Environmental sensor networks are now commonly being deployed within environmental observatories and as a component of numerous smaller-scale ecological and environmental experiments. Effectively using streaming data from these sensor networks in near real-time proposes a set of technical challenges that is difficult for scientists to overcome and severely limits the adoption of automated sensing technologies in environmental science. The Realtime Environment for Analytical Processing (REAP) project addresses these technical challenges related to accessing and using heterogeneous streaming sensor data from within the Kepler scientific workflow system. Scientific workflow systems can be used to access, stream, and analyze data from observatory networks and archives. Integrated access to both near real-time data streams and data archives from within the Kepler scientific workflow system facilitates sophisticated analysis and modeling with these data sources. We outline applications of sensor-enabled scientific workflows for a terrestrial ecology use case.