Climate change forecasting in a mountainous data scarce watershed using CMIP5 models under representative concentration pathways

Hydrology cycle of river basins and available water resources in arid and semi-arid regions are highly affected by climate changes. In recent years, the increment of temperature due to excessive increased emission of greenhouse gases has led to an abnormality in the climate system of the earth. The...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Theoretical and applied climatology 2017-07, Vol.129 (1-2), p.683-699
Hauptverfasser: Aghakhani Afshar, A., Hasanzadeh, Y., Besalatpour, A. A., Pourreza-Bilondi, M.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 699
container_issue 1-2
container_start_page 683
container_title Theoretical and applied climatology
container_volume 129
creator Aghakhani Afshar, A.
Hasanzadeh, Y.
Besalatpour, A. A.
Pourreza-Bilondi, M.
description Hydrology cycle of river basins and available water resources in arid and semi-arid regions are highly affected by climate changes. In recent years, the increment of temperature due to excessive increased emission of greenhouse gases has led to an abnormality in the climate system of the earth. The main objective of this study is to survey the future climate changes in one of the biggest mountainous watersheds in northeast of Iran (i.e., Kashafrood). In this research, by considering the precipitation and temperature as two important climatic parameters in watersheds, 14 models evolved in the general circulation models (GCMs) of the newest generation in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were used to forecast the future climate changes in the study area. For the historical period of 1992–2005, four evaluation criteria including Nash–Sutcliffe (NS), percent of bias (PBIAS), coefficient of determination ( R 2 ) and the ratio of the root-mean-square-error to the standard deviation of measured data (RSR) were used to compare the simulated observed data for assessing goodness-of-fit of the models. In the primary results, four climate models namely GFDL-ESM2G, IPSL-CM5A-MR, MIROC-ESM, and NorESM1-M were selected among the abovementioned 14 models due to their more prediction accuracies to the investigated evaluation criteria. Thereafter, climate changes of the future periods (near-century, 2006–2037; mid-century, 2037–2070; and late-century, 2070–2100) were investigated and compared by four representative concentration pathways (RCPs) of new emission scenarios of RCP2.6, RCP4.5, RCP6.0, and RCP8.5. In order to assess the trend of annual and seasonal changes of climatic components, Mann–Kendall non-parametric test (MK) was also employed. The results of Mann–Kendall test revealed that the precipitation has significant variable trends of both positive and negative alterations. Furthermore, the mean, maximum, and minimum temperature values had significant positive trends at 90, 99, and 99.9 % confidence level. On the other hand, in all parts of the Kashafrood Watershed (KW), the average temperature of watershed will be increased up to 0.56–3.3 °C and the mean precipitation will be decreased up to 10.7 % by the end of the twenty-first century comparing to the historical baselines. Also, in seasonal scale, the maximum and minimum precipitations will occur in spring and summer, respectively, and the mean temperature is higher than the historical b
doi_str_mv 10.1007/s00704-016-1908-5
format Article
fullrecord <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_journals_1910455157</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A495733824</galeid><sourcerecordid>A495733824</sourcerecordid><originalsourceid>FETCH-LOGICAL-c389t-3e80021a4be8e22cb5426bb7d401b539864c28392be14a795933651dc5fd7743</originalsourceid><addsrcrecordid>eNp1kU9v3CAQxVHVSN0m_QC9IfXUg1MwYOAYrfpnpVStkhx6QxiPdx3twhZw0tz60Tsr99AcKiTQoN-beZpHyFvOLjlj-kPBi8mG8a7hlplGvSArLoVspDTiJVkxrnWjrfnxirwu5Z4x1nadXpHf6_108BVo2Pm4BTqmDMGXOsUtnSL19JDmWP0U01zo4KunJfgcgD6iKJcdDHQuJ3j9dfNdIT3AvtA5DpBphmOGAiiv0wNOSDFgkbFKkR593T36p3JBzka_L_Dm73tO7j59vFt_aa6_fd6sr66bIIytjQCDlrmXPRho29Ar2XZ9rwfJeK-ENZ0MrRG27YFLr62yQnSKD0GNg9ZSnJN3S9tjTj9nKNXdpzlHnOi45UwqxZVG6nKhtn4PbopjQrsBzwCHCf3DOOH_lbTICtOe2r5_JkCmwq-69XMpbnN785zlCxtyKiXD6I4Zd5-fHGfuFKJbQnQYojuF6BRq2kVTkMV88j-2_yv6A0lKn4g</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1910455157</pqid></control><display><type>article</type><title>Climate change forecasting in a mountainous data scarce watershed using CMIP5 models under representative concentration pathways</title><source>SpringerNature Journals</source><creator>Aghakhani Afshar, A. ; Hasanzadeh, Y. ; Besalatpour, A. A. ; Pourreza-Bilondi, M.