embed a computational intelligence in the environment, linking sensor pods through wireless technology in a manner that allows the network to conduct adaptive monitoring and real-time control. Development of new sensors from nanosensors to new satellite-based systems was also described in Chapter 2.
Merging observations with models: Data sets are frequently assimilated into models, both to provide model-based forecasts (e.g., upper air observations used for weather forecasting; precipitation and river stage observations to forecast flood stages) and to predict variables not well measured (e.g., nonpoint pollution runoff, terrestrial evaporation).
Using results from an integrated observational-modeling system: Data and model products have no value unless they are used. They can only be used if they can be easily discovered, acquired, and understood in a timely manner to those who wish to apply them to practical issues such as flood forecasting, water availability modeling, and ecological flows, as inputs to decisionmaking. The communication and delivery of data and information to such end users is the back-bone to a beneficial integrated system. New “web-based hydrologic services” are being developed at the University of Texas by Professor David Maidment under National Science Foundation funding, and similar applications with remote sensing at the University of Illinois by Professor Praveen Kumar (Box 3-1). These nascent activities facilitate data discovery, acquisition, and integration need to be further developed and integrated with users through demonstration projects; and other competing approaches need to be developed and evaluated through similar means.