At field scale, surface soil had special characteristics of volumetric moisture content (VMC) with a relatively little difference and spatial heterogeneity induced by physical and chemical properties, roughness, straw residues, etc. It has been a great challenge for near infrared diffuse reflectance spectroscopy (NIR-DRS) measurement of surface soil moisture in situ. In this study, exonential decay models based on seven water-related wavelengths (1 200, 1 400, 1 450, 1 820, 1 940, 2 000 and 2 250 nm), linear models of normalized difference soil moisture index (NSMI) and relative absorption depth (RAD) based on wavelength combinations, linear or quadratic model of width of the inflection (σ), center amplitude of the function (Rd) and area under the Gaussian curve (A) from soil moisture Gaussian model (SMGM), and partial least square (PLS) regression models based on bands were used to quantify VMC. The results indicated that (1) of all the single wavelengths, 2 000 nm showed the best validation result, indicated by the lowest RMSEp (2.463) and the highest RPD value (1.060). (2) Comparing with RAD, the validation of NSMI was satisfactory with higher R2 (0.312), lower RMSEp (2.133) and higher RPD value (1.224). (3) In the validation results of SMGM parameters and PLS fitting, Rd was found to produce the best fitting quality identified by the highest R2 (0.253), the lowest RMSEp (2.222), and the highest RPD value (1.175). (4) Comprehensively, a linear model based on NSMI showed the highest validation accuracy of all the methods. What is more, its calculation process is simple and easy to operate, and therefore become the preferred method to quantify surface soil moisture content in situ.