<p>This study addresses the nonlinear inverse problem of concurrently identifying the time-varying potential and force coefficients in the sixth-order Boussinesq-Love equation, utilizing supplementary observations within the spatial domain. The issues of existence and uniqueness of the solution are established via the contraction mapping principle over a sufficiently small time interval. Conditional stability for the nonlinear inverse problem is demonstrated by employing suitable a priori estimates on the unknown coefficients. The unique solvability of the governing inverse problem is rigorously established through dedicated theorems. Nevertheless, the underlying sixth-order equation remains ill-posed, wherein minor perturbations in the additional input data can lead to substantial deviations in the recovered potential and force terms. To address this instability, a regularization technique is employed to stabilize the solution. To obtain a stable solution, the regularized cost functional is minimized for the retrieval of the unknown coefficients. The sixth-order Boussinesq-type equation is numerically treated using a septic B-spline (SB-spline) collocation scheme, leading to its transformation into a nonlinear least-squares optimization problem within the framework of Tikhonov regularization. The resulting system is numerically solved using MATLAB’s built-in subroutine, <Emphasis FontCategory="NonProportional">lsqnonlin</Emphasis>. The proposed framework is applied to invert both noisy (perturbed) and exact analytical datasets. Numerical results corresponding to a benchmark test case are presented and analyzed to assess the accuracy and robustness of the method. Additionally, the von-Neumann stability analysis is conducted to evaluate the stability characteristics of the SB-spline-based numerical scheme.</p>