The current study uses a 30-year time series of daily meteorological data (1980/81-2009/10) and
crop areas and production data of 29 crop seasons (1981-2009). Soil water holding capacities were
computed over each communitys agricultural area, instead of over the full community area, as in
the previous study of Zoumides and Bruggeman (2010). Soil water balances and irrigation
requirements are computed on a daily basis using a dual crop coefficient approach (Allen et al.,
1998).
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2.Methods2.1 Description of the Green-Blue Water Model
A Fortran program was written to compute the continuous soil water balances and water uses of allcrops grown in all communities in Cyprus, on a daily basis. The model uses the dual crop coefficient
approach and procedures presented in Allen et al. (1998) for computing crop evapotranspiration
(ETc) and scheduling irrigation, as summarized below. The model distinguishes the crops use of
precipitation (green) and irrigation water (blue) and is thus named the green-blue water model.
Crop evapotranspiration
The computation of crop evapotranspiration is a two-step process. First, the evapotranspiration of a
standard, hypothetical grass surface, named reference evapotranspiration (ETo), is computed from
the daily climate parameters and the reference surface characteristics. Secondly, the crop
evapotranspiration (ETc) of a specific crop is computed from the reference evapotranspiration (ET o)
by using coefficients for the specific crop and crop stage.
For the reference surface, Allen et al. (1998) selected a hypothetical grass crop with a height of 0.12
m, a surface resistance of 70 s/m and an albedo of 0.23. The resulting, so-called FAO Penman-
Monteith equation (Allen et al. 1998) is given as:
)0.34u(1
)e(eu273T
900G)(R0.408
ET2
as2n
o
(1)
where ETo is reference evapotranspiration (mm day-1
), is the slope of the vapour pressure curve
(kPa C-1
), Rn is the net radiation at the crop surface (MJ m-2
d-1
), G is the soil heat flux density (MJ m-2
day-1
), T is the daily mean air temperature (C), u2 is the wind speed at 2-m height (m s-1
), es is the
saturation vapour pressure (kPa), ea is the actual vapour pressure (kPa) and is the psychometric
constant (kPa C-1
).
For the second step, the computation of crop evapotranspiration, the dual crop coefficient approach
was used. The main equations can be expressed as follows:
ETc = (Kcb + Ke) ETo (2)
ETa = (Ks Kcb + Ke) ETo (3)
Ke = Kr (Kc max - Kcb) few Kc max (4)
where ETc is the crop evapotranspiration with no limits on water availability (mm/d), Kcb is the basal
crop coefficient, Ke is the soil evaporation coefficient, ETo is the reference evapotranspiration
(mm/d), ETa is the actual plant water use (mm/d), Ks is a stress coefficient (0-1), Kr is an evaporation
reduction coefficient (0-1), Kc max is the maximum possible evapotranspiration (1.05-1.3) and few is the
fraction of the soil that is both exposed to radiation and wetted.
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Crop coefficients for the mid and late season stage (as explained below) are adjusted for climate
effects, if exceeding 0.45, according to:
Kcb = Kcb + [(0.04 (u2 2) 0.004 (RHmin - 45)] (h/3)0.3
(5)
where RHmin is the daily minimum relative humidity, h is the mean plant height (m), and all otherparameters are as defined previously.
Irrigation is scheduled when soil water in the root zone falls below the readily available water level.
The readily available water (RAW) is computed as:
RAW = p TAW (6)
TAW = (FC WP ) z (7)
where p is the soil water depletion fraction, which is the threshold at which stress starts to occur
and depends on the crop, TAW is the total available water, FC is the soil water content at field
capacity (fraction), WP is the wilting point water content (fraction) and z is the depth of the root
zone (mm). When the soil water content falls below RAW and no irrigation is given, K s decreases
linearly towards its minimum value of 0.0 at WP. Considering the general limited soil depths in the
study area, the model did not compute the crop root zone development, but used the full root zone
and a maximum irrigation depth of 50 mm, based on local irrigation practices.
Similarly to the stress coefficient, the soil evaporation reduction coefficient (K r) is at its maximum
value of 1.0 until the readily evaporable soil water (REW) has evaporated, and then decreases
linearly to 0.0 as evaporation approaches the soils total evaporable water (TEW). The fraction of thesoil that is wetted is set based on the irrigation method used (e.g., drip systems or micro-sprinklers).
Thus, field irrigation application efficiencies (evaporation losses) are computed by the model.
The blue water is computed as the total irrigation water given to the crop during the season. The
green water is the total seasonal ETa minus surface runoff or drainage, and change in soil moisture
storage.
Crop development
The crop coefficient is a function of the crop growth stage. The growing period can be divided into
four distinct growth stages: initial, crop development, mid-season and late season (see Figure 1).These stages have been described by Allen et al. (1998), as presented below.
The initial stage runs from planting date to approximately 10% ground cover. For perennial crops
(fruit trees and vines), the planting date is the 'green-up' date, i.e., the time when the initiation of
new leaves occurs. For this study, the initial period and the Kc_ini were used to cover the winter
months, with low evapotranspiration rates.
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Figure 1. Crop development stages and crop coefficients (taken from Bos et al., 2009)
The crop development stage runs from 10% ground cover to effective full cover. Effective full cover
for many crops occurs at the initiation of flowering. For some crops, especially those taller than 0.5
m, the average fraction of the ground surface covered by vegetation (fc) at the start of effective full
cover is about 0.7-0.8. For dense grasses, effective full cover may occur at about 0.10-0.15 m height.
Densely planted forages such as alfalfa and clover reach effective full cover at about 0.3-0.4 m. The
crop or plant can still continue to grow after the time of effective full cover.
The mid-season stage runs from effective full cover to the start of maturity. The start of maturity is
often indicated by the beginning of the ageing, yellowing or senescence of leaves, leaf drop, or the
browning of fruit. The mid-season stage is the longest stage for perennials and for many annuals, but
it may be relatively short for vegetable crops that are harvested fresh for their green vegetation.
