Abstract: Hydrologic information systems must address the full range of operational needs, rather than be divided into specialty "silos", because of the strong interactions among observations, characterization, forecasts, and planning. These characterize both water resources and restoration projects. Hydrologic data assimilation puts observations first, in a systematic procedure that corrects forecasts based on measurements, on estimates of errors in observations and in forecasting, and on significant operative processes. In effect, each data collection event is used to update predictive modeling tools. Exploiting observational data in this way has an economic benefit (the return on data collection costs is sooner) and a technical benefit (constraints provided by data improve predictability). Practical benefits are realized by improving the design and operations of well fields (e.g., locations and rates), as well as the design and operations of monitoring networks. This talk examines the distinctive challenges of this strategy and discusses approaches for dealing with them.
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