Environmental Data Management

A holistic viewpoint is taken of basic data needs to support environmental forecasting, modeling, and decision making. A protocol is suggested which places forecast errors in a key role. Data bases should be reviewed and their error properties analyzed with respect to forecasting precision. Data programs should be oriented to minimizing forecast variance within cost and overall program needs constraints. Recognized big issues concern the: (1)Need for a rational data assessment protocol; (2)difficulty of generalizing requirements; (3)fact that simulation models have outdistanced the availability of data to support them; (4)observation that agency programs apparently place too much stress on analysis and not enough on data gathering activities; and (5)chronic problem that water quantity and quality data collection needs to be coordinated.