Building and evaluating the high-resolution, integrated groundwater-surface water ParFlow modeling platform of continental China (CONCN): leveraging global datasets in a data-poor region

ParFlow CONCN model is the first integrated groundwater-surface water modeling platform over the mainland of China with a resolution of 30-arcsec and a depth of 492 m. With the flexibility of reconstruction and prediction of groundwater and surface water states and fluxes, it is undoubtedly an efficient tool for scientific understanding on water cycle and decision making on water resources and thus to tackle China’s water crisis in the changing world. Nonetheless, the CONCN model may have broader significances to the hydrologic community. Model evaluation and comparison is a common practice in the geoscientific modeling communities, such as those of land surface and earth system models. Due to the challenges in aquifer parameterization and the expensive computing requirement, high-resolution, large-scale, 3D groundwater modeling or integrated hydrologic modeling with 3D groundwater component is still under development though becoming more active in the past decade. Several national-scale such integrated hydrologic models, for example, ParFlow models over CONUS, west Africa, and Germany, have been built at 1 km resolution or higher with satisfying performances. However, the wide extension of modeling in this category to other places worldwide or to global scale is limitedly explored, preventing the evaluation of modeling workflows at different places and comparison with models using other parameterization schemes. Here, we demonstrate the construction and the first-phase evaluation of CONCN model by leveraging global datasets. Global permeability (GLHYMPS 1.0) and hydrography (MERIT Hydro) products were helpful to build the model while global water table depth (Fan et al., Science, 2013 and Zeng et al., JAMES, 2018) and streamflow (GRADES-HYDRDL and CNRD v1.0) products were adopted to preliminarily evaluate the simulation results. In this data-poor modeling area, both the construction and evaluation of the CONCN model are impossible about five years earlier as most of these global datasets did not exist. Therefore, the CONCN model can be one of the pioneers to evaluate and then to improve the current workflow of the existing models and address the challenges in new modeling areas with hydrogeology, hydrography, and climatology unseen in existing models. We also expect our dilemma caused by lacking observations as many other modelers in China can push the data-sharing to constrain hydrologic models and to motivate the collaboration such as model intercomparison in the Chinese hydrologic modeling community, which are well developed in the global community.