Mapping of climatic parameters under climate change impacts in Iran

31 Pages·2015·2.03 MB·English

Hydrological Sciences Journal
ISSN: 0262-6667 (Print) 2150-3435 (Online) Journal homepage: http://www.tandfonline.com/loi/thsj20
Mapping of climatic parameters under climate
change impacts in Iran
M.T. Dastorani & S. Poormohammadi
To cite this article: M.T. Dastorani & S. Poormohammadi (2016) Mapping of climatic parameters
under climate change impacts in Iran, Hydrological Sciences Journal, 61:14, 2552-2566, DOI:
10.1080/02626667.2015.1131898
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HYDROLOGICALSCIENCESJOURNAL–JOURNALDESSCIENCESHYDROLOGIQUES,2016
VOL.61,NO.14,2552–2566
http://dx.doi.org/10.1080/02626667.2015.1131898
Mapping of climatic parameters under climate change impacts in Iran
M.T. Dastorania and S. Poormohammadib
aFacultyofNaturalResourcesandEnvironment,FerdowsiUniversityofMashhad,Mashhad,Iran;bNationalCloudSeedingResearchCenter,Water
ResearchInstitute,Yazd,Iran
ABSTRACT ARTICLEHISTORY
This research aims to provide a comprehensive evaluation of climate change effects on temperature, Received28July2014
precipitationandpotentialevapotranspirationoverthecountryofIranforthetimeperiods2010–2039, Accepted9December2015
2040–2069and2070–2099,andunderscenariosA2andB2.Afterpreparationofmeasuredtemperature EDITOR
andprecipitationdataandcalculationofpotentialevapotranspirationforthebasetimeperiodof1960– Z.W.Kundzewicz
1990 for 46 meteorological stations (with a nationwide distribution), initial zoning of these three
ASSOCIATEEDITOR
parameters over the country was attempted. Maximum and minimum temperatures and values of
notassigned
precipitation were obtained from the HadCM3 model under scenarios A2 and B2 for the three time
periods,andthesedataweredownscaled.Correspondingmapswerepreparedforthethreeparameters KEYWORDS
in the three time periods, and spatial and temporal variations of these climatic parameters under Climatechange;Iran;
scenarios A2 and B2 were extracted and interpreted. Results showed that the highest increase in precipitation;temperature;
temperature would occur in western parts of the country, but the highest increase of potential potentialevapotranspiration
evapotranspiration would occur in the central region of Iran. However, precipitation would vary
temporally and spatially in different parts of the country depending on the scenario used and the
timeperiodselected.
1 Introduction
P should be considered together as two major climatic
variables.
Climate change is defined as “a change of climate which is
Trenberth (2008) evaluated the impacts of climate change
attributed directly or indirectly to human activity that alters
and variability on heavy precipitation, floods and drought,
the composition of the global atmosphere and which is in
and concluded that there is likely to be increased runoff and
addition to natural climate variability observed over compar-
risk of flooding in early spring but increased risk of drought
able time periods” (UNFCCC 1992). This phenomenon is
in high summer, especially over continental areas. Karamouz
caused by so-called greenhouse gases in the Earth’s atmo-
et al. (2009) simulated flood flows under climate change
sphere. Emissions of greenhouse gases have been increasing
scenarios using GCM models for the Kajoo River basin,
since industrialization in the 1900s, due to increased fossil
located in the arid and semi-arid regions of southeast Iran,
fuel burning. These gases allow solar radiation to reach the
and estimated the magnitude of floods that would occur in
Earth’ssurface,but preventradiationfromthe surfacetravel-
the future due to the impacts of climate change. Abbaspour
ling back into space. This causes the Earth’s temperature to
et al. (2009) studied the impact of climate change on water
rise gradually (Takara et al. 2009)
resourcesinIran. Theyusedthe SWATmodel foranalysisof
It is expected that climate change will strongly affect the
daily river discharge and annual wheat yield data at the sub-
hydrologicalcycleinfuturedecades(Millyetal.2005,Gedney
basin level for the period 1980–2002. They also used CGCM
et al. 2006). It will also have significant impacts on the
3.1 with scenarios A1, B1 and A2 for simulation of the water
availability, as well as the quality and quantity of water.