</creator><creatorcontrib>Aghakhani Afshar, A. ; Hasanzadeh, Y. ; Besalatpour, A. A. ; Pourreza-Bilondi, M.</creatorcontrib><description>Hydrology cycle of river basins and available water resources in arid and semi-arid regions are highly affected by climate changes. In recent years, the increment of temperature due to excessive increased emission of greenhouse gases has led to an abnormality in the climate system of the earth. The main objective of this study is to survey the future climate changes in one of the biggest mountainous watersheds in northeast of Iran (i.e., Kashafrood). In this research, by considering the precipitation and temperature as two important climatic parameters in watersheds, 14 models evolved in the general circulation models (GCMs) of the newest generation in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were used to forecast the future climate changes in the study area. For the historical period of 1992–2005, four evaluation criteria including Nash–Sutcliffe (NS), percent of bias (PBIAS), coefficient of determination ( R 2 ) and the ratio of the root-mean-square-error to the standard deviation of measured data (RSR) were used to compare the simulated observed data for assessing goodness-of-fit of the models. In the primary results, four climate models namely GFDL-ESM2G, IPSL-CM5A-MR, MIROC-ESM, and NorESM1-M were selected among the abovementioned 14 models due to their more prediction accuracies to the investigated evaluation criteria. Thereafter, climate changes of the future periods (near-century, 2006–2037; mid-century, 2037–2070; and late-century, 2070–2100) were investigated and compared by four representative concentration pathways (RCPs) of new emission scenarios of RCP2.6, RCP4.5, RCP6.0, and RCP8.5. In order to assess the trend of annual and seasonal changes of climatic components, Mann–Kendall non-parametric test (MK) was also employed. The results of Mann–Kendall test revealed that the precipitation has significant variable trends of both positive and negative alterations. Furthermore, the mean, maximum, and minimum temperature values had significant positive trends at 90, 99, and 99.9 % confidence level. On the other hand, in all parts of the Kashafrood Watershed (KW), the average temperature of watershed will be increased up to 0.56–3.3 °C and the mean precipitation will be decreased up to 10.7 % by the end of the twenty-first century comparing to the historical baselines. Also, in seasonal scale, the maximum and minimum precipitations will occur in spring and summer, respectively, and the mean temperature is higher than the historical baseline in all seasons. The maximum and minimum values of the mean temperature will occur in summer and winter, respectively, and the amount of seasonal precipitation in these seasons will be reduced.</description><identifier>ISSN: 0177-798X</identifier><identifier>EISSN: 1434-4483</identifier><identifier>DOI: 10.1007/s00704-016-1908-5</identifier><language>eng</language><publisher>Vienna: Springer Vienna</publisher><subject>Air pollution ; Analysis ; Annual variations ; Aquatic Pollution ; Area ; Arid regions ; Arid zones ; Atmospheric precipitations ; Atmospheric Protection/Air Quality Control/Air Pollution ; Atmospheric Sciences ; Basins ; Bias ; Circulation ; Climate ; Climate change ; Climate models ; Climate science ; Climate system ; Climatology ; Coefficients ; Components ; Data ; Deviation ; Earth ; Earth and Environmental Science ; Earth Sciences ; Emission ; Emissions ; Error analysis ; Evaluation ; Forecasting ; Future climates ; Gases ; General circulation ; General circulation models ; Global temperature changes ; Greenhouse effect ; Greenhouse gases ; Hydrology ; Intercomparison ; Mean precipitation ; Mean temperatures ; Mountains ; Original Paper ; Parameters ; Precipitation ; Precipitation (Meteorology) ; River basins ; Seasonal precipitation ; Seasonal variation ; Seasonal variations ; Seasons ; Semi arid areas ; Semiarid lands ; Simulation ; Spring (season) ; Standard deviation ; Summer ; Surveying ; Surveys ; Temperature ; Temperature effects ; Trends ; Waste Water Technology ; Water Management ; Water Pollution Control ; Water resources ; Water temperature ; Watersheds ; Winter</subject><ispartof>Theoretical and applied climatology, 2017-07, Vol.129 (1-2), p.683-699</ispartof><rights>Springer-Verlag Wien 2016</rights><rights>COPYRIGHT 2017 Springer</rights><rights>Theoretical and Applied Climatology is a copyright of Springer, 2017.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c389t-3e80021a4be8e22cb5426bb7d401b539864c28392be14a795933651dc5fd7743</citedby><cites>FETCH-LOGICAL-c389t-3e80021a4be8e22cb5426bb7d401b539864c28392be14a795933651dc5fd7743</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00704-016-1908-5$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00704-016-1908-5$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Aghakhani Afshar, A.</creatorcontrib><creatorcontrib>Hasanzadeh, Y.</creatorcontrib><creatorcontrib>Besalatpour, A. A.</creatorcontrib><creatorcontrib>Pourreza-Bilondi, M.</creatorcontrib><title>Climate change forecasting in a mountainous data scarce watershed using CMIP5 models under representative concentration pathways</title><title>Theoretical and applied climatology</title><addtitle>Theor Appl Climatol</addtitle><description>Hydrology cycle of river basins and available water resources in arid and semi-arid regions are highly affected by climate changes. In recent years, the increment of temperature due to excessive increased emission of greenhouse gases has led to an abnormality in the climate system of the earth. The main objective of this study is to survey the future climate changes in one of the biggest mountainous watersheds in northeast of Iran (i.e., Kashafrood). In this research, by considering the precipitation and temperature as two important climatic parameters in watersheds, 14 models evolved in the general circulation models (GCMs) of the newest generation in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were used to forecast the future climate changes in the study area. For the historical period of 1992–2005, four evaluation criteria including Nash–Sutcliffe (NS), percent of bias (PBIAS), coefficient of determination ( R 2 ) and the ratio of the root-mean-square-error to the standard deviation of measured data (RSR) were used to compare the simulated observed data for assessing goodness-of-fit of the models. In the primary results, four climate models namely GFDL-ESM2G, IPSL-CM5A-MR, MIROC-ESM, and NorESM1-M were selected among the abovementioned 14 models due to their more prediction accuracies to the investigated evaluation criteria. Thereafter, climate changes of the future periods (near-century, 2006–2037; mid-century, 2037–2070; and late-century, 2070–2100) were investigated and compared by four representative concentration pathways (RCPs) of new emission scenarios of RCP2.6, RCP4.5, RCP6.0, and RCP8.5. In order to assess the trend of annual and seasonal changes of climatic components, Mann–Kendall non-parametric test (MK) was also employed. The results of Mann–Kendall test revealed that the precipitation has significant variable trends of both positive and negative alterations. Furthermore, the mean, maximum, and minimum temperature values had significant positive trends at 90, 99, and 99.9 % confidence level. On the other hand, in all parts of the Kashafrood Watershed (KW), the average temperature of watershed will be increased up to 0.56–3.3 °C and the mean precipitation will be decreased up to 10.7 % by the end of the twenty-first century comparing to the historical baselines. Also, in seasonal scale, the maximum and minimum precipitations will occur in spring and summer, respectively, and the mean temperature is higher than the historical baseline in all seasons. The maximum and minimum values of the mean temperature will occur in summer and winter, respectively, and the amount of seasonal precipitation in these seasons will be reduced.