The late season stage runs from the start of maturity to harvest, full senescence, or leave drop. For
perennial vegetation that grows year round (in frost free climates) the date of termination may be
taken the same as the date of planting.
Yield reduction
Yield reduction fractions for rain-fed crops are computed using the equations of Allen et al. (1998):
(8)
where Ya is the actual yield (ton), Ym is the yield under no water-stress conditions (ton), Ky is a yield
response factor, ETa is the actual seasonal crop evapotranspiration (mm) and ETc is the seasonal crop
evapotranspiration for standard conditions without water stress (mm).
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For crops that are grown both under irrigated and rain-fed conditions (e.g., wheat, olives), it was
assumed that the irrigated crop area would achieve an optimal yield (Ym). Thus, within any given
year, the average irrigated and rain-fed yields of a selected crop could be computed as:
(9)
(10)
here YIR is the yield of the selected crop under irrigated conditions (ton/ha), YRF is the yield of the
crop under rain-fed conditions (ton/ha), ProdTOT is the total production of the selected crop (ton),
ARF, AIR, ATOT are the rain-fed, irrigated and total area of the selected crop (ha), and Y a/Ym is the yield
reduction fraction computed by the model. Note that YIR = Ym and Ya = YRF.
Similarly, water productivities for irrigated and rain-fed crops were computed as follows:
(11)
(12)
where WPIR is the water productivity of an irrigated crop (kg/m3), Wblue is the irrigation water
supplied to the crop (m3/ha), Wgreen is the precipitation used by the crop (m
3/ha) and WPRF is the
water productivity of a rain-fed crop (kg/m3).
Model input data
The input data for the model are: cropped areas for each community and season; crop parameters
for all crops (crop coefficients, duration of stages, soil water depletion fraction at which stress
occurs, yield response factor, irrigation method); the average total available soil water storage
capacity (TAW) for each community, and daily climate data, from the climate station and rain gauge
that has been allocated to each community. All input and output files are comma separated files
(csv), which can be easily generated from and used in standard spreadsheet software.
Model computations start after the dry summer months on September 1, which is the start of the
hydro-meteorological year. The model uses one spin-up year to provide expected initial values for
the soil moisture.
2.2 Data Sources
2.2.1 Climate
Daily data from 70 precipitation gauges and 42 climate stations, for the period January 1980 to
December 2010, were made available by the Cyprus Meteorological Service. The locations of the
stations are given in Figure 2. All 42 stations had records of daily maximum and minimum
temperature and relative humidity measured at 8 am. Eight of the climate stations had relativelyshort records (less than 15 years) or were located very close to other stations. These stations were
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only used to fill in missing data for the final set of 34 stations, and are referred to as extra in Figure
2. Relative humidity at 1 pm was measured at 24 of the 34 stations, wind speed was measured at 22
stations, and sun hours at 7 stations. The daily mean relative humidity was estimated as the average
between the measured 8-am and 1-pm values.
All climate data were checked for errors. To fill in missing data, linear regression equations were
developed for all parameters, between all stations. For each parameter and station, two or three
neighboring stations, within 50-km distance and an 800-m elevation range, were selected, based on
the coefficient of determination of the regression equations. Missing values were subsequently
computed as the average of the values computed with the linear regression equations of the
selected stations. The relative humidity at 1 pm for the stations without afternoon measurements
were obtained from the linear regression equation between the 8-am and 1-pm humidity from a
nearby station, which was selected based on the relation between the 8-am humidity of the two
stations, similar to above. Wind speed data were taken from a nearby station with similar
characteristics. Missing sun hour data were obtained from station 731 at Larnaca, using a coefficient
for each station, based on elevation and latitude, obtained from the 7 stations with sun hour data.
The coefficients ranged between 0.77 for station 270 at Troodos square (1725 m asl) and 1.02 for
station 41 at Polis Chrysochous along the west coast of the island.
Figure 2. Location of precipitation gauges and climate stations used in the study, the stations
identified as climate (extra) were used to fill in data gaps only.
Time trends were analyzed for four stations with no more than three days missing during theJanuary 1980 December 2010 record. These stations were Prodromos (225), Platania (310), Kornos
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(660) and Larnaca (731). The monthly average daily minimum and maximum temperature, relative
humidity at 8 am, and monthly precipitation were analyzed using a set of non-parametric tests
(seasonal Kendall, Mann-Kendall for individual months, Sen slopes), as described by Gilbert (1987).
Significance was assessed at the alpha 0.05 level. Parameter values for the few missing days were
assumed to be equal to the monthly average value.
Climate change projections for the medium emission A1B scenario from six Regional Climate Models,
driven by three different General Circulation Models (CNRM-ARPEGE, HadCM3Q0, ECHAM5-r3),
from the European FP7 ENSEMBLES project, have been extracted and evaluated for Cyprus by
Hadjinicolaou et al. (2010). These authors assessed the simulated changes between 1976-2000 and
2026-2050 for Nicosia, Limassol, and Saitas. These results were reviewed to assess climate change
effects.
2.2.2 Land Use and Production
The agricultural censuses of the past three decades (Statistical Service, 1987; 1996; 2006) provide
spatial information on crop areas by the farmers community of residence. Because many owners of
a plot of agricultural land live in urban areas, these data do not precisely reflect the actual
distribution of the crop areas for rural communities. The agricultural census of 2003, however, gives
also data on the area of each crop group per community based on the actual location of the field
(Statistical Service, 2006). Twelve crop groups were used: (1) cereals; (2) forages and legumes; (3)
industrial crops; (4) potatoes, (5) vegetables, melons and strawberries; (6) flowers and ornamentals;
(7) greenhouse crops and flowers; (8) olives, (9) fruit trees, (10) citrus, (11) vines, (12) nuts and
carobs. It was assumed that the relative distribution of the crops within each crop group was the
same for all communities and that the relative distribution of the crops over the communitiesremained constant over the 1980-2009 study period. Thus, the area of each crop for each
community could be computed as follows:
A(crop,com,year) = A(crop,year) x A(cropgroup,com,2003) / A(cropgroup,2003) (13)
where A(crop,com,year) is the area of a selected crop, in a selected community and year,
A(crop,year) is the national area of the selected crop and year from the annual agricultural statistics
(Statistical Service, 1982-2010), A(cropgroup,com,2003) is the area of the crop group that includes
the selected crop for the selected community in the 2003 Census, and A(crop-group,2003) is the
total national area of this crop group in the 2003 Census.
