Abstract
Hidro-meteorolojik verilerin miktarları, insan kaynaklı küresel iklim değişikliği nedeniyle zaman içinde değişmiştir. Özellikle tarımsal su yönetimi bağlamında hayati önem taşıyan bitki su tüketim parametresinin tahmininde kullanılacak verilerin durağan koşullarda elde edilmesi güvenilirlik açısından bir zorunluluktur. Verilerin zaman içinde farklılaşması, frekans dağılım davranışının da değiştiği anlamına gelir. Bu çalışmanın ana hedefi bahse konu bu değişim üzerine oldu. Bu amaçla Amasya ve Samsun istasyonlarının yıllık referans evapotranspirasyon (ETo) değerleri materyal olarak kullanılmıştır. ETo verilerindeki değişim ITA ve PITA yaklaşımları ile analiz edilmiştir. Amasya için ITA analizi, ETo verilerinde istatistiksel olarak artan bir değişim ortaya çıkarırken, Samsun istasyonu için istatistiksel olarak anlamlı bir değişiklik olmadı. Tam verilerin PITA tekniğine göre bölünmesiyle elde edilen birinci yarı (FH) ve ikinci yarının (SH) veri dizilerine en yakın olan olasılık dağılımları Amasya istasyonu için sırasıyla Gama ve Gumbel olmuştur. Samsun istasyonunun iki yarısı için normal dağılım bulunmuştur. Bu bulgu, Amasya istasyonuna ait verilerin zaman içinde istatistiksel olarak değiştiğini doğrulamıştır. Amasya istasyonu için özellikle daha yüksek risk düzeylerinde niceliklerde dikkate değer farklılıklar tespit edilmiştir.
Project Number
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References
- Allen RG, Pereira LS, Raes D and Smith M (1998). Crop Evapotranspiration (guidelines for computing crop water requirements). FAO Irrigation and Drainage Paper No. 56, Rome.
- Akgul ÇM and Dino I (2020). Climate change impact assessment in residential buildings utilizing RCP4.5 and RCP8.5 scenarios. Journal of the Faculty of Engineering and Architecture of Gazi University. 35: 1665-1683.
- Carvalho DF, Rocha HS, Bonomo R and Souza AP (2015). Estimating reference evapotranspiration with limited meteorological data. Pesquisa Agropecuária Brasileira. 50: 1-11. Pettitt AN (1979). A non-parametric approach to the change-point problem. Journal of the Royal Statistical Society. Series C (Applied Statistics). 28:126–135.
- Soubie R, Heinesch B, Granier A, Aubinet M and Vincke C (2016). Evapotranspiration assessment of a mixed temperate forest by four methods: Eddy covariance, soil water budget, analytical and model. Agricultural and Forest Meteorology. 228: 191–204.
- Schwarz G (1978) Estimating the dimension of a model. Annals of Statistics. 6: 461-464. http://dx.doi.org/10.1214/aos/1176344136
- Şen Z (2017). Innovative trend significance test and applications. Theoretical and Applied Climatology. 127: 939-947. DOI 10.1007/s00704-015-1681-x
- Şen Z (2020). Probabilistic innovative trend analysis. International Journal of Global Warming. 20: 93-105. https://dx.doi.org/10.1504/IJGW.2020.105387
- Yang X, Chen Y, Pacenka S, Gao W, Ma L, Wang G, Yan P, Sui P and Steenhuis T S (2015). Effect of diversified crop rotations on groundwater levels and crop water productivity in the North China Plain. Journal of Hydrology. 522: 428–438.
- Yee MS, Pauwels VRN, Daly E, Beringer J, Rüdiger C, McCabe MF and Walker JP (2015). A comparison of optical and microwave scintillometers with eddy covariance derived surface heat fluxes. Agricultural and Forest Meteorology. 213: 226–239.
Abstract
The amounts of hydro-meteorological data have varied over time due to human-induced global climate change. Obtaining the data to be used in the estimation of the crop water consumption parameter, which is of vital importance especially in the context of agricultural water management, under stationary conditions is a necessity in terms of reliability. The differentiation of data over time means that its frequency distribution behaviour also changes. The main goal of this study was on this change in question. For this purpose, annual reference evapotranspiration (ETo) values of Amasya and Samsun stations were used as material. The change in ETo data was analyzed with the ITA and PITA approaches. The ITA analysis regarding the Amasya station showed a statistically increasing change in the ETo data, whereas there was no statistically significant change for the Samsun station. Probability distributions fit most approximate to the data sequences of the first halve (FH) and second halve (SH) obtained by dividing the full data according to the PITA technique were Gama and Gumbel for the Amasya station, respectively. The normal distribution was found for two halves of the Samsun station. This finding confirmed that the data of the Amasya station has changed statistically over time. Remarkable differences were detected in the quantiles at especially higher risk levels for the Amasya station.
Supporting Institution
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Project Number
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Thanks
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References
- Allen RG, Pereira LS, Raes D and Smith M (1998). Crop Evapotranspiration (guidelines for computing crop water requirements). FAO Irrigation and Drainage Paper No. 56, Rome.
- Akgul ÇM and Dino I (2020). Climate change impact assessment in residential buildings utilizing RCP4.5 and RCP8.5 scenarios. Journal of the Faculty of Engineering and Architecture of Gazi University. 35: 1665-1683.
- Carvalho DF, Rocha HS, Bonomo R and Souza AP (2015). Estimating reference evapotranspiration with limited meteorological data. Pesquisa Agropecuária Brasileira. 50: 1-11. Pettitt AN (1979). A non-parametric approach to the change-point problem. Journal of the Royal Statistical Society. Series C (Applied Statistics). 28:126–135.
- Soubie R, Heinesch B, Granier A, Aubinet M and Vincke C (2016). Evapotranspiration assessment of a mixed temperate forest by four methods: Eddy covariance, soil water budget, analytical and model. Agricultural and Forest Meteorology. 228: 191–204.
- Schwarz G (1978) Estimating the dimension of a model. Annals of Statistics. 6: 461-464. http://dx.doi.org/10.1214/aos/1176344136
- Şen Z (2017). Innovative trend significance test and applications. Theoretical and Applied Climatology. 127: 939-947. DOI 10.1007/s00704-015-1681-x
- Şen Z (2020). Probabilistic innovative trend analysis. International Journal of Global Warming. 20: 93-105. https://dx.doi.org/10.1504/IJGW.2020.105387
- Yang X, Chen Y, Pacenka S, Gao W, Ma L, Wang G, Yan P, Sui P and Steenhuis T S (2015). Effect of diversified crop rotations on groundwater levels and crop water productivity in the North China Plain. Journal of Hydrology. 522: 428–438.
- Yee MS, Pauwels VRN, Daly E, Beringer J, Rüdiger C, McCabe MF and Walker JP (2015). A comparison of optical and microwave scintillometers with eddy covariance derived surface heat fluxes. Agricultural and Forest Meteorology. 213: 226–239.
Details
| Primary Language | English |
|---|---|
| Subjects | Agricultural Engineering |
| Journal Section | Research Articles |
| Authors | |
| Project Number | *** |
| Publication Date | August 31, 2022 |
| Published in Issue | Year 2022 |