Genome-wide association studies (GWAS) have been widely used to identify quantitative trait loci (QTLs) underlying complex agronomic traits. The conventional GWAS model is based on a single-locus model, which may prove inaccurate if a trait is controlled by multiple loci, which is the case for most agronomic traits in barley (Hordeum vulgare L.). Additionally, an individual single nucleotide polymorphism (SNP) will prove incapable of capturing underlying allelic diversity. A multilocus model could potentially represent a better alternative for QTL identification. This study aimed to explore different GWAS approaches (single-SNP, multi-SNP, and haplotype-based) to establish SNP-trait associations and to potentially describe the complex genetic architecture of seven key traits in spring barley. The multi-SNP and haplotype-based approaches unveiled a larger number of significant associations, some of which were shared with the single-SNP approach. Globally, the multi-SNP approach explained more of the phenotypic variance (cumulative R-2) and provided the best fit with the genetic model [Bayesian information criterion (BIC)]. Compared with the multi-SNP approach, the single-SNP and haplotype-based approaches were relatively similar in terms of cumulative R-2 and BIC, with an improvement with the haplotype-based approach. Despite limited overlap between detected QTLs, each approach discovered QTLs that had been validated previously, suggesting that each approach can uncover a different subset of QTLs. An integrated GWAS procedure, considering single-locus and multilocus GWAS approaches jointly, may improve the capacity of association studies to detect key QTLs and to provide a more complete picture of the genetic architecture of complex traits in barley.