</description><subject>Air pollution</subject><subject>Analysis</subject><subject>Annual variations</subject><subject>Aquatic Pollution</subject><subject>Area</subject><subject>Arid regions</subject><subject>Arid zones</subject><subject>Atmospheric precipitations</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>Atmospheric Sciences</subject><subject>Basins</subject><subject>Bias</subject><subject>Circulation</subject><subject>Climate</subject><subject>Climate change</subject><subject>Climate models</subject><subject>Climate science</subject><subject>Climate system</subject><subject>Climatology</subject><subject>Coefficients</subject><subject>Components</subject><subject>Data</subject><subject>Deviation</subject><subject>Earth</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Emission</subject><subject>Emissions</subject><subject>Error analysis</subject><subject>Evaluation</subject><subject>Forecasting</subject><subject>Future climates</subject><subject>Gases</subject><subject>General circulation</subject><subject>General circulation models</subject><subject>Global temperature changes</subject><subject>Greenhouse effect</subject><subject>Greenhouse gases</subject><subject>Hydrology</subject><subject>Intercomparison</subject><subject>Mean precipitation</subject><subject>Mean temperatures</subject><subject>Mountains</subject><subject>Original Paper</subject><subject>Parameters</subject><subject>Precipitation</subject><subject>Precipitation (Meteorology)</subject><subject>River basins</subject><subject>Seasonal precipitation</subject><subject>Seasonal variation</subject><subject>Seasonal variations</subject><subject>Seasons</subject><subject>Semi arid areas</subject><subject>Semiarid lands</subject><subject>Simulation</subject><subject>Spring (season)</subject><subject>Standard deviation</subject><subject>Summer</subject><subject>Surveying</subject><subject>Surveys</subject><subject>Temperature</subject><subject>Temperature effects</subject><subject>Trends</subject><subject>Waste Water Technology</subject><subject>Water Management</subject><subject>Water Pollution Control</subject><subject>Water resources</subject><subject>Water temperature</subject><subject>Watersheds</subject><subject>Winter</subject><issn>0177-798X</issn><issn>1434-4483</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kU9v3CAQxVHVSN0m_QC9IfXUg1MwYOAYrfpnpVStkhx6QxiPdx3twhZw0tz60Tsr99AcKiTQoN-beZpHyFvOLjlj-kPBi8mG8a7hlplGvSArLoVspDTiJVkxrnWjrfnxirwu5Z4x1nadXpHf6_108BVo2Pm4BTqmDMGXOsUtnSL19JDmWP0U01zo4KunJfgcgD6iKJcdDHQuJ3j9dfNdIT3AvtA5DpBphmOGAiiv0wNOSDFgkbFKkR593T36p3JBzka_L_Dm73tO7j59vFt_aa6_fd6sr66bIIytjQCDlrmXPRho29Ar2XZ9rwfJeK-ENZ0MrRG27YFLr62yQnSKD0GNg9ZSnJN3S9tjTj9nKNXdpzlHnOi45UwqxZVG6nKhtn4PbopjQrsBzwCHCf3DOOH_lbTICtOe2r5_JkCmwq-69XMpbnN785zlCxtyKiXD6I4Zd5-fHGfuFKJbQnQYojuF6BRq2kVTkMV88j-2_yv6A0lKn4g</recordid><startdate>20170701</startdate><enddate>20170701</enddate><creator>Aghakhani Afshar, A.</creator><creator>Hasanzadeh, Y.</creator><creator>Besalatpour, A. A.</creator><creator>Pourreza-Bilondi, M.</creator><general>Springer Vienna</general><general>Springer</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ISR</scope><scope>3V.</scope><scope>7QH</scope><scope>7TG</scope><scope>7TN</scope><scope>7UA</scope><scope>7XB</scope><scope>88I</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>L6V</scope><scope>M2P</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope></search><sort><creationdate>20170701</creationdate><title>Climate change forecasting in a mountainous data scarce watershed using CMIP5 models under representative concentration pathways</title><author>Aghakhani Afshar, A. ; Hasanzadeh, Y. ; Besalatpour, A. A. ; Pourreza-Bilondi, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c389t-3e80021a4be8e22cb5426bb7d401b539864c28392be14a795933651dc5fd7743</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Air pollution</topic><topic>Analysis</topic><topic>Annual variations</topic><topic>Aquatic Pollution</topic><topic>Area</topic><topic>Arid regions</topic><topic>Arid zones</topic><topic>Atmospheric precipitations</topic><topic>Atmospheric Protection/Air Quality Control/Air