Predicted the Cumulative Annual Rainfall in Iraq Using SDSM Modal
DOI:
https://doi.org/10.23851/mjs.v32i2.977Keywords:
SDSM, Rainfall, IMOS, ARIMAAbstract
Rain is deemed one of the most important climate elements. It must be given special attention for being the basis without which no kind of life in the world can be there. the aim of the study is to use Statistical models Downscaling (SDSM) where it is a universal model used to converting large scale output into a small scale that can be used to study impact at the local scale (Iraq)' to Forecasting cumulative annual rainfall for the next years where there are a few studies used this model in Iraq. Daily rainfall data from the Iraqi Meteorological Organization and Seismology (IMOS) (2007-2016) for the study areas (Baghdad, Karbala, Al-Hay, Mosul, Kirkuk, Khanaqin, Basra, Nasiriya, Diwaniya, and Rutba) is used to estimate the amount of rainfall by using SDSM. The model was used to estimate the rain values and then the results were compared with the actual values, the results were very close to each other. Also, the model used to predict the cumulative annual rainfall from (2017-2021), The result shows that the bigger amount of rainfall in the north region with (3821) mm and the lowest amount in the west region (665) mm, while middle region (1848) mm and south region (1828) mm.Downloads
References
J. A. Martins, V. S. Brand, M. N. Capucim, C. B. Machado, D. G. A. Piccilli, and L. D. Martins, "The impact of rainfall and land cover changes on the flow of a medium-sized river in the South of Brazil," Energy Procedia, vol. 95, pp. 272-278, 2016.
H. L. Berry, K. Bowen, and T. Kjellstrom, "Climate change and mental health: a causal pathways framework," International journal of public health, vol. 55, no. 2, pp. 123-132, 2010.
J. Acker, R. Soebiyanto, R. Kiang, and S. Kempler, "Use of the NASA Giovanni data system for geospatial public health research: example of weather-influenza connection," ISPRS International Journal of Geo-Information, vol. 3, no. 4, pp. 1372-1386, 2014.
M. Kleidorfer, C. Mikovits, A. Jasper-Tönnies, M. Huttenlau, T. Einfalt, and W. Rauch, "Impact of a changing environment on drainage system performance," Procedia Engineering, vol. 70, pp. 943-950, 2014.
Y. Cao, Z. Wu, and Z. Xu, "Effects of rainfall on aircraft aerodynamics," Progress in Aerospace Sciences, vol. 71, pp. 85-127, 2014.
F. Olaiya and A. B. Adeyemo, "Application of data mining techniques in weather prediction and climate change studies," International Journal of Information Engineering and Electronic Business, vol. 4, no. 1, p. 51, 2012.
h. a. Asraa Khtan Abdulkareem, taha hantush "Models for Estimating Probable Maximum Precipitation For Selected Stations in Iraq," phd, atmospheric sciense Mustansiriya University, Iraq, 2008.
H. K. AL-Shmirty, huasn alsharaa "Precipitation data Analysis of Iraq using Markov Chains," msc, atmospheric science Mustansiriyah University, Iraq, 2008.
A. H. El-Shafie, A. El-Shafie, H. G. El Mazoghi, A. Shehata, and M. R. Taha, "Artificial neural network technique for rainfall forecasting applied to Alexandria, Egypt," International Journal of Physical Sciences, vol. 6, no. 6, pp. 1306-1316, 2011.
Z. Hassan and S. Harun, "Application of statistical downscaling model for long lead rainfall prediction in Kurau River catchment of Malaysia," Malaysian Journal of Civil Engineering, vol. 24, no. 1, pp. 1-12, 2012.
S. Chandniha and M. Kansal, "Rainfall estimation using multiple linear regression based statistical downscaling for Piperiya watershed in Chhattisgarh," Journal of Agrometeorology, vol. 18, no. 1, p. 106, 2016.
M. Al-Mukhtar and M. Qasim, "Future predictions of precipitation and temperature in Iraq using the statistical downscaling model," Arabian Journal of Geosciences, vol. 12, no. 2, p. 25, 2019.
A. Abbas and T. Abdulateef, "Generation of rainfall for Mosul city using statistical downscaling method (SDSM)," MS&E, vol. 737, no. 1, p. 012165, 2020.
A.-J. Ali Mokhles and A. Asraa Khtan, "Conversion of rain data from surface stations to forecast models data," Mesopotamia Environmental Journal , vol. 5, no. 3, pp. 40-48, 2020.
M. Bermúdez, L. Cea, E. Van Uytven, P. Willems, J. Farfán, and J. Puertas, "A robust method to update local river inundation maps using global climate model output and weather typing based statistical downscaling," Water Resources Management, vol. 34, no. 14, pp. 4345-4362, 2020.
P. Mujumdar and D. N. Kumar, Floods in a changing climate: hydrologic modeling. Cambridge University Press, 2012.
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