Emerging Sensors and their Implications for the Future of Environmental Observatories

Considering the range of space and timescales involved and the diverse nature of watershed-scale processes, environmental measurements can only be meaningful when they are performed long-term at high spatial-temporal density. The establishment of coastal observatories will depend a lot on our ability to obtain such high density datasets requiring long-term in situ unattended data acquisition. Also, the interplay of environmental and forces and bio-geochemical cycling necessitates long-term studies and different variables need to be measured to develop adequate forecast and response systems. Since nutrients partition to particulate matter, embayment productivity can be directly correlated with particulate matter mass flux at flux points or across system boundaries. Without the prerequisite sensors our ability to quantify those fluxes will be limited. Particulate biogenic matter (e.g., phytoplankton) in surface waters is directly related to water quality. Phytoplankton abundance can be an indicator of aquatic health in lakes, bays and estuaries which can be linked to exceedingly high productivity most often due to high nutrient (N, P) loading into the receiving water body. According to the 2000 report from the Committee on Environment and Natural Resources, the annual cost of HABs in the US is $300–$700 million. However there has been relatively small progress in developing dynamic sensor systems for bio-chemical characterization of aquatic environments to date, seriously hampering the development of effective monitoring programs for critical water resources. Against this backdrop, bio-chemical sensors are required to enable better understanding of human-dominated water-environments, their stressors, and the links between them. There is a need for novel instrumentation to measure and monitor two critical nutrients nitrogen and phosphorous (total and available N, P) in surface and ground waters concurrent with determination of the impact of nutrient loading on important biota in real time. Phytoplankton growth kinetics is also critical to water quality models but the representation of biomass based on chlorophyll-`a' measurements can lead to erroneous parameterization of such models. Proper quantification of phytoplankton abundance should be a key thrust of instrumentation development which will combine both the quantification of biomass growth (specifically plankton) with information obtained on the underlying biochemical cycling (nutrients, CO₂). With advancements in photonics, the enabling technology exists in image processing, pattern recognition, digital imagery, high-resolution optical detectors, and we can match this challenge. Efforts are now geared towards developing sensor array designed purposely to be a near real-time nutrient sensor directly coupled with a trainable optical recognition particle identification and characterization unit to detect and identify biogenic particles. The ability to track N and P loading and biomass in real-time will afford the scientific community the opportunity to develop improved water quality models and better resource management programs for the nation's water resources.