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Featured researches published by Mike Schaffner.


Water Resources Research | 2008

Understanding uncertainty in distributed flash flood forecasting for semiarid regions

Soni Yatheendradas; Thorsten Wagener; Hoshin V. Gupta; Carl L. Unkrich; David C. Goodrich; Mike Schaffner; Anne Stewart

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 high-resolution 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.


Eos, Transactions American Geophysical Union | 2007

Impact of recent extreme Arizona storms

Christopher S. Magirl; Robert H. Webb; Peter G. Griffiths; Mike Schaffner; Craig Shoemaker; Eric Pytlak; Soni Yatheendradas; Steve W. Lyon; Peter Troch; Sharon L. E. Desilets; D. C. Goodrich; Carl L. Unkrich; Ann Youberg; Phil A. Pearthree

Heavy rainfall on 27–31 July 2006 led to record flooding and triggered an historically unprecedented number of debris flows in the Santa Catalina Mountains north of Tucson, Ariz. The U.S. Geological Survey (USGS) documented record floods along four watercourses in the Tucson basin, and at least 250 hillslope failures spawned damaging debris flows in an area where less than 10 small debris flows had been documented in the past 25 years. At least 18 debris flows destroyed infrastructure in the heavily used Sabino Canyon Recreation Area (http://wwwpaztcn.wr.usgs.gov/rsch_highlight/articles/20061 l.html). In four adjacent canyons, debris flows reached the heads of alluvial fans at the boundary of the Tucson metropolitan area. While landuse planners in southeastern Arizona evaluate the potential threat of this previously little recognized hazard to residents along the mountain front, an interdisciplinary group of scientists has collaborated to better understand this extreme event.


Bulletin of the American Meteorological Society | 2014

AN ALL-SEASON FLASH FLOOD FORECASTING SYSTEM FOR REAL-TIME OPERATIONS

Patrick D. Broxton; Peter Troch; Mike Schaffner; Carl L. Unkrich; David C. Goodrich

Flash floods can cause extensive damage to both life and property, especially because they are difficult to predict. Flash flood prediction requires high-resolution meteorological observations and predictions, as well as calibrated hydrological models, which should effectively simulate how a catchment filters rainfall inputs into streamflow. Furthermore, because of the requirement of both hydrological and meteorological components in flash flood forecasting systems, there must be extensive data handling capabilities built in to force the hydrological model with a variety of available hydrometeorological data and predictions, as well as to test the model with hydrological observations. The authors have developed a working prototype of such a system, called KINEROS/hsB-SM, after the hydrological models that are used: the Kinematic Erosion and Runoff (KINEROS) and hillslope-storage Boussinesq Soil Moisture (hsB-SM) models. KINEROS is an event-based overland flow and channel routing model that is designed to ...


Archive | 2010

Application of the KINEROS2 site specific model to south-central NY and northeast PA : forecasting gaged and ungaged fast responding watersheds

Mike Schaffner; Carl L. Unkrich; David C. Goodrich


Water Resources Research | 2008

Understanding uncertainty in distributed flash flood forecasting for semiarid regions: SEMIARID FLASH FLOODS

Soni Yatheendradas; Thorsten Wagener; Hoshin V. Gupta; Carl L. Unkrich; David C. Goodrich; Mike Schaffner; Anne Stewart


IAHS-AISH publication | 2007

Understanding sources of uncertainty in flash- flood forecasting for semi-arid regions

Thorsten Wagener; Hoshin V. Gupta; Soni Yatheendradas; David C. Goodrich; Carl L. Unkrich; Mike Schaffner


Open-File Report | 2007

Debris Flows and Record Floods from Extreme Mesoscale Convective Thunderstorms over the Santa Catalina Mountains, Arizona

Christopher S. Magirl; Craig Shoemaker; Robert H. Webb; Mike Schaffner; Peter G. Griffiths; Erik Pytlak


Archive | 2009

Improving Flash Flood Prediction in Multiple Environments

Patrick D. Broxton; Peter Troch; Mike Schaffner; Carl L. Unkrich; D. C. Goodrich; Thorsten Wagener; Soni Yatheendradas


Archive | 2008

Combining radar and rain gauges to capture the space-time variability of monsoon rainfall during an extreme flood event

Steve Lyon; Till H. M. Volkmann; P Hazenberg; Soni Yatheendradas; Mike Schaffner; Erik Pytlak; Carl L. Unkrich; D. C. Goodrich; Peter Troch


Archive | 2007

Forecast uncertainty in semi-arid flash flood modeling using radar rain input

Carl L. Unkrich; Soni Yatheendradas; Hoshin V. Gupta; Thorsten Wagener; D. C. Goodrich; Mike Schaffