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Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=thsj20 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 To link to this article: https://doi.org/10.1080/02626667.2015.1131898 Accepted author version posted online: 03 Mar 2016. Published online: 11 Jul 2016. Submit your article to this journal Article views: 129 View related articles View Crossmark data

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Page 1: Mapping of climatic parameters under climate change ...profdoc.um.ac.ir/articles/a/1056657.pdf · et al.(2009) simulated flood flows under climate change scenarios using GCM models

Full Terms & Conditions of access and use can be found athttp://www.tandfonline.com/action/journalInformation?journalCode=thsj20

Hydrological Sciences Journal

ISSN: 0262-6667 (Print) 2150-3435 (Online) Journal homepage: http://www.tandfonline.com/loi/thsj20

Mapping of climatic parameters under climatechange impacts in Iran

M.T. Dastorani & S. Poormohammadi

To cite this article: M.T. Dastorani & S. Poormohammadi (2016) Mapping of climatic parametersunder climate change impacts in Iran, Hydrological Sciences Journal, 61:14, 2552-2566, DOI:10.1080/02626667.2015.1131898

To link to this article: https://doi.org/10.1080/02626667.2015.1131898

Accepted author version posted online: 03Mar 2016.Published online: 11 Jul 2016.

Submit your article to this journal

Article views: 129

View related articles

View Crossmark data

Page 2: Mapping of climatic parameters under climate change ...profdoc.um.ac.ir/articles/a/1056657.pdf · et al.(2009) simulated flood flows under climate change scenarios using GCM models

Mapping of climatic parameters under climate change impacts in IranM.T. Dastorania and S. Poormohammadib

aFaculty of Natural Resources and Environment, Ferdowsi University of Mashhad, Mashhad, Iran; bNational Cloud Seeding Research Center, WaterResearch Institute, Yazd, Iran

ABSTRACTThis research aims to provide a comprehensive evaluation of climate change effects on temperature,precipitation and potential evapotranspiration over the country of Iran for the time periods 2010–2039,2040–2069 and 2070–2099, and under scenarios A2 and B2. After preparation of measured temperatureand precipitation data and calculation of potential evapotranspiration for the base time period of 1960–1990 for 46 meteorological stations (with a nationwide distribution), initial zoning of these threeparameters over the country was attempted. Maximum and minimum temperatures and values ofprecipitation were obtained from the HadCM3 model under scenarios A2 and B2 for the three timeperiods, and these data were downscaled. Corresponding maps were prepared for the three parametersin the three time periods, and spatial and temporal variations of these climatic parameters underscenarios A2 and B2 were extracted and interpreted. Results showed that the highest increase intemperature would occur in western parts of the country, but the highest increase of potentialevapotranspiration would occur in the central region of Iran. However, precipitation would varytemporally and spatially in different parts of the country depending on the scenario used and thetime period selected.

ARTICLE HISTORYReceived 28 July 2014Accepted 9 December 2015

EDITORZ. W. Kundzewicz

ASSOCIATE EDITORnot assigned

KEYWORDSClimate change; Iran;precipitation; temperature;potential evapotranspiration

1 Introduction

Climate change is defined as “a change of climate which isattributed directly or indirectly to human activity that altersthe composition of the global atmosphere and which is inaddition to natural climate variability observed over compar-able time periods” (UNFCCC 1992). This phenomenon iscaused by so-called greenhouse gases in the Earth’s atmo-sphere. Emissions of greenhouse gases have been increasingsince industrialization in the 1900s, due to increased fossilfuel burning. These gases allow solar radiation to reach theEarth’s surface, but prevent radiation from the surface travel-ling back into space. This causes the Earth’s temperature torise gradually (Takara et al. 2009)

It is expected that climate change will strongly affect thehydrological cycle in future decades (Milly et al. 2005, Gedneyet al. 2006). It will also have significant impacts on theavailability, as well as the quality and quantity of water.Among the climatic variables, precipitation (P) and potentialevapotranspiration (ET) have the greatest importance in long-term changes of water resources (Piao et al. 2007). Manyresearchers have predicted that climate change will acceleratewater cycles, with higher ET and increased precipitation insome parts of the globe (Oki and Kanae 2006, Betts et al.2007). But increased precipitation does not necessarily lead tosustainable water resources because less frequent but heavierprecipitation may lead to extreme flood or drought occur-rences (Andreadis and Lettenmaier 2006). Therefore, itshould be emphasized that in order to monitor and assessthe impact of climate change on drought occurrence, ET and

P should be considered together as two major climaticvariables.

Trenberth (2008) evaluated the impacts of climate changeand variability on heavy precipitation, floods and drought,and concluded that there is likely to be increased runoff andrisk of flooding in early spring but increased risk of droughtin high summer, especially over continental areas. Karamouzet al. (2009) simulated flood flows under climate changescenarios using GCM models for the Kajoo River basin,located in the arid and semi-arid regions of southeast Iran,and estimated the magnitude of floods that would occur inthe future due to the impacts of climate change. Abbaspouret al. (2009) studied the impact of climate change on waterresources in Iran. They used the SWAT model for analysis ofdaily river discharge and annual wheat yield data at the sub-basin level for the period 1980–2002. They also used CGCM3.1 with scenarios A1, B1 and A2 for simulation of the waterresource situation for 2010–2040 and 2070–2100. Theirresults indicated that daily rainfall intensities will be greaterin the future, causing larger floods in the humid regions andmore prolonged droughts in the dry regions.

Harmsen et al. (2009) estimated precipitation (P), refer-ence evapotranspiration (ET0), precipitation deficit (PD = P− ET0), and relative crop yield reduction (YR) for a genericcrop under climate change conditions for three locations inPuerto Rico. Results from their analysis indicated that therainy season will become wetter and the dry season willbecome drier. The 20-year average September precipitationexcess increased for all scenarios and locations, from 121 to

CONTACT M.T. Dastorani [email protected]

HYDROLOGICAL SCIENCES JOURNAL – JOURNAL DES SCIENCES HYDROLOGIQUES, 2016VOL. 61, NO. 14, 2552–2566http://dx.doi.org/10.1080/02626667.2015.1131898

© 2016 IAHS

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321 mm between 2000 and 2090. Conversely, the 20-yearaverage February precipitation deficit changed from −27 to−77 mm between 2000 and 2090.

Rosenberg et al. (2010), evaluated the impacts of climatechange on precipitation extremes and storm-water infrastruc-ture in Washington State, USA. Although their simulationsgenerally predicted increases in extreme rainfall magnitudes,the range of these projections is too large at present toprovide a basis for engineering design, and can only benarrowed through consideration of a larger sample of simu-lated climate data. Nonetheless, the evidence suggests thatdrainage infrastructure designed using mid-20th-centuryrainfall records may be subject to a future rainfall regimethat differs from current design standards.

Dastorani et al. (2011) studied the effects of climate changeon drought indices for Yazd station in Iran. This researchemployed the HadCM3 model based on the IPCC-SRES sce-narios A2 and B2. The results indicated that the values of SPI(standardized precipitation index) and RDI (reconnaissancedrought index) for scenario A2 have a negative trend alongthe projected years, while these indicators tended to have apositive trend when scenario B2 was applied. SPI and RDI arethe most important indices for evaluation of drought char-acteristics (Bari Abarghouei et al. 2011, Kousari et al. 2014).

Azaranfar et al. (2009) studied variations of precipitationand temperature in the Zayanderud basin in Iran using sta-tistical methods. Their results suggested that temperature andprecipitation will increase in 2010–2039. Massah Bavani(2006) studied the effects of uncertainty on runoff probabilitydistributions under climate change in the same basin. Theirprobability distributions were most effective in estimatingrunoff for 2070–2099.

Trenberth (2011) studied changes in precipitation due toclimate change and concluded that global warming has a directinfluence on precipitation. Increased heating leads to greaterevaporation and thus surface drying, thereby increasing theintensity and duration of drought. However, the water-holdingcapacity of air increases by about 7% per 1°C warming, whichleads to increased water vapour in the atmosphere. Hencestorms, whether individual thunderstorms, extratropical rainor snow storms, or tropical cyclones, are supplied with increasedmoisture, and produce more intense precipitation events. Suchevents are now occurring widely, even where total precipitationis decreasing, and this increases the risk of flooding.

Acharya et al. (2013) investigated the impacts of climatechange on extreme precipitation events over the FlamingoTropicana watershed in Nevada, USA. According to theirresults, the predicted cumulative annual precipitation foreach 30-year period shows a continuous decrease from 2011to 2099. However, the summer convective storms, which areconsidered as extreme storms for the study area, are expectedto be more intense in future. Extreme storm events showlarger changes in streamflow under different climate scenariosand time periods. The simulated peak streamflow and totalrunoff volume both showed an increase of from 40% to morethan 150% (during 2011–2099) for different climate scenarios.

Ge et al. (2013) evaluated the effects of climate change onevapotranspiration and soil water availability in Norwayspruce forests in southern Finland. Their results showed

that, on average, the cumulative canopy surface evaporationand evaporation from the soil surface were 16% and 14%higher, respectively, than those at present. However, thecumulative transpiration was 12% lower.

Khalil (2013) analysed the effects of climate change on eva-potranspiration in Egypt. In this study, agrometeorological datawere collected from 20 stations in the Nile Valley and Nile Deltato determine the variation of evapotranspiration under currentand future climate conditions. The Penman-Monteith equationwas used to calculate reference evapotranspiration according tothe agrometeorological data. Results showed that under thecurrent climate the Aswan region shows the highest andDamietta shows the lowest rates of evapotranspiration.However, under climate change, evapotranspiration willincrease at all 20 stations, especially using scenarios A2 andB1. These results reveal that water requirements will increaseunder climate change conditions due to increasedevapotranspiration.

Tanasijevic et al. (2014) evaluated the impacts of climatechange on the evapotranspiration and irrigation requirementsof the olive crop in the Mediterranean region, focusing onolive growth and possible alterations to cultivable areas underchanging climate. The results showed that olive flowering islikely to be advanced by 11 ± 3 days and crop evapotranspira-tion is expected to increase by 8% (51 ± 17 mm season−1). Netirrigation requirements were predicted to increase by 18.5%(70 ± 28 mm season−1). In addition, effective evapotranspira-tion of rainfed olives could decrease in most areas due to theexpected reduction of precipitation and increase of evapo-transpirative demand, thus making it impossible to maintainrainfed production as it is at present.

The phenomenon of global warming and climate change isthe most important challenge of the 21st century. However,climate change impacts on rainfall and evapotranspiration havenot been determined conclusively. Decreases in rainfall andincreases in temperature would result in increases in evapo-transpiration (Abtew and Melesse, 2013). The effects of climatechange could be different in different parts of the world; there-fore, regional research projects are necessary to enable results tobe combined to build a comprehensive understanding of theimpacts on hydrology and water resources for the whole planet.This research was carried out to provide some of the knowledgerequired on regional impacts of climate change on three mainparameters of hydrology. The purpose was the evaluation andmapping of the impacts of climate change on precipitation,temperature and potential evapotranspiration in Iran underscenarios A2 and B2 for the time periods 2010–2039, 2040–2069 and 2070–2099. Awareness of the type and the size ofchanges in such important parameters would help the autho-rities and planners to adopt better optimized and effectivemanagement strategies for water resources to be able to copewith the conditions expected in the future.

2 Materials and methods

2.1 Study area

The study area for this research is the country of Iran, locatedin northwest Asia. Climate conditions vary considerably over

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the country, especially from north to south. In a narrow stripof northern Iran annual precipitation is over 1000 mm, and inareas covered by dense forests precipitation can reach over1700 mm. However, most parts of Iran, especially the centraland southeast regions, are warm hyper-arid areas with lessthan 100 mm annual precipitation and over 3500 mm annualpotential evapotranspiration. This considerable variation inclimate conditions causes a wide range of biodiversity inanimal and plant communities. Data from different regionsof Iran were chosen to cover these variations. Figure 1 showsthe distribution of the meteorological stations selected fordata collection.

Table 1 presents general information for the 46 meteoro-logical stations. As can be seen from the table, the highestmean annual precipitation occurs at Anzali, with 1780 mm,while Zabol receives only 54 mm per year, the lowest valueamong the selected sites. The warmest site is Bandarabbas,with annual average temperature of 27.4°C, while the lowestvalue of this parameter is 11.45°C at Zanjan, in the northwest.