Data on total area and production per crop were extracted from the annual agricultural statistics for
the years 1980 to 2008 (Statistical Service, 1982-2010). The agricultural statistics provide data of 60
crops. However, some of these crops include different management systems (11 greenhouse crops)
or subcategories (4 fodder crops, 2 main potato planting seasons, 3 leafy vegetable crops). Thus,
crop water use was computed for a total of 87 different agricultural production systems. Area and
production data from FAO Stat (http://faostat.fao.org/site/567/default.aspx#ancor) were used for
the year 2009 and to fill in a few missing data points and inconsistencies. This crop area dataset is
referred to as the Cystat dataset.
http://faostat.fao.org/site/567/default.aspx#ancorhttp://faostat.fao.org/site/567/default.aspx#ancorhttp://faostat.fao.org/site/567/default.aspx#ancorhttp://faostat.fao.org/site/567/default.aspx#ancor7/29/2019 Effect of climate variability and climate change on crop production and water resources in Cyprus.pdf
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The Cyprus Agricultural Payment Organisation (CAPO) hosts a second source of spatially distributed
agricultural crop area data, covering the period 2005-2010. These data are derived from farmers'
applications for the Single Area Payment Scheme for land that is maintained in good agricultural
condition. The farmer applications are checked through on-the-spot field inspection visits and with
the help of satellite images, following EU regulations (CAPO, 2008). CAPO officials estimate these
areas to cover 95% of all planted areas in Cyprus. A drawback of the CAPO dataset is that the crop
categories lack a clear definition and categories have been added or removed over time. For the
current study 87 different crops were identified.
Figure 3 provides an overview of the area covered by temporary (annual) and permanent crops, as
present in the Cystat and CAPO datasets. In general, the CAPO values are higher than the Cystat
values. This could be attributed to the fact that the CAPO data are the claimed planted crop areas
whereas Cystat data are the harvested crop areas. However, if two crops are grown during one year
in the same field, this would not show up in the CAPO dataset, while in the Cystat dataset this area
would be counted twice. It should be noted that some of the changes in the CAPO areas during the
first few years (2005-2007) are due to an improvement in the quality of the dataset. However, even
after 2007, the data show a steady decrease of the permanent crop area. A similar decrease is also
observed in the CyStat dataset.
Figure 3. Areas of temporary and permanent crops in the Cystat (2005-2009) and CAPO dataset
(2005-2010).
The 2003 agricultural census (Statistical Service, 2006) reports crop-group areas for 426
communities, while the CAPO dataset contains agricultural plots in 428 communities. Five
communities from the census are not listed in the 2005-2010 CAPO dataset, while seven
communities in the CAPO data set are not listed in the census. Three of the five additional censuscommunities (Mandres Lefkosia, Variseia, Ammadies) have been occupied by Turkish forces and are
0
20
40
60
80
100
120
140
160
2005 2006 2007 2008 2009 2010
Croparea(103h
a)
Permanent crops (Cystat) Permanent crops (CAPO)
Temporary crops (Cystat) Temporary crops (CAPO)
Total crop area (Cystat) Total crop area (CAPO)
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abandoned. Therefore, these three communities were excluded from the dataset. The remaining
two communities: Anthopouli (code 1022) and Livadi (6370) were added to the CAPO dataset. The
community of Pano Amiantos (5353), which appears in the population census of 2001 (Statistical
Service, 2004) with 44 living quarters and a permanent population of 3 people, was added for
completeness, although it currently does not have agricultural land and was listed in neither the
2003 census nor the CAPO dataset. Thus, the final dataset used for this study contains 431
communities that have all or part of their land located in the Government controlled area of Cyprus.
It should be noted that some of the communities with agricultural land are not inhabited anymore.
The 2001 Census of Population (Statistical Service, 2004) has counted people in 388 communities.
2.2.3 Soils
Cyprus has never been covered by a full set of soil surveys. Therefore, soil depths and water holding
capacities were estimated based on the soil units of the 1:250,000 digital soil map of Cyprus
(Hadjiparaskevas, 2005), which was provided by the Department of Agriculture. Soil depths andwater holding capacities of the 19 dominant soils of this map were derived from the 0.5 degree
Harmonized World Soil database (FAO et al., 2009) and from soil physical information for similar soils
provided by the European Soil Bureau Network (2005). These soil water capacities were added to
the soil units in the digital soil map. To define the average soil water holding capacity of the
agricultural land in each community, the soil water capacity for the center point of each agricultural
plot in the CAPO dataset was extracted with the help of a Geographical Information System (GIS).
The average soil water holding capacity of each community was subsequently computed as the
average of all CAPO plot values within the community.
2.2.4 Agricultural Management
Irrigation
The fraction of the crop area that was irrigated was obtained from the Cystat dataset (Statistical
Service, 1982-2010; Table 7). These tables define 10 crop groups, nearly identical to the crop groups
of the census defined above, i.e. (1) cereals; (2) forages; (3) legumes; (4) industrial crops; (5)
vegetables, melons, strawberries and potatoes; (6) olive and carob, (7) fruit trees, (8) citrus, (9)
vines, and (10) nuts. It should be noted that these tables refer to the areas irrigable, which is defined
in the 2003 census as land that has the potential to be irrigated, but does not include areas in which
mobile irrigation equipment was used. Irrigated land, on the other hand, is land that has beenirrigated at least once during the reference season (Statistical Service, 2006). The 2003 census
reported 35,928 ha irrigated land and 45,449 ha irrigable land (Statistical Service, 2006). However,
the 2003 agricultural statistics list 32,700 ha irrigable land (Statistical Service, 2007). Thus, it was
assumed that the numbers for irrigable land in the annual statistics refer in fact to irrigated land.
