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Estimation of evapotranspiration and recharge flux are fundamental to sustainable water resource management. These fluxes provide valuable insights for decision-makers, enabling them to implement effective strategies that balance water demand with available resources, promote resilience in the face of climate change, and ensure the long-term sustainability of water ecosystems. In-situ observations of evapotranspiration and recharge are scarce and not representative of large areas. An observation driven variational data assimilation system, named LIDA-2 (Land Integrated Data Assimilation framework) is developed to estimate the key parameters (evaporative fraction, bulk heat transfer coefficient, Brooks-Corey parameter) of evapotranspiration and recharge fluxes by assimilating GOES land surface temperature (LST) and SMAP surface soil moisture observations into a coupled water and dual- source energy balance model. Second order information is used to estimate the uncertainty and guide the model toward a well-posed estimation problem. The algorithm is implemented in part of the US southern great plain, and its performance is evaluated through comparison tests, uncertainty analysis and consistency test. Soil moisture and evapotranspiration estimations are validated against in-situ observations. The spatial pattern of estimated annual recharge map is in good agreement with maps from literature. Overall, the VDA based framework demonstrated its efficacy to do largescale mapping of recharge, and evapotranspiration.