2.2. Methodology

In this study, the four main sources of data were:

(1) Historical daily temperature and precipitation data forthe selected meteorological stations from 1961 to 1990(Tmin, Tmax and P).

(2) Projected monthly data from the HadCM3 model forthe periods 2010–2039, 2040–2069 and 2070–2099(Tmin, Tmax and P) that resulted from GCM runs forthe Third Assessment Report (TAR) based on theIPCC-SRES scenario A2.Scenario A2 is based on regionalization, with theemphasis on human wealth. The A2 storyline andscenario family describe a very heterogeneousworld. The underlying theme is self-reliance andpreservation of local identities. Fertility patternsacross regions converge very slowly, which resultsin continuously increasing global population.Economic development is primarily regionallyoriented and per capita economic growth and tech-nological change are more fragmented and slowerthan in other storylines.

(3) Projected monthly data from the HadCM3 model forthe periods 2010–2039, 2040–2069 and 2070–2099(Tmin, Tmax and P), based on scenario B2.Scenario B2 is based on regionalization, with theemphasis on sustainability and equity. The B2

Figure 1. Distribution across Iran of the synoptic meteorological stations used in this research.

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storyline and scenario family describe a world inwhich the focus is on local solutions to economic,social and environmental sustainability. It is a worldwith continuously increasing global population at arate lower than that in A2, intermediate levels ofeconomic development, and less rapid and morediverse technological change than in the B1 andA1 storylines. While the scenario is also orientedtowards environmental protection and social equity,its focus is at local and regional levels.

(4) Calculated potential evapotranspiration for each timeperiod using monthly Tmin and Tmax.

Figure 2 illustrates the procedure used to study theimpact of climate change on temperature, precipitationand potential evapotranspiration. After downscaling thetemperature and precipitation data for the three time per-iods, 2010–2039, 2040–2069 and 2070–2099, at all selectedsites, values of reference evapotranspiration were calculatedfor the base period as well as the future periods. Then,nationwide maps of mean temperature, precipitation andpotential evapotranspiration for the future periods wereprepared. Based on these maps, the effects of climatechange on the studied parameters (T, P and ET0) havebeen analysed.

Observed data of Iran (1961–1990)

Projected data of HadCM3 for three timeperiods (2010–2039,2040–2069, 2070–2099)

B2 scenarioA2 scenario Tmin(1961–1990)

Tmax(1961–1990)

P(1961–1990)

DownscalingDownscaling

Tmin(2010–2039)

Tmax(2010–2039)

P(2010–2039)

Tmin(2010–2039)

Tmax(2010–2039)

P(2010–2039)

ET

Comparison

Analysis

ETET

Figure 2. Proposed methodology for study of climate change impacts on temperature, precipitation and potential evapotranspiration in this research.

Table 1. Properties of meteorological stations used in this research.

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 11.55Ahvaz 31.33 48.67 196 24.8 Sanandaj 35.33 47.00 470 13.55Anzali 37.47 49.47 1780 16 Semnan 35.55 53.38 105 17.65Arak 34.10 49.40 354 13.95 Shahrekord 32.32 50.85 285 11.95Babulsar 36.72 52.65 813 16.7 Shahroud 36.42 55.03 135 14.3Bakhtaran 34.27 47.12 443 14.05 Shiraz 29.53 52.58 323 17.15Bam 29.10 58.40 67 22.3 Tabas 33.60 56.90 74 21.05Bandarabbas 27.22 56.37 139 27.4 Tabriz 38.08 46.28 222 11.85Bandarlengeh 26.58 54.83 81 26.1 Tehran 35.68 51.32 226 16.65Birjand 32.87 59.20 161 16.95 Torbat- Hey. 35.27 59.22 237 14.45Bushehr 28.98 50.83 256 24.25 Varamin 35.35 51.68 156 16.5Chabahar 25.42 60.75 87 26.1 Yazd 31.90 54.40 57 18.85Dezful 32.40 48.38 366 24.35 Zabol 31.33 61.48 54 21.75Esfahan 32.62 51.07 110 15.8 Zahedan 29.47 60.88 108 18.25Fasa 28.97 53.68 219 19.25 Zanjan 36.23 48.48 320 11.45Garmsar 35.25 52.17 100 17.55 Khoramabad 33.50 48.30 516 17.95Ghazvin 36.25 50.00 285 14.5 Khoy 38.55 44.97 269 12.5Gorgan 36.82 54.47 655 17.8 Mashhad 36.27 59.63 239 13.6Iranshahr 27.20 60.70 81 26.6 Nowjeh 35.20 48.72 343 11.5Jask 25.63 57.77 152 26.7 Orumiyeh 37.53 45.08 367 12.3Kashafrud 35.98 60.83 284 17.15 Ramsar 36.90 50.67 1234 15.9Kashan 33.98 51.45 134 19.5 Rasht 37.25 49.60 1278 15.6Kerman 30.25 56.97 164 15.9 Sabzevar 36.22 57.67 155 16.5

1Geographical latitude, 2Geographical longitude, 3Mean annual precipitation, 4Mean annual temperature.

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2.3 Downscaling

Downscaling is a procedure that derives local- or regional-scale information from larger-scale data such as GCM modeloutputs (Bates et al. 2008, Giorgi et al. 2001). The two mainmethods that have been adopted are dynamical and statisticaldownscaling approaches. Statistical downscaling methodsgenerally develop statistical relationships to relate the large-scale atmospheric variables to local climate variables. Thesemethods include weather pattern-based approaches, regres-sion methods and stochastic weather generators. In all cases,the quality of the downscaled product depends on the qualityof the model (Bates et al. 2008). In this study, the stochasticapproach was used for downscaling of daily data of theHadCM3 model for the projected periods, with the help ofClimGen software (Massah Bavani 2006). Daily data includeTmin, Tmax and P. For example, for the monthly temperature:

ΔTGCM;i ¼ TGCMð2010�2039Þ;i � TGCMð1961�1990Þ;i (1)

where �TGCMð1961�1990Þ;i and �TGCMð2010�2039Þ;i are meanmonthly temperatures (Tmin or Tmax) resulting from the dif-ferent scenarios (A2 and B2) for the baseline (1961–1990) anda projected period in month i. In fact, ΔT illustrates thedifferences between monthly temperatures of past and futureperiods under the A2 or B2 scenarios. To estimate tempera-tures for a projected period at site scale resolution(�TGCMð2010�2039Þ;i), monthly observed temperature data wereacquired (�Tobservedð1961�1990Þ) and added to ΔTGCM;i of thecorresponding month:

Tð2010�2039Þ;i ¼ �Tobservedð1961�1990Þ;i þ ΔTGCM;i (2)

These monthly temperatures (Tmin or Tmax) were then con-verted to daily values using ClimGen software. A similarprocedure was used for production of daily precipitation forthe future periods:

ΔPGCM;I ¼PGCMð2010�2039Þ;iPGCMð1961�1990Þ;i

(3)

Pð2010�2039Þ;i ¼ �Pð1961�1990ÞΔPGCM;i (4)

where ΔPGCM;i is the ratio of projected to baseline monthlyprecipitation resulting from HadCM3 under different scenar-ios. �Pð1961�1990Þis observed monthly mean precipitation for theselected meteorological stations, while Pð2010�2039Þ;i is the cor-responding monthly mean downscaled precipitation for theprojected periods. ClimGen was also used for generation ofdaily precipitation (Massah Bavani 2006).

2.4 Potential evapotranspiration model

The Hargreaves-Samani method (Ravazzani et al. 2012) wasused for calculation of reference potential evapotranspiration.In this method, which is a commonly used approach, and isalso relevant to Iranian meteorological conditions (Ravazzaniet al. 2012), minimum temperature, maximum temperatureand mean temperature were used to calculate ET0 using thefollowing equation:

ET0 ¼ 0:1315 KTð ÞRaTD0:5 T þ 17:8ð Þ (5)

where

KT ¼ 0:00185 TDð Þ2 � 0:0433TDþ 0:4023 (6)

ET0 is potential evapotranspiration in mm/month, KT is anadjustment coefficient of temperature difference, TD is thedifference between monthly minimum and maximum tem-peratures in °C and Ra is the radiation leaving the Earth permm water, which is estimated for each site for each monthbased on geographical latitude. Kriging was used for inter-polation to create the related maps.

3 Results

3.1 Precipitation

Scenario A2 Figure 3 shows the precipitation map for thetime periods 2010–2039, 2040–2069 and 2070–2099 estimatedusing scenario A2. The map resolution (pixel size) wasdefined as a function of nationwide scale. As can be seenfrom the precipitation map for the base period (measuredvalues; Map A), more precipitation occurs in the north andnorthwest parts of the country than in the central and south-east parts. As seen in Map B (2012–2039) precipitation (incomparison to the baseline measured values) varies from siteto site, although in general there is an increase for this periodcompared to the base period. The greatest precipitationincrease occurs at Anzali (in the north of Iran), at 76.2 mm(4.3%), while the greatest decrease is for Khoy (in the north-west), with a 21.7 mm (8.1%) decrease compared to the baseperiod.

The results for 2040–2069 are different from those for2010–2039, as for most of the sites a decrease in precipitationoccurs as compared to the baseline, although for some sta-tions an increase is still seen. Comparison of the outputs for2040–2069 with those of 2010–2039 shows that at sites wherevalues for 2010–2039 decrease (compared to the base period),this decrease continues sharply in 2040–2069. In addition, atsome sites where increases occur in 2010–2039, these changeto decreases for the following period (2040–2069). The high-est increase for 2040–2069 is at Khoramabad in the west ofthe country, at 45.7 mm (8.86%) per year, while the highestdecrease is seen at Shiraz in the south, with a value of54.7 mm (16.93%) compared to the preceding period (2010–2039). Both stations show slight increases for 2010–2039 incomparison with the base period (1961–1990).

For 2070–2099, precipitation shows decreases at all sitesexcept three: Babulsar (at 22 mm, which is a 2.7% increase),Gorgan (17.6 mm, 2.7% increase) and Shahroud (3.6 mm,2.67% increase); all these stations are located in northernIran. The highest decrease occurs at Anzali in the north,with a value of 224.2 mm (12.6%) compared to the baseperiod, where there was an increase in precipitation amountsin both previous time periods (2010–2039 and 2040–2069).Map D clearly shows this general decrease of precipitation in2070–2099 in comparison to the base period as well as inperiods 2010–2039 and 2040–2069.

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In order to have a better comparison and analysis, thehighest, lowest, mean and standard deviation of precipitationin all time periods (baseline and future) are shown inFigure 4. It can be seen in the figure that for almost all theparameters there is an increase for 2010–2039 and then agradual decrease in the following time periods.

Scenario B2 Figure 5 shows the precipitation map for thebase period and also for 2010–2039, 2040–2069 and 2070–2099 under scenario B2. As seen from Figure 5(b), precipita-tion decreases in 2010–2039 in comparison to the base per-iod. Although at most of the stations precipitation decreasesfor this time period, the highest decrease is seen at Sanandajin western Iran, with 40.5 mm (8.62%) compared to the baseperiod. For the same period, Bushehr on the south coastshows a 20.5 mm (8%) increase in precipitation comparedto the base period.

The precipitation map for 2040–2069 is shown in Figure 5(c). This map indicates that precipitation decreases for almosthalf of the stations while it increases for the other half.However, the precipitation decline is less than for 2010–2039. The highest decline in precipitation for this periodoccurs at Shiraz, with a 37.6 mm (11.64%) decrease, and thehighest increase belongs to Khorramabad, with a 38.3 mm(7.42%) increase over the values for the base period. Sanandaj

in the west, which showed the highest decrease in precipita-tion for 2010–2039, shows a 1.7 mm (0.36%) increase in2040–2069. Bushehr in the south, which showed the highestincrease of precipitation in 2010–2039, shows a decrease of29.1 mm (11.3%) in 2040–2069.

Figure 5(d) shows the 30-year precipitation map for2070–2099. This map shows that for all stations exceptfive (Abadan, Babulsar, Mashhad, Gorgan and Shahroud)precipitation amounts show considerable decreases com-pared to the previous 30 years (2040–2069) and also thebase period. The highest decrease is 71.2 mm (22%) forShiraz in the south. However, Mashhad in the northeastshows a 12.3 mm (5.15%) increase compared to the baseperiod. Mashhad is a place that shows an increase ofprecipitation in all three studied time periods, withincreases over the base period of 9.1 mm (3.81%),17.5 mm (7.32%) and 12.3 mm (5.15%) for 2010–2039,2040–2069 and 2070–2099, respectively. In contrast,Shiraz is a place where precipitation decreases in allthree studied time periods, with the highest decrease ofabout 22% in 2070–2099 compared to the base period.