All areas planted with industrial crops, vegetables and melons and fresh fruit (trees) were irrigated,
with a few exceptions during 1980-1986 for industrial crops and fruit trees, which were ignored. The
fraction of the crop area irrigated for the other groups is presented in Figure 4. The data exhibited
inconsistent jumps, especially before and after the census years. Therefore, all irrigation fractions
were kept constant for this study. It should be noted that the fractions are also affected by the areal
fraction of the individual crops within the group, and within the legume group also the inconsistent
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inclusion of fresh green beans, cow peas and broad beans either under the legume or vegetable
group.
The irrigated area fractions of the individual crops, which make up these groups, were derived from
the data of the 1985, 1994 and 2003 census (Statistical Service, 1988; 1997; 2006), the cereals
statistics for 2006-2009 (Statistical Service, 2007-2010) and the vine statistics for 2006-2009
(Statistical Service, 2007-2009) and CAPO data from 2010 (Table 1). It was assumed that all carob
trees were grown under rain-fed conditions. On the other hand, all alfalfa and maize crops are fully
irrigated and the areas occupied by these crops are not included in the fodder crop groups listed in
Table 1. Given that no complete information exists regarding the location of the irrigated areas, this
same set of irrigation fractions was used for all 431 communities.
The commonly used irrigation method for each crop was taken from Markou and Mavrogenis (2002,
cited in Karavokyris et al, 2010). The fraction of the surface area wetted by irrigation, for the
different irrigation methods, was based on the guidelines given by Allen et al. (1998). This fractionwas 0.35 for drip systems, 0.70 for micro-sprinklers, and 1.0 low-pressure sprinklers.
Figure 4. Fraction of crop area irrigated (Statistical Service, 1982-2010).
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
1980 1985 1990 1995 2000 2005 2010
Fractionirrigate
d
Cereals Legumes Fodder crops Vines Nuts Olives and carobs
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Table 1. Fraction of crop area irrigated, for all crops which are grown under both irrigated and
rain-fed conditions, and fraction of crop area in greenhouses.
Crop name Fraction irrigated Crop name Fraction greenhouse
Wheat 0.09 Tomatoes 0.30
Barley 0.02 Zucchini (marrows) 0.05
Oats 0.03 Cucumbers 0.50
Broad beans 0.40 Eggplant 0.30
Chickpeas 0.60 Peppers 0.20
Lentils 0.05 Green beans 0.10
Louvana 0.10 Strawberries 0.40
Vetches (vicos, rovi, favetta) 0.05 Water melons 0.10
Cereal fodder 0.05 Sweet melons 0.10
Legume fodder 0.05 Flowers 0.50
Wine Grapes 0.05 Nursery products 0.50
Table Grapes 0.90Almonds 0.10
Walnuts 0.90
Hazelnuts 0.45
Pistachios 0.55
Olives 0.40
Greenhouses
Fractions of the area of tomatoes, cucumbers, zucchini, eggplant, pepper, green beans, melons
strawberries, flowers and nursery products that are grown in greenhouses or low plastic tunnels
were again based on the 1985, 1994 and 2003 census and on data of 2005 from Markou and
Papadavid (2008) and on data for the 2006/07-2009/10 seasons provided by the Agriculture
Department. Because of the lack of specific production statistics for these systems, greenhouses and
plastic tunnels were grouped together, and hereinafter referred to as greenhouses. Most
greenhouse area fractions were surprisingly constant over the 1985-2010 period. Therefore, the
average areal greenhouse fraction over the time period was taken for each crop (see Table 1); and it
was assumed that these fractions remained constant over the study period.
Water use of greenhouse crops was computed separately by the green-blue water model. Thesenumbers were subsequently added to the water use of each same crop grown in the open field, such
that the water productivity of these crops could be computed from the total water use and reported
total production values.
Crop coefficients
Crop coefficients were taken from Allen et al. (1998) and Allen and Pereira (2009). It was assumed
that most trees were planted with high or medium density. Crop coefficients for greenhouse crops
were taken from the studies of Orgaz et al. (2005) and Bonachela et al. (2006) in Spain. These
authors also found reference evapotranspiration inside greenhouses to be slightly higher than half
the reference evapotranspiration in the open air (Fernandez et al., 2010). A factor 0.6 was used to
convert the computed reference evapotranspiration to a value for greenhouses and plastic tunnels.
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Crop heights, depletion fractions (p) and yield response factors (Ky) were also obtained from Allen et
al. (1998). The yield response factor for beans was taken from Lorite et al. (2004).
Planting dates and crop development
From the coastal plains to the top of the Troodos mountains and down again to the Mesaoria plain
in the rain shadow of the mountains, Cyprus has a large range of climates. Thus, optimal planting
and harvesting dates and phenological development of both annual and permanent crops is affected
by the crops location on the island. Information on planting and harvesting dates and crop
development periods for the different agricultural districts in Cyprus have been provided by the
Department of Agriculture through surveys. Additional information was obtained from studies of the
Agricultural Research Institute (e.g., Eliades et al., 1995; Chimonidou, 2001; Metochis, 1999, 2006a,
2006b; Josephides and Kyratzis, 2007; Kari, 2007). Critical stages of most crops grown in Cyprus can
also be found in the agricultural labour input calendars of the Norm Input/Output report of Markou
and Papadavid (2008). For the current study, representative, average dates that would cover the
crops growing environments were selected. It should also be noted that some of the differences incrop development are also evened out because of the specific locations where the crops are
generally grown, e.g., fruit trees in the mountains and vegetables in the coastal plains. Furthermore,
the mild winter climate in the plains allows cultivation of irrigated vegetables nearly year round.
In the Mediterranean region, potatoes are grown in different seasons. Potatoes are either planted in
January (spring potatoes), August (fall potatoes), or October (winter potatoes). The total potato area
listed in the annual agricultural statistics was assumed to cover 25% winter potatoes and 75% spring
potatoes, as was indicated by data from the 1985 and 1994 census (Statistical Service, 1988; 1997).
