Remote monitoring of our environment can be done, even in the harshest conditions, using a combination of sensors. The health and wellness of a river can be monitored by measuring water depth, turbidity, pH, conductivity, and nutrient content (nitrogen and phosphate), some of these being cheap and off-the-shelf, others being more expensive, and all suffering from problems of calibration and biofouling. Similarly for a coastal area like a bay, we can measure sea surface temperature, wave height, chlorophyll content and water composition with the same issues of calibration and biofouling. Each of the sensors we use to monitor environments, especially water-based environments, produce streams of data values which need to be woven together in order to get an holistic overview of the health of the area being monitored. In this presentation I will describe how environmental monitoring using multiple sensor streams is really a problem of data fusion where each of the incoming data streams has accuracy and reliability issues. I will also describe how we have developed, and deployed, a trust and reputation framework to address these issues and how we have put this into effect in remote monitoring of two coastal regions.