Temporal and Spatial Analysis of Rainfall and Evapotranspiration in Erbil Plain and the Peripheral Areas | ||
| Kirkuk University Journal For Agricultural Sciences | ||
| Volume 14, Issue 3, September 2023, Pages 317-334 PDF (1.43 M) | ||
| Document Type: Research Paper | ||
| DOI: 10.58928/ku23.14333 | ||
| Authors | ||
| khalis J. Hamad rashid* 1; Tariq H. Karim* 2 | ||
| 1Department of Soil and Water, College of Agricultural Engineering Sciences, University of Salahaddin, Erbil, Iraq. | ||
| 2Department of Surveying and Geomatics Engineering, Faculty of Engineering, Tishk International University-Erbil, Iraq. | ||
| Abstract | ||
| Since analysis of spatial events is region specific and cannot be generalized, local studies are of vital importance to identify the most accurate interpolation methods. Furthermore, the trend analysis of climatic parameters at different time scales is helpful for making a better climate change adaptation and mitigation plan to overcome water scarcity. Accordingly, the current study was proposed to detect trends in rainfall and evapotranspiration at monthly and annual time scales over the Erbil plain and the surrounding area using parametric and non-parametric tests. Moreover, four deterministic and five geostatistical methods were evaluated for searching the best interpolation method to generate a continuous surface for the indicated climatic variables. The results revealed that the majority of data sets are categorized useful class and serially independent. Furthermore, it was found both rainfall and potential evapotranspiration have a mix of upward and downward trends and most of them are insignificant at 5% level of significance. Further, the interpolation analysis indicated that local polynomial interpolation (LPI) method was proven to be best interpolator for generating continuous surfaces for rainfall and ETo over the area under study followed by the empirical Bayesian Kriging method. | ||
| Keywords | ||
| Keywords: Climatic variables,,; ,،Trend analysis,,; ,،interpolation methods,,; ,،Erbil plain,,; ,،TOPSIS | ||
| References | ||
|
[1] Zhang H, Wang L. Analysis of the variation in potential evapotranspiration and surface wet conditions in the Hancang River Basin, China. Scientific Reports. 2021;11(1):8607.
[2] Onyutha C, Acayo G, Nyende J. Analyses of precipitation and evapotranspiration changes across the Lake Kyoga Basin in east Africa. Water. 2020;12(4):1134.
[3] Sonali P, Kumar DN. Review of trend detection methods and their application to detect temperature changes in India. Journal of Hydrology. 2013;476:212-27.
[4] Obada E, Alamou EA, Chabi A, Zandagba J, Afouda A. Trends and changes in recent and future Penman-Monteith potential evapotranspiration in Benin (West Africa). Hydrology. 2017;4(3):38.
[5] Chaouche K, Neppel L, Dieulin C, Pujol N, Ladouche B, Martin E, et al. Analyses of precipitation, temperature and evapotranspiration in a French Mediterranean region in the context of climate change. Comptes Rendus Geoscience. 2010;342(3):234-43.
[6] Rahman MM, Imam MH, Roy S, Hoque F, Ahsan U. Analysis of long-term rainfall trends in Bangladesh. 2021.
[7] Shadmani M, Marofi S, Roknian M. Trend analysis in reference evapotranspiration using Mann-Kendall and Spearman’s Rho tests in arid regions of Iran. Water resources management. 2012;26:211-24.
[8] Khanmohammadi N, Rezaie H, Montaseri M, Behmanesh J. The effect of different meteorological parameters on the temporal variations of reference evapotranspiration. Environmental Earth Sciences. 2017;76:1-13.
[9] Zhang Q, Liu C, Xu C-y, Xu Y, Jiang T. Observed trends of annual maximum water level and streamflow during past 130 years in the Yangtze River basin, China. Journal of hydrology. 2006;324(1-4):255-65.
[10] Chen H, Guo S, Xu C-y, Singh VP. Historical temporal trends of hydro-climatic variables and runoff response to climate variability and their relevance in water resource management in the Hanjiang basin. Journal of hydrology. 2007;344(3-4):171-84.
