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Yağışın mekânsal dağılışında deterministik ve stokastik yöntemler: Mauritius örneği, Doğu Afrika

Yıl 2016, Cilt: 14 Sayı: 1, 1 - 14, 01.04.2016
https://doi.org/10.1501/Cogbil_0000000170

Öz

Yağış, mekânsal ve zamansal ölçekte büyük değişkenlik gösteren en önemli iklim parametrelerinden biridir. Yağışın doğru bir biçimde modellenmesi, hidrolojik çalışmalar, kuraklık ve sel gibi olayların tahmin edilmesi, yerüstü ve yeraltı su kaynakları miktarının tahmini, su kaynaklarının kirlenmesi ile ilişkili pek çok araştırmanın en önemli bölümünü oluşturur. Bu sebeple, yağışın modellenmesinde çok sayıda enterpolasyon yöntemleri uygulanmakta ve birbirleriyle karşılaştırılarak doğru modeller oluşturulmaktadır. Bu çalışmada, 1981–2010 dönemine ait 53 meteoroloji istasyonunun verileri kullanılarak Doğu Afrika’nın Mauritius ada ülkesinin yıllık ortalama toplam yağış dağılış modeli deterministik yöntemlerden, Thiessen Polygon (TP) ve Inverse Distance Method (IDW) ile stokastik yöntemlerden Ordinary Kriging (OK) kullanılarak gerçekleştirilmiştir. Yağış modellerinin doğruluğu Çapraz Geçerlilik (Cross-Validation) yöntemiyle test edilmiş ve modellerin karşılaştırılmasında Ortalama Hata (Mean Error, ME), Ortalama Mutlak Hata (Mean Absolute Error, MAE), Kök Ortalama Kare Hata (Root Mean Square Error, RMSE), Belirleyicilik Katsayısı (Detemination Coefficient, R2)’ndan yararlanılmıştır. Stokastik bir yöntem olan Ordinary Kriging (OK) -17,66 ME, 527,21 MAE, 329,53 mm RMSE ve 0.88 R2değerleri ile en yüksek performans sonucunu vermiştir. Buna karşın deterministik yöntemlerinden biri olan Thiessen Polygon (TP) -78,83 ME, 453,92 MAE, 621,58 mm RMSE ve 0,60 R2değerleriyle en düşük performans değerini göstermiştir. Buna göre, stokastik yöntem sonucu oluşturulan yağış modelinin, deterministik yöntemler kullanılarak oluşturulan yağış modellerine kıyasla doğru bir yağış modeli oluşturduğu sonucuna ulaşılmıştır

