Remote collection and analysis of witness reports on flash floods J.J. Gourley a, * , J.M. Erlingis a,b , T.M. Smith a,b , K.L. Ortega a,b , Y. Hong c a NOAA/National Severe Storms Laboratory, Norman, OK 73072, USA b Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, OK 73072, USA c Department of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73072, USA article info Keywords: Flash flood Database Survey Google Earth™ summary Typically, flash floods are studied ex post facto in response to a major impact event. A complement to field investigations is developing a detailed database of flash flood events, including minor events and null reports (i.e., where heavy rain occurred but there was no flash flooding), based on public survey questions conducted in near-real time. The Severe hazards analysis and verification experiment (SHAVE) has been in operation at the National Severe Storms Laboratory (NSSL) in Norman, OK, USA during the summers since 2006. The experiment employs undergraduate students to analyse real-time products from weather radars, target specific regions within the conterminous US, and poll public residences and businesses regarding the occurrence and severity of hail, wind, tornadoes, and now flash floods. In addition to providing a rich learning experience for students, SHAVE has also been successful in creating high-resolution datasets of severe hazards used for algorithm and model verification. This paper describes the criteria used to initiate the flash flood survey, the specific questions asked and information entered to the database, and then provides an analysis of results for flash flood data collected during the summer of 2008. It is envisioned that specific details provided by the SHAVE flash flood observation data- base will complement databases collected by operational agencies (i.e., US National Weather Service Storm Data reports) and thus lead to better tools to predict the likelihood of flash floods and ultimately reduce their impacts on society. Published by Elsevier B.V. 1. Introduction Societal impacts from flash flooding can be mitigated through the development of better tools to identify regions being impacted or about to be impacted by flash floods (Ruin et al., 2008). These prognostic indicators require detailed observations of basin char- acteristics, antecedent states of the soils, streams, and atmosphere, accurate estimates of rainfall, and an adequate understanding and accompanying model of the rainfall–runoff processes associated with flash floods. Given the uncertainty inherent in the observa- tions and an incomplete understanding of the underling physics, it is standard practice to train or calibrate the modelling system (Beven and Binley, 1992; Gupta et al., 1998; Vrugt et al., 2005) to recognise and alert on extreme events; i.e., those that differ signif- icantly from the historical distribution. A quantification of the dis- tribution of stream discharge magnitudes in upland basins susceptible to flash flooding requires an appropriate observational database. Current observational datasets include measurements from in situ stream gauges and acoustic Doppler profilers (Simpson and Oltmann, 1993), remotely sensed surface water extents from space–borne platforms (see Brakenridge et al. (2005) for a sum- mary), spotter reports collected by operational agencies such as the US National Weather Service (NWS), ex post facto field investi- gations (Gaume and Borga, 2008; Marchi et al., 2009), and indirect inferences from hourly precipitation datasets (Brooks and Stensrud, 2000). The level of detail provided by each of these data- sets, even when combined, is insufficient to accurately portray the frequency, magnitude, and spatial patterns of flash floods (Gruntfest, 2009). Observational flash flood databases are incom- mensurate with their societal impacts; they are a significant natu- ral hazard impacting many global societies, yet they remain poorly observed (Gaume et al., 2009). This paper introduces a survey-based data collection methodol- ogy for studying the impacts and characteristics of flash floods. It is organized as follows. Section 2 summarizes the current state of flash flood observations. Section 3 describes the history, motiva- tion, and basic design of SHAVE. Section 4 discusses the SHAVE data collection effort for flash flooding. Section 5 compares the SHAVE dataset to the NWS operational Storm Data flash flood reports in regards to their spatial characteristics, population 0022-1694/$ - see front matter Published by Elsevier B.V. doi:10.1016/j.jhydrol.2010.05.042 * Corresponding author. Address: National Weather Center, 120 David L. Boren Blvd, Norman, OK 73072, USA. Tel.: +1 405 325 6472; fax: +1 405 325 6780. E-mail address: jj.gourley@noaa.gov (J.J. Gourley). Journal of Hydrology 394 (2010) 53–62 Contents lists available at ScienceDirect Journal of Hydrology journal homepage: www.elsevier.com/locate/jhydrol