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<!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.7//EN" "https://dtd.nlm.nih.gov/ncbi/pubmed/in/PubMed.dtd">
<ArticleSet>
<Article>
<Journal>
				<PublisherName>انجمن هیدرولیک ایران</PublisherName>
				<JournalTitle>نشریه علمی هیدرولیک</JournalTitle>
				<Issn>2345-4237</Issn>
				<Volume>3</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2008</Year>
					<Month>05</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Simulation of Urmia Lake Level Changes and Its Uncertainty and Sensitivity to Water Budget Components</ArticleTitle>
<VernacularTitle>شبیه سازی، تحلیل حساسیت و عدم قطعیت تغییرات تراز آب دریاچه ارومیه نسبت به مولفه های بیلان آبی آن</VernacularTitle>
			<FirstPage>45</FirstPage>
			<LastPage>55</LastPage>
			<ELocationID EIdType="pii">85448</ELocationID>
			
<ELocationID EIdType="doi">10.30482/jhyd.2008.85448</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>مجید</FirstName>
					<LastName>دلاور</LastName>
<Affiliation></Affiliation>
<Identifier Source="ORCID">0000-0003-3897-8007</Identifier>

</Author>
<Author>
					<FirstName>سعید</FirstName>
					<LastName>مرید</LastName>
<Affiliation>دانشگاه تربیت مدرس دانشکده کشاورزی</Affiliation>

</Author>
<Author>
					<FirstName>مهدی</FirstName>
					<LastName>شفیعی فر</LastName>
<Affiliation></Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2008</Year>
					<Month>03</Month>
					<Day>21</Day>
				</PubDate>
			</History>
		<Abstract>This research work is an attempt to simulate and analyze monthly water level changes in Urmia Lake.&lt;br /&gt;To this end, water budget, multiple regression and artificial neural networks (ANNs) approaches have&lt;br /&gt;been investigated, using monthly data of effective components of water budget equation such as input&lt;br /&gt;discharge, average rainfall and average evaporation. Furthermore, uncertainty and sensitivity analysis&lt;br /&gt;were employed to compare the simulation methods capabilities. The results suggested that ANNs&lt;br /&gt;model using monthly discharge, rainfall and evaporation as inputs gave best results with less&lt;br /&gt;sensitivity, but greater uncertainty.</Abstract>
			<OtherAbstract Language="FA"></OtherAbstract>
<ArchiveCopySource DocType="pdf">https://jhyd.iha.ir/article_85448_ec9257e066b6ca9d278e4ba4c00d8a21.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