resource situation for 2010–2040 and 2070–2100. Their
Among the climatic variables, precipitation (P) and potential
results indicated that daily rainfall intensities will be greater
evapotranspiration(ET)havethegreatestimportanceinlong-
in the future, causing larger floods in the humid regions and
term changes of water resources (Piao et al. 2007). Many
more prolonged droughts in the dry regions.
researchers have predicted that climate change will accelerate
Harmsen et al. (2009) estimated precipitation (P), refer-
water cycles, with higher ET and increased precipitation in
ence evapotranspiration (ET ), precipitation deficit (PD = P
some parts of the globe (Oki and Kanae 2006, Betts et al. 0
−ET ), and relative crop yield reduction (YR) for a generic
2007).Butincreasedprecipitationdoesnotnecessarilyleadto 0
crop under climate change conditions for three locations in
sustainable water resources because less frequent but heavier
Puerto Rico. Results from their analysis indicated that the
precipitation may lead to extreme flood or drought occur-
rainy season will become wetter and the dry season will
rences (Andreadis and Lettenmaier 2006). Therefore, it
become drier. The 20-year average September precipitation
should be emphasized that in order to monitor and assess
excess increased for all scenarios and locations, from 121 to
the impact of climate change on drought occurrence, ET and
CONTACTM.T.Dastorani [email protected]
©2016IAHS
HYDROLOGICALSCIENCESJOURNAL–JOURNALDESSCIENCESHYDROLOGIQUES 2553
321 mm between 2000 and 2090. Conversely, the 20-year that, on average, the cumulative canopy surface evaporation
average February precipitation deficit changed from −27 to and evaporation from the soil surface were 16% and 14%
−77 mm between 2000 and 2090. higher, respectively, than those at present. However, the
Rosenberg et al. (2010), evaluated the impacts of climate cumulative transpiration was 12% lower.
changeonprecipitationextremesandstorm-waterinfrastruc- Khalil (2013) analysed the effectsofclimate change oneva-
ture in Washington State, USA. Although their simulations potranspirationinEgypt.Inthisstudy,agrometeorologicaldata
generally predicted increases in extreme rainfall magnitudes, werecollectedfrom20stationsintheNileValleyandNileDelta
the range of these projections is too large at present to todeterminethevariationofevapotranspirationundercurrent
provide a basis for engineering design, and can only be andfutureclimateconditions.ThePenman-Monteithequation
narrowed through consideration of a larger sample of simu- wasusedtocalculatereferenceevapotranspirationaccordingto
lated climate data. Nonetheless, the evidence suggests that the agrometeorological data. Results showed that under the
drainage infrastructure designed using mid-20th-century current climate the Aswan region shows the highest and
rainfall records may be subject to a future rainfall regime Damietta shows the lowest rates of evapotranspiration.
that differs from current design standards. However, under climate change, evapotranspiration will
Dastoranietal.(2011)studiedtheeffectsofclimatechange increase at all 20 stations, especially using scenarios A2 and
on drought indices for Yazd station in Iran. This research B1. These results reveal that water requirements will increase
employed the HadCM3 model based on the IPCC-SRES sce- under climate change conditions due to increased
nariosA2andB2.TheresultsindicatedthatthevaluesofSPI evapotranspiration.
(standardized precipitation index) and RDI (reconnaissance Tanasijevic et al. (2014) evaluated the impacts of climate
drought index) for scenario A2 have a negative trend along changeontheevapotranspirationandirrigationrequirements
the projected years, while these indicators tended to have a of the olive crop in the Mediterranean region, focusing on
positivetrendwhenscenarioB2wasapplied.SPIandRDIare olivegrowthandpossiblealterationstocultivableareasunder
the most important indices for evaluation of drought char- changing climate. The results showed that olive flowering is
acteristics (Bari Abarghouei et al. 2011, Kousari et al. 2014). likelytobeadvancedby11±3daysandcropevapotranspira-
Azaranfar et al. (2009) studied variations of precipitation tionisexpectedtoincreaseby8%(51±17mmseason−1).Net
and temperature in the Zayanderud basin in Iran using sta- irrigation requirements were predicted to increase by 18.5%
tisticalmethods.Theirresultssuggestedthattemperatureand (70±28mm season−1).Inaddition,effective evapotranspira-
precipitation will increase in 2010–2039. Massah Bavani tion of rainfed olives could decrease in most areas due to the
(2006)studiedtheeffectsofuncertaintyonrunoffprobability expected reduction of precipitation and increase of evapo-
distributions under climate change in the same basin. Their transpirative demand, thus making it impossible to maintain
probability distributions were most effective in estimating rainfed production as it is at present.