The much smaller area of potatoes planted in August was not computed separately.
2.3 Analysis of Climate Variability and Climate Change
To assess the effect of climate variability on crop production and irrigation water use in Cyprus, crop
water requirements for the spatially distributed Cystat crop areas from the 1980/81 to 2008/09
seasons were computed for all 431 communities with the green-blue water model, with the daily
climate data of the 34 climate stations and the 70 rain gauges. Annual yield reduction fractions of
each crop were computed by the model according to equation 8. Yield and water productivities for
rain-fed and irrigated crops were subsequently computed from the national agricultural statistics,using equations 9-12. The results of the 29 crop seasons were divided into three classes: seven dry
years, fifteen average years, and seven wet years, based on the seasons average aridity ratio
(P/ETo), computed as the average of the 34 climate station. Thus, these classes do not only represent
the variability in precipitation but also changes in temperatures.
Data on the area of each crop at the community level from the Cyprus Agricultural Payment
Organisation (CAPO) for the year 2010 were used to assess the effect of climate change and reduced
irrigation water supply for a possible 2013/14-2019/20 climate future. For this future scenario, it was
also assumed that the Water Development Department would enforce sustainable water use limits,
according to the water management policy proposals for the implementation of the European Water
Framework Directive (Karavokyris et al., 2010). These authors estimated a current irrigation water
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demand of 152106
m3/yr and recommended a gradual reduction of 15%. This would bring irrigation
water supply down to 129.2106
m3/yr.
Neither Global Circulation Models nor Regional Climate Models reproduce the past and present
spatial and temporal distribution of daily precipitation very well (e.g., Dai, 2006; Boberg et al., 2009),
especially in complex topographic environments such as Cyprus (Hadjinicolaou et al., 2010).
Therefore, for this study we used the observed daily data of the past to represent the future. Two
different scenarios were developed.
The future scenarios make use of the three classes defined for the climate variability analysis of the
past 29 seasons (dry, average, wet). Scenario 1 represents a possible worst case climate future for
2013/14-2019/20. This scenario is made up of the seven driest years from the past, based on their
aridity ratio. Scenario 2 represents a perhaps more realistic scenario, made up of three dry years,
two average years and two wet years. Within these three aridity classes, the years with the highest
reference evapotranspiration were selected to represent a warmer future. For both scenarios,
irrigation water supply was brought down to 129106
m3/yr by reducing the area of each crop with
the same fraction.
First, the green-blue water model was used to compute the irrigation water demand for the CAPO
crop areas for the seven selected years. Secondly, all irrigated areas were reduced with an equal
percentage for all crops, to reduce the total irrigation water demand to 129106
m3/yr. Then the
model was run again to compute the total green and blue water use and the relative yield reductions
due to water stress for the rain-fed areas. Finally, the production data was estimated based on the
relative yield reductions and the historic yields of the selected years, under irrigated conditions.
Thus, while water stress is explicitly accounted for, other factors that affect crop yields, such asfrosts, high temperatures, wind, pests, diseases, salinity and management practices, are included in
the yield data.
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3.Results and Discussion3.1 Climate Variability and Climate Change
Average observed precipitation and the computed reference evapotranspiration (ETo) for the1980/81-2009/10 September-August hydrometeorological seasons are presented in Figure 5. These
values are the averages of the individual values of the 34 climate stations and the 70 rain gauges
used in this study, not spatially averaged values over the country. The 2007/08 season, which was
the driest in the 30 year record with 302 mm, also experienced the highest ET o (1395) of the 30-year
period. The wettest season (1991/92) received an average precipitation of 691 mm and had the
second lowest ETo (1257 mm). The ratio between precipitation and ETo (aridity ratio) is far from
constant; it ranged between 0.22 and 0.55 during the 30-year record.
As described in the previous section, for the climate variability modeling analysis, the 1981/82-
2008/09 seasons were divided into three periods. The seven seasons with the lowest aridity ratio
(1989/90, 1990/91, 1995/96, 1997/98, 1999/2000, 2005/06, 2007/08) were also the seasons with
the lowest precipitation, indicating the over-ruling influence of precipitation in this semi-arid
environment. Similarly, the seasons with the highest aridity ratio were also the wettest seasons
(1980/81, 1986/87, 1987/88, 1991/92, 2001/02, 2002/03, 2003/04). The spatially averaged
precipitation over the government controlled area of Cyprus for the seven driest, fifteen average
and seven wettest years was 344, 460 and 581 mm, respectively (CMS, 2010; 2011).
Figure 5. Average precipitation, reference evapotranspiration and aridity ratio for the September-
August hydro-meteorological years for the 70 rain gauges and 34 climate stations used in this
study.
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0
200
400
600
800
1000
1200
1400
1600
Ari
dityratio
Precipitationorevapotranpiration
(mm
/yr)
Precipitation Reference evapotranspiration Aridity ratio
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Figure 6 presents the monthly average precipitation and ETo for the 19802010 period at
Astromeritis (415) in the Mesaoria plain, which was the driest of the 34 stations; and Troodos
Square, which was the wettest and also the highest of the 34 stations, with an elevation of 1725 m
asl. With its aridity ratio of 0.21, Astromeritis would be considered semi-arid (less than 0.20 is arid),
according to the widely used classification of Middleton and Thomas (1997). The Troodos square had
an aridity ratio of 1.0 and classifies as humid. The aridity index was originally computed with the
potential evapotranpiration method of Thorntwaithe (Middleton and Thomas, 1997), thus,
classifications may differ slightly. The monthly pattern of Astromeritis shows a moisture deficit in 10
out of 12 months. On average, only in December and January the soils will receive some recharge. At
the Troodos square the moisture deficit starts in April and lasts until October. Precipitation in winter
is high but in most of the mountain areas the soils are too shallow to store all this water for the dry
season.
Figure 6. Average monthly precipitation and reference evapotranspiration (1980-2010) at
Astromeritis (station 415) and Troodos square (station 270).
