A novel probabilistic approach to characterization of water quality vulnerability along Urban Gradients

Water quality along urban streams are influenced by point and nonpoint source pollutant loads. Regulatory approaches, such as the Total Maximum Daily Load (TMDL) program, aim to reduce pollutant loads from these sources to improve physical, chemical, and biological integrity of water bodies. This study presents a novel probabilistic approach to characterizing vulnerability to water quality degradation as a function of both ambient water quality conditions as well as desired water quality standards and targets. A coherent and rigorous statistical method was developed to quantify the likelihood of violating water quality standards under varying hydrologic regimes. The methodology reconciles probability models for various water quality parameters, i.e. total phosphorus, total nitrogen, nitrate, and dissolved oxygen, with load duration curves to investigate geospatial variables and urban influences that drive water quality impairments in urban streams. The assessment framework was demonstrated in six regions across the continental United States, encompassing varying ecohydrologic conditions. Results show that water quality degradation occurs as average population density, cumulative wastewater treatment facility capacity, and percent urban land cover increases. For example, results for Denver, Colorado indicate that total phosphorus and nitrogen vulnerability to exceeding established state level water quality standards increase along the South Platte River as urban influences increase. This approach to vulnerability characterization will provide important information to assist in TMDL development and maintenance in order to meet current water quality standards, and to continue meeting water quality standards in the future, ultimately to protect rivers as a valuable resource in growing cities.