runoff for 2070–2099. The phenomenon of global warming and climate change is
Trenberth (2011) studied changes in precipitation due to the most important challenge of the 21st century. However,
climatechangeandconcludedthatglobalwarminghasadirect climatechangeimpactsonrainfallandevapotranspirationhave
influence on precipitation. Increased heating leads to greater not been determined conclusively. Decreases in rainfall and
evaporation and thus surface drying, thereby increasing the increases in temperature would result in increases in evapo-
intensityanddurationofdrought.However,thewater-holding transpiration(AbtewandMelesse,2013).Theeffectsofclimate
capacity ofair increases byabout 7% per 1°C warming, which changecouldbedifferentindifferentpartsoftheworld;there-
leads to increased water vapour in the atmosphere. Hence fore,regionalresearchprojectsarenecessarytoenableresultsto
storms, whether individual thunderstorms, extratropical rain be combined to build a comprehensive understanding of the
orsnowstorms,ortropicalcyclones,aresuppliedwithincreased impactsonhydrologyandwaterresourcesforthewholeplanet.
moisture,andproducemoreintenseprecipitationevents.Such Thisresearchwascarriedouttoprovidesomeoftheknowledge
eventsarenowoccurringwidely,evenwheretotalprecipitation required on regional impacts ofclimate change on three main
isdecreasing,andthisincreasestheriskofflooding. parameters of hydrology. The purpose was the evaluation and
Acharya et al. (2013) investigated the impacts of climate mapping of the impacts of climate change on precipitation,
change on extreme precipitation events over the Flamingo temperature and potential evapotranspiration in Iran under
Tropicana watershed in Nevada, USA. According to their scenarios A2 and B2 for the time periods 2010–2039, 2040–
results, the predicted cumulative annual precipitation for 2069 and 2070–2099. Awareness of the type and the size of
each 30-year period shows a continuous decrease from 2011 changes in such important parameters would help the autho-
to 2099. However, the summer convective storms, which are rities and planners to adopt better optimized and effective
consideredasextremestormsforthestudyarea,areexpected management strategies for water resources to be able to cope
to be more intense in future. Extreme storm events show withtheconditionsexpectedinthefuture.
largerchangesinstreamflowunderdifferentclimatescenarios
and time periods. The simulated peak streamflow and total
runoffvolumebothshowedanincreaseoffrom40%tomore 2 Materials and methods
than150%(during2011–2099)fordifferentclimatescenarios.
2.1 Study area
Ge et al. (2013) evaluated the effects of climate change on
evapotranspiration and soil water availability in Norway ThestudyareaforthisresearchisthecountryofIran,located
spruce forests in southern Finland. Their results showed in northwest Asia. Climate conditions vary considerably over
2554 M.T.DASTORANIANDS.POORMOHAMMADI
thecountry,especiallyfromnorthtosouth.Inanarrowstrip (1) Historicaldailytemperatureandprecipitation datafor
ofnorthernIranannualprecipitationisover1000mm,andin theselectedmeteorologicalstationsfrom1961to1990
areas covered by dense forests precipitation can reach over (T , T and P).
min max
1700 mm. However, most parts of Iran, especially the central (2) Projected monthly data from the HadCM3 model for
and southeast regions, are warm hyper-arid areas with less the periods 2010–2039, 2040–2069 and 2070–2099
than100mmannualprecipitationandover3500mmannual (T , T and P) that resulted from GCM runs for
min max
potential evapotranspiration. This considerable variation in the Third Assessment Report (TAR) based on the
climate conditions causes a wide range of biodiversity in IPCC-SRES scenario A2.
animal and plant communities. Data from different regions Scenario A2 is based on regionalization, with the
of Iran were chosen to cover these variations. Figure 1 shows emphasis on human wealth. The A2 storyline and
the distribution of the meteorological stations selected for scenario family describe a very heterogeneous
data collection. world. The underlying theme is self-reliance and
Table 1 presents general information for the 46 meteoro- preservation of local identities. Fertility patterns
logical stations. As can be seen from the table, the highest across regions converge very slowly, which results
mean annual precipitation occurs at Anzali, with 1780 mm, in continuously increasing global population.
while Zabol receives only 54 mm per year, the lowest value Economic development is primarily regionally
among the selected sites. The warmest site is Bandarabbas, oriented and per capita economic growth and tech-
with annual average temperature of 27.4°C, while the lowest nological change are more fragmented and slower
valueofthisparameteris11.45°CatZanjan,inthenorthwest. than in other storylines.
