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Spatial Analysis of Monthly and Annual Precipitation Trends in Turkey

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  • Hüseyin Yavuz
  • Saffet Erdoğan

Abstract

Global climate change could have important effects on various environmental variables in many countries around the world. Changes in precipitation regime directly affect water resources management. So that, it is important to analyze the changes in the spatial and temporal rainfall pattern in order to improve water resources management policies. For this reason, non-parametric Mann-Kendall rank correlation test is used in order to examine the existence of trends in annual and monthly rainfall distribution. To understand the regional differences of precipitation in Turkey, the detected trends are spatially interpolated using geostatistical techniques in a GIS environment. The main objective of this paper is to evaluate three interpolation methods, concerning their suitability for spatial prediction of temporal trends of Turkey’s monthly and annual rainfall data. The study used a dense and homogeneous monthly precipitation database comprising 120 rain-gauge stations over a 32 years testing period of 1975–2009. The results conclusively show that significant positive trends are both infrequent and found only in outlying stations during March, April and October. In order to estimate and characterize the magnitude of observed changes at unmeasured locations, Ordinary Kriging, Inverse Distance Weighted and Completely Regularized Spline interpolation methods were employed and compared. A comparative analysis of interpolation techniques shows that Ordinary Kriging with having RMSE of 0.148 is the best choice. This is followed by Inverse Distance Weighted (RMSE 0.151), and Splines (RMSE 0.152). Cross validation of the results shows the largest over prediction at Kars rainfall station and largest under prediction at Burdur station. Upon for the examination of the cross-validation and spatial error clustering results, the Ordinary Kriging method was concluded to be the best algorithm in the interpolation process. Copyright Springer Science+Business Media B.V. 2012

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  • Hüseyin Yavuz & Saffet Erdoğan, 2012. "Spatial Analysis of Monthly and Annual Precipitation Trends in Turkey," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(3), pages 609-621, February.
    • Handle: RePEc:spr:waterr:v:26:y:2012:i:3:p:609-621
    DOI: 10.1007/s11269-011-9935-6
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    References listed on IDEAS

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    1. M. Mardikis & D. Kalivas & V. Kollias, 2005. "Comparison of Interpolation Methods for the Prediction of Reference Evapotranspiration—An Application in Greece," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 19(3), pages 251-278, June.
    2. Nazzareno Diodato & Gianni Tartari & Gianni Bellocchi, 2010. "Geospatial Rainfall Modelling at Eastern Nepalese Highland from Ground Environmental Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(11), pages 2703-2720, September.
    3. Sheng Yue & ChunYuan Wang, 2004. "The Mann-Kendall Test Modified by Effective Sample Size to Detect Trend in Serially Correlated Hydrological Series," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 18(3), pages 201-218, June.
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    Cited by:

    1. Annisa Nur Falah & Budi Nurani Ruchjana & Atje Setiawan Abdullah & Juli Rejito, 2023. "The Hybrid Modeling of Spatial Autoregressive Exogenous Using Casetti’s Model Approach for the Prediction of Rainfall," Mathematics, MDPI, vol. 11(17), pages 1-21, September.
    2. Jin Huang & Shanlei Sun & Yan Xue & Jinjian Li & Jinchi Zhang, 2014. "Spatial and Temporal Variability of Precipitation and Dryness/Wetness During 1961–2008 in Sichuan Province, West China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(6), pages 1655-1670, April.
    3. J. Vicente-Guillén & E. Ayuga-Telléz & D. Otero & J. Chávez & F. Ayuga & A. García, 2012. "Performance of a Monthly Streamflow Prediction Model for Ungauged Watersheds in Spain," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(13), pages 3767-3784, October.
    4. İsmail Dabanlı & Zekai Şen & Mehmet Öner Yeleğen & Eyüp Şişman & Bülent Selek & Yavuz Selim Güçlü, 2016. "Trend Assessment by the Innovative-Şen Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5193-5203, November.
    5. Carlos E. Melo & Oscar O. Melo & Jorge Mateu, 2018. "A distance-based model for spatial prediction using radial basis functions," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(2), pages 263-288, April.

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