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...
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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 |
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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. 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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> |
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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 |