The area of water resource applications is one of growing importance for GCIP because of both strong interest within NOAA and the priorities of the GEWEX Hydrometeorology Panel (GHP). GCIP is already carrying out research related to this topic. The University of Arizona has prepared summaries of relationships between GCIP and the water resources sector. Relevant studies have been carried out to determine the effects of the spatial scale of precipitation inputs to hydrologic models for streamflow forecasts. Studies have also been done to characterize the scaling properties of precipitation in order to develop a wavelet scheme for downscaling precipitation for input into hydrological models. Work on distributed hydrologic models will facilitate the coupling of hydrologic and atmospheric models for further studies involving the prediction of water budget components. The results of some of this research have already been applied in a water resource assessment project being carried out in the Columbia River Basin.

GCIP plans to increase the level of effort in this area. It has been working with the Office of Hydrology in the area of hydrologic modeling with the hope that some links will be forged with water resource agencies through this initiative. The priority for the Des Moines River Basin in the LSA-NC is recognition that links to water resource managers could be strengthened within this area - the first basin in the nation where the Office of Hydrology is installing its Advanced Hydrologic Prediction System. Other potential links between GCIP and the Office of Hydrology will become clearer as the program is implemented.

In the past, a Water Resources Principal Research Area has considered the issue of climate change and water resources. Since the prioirties for GCIP in this area have now broadened with the clarification of the GCIP mission statement by the National Academy of Sciences, a focus on hydrologic modeling and its application to water resources is now taking place in GCIP. The results from the LSA-E detailed Design Workshop provide an excellent start along these lines. A complete summary report of this workshop is given in Appendix B. Recommendations prepared by the work session on hydrometeorological prediction and water resources management is given in the remainder of this section.

The water resources working group at the LSA-E Detailed Design Workshop focused on how GCIP LSA-E activities could contribute to GCIP's evolving goals with respect to water resources. The working group focused its recommendations on those LSA-E activities which would have the greatest "spinoff" benefits for water resource systems operations. It was clear that improvements in short and long-range weather forecasting represent the strongest tie between the GCIP research community and water resources operations, both generally and for LSA-E in particular. As a means to direct the LSA-E water resources activity in this direction, the an experimental water resources forecast capability for part or all of LSA-E was recommended, as follows:

1) GCIP should develop an experimental streamflow forecast capability for the two major river systems within LSA-E: The Tennessee-Cumberland, and the Ohio River systems. It is important that this activity be implemented with parallel research and operational pathways, the latter of which would incorporate the involvement of the two RFCs that operate in LSA-E.

2) An ensemble approach to hydrologic forecasting is needed for several reasons. First, PRYSM-type water resources systems models are designed to process ensembles of events to evaluate the implications of alternative operating decisions when the future reservoir inflows are not known exactly. In addition, ensemble prediction methods allow uncertainty in future precipitation patterns throughout a river basin to be analyzed in a way that is statistically consistent for all forecast points in the basin. The TVA system would provide an excellent test site for evaluation of ensemble hydrologic forecasts derived from coupled land-atmosphere models.

3) Opportunities for diagnosis of NWP models (especially NCEP/Eta, but longer range forecast models as well as their land surface schemes are updated) soil moisture should be exploited using the parallel simulations produced using observed forcings. The potential for updating for NWP model soil moisture using streamflow prediction errors should be evaluated as well.

4) Attention should be given to the role of biases in both meteorological forecasts (forcings to hydrologic forecast models) and in the hydrologic models themselves. Every hydrologic model includes at least some seasonal bias in the statistical properties (e.g., means and variances) of model outputs when the models are operated in a simulation mode using historical observations. Some method of correcting for these biases is essential for water resource applications of the forecasts.