Prediction lake level variations using satellite observations in Caspian Sea: Case study

M. Imani, R. J. You, C. Y. Kuo

研究成果: Conference contribution

摘要

The demand for accurate predictions of sea level fluctuations in coastal management and ship navigation activities is increasing. To meet such demand, accessible high-quality data and proper modeling process are critically required. In this study, we successfully present the analysis and forecasting of Caspian Sea level anomalies based on about 15-year Topex/Poseidon and Jason-1 altimetry data covering 1993-2008, which are originally developed and optimized for open oceans but have the considerable capability to monitor inland water level changes. The forecast is performed by Holt-Winters exponential smoothing (HWES) and multi-layer perceptron (MLP) neural network as alternative methods to the conventional models to assess their applicability for estimating Caspian Sea level anomalies. The modeling results agree well with the observed time series and satisfactorily present reliable results for the short-term prediction of Caspian Sea level anomalies providing reasonable precision and accuracy for supporting water reservoir management plans.

原文English
主出版物標題34th Asian Conference on Remote Sensing 2013, ACRS 2013
發行者Asian Association on Remote Sensing
頁面1710-1715
頁數6
ISBN(列印)9781629939100
出版狀態Published - 2013
事件34th Asian Conference on Remote Sensing 2013, ACRS 2013 - Bali, Indonesia
持續時間: 2013 10月 202013 10月 24

出版系列

名字34th Asian Conference on Remote Sensing 2013, ACRS 2013
2

Other

Other34th Asian Conference on Remote Sensing 2013, ACRS 2013
國家/地區Indonesia
城市Bali
期間13-10-2013-10-24

All Science Journal Classification (ASJC) codes

  • 電腦網路與通信

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