Pollution</topic><topic>Atmospheric Sciences</topic><topic>Basins</topic><topic>Bias</topic><topic>Circulation</topic><topic>Climate</topic><topic>Climate change</topic><topic>Climate models</topic><topic>Climate science</topic><topic>Climate system</topic><topic>Climatology</topic><topic>Coefficients</topic><topic>Components</topic><topic>Data</topic><topic>Deviation</topic><topic>Earth</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Emission</topic><topic>Emissions</topic><topic>Error analysis</topic><topic>Evaluation</topic><topic>Forecasting</topic><topic>Future climates</topic><topic>Gases</topic><topic>General circulation</topic><topic>General circulation models</topic><topic>Global temperature changes</topic><topic>Greenhouse effect</topic><topic>Greenhouse gases</topic><topic>Hydrology</topic><topic>Intercomparison</topic><topic>Mean precipitation</topic><topic>Mean temperatures</topic><topic>Mountains</topic><topic>Original Paper</topic><topic>Parameters</topic><topic>Precipitation</topic><topic>Precipitation (Meteorology)</topic><topic>River basins</topic><topic>Seasonal precipitation</topic><topic>Seasonal variation</topic><topic>Seasonal variations</topic><topic>Seasons</topic><topic>Semi arid areas</topic><topic>Semiarid lands</topic><topic>Simulation</topic><topic>Spring (season)</topic><topic>Standard deviation</topic><topic>Summer</topic><topic>Surveying</topic><topic>Surveys</topic><topic>Temperature</topic><topic>Temperature effects</topic><topic>Trends</topic><topic>Waste Water Technology</topic><topic>Water Management</topic><topic>Water Pollution Control</topic><topic>Water resources</topic><topic>Water temperature</topic><topic>Watersheds</topic><topic>Winter</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Aghakhani Afshar, A.</creatorcontrib><creatorcontrib>Hasanzadeh, Y.</creatorcontrib><creatorcontrib>Besalatpour, A. A.</creatorcontrib><creatorcontrib>Pourreza-Bilondi, M.</creatorcontrib><collection>CrossRef</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Aqualine</collection><collection>Meteorological &amp; Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Earth, Atmospheric &amp; Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ProQuest Central Student</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy &amp; Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Meteorological &amp; Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) Professional</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Science Journals</collection><collection>Engineering Database</collection><collection>ProQuest advanced technologies &amp; aerospace journals</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>Earth, Atmospheric &amp; Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering collection</collection><collection>ProQuest Central Basic</collection><jtitle>Theoretical and applied climatology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Aghakhani Afshar, A.</au><au>Hasanzadeh, Y.</au><au>Besalatpour, A. A.</au><au>Pourreza-Bilondi, M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Climate change forecasting in a mountainous data scarce watershed using CMIP5 models under representative concentration pathways</atitle><jtitle>Theoretical and applied climatology</jtitle><stitle>Theor Appl Climatol</stitle><date>2017-07-01</date><risdate>2017</risdate><volume>129</volume><issue>1-2</issue><spage>683</spage><epage>699</epage><pages>683-699</pages><issn>0177-798X</issn><eissn>1434-4483</eissn><abstract>Hydrology cycle of river basins and available water resources in arid and semi-arid regions are highly affected by climate changes. In recent years, the increment of temperature due to excessive increased emission of greenhouse gases has led to an abnormality in the climate system of the earth. The main objective of this study is to survey the future climate changes in one of the biggest mountainous watersheds in northeast of Iran (i.e., Kashafrood). In this research, by considering the precipitation and temperature as two important climatic parameters in watersheds, 14 models evolved in the general circulation models (GCMs) of the newest generation in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were used to