(3) Projected monthly data from the HadCM3 model for
the periods 2010–2039, 2040–2069 and 2070–2099
(T , T and P), based on scenario B2.
2.2. Methodology min max
Scenario B2 is based on regionalization, with the
In this study, the four main sources of data were: emphasis on sustainability and equity. The B2
Figure1.DistributionacrossIranofthesynopticmeteorologicalstationsusedinthisresearch.
HYDROLOGICALSCIENCESJOURNAL–JOURNALDESSCIENCESHYDROLOGIQUES 2555
Table1. Propertiesofmeteorologicalstationsusedinthisresearch.
Station Lat.1 Long.2 P(mm)3 T(ºC)4 Station Lat. Long. P(mm) T(ºC)
Abadan 30.37 48.25 128 25.15 Saghez 36.25 46.27 422 11.55
Ahvaz 31.33 48.67 196 24.8 Sanandaj 35.33 47.00 470 13.55
Anzali 37.47 49.47 1780 16 Semnan 35.55 53.38 105 17.65
Arak 34.10 49.40 354 13.95 Shahrekord 32.32 50.85 285 11.95
Babulsar 36.72 52.65 813 16.7 Shahroud 36.42 55.03 135 14.3
Bakhtaran 34.27 47.12 443 14.05 Shiraz 29.53 52.58 323 17.15
Bam 29.10 58.40 67 22.3 Tabas 33.60 56.90 74 21.05
Bandarabbas 27.22 56.37 139 27.4 Tabriz 38.08 46.28 222 11.85
Bandarlengeh 26.58 54.83 81 26.1 Tehran 35.68 51.32 226 16.65
Birjand 32.87 59.20 161 16.95 Torbat-Hey. 35.27 59.22 237 14.45
Bushehr 28.98 50.83 256 24.25 Varamin 35.35 51.68 156 16.5
Chabahar 25.42 60.75 87 26.1 Yazd 31.90 54.40 57 18.85
Dezful 32.40 48.38 366 24.35 Zabol 31.33 61.48 54 21.75
Esfahan 32.62 51.07 110 15.8 Zahedan 29.47 60.88 108 18.25
Fasa 28.97 53.68 219 19.25 Zanjan 36.23 48.48 320 11.45
Garmsar 35.25 52.17 100 17.55 Khoramabad 33.50 48.30 516 17.95
Ghazvin 36.25 50.00 285 14.5 Khoy 38.55 44.97 269 12.5
Gorgan 36.82 54.47 655 17.8 Mashhad 36.27 59.63 239 13.6
Iranshahr 27.20 60.70 81 26.6 Nowjeh 35.20 48.72 343 11.5
Jask 25.63 57.77 152 26.7 Orumiyeh 37.53 45.08 367 12.3
Kashafrud 35.98 60.83 284 17.15 Ramsar 36.90 50.67 1234 15.9
Kashan 33.98 51.45 134 19.5 Rasht 37.25 49.60 1278 15.6
Kerman 30.25 56.97 164 15.9 Sabzevar 36.22 57.67 155 16.5
1Geographicallatitude,2Geographicallongitude,3Meanannualprecipitation,4Meanannualtemperature.
Projected data of HadCM3 for three time Observed data of Iran
periods (2010–2039,2040–2069, 2070–2099) (1961–1990)
A2 scenario B2 scenario Tmax Tmin P
(1961–1990) (1961–1990) (1961–1990)
Downscaling Downscaling
P Tmax Tmin P Tmax Tmin
(2010–2039) (2010–2039) (2010–2039) (2010–2039) (2010–2039) (2010–2039)
ET ET ET
Comparison
Analysis
Figure2.Proposedmethodologyforstudyofclimatechangeimpactsontemperature,precipitationandpotentialevapotranspirationinthisresearch.
