Currently, although various of high precision relative gravity instruments have emerged [8; 9; 10; 11; 12; 13; 32; 33], portable spring-based relative gravimeters such as the Scintrex CG-5 gravimeter (CG-5) and the Lacoste & Romberg--G (LCR-G) gravimeter still play a key role in terrestrial gravity measurement. Generally, the zero-length spring is applied as the sensor for most relative gravimeters, and the measurement of the spring gravimeter is the feedback voltage, as it is proportional to the gravity change. The sensor of the CG-5 is a nonstatic fused quartz spring, which delivers accuracy better than 5 \(\mu\)Gal (1 \(\mu\)Gal = 1 \(\times\) 10\({}^{-8}\) m/s\({}^{2}\)) and reading resolution of 1 \(\mu\)Gal [34]. In practice, nonlinear drift of a CG-5 relative gravimeter is inevitable due to the feature of quartz elastic, and it can reach up to 200 \(\mu\)Gal/d [35; 36], especially for a survey campaign with duration longer than 24 h [36]. Unlike the CG-5, the LCR-G gravimeter uses a metal spring as its sensor, which has less drift than a quartz system [35]. Additionally, another key factor is the main constant in relative gravimeters which called scale factor (SF) or calibration factor, and stress reduction in the spring of a gravimeter under the action of an alternating load will lead to a change of SF over time [37]. Generally, in China, SF calibration is performed every 3-5 years by the China Earthquake Administration on the long-baseline with known AG values. However, it is a time-consuming and expensive process, and the calibration period cannot meet the requirement for a twice-yearly observation survey. For some regional survey networks, the SF is calibrated on the short-baseline annually, which may be not accurate due to the insufficient gravity difference of the konwn AGs. The classical gravity adjustment (CLS) method usually adopts the least squares method for the adjustment process [38; 39; 40], while the drift rate over the entire period of the campaign is considered linear. A number of different improvement methods have been proposed to remove errors attributable to SF bias [37; 40; 41] and instrumental drift [35; 38; 42]. However, the drift rate of the instruments is generally considered to be linear in the short period of loops (with few hours) or in the entire survey campaign, which is not accurate for the large-scale survey campaign with time span of months. Additionally, consideration of both SF calibration and nonlinear drift rate in the process of adjustment of relative gravimeters has rarely been discussed and applied in the large-scale continental gravity measurements. Different from the assumption of linear drift in the classical adjustment or piecewise zero drift based on the assumption of a smooth variation of the drift rate, [PERSON] proposed the Bayesian gravity adjustment (BGA) method [34], in which [PERSON]'s Bayesian information criterion (ABIC) [43; 44] was first applied to hybrid relative gravity survey adjustment. In this approach, the noise variance and drift rate variance are regarded as hyperparameters that can be estimated on the basis of the ABIC minimization criterion, and the unconditional marginal probability density function of absolute and relative gravity observations derived. Subsequently, [PERSON] proposed the modified Bayesian gravity adjustment (MBGA) method [45], which adopts the SF as a third hyperparameter to be calculated. In this study, using time-variable gravity data from the southeastern Tibetan Plateau acquired during 2018-2020, the effects of nonlinear drift rate and inaccurate SFs of different gravimeters were analyzed quantitatively using different gravity adjustment methods: the CLS method, BGA method, and MBGA method.