Biochar can provide many available phosphorus (P) that can be absorbed and utilized by plants. In this paper, laser-induced breakdown spectroscopy (LIBS) was used to detect water-soluble P in straw based biochar quantitatively. To reduce the serious “coffee ring effect” on the substrate's surface after droplet drying, hydrophobic polyethylene plate was selected as the liquid-solid conversion substrate. To solve the problem of the low sensitivity of LIBS signal of water-soluble P element in biochar, the signal enhancement performance of three kinds of Au nanoparticles (AuNPs) on four analytical lines of P element was studied and discussed. The results show that Au nanoparticles with large particle size (73 and 105 nm) are more prone to the aggregation effect, and the spectral signal-to-noise ratio is large. Furthermore, the P element's univariate calibration curve models enhanced by three kinds of particle size Au nanoparticles were compared and analyzed. The results show that the univariate calibration curve models with 45 nm Au nanoparticles signal enhancement are the best. Finally, the four enhanced spectral broadening bands enhanced by the Au nanoparticles were used to develop the ElasticNet-support vector regression (EN-SVR) model. The average error of the prediction set (ARP) and the relative standard deviation of the prediction set (RSDP) of the optimal model were 5.40% and 11.09%, respectively. The results show that nanoparticle enhanced laser induced breakdown spectroscopy (NELIBS) combined with the EN-SVR model can be used for the accurate quantitative determination of water-soluble P in biochar.