[11] Sluiter R. Interpolation methods for climate data: literature review. KNMI intern rapport, Royal Netherlands Meteorological Institute, De Bilt. 2009.
[12] Antal A, Guerreiro PM, Cheval S. Comparison of spatial interpolation methods for estimating the precipitation distribution in Portugal. Theoretical and Applied Climatology. 2021;145(3-4):1193-206.
[13] Ly S, Charles C, Degre A. Geostatistical interpolation of daily rainfall at catchment scale: the use of several variogram models in the Ourthe and Ambleve catchments, Belgium. Hydrology and Earth System Sciences. 2011;15(7):2259-74.
[14] Ahmad I, Tang D, Wang T, Wang M, Wagan B. Precipitation trends over time using Mann-Kendall and spearman’s rho tests in swat river basin, Pakistan. Advances in Meteorology. 2015;2015.
[15] Mohammed K, Karim T. MODELS TO PREDICT SLOPE LENGTH FROM OTHER WATERSHED ATTRIBUTES. Iraqi Journal of Agricultural Sciences. 2020;51(4).
[16] Keya DR, Karim TH. MULTIVARIATE MODELS FOR PREDICTING RAINFALL EROSIVITY FROM ANNUAL RAINFALL AND GEOGRAPHICAL COORDINATES IN A REGION WITH A NON-UNIFORM PLUVIAL REGIME. Iraqi Journal of Agricultural Sciences. 2020;51(5).
[17] Mahmood R, Jia S, Zhu W. Analysis of climate variability, trends, and prediction in the most active parts of the Lake Chad basin, Africa. Scientific Reports. 2019;9(1):6317.
[18] UNESCO. Aridity definition (UN documents). United Nation Educational Scientific and Cultural Organization, New York. 1979.
[19] Rao AR, Hamed KH, Chen H-L. Nonstationarities in hydrologic and environmental time series: Springer Science & Business Media; 2003.
[20] Allen RG, Pereira LS, Raes D, Smith M. Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. Fao, Rome. 1998;300(9):D05109.
[21] Chen Y, Li J, Chen A. Does high risk mean high loss: Evidence from flood disaster in southern China. Science of the total environment. 2021;785:147127.
[22] Wilding L, editor Spatial variability: its documentation, accomodation and implication to soil surveys. Soil spatial variability, Las Vegas NV, 30 November-1 December 1984; 1985.
[23] Zakaria S, Al-Ansari N, Knutsson S, Al-Badrany T. ARIMA Models for weekly rainfall in the semi-arid Sinjar District at Iraq. Journal of Earth Sciences and Geotechnical Engineering. 2012;2(3).
[24] Elzeiny R, Khadr M, Zahran S, Rashwan E. Homogeneity analysis of rainfall series in the upper blue nile river basin, Ethiopia. Journal of Engineering Research. 2019;3(September):46-53.
[25] AL-Lami AM, AL-Timimi YK, AL-Salihi AM. The homogeneity analysis of rainfall time series for selected meteorological stations in Iraq. Diyala Journal for Pure Science. 2014;10(2):60-77.
[26] Govay MB, Karim TH. Rainfall time series in a semiarid region of Duhok Governorate, Iraqi Kurdistan Region. Iraqi Journal of Agricultural Sciences. 2022;IJASVol.56,( (1), 2025).
[27] Luo W, Taylor M, Parker S. A comparison of spatial interpolation methods to estimate continuous wind speed surfaces using irregularly distributed data from England and Wales. International Journal of Climatology: A Journal of the Royal Meteorological Society. 2008;28(7):947-59.
[28] Gong L, Xu C-y, Chen D. Spatial interpolation and analyses of reference evapotranspiration and its temporal trends in Changjiang (Yangtze River) Catchment, China. 2005. | ||
|
Statistics Article View: 883 PDF Download: 84 |
||