Kaynakça

  • Aydın, O. Çiçek, İ. (2013) “Ege Bölgesi’nde yağışın mekânsal dağılımı”, Coğrafi Bilimler Dergisi, 11(2), 101–120.
  • Aydin, O.; Çiçek, İ. (2015) Geostatistical Interpolation of Precipitation in Turkey, Lambert Academic Publishing, Saarbrucken, Germany.
  • Aydin, O.; Türkoğlu, N.; Çiçek, İ. (2015) "The importance of geostatistics in physical geography", International Journal of Human Science, 12(2), 1397–1415.
  • Barnsley, M.J. (2007) Environmental Modeling, CRC Press, USA.
  • Basistha, A.; Arya, D.S.; Goel, N.K. (2008) “Spatial distribution of rainfall in Indian Himalayas: a case study of Uttarakhand Region, Water Resources Management, 22, 1325–1346.
  • Bivand, R.S.; Pebesma, E.; Gómez-Rubio, V. (2008) Applied Spatial Data Analysis with R (use R ), 1. Edition, Springer, London.
  • Boer, E.P.J.; Beurs, K.M.; Hartkamp, A.D. (2001) “Kriging and thin plate splines for mapping climate variables”, International Journal of Applied Earth Observation and Geoinformation, 3(2), 146–154.
  • Buytaert, W.; Celleri, R.; Willems, P.; Bie`vre, D.B.; Wyseure, G. (2006) “Spatial and temporal rainfall variability in mountainous areas: a case study from the south Ecuadorian Andes, Journal of Hydrology, 329, 413–421.
  • Burrough, P.A.; McDonnell, R.A. (1998) Creating continuous surfaces from point data. In: Burrough, P.A., Goodchild, M.F., McDonnell, R.A., Switzer, P., Worboys, M. (Eds.), Principles of Geographic Information Systems. Oxford University Press, Oxford, UK.
  • Caruso, C.; Quarta, F. (1998) “Interpolation methods comparison”, Computers and Mathematics with Applications, 35(12), 109–126.
  • Diodato, N. (2005) “The influence of topographic co-variables on the spatial variability of precipitation over small regions of complex terrain”, International Journal of Climatology, 25(3), 351–363.
  • Dirks, K.N.; Hay, J.E.; Stow, C.D.; Harris, D. (1998) “High-resolution studies of rainfall on Norfolk Island. Part 2: interpolation of rainfall data, Journal of Hydrology, 208(3–4), 187–193.
  • Fowdur, S.C.; Rughooputh, S.D.D.V.; Cheeneebash, J.; Boojhawon, R.; Gopaul, A. (2014) “Rainfall analysis over Mauritius using principal componant analysis”, Environmental Management and Sustainable Development, 3(2), 94–108.
  • Franke, R.; Nielson, G. (1980) “Smooth interpolation of large sets of scattered data”, International Journal for Numerical Methods in Engineering, 15, 1691–1704.
  • Goovaerts, P. (2000) “Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall”, Journal of Hydrology, 228, 113–129.
  • Haig, H. (1895) “The physical features and geology of Mauritius”, The Quarterly Journal of the Geological Society, 51, 463– 471.
  • Hengl, T. (2009) A Practical Guide to Geostatisticstical Mapping, Office for Official Publications of the European Communities, Luxembourg.
  • Hession, S.L.; Moore, N. (2011) “A spatial regression analysis of the influence of topography on monthly rainfall in East Africa”, International Journal of Climatology, 31, 1440–1456.
  • Hofierka, j.; Parajka, J.; Mitasova, H.; Mitasi L. (2002) “Multivariate interpolation of precipitation using regularized spline with tension”, Transactions in GIS, 6(2), 135–150.
  • Hutchinson, M.F. (1998) “Interpolation of rainfall data with thin plate smoothing splines-part II: analysis of topographic dependence”, Journal of Geographic Information and Decision Analysis, 2(2), 152–167.
  • Isaaks, E.; Srivastava, R. (1989) An Introduction to Applied Geostatistics, Oxford University Press, New York.
  • Isaaks, E.H.; Srivastava, R.M. (1990) An Introduction to Applied Geostatistics, Oxford University Press, New York, USA.
  • Jagannathan, P.; Arlery, R.; Ten, K.H.; Zavarina, M. (1967) “A note on climatological normals”, World Meteorological Organization, Technical Note 84, WMO, Geneva.
  • Jury, M.R. (1993) “A preliminary study of climatological associations and characteristics of tropical cyclones in the SW Indian Ocean”, Meteorology and Atmospheric Physics, 51, 101–115.
  • Kalkhan, M.A. (2011) Spatial Statistics Geospatial Information Modelling and Thematic Mapping, CRC Press, USA.
  • Kieffer Weisse, A.; Bois, P.H. (2002) “A comparison of methods for mapping statistical characteristics of heavy rainfall in the French Alps: the use of dairly information”, Hydrological Sciences, 47(5), 739–752.
  • Kyriakidis, P.C.; Kim, J.; Miller, N.L. (2001) “Geostatistical mapping of precipitation from rain gauge data using atmospheric and terrain characteristics”, Journal of Applied Meteorology, 40, 855–1877.
  • Lichtenstern, A. (2013) Kriging Methods in Spatial Statistics, Bachelor’s Thesis, Technische Universität München, Department of Mathematics, Germany.
  • Lloyd, C.D. (2005) “Assessing the effect of integrating elevation data into the estimation of monthly precipitation in Great Britain”, Journal of Hydrology, 308, 128–150.
  • Lloyd, C.D. (2010) “Nonstationary models for exploring and mapping monthly precipitation in the United Kingdom”, International Journal of Climatology, 30, 390–405.
  • Ly, S.; Charles, C.; Degré, A. (2013) “Different methods for spatial interpolation of rainfall data for operational hydrology and hydrological modeling at watershed scale. A review”, Biotechnologie, Agronomie, Société et Environnement, 17(2), 392–406.
  • Nalder, I.A.; Wein, R.W. (1998) “Spatial interpolation of climatic Nor- mals: test of a new method in the Canadian boreal forest”, Agricultural and Forest Meteorology, 92, 211–225.
  • Nel, W.; Mongwa, T.; Sumner, P.D.; Anderson, R.L.; Dhurmea, K.R.; Boodhoo, Y.; Boojhawon, R.; Rughooputh, S.D.D.V. (2012) “The natura of erosive rainfall on a trapical volcanic island with an elevated interior”, Physical Geography, 33(3), 269–284.
  • Oliver, M.A.; Webster, R. (2014) “A tutorial guide to geostatistics: computing and modeling variograms and kriging”, Catena, 113, 56–69.
  • Padya, B.M. (1989) Weather and Climate of Mauritius, The Mahatma Ghandi Institute Press, Mauritius.
  • Pebesma, E.J.; Wesseling, C.G. (1998) “Gstat, a program for geostatistical modelling, prediction and simulation”, Computers & Geosciences, 24(1), 17–31.
  • Pebesma, E.J. (2004) “Multivariable geostatistics in S: the gstat package”, Computer&Geosciences, 30, 683–691.
  • 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, 58(1–2), 119–141.
  • Teltik, İ. (2008) Van Gölü Su Seviyesinin Stokastik Modellenmesi, İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, İstanbul.
  • 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, 401, 77–89.
  • Willmott, C.J. (1982) “Some comments on the evaluation of model performance”, Bulletion of the American Meteorological Society, 63, 1309–1313.
  • 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, 233(1–4), 86–101.
  • WRU (Water Resources Unit) (2007) Hydrology Data Book for Period 2000–2005, Water Resources Unit, Rose-Hill, Mauritius.
  • Vicente-Serrano, S.M.; Saz-Sánchez, M.A.; Cuadrat, J.M. (2003) “Comparative analysis of interpolation methods, in the middle Ebro Valley (Spain): application to annual precipitation and temperature”, Climate Research, 24, 161–180.
  • 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, 9, 301– 417.

