Abstract
Middle East, like North Africa, is considered as arid to semi-arid region. Water shortages in this region, represents an extremely important factor in stability of the region and an integral element in its economic development and prosperity. Iraq was an exception due to presence of Tigris and Euphrates Rivers. After the 1970s the situation began to deteriorate due to continuous decrease in discharges of these rivers, are expected to dry by 2040 with the current climate change. In the present paper, long rainfall trends up to the year 2099 were studied in Sinjar area, northwest of Iraq, to give an idea about its future prospects. Two emission scenarios, used by the Intergovernmental Panel on Climate Change (A2 and B2), were employed to study the long term rainfall trends in northwestern Iraq. All seasons consistently project a drop in daily rainfall for all future periods with the summer season is expected to have more reduction compared to other seasons. Generally the average rainfall trend shows a continuous decrease. The overall average annual rainfall is slightly above 210 mm. In view of these results, prudent water management strategies have to be adopted to overcome or mitigate consequences of future severe water crisis.
[1] Al-Ansari N. A., Water resources in the Arab countries: Problems and possible solutions. UNESCOInternational conf. (Water: a looming crisis), Paris, 1998, 367–376 Search in Google Scholar
[2] Naff T., Conflict and water use in the Middle East, in Roger R. and Lydon P. (Ed.), Water in the Arab Word: Perspectives and Prognoses, Harvard University, 1993, 253–284 Search in Google Scholar
[3] AL-Ansari N. A., Applied surface Hydrology, Al al-Bayt University Publication, 2005 Search in Google Scholar
[4] Bazzaz F., Global climatic changes and its consequences for water availability in the ArabWorld, in Roger R. and Lydon P. (Ed.), Water in the Arab Word: Perspectives and Prognoses, Harvard University, 1993, 243–252 Search in Google Scholar
[5] Voss K., Famiglietti J., Lo M., de Linage C., Rodell M. and Swenson S., Groundwater depletion in the Middle East from GRACE with implications for transboundary water management in the Tigris-Euphrates-Western Iran region, Water Resources Researc 49, 2013, 904–914 http://dx.doi.org/10.1002/wrcr.2007810.1002/wrcr.20078Search in Google Scholar
[6] Al-Ansari N. A., Management of Water Resources in Iraq: Perspectives and Prognoses, J. Engineering 5, 2013, 667–684 10.4236/eng.2013.58080Search in Google Scholar
[7] Elasha B. O., Mapping of Climate Change Threats and Human Development Impacts in the Arab Region, United Nations Development programme, Arab Human Development Report (AHDR), Research Paper Series, http://www.arab-hdr.org/publications/other/ahdrps/paper02-en.pdf. Last accessed 22/12/2013 Search in Google Scholar
[8] IPCC (Intergovernmental Panel on Climate Change), “Climate Change, Climate Change Impacts, Adaptation and Vulnerability”, Cambridge University Press, 2007 10.1017/CBO9780511546013Search in Google Scholar
[9] Milly P. C. D., Dunne K. A and Vecchia A. V., Global Patterns of Trends in Streamflow and Water Availability in a Changing Climate. Nature, 2005, 438, 347–350 http://dx.doi.org/10.1038/nature0431210.1038/nature04312Search in Google Scholar
[10] Al-Ansari N. A., Knutsson S., Toward Prudent Management of Water Resources in Iraq. Journal of Advanced Science and Engineering Research, 2011, 1, 53–67 Search in Google Scholar
[11] UN, Water Resources Management White Paper, United Nations Assistance Mission for Iraq, United Nations Country Team in Iraq, 2010, 20 Search in Google Scholar
[12] Al-Ansari N. A., Salameh E. and Al-Omari I., Analysis of Rainfall in the Badia Region, Jordan, Al al-Bayt University Research paper No. 1, 1999, 66 Search in Google Scholar
[13] Al-Ansari N. A., Al-Shamali B. and Shatnawi A., Statistical analysis at three major meteorological stations in Jordan, Al Manara Journal for scientific studies and research 12, 2006, 93–120 Search in Google Scholar
[14] Al-Ansari N. A., Baban S., Rainfall Trends in the Badia Region of Jordan, Surveying and Land Information Science 65, 2005, 233–243 Search in Google Scholar
[15] Rasheed H., Mohammad E. and Awchi T., A field study on influence of initial moisture content on infiltration function. J. Al-Rafidain Engineering 2, 1994, 1–10 Search in Google Scholar
[16] Kalnay E., Kanamitsu M., Kistler R., Collins W., Deaven D., Gandin L., Iredell M., Saha S., White G., Woollen J., Zhu Y., Leetmaa A., Reynolds B., Chelliah M., Ebisuzaki W., Higgins W., Janowiak J., Mo K. C., Ropelewski C., Wang J., Jenne R. & Joseph D., The NCEP/NCAR 40-Year Reanalysis Project. Bulletin of the American Meteorological Society 77, 1996, 437–471 http://dx.doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;210.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2Search in Google Scholar
[17] Wheater H. S., Progress in and prospects for fluvial flood modelling. Philosophical Transactions: Mathematical Physical and Engineering Sciences 360, 2002, 1409–431 http://dx.doi.org/10.1098/rsta.2002.100710.1098/rsta.2002.1007Search in Google Scholar
