In the context of GCIP one of the eventual aims of the modeling effort is to generate inputs for operational hydrological and water resources management models over a range of time scales up to interannual. The specific GCIP objective for this area is to improve the utility of hydrologic predictions for water resources management up to seasonal and interannual time scales. The approach will be to link with GCIP coupled modeling and data collection activities, to produce more accurate streamflow forecasts, and in turn, to develop methods of utilizing those forecasts for water management purposes. The lead times to be emphasized will be longer than the currently accepted upper limit of weather forecasts, which is currently about one week, and up to interannual.

6.1 Water Resource Applications in the LSA-NW

The Missouri River basin provides an interesting variety of hydrometeorological prediction and water management challenges for the research community. These range from the analysis and prediction of snowpack in the headwaters along the Continental Divide in the high elevations of the Rocky Mountains to the High Plains runoff from glacial till and rich fertile soils of the lower basin. Mesoclimates of the Prairie Pothole Region of the Dakotas present challenges for surface runoff and simulation of local ponds and wetland surface energy balance feedbacks that impact regional-scale prediction models. Highly regulated flows in the Missouri River basin provide an opportunity to demonstrate the value of enhanced hydrometeorological forecasting for water resource management from Montana to Missouri, by the USGS Bureau of Reclamation and the Army Corps of Engineers. Close partnerships with these end users and GCIP researchers will enable the program to demonstrate practical applications with immediate benefit to stakeholders.

Present operational systems in the Bureau of Reclamation use the NOAA- Missouri Basin River Forecast Center (MBRFC) forecasts for their daily and monthly operational planning and decision-making. Forecasts of streamflow at key points on the Madison, Jefferson, Milk and mainstem Missouri Rivers above Bureau of Reclamation facilities are used in operational decisions. Close coordination with the Natural Resource Conservation Service and the Army Corps of Engineers and the MBRFC and the Bureau of Reclamation's operations teams leads to a consensus decision on many forecasts. Enhancement of the current system that applies research tools and knowledge developed through the GCIP program will require close coordination among these agencies.

6.2 Scientific Objective and LSA-NW Research Activities

The overall scientific objective for research applications in hydrometeorological prediction and water resources is to enhance the reliability of precipitation, streamflow and related hydrologic variables that impact the water supply and demand forecasts for water managers in temporal scales up to seasonal. Research to support improved use of short-range to seasonal and interannual predictions for the LSA-NW can be organized into three main research activities:
(i) Improved application of coupled model outputs and other forecast products. This would include studies to use a wide range of forecast products as input to hydrologic forecast models as well as related demonstration projects with water resources applications agencies.

(ii) Improved hydrologic forecast models. This would include studies to evaluate present forecast models and to transfer what has been done to develop improved land surface parameterizations for atmospheric models for use in river forecasting.

(iii) Improved representation of precipitation in complex terrain. One of the main limitations in using both forecasts and precipitation observations as input to hydrologic models in the LSA-NW is that area average estimates over complex terrain are generally not very accurate, especially for short computational time steps.

6.2.1 Improved Application of Coupled Model and Other Forecast Products.

Applications of coupled model outputs as inputs to hydrologic prediction models are needed. There are two major activity areas. One is make better use of forecast products to create inputs required by hydrologic models. The other is to use the hydrologic model outputs to make water resources decisions. Opportunities include applications to water supply forecasts, groundwater interaction from surface to aquifers for balanced, transfer coupled model outputs to stream flow forecasts floods and longer term forecasts. Some of the specific research topics include use of: The applied research will require education of the end-users regarding the capabilities and limitations of products to establish credibility. This effort requires formatting of products such that end-users can readily use the forecasts in their operational tools and models.

To demonstrate reliability to end-users and the academic community, relative feasibility of retrospective runs and archival of runs should be examined. Before operational entities can rely on new techniques and models, they must be convinced that these are reliable and are an improvement over existing methods.

The application of coupled model outputs as inputs to hydrologic prediction models includes the operational applications to water supply forecasts and groundwater interaction from surface to aquifers for balanced water conservation measures.

Several basic questions need review and prioritization:

How good are the forecasts and how can we improve them?
How can we improve research model efficiency to make us more effective?
How can four dimensional data assimilation and explicit physical process models be integrated into the hydrologic runoff modeling to improve upon traditional regression analysis methods for rainfall runoff and streamflow analysis and forecasts?

