Konstantinos M. Andreadis

Toward global-scale data assimilation using SWOT: Requirements for global hydrodynamics models

The measurement of spatially distributed water surface elevation (WSE) at the global scale, which is planned by “Surface Water and Ocean Topography (SWOT) mission”, will bring lots of fresh knowledge on global-scale terrestrial water circulation especially when observed WSE is merged into global hydrodynamics modes by data assimilation. In this paper, we discussed the predictability of WSE by a global hydrodynamics model, which is required as a dynamic core for global-scale data assimilation using SWOT. From the comparison against WSE observed by the altimeter on Envisat, we found that the up-to-date global hydrodynamics model is able to reproduce the seasonal variations of WSE in the Amazon River, though predicted WSE still has errors due to the uncertainties in topographic parameters and sub-grid-scale dynamics of the model. Reduction of these uncertainties is required along with the development of the algorithm itself for achieving global-scale data assimilation of WSE.

A genetic approach to estimating river bed topography from SWOT observations

River bathymetry plays a key role in estimating river discharge as well as improving our modeling capabilities of fluvial geomorphology. Genetic algorithm techniques can be used to derive river bed topography using only water surface elevations and the corresponding temporal and spatial rates of change. Each river bathymetric estimate, also referred to as a solution, is modeled as a successive collection of cross-sections, also referred to as genes. An initial population of potential solutions is created from solutions comprised of random cross-sections with depths ranging as deep as the surface height to no depth at all. The population is successively evolved by randomly mutating the depths at a random number of cross-sections. The solutions are selected for the next generation by evaluating their individual fitness. Three varieties of fitness tests are applied to each potential solution: Saint-Venants 1-D flow equation, flow continuity, and the statistical power-law relationships suggested by Leapold & Maddock[1]. In this manner, an ideal solution is derived.