storyline and scenario family describe a world in Figure 2 illustrates the procedure used to study the
which the focus is on local solutions to economic, impact of climate change on temperature, precipitation
social and environmental sustainability. It is a world and potential evapotranspiration. After downscaling the
with continuously increasing global population at a temperature and precipitation data for the three time per-
rate lower than that in A2, intermediate levels of iods, 2010–2039, 2040–2069 and 2070–2099, at all selected
economic development, and less rapid and more sites, values of reference evapotranspiration were calculated
diverse technological change than in the B1 and for the base period as well as the future periods. Then,
A1 storylines. While the scenario is also oriented nationwide maps of mean temperature, precipitation and
towards environmentalprotectionandsocialequity, potential evapotranspiration for the future periods were
its focus is at local and regional levels. prepared. Based on these maps, the effects of climate
(4) Calculated potential evapotranspiration for each time change on the studied parameters (T, P and ET ) have
0
period using monthly T and T . been analysed.
min max
2556 M.T.DASTORANIANDS.POORMOHAMMADI
2.3 Downscaling ET ¼0:1315ðK ÞR TD0:5ðTþ17:8Þ (5)
0 T a
Downscaling is a procedure that derives local- or regional-
where
scale information from larger-scale data such as GCM model
outputs (Bates et al. 2008, Giorgi et al. 2001). The two main K ¼0:00185ðTDÞ2(cid:2)0:0433TDþ0:4023 (6)
T
methodsthathavebeenadoptedaredynamicalandstatistical
downscaling approaches. Statistical downscaling methods ET is potential evapotranspiration in mm/month, K is an
0 T
generally develop statistical relationships to relate the large- adjustment coefficient of temperature difference, TD is the
scale atmospheric variables to local climate variables. These difference between monthly minimum and maximum tem-
methods include weather pattern-based approaches, regres- peratures in °C and R is the radiation leaving the Earth per
a
sion methods and stochastic weather generators. In all cases, mm water, which is estimated for each site for each month
thequalityofthedownscaledproductdependsonthequality based on geographical latitude. Kriging was used for inter-
of the model (Bates et al. 2008). In this study, the stochastic polation to create the related maps.
approach was used for downscaling of daily data of the
HadCM3 model for the projected periods, with the help of
ClimGen software (Massah Bavani 2006). Daily data include
3 Results
T , T and P. For example, for the monthly temperature:
min max
3.1 Precipitation
ΔTGCM;i ¼TGCMð2010(cid:2)2039Þ;i(cid:2)TGCMð1961(cid:2)1990Þ;i (1)
Scenario A2 Figure 3 shows the precipitation map for the
(cid:1) (cid:1)
where TGCMð1961(cid:2)1990Þ;i and TGCMð2010(cid:2)2039Þ;i are mean timeperiods2010–2039,2040–2069and2070–2099estimated
monthly temperatures (Tmin or Tmax) resulting from the dif- using scenario A2. The map resolution (pixel size) was
ferentscenarios(A2andB2)forthebaseline(1961–1990)and defined as a function of nationwide scale. As can be seen
a projected period in month i. In fact, ΔT illustrates the from the precipitation map for the base period (measured
differences between monthly temperatures of past and future values; Map A), more precipitation occurs in the north and
periods under the A2 or B2 scenarios. To estimate tempera- northwestparts of the country than in the central and south-
tures for a projected period at site scale resolution east parts. As seen in Map B (2012–2039) precipitation (in
(cid:1)
(TGCMð2010(cid:2)2039Þ;i), monthly observed temperature data were comparison to the baseline measured values) varies from site
acquired (T(cid:1)observedð1961(cid:2)1990Þ) and added to ΔTGCM;i of the tosite,althoughingeneralthereisanincreaseforthisperiod
corresponding month: compared to the base period. The greatest precipitation
increase occurs at Anzali (in the north of Iran), at 76.2 mm
Tð2010(cid:2)2039Þ;i ¼T(cid:1)observedð1961(cid:2)1990Þ;iþΔTGCM;i (2) (4.3%), while the greatest decrease is for Khoy (in the north-
west), with a 21.7 mm (8.1%) decrease compared to the base
These monthly temperatures (T or T ) were then con-
min max period.