Deterministic and stochastic methods to analyse the spatial distribution of precipitation: The case of Mauritius, East Africa

Yıl 2016, Cilt: 14 Sayı: 1, 1 - 14, 01.04.2016
https://doi.org/10.1501/Cogbil_0000000170

Öz

Precipitation is one of the most important climatic parameters displaying significant changes across space and time. The accurate modeling of precipitation has become an important part of climate research for hydrological studies, the forecast of events such as droughts and floods and the estimation of ground and surface water resources. For this reason, several interpolation methods have been applied and compared for the accurate generation of models. In this study, the spatial distribution of annual mean total precipitation of Mauritius, located east of Africa, was investigated by applying deterministic methods, namely Thiessen Polygon (TP) and Inverse Distance Method (IDW), and stochastic methods, namely Ordinary Kriging (OK), using precipitation data from 53 meteorological stations for the period 1981–2010. The accuracy of the models was tested using the Cross Validation method and the models were compared using the Mean Error (ME), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and the Coefficient of Determination (R2). The stochastic method, OK, provided the highest performance results, generating ME, MAE, RMSE and R2 values of -17,66, 527,21, 329,53 mm and 0,88 respectively. In contrast, the deterministic method, Thiessen Polygon (TP), generated the lowest performance results, generating ME, MAE, RMSE, R2 values of -78,83, 453,92, 621,58 mm and 0,60 respectively. Therefore, according to the results obtained, it can be concluded that stochastic methods provide more accurate models as compared to deterministic methods

