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BibTex RIS Kaynak Göster

Investigation of Climate Change Impact on Salt Lake by Statistical Methods

Yıl 2017, Cilt: 4 Sayı: 1, 54 - 62, 01.03.2017
https://doi.org/10.30897/ijegeo.306493

Öz

The main purpose of this paper is to investigate climate change impact that have been occurred on Salt Lake
located in the central Anatolia is one of the area that has been faced to extinction. In order to monitor current
status of the Salt Lake, Landsat satellite images has been obtained between the year of 2000 and 2014 (for the
months of February, May, August and November). Satellite images has been processed by using ArcGIS and
ERDAS softwares and the water surface area has been determined. The time series of water surface areas has
been analyzed with auto-correlation method and repeated pattern has been detected. The seasonal part of the
time series which period is 1 year and causes about 400 km² fluctuations has been removed with Moving
Average filter, successfully. As a result of filtration process, non-seasonal time series of water surface area of
Salt Lake were obtained. It is understood from the non-seasonal time series that the water surface area showed
variability between 2000 and 2010 and after 2010 it is stable until 2014. In order to explain the variability,
meteorological data (precipitation and temperature) of the surrounding area has been acquired from the related
service. The cross-correlation analyses has been performed with the movement of the water surface area and
meteorological time series. As a result of analysis, the relationship between water surface changes in Salt Lake
and meteorological data have correlated up to 80%. Consequently, several conclusion have been detected that
the topography of the region play a direct role of the correlation coefficients and the water surface changes are
effected from the environmental events that is occurred in the south of Salt Lake sub-Basin.

Kaynakça

  • AAT.(2007): All About Turkey. Available at: http://www.allaboutturkey.com/tuzlake.htm, (Accessed 27.11.2014). Birkett, C.M. (2000): Synergistic remote sensing of Lake Chad: variability of basin inundation. Remote Sens Environ. 72: 218–236.
  • Booth, E., Mount, J. and Viers, J. H. (2006): Hydrologic variability of the Cosumnes River floodplain. San Francisco Estuary and Watershed Science, 4(2):1-19.
  • Du, Y., Cai, S., Zhang and X., Zhao, Y.(2001): Interpretation of the environmental change of Dongting Lake, middle reach of Yangtze River, China, by 210Pb measurement and satellite image analysis. Geomorphology. 41:171–181.
  • Dube, O. (2001): Remote sensing, climate change and landuse impacts in semi-arid lands of Southern Africa. Geoscience and Remote Sensing Symposium, 2001. IGARSS apos;01. IEEE 2001 International. 6: 2686–2688.
  • Dunn, P. F. (2014). Measurement and data analysis for engineering and science. CRC press.
  • Gazioğlu C., Burak,S., Alpar, B., Türker, A. and Barut, IF. (2010): Foreseeable impacts of sea level rise on the southern coast of the Marmara Sea (Turkey), Water Policy.Vol.12(6): 932-943.
  • Kantarci, M. D. (2005): Forest ecosystems knowledge, Istanbul University published book no: 4594. Forest Faculty published no: 488, Istanbul (in Turkish).
  • Kiage, L.M., Liu, K.B., Walker, N.D., Lam, N. and Huh, O.K. (2007): Recent land-cover/use change associated with land degradation in the Lake Baringo catchment, Kenya, East Africa: evidence from Landsat TM and ETM+. Int J Remote Sens. 28(19),4285–4309.
  • Legesse, D. and Ayenew, T. (2006): Effect of improper water and land resource utilization on the central main Ethiopian rift lakes. Quat Int. 148,8–18.
  • Mcfeeters, S.K. (1996): The use of normalized difference water index (NDWI) in the delineation of open water features. International Journal of Remote Sensing. 17:1425–1432.
  • Medina, C.E., Enri, J.G. and Villares, A.P. (2008): Water level fluctuations derived Ftom ENVISAT Radar Altimeter (RA-2) and in-situ measurements in subtropical waterbody: Lake Izabel (Guatemala). Remote Sens Environ. 112: 3604–3617.
  • Mercier, F., Cazenave, A. and Maheu, C. (2002): Interannual lake level fluctuations (1993–1999) in Africa from Topex/Poseidon: connections with ocean–atmosphere interactions over the Indian Ocean. Glob Planet Changes. 32:141–163.
  • Moln’ar, P., Burlando, P. and Ruf, W.(2002): Integrated catchment assessment of riverine landscape dynamics. Aquat Sci. 64:129–140.
  • Orhan, O,. Ekercin, E, and Dadaser-Celik, F. (2014): Use of Landsat Land Surface Temperature and Vegetation Indices for Monitoring Drought in the Salt Lake Basin Area, Turkey. The Scientific World Journal. 2014, 11.
  • Penny, D. and Kealhofer, L. (2005): Microfossil evidence of land-use intensification in north Thailand. J Archaeol Sci. 32,69–82.
  • Piwowar, J. M. and Ledrew, E. F. (2002): ARMA time series modelling of remote sensing imagery: A new approach for climate change studies. International Journal of Remote Sensing. 23: 5225–5248.
  • Pozdnyakov, D., Korosov, A., Grassl, H. and Pettersson, L. (2005): An advanced algorithm for operational retrieval of water quality from satellite data in the visible. International Journal of Remote Sensing. 26: 2669–2687.
  • Simav Ö, Şeker DZ. and Gazioğlu C (2013) Coastal inundation due to sea level rise and extreme sea state and its potential impacts: Çukurova Delta case. Turkish J Earth sci 22:671–680.
  • Yalvaç, S. (2016): Detecting Land Subsidence in Konya Closed Basin by Means of GNSS Time Series, University of Selcuk).
  • Yang, X. and Lu, X. (2014): Drastic change in China's lakes and reservoirs over the past decades. Scientific Reports. 4, Article number:6041.
  • Yıldırım, U,. Erdoğan, S, and Uysal, M, (2011): Changes in the Coastline and Water Level of the Aksehir and Eber Lakes Between 1975 and 2009. Water Resources Management. 25:941–962.
Yıl 2017, Cilt: 4 Sayı: 1, 54 - 62, 01.03.2017
https://doi.org/10.30897/ijegeo.306493

