Project Description

Sampling in the Little Bear River

The Little Bear River Test Bed, which is located near Logan, UT, is an environmental research facility associated with Utah State University. It is one of 10 WATERS Network test bed projects located across the United States and funded by the National Science Foundation. These test beds focus on environmental sensors, deployment of sensor networks, development of new modeling tools, and development of cyberinfrastructure.

This project is examining a special case of a general problem important for environmental observatory design by developing a set of “smart” sensors connected to a central database. The sensors collect real-time, high frequency data of easily monitored variables (e.g. turbidity), and the control system will use that information with a Bayesian Network to initiate intermittent sampling of more difficult to measure constituents (e.g. phosphorus). The real-time values will be related to the wet chemistry data and used as surrogates to quantify fluxes of interest. Specific objectives include the estimation of fluxes from surrogate data, the relation fluxes to watershed attributes and management practices, and the development of two way linkages between the sensors, a central database, and models or data analysis software.

Research infrastructure in the Little Bear River test bed includes several real time streamflow and water quality stations, four real time weather stations, a spread spectrum radio telemetry network, and the database, software, and computer infrastructure required to process and manage the data collected in the Little Bear River watershed.

Project Objectives

Objective 1: Data Collection and Surrogate Measures - An Integrated Monitoring System

Sensor technology currently does not exist for measuring the concentrations of many important water quality constituents continuously and in real time. Under this objective we are working to construct time series of estimates for constituents that we cannot measure continuously from surrogate measurements that can be collected inexpensively and frequently. An example is using turbidity as a surrogate measure for total suspended solids. The following figure depics the integrated monitoring system that is being used in the Little Bear River to satisfy this objective.

Integrated Monitoring System

Objective 2: Assess High Frequency Nutrient Loading

Traditional monitoring approaches are generally inadequate for capturing the true variability in constituent fluxes. This is because grab samples do not have the temporal resolution required to represent dynamic environmental processes.

Traditional Sampling Example

Continuous monitoring of surrogate measures with high frequency reveals variability in streamflow and water quality at time scales that are much smaller than gaps between traditional grab samples.

High Frequency Sampling Example

By combining high frequency surrogate measurements with low frequency grab samples and higher frequency automated sampling of storm events, a much clearer overall loading picture may emerge. In addition, loads can be partitioned between storm events, spring runoff, and baseline loading.

Integrated Sampling Example

Objective 3: Cyberinfrastructure Development

Sensor Deployment: We are deploying continuous streamflow and water quality monitoring instrumentation at several locations within the Little Bear River watershed. The data collected at these sites are providing the basis for the scientific analyses being conducted.

Installation of Monitoring Infrastructure

Telemetry and Data Management: We are developing the communications and data processing infrastructure to link the sensors and a central observations database in real time. We are using the CUAHSI HIS Observations Data Model (ODM) as the central repository for all of our monitoring data.

Development of Communcations Infrastructure

Client Application Development: We are implementing portions of the CUAHSI Hydrologic Information System and other client applications that use the continuous monitoring data and serve it to the public.

Development of Applications