Structural variations (SVs) pervade plant genomes and contribute substantially to the phenotypic diversity. However, most SVs were ineffectively assayed due to their complex nature and the limitations of early genomic technologies. By applying the PacBio high-fidelity (HiFi) sequencing for wheat genomes, we performed a comprehensive evaluation of mainstream long-read aligners and SV callers in SV detection. The results indicated that the accuracy of deletion discovery is markedly influenced by callers, accounting for 87.73% of the variance, whereas both aligners (38.25%) and callers (49.32%) contributed substantially to the accuracy variance for insertions. Among the aligners, Winnowmap2 and NGMLR excelled in detecting deletions and insertions, respectively. For SV callers, SVIM achieved the best performance. We demonstrated that combining the aligners and callers mentioned above is optimal for SV detection. Furthermore, we evaluated the effect of sequencing depth on the accuracy of SV detection, revealing that low-coverage HiFi sequencing is sufficiently robust for high-quality SV discovery. This study thoroughly evaluated SV discovery approaches and established optimal workflows for investigating structural variations using low-coverage HiFi sequencing in the wheat genome, which will advance SV discovery and decipher the biological functions of SVs in wheat and many other plants.