Öz

Kaynakça

  • AAT.(2007): All About Turkey. Available at: http://www.allaboutturkey.com/tuzlake.htm, (Accessed 27.11.2014). Birkett, C.M. (2000): Synergistic remote sensing of Lake Chad: variability of basin inundation. Remote Sens Environ. 72: 218–236.
  • Booth, E., Mount, J. and Viers, J. H. (2006): Hydrologic variability of the Cosumnes River floodplain. San Francisco Estuary and Watershed Science, 4(2):1-19.
  • Du, Y., Cai, S., Zhang and X., Zhao, Y.(2001): Interpretation of the environmental change of Dongting Lake, middle reach of Yangtze River, China, by 210Pb measurement and satellite image analysis. Geomorphology. 41:171–181.
  • Dube, O. (2001): Remote sensing, climate change and landuse impacts in semi-arid lands of Southern Africa. Geoscience and Remote Sensing Symposium, 2001. IGARSS apos;01. IEEE 2001 International. 6: 2686–2688.
  • Dunn, P. F. (2014). Measurement and data analysis for engineering and science. CRC press.
  • Gazioğlu C., Burak,S., Alpar, B., Türker, A. and Barut, IF. (2010): Foreseeable impacts of sea level rise on the southern coast of the Marmara Sea (Turkey), Water Policy.Vol.12(6): 932-943.
  • Kantarci, M. D. (2005): Forest ecosystems knowledge, Istanbul University published book no: 4594. Forest Faculty published no: 488, Istanbul (in Turkish).
  • Kiage, L.M., Liu, K.B., Walker, N.D., Lam, N. and Huh, O.K. (2007): Recent land-cover/use change associated with land degradation in the Lake Baringo catchment, Kenya, East Africa: evidence from Landsat TM and ETM+. Int J Remote Sens. 28(19),4285–4309.
  • Legesse, D. and Ayenew, T. (2006): Effect of improper water and land resource utilization on the central main Ethiopian rift lakes. Quat Int. 148,8–18.
  • Mcfeeters, S.K. (1996): The use of normalized difference water index (NDWI) in the delineation of open water features. International Journal of Remote Sensing. 17:1425–1432.
  • Medina, C.E., Enri, J.G. and Villares, A.P. (2008): Water level fluctuations derived Ftom ENVISAT Radar Altimeter (RA-2) and in-situ measurements in subtropical waterbody: Lake Izabel (Guatemala). Remote Sens Environ. 112: 3604–3617.
  • Mercier, F., Cazenave, A. and Maheu, C. (2002): Interannual lake level fluctuations (1993–1999) in Africa from Topex/Poseidon: connections with ocean–atmosphere interactions over the Indian Ocean. Glob Planet Changes. 32:141–163.
  • Moln’ar, P., Burlando, P. and Ruf, W.(2002): Integrated catchment assessment of riverine landscape dynamics. Aquat Sci. 64:129–140.
  • Orhan, O,. Ekercin, E, and Dadaser-Celik, F. (2014): Use of Landsat Land Surface Temperature and Vegetation Indices for Monitoring Drought in the Salt Lake Basin Area, Turkey. The Scientific World Journal. 2014, 11.
  • Penny, D. and Kealhofer, L. (2005): Microfossil evidence of land-use intensification in north Thailand. J Archaeol Sci. 32,69–82.
  • Piwowar, J. M. and Ledrew, E. F. (2002): ARMA time series modelling of remote sensing imagery: A new approach for climate change studies. International Journal of Remote Sensing. 23: 5225–5248.
  • Pozdnyakov, D., Korosov, A., Grassl, H. and Pettersson, L. (2005): An advanced algorithm for operational retrieval of water quality from satellite data in the visible. International Journal of Remote Sensing. 26: 2669–2687.
  • Simav Ö, Şeker DZ. and Gazioğlu C (2013) Coastal inundation due to sea level rise and extreme sea state and its potential impacts: Çukurova Delta case. Turkish J Earth sci 22:671–680.
  • Yalvaç, S. (2016): Detecting Land Subsidence in Konya Closed Basin by Means of GNSS Time Series, University of Selcuk).
  • Yang, X. and Lu, X. (2014): Drastic change in China's lakes and reservoirs over the past decades. Scientific Reports. 4, Article number:6041.
  • Yıldırım, U,. Erdoğan, S, and Uysal, M, (2011): Changes in the Coastline and Water Level of the Aksehir and Eber Lakes Between 1975 and 2009. Water Resources Management. 25:941–962.
Toplam 21 adet kaynakça vardır.

Ayrıntılar

Bölüm Research Articles
Yazarlar

Osman Orhan

Sefa Yalvaç Bu kişi benim

Semih Ekercin

Yayımlanma Tarihi 1 Mart 2017
Yayımlandığı Sayı Yıl 2017 Cilt: 4 Sayı: 1

Kaynak Göster

APA Orhan, O., Yalvaç, S., & Ekercin, S. (2017). Investigation of Climate Change Impact on Salt Lake by Statistical Methods. International Journal of Environment and Geoinformatics, 4(1), 54-62. https://doi.org/10.30897/ijegeo.306493