The results of the Man-Kendall trend analysis of the monthly precipitation for the four stations with
complete records (see Section 2.2.1) underlined the variable nature of the precipitation. At a
probability level (alpha) of 0.05, the only statistically significant trend was found for March at the
foothill station of Kornos, with a Sen slope of -1.9 mm per year.
Statistically significant trends of increasing monthly average daily minimum temperatures were
found for the June-August summer months at Prodromos and Platania in the mountains and for June
and July at Kornos. At Larnaca both minimum and maximum temperatures showed significant
positive trends for almost all calendar months. Significant positive trends of maximum temperature
were also found at Prodromos (five months) and Kornos (seven months). The sun hours at Larnaca
exhibited statistically significant positive trends for the months May, June and July.
Average monthly relative humidity at 8 am had statistically significant negative trends for the
months March and September at Prodromos; January, February, September at Platania; November
at Kornos; and November-April at Larnaca. Thus, it seems that non-significant increases in
0
50
100
150
200
250
Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug
PrecipitationorETo(mm/mo)
415PrecipitationEvapotranspiration
0
50
100
150
200
250
Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug
PrecipitationorETo(mm/mo)
270
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temperature and non-significant decreases in precipitation combine into significant decreases in
humidities during the rainy season. These trends should be looked at in more detail.
Climate projections for Nicosia, provided by the six RCMs analyzed by Hadjinicolaou et al. (2010), are
presented in Figures 7 and 8. These figures also show the ensemble mean of the six models (ENS)
and the observed values for 1976-2000 (OBS). Most models represent the highly variable nature of
the precipitation quite well, but this variability is less well represented by the ensemble mean. It
does look like Nicosia could be expected to become somewhat drier in the future, but this trend is
masked by the high inter-annual variability, which continues into the future. Hadjinicolaou et al.
(2010) found a 2-8% decrease in precipitation for 2026-2050, relative to 1976-2000, for the three
analyzed locations in Cyprus (Nicosia, Limassol, Saitas).
Figure 7. Projections of annual precipitation for Nicosia from six Regional Climate Models, the
average of the six models (ENS) and the observed values for 1976-2000 (OBS).
All six RCM projections of the annual average daily maximum and minimum temperatures show
positive trends (Figure 8). These trends seem to have started already in the late 1990s, which was
also indicated by the significant trends found in the above presented non-parametric trend analysis.
The individual models seem to capture the inter-annual variability of the observations quite well,
whereas the ensemble mean seems again to smooth.
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Figure 8. Projections of average annual daily maximum (Tmax) and minimum temperature (Tmin)
for Nicosia from six Regional Climate Models, the average of the six models (ENS) and the
observed values for 1976-2000 (OBS).
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3.2 Effect of Climate Variability on Crop ProductionCrop areas
The trends in the total harvested areas of temporary and permanent crops over time are presented
in Figure 9. The highest crop land utilisation was found during the 1985 season and the lowest in
2008. The area of temporary crops peaked after a sequence of three wet seasons in 2005 (101.9103
ha) and decreased sharply during the 2008 drought year (70.9103
ha). The harvested permanent
crop area decreased by almost 40% from 62.2103
ha in 2008 to 38.4103
ha in 2009, but was at an
all-time low during the 2008 drought season (31.8103
ha).
On average, 50% of the temporary area is used for the production of cereals and 25% for fodder
crops (Figure 10). It is interesting to note that both groups are inversely correlated over time, e.g.
when cereals increased, fodder crops decreased. This fluctuation is attributed to the fact that most
crops included in these groups are rain-fed. During wet years, more area is harvested for cereals andless for fodder crops and vice versa. The remaining crops under the temporary area are mainly
irrigated crops and have steadily decreased over time. Potatoes, for example, decreased from 9.9
103
ha in 1995 to 5.4103
ha in 2009.
Figure 9. Areas with permanent and temporary crops and total crop areas for Cystat dataset (1980-2009)
0
25
50
75
100
125
150
175
1980 1985 1990 1995 2000 2005 2010
Croparea(103h
a)
Permanent crops (Cystat) Temporary crops (Cystat) Total crop area (Cystat)
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Figure 10. Areas of temporary crop groups (1980-2009).
Apart from the olive area, which increased from 5.7 to 12.0103
ha, most permanent crop areas
decreased during the period 1980-2009 (Figure 11). Most notably, grapes decreased from 34.3 to
8.3103
ha and nut trees from 13.3 to 5.3103
ha. This decline of the permanent crop area is likely
due to a combination of factors such as increased costs of labour, insufficient irrigation water supply,
and an overall reduction in profitability.
Figure 11. Areas of permanent crop groups (1980-2009).
0
10
20
30
40
50
60
70
80
1980 1985 1990 1995 2000 2005 2010
Temporarycroparea(103h
a)
Cereals Fodder crops Potatoes
Vegetables & melons Legumes Industrial crops & flowers
0
5
10
15
20
25
30
35
40
1980 1985 1990 1995 2000 2005 2010
Permanentcroparea(103h
a)
Grapes Citrus Fresh fruit Nuts Olives
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Crop production
The total annual production of temporary (seasonal) and permanent crops in Cyprus for the period
1980-2008, as reported in the annual agricultural statistics, are presented in Figure 12; for
comparative purposes, the mean annual precipitation is added to the graph. Temporary crop
production fluctuates over time, following a somewhat similar trend as the precipitation, i.e., in dry
years the production decreases and vice versa. Similar to the permanent crop area, the production
of permanent crops decreased by half over the past 29 years. Thus, the statistics do not indicate that
the more efficient farms with higher yields (production per area) remained while marginal farms
with low yields went out production.
Figure 12. Crop production and precipitation during 1980/81-2009/10.
The green-blue water model computations indicated that the irrigated crop areas, which cover 23%
of the crop area of the country, are, on average, responsible for 65% of the total production. During
wet years, the relative contribution of the irrigated crops decreased to 62%, while it was 71% during
dry years. The average annual crop production of all rain-fed and irrigated, seasonal and permanent
crops for the seven wettest, fifteen average and seven driest seasons are presented in Figure 13.