6.2.2 Improved Hydrologic Forecast Models.

Improvements of hydrologic prediction systems using coupled model inputs should be made that include: Evaluation of existing forecast systems - How good are the forecasts and how can we improve them? A comprehensive analysis of forecast uncertainty due to: observations, model physics, and hydrometeorological forecast variables is needed. Potential sources of significant improvements are: improved estimation of initial conditions, improved model components - vegetation, energy, frozen ground, ground water dynamics, improved calibration and estimation, enhanced forecast operations efficiency. These operations efficiency efforts include: diagnostic studies, model bias compensation, applied 4DDA, comparison of physical vs. regression models and other tests of the operational efficiency and accuracy of the forecast system.

A new research focus for the LSA-NW is in ground water and soil moisture's role in predictability of water supplies and coupling to atmospheric models. This has a bearing on climate and long term forecast issues. In the LSA-NW groundwater is an important water source for both domestic and agricultural usage. The ability to manage groundwater resources requires an understanding of recharge characteristics. It becomes important to identify recharge zones and associated recharge rates. Processes defining recharge rates are fundamental to groundwater/surface water interactions. The representation of these interactions needs to be improved in surface hydrologic/parameterization components of coupled models.

There are generally two pathways for recharge: (1) direct streamflow losses to aquifer outcrop zones, and (2) recharge over broad land surface areas. Direct streamflow losses must be considered in the context of routing schemes in surface hydrology. Groundwater recharge over broad land surfaces must be considered in the context of soil moisture balance process in surface hydrology/parameterization models. The movement of water through the soil zone complex to a zone of recharge affects the availability of moisture for ET. Thus, recharge processes can have an effect on moisture and energy fluxes between the land surface and atmosphere.

6.2.3 Precipitation Analysis in Complex Terrain

Analysis of precipitation and accumulated snow in complex terrain is needed to: derive accurate water budgets from limited in-situ and remote sensed data, and downscale atmospheric model precipitation to appropriate basin scale precipitation using physical and statistical methods.

In complex terrain the basic precipitation measurements at individual gage sites are subject to similar, but often more difficult, siting and exposure considerations than in flat terrain. In addition, inference of areal precipitation amounts from those point measurements requires accounting for generally greater small-scale variability as well as systematic influences such as elevation or orientation with respect to ambient wind flow. In complex terrain a significant component of the small-scale variability may be anchored to specific topographic features and thus less susceptible to smoothing over time than is usually the case in flat terrain. Radar observations can contribute to improving the analysis of precipitation by revealing systematic patterns in the small-scale variability and in relation to the topography. Model simulations can also provide indications of terrain-related variability and in relation to the topography. Model simulations can also provide indications of terrain-related features in the precipitation patterns and indicate how they vary with wind direction and speed. A synthesis of radar observations and model results, indicating such systematic features of the precipitation patterns, with the relatively sparse gage observations in the LSA-NW (which may be subject to less uncertainty regarding quantitative values), should give a more accurate analysis of precipitation in the complex terrain.

We need to recognize the dominant role that mountain orographic precipitation plays in water supplies of the headwaters of the Missouri Basin. GCIP research plans for the LSA-NW need to include the following areas:

(a). Derive accurate water budgets from limited in-situ and remotely sensed data

(b) Simulate local orographic effects using mesoscale models with high resolution of about one km to accurately depict local 3-dimensional flows and cloud and precipitation responses.

(c) Downscale atmospheric model precipitation to appropriate basin scale precipitation using physical and statistical methods

(d) Validation of the modeling, downscaling, and physical process models

(e) More applied research in the analysis of precipitation in complex terrain is needed that includes: observational in-situ and remotely sensed data and validation of models that use these data for initial conditions.

6.3 Implementation Strategy

The main issue here is that we need to have parallel research and operational paths as part of the strategy. The approach for a research path is relatively clear. An approach for an operational path linked to the research path is much less clear. But, a key point is that the operational entities are in the best position to judge if useful research has been done. Also, the researchers need to demonstrate that they have actually made improvements relative to current operational capabilities. This also requires an operational path to provide the information to make such comparisons possible. It is planned to form a taskgroup to work with forecasting researchers and providers OH/OM/RFC/WFO and the end-users (Reclamation, USACE?) to help expedite transfer of technology. The operational users should include the water operations managers, who are responsible for daily and monthly operating decisions with assistance from research teams in the operating agencies.