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<br />ACKNOWLEDGEMENTS <br /> <br />not translate into streamflow. Overall, more investigation is needed to validate the estimates from <br />SNODAS or develop quantitative relationships with other data sources. <br /> <br />The monthly water balance analysis was used to identify the major water balance terms in the <br />RIODELCO basin. The results of the water balance analysis indicate four variables may contribute to <br />differences between actual and forecasted seasonal runoff volumes: soil moisture, summer precipitation, <br />snowmelt timing, and sublimation. The SNODAS data products were used successfully to characterize <br />two of these terms (snowmelt timing and sublimation losses). <br /> <br />Based on the results of this project, RTi recommends the following activities for the future: <br /> <br />· Continue processing the SNODAS data and producing weekly data products for the WY 2009 melt <br />season that incorporates both SWE and sublimation information. <br /> <br />· Continue exploring ways to match the forecasted and actual seasonal runoff volumes. Potential work <br />includes: <br /> <br />· Continuing the monthly water balance analysis for WY 2009. The water balance <br />spreadsheet could be developed into a forecasting tool. This would require developing <br />procedures to estimate the water balance terms (e.g., sublimation) into the future. A water <br />balance forecasting tool could be used to evaluate different scenarios based on forecasted <br />precipitation and temperature for the remainder of the season. The scenarios could <br />incorporate information from shorter-term forecasts of temperature and precipitation such <br />as those available from CPC and NOAA-ClRES (NOAA-ClRES 2008) as well as effects <br />from longer-term hydro-climatic indices (HDR Engineering 2007). <br /> <br />· Implementing a hydrologic model that incorporates soil moisture accounting. A hydrologic <br />model would better capture the AET losses and soil moisture changes in the water balance <br />and provide additional forecasting guidance. <br /> <br />· Investigate alternative methods for analyzing and displaying SNODAS data. For example, one <br />suggestion included producing a graph that displays SWE by elevation band for each basin. The <br />graph could also show changes in the snow distribution over time. Attachment 4 contains an example <br />graph provided by Tom Pagano from the NRCS. <br /> <br />· Utilize SNODAS data to support network design. SNODAS SWE and areal extent of snow cover <br />information could be used to identify gaps in existing monitoring networks. <br /> <br />6, Acknowledgements <br /> <br />RTi would like to thank the members of the steering committee for providing guidance and data during <br />the course of the project: <br /> <br />· Joe Busto and Michelle Ganison at the Colorado Water Conservation Board (CWCB) <br /> <br />· Mike Sullivan and Craig Cotten at the Colorado Division of Water Resources <br /> <br />· Tom Pagano, Chris Pacheco, and Mike Gillespie at NRCS <br /> <br />· Rich Stodt at the Bureau of Reclamation <br /> <br />9 <br /> <br />~Riverside Technology, inc. <br />