Algeria is the Africa’s first-largest country, but only 3.4 percent is arable land, of which less than one-fifth is cultivated. The country depends on imports for 45 percent of its food. The country is facing a tremendous challenge which is to keep its increasing population nourished. Large imports of agricultural products (and mostly wheat) are filling the gap between internal production and consumption. Authorities are deeply concerned by its consequences on the trade balance and the increasing national food-security dependence on international markets. Wheat is the most predominant crop and need to be improved to satisfy the increasing demand. In fact, Algeria needs to import, in near future, more than 11 million tons of cereals to cover the demand of an overgrowing population. Algeria has the potential to consolidate the position of wheat as a food security crop through local production, but significant yield-limiting challenges must be overcome. To meet future production demands, multi-disciplinary breeding approaches are needed to achieve the genetic gains. Genome-wide association mapping (GWAM) can be a powerful tool for the identification of genes associated with important agronomic traits in wheat. The objective of this work was to identify marker-trait associations (MTAs) for various physiological, morphological and relevant agronomical traits for improving wheat to drought stress using GWAM approach. The plant material consisted of 600 F4 bread wheat lines which were phenotyped in the field at Sétif region (Algeria), under rain-fed and supplemental irrigation environments, and genotyped using the Illumina 15K Infinium SNP array. Population structure analysis revealed four subpopulations. GWAM results identified several significant MTAs detected in one or more environments for the measured traits in rain-fed and irrigated environments plus combined data across environments. Multi-trait QTLs were obtained on many chromosome regions of which chromosomes 1A, 2A, 3B, 3D, 4B, 5B, 6A and 7B are most significant having QTLs of grain yield co-located with flag leaf area, plant height, number of spikes, spike weight, thousand kernel weight, number of grains, biological yield, straw yield, and harvest index. However, only those on 1A, 2A, and 6A were stable across two over three environments.