Accurate spectral calibration is essential for quantitative imaging spectroscopy, as even sub-nanometer wavelength errors can propagate into atmospheric correction and surface-property retrievals. Existing approaches for in-flight wavelength calibration typically assume simplified spectral parameterizations, limiting the complexity of wavelength variations that can be recovered from atmospheric absorption features. In this study, we investigate the information content of visible-to-shortwave infrared (VSWIR) observations for constraining instrument wavelength calibration using a Bayesian maximum a posteriori retrieval framework. Using nine high signal-to-noise EMIT (Earth Surface Mineral Dust Source Investigation) scenes acquired over spectrally homogeneous desert targets, we systematically evaluate spline-based wavelength calibration models with varying numbers and placements of spline knot points. Model performance is assessed using agreement with Zemax optical simulations, solution consistency across independent scenes, and leave-one-out cross-validation. All three evaluation criteria identify a four-knot spline representation as the optimal balance between model flexibility and stability, whereas more complex parameterizations exhibit increased sensitivity to knot placement and reduced reproducibility. Applying this optimal configuration independently across the detector array reveals coherent cross-track wavelength-dispersion variations that cannot be adequately represented by traditional uniform or simple spectral-smile corrections. Although the retrieved spatial variations are small—typically on the order of 1 % of a spectral channel width—they exhibit a structured saddle-shaped pattern that is consistent across scenes and indicative of genuine instrument behavior. These results demonstrate that atmospheric absorption features provide sufficient information to retrieve spatially varying wavelength calibration for modern VSWIR imaging spectrometers, supporting more accurate radiometric processing and motivating spatially resolved spectral calibration strategies for current and future spaceborne missions.