The water quality of streams draining watersheds has been degraded by increasing urbanization. The general symptoms of this degradation include more frequent large flow events, reduction in channel complexity, reduced retention of natural organic matter, and elevated concentrations of nutrients. Newly emerging urban water quality threats, including insecticides, herbicides, pharmaceuticals, and estrogens, are known or suspected to damage the health of humans and ecosystems. The restoration and management of streams have traditionally attempted to improve the hydrological and water quality conditions in-stream or in riparian zones. Recent studies have indicated the portion of a watershed covered by impervious surfaces and connected to the stream by stormwater drainage is the primary degrading process of stream ecology and health. These findings suggest that the sustainable restoration and management of stream water quality require quantification of hydrological, chemical, biological, and geomorphological processes, and that these processes must be assessed across a range of scales. Furthermore, interactions among biogeochemical processes across watersheds are either non-linear processes or linear processes dependent on non-linear drivers. The monitoring of such a system inherently requires a change in traditional field sampling strategies. We propose to transform traditional and very limited (in terms of spatial and temporal resolution) field measurements through the integration of multi-scale, spatially-dense, high frequency, real-time, and event-driven observations by a wireless network with embedded networked sensing. Intellectual merit: The objective of our research is to establish a wireless network with embedded sensing capable of monitoring fundamental water quality parameters. Such a network is a key component for watershed observatory networks. The ability of these fundamental water quality parameters to be used for predicting the presence of emerging chemical contaminants in urban streams will also be determined. It is hypothesized that the concentrations of emerging contaminants will correlate with the fundamental parameters measured using the sensor network and that the sensor network will give improved prediction of the loads of these contaminants compared to traditional, discrete grab sampling. Our overall hypothesis is that water quality in streams draining impervious areas of urban land is controlled by the mean and variance of effective stormwater residence time. The mean and variance of water residence time, the time it takes urban runoff to travel between the impervious urban land and a receiving aquatic body, will be quantified by radio frequency identification technology (RFID), tracer studies, and fluid-flow velocity measurements within the proposed wireless network. A small urban watershed will be equipped with wireless networked sensing to address the following objectives: (1) measurement of fundamental water quality and hydrologic parameters with spatiallydense and high frequency resolution, (2) correlation of general parameters with the presence and/or levels of emerging contaminants, and (3) integration of field measurements to the watershed using primarily the mean and variance of effective stormwater residence time. Water quality in streams will be observable as a dynamic response to land use gradients and hydrological transients rather than as an equilibrium described byaverage properties. This approach will enable process-based scaling and forecasting of water quality in streams from the in-stream processes to the watershed level. Broader impact: Wireless networks with embedded networked sensing are designed to quantify spatial and temporal heterogeneities of variables across a variety of scales and are perfectly suited not only for water quality management in streams but also to all environmental processes where interconnectivity among different parts determines the overall state of the system. The network to be developed in this project will focus on an urban stream, but can be expanded to include other watersheds with different land uses in the future. Generated data and scaling relationships will transform urban planning practices and management of water quality in streams draining urban land. Rather than focusing on manipulating in-stream processing only, a more sustainable approach would be to focus on selection and location of stormwater best management practices (e.g., detention ponds or wetlands). The proposed field measurements are focused on evaluating best management practices for more appropriate and effective hydrologic management. The project will have two educational components. One addresses students and scientists through a revised educational curriculum. The other is an international collaboration with the Technical University of Denmark through a developed Internet course on "Integrated Urban Water Quality Management."
