Abstract: The CNMM-DNDC model, which is developed by the authors, is a three-dimensional (3D), high-resolution, and process-oriented terrestrial hydro-biogeochemical model that fully couples the cycling processes of carbon (C), nitrogen (N), phosphorus (P), and water in terrestrial ecosystems on the site, catchment, regional, or global scale. This work reviews the proposed model based on the development background, basic ideals, and theories; core scientific processes, characteristics, and features; comprehensive functions; observational verifications; and preliminary applications on the site, regional, or catchment/basin scale. Since the publication of its first version in 2018, this model has undergone several improvements in scientific process and function. The complete coupling of C, N, P, and water cycles in this model has been realized by numerically linking a series of biogeochemical reactions of these life elements and phase changes and mechanical movements of matter occurring in terrestrial earth surface systems. Wide validations with comprehensive field observations indicate that the proposed CNMM-DNDC model can be generally applied to long-time 3D and “3H” integrative simulations of terrestrial ecosystems in different bioclimatic zones from tropical to boreal permafrost regions; here, “3H” refers to high spatial, temporal, and process resolutions. Because this model was developed to efficiently describe the biogeochemical transformations and 3D movements of the three life elements and water on different scales (site, ecosystem, catchment/basin, regional, or global), current validations and preliminary applications could demonstrate its potential to simultaneously forecast multiple variables for estimating ecosystem sustainability in terms of the United Nations Sustainable Goals (SDGs). The predictable variables include hydraulic soil erosion; surface runoff and subsurface flow; leaching of water and C, N, and P solutes; horizontal flows of dissolved and particulate C, N, and P substrates or matter; greenhouse gases (carbon dioxide, methane, and nitrous oxide) and gaseous N pollutants (ammonia and nitric oxide) emissions; ecosystem productivity; water evapotranspiration; and balances between energy, water, C, N, and P. In conclusion, our model is anticipated to offer state-of-the-art technical support for performing numerical simulations for the multiple-goal implementations of SDGs as it could be (a) a robust tool for virtually experimental studies on complex processes on different scales and (b) a core model of a decision supporting system for optimizing the carbon and environmental management.