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Utilizing Long-Term ARS Data to Compare and Contrast Hydroclimatic Trends from Snow and Rainfall Dominated Watersheds
- Goodrich, D. C., Marks, D., Seyfried, M. S., Keffer, T. O., Unkrich, C. L., Anson, E. A., Clark, P. E., Flerchinger, G. N., Hamerlynck, E. P., Hardegree, S. P.
- Proceedings of the Fourth Interagency Conference on Research in the Watersheds 2011 pp. 34-39
- Agricultural Research Service, air temperature, databases, instrumentation, monsoon season, rain, runoff, snow, snowmelt, storms, stream flow, subwatersheds, summer, temporal variation, water supply, watershed hydrology, Arizona, Idaho
- The U.S. Department of Agriculture–Agricultural Research Service, Northwest and Southwest Watershed Research Centers have operated the Reynolds Creek Experimental Watershed (RCEW) in southwestern Idaho and the Walnut Gulch Experimental Watershed (WGEW) in southern Arizona since the 1950s. Each watershed is densely instrumented with a variety of hydrometeorological instrumentation and has multiple gauged subwatersheds spanning a range of spatial scales. These watersheds have yielded an extensive knowledge base of watershed processes over multiple decades of use as outdoor hydrologic laboratories. Both research centers have published data reports in Water Resources Research describing the RCEW and WGEW and their associated characteristics and observational databases. Precipitation and runoff generation in RCEW is dominated by snow and snowmelt processes, while WGEW is dominated by thunderstorm-generated rainfall during the summer monsoon. Mean annual temperatures in the continental United States have increased from 1 to 3°C since the establishment of these experimental watersheds and this change has affected water supply, hydrology, and watershed response at both locations. This study compared and contrasted hydroclimatic variables at these experimental watersheds, including temperature, precipitation, and streamflow. Monthly, seasonal, and annual data of temperature, precipitation and runoff were tested for significant trends in these variables.