Over the past century, coastal regions have been increasingly experiencing environmental hazards resulting from changes in human activities and climate. Hypoxia, recurrent low-oxygen conditions that are unsuitable for benthic/pelagic species, provides one such example. In the Chesapeake Bay (CB) alone, ~8km³ of water is typically hypoxic during the summer months, and warmer waters are increasing this volume. The present work is part of the Department of Energy's (DOE) Integrated Coastal Modeling project (ICoM) which aims to improve the ability of Earth System Models to represent coupled interactions between human and natural systems over multi-decadal timescales. Here we evaluate the capability of current DOE modeling tools to simulate CB hypoxia. Specifically, hydrologic and oceanic forcings from DOE are integrated (one component at a time) into an existing regional 3D physical-biogeochemical model of CB. Modified forcings include: riverine freshwater discharge as well as the continental shelf salinity, temperature and sea surface height. The skill of the resulting model simulations is evaluated using data from CB's Water Quality Monitoring Program. Results indicate that short-term (days to month) variability in CB conditions remains mostly the same between the simulations and is thus largely dictated by the meteorology. However, substantial biases in salinity (1.0 psu) and temperature (0.7C) develop when DOE's hydrographic forcings are imposed on the shelf. These changes are apparent throughout the estuary's bottom layer up to its head (400km away). The biological response to these changes is relatively minor, with the key effect being an inland-directed shift in where primary production occurs, and a small impact on the dissolved oxygen skill. Greatest changes in summertime hypoxic volume (<20%) are associated with high river discharge events. Larger changes in model skill are expected to be seen in upcoming simulations where other model forcings will be modified, notably nutrient loadings and air temperatures. These results will help us better understand how regional earth system models can be improved, so they can be used for climate change adaption and mitigation decisions.