UNIVARIATE AND MULTIVARIATE TIME SERIES ASSESSMENT IN FORECASTING URMIA LAKE WATER LEVEL

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

KHALILI K.; NAZERI TAHROUDI M.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Iranian Journal of Irrigation and Drainage Year:2016 | Volume:10 | Issue:2 Page(s): 145-155

Download Full-Text

Persian Verion

View:

1,446

Download:

Cites:

Information Journal Paper

Title

UNIVARIATE AND MULTIVARIATE TIME SERIES ASSESSMENT IN FORECASTING URMIA LAKE WATER LEVEL

Author(s)

KHALILI K. | NAZERI TAHROUDI M. | Issue Writer Certificate

Keywords

ARMA MODELQ2

CARMA MODELQ1

FORECASTINGQ2

TIME SERIESQ2

URMIA LAKEQ1

Abstract

For over three decades, hydrologists were recommended multivariate models to describe and modeling complex hydrological processes. While recently the multivariate models in hydrology is discussed. In multivariate models, the modeling and predicting various parameters can be improved by involving other factors.In this study, univariate and contemporaneous multivariate ARMA MODELs (CARMA) were evaluated for modeling of URMIA LAKE water level. The TIME SERIES of URMIA LAKE water level in annual scale in the period of 1982-2011 were used for ARMA MODELs and the TIME SERIES of Shahrchai, Nazloochai and Barandoozchai flow rates and URMIA LAKE water level in mentioned data period were used for CARMA MODELs. The results of evaluation and verification of models showed that by adding river flow data, the accuracy of modeling and verification of models will increase. Also the results showed that according to R-square coefficient equal to 0.75 between validation data of models and the root mean square error criterion equal to 0.62, the CARMA MODELs can provide better results than ARMA MODELs. Using multivariate models in the modeling and FORECASTING of URMIA LAKE water level increased the accuracy of modeling about 20 percent.

Cites

No record.

References

No record.

Cite

APA: Copy

KHALILI, K., & NAZERI TAHROUDI, M.. (2016). UNIVARIATE AND MULTIVARIATE TIME SERIES ASSESSMENT IN FORECASTING URMIA LAKE WATER LEVEL. IRANIAN JOURNAL OF IRRIGATION AND DRAINAGE, 10(2 ), 145-155. SID. https://sid.ir/paper/131608/en

Vancouver: Copy

KHALILI K., NAZERI TAHROUDI M.. UNIVARIATE AND MULTIVARIATE TIME SERIES ASSESSMENT IN FORECASTING URMIA LAKE WATER LEVEL. IRANIAN JOURNAL OF IRRIGATION AND DRAINAGE[Internet]. 2016;10(2 ):145-155. Available from: https://sid.ir/paper/131608/en

IEEE: Copy

K. KHALILI, and M. NAZERI TAHROUDI, “UNIVARIATE AND MULTIVARIATE TIME SERIES ASSESSMENT IN FORECASTING URMIA LAKE WATER LEVEL,” IRANIAN JOURNAL OF IRRIGATION AND DRAINAGE, vol. 10, no. 2 , pp. 145–155, 2016, [Online]. Available: https://sid.ir/paper/131608/en

Related Journal Papers