I am a PhD student and am currently developing a new project for my dissertation. Overall, my research focuses on the impacts of soil and freshwater salinization on riparian and aquatic ecosystem processes and functions. For my new project, I would like to specifically examine how anthropogenic additions of sodium via agriculture (ex. fertilizers) impact soil sodium and other nutrients, river water cation concentrations, and concentrations of sodium and other micronutrients in leaf tissues. To test the impact of land use, I would like to sample along two separate rivers located in the same watershed. The Ouachita River is heavily industrialized, developed, and receives large inputs of agricultural runoff. The other river, the Saline, is considered by the state to be pristine, is mostly wooded, and receives little agricultural runoff compared to the Ouachita. The two rivers meander separately in different directions for hundreds of miles but join together at the mouth of the Saline. Both rivers also receive natural deposits of sodium from atmospheric deposition, natural underground salt domes, and weathering. The Saline River actually got its name from a natural salt dome that was mined for salt until it closed in the mid 20th century. My big question is this, if I sample the two rivers, how do I design my experimental setup so that I can clearly parse apart land use impacts from the effects of natural salinity gradients? Can I even gain impactful data using two different rivers given that they are spatially different? My initial thought is to locate at least three sites for each river that would receive agricultural runoff, and three sites for each river that are heavily wooded and not directly downstream of any agricultural or industrial operations. I would sample three forest sites and three agricultural sites per river and would have 12 sites overall which would give me the statistical power needed; however, I'm still concerned that I wouldn't be able to confidently say that the results I get are land use driven and not influenced by natural gradients, spatial differences, etc. Does anyone have any design suggestions or input? I am a first year PhD student and am still learning how think like a researcher, and design my own experiments to gain impactful data, so any and all advice is welcome. Thanks!