verted to daily values using ClimGen software. A similar The results for 2040–2069 are different from those for
procedure was used for production of daily precipitation for 2010–2039,asformostofthesitesadecreaseinprecipitation
the future periods:
occurs as compared to the baseline, although for some sta-
ΔPGCM;I ¼PGCMð2010(cid:2)2039Þ;i (3) t2i0o4n0s–a2n06i9ncwreitahsethisossetiollfs2e0e1n0.–C2o0m39pashriosownstohfatthaetosiuttepsuwtsheforer
PGCMð1961(cid:2)1990Þ;i valuesfor2010–2039decrease(comparedtothebaseperiod),
Pð2010(cid:2)2039Þ;i ¼P(cid:1)ð1961(cid:2)1990ÞΔPGCM;i (4) this decrease continues sharply in 2040–2069. In addition, at
some sites where increases occur in 2010–2039, these change
where ΔPGCM;i is the ratio of projected to baseline monthly to decreases for the following period (2040–2069). The high-
precipitation resultingfrom HadCM3under different scenar- est increase for 2040–2069 is at Khoramabad in the west of
(cid:1)
ios.Pð1961(cid:2)1990Þisobservedmonthlymeanprecipitationforthe the country, at 45.7 mm (8.86%) per year, while the highest
selected meteorological stations, while Pð2010(cid:2)2039Þ;i is the cor- decrease is seen at Shiraz in the south, with a value of
responding monthly mean downscaled precipitation for the 54.7 mm (16.93%) compared to the preceding period (2010–
projected periods. ClimGen was also used for generation of 2039). Both stations show slight increases for 2010–2039 in
daily precipitation (Massah Bavani 2006). comparison with the base period (1961–1990).
For 2070–2099, precipitation shows decreases at all sites
except three: Babulsar (at 22 mm, which is a 2.7% increase),
Gorgan (17.6 mm, 2.7% increase) and Shahroud (3.6 mm,
2.4 Potential evapotranspiration model
2.67% increase); all these stations are located in northern
The Hargreaves-Samani method (Ravazzani et al. 2012) was Iran. The highest decrease occurs at Anzali in the north,
usedforcalculationofreferencepotentialevapotranspiration. with a value of 224.2 mm (12.6%) compared to the base
In this method, which is a commonly used approach, and is period, where there was an increase in precipitation amounts
also relevant to Iranian meteorological conditions (Ravazzani in both previous time periods (2010–2039 and 2040–2069).
et al. 2012), minimum temperature, maximum temperature Map D clearly shows this general decrease of precipitation in
and mean temperature were used to calculate ET using the 2070–2099 in comparison to the base period as well as in
0
following equation: periods 2010–2039 and 2040–2069.
HYDROLOGICALSCIENCESJOURNAL–JOURNALDESSCIENCESHYDROLOGIQUES 2557
(a) (b)
(c) (d)
Figure3.MapsofprecipitationvaluesinthebaseandfuturetimeperiodsunderscenarioA2.(a)Baseperiod;scenarioA2for(b)2010–2039,(c)2040–2069,(d)2070–2099.
In order to have a better comparison and analysis, the in the west, which showed the highest decrease in precipita-
highest, lowest, mean and standard deviation of precipitation tion for 2010–2039, shows a 1.7 mm (0.36%) increase in
in all time periods (baseline and future) are shown in 2040–2069. Bushehr in the south, which showed the highest
Figure 4. It can be seen in the figure that for almost all the increase of precipitation in 2010–2039, shows a decrease of
parameters there is an increase for 2010–2039 and then a 29.1 mm (11.3%) in 2040–2069.
gradual decrease in the following time periods. Figure 5(d) shows the 30-year precipitation map for
Scenario B2 Figure5 shows the precipitation mapfor the 2070–2099. This map shows that for all stations except
base period and also for 2010–2039, 2040–2069 and 2070– five (Abadan, Babulsar, Mashhad, Gorgan and Shahroud)
2099 under scenario B2. As seen from Figure 5(b), precipita- precipitation amounts show considerable decreases com-
tion decreases in 2010–2039 in comparison to the base per- pared to the previous 30 years (2040–2069) and also the
iod. Although at most of the stations precipitation decreases base period. The highest decrease is 71.2 mm (22%) for
for this time period, the highest decrease is seen at Sanandaj Shiraz in the south. However, Mashhad in the northeast
in western Iran, with 40.5 mm (8.62%) compared to the base shows a 12.3 mm (5.15%) increase compared to the base
period. For the same period, Bushehr on the south coast period. Mashhad is a place that shows an increase of
shows a 20.5 mm (8%) increase in precipitation compared precipitation in all three studied time periods, with
to the base period. increases over the base period of 9.1 mm (3.81%),
Theprecipitationmapfor2040–2069isshowninFigure5 17.5 mm (7.32%) and 12.3 mm (5.15%) for 2010–2039,
(c).Thismapindicatesthatprecipitationdecreasesforalmost 2040–2069 and 2070–2099, respectively. In contrast,
half of the stations while it increases for the other half. Shiraz is a place where precipitation decreases in all
However, the precipitation decline is less than for 2010– three studied time periods, with the highest decrease of