[18] Nakicenovic N., Davidson O., Davis G., Grübler A., Kram T., Lebre La Rovere E., Metz B., Morita T., Pepper W., Pitcher H., Sankovski A., Shukl P., Swart R., Watson R., Dadi Z., Emissions Scenarios. A Special Report of the Intergovernmental Panel on Climate Change. Cambridge University Press; 2000, Cambridge, UK Search in Google Scholar
[19] Von V., Heckl A., Impact of Climate Change on the Water Availability in the Near East and the Upper Jordan River Catchment. Phd Thesis, 2000. University of Augsburg, Germany Search in Google Scholar
[20] Hewitson B. C., Crane R. G., Climate downscaling: techniques and application, Clim Res 7, 1996, 85–95 http://dx.doi.org/10.3354/cr00708510.3354/cr007085Search in Google Scholar
[21] Cavazos T. Hewitson B. C., Performance of NCEP variables in statistical downscaling of daily precipitation. Clim Res 28, 2005, 95–107 http://dx.doi.org/10.3354/cr02809510.3354/cr028095Search in Google Scholar
[22] Ojha, C.S.P., Goyal, M. K., Adeloye, A. J., Downscaling of Precipitation for Lake Catchment in Arid Region in India using Linea Multiple Regression and Neural Networks. The Open Hydrology Journal 4, 2010, 122–136 http://dx.doi.org/10.2174/187437810100401012210.2174/1874378101004010122Search in Google Scholar
[23] Hoai N. D., Udo K., Mano A., Downscaling Global Weather Forecast Outputs Using ANN for Flood Prediction. Journal of Applied Mathematics, 2011, Article ID246286, 14 pages doi:10.1155/2011/246286 10.1155/2011/246286Search in Google Scholar
[24] Fistikoglu O., Okkan U., Statistical Downscaling of Monthly Precipitation Using NCEP/NCAR Reanalysis Data for Tahtali River Basin in Turkey. J. Hydrol. Eng. 16, 2011, 157–164 doi 10.1061/(ASCE)HE.1943-5584.0000300 http://dx.doi.org/10.1061/(ASCE)HE.1943-5584.000030010.1061/(ASCE)HE.1943-5584.0000300Search in Google Scholar
[25] Coulibaly P., Dibike Y. B., Downscaling Precipitation and Temperature with Temporal Neural Networks. J. Hydrometrology, 2004, 483–496 10.1175/JHM409.1Search in Google Scholar
[26] Lisboa P. G. J., Neural Networks: current applications, Chapman & Hall, New York, 1992 Search in Google Scholar
[27] Trigo R. M., Improving Metrological Downscaling Methods with Artificial Neural Network Models. PhD thesis, 2000 University of East Anglia Search in Google Scholar
[28] Levenberg K., A method for the solution of certain problems in least squares, Quarterly of Applied Mathematics 5, 1944, 164–168 10.1090/qam/10666Search in Google Scholar
[29] Marquardt D., An algorithm for least-squares estimation of nonlinear parameters, SIAM Journal on Applied Mathematics 11, 1963, 431–441 http://dx.doi.org/10.1137/011103010.1137/0111030Search in Google Scholar
[30] Jeong D-I., Kim Y-O., Rainfall-runoff models using artificial neural networks for ensemble stream flow prediction. Hydrol. Process 19, 2005, 3819–3835 http://dx.doi.org/10.1002/hyp.598310.1002/hyp.5983Search in Google Scholar
[31] Yadav D., Naresh R., Sharma V., Stream flow forecasting using Levenberg-Marquardt algorithm approach. IJWREE 3, 2010, 30–40 Search in Google Scholar
[32] Legates D. R., McCabe G. J., Evaluating the use of goodness-of-fit measures in hydrologic and hydroclimatic model validation. Water Resources Research 35, 1999, 233–241 http://dx.doi.org/10.1029/1998WR90001810.1029/1998WR900018Search in Google Scholar
[33] Schaap M. G., Leij F. J., Database related accuracy and uncertainty of pedotransfer functions. Soil Science 16, 1998, 765–779 http://dx.doi.org/10.1097/00010694-199810000-0000110.1097/00010694-199810000-00001Search in Google Scholar
[34] Gupta H. V, Sorooshian S., Yapo P. O., Status of automatic calibration for hydrologic models: Comparison with multilevel expert calibration. J Hydrologic Eng. 4, 1999, 135–143 http://dx.doi.org/10.1061/(ASCE)1084-0699(1999)4:2(135)10.1061/(ASCE)1084-0699(1999)4:2(135)Search in Google Scholar
[35] Coles, S., An introduction to statistical modeling of extreme values, 2001, Springer, London http://dx.doi.org/10.1007/978-1-4471-3675-010.1007/978-1-4471-3675-0Search in Google Scholar
[36] Hannaford C. and Marsh T., An assessment of trends in UK runoff and low flows using a network of undisturbed basins, International Journal of Climatology 26, 2006, 1237–1253 http://dx.doi.org/10.1002/joc.130310.1002/joc.1303Search in Google Scholar
[37] FAO, Improving Productivity of Dry land Areas. Committee on Agriculture (Ninth session), 1987, FAO, Rome. http://www.fao.org/docrep/meeting/011/ag415e/ag415e04.htm#4.1. Last accessed 22/12/2013 Search in Google Scholar
[38] IPCC. Special Report on Emission Scenarios Summary for policy makers. IPCC, Working Group III. Cambridge University Press. 2001 Search in Google Scholar
[39] Shabani, Farzin, Lalit Kumar, and Subhashni Taylor, Climate Change Impacts on the Future Distribution of Date Palms: A Modeling Exercise Using CLIMEX, PLOSONE, 2012, DOI: 10.1371/journal.pone.0048021 10.1371/journal.pone.0048021Search in Google Scholar PubMed PubMed Central
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