The comparison of the Hydrological Angular Momentum (HAM) with hydrological signal in observed geodetic excitation functions is a common method of assessing the influence of land hydrology on polar motion excitation function.

This hydrological signal is estimated as differences between observed geodetic excitation functions (Geodetic Angular Momentum, GAM) and a sum of Atmospheric Angular Momentum (AAM) and Oceanic Angular Momentum (OAM).

HAM can be estimated either from global models of land hydrosphere or from harmonics coefficients C_{nm}, S_{nm }of the Earth’s gravity field.

We compare several sets of degree-2, order-1 harmonics of the Earth’s gravity field, derived from the Gravity Recovery and Climate Experiment (GRACE), Satellite Laser Ranging (SLR) and Global Navigation Satellite Systems (GNSS) data. We use the degree-2 coefficients to estimate gravimetric polar motion excitation functions χ_{1} and χ_{2}. Additionally, the global models of land hydrology such as Global Land Data Assimilation Systems (GLDAS), which contain information about water mass redistributions in the global hydrosphere, are used to estimate hydrological polar motion excitation functions χ_{1} and χ_{2}.

The aim of this study is to determine the optimum model of the hydrological angular momentum (HAM) by finding the best agreement between the values derived from geodetic observations and different combination of the hydrological excitation functions.

Our algorithm is based on a fit of hydrological excitation functions to geodetic residuals using the least-square method.