Dissolved natural organic matter (NOM) and heavy metals are ubiquitous in aqueous and terrestrial systems. Adsorption processes involving mineral surfaces largely control the fate, transport, and environmental impacts of NOM and heavy metals. An understanding of NOM and metal sorptive behaviors is therefore helpful in the development of predictive models. To better understand the interactions between NOM, heavy metals, and mineral surfaces, this research (1) evaluated a bulk property approach to study NOM and potential aqueous complexation between NOM and heavy metals, (2) studied the mutual effects of NOM and cadmium on their sorption to goethite, and (3) began to develop a web-based computer simulator to model NOM adsorption at the mineral-water interface. In the first project, the effects of cadmium and lead on NOM properties and the potential effects of metals and counterions on analytical methods were investigated using a bulk property approach. This study showed that Cd2+ and Cl- did not influence the absorbance, molecular weight distribution (MWD) and apparent molecular weight (MW) of NOM. It also showed that Pb2+ and NO3- produced analytical artifacts that can interfere with the system under investigation when they are present in the samples analyzed using molecular absorbance spectrometry (MAS) and high pressure size exclusion chromatography (HPSEC). The second and third projects examined the sorption trends of cadmium and NOM to goethite, with results similar to those found in the literature. The results showed that the presence of cadmium increased NOM adsorption and that the presence of NOM increased cadmium adsorption. This study also demonstrated that sorptive fractionation of NOM was influenced by pH. At low pH, the presence of cadmium had little effect on the adsorptive fractionation of NOM; whereas, at high pH, the presence of cadmium enhanced it. In the final project, a stochastic agent-based simulator, NOMAdSIM, was developed to model NOM adsorption based on MW transformations under batch (no-flow) and column (flow) conditions. In addition to refining specific parameters, NOMAdSIM can be further developed to accommodate changes in ionic strength, pH, and sorbent affinities. Eventually, the model's applicability could be expanded for metal and microbial interactions as well as other processes.