[1] Semiarid flash floods pose a significant danger for life and property in many dry regions around the world. One effective way to mitigate flood risk lies in implementing a real-time forecast and warning system based on a rainfall-runoff model. This study used a semiarid, physics-based, and spatially distributed watershed model driven by highresolution radar rainfall input to evaluate such a system. The predictive utility of the model and dominant sources of uncertainty were investigated for several runoff events within the U.S. Department of Agriculture Agricultural Research Service Walnut Gulch Experimental Watershed located in the southwestern United States. Sources of uncertainty considered were rainfall estimates, watershed model parameters, and initial soil moisture conditions. Results derived through a variance-based comprehensive global sensitivity analysis indicated that the high predictive uncertainty in the modeled response was heavily dominated by biases in the radar rainfall depth estimates. Key model parameters and initial model states were identified, and we generally found that modeled hillslope characteristics are more influential than channel characteristics in small semiarid basins. We also observed an inconsistency in the parameter sets identified as behavioral for different events, which suggests that model calibration to historical data is unlikely to consistently improve predictive performance for different events and that real-time parameter updating may be preferable.

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An extensive precipitation database at the ∼149 km2 Walnut Gulch Experimental Watershed (WGEW) has been developed over the past 53 years with the first records starting in August 1953 and continuing to the present. The WGEW is a tributary of the San Pedro River, is located in southeastern Arizona, and surrounds the town of Tombstone. Average annual precipitation for the period of 1956–2005, as measured with six gauges, is roughly 312 mm, with approximately 60% falling during the summer monsoon. From a historical high of 95 rain gauges, a current network of 88 gauges is operational. This constitutes one of the densest rain gauge networks in the world (∼0.6 gauges/km2) for watersheds greater than 10 km2. Through 1999, the network consisted of analog recording weighing rain gauges. In 2000, a newly designed digital gauge with telemetry was placed adjacent (∼1 m) to the analog gauges. Both the analog and digital networks of gauges were in operation from 2000 to 2005 to enable a comparative analysis of the two systems. The analog data were digitized from paper charts and were stored in breakpoint format. The digital data consist of rainfall depths at 1‐min intervals during periods of rainfall. All these data can be obtained in a variety of formats and were accumulated over various time intervals (daily, monthly, and annual) via a web interface at http://www.tucson.ars.ag.gov/dap/.

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A variety of aircraft remotely sensed and conventional ground-based measurements of volumetric soil water content (SW) were made over two subwatersheds (4.4 and 631 ha) of the U.S. Department of Agriculture's Agricultural Research Service Walnut Gulch experimental watershed during the 1990 monsoon season. Spatially distributed soil water contents estimated remotely from the NASA push broom microwave radiometer (PBMR), an Institute of Radioengineering and Electronics (IRE) multifrequency radiometer, and three ground-based point methods were used to define prestorm initial SW for a distributed rainfall-runoff model (KINEROS; Woolhiser et al., 1990)•at a small catchment scale (4.4 ha). At a medium catchment scale (631 ha or 6.31 km •) spatially distributed PBMR SW data were aggregated via stream order reduction. The impacts of the various spatial averages of SW on runoff simulations are discussed and are compared to runoff simulations using $W estimates derived from a simple daily water balance model. It was found that at the small catchment scale the SW data obtained from any of the measurement methods could be used to obtain reasonable runoff predictions. At the medium catchment scale, a basin-wide remotely sensed average of initial water content was sufficient for runoff simulations. This has important implications for the possible use of satellite-based microwave soil moisture data to define prestorm SW because the low spatial resolutions of such sensors may not seriously impact runoff simulations under the conditions examined. However, at both the small and medium basin scale, adequate resources must be devoted to proper definition of the input rainfall to achieve reasonable runoff simulations. 1. Introduction Passive microwave soil moisture research has focused on the basic questions involved in the data interpretation algorithm [Jackson and Schmugge, 1989]. There have been a number of efforts to develop water balance models that utilize these surface observations [Jackson, 1986; Prevot et al., 1984]; however, these have only considered a single profile and have not considered surface runoff dynamics. Engrnan and Gurney [1991] recently summarized some common viewpoints concerning remotely sensed soil moisture observations and hydrologic modeling. The general conclusion was that in order to fully utilize the information that frequent spatially distributed soil moisture observations might provide, we must reevaluate the hydrologic models themselves. The soil component of many existing models is constructed in such a way to make the model work even though soil moisture has never been available as an input variable. This element of the hydrologic cycle has thus Gurney [1991] noted, actual observations of soil moisture may offer no improvement in runoff estimation because these models do not properly incorporate this variable. This was observed by Jackson et al. [1981] in a study involving a continuous runoff simulation model. In that study they examined how repetitive surface soil moisture observations could be us...

[1] Spatial and temporal rainfall variability over watersheds directly impacts the hydrologic response over virtually all watershed scales. Changes in the precipitation regime over decades due to some combination of inherent local variability and climate change may contribute to changes in vegetation, water supply, and, over longer timescales, landscape evolution. Daily, seasonal, and annual precipitation volumes and intensities from the dense network of rain gauges on the Agricultural Research Service, U. S. Department of Agriculture Walnut Gulch Experimental Watershed (WGEW) in southeast Arizona are evaluated for multidecadal trends in amount and intensity over a range of watershed scales (1.5 ha to 149 km 2 ) using observations from 1956 to 2006. Rainfall and runoff volume and rate variability are compared over the same spatial scales over a 40 year period . The major findings of this study are that spatial variability of cumulative precipitation decreases exponentially with time, and, on average, became spatially uniform after 20 years of precipitation accumulation. The spatial variability of high-intensity, runoff-producing precipitation also decreased exponentially, but the variability was still well above the measurement error after 51 years. There were no significant temporal trends in basin scale precipitation. A long-term decrease in runoff from 1966 to 1998 from ephemeral tributaries like the WGEW may be a critical factor in decreasing summer flows in the larger San Pedro due to changes in higher-intensity, runoff-producing rainfall.

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