2039. The highest decline in precipitation for this period about 22% in 2070–2099 compared to the base period.
occurs at Shiraz, with a 37.6 mm (11.64%) decrease, and the Figure 6 shows the maximum, minimum, mean and stan-
highest increase belongs to Khorramabad, with a 38.3 mm dard deviation (s.d.) of precipitation for the base time period
(7.42%)increaseoverthevaluesforthebaseperiod.Sanandaj and the following three 30-year periods. For 2010–2039, the
2558 M.T.DASTORANIANDS.POORMOHAMMADI
P(A2)
1780 1856 1825
2000
1556
P
r
e 1500
c
ip
ita max
tio 1000 mean
n
(m 343 342 353 358 344 355 294 306 min
m 500 54 58 52 49 SD
)
0
base 2010-2039 2040-2069 2070-2099
Time period
Figure4.Thevaluesofmaximum,mean,minimumandstandarddeviationofprecipitationinthebaseandfuturetimeperiodsunderscenarioA2.
(a) (b)
(c) (d)
Figure5.MapsofprecipitationvaluesinthebaseandfuturetimeperiodsunderscenarioB2.(a)Baseperiod;scenarioB2for(b)2010–2039,(c)2040–2069,(d)2070–2099.
values ofmaximum and s.d.increase, respectively, from 1780 2099, all four parameters show a decrease compared to the
and 343 in the base time period to 1787 and 345. However, base period.
meanand minimum values decreasefrom 343 and 54mm to ComparingtheresultsfromscenariosA2andB2,itseemsthat
335 and 52 mm. In 2040–2069, the values of maximum and the decreases in precipitation in future decades (especially
s.d.increaseoverthebaseperiod,butthevaluesofmeanand for 2070–2099) under scenario A2 are higher than under
minimum decrease compared to the base period. For 2070– scenarioB2.
HYDROLOGICALSCIENCESJOURNAL–JOURNALDESSCIENCESHYDROLOGIQUES 2559
P(B2)
2000 1787 1817 1709 1780
p
r
ec1500
ip
ita max
tio1000 mean
n
(m 335 345 341 354 320 333 343 343 min
m 500 52 49 49 54 SD
)
0
base 2010-2039 2040-2069 2070-2099
Time period
Figure6.Thevaluesofmaximum,mean,minimumandstandarddeviationofprecipitationinthebaseandfuturetimeperiodsunderscenarioB2.
(a)
(b)
(c) (d)
Figure7.MapsoftemperaturevaluesinthebaseandfuturetimeperiodsunderscenarioA2.(a)Baseperiod;scenarioA2for(b)2010–2039,(c)2040–2069,(d)2070–2099.
3.2 Temperature annual temperature of 27.4°C, and Zanjan is the coldest
station, with mean annual temperature of 11.45°C. Figure 7
Scenario A2 Figure 7 shows temperature maps for Iran for
(b) shows that at all stations temperatures increase for
the base and future time periods under scenario A2. As
2010–2039comparedtothebaseperiod.Thehighestincrease
Figure 7(a) shows, the highest temperatures are found in the
occurs at Ahwaz and Abadan in the southwest, with a 1.6°C
central and south-coast areas, and the lowest temperatures
increase, and the lowest increase belongs to Chahbahar on
relate to northwest mountainous parts of the country.
the southeast coast, at only 0.8°C over the base period.
Bandarabbas in the south is the warmest point, with mean
2560 M.T.DASTORANIANDS.POORMOHAMMADI
T(A2)
32.2
30.2
27.4 28.7
30.0
T 22.7
e 20.7
mp 24.0 17.9 19.3 14.3 16.7
era 18.0 11.5 13.0 max
tu mean
r
e (° 12.0 4.7 4.6 4.6 4.5 min
c) 6.0 SD
0.0
base 2010-2039 2040-2069 2070-2099
Time period
Figure8.Thevaluesofmaximum,mean,minimumandstandarddeviationoftemperatureinthebaseandfuturetimeperiodsunderscenarioA2.