Even though crop areas, management practices, climate events (frosts, heat spells), pests and
diseases vary during the 29 seasons, the irrigated crop production remained nearly steady for all
three periods. Average annual production for irrigated permanent crops ranged between 209 103
ton (average years) and 215103
ton (wet years). For irrigated temporary crops, the production
ranged between 301103
ton (wet years) and 306103
ton (dry and average years). It is possible that
some of the wet years had lower production because they were too wet, but these small differences
could also be due to any of the other reasons mentioned above.
0
200
400
600
800
1000
1200
1400
1600
1800
2000
0
200
400
600
800
1,000
1980 1985 1990 1995 2000 2005 2010
Precipitation(mm)
Croppoduction(103t
ons)
Precipitation Permanent crops Temporary crops Total production
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Figure 13. Average production of rain-fed and irrigated crops for the seven wettest, fifteen average and
seven driest seasons for the period 1980/81-2008/09.
Obviously, the rain-fed crops are the ones that are affected most by the differences in climate. The
average annual production for seasonal, rain-fed crops ranged between 128103
ton (dry years) and
197103
ton (wet years). For permanent, rain-fed crops production output was on average 83103
ton during dry years and 122103
ton during wet years. The lowest absolute production of rain-fed
crops was in 2008, with 14103
ton for seasonal crops and 39103
ton for permanent crops.
Average yields for the rain-fed and irrigated crops are presented in Figure 14. Clearly yields in the
rain-fed systems are much lower than in the irrigated areas. In the rain-fed systems yields are higher
for permanent crops (olives, wine grapes, carob) than for seasonal crops (e.g., barley), while in the
irrigated areas yields are higher for the seasonal crops (e.g., potatoes, tomatoes) than for the
permanent crops (fruit trees). The relatively small differences between the average yields of rain-fed
crops in dry, average and wet years is remarkable. One reason is that during wet years, part of the
precipitation cannot be stored in the soil profile and, thus, not all rain will contribute to the crop
production. A further explanation lies in the fact that, in general, during dry years, the more
marginal lands will not be harvested and reported. Finally, it could also be expected that during dry
years, some farmers may provide their rain-fed crops with supplementary irrigation.
0
100
200
300
400
500
600
Dry Average Wet Dry Average Wet
Cropproduction(1
03t
on/yr)
Temporary, rain-fed Permanent, rain-fed
Temporary, irrigated Permanent, irrigated
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Figure 14. Average yields of rain-fed and irrigated crops for the seven wettest, fifteen average and seven
driest seasons for the period 1980/81-2008/09.
Water use
The computed green water use and blue water demand of both irrigated and rain-fed crops duringthe 1980/81-2008/09 crop seasons is presented in Figure 15. Blue water demand was, on average,
190106
m3/yr for the 29 year period. The highest blue water demand was in 1989/90 with 21910
6
m3
and the lowest in 2008/09 with 150106
m3. However, average blue water demand for the seven
dry years was 193106
m3/yr, while it was 18610
6m
3/yr for the seven wet years. Even though the
water demand was low in the 2008 drought year, when very little water was available from the
Government Irrigation Projects and much fewer seasonal crops were planted, still not all blue water
demands may always be met. On the other hand, some farmers may also apply more water than
needed by the crop. Furthermore, in areas where groundwater has been affected by salt water
intrusion, additional water is used to leach salts from the root zone. Therefore, the computed blue
water demand is generally referred to as blue water use.
On average, 65106
m3
of green water was utilized by 33103
ha irrigated crops and 277106
m3
green water was used by 107103
ha rain-fed crops. For irrigated crops, the highest green water use
occurred in 1988 with 82106
m3
and the lowest in 2008 with 34106
m3. For rain-fed crops, the
highest green water use was in 2003 with 368106 m3 and the lowest in 2008 with 135106 m3. On
average, irrigated crops used 48% of the total annual blue and green water use in Cyprus.
Blue water use of permanent crops was more than double the blue water demand of the seasonal
crops (Figure 16). However, with the reduction of the orchard and vineyard areas over time the
demand of the permanent plantations has also reduced.
0
5
10
15
20
25
30
35
Dry Average Wet Dry Average Wet
Yie
ld(ton
/ha
)
Temporary, rain-fed Permanent, rain-fed Temporary, irrigated Permanent, irrigated
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Figure 15. Computed blue and green water use of irrigated and rain-fed crops for the period 1981-
2009.
Figure 16. Blue water use of temporary and permanent crops during the 1980/81-2008/09
seasons.
The water productivities (production per unit water) of the rain-fed and irrigated, temporary andpermanent crops are presented in Figure 17. Thus, while rain-fed crops produce much less than
0
100
200
300
400
500
600
700
1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009
Cropwateruse(Mm
3)
Blue water use (irrigated) Green water use (irrigated) Green water use (rain-fed)
0
50
100
150
200
250
1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009
Buewateruse(Mm3)
Temporary Permanent Total Irrigation
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irrigated crops per unit of land (Figure 14), the difference between rain-fed and irrigated crops
becomes smaller, when considering the production per unit of water (Figure 17). It is also important
to point out that for irrigated crops the denominator of the water productivity equation constitutes
precipitation as well as irrigation water. On the other hand, the denominator for the rain-fed crops is
just precipitation. And while the precipitation fell from the sky for free, the irrigation water was
pumped from aquifers or captured and stored in dams and reservoirs and pumped through irrigation
networks. Thus, rain-fed crops are indeed rather effective users of the scarce water resources of
Cyprus.
The presented numbers are, of course, affected by the crops that make up these groups. The
detailed data on water use per crop, per year, and per community, computed by the green-blue
water model, indicated that there is an enormous scope for climate adaptation in Cyprus.
Figure 17. Water productivity of rainfed and irrigated crops for the seven wettest, fifteen average
and seven driest seasons for the period 1980/81-2008/09.