Kaynakça

  • Aydın, O. Çiçek, İ. (2013) “Ege Bölgesi’nde yağışın mekânsal dağılımı”, Coğrafi Bilimler Dergisi, 11(2), 101–120.
  • Aydin, O.; Çiçek, İ. (2015) Geostatistical Interpolation of Precipitation in Turkey, Lambert Academic Publishing, Saarbrucken, Germany.
  • Aydin, O.; Türkoğlu, N.; Çiçek, İ. (2015) "The importance of geostatistics in physical geography", International Journal of Human Science, 12(2), 1397–1415.
  • Barnsley, M.J. (2007) Environmental Modeling, CRC Press, USA.
  • Basistha, A.; Arya, D.S.; Goel, N.K. (2008) “Spatial distribution of rainfall in Indian Himalayas: a case study of Uttarakhand Region, Water Resources Management, 22, 1325–1346.
  • Bivand, R.S.; Pebesma, E.; Gómez-Rubio, V. (2008) Applied Spatial Data Analysis with R (use R ), 1. Edition, Springer, London.
  • Boer, E.P.J.; Beurs, K.M.; Hartkamp, A.D. (2001) “Kriging and thin plate splines for mapping climate variables”, International Journal of Applied Earth Observation and Geoinformation, 3(2), 146–154.
  • Buytaert, W.; Celleri, R.; Willems, P.; Bie`vre, D.B.; Wyseure, G. (2006) “Spatial and temporal rainfall variability in mountainous areas: a case study from the south Ecuadorian Andes, Journal of Hydrology, 329, 413–421.
  • Burrough, P.A.; McDonnell, R.A. (1998) Creating continuous surfaces from point data. In: Burrough, P.A., Goodchild, M.F., McDonnell, R.A., Switzer, P., Worboys, M. (Eds.), Principles of Geographic Information Systems. Oxford University Press, Oxford, UK.
  • Caruso, C.; Quarta, F. (1998) “Interpolation methods comparison”, Computers and Mathematics with Applications, 35(12), 109–126.
  • Diodato, N. (2005) “The influence of topographic co-variables on the spatial variability of precipitation over small regions of complex terrain”, International Journal of Climatology, 25(3), 351–363.
  • Dirks, K.N.; Hay, J.E.; Stow, C.D.; Harris, D. (1998) “High-resolution studies of rainfall on Norfolk Island. Part 2: interpolation of rainfall data, Journal of Hydrology, 208(3–4), 187–193.
  • Fowdur, S.C.; Rughooputh, S.D.D.V.; Cheeneebash, J.; Boojhawon, R.; Gopaul, A. (2014) “Rainfall analysis over Mauritius using principal componant analysis”, Environmental Management and Sustainable Development, 3(2), 94–108.
  • Franke, R.; Nielson, G. (1980) “Smooth interpolation of large sets of scattered data”, International Journal for Numerical Methods in Engineering, 15, 1691–1704.
  • Goovaerts, P. (2000) “Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall”, Journal of Hydrology, 228, 113–129.
  • Haig, H. (1895) “The physical features and geology of Mauritius”, The Quarterly Journal of the Geological Society, 51, 463– 471.
  • Hengl, T. (2009) A Practical Guide to Geostatisticstical Mapping, Office for Official Publications of the European Communities, Luxembourg.
  • Hession, S.L.; Moore, N. (2011) “A spatial regression analysis of the influence of topography on monthly rainfall in East Africa”, International Journal of Climatology, 31, 1440–1456.
  • Hofierka, j.; Parajka, J.; Mitasova, H.; Mitasi L. (2002) “Multivariate interpolation of precipitation using regularized spline with tension”, Transactions in GIS, 6(2), 135–150.
  • Hutchinson, M.F. (1998) “Interpolation of rainfall data with thin plate smoothing splines-part II: analysis of topographic dependence”, Journal of Geographic Information and Decision Analysis, 2(2), 152–167.
  • Isaaks, E.; Srivastava, R. (1989) An Introduction to Applied Geostatistics, Oxford University Press, New York.
  • Isaaks, E.H.; Srivastava, R.M. (1990) An Introduction to Applied Geostatistics, Oxford University Press, New York, USA.
  • Jagannathan, P.; Arlery, R.; Ten, K.H.; Zavarina, M. (1967) “A note on climatological normals”, World Meteorological Organization, Technical Note 84, WMO, Geneva.