Comparing the maps in Figure 7(c) and (a), a clear Figure 9(d) shows the temperature map of Iran for 2070–
increase in temperature is seen for all stations in 2040–2069 2099. This map also shows clear increases of temperature for
incomparisontothebaseperiod.Thehighestincreaseoccurs thisperiodoverthepreviousperiodsandthebaseperiod.The
at Khoy in the northwest, at 3.1°C, and the lowest increase is highest increase occurs at Saghez in the west, at 4.08°C over
at Chahbahar, at 1.6°C, over the base period. the base period, whereas the lowest increase is seen at
Figure7(d)showsthetemperaturemapforIranfor2070– Chahbahar on the southeast coast, at 2.1°C over the base
2099. This map also shows clear increases of temperature in period. It must be mentioned that the rate of temperature
this period over the previous periods as well as the base increase in this period is greater than that in the previous
period. The highest increase occurs at Saghez in the west, at periods (2010–2039 and 2040–2069).
5.4°C over the base period, whilst the lowest increase is seen The values of maximum, mean, minimum and s.d. of
at Chahbahar on the southeast coast, at 3.6°C over the base temperature in future time periods under scenario B2 and
period. the base time period are shown in Figure 10. The maximum
The values of maximum, mean, minimum and s.d. of temperatures in 2010–2039, 2040–2069 and 2070–2099
temperature in the three future 30-year periods under sce- increase, respectively, by 1.2, 2.5 and 3.5°C over the base
narioA2andthebasetimeperiodareshowninFigure8.The period.Theincreasesinmeantemperatureforthementioned
maximumtemperaturesfor2010–2039,2040–2069and2070– timeperiodsare,respectively,1.5,2.5and3.5°Coverthebase
2099increase,respectively,by1.3,2.8and4.8°Coverthebase period.AsFigure10shows,theincreasedvaluesofminimum
period.The increasesin mean temperature for the same time temperature for the three 30-year time periods are, respec-
periods are, respectively, 1.4, 2.8 and 4.8°C over the base tively, 1.8, 2.7 and 3.8°C over the base period. The values of
period. As Figure 8 shows, the increased values of minimum s.d.decreaseinallthreeperiodscomparedtothebaseperiod,
temperature for the mentioned 30-year time periods are, by 0.1, 0.1 and 0.2°C, respectively. This indicates relatively
respectively, 1.5, 2.8 and 5.2°C over the base time period. small variations of temperature among the seasons and a
The values of s.d. decrease in the future periods compared gradual decrease in difference between minimum and max-
to the base time period by 0.1, 0.1 and 0.2°C, respectively. imum values.
This figure also shows that in all the future time periods, the
increase in minimum temperature is greater than that in the
3.3 Potential evapotranspiration
maximum temperature, which is important in relation to the
length of growing season for plants and for agricultural Scenario A2 Figure 11 shows maps of potential evapotran-
management. spiration rate for Iran for the base time period of 1961–1990
ScenarioB2 Figure9showsthetemperaturemapsofIran and the following periods of 2010–2039, 2040–2069 and
for the base and future time periods under scenario B2. 2070–2099 under scenario A2. Comparing the maps in
Figure 9(b) shows that at all stations temperature increases Figure 11(b) and 11(a), it is clear that the evapotranspiration
for 2010–2039 compared to the base period. The highest rate increases for 2010–2039 at all stations.
increase occurs at Khoy in northwest Iran, with a 2°C Maximum, mean, minimum and standard deviation (s.d.)
increase, and the lowest increase is at Babulsar on the north of estimated potential evapotranspiration under scenario A2
coast, with 0.8°C. areshowninFigure12.Thevaluesofthemaximuminthefirst
Comparing the maps in Figure 9(c) and (a), a clear twoperiods(2010–2039and2040–2069)decreasecomparedto
increase in temperature is seen for all stations in 2040– the base period by 52 and 16 mm, respectively. However, for
2069 in comparison to the base period. The highest increase the third period (2070–2099), evapotranspiration increases
occurs at Ahwaz in the southwest, at 2.7°C, and the lowest overthebaseperiodby341mm.Thevaluesofmeanpotential
increase is at Chahbahar in the southeast, at 1.5°C over the evapotranspiration increase in 2010–2039, 2040–2069 and
base period. 2070–2099 by 29, 91 and 211 mm, respectively, over the base