Figure 6 shows the maximum, minimum, mean and stan-dard deviation (s.d.) of precipitation for the base time periodand the following three 30-year periods. For 2010–2039, the

(b)(a)

(d)(c)

Figure 3. Maps of precipitation values in the base and future time periods under scenario A2. (a) Base period; scenario A2 for (b) 2010–2039, (c) 2040–2069, (d) 2070–2099.

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values of maximum and s.d. increase, respectively, from 1780and 343 in the base time period to 1787 and 345. However,mean and minimum values decrease from 343 and 54 mm to335 and 52 mm. In 2040–2069, the values of maximum ands.d. increase over the base period, but the values of mean andminimum decrease compared to the base period. For 2070–

2099, all four parameters show a decrease compared to thebase period.

Comparing the results from scenarios A2 and B2, it seems thatthe decreases in precipitation in future decades (especiallyfor 2070–2099) under scenario A2 are higher than underscenario B2.

(b)(a)

(d)(c)

Figure 5. Maps of precipitation values in the base and future time periods under scenario B2. (a) Base period; scenario B2 for (b) 2010–2039, (c) 2040–2069, (d) 2070–2099.

0

500

1000

1500

2000

base 2010-2039 2040-2069 2070-2099

1780 1856 1825

1556

343 353 344 29454 58 52

49

342 358 355 306

Precip

itation

(mm

)

Time period

P(A2)

max

mean

min

SD

Figure 4. The values of maximum, mean, minimum and standard deviation of precipitation in the base and future time periods under scenario A2.

2558 M. T. DASTORANI AND S. POORMOHAMMADI

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3.2 Temperature

Scenario A2 Figure 7 shows temperature maps for Iran forthe base and future time periods under scenario A2. AsFigure 7(a) shows, the highest temperatures are found in thecentral and south-coast areas, and the lowest temperaturesrelate to northwest mountainous parts of the country.Bandarabbas in the south is the warmest point, with mean

annual temperature of 27.4°C, and Zanjan is the coldeststation, with mean annual temperature of 11.45°C. Figure 7(b) shows that at all stations temperatures increase for2010–2039 compared to the base period. The highest increaseoccurs at Ahwaz and Abadan in the southwest, with a 1.6°Cincrease, and the lowest increase belongs to Chahbahar onthe southeast coast, at only 0.8°C over the base period.

0

500

1000

1500

2000

base 2010-2039 2040-2069 2070-2099

1787 1817 1709 1780

335 341 320 34352 49 49 54

345 354 333 343

precip

itation

(mm

)

Time period

P(B2)

max

mean

min

SD

Figure 6. The values of maximum, mean, minimum and standard deviation of precipitation in the base and future time periods under scenario B2.

(b)(a)

(d)(c)

Figure 7. Maps of temperature values in the base and future time periods under scenario A2. (a) Base period; scenario A2 for (b) 2010–2039, (c) 2040–2069, (d) 2070–2099.

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Comparing the maps in Figure 7(c) and (a), a clearincrease in temperature is seen for all stations in 2040–2069in comparison to the base period. The highest increase occursat Khoy in the northwest, at 3.1°C, and the lowest increase isat Chahbahar, at 1.6°C, over the base period.

Figure 7(d) shows the temperature map for Iran for 2070–2099. This map also shows clear increases of temperature inthis period over the previous periods as well as the baseperiod. The highest increase occurs at Saghez in the west, at5.4°C over the base period, whilst the lowest increase is seenat Chahbahar on the southeast coast, at 3.6°C over the baseperiod.

The values of maximum, mean, minimum and s.d. oftemperature in the three future 30-year periods under sce-nario A2 and the base time period are shown in Figure 8. Themaximum temperatures for 2010–2039, 2040–2069 and 2070–2099 increase, respectively, by 1.3, 2.8 and 4.8°C over the baseperiod. The increases in mean temperature for the same timeperiods are, respectively, 1.4, 2.8 and 4.8°C over the baseperiod. As Figure 8 shows, the increased values of minimumtemperature for the mentioned 30-year time periods are,respectively, 1.5, 2.8 and 5.2°C over the base time period.The values of s.d. decrease in the future periods comparedto the base time period by 0.1, 0.1 and 0.2°C, respectively.This figure also shows that in all the future time periods, theincrease in minimum temperature is greater than that in themaximum temperature, which is important in relation to thelength of growing season for plants and for agriculturalmanagement.

Scenario B2 Figure 9 shows the temperature maps of Iranfor the base and future time periods under scenario B2.Figure 9(b) shows that at all stations temperature increasesfor 2010–2039 compared to the base period. The highestincrease occurs at Khoy in northwest Iran, with a 2°Cincrease, and the lowest increase is at Babulsar on the northcoast, with 0.8°C.

Comparing the maps in Figure 9(c) and (a), a clearincrease in temperature is seen for all stations in 2040–2069 in comparison to the base period. The highest increaseoccurs at Ahwaz in the southwest, at 2.7°C, and the lowestincrease is at Chahbahar in the southeast, at 1.5°C over thebase period.

Figure 9(d) shows the temperature map of Iran for 2070–2099. This map also shows clear increases of temperature forthis period over the previous periods and the base period. Thehighest increase occurs at Saghez in the west, at 4.08°C overthe base period, whereas the lowest increase is seen atChahbahar on the southeast coast, at 2.1°C over the baseperiod. It must be mentioned that the rate of temperatureincrease in this period is greater than that in the previousperiods (2010–2039 and 2040–2069).

The values of maximum, mean, minimum and s.d. oftemperature in future time periods under scenario B2 andthe base time period are shown in Figure 10. The maximumtemperatures in 2010–2039, 2040–2069 and 2070–2099increase, respectively, by 1.2, 2.5 and 3.5°C over the baseperiod. The increases in mean temperature for the mentionedtime periods are, respectively, 1.5, 2.5 and 3.5°C over the baseperiod. As Figure 10 shows, the increased values of minimumtemperature for the three 30-year time periods are, respec-tively, 1.8, 2.7 and 3.8°C over the base period. The values ofs.d. decrease in all three periods compared to the base period,by 0.1, 0.1 and 0.2°C, respectively. This indicates relativelysmall variations of temperature among the seasons and agradual decrease in difference between minimum and max-imum values.

