Multicriteria design of rain gauge networks for flash flood prediction in semiarid catchments with complex terrain

Despite the availability of weather radar data at high spatial (1 km(2)) and temporal (5-15 min) resolution, ground-based rain gauges continue to be necessary for accurate estimation of storm rainfall input to catchments during flash flood events, especially in mountainous catchments. Given economical considerations, a long-standing problem in catchment hydrology is to establish optimal placement of a small number of rain gauges to acquire data on both rainfall depth and spatiotemporal variability of intensity during extreme storm events. Using weather radar observations and a dense network of 40 tipping bucket rain gauges, this study examines whether it is possible to determine a reliable best set of rain gauge locations for the Sabino Canyon catchment near Tucson, Arizona, USA, given its complex topography and dominant storm track pattern. High-quality rainfall data are used to evaluate all possible configurations of a practical network having from one to four rain gauges. A multicriteria design strategy is used to guide rain gauge placement, by simultaneously minimizing the residual percent bias and maximizing the coefficient of correlation between the estimated and true mean areal rainfall and minimizing the normalized spatial mean squared error between the estimated and true spatiotemporal rainfall distribution. The performance of the optimized rain gauge network was then compared against randomly designed network ensembles by evaluating the quality of streamflows predicted using the Kinematic Runoff and Erosion (KINEROS2) event-based rainfall-runoff model. Our results indicate that the multicriteria strategy provided a robust design by which a sparse but accurate network of rain gauges could be implemented for semiarid basins such as the one studied.