  • Jury, M.R. (1993) “A preliminary study of climatological associations and characteristics of tropical cyclones in the SW Indian Ocean”, Meteorology and Atmospheric Physics, 51, 101–115.
  • Kalkhan, M.A. (2011) Spatial Statistics Geospatial Information Modelling and Thematic Mapping, CRC Press, USA.
  • Kieffer Weisse, A.; Bois, P.H. (2002) “A comparison of methods for mapping statistical characteristics of heavy rainfall in the French Alps: the use of dairly information”, Hydrological Sciences, 47(5), 739–752.
  • Kyriakidis, P.C.; Kim, J.; Miller, N.L. (2001) “Geostatistical mapping of precipitation from rain gauge data using atmospheric and terrain characteristics”, Journal of Applied Meteorology, 40, 855–1877.
  • Lichtenstern, A. (2013) Kriging Methods in Spatial Statistics, Bachelor’s Thesis, Technische Universität München, Department of Mathematics, Germany.
  • Lloyd, C.D. (2005) “Assessing the effect of integrating elevation data into the estimation of monthly precipitation in Great Britain”, Journal of Hydrology, 308, 128–150.
  • Lloyd, C.D. (2010) “Nonstationary models for exploring and mapping monthly precipitation in the United Kingdom”, International Journal of Climatology, 30, 390–405.
  • Ly, S.; Charles, C.; Degré, A. (2013) “Different methods for spatial interpolation of rainfall data for operational hydrology and hydrological modeling at watershed scale. A review”, Biotechnologie, Agronomie, Société et Environnement, 17(2), 392–406.
  • Nalder, I.A.; Wein, R.W. (1998) “Spatial interpolation of climatic Nor- mals: test of a new method in the Canadian boreal forest”, Agricultural and Forest Meteorology, 92, 211–225.
  • Nel, W.; Mongwa, T.; Sumner, P.D.; Anderson, R.L.; Dhurmea, K.R.; Boodhoo, Y.; Boojhawon, R.; Rughooputh, S.D.D.V. (2012) “The natura of erosive rainfall on a trapical volcanic island with an elevated interior”, Physical Geography, 33(3), 269–284.
  • Oliver, M.A.; Webster, R. (2014) “A tutorial guide to geostatistics: computing and modeling variograms and kriging”, Catena, 113, 56–69.
  • Padya, B.M. (1989) Weather and Climate of Mauritius, The Mahatma Ghandi Institute Press, Mauritius.
  • Pebesma, E.J.; Wesseling, C.G. (1998) “Gstat, a program for geostatistical modelling, prediction and simulation”, Computers & Geosciences, 24(1), 17–31.
  • Pebesma, E.J. (2004) “Multivariable geostatistics in S: the gstat package”, Computer&Geosciences, 30, 683–691.
  • 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, 58(1–2), 119–141.
  • Teltik, İ. (2008) Van Gölü Su Seviyesinin Stokastik Modellenmesi, İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, İstanbul.
  • 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, 401, 77–89.
  • Willmott, C.J. (1982) “Some comments on the evaluation of model performance”, Bulletion of the American Meteorological Society, 63, 1309–1313.
  • 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, 233(1–4), 86–101.
  • WRU (Water Resources Unit) (2007) Hydrology Data Book for Period 2000–2005, Water Resources Unit, Rose-Hill, Mauritius.
  • Vicente-Serrano, S.M.; Saz-Sánchez, M.A.; Cuadrat, J.M. (2003) “Comparative analysis of interpolation methods, in the middle Ebro Valley (Spain): application to annual precipitation and temperature”, Climate Research, 24, 161–180.
  • 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, 9, 301– 417.
Toplam 45 adet kaynakça vardır.

Ayrıntılar

Diğer ID JA38GC32UP
Bölüm Araştırma Makalesi
Yazarlar

Olgu Aydın

Nussaibah Begum Raja Bu kişi benim

Yayımlanma Tarihi 1 Nisan 2016
Yayımlandığı Sayı Yıl 2016 Cilt: 14 Sayı: 1

Kaynak Göster

APA Aydın, O., & Raja, N. B. (2016). Yağışın mekânsal dağılışında deterministik ve stokastik yöntemler: Mauritius örneği, Doğu Afrika. Coğrafi Bilimler Dergisi, 14(1), 1-14. https://doi.org/10.1501/Cogbil_0000000170