0.00
1.00
2.00
3.00
4.00
5.00
6.00
Dry Average Wet Dry Average Wet
Waterpro
ductivity
(kg
/m3
)
Temporary, rain-fed Permanent, rain-fed Temporary, irrigated Permanent, irrigated
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3.3 Effect of Climate Change and Reduced Irrigation Water Supply on CropProduction
The effects of the two future scenarios on crop production are presented in Figure 18 and 19. Total
irrigation water use was 129.1106
m3
for scenario 1 (seven dry years) and 128.0106
m3
for scenario2 (three dry, two average and two wet years), as compared to 189.710
6m
3during the 1980/81-
2008/09 reference period. Scenario 1 included the years 1989/90, 1990/91, 1995/96, 1997/98,
1999/2000, 2005/06, 2007/08, while scenario 2 included 1993/94, 1999/2000, 2002/03, 2003/04,
2005/06, 2007/08, 2008/09. The overwhelming contribution of recent years to scenario 2 is due to
the selection of years with the highest ETo within each aridity group. For both scenarios, the 2010
CAPO crop area dataset was used with all irrigated crop areas set to 75% of their 2010 areas. The use
of historic crop yield data for estimating the production of the selected scenario years ensured,
beside the modeled water stress effect, the inclusion of both abiotic and biotic stresses as well as
management effects.
Average annual crop production, which amounted to 790103
ton/yr during the reference period,
was reduced by 41% in scenario 1 (464103
ton/yr) and by 43% in scenario 2 (449103
ton/yr). The
loss in irrigated production was, on average, 193103
ton/yr under scenario 1 and 216103
ton/yr
under scenario 2, relative to the 1980/81-2008/09 reference period. The loss in rain-fed production
was 132103
ton/yr under scenario 1 and 125103
ton/yr under scenario 2. The loss in irrigated
production is mainly due to the reduction in irrigation water supply, whereas the loss in rain-fed
production is both due to climate change and an overall decrease in agricultural land use. During
1980/81-2008/09 the average harvested area of rain-fed crops and trees was 107103
ha, but based
on the CAPO data it was assumed to be 92
10
3
ha during the 2013-2020 future period. As could beconcluded from the nearly identical production reductions for the two scenarios, these computed
reductions could be considered a fairly robust estimate of future crop production in Cyprus. And
while the reduction in irrigation water supply, as a result of water management policies, had more
effect on the national crop production than the change in climate, it is likely that future irrigation
water supplies will be reduced further by climate change.
The reduction in the production of annual crops, relative to the reference period, was slightly higher
under scenario 1 (35%) than under scenario 2 (32%). However, for permanent crops (fruit and nut
trees) the production reduction was 50% under scenario 1 and 60% under scenario 2. The higher
decrease in production under scenario 2, as compared to scenario 1, were partly due to the loweryields of citrus trees during the two wet years that were part of scenario 2.
Under the two future scenarios, the irrigated areas covered 18% of the total crop area but
contributed 70% (scenario 1) and 67% (scenario 2) to the total crop production of the country.
Under the 1980/81-2008/09 reference conditions, as presented previously, the irrigated areas
covered 23% of the crop land and contributed 65% of the total production. These numbers indicate
that, as expected, irrigation becomes even more important under climate change.
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Figure 18. Average annual crop production of rain-fed and irrigated crops for 1980/81-2008/09 and
for 2013/14-2019/20 under scenario 1 (seven dry years and 129106 m3 irrigation water supply).
Figure 19. Average annual crop production of rain-fed and irrigated crops for 1980/81-2008/09 and
for 2013/14-2019/20 under scenario 2 (three dry, two average and two wet years and 128106 m3irrigation water supply).
0
100
200
300
400
500
600
Average 1981-2009 Average 2014-2020 Average 1981-2009 Average 2014-2020
Cropproduction(103ton/yr)
Temporary, rain-fed Permanent, rain-fed Temporary, irrigated Permanent, irrigated
0
100
200
300
400
500
600
Average 1981-2009 Average 2014-2020 Average 1981-2009 Average 2014-2020
Cropproduction(103ton/yr)
Temporary, rain-fed Permanent, rain-fed Temporary, irrigated Permanent, irrigated
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4.ConclusionsAnalysis of the daily climate and precipitation data for the past 30 seasons (1980/81-2009/10)
confirmed the highly variable nature of the climate in Cyprus, both in space and in time. Statistically
significant increasing trends were found for minimum and maximum temperature. Analysis of the
crop areas of the past 29 crop seasons (1980/81-2008/09) in Cyprus showed a 39% reduction in the
harvested areas of vines and fruit trees. The area planted with seasonal crops fluctuated between
dry and wet years, but overall remained fairly stable.
Average national crop production for the seven dry, fifteen average and seven wet years averaged
730103, 79610
3, and 83510
3ton/yr, respectively. This amounts to an average 8% yield reduction
during dry years, and 5% increase during wet years, relative to the 15 average years. Average
irrigation water use for these dry, average and wet years was 193106, 19010
6and 18610
6m
3/yr.
Irrigation has an important effect on reducing the variability in total annual production. Overall, the
irrigated area covered 23% of the land, used 48% of the total green and blue water and was
responsible for 65% of the total annual crop production.
Climate change projections extracted from six RCMs under the medium emission A1B scenario
showed a clear increase in temperature, while trends in precipitation are masked by the highly
variable nature of the precipitation. However, a reduction of 2-8% has been projected for 2026-
2050, relative to 1976-2000 (Hadjinicolaou et al., 2010). Analysis of two possible climate change
scenarios, represented by more dry years, higher evaporative demand, and less irrigation water
supply, which resulted in a reduction of the 2010 irrigated area by 25%, projected a possible
reduction of 41 to 43% in total national crop production for 2013/14-2019/2020, relative to
1980/81-2008/09.
The modeling results indicated that rain-fed crops are very effective users of water. Thus, under
future climate change, it may be wise to allocate some irrigation water to rain-fed crops in the drier
parts of the island, to ensure their yields during drought periods. The modeling analysis also showed
high variability in water use for the different crops, communities and years, indicating that there are
various options for climate change adaptation.
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