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<Article>
<Journal>
				<PublisherName>دانشگاه کاشان</PublisherName>
				<JournalTitle>مهندسی اکوسیستم بیابان</JournalTitle>
				<Issn>2538-6336</Issn>
				<Volume>15</Volume>
				<Issue>51</Issue>
				<PubDate PubStatus="epublish">
					<Year>2026</Year>
					<Month>08</Month>
					<Day>23</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Assessment of Climate Variables under CMIP6 Future Climate Scenarios in a Semi-Arid Region of Northwestern Iran</ArticleTitle>
<VernacularTitle>Assessment of Climate Variables under CMIP6 Future Climate Scenarios in a Semi-Arid Region of Northwestern Iran</VernacularTitle>
			<FirstPage>1</FirstPage>
			<LastPage>17</LastPage>
			<ELocationID EIdType="pii">115623</ELocationID>
			
<ELocationID EIdType="doi">‎10.22052/deej.2026.258580.1140</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Raoof</FirstName>
					<LastName>Mostafazadeh</LastName>
<Affiliation>Department of Natural Resources, Faculty of Agriculture and Natural Resources, Member of Water Management Research Center, University of Mohaghegh Ardabili, Ardabil, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Ali</FirstName>
					<LastName>Nasiri Khiavi</LastName>
<Affiliation>Ardabil Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Ardabil, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Shahnaz</FirstName>
					<LastName>Mirzaei</LastName>
<Affiliation>Department of Watershed Management, Faculty of Range and Watershed Management, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2026</Year>
					<Month>04</Month>
					<Day>30</Day>
				</PubDate>
			</History>
		<Abstract>Climate change, largely driven by anthropogenic activities, has intensified the frequency and severity of extreme weather events, including floods, droughts, hailstorms, heatwaves, and anomalous cold spells. This study evaluates the performance of three CMIP6 models (ACCESS-CM2, MIROC6, and NESM3) in simulating daily precipitation and temperature for the flood-prone Gharesou watershed in Ardabil, Iran. The models were validated against observed data from 1984–2014 using statistical metrics, including Root Mean Square Error (RMSE), Percent Bias (PBIAS), and the Nash-Sutcliffe Efficiency (NSE). Following validation, future projections were downscaled and bias-corrected under SSP1-2.6, SSP2-4.5, and SSP3-7.0 scenarios using the delta change method. Based on the superior performance in PBIAS and NSE metrics across all stations—with minor exceptions in specific precipitation and maximum temperature parameters at the Ardabil and Namin stations—the ACCESS-CM2 model was selected for long-term projections. The results indicate a general downward trend in monthly precipitation, with localized exceptions during the June–August period in Ardabil, March–August at the Airport station, and July in Namin and Nir. A comparative analysis between observed and projected mean annual precipitation under the SSP1-2.6 scenario reveals site-specific variations: declines of 31.07 mm, 37.60 mm, and 116.69 mm at the Ardabil, Namin, and Nir stations, respectively, alongside a marginal increase of 1.44 mm at the Ardabil airport station. Furthermore, all scenarios project a consistent rise in mean annual maximum and minimum temperatures. Specifically, the projected increase in maximum temperature ranges from 1.2 °C (SSP2-4.5, Ardabil) to 2.05 °C (SSP1-2.6, Namin), while minimum temperatures are expected to rise by 3.65 °C (SSP2-4.5, Namin) to 7.75 °C (SSP1-2.6, Ardabil airport). These forecasts, characterized by decreasing precipitation and significant warming, underscore the likelihood of imminent climate-driven extremes. Consequently, these findings provide a critical foundation for water resource managers to develop targeted risk mitigation strategies and enhance environmental and hydrological resilience in the region.</Abstract>
			<OtherAbstract Language="FA">Climate change, largely driven by anthropogenic activities, has intensified the frequency and severity of extreme weather events, including floods, droughts, hailstorms, heatwaves, and anomalous cold spells. This study evaluates the performance of three CMIP6 models (ACCESS-CM2, MIROC6, and NESM3) in simulating daily precipitation and temperature for the flood-prone Gharesou watershed in Ardabil, Iran. The models were validated against observed data from 1984–2014 using statistical metrics, including Root Mean Square Error (RMSE), Percent Bias (PBIAS), and the Nash-Sutcliffe Efficiency (NSE). Following validation, future projections were downscaled and bias-corrected under SSP1-2.6, SSP2-4.5, and SSP3-7.0 scenarios using the delta change method. Based on the superior performance in PBIAS and NSE metrics across all stations—with minor exceptions in specific precipitation and maximum temperature parameters at the Ardabil and Namin stations—the ACCESS-CM2 model was selected for long-term projections. The results indicate a general downward trend in monthly precipitation, with localized exceptions during the June–August period in Ardabil, March–August at the Airport station, and July in Namin and Nir. A comparative analysis between observed and projected mean annual precipitation under the SSP1-2.6 scenario reveals site-specific variations: declines of 31.07 mm, 37.60 mm, and 116.69 mm at the Ardabil, Namin, and Nir stations, respectively, alongside a marginal increase of 1.44 mm at the Ardabil airport station. Furthermore, all scenarios project a consistent rise in mean annual maximum and minimum temperatures. Specifically, the projected increase in maximum temperature ranges from 1.2 °C (SSP2-4.5, Ardabil) to 2.05 °C (SSP1-2.6, Namin), while minimum temperatures are expected to rise by 3.65 °C (SSP2-4.5, Namin) to 7.75 °C (SSP1-2.6, Ardabil airport). These forecasts, characterized by decreasing precipitation and significant warming, underscore the likelihood of imminent climate-driven extremes. Consequently, these findings provide a critical foundation for water resource managers to develop targeted risk mitigation strategies and enhance environmental and hydrological resilience in the region.</OtherAbstract>
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			<Object Type="keyword">
			<Param Name="value">Delta change factor</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Bias correction</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">ACCESS-CM2 model</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">SSP1-2.6 scenario</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Gharesou watershed</Param>
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<ArchiveCopySource DocType="pdf">https://deej.kashanu.ac.ir/article_115623_50a176c519b97aa5a1c8f034e13bb3f8.pdf</ArchiveCopySource>
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