Covariance kernels investigation from diffusive wave equations for data assimilation in hydrology

Abstract In data assimilation (DA), the estimation of background error covariance operator is a classical and still open topic. However, this often modeled using empirical information. order to exploit at best potential knowledge physics, present study proposes method derive operators from underlying equations. addition, Green’s kernels can be used model are naturally linked them. Therefore, equations representing physics provide physically-derived estimates operator, also physically-consistent parameters. context, in variational DA (VDA) process altimetric infer bathymetry Saint-Venant investigate these new operators, associated VDA results compared with arbitrary The exponential better accuracy faster convergence than especially during first iterations optimization process.