Hyporheic exchange directly controls and regulates the transport of nutrients, heat, and organic matter across the sediment–water interface (SWI), thereby affecting the biochemical processes in rivers, which is critical for maintaining the health of aquatic ecosystems. The interface exchange is controlled by multiple processes, including physical, chemical, and biological processes, which can be modeled by the effective diffusion model using an effective diffusion coefficient, D_eff, to quantify the hyporheic exchange rate. In this study, genetic programming (GP), a machine learning (ML) technique based on natural selection, is adopted to search for a robust relationship between the effective diffusion coefficient and surface flow conditions, bedforms, and sediment characteristics on the basis of published broad interfacial mass exchange flux measurements. By utilizing a data set covering a wide range of environmental …