3.3 Potential evapotranspiration

Scenario A2 Figure 11 shows maps of potential evapotran-spiration rate for Iran for the base time period of 1961–1990and the following periods of 2010–2039, 2040–2069 and2070–2099 under scenario A2. Comparing the maps inFigure 11(b) and 11(a), it is clear that the evapotranspirationrate increases for 2010–2039 at all stations.

Maximum, mean, minimum and standard deviation (s.d.)of estimated potential evapotranspiration under scenario A2are shown in Figure 12. The values of the maximum in the firsttwo periods (2010–2039 and 2040–2069) decrease compared tothe base period by 52 and 16 mm, respectively. However, forthe third period (2070–2099), evapotranspiration increasesover the base period by 341 mm. The values of mean potentialevapotranspiration increase in 2010–2039, 2040–2069 and2070–2099 by 29, 91 and 211 mm, respectively, over the base

0.0

6.0

12.0

18.0

24.0

30.0

base 2010-2039 2040-2069 2070-2099

27.4 28.730.2 32.2

17.9 19.3 20.722.7

11.5 13.014.3 16.7

4.7 4.6 4.6 4.5

Tem

peratu

re (°c)

Time period

T(A2)

max

mean

min

SD

Figure 8. The values of maximum, mean, minimum and standard deviation of temperature in the base and future time periods under scenario A2.

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period. The increases in minimum potential evapotranspira-tion in the three periods over the base period are, respectively,41, 84 and 176 mm. Mean annual evapotranspiration shows anincrease in all three periods of 29, 91 and 211 mm, respectively,over the base period. The values of s.d. decrease in 2010–2039and 2040–2069 but increase in the last period (2070–2099)compared to the base period.

Scenario B2 Figure 13 shows annual potential evapotran-spiration maps for the base time period as well as for 2010–2039, 2040–2069 and 2070–2099 under scenario B2. AsFigure 12(b) demonstrates, the potential evapotranspirationincreases for all stations except Zabol and Iranshahr in thesoutheast in 2010–2039 in comparison with the base period.The highest increase occurs at Garmsar in central Iran. The

(b)(a)

(d)(c)

Figure 9. Maps of temperature values in the base and future time periods under scenario B2. (a) Base period; scenario B2 for (b) 2010–2039, (c) 2040–2069, (d) 2070–2099.

0.0

6.0

12.0

18.0

24.0

30.0

base 2010-2039 2040-2069 2070-2099

27.4 28.6 29.9 30.9

17.9 19.4 20.4 21.4

11.5 13.314.2 15.3

4.7 4.6 4.6 4.5

Tem

peratu

re (°c)

Time period

T(B2)

max

mean

min

SD

Figure 10. The values of maximum, mean, minimum and standard deviation of temperature in the base and future time periods under scenario B2.

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decrease for Zabol and Iranshahr in this period is 28 mm. For2040–2069, potential evapotranspiration increases over thebase period at all stations. The highest increase occurs atGarmsar, with 240.2 mm over the base period, whilst thelowest increase is at Babulsar in the north, with 38.3 mm.In 2070–2099, potential evapotranspiration increases

considerably at all stations, with the highest value of355.9 mm at Garmsar in the central region, and the lowestvalue at Iranshahr in the southeast, at 44.4 mm over the basetime period.

Figure 14 shows the values of maximum, minimum, meanand s.d. of potential evapotranspiration over the country for

(b)(a)

(d)(c)

Figure 11. Maps of potential evapotranspiration values in the base and future time periods under scenario A2. (a) Base period; scenario A2 for (b) 2010–2039, (c)2040–2069, (d) 2070–2099.

0

500

1000

1500

2000

base 2010-2039 2040-2069 2070-2099

1713 1661 1697

2054

1144 11731235

1355

690 731774

866

187 174 186 195

En

apo

transp

iration

(mm

)

Time period

ET(A2)

max

mean

min

SD

Figure 12. The values of maximum, mean, minimum and standard deviation of potential evapotranspiration in the base and future time periods under scenario A2.

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different time periods under scenario B2. As the figure shows,the maximum value decreases by 29 mm in 2010–2039 butincreases in 2040–2069 and 2070–2099 by 42 and 92 mm,respectively, over the base time period. The value of the meandecreases by about 2 mm in 2010–2039, but increases for thesubsequent time periods. The value of the minimum increasesin all periods 2010–2039, 2040–2069 and 2070–2099 by 59, 74and 113 mm, respectively. The values of s.d. also increase inall three time periods.

4 Discussion

Table 2 shows the stations having the highest and lowestincreases and decreases in temperature, precipitation andpotential evapotranspiration (for 2010–2039 under scenariosA2 and B2). The variations in each parameter and over thecountry have been presented and explained in previous sec-tions, so Table 2 is only for comparison of the results pre-sented by scenarios A2 and B2 to specify the potentially

(b)(a)

(c) (d)

Figure 13. Maps of potential evapotranspiration values in the base and future time periods under scenario B2. (a) Base period; scenario B2 for (b) 2010–2039; (c)2040–2069; (d) 2070–2099.

0

500

1000

1500

2000

base 2010-2039 2040-2069 2070-2099

1713 1684 1755 1805

1144 1142 1184 1231

690 749 764 803

187 248 268 280

Evap

otran

spiratio

n (m

m)

Time period

ET(B2)

max

mean

min

SD

Figure 14. The values of maximum, mean, minimum and standard deviation of potential evapotranspiration in the base and future time periods under scenario B2.

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hazardous regions where extreme variations occur. The tableshows that the uncertainties related to the different scenariosare quite clear, as the values of the extremes and the relatedstations are different depending on the scenario selected. Inthis regard, it must be mentioned that Garmsar (in centralIran) and Iranshahr (in the southeast) are exceptions, as theyrespectively show the highest and lowest increases in potentialevapotranspiration under both scenarios and for all threetime periods. Khoy in the northwest shows two extremes:the highest increase in precipitation under scenario A2, andthe highest increase in temperature under scenario B2.

By considering the locations of extreme values across thecountry (Table 2), it becomes possible to specify the mostthreatened regions in terms of decrease in precipitation andincrease in temperature, as well as potential evapotranspira-tion, which limit water availability and intensify water short-age. Results show that, under scenario A2, stations located innorthern parts of Iran would experience the highest increaseof precipitation. However, under scenario B2, Bushehr andother stations located on the south coast show the highestincreases in precipitation during future decades. Therefore,both north and south coasts are the regions experiencing thehighest increases in precipitation under both scenarios and,therefore, management of water resulting from extra precipi-tation here will be of importance for agriculture, naturalresources, storage and hydropower plants. On the otherhand, increases in precipitation in these regions wouldincrease the risk of flooding, soil erosion and landslides,which also require effective management and planning stra-tegies. Investigation of seasonal variations of precipitation isalso important, as such variations affect the types of compa-tible species and growing period for crops, especially inrainfed farming.

The results also show that under both scenarios the highestdecrease in precipitation occurs in the west and northwestparts of the country. These areas are predicted to be affectedby a precipitation decrease and water scarcity in 2010–2039.This necessitates specific planning and management of waterresources for these regions to overcome the problem of watershortages. The west and northwest regions of Iran are themost important areas of the country for rainfed agriculture(especially for rainfed wheat production), which would beaffected considerably by a precipitation decrease caused by

climate change. Estimation and analysis of seasonal variationsof precipitation under climate change scenarios is of impor-tance for sustainable agricultural planning in these parts ofthe country.

Under both scenarios for 2010–2039, the highest increaseof temperature occurs in the western half of the country,which is mostly mountainous and cold. Temperatureincreases in these regions would affect agricultural and nat-ural resources. Most of the people in these regions are depen-dent on agricultural and pastoral activities, so the effects ofclimate change (precipitation decrease and temperatureincrease in 2010–2039) on their lives cannot be ignored. Itshould also be mentioned that in some cold regions of thecountry, in the west and northwest, temperature increaseswould increase the length of the growing season, whichwould be a positive effect. Under both scenarios, the lowestincreases in temperature would occur in the southeast (a dryenvironment) and also in the north (a humid region).

As seen in Table 2, the highest increase in potential evapo-transpiration occurs at Garmsar in central Iran under bothscenarios. By comparing the values for different stations, itcan be seen that, in general, increases in potential evapotran-spiration are highest in central Iran. For 2010–2039, andunder both scenarios, potential evapotranspiration decreasesin southeast Iran. Central and southeast Iran are hyper-aridregions with current mean annual precipitation of less than100 mm. In these regions, water shortage is the main problemfor development at present, so climate change will intensifythis issue in the future.

Table 3 shows the stations that have the highest and lowestincreases and decreases in temperature, precipitation andpotential evapotranspiration for 2040–2069 under scenariosA2 and B2. The most important point to note for 2040–2069is that the stations where precipitation extremes (highestincrease and highest decrease) occur are the same for bothscenarios. The highest increase in precipitation under bothscenarios in this time period is at Khorramabad in the west.Precipitation increases occur at almost all stations of thewestern region under both scenarios, although the rate ofincrease for scenario A2 is higher than for scenario B2. Incontrast, the highest decrease of precipitation in 2040–2069occurs at Shiraz in the south. Evaluation of other stationsshows that, in general, the highest decrease in precipitation inthis time period occurs in the south of the country. Southernparts of the country generally have dry climatic conditions, soa precipitation decline would intensify water shortages indifferent sectors of this region.

Table 2. Extreme values of P, T and ET for 2010–2039 under scenarios A2 andB2.

Station Location inIran

A2 B2

P T ET P T ET

Anzali North 1856.1* 17.4 822.1 1786.5 17.6 822.3Khoy Northwest 247.3# 14.1 829.4 233.6 14.5* 851.4Abadan Southwest 122.5 26.7* 1466.6 121.7 26.8 1487.5Ahwaz Southwest 206.5 26.4* 1575.9 195.9 26.6 1591.1Chabahar Southeast 79.3 26.9# 1159.4 70.2 26.9 1159.4Garmsar Centre 100.7 19.1 1587.2* 94.3 19.2 1621.3*Iranshahr Southeast 92.8 27.8 1661.5# 86.4 27.6 1684.0#

Bushehr South 252.4 25.4 1086.5 276.5* 25.5 1089.1Sanandaj West 470.6 15.1 955.3 429.5# 15.4 987.7Babolsar North 861.4 17.6 818.1 818.0 17.5# 814.6Zahedan South 121.6 19.5 1422.4 120.7 19.3 1422.9#

Bold values indicate extreme variations; #highest decrease or lowest increase;*highest increase.

Table 3. Extreme values of P, T and ET for 2040–2069 under scenarios A2 andB2.

Station Location inIran

A2 B2

P T ET P T ET

Khoramabad West 561.7* 20.9 1290.6 554.3* 20.6 1293.5Shiraz South 270.5# 20.0 1452.8 285.4# 19.6 1487.5Khoy North 238.1 15.6* 883.5 246.7 15.3* 869.8Chabahar Southeast 72.7 27.7# 1179.8 84.4 27.5# 1176.4Garmsar Centre 98.0 20.4 1697.1* 97.9 20.2 1689.3*Iranshahr Southeast 66.4 29.0 1755.2# 75.1 29.3 1693.9Babolsar North 830.6 18.6 839.3 841.4 18.4 834.7#

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Khoy in the northwest shows the highest increase in tem-perature under both scenarios. Consideration of the locationsof extreme temperature values across the country makes itclear that the highest temperature increases for 2040–2069would occur in western parts of the country. The rate ofincrease for scenario A2 is higher than for scenario B2.Chahbahar and other stations located in the southeast regionshow the lowest increases of temperature for 2040–2069.Similar to 2010–2039, the highest increase in potential evapo-transpiration would occur at Garmsar in central Iran underboth scenarios for 2040–2069. By comparing values for dif-ferent stations, it can be seen that, in general, increases inpotential evapotranspiration are highest in northern parts ofthe central region. The lowest increase of evapotranspirationfor 2040–2069, under both scenarios, belongs to the southeastof Iran.

The highest and lowest increases and decreases in tem-perature, precipitation and potential evapotranspiration for2070–2099 under scenarios A2 and B2 are shown in Table 4.The most important point to note for 2070–2099 is the cleardecrease of precipitation (Figure 4), which drops considerablyeven compared to the base time period, by about 50 mm onaverage over the country. As the present average annualprecipitation for the country is about 250 mm, a 50 mm(20%) decrease would be a big drop in precipitation, andwould seriously affect the availability of water across thecountry. Overall, it can be predicted that for the next30 years (from the present) the average precipitation willincrease across the country; for the following 30 years condi-tions will be mostly similar to those in the base time period;and for the third 30 years a considerable decrease in precipi-tation will occur across the country. In this final time period,the highest decrease in precipitation occurs at Anzali in thenorth under scenario A2. However, under scenario B2 thesouthern part of country experiences the highest decrease ofprecipitation.

The highest increases of temperature under both scenariosoccur in western parts of Iran. Under both scenarios thelowest increase in temperature occurs in the southeast.Similar to the previous time periods, the highest increase inpotential evapotranspiration occurs in central Iran underboth scenarios for 2070–2099. The lowest increase of poten-tial evapotranspiration for 2070–2099, under both scenarios,also belongs to the southeast. The most threatened regions inthis time period are west and central parts of Iran, whichexperience the highest increases, respectively, in temperatureand potential evapotranspiration, which would increase water

loss from soils, vegetation and surfaces, and deplete subsur-face water resources. This would affect wildlife, natural eco-systems and people, especially during drought periods and thewarm seasons.

Overall, Tables 2–4 show that the highest increase intemperature occurs in western parts of the country, but thehighest increase in potential evapotranspiration belongs tocentral regions of Iran. However, variations of precipitationare different in different parts of the country depending onthe scenario used and the time period selected. It must bementioned that even an increase in precipitation would notresult in more availability of water due to the temperatureincrease, which would increase evapotranspiration. In gen-eral, it can be said that increasing average global temperatureswill result in a number of impacts on the hydrological cycle,including changes in precipitation. Precipitation will bedirectly impacted by changes in atmospheric circulation andincreases in atmospheric water vapour and evaporation asso-ciated with warmer temperatures. Precipitation changes areexpected to differ from region to region, as seen in thisresearch, with some areas becoming wetter and othersbecoming dryer. Any change in precipitation amount willresult in corresponding regional changes in runoff, thusimpacting water supply management regimes. Waterresources in arid and semi-arid regions, like most parts ofIran, will be most vulnerable to changes in precipitation, sincerunoff and river flows in these areas are particularly sensitiveto changes in precipitation. Additionally, changes in averagerainfall will impact groundwater recharge rates, thus poten-tially impacting water supplies. Water resource managers whoexperience a decrease in precipitation may have to explorenew sources of supply, implement demand managementactivities, or invest in new treatment techniques. Managerswho experience an increase in precipitation may need tomake infrastructure investments to mitigate an increasedrisk of flooding and higher reservoir levels, along with devel-oping new treatment processes. The results of this study aresimilar to those of other researchers, such as Azaranfar et al.(2009) on effects of climate change on temperature and pre-cipitation, and Ge et al. (2013), Khalil (2013) and Tanasijevicet al. (2014) on the effects of climate change onevapotranspiration.

5 Conclusions

Climate change modelling is fraught with uncertainties, butanalysis of these uncertainties is beyond the scope of thisresearch. As seen in this research, the results of the modelfor temperature, precipitation and potential evapotranspira-tion under the scenarios A2 and B2 are different in differentareas of Iran. The extreme values produced by scenario A2are higher than those of scenario B2. At all stations, for allthree time periods (2010–2039, 2040–2069 and 2070–2099)and under both scenarios, temperature increases but the rateof increase under scenario A2 is higher than under B2.Potential evapotranspiration is another parameter thatincreases in all three studied time periods under both scenar-ios and at all stations (except for a few stations in time period2010–2039) across the country, but the rate of increase under

Table 4. Extreme values of P, T and ET for 2070–2099 under scenarios A2 andB2.

Station Location inIran

A2 B2

P T ET P T ET

Babolsar North 835.0* 19.8 866.7 818.9 19.0 850.1Anzali North 1555.8# 20.9 890.7 1709.0 19.6 866.1Chabahar Southeast 85.5 28.7# 1206.5# 71.8 28.2# 1193.0Saghez West 337.3 17.0* 1366.1 390.5 15.6* 1211.0Garmsar Centre 83.1 22.7 2054.6* 92.4 21.3 1805.0*Shiraz South 250.9 22.0 1612.4 251.8# 20.7 1548.5Mashhad Northeast 227.9 18.2 1067.9 251.3* 16.8 990.5Iranshahr Southeast 54.5 31.1 1798.2 61.7 30.0 1757.3#

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scenario A2 is again higher than under B2. Therefore, it canbe said that, during the following decades and under bothscenarios, temperature and potential evapotranspiration showan increase, and this increase intensifies from 2010–2039toward 2070–2099. This condition would limit water avail-ability and increase the demand for water in different sectors.However, regarding precipitation, the results do not follow aclear ascending or descending trend like that seen for tem-perature and potential evapotranspiration. For example,under both scenarios in 2010–2039, some stations show anincrease but some show a decrease. From 2010–2039 toward2070–2099, more stations show a decrease in precipitation,and in 2070–2099 all but a few stations have a decrease inprecipitation compared to the base time period. Variation ofprecipitation under scenario A2 is higher than under B2.Although the results produced under scenarios A2 and B2are different, the general trends for all three parameters arealmost the same for both scenarios. This indicates that Iranwill be strongly affected by global warming and climatechange during future decades. As most parts of Iran arehyper-arid, arid and semi-arid regions, water shortage isalready a big problem for social and economic development.Mean annual precipitation over the country is about 250 mm,whereas mean annual potential evapotranspiration is over2100 mm, resulting in high sensitivity of the state to water-related problems. Climate change would definitely intensifythis condition over the coming decades. Therefore, to be ableto cope with the difficult conditions expected in the future,more research and efficient management and planning stra-tegies are required, especially for high-risk zones where thegreatest effects of climate change are expected to take place.According to this research, western parts of the country are atmost threat of water shortage in the future.

Disclosure statement

No potential conflict of interest was reported by the authors.

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