forecast the future climate changes in the study area. For the historical period of 1992–2005, four evaluation criteria including Nash–Sutcliffe (NS), percent of bias (PBIAS), coefficient of determination ( R 2 ) and the ratio of the root-mean-square-error to the standard deviation of measured data (RSR) were used to compare the simulated observed data for assessing goodness-of-fit of the models. In the primary results, four climate models namely GFDL-ESM2G, IPSL-CM5A-MR, MIROC-ESM, and NorESM1-M were selected among the abovementioned 14 models due to their more prediction accuracies to the investigated evaluation criteria. Thereafter, climate changes of the future periods (near-century, 2006–2037; mid-century, 2037–2070; and late-century, 2070–2100) were investigated and compared by four representative concentration pathways (RCPs) of new emission scenarios of RCP2.6, RCP4.5, RCP6.0, and RCP8.5. In order to assess the trend of annual and seasonal changes of climatic components, Mann–Kendall non-parametric test (MK) was also employed. The results of Mann–Kendall test revealed that the precipitation has significant variable trends of both positive and negative alterations. Furthermore, the mean, maximum, and minimum temperature values had significant positive trends at 90, 99, and 99.9 % confidence level. On the other hand, in all parts of the Kashafrood Watershed (KW), the average temperature of watershed will be increased up to 0.56–3.3 °C and the mean precipitation will be decreased up to 10.7 % by the end of the twenty-first century comparing to the historical baselines. Also, in seasonal scale, the maximum and minimum precipitations will occur in spring and summer, respectively, and the mean temperature is higher than the historical baseline in all seasons. The maximum and minimum values of the mean temperature will occur in summer and winter, respectively, and the amount of seasonal precipitation in these seasons will be reduced.</abstract><cop>Vienna</cop><pub>Springer Vienna</pub><doi>10.1007/s00704-016-1908-5</doi><tpages>17</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0177-798X
ispartof Theoretical and applied climatology, 2017-07, Vol.129 (1-2), p.683-699
issn 0177-798X
1434-4483
language eng
recordid cdi_proquest_journals_1910455157
source SpringerNature Journals
subjects Air pollution
Analysis
Annual variations
Aquatic Pollution
Area
Arid regions
Arid zones
Atmospheric precipitations
Atmospheric Protection/Air Quality Control/Air Pollution
Atmospheric Sciences
Basins
Bias
Circulation
Climate
Climate change
Climate models
Climate science
Climate system
Climatology
Coefficients
Components
Data
Deviation
Earth
Earth and Environmental Science
Earth Sciences
Emission
Emissions
Error analysis
Evaluation
Forecasting
Future climates
Gases
General circulation
General circulation models
Global temperature changes
Greenhouse effect
Greenhouse gases
Hydrology
Intercomparison
Mean precipitation
Mean temperatures
Mountains
Original Paper
Parameters
Precipitation
Precipitation (Meteorology)
River basins
Seasonal precipitation
Seasonal variation
Seasonal variations
Seasons
Semi arid areas
Semiarid lands
Simulation
Spring (season)
Standard deviation
Summer
Surveying
Surveys
Temperature
Temperature effects
Trends
Waste Water Technology
Water Management
Water Pollution Control
Water resources
Water temperature
Watersheds
Winter
title Climate change forecasting in a mountainous data scarce watershed using CMIP5 models under representative concentration pathways
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-28T11%3A33%3A12IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Climate%20change%20forecasting%20in%20a%20mountainous%20data%20scarce%20watershed%20using%20CMIP5%20models%20under%20representative%20concentration%20pathways&rft.jtitle=Theoretical%20and%20applied%20climatology&rft.au=Aghakhani%20Afshar,%20A.&rft.date=2017-07-01&rft.volume=129&rft.issue=1-2&rft.spage=683&rft.epage=699&rft.pages=683-699&rft.issn=0177-798X&rft.eissn=1434-4483&rft_id=info:doi/10.1007/s00704-016-1908-5&rft_dat=%3Cgale_proqu%3EA495733824%3C/gale_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1910455157&rft_id=info:pmid/&rft_galeid=A495733824&rfr_iscdi=true