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dc.contributor.authorTadlaoui, Sarra
dc.date.accessioned2019-03-04T11:41:40Z
dc.date.available2019-03-04T11:41:40Z
dc.date.issued2018
dc.identifier.urihttp://repository.pauwes-cop.net/handle/1/207
dc.description.abstractWater resources could become scarcer in future decades worldwide. This will significantly affect semi-arid to arid climatic regions. The rapid evolution population, industrial development, and the expansion of agriculture coupled with reduced resources related to the increased frequency of extreme weather events: droughts, and transitional floods and / or linked to climate change are the main factors responsible for increasing scarcity of water resources. Algeria and in particular the western part has experienced several periods of drought during this century (decrease in rainfall as well as significant increase in temperature). The last major drought from early 1980s to the present day was characterized by its intensity and its significant impact on water resources and crop yields. Understanding changes in key statistics of weather parameters is very important. The main contribution of this work is twofold: First, articulating climate change through an assessment of climate data for Tafna basin, based on two parameters (precipitation and temperature)during two distinct periods (1923-1980)-(1980-2017), using different statistical methods. The most important part of this is focused on the meteorological drought defined by the Standardized Precipitation Index (SPI). A Seasonal and annual SPI was calculated for 8rainfall stations. It has been shown that the average rainfall before 80s and after 80shave decreased by about 19 % to 47% in the studied stations. The largest decrease was observed in the center of the basin. Second, understanding the prediction of future climate of Tafna basin using downscaled climate projection from GCM product outputs of HadCM3. A Multi linear regression (MLR) was used to downscale the GCM data from A2 and B2 emissions scenarios for future climate predictions. The output generated from the statistical downscale model (precipitation and temperature) were then used to assess how these parameters may change in the future.en_US
dc.language.isoenen_US
dc.subjectClimate Changeen_US
dc.subjectStandardized Precipitation Index (SPI)en_US
dc.subjectGCMen_US
dc.subjectDownscalingen_US
dc.subjectHadCM3en_US
dc.subjectTafna basinen_US
dc.titleAssessment of Climate Change and Its Impact on Water Resources: Case of Tafna Basin–North West of Algeriaen_US
dc.typeMaster Thesisen_US


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