The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-4/W4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W4, 5–9, 2017
https://doi.org/10.5194/isprs-archives-XLII-4-W4-5-2017
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W4, 5–9, 2017
https://doi.org/10.5194/isprs-archives-XLII-4-W4-5-2017

  26 Sep 2017

26 Sep 2017

INVESTIGATING AND MODELLING EFFECTS OF CLIMATICALLY AND HYDROLOGICALLY INDICATORS ON THE URMIA LAKE COASTLINE CHANGES USING TIME SERIES ANALYSIS

M. Ahmadijamal and M. Hasanlou M. Ahmadijamal and M. Hasanlou
  • School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran

Keywords: Modelling, Water level changes, Hydrological indicator, climatically indicator, Time series, Urmia Lake

Abstract. Study of hydrological parameters of lakes and examine the variation of water level to operate management on water resources are important. The purpose of this study is to investigate and model the Urmia Lake water level changes due to changes in climatically and hydrological indicators that affects in the process of level variation and area of this lake. For this purpose, Landsat satellite images, hydrological data, the daily precipitation, the daily surface evaporation and the daily discharge in total of the lake basin during the period of 2010-2016 have been used. Based on time-series analysis that is conducted on individual data independently with same procedure, to model variation of Urmia Lake level, we used polynomial regression technique and combined polynomial with periodic behavior. In the first scenario, we fit a multivariate linear polynomial to our datasets and determining RMSE, NRSME and R² value. We found that fourth degree polynomial can better fit to our datasets with lowest RMSE value about 9 cm. In the second scenario, we combine polynomial with periodic behavior for modeling. The second scenario has superiority comparing to the first one, by RMSE value about 3 cm.