REGIONAL SCALE ANALYSIS OF RIVER FLOW AND CHEMISTRY SHOWS LITHOLOGY, CLIMATE, AND ANTHROPOGENIC CONTROLS ON SPATIAL TRENDS IN MAJOR ION BEHAVIOR ON THE COLORADO RIVER, TX

Understanding surface water quality and managing river systems that span large climatic, lithology, and land use gradients requires regional scale approaches, yet historically hydrologic studies have focused either on small well-instrumented catchments or with continental scale models. Studies focused on intermediate regional-scale river systems are needed in bridging the gap between the above two scales of models and allow for increased complexity while utilizing publicly available and long-term datasets. Stream chemistry in rivers is influenced by a combination of variables including climate, land use, lithology, tectonics, and watershed landscapes. A combination of multiple analytical techniques gives an opportunity for identification of driving factors and their degrees of influence within a system. In this study, we utilize the Colorado River in Texas as an ideal laboratory to understand impacts of changing lithology and land use across a climate gradient. The Colorado river flows northwest to southeast across Texas where precipitation and land use intensity generally increase eastward, and lithologic changes occur perpendicular to flow. Readily available measurements of river flow (155 sites) and concentration of major ions (approximately 4,700 measurements of each solute) from 1958-2018 and newly collected stream water chemistry data are used in this study to parse out climate, land use, and lithology controls on spatial variations in stream water chemistry. Preliminary assessment of concentration-discharge (C-Q) relationships, piper diagrams, and compositional principal components analysis has revealed spatial trends in stream water chemistry that can be attributed to evapotranspiration, presence of carbonates and gypsum, mixing associated with reservoirs, inputs of solutes from oilfield brines, and contributions from tributaries with differing watershed attributes. Regression model development using sub-watershed characteristics in combination with stream chemical data allows for quantification of these influencing factors across spatial scales. Our analyses offer a transferable workflow that can illuminate complex processes controlling hydro-geo-chemistry and provide insights into watershed-based management strategies at a regional scale.