Journals / Dumlupınar Üniversitesi Sosyal Bilimler Dergisi / 2018 / Cilt: 0 - Sayı: 56

EVALUATION OF KRIGING WITH EXTERNAL DRIFT METHOD IN SPATIAL MODELLING OF PRECIPITATION: A CASE OF AEGEAN REGION, TURKEY

YAĞIŞIN MEKÂNSAL OLARAK MODELLENMESİNDE KRIGING WITH EXTERNAL DRIFT YÖNTEMİNİN DEĞERLENDİRİLMESİ: EGE BÖLGESİ

Pages
1–22
Publication Date
2022-10-11
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results show that Kriging with External Drift and incorporation of elevation as a secondary variable could be used to supplement sparse observations in the mapping of precipitation

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The structures and geographical formations observed in the Aegean region of Turkey differ from the other coastal regions of the country.
📊
Key Findings & Data:Annual mean total precipitation data obtained from 36 stations (1976–2010) were used.
💡
Conclusion & Impact:The results show that Kriging with External Drift and incorporation of elevation as a secondary variable could be used to supplement sparse observations in the mapping of precipitation
🔬Design:Modeling & Simulation
📍Scope:2010 Verileri
⚙️Variables:Domain Parameters

Abstract

The structures and geographical formations observed in the Aegean region of Turkey differ from the other coastal regions of the country. Especially, elevation and aspect have different characteristics in this region. Thus, the precipitation conditions are influenced and the annual precipitation amounts observed in the plains are not consistent. In this study, Kriging with External Drift was applied to obtain a prediction map of precipitation in the Aegean region. Annual mean total precipitation data obtained from 36 stations (1976–2010) were used. Elevation was used as a secondary variable in Kriging with External Drift calculations. The R2 of 0.35 shows that at least one quarter of the precipitation behaviour can be explained by the model. A distribution that complies with the orographic extension draws attention in the Kriging with External Drift precipitation estimation map. The results show that Kriging with External Drift and incorporation of elevation as a secondary variable could be used to supplement sparse observations in the mapping of precipitation

Özet

Ege Bölgesi’nde görülen coğrafi oluşumlar ve yapılar, Türkiye’nin diğer kıyı bölgerinden farklılık göstermektedir. Özellikle bu bölgedeki yükseklik ve bakı, farklı karekteristiklere sahiptir. Bu nedenle, yağış durumu etkilenmektedir ve düzlük alanlarda görülen yıllık yağış miktarlarında bir istikrar gözlenmemektedir. Bu çalışmada, Ege Bölgesi’nde yağış haritası tahmini için Kriging with External Drift yöntemi kullanılmıştır. Çalışmada 36 istasyonda 1976–2010 yıllarında ölçülmüş aylık ortalama yağış değerlerinden elde edilen yıllık toplam yağış verisi kullanılmıştır. Yağış tahmininde yardımcı değişken olarak yükseklik verisinden yararlanılmıştır. Kriging with External Drift yağış tahmin haritasında orografik uzanımlar ile uyumlu bir dağılım dikkat çekmektedir. Sonuçlar, yüksekliğin yardımcı değişken olarak kullanıldığı Kriging with External Drift analizinin seyrek gözlemlerin olduğu yerlerin yağış haritalarının oluşturulmasına yardımcı bir yöntem olduğunu göstermiştir

🔖

Cite This Article

AYDIN, O. (2022). EVALUATION OF KRIGING WITH EXTERNAL DRIFT METHOD IN SPATIAL MODELLING OF PRECIPITATION: A CASE OF AEGEAN REGION, TURKEY. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, Cilt: 0 - Sayı: 56, 1–22. https://ajindex.com/articles/492867

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (13)

  1. Yin, Z.Y., Zhang, X., Liu, X., Colella, M., Chen, X. (2008). “An Assessment of the Biases of Satellite Rainfall Estimates Over the Tibetan Plateau and Correction Methods Based on Topographic Analysis”, Journal of Hydrometeorology, Vol. 9, Pp. 301–417
  2. Wotling, G., Bouvier, Ch., Danloux, J., Fritsch, M.J. (2000). “Regionalization of Extreme Precipitation Distribution Using the Principal Components of the Topographical Environment”, Journal of Hydrology, Vol. 233, No. 1–4, Pp. 86–101.
  3. Wilmott, C.J. (1982). “Some Comments on the Evaluation of Model Performance”, Bulletion of the American Meteorological Society, Vol. 63, Pp. 1309–1313.
  4. Tobin, C., Nicotina, L., Parlange, M.B., Berne, A., Rinaldo, A. (2011). “Improved Interpolation of Meteorological Forcings for Hydrologic Applications in a Swiss Alpine Region”, Journal of Hydrology, Vol. 401, Pp. 77–89.
  5. Silva, W.M., Simões, S.J. (2014). Spatial Intra-annual Variability of Precipitation Based on Geostatistics: A Case Study for the Paraiba Do Sul Basin, Southeastern Brazil. International Journal of Geosciences, Vol. 5, Pp. 408–417.
  6. Qing, Y., Zhu-Guo, M., Liang, C. (2011). “A Preliminary Analysis of the Relationship Between Precipitation Variation Trends and Altitude in China”, Atmospheric and Oceanic Science Letters, Vol. 4, No. 1, Pp. 41–46
  7. Phillips, D.L., Dolph, J., Marks, D. (1992). “A Comparison of Geostatistical Procedures for Spatial Analysis of Precipitation in Mountainous Terrain”, Agricultural and Forest Meteorology, Vol. 58, No. 1–2, 119–141.
  8. Pebesma, E.J. (2004). “Multivariable Geostatistics in S: The Gstat Package”, Computer&Geosciences, Vol. 30, Pp. 683–691.
  9. Pebesma, E.J., Wesseling, C.G. (1998).
  10. Gstat, A Program for Geostatistical Modelling, Prediction and Simulation. Computers & Geosciences, Vol. 24, No. 1, Pp. 17–31. Pardo-Igúzquiza, E. (1998). “Comparison of Geostatistical Methods for Estimating the Areal Average Climatological Rainfall Mean Using Data of Precipitation and Topography”, International Journal of Climatology, Vol. 18, Pp. 1031–1047.
  11. Moral, F.J. (2010). “Comparison of Different Geostatistical Approaches to Map Climate Variables: Application to Precipitation”, International Journal of Climatology, Vol. 30, Pp. 620–631.
  12. Mair, A., Fares, A. (2011). “Comparison of Rainfall Interpolation Methods in a Mountainous Region”, Journal of Hydrologic Engineering, Pp. 371–383.
  13. Lloyd, C.D. (2010). “Nonstationary Models for Exploring and Mapping Monthly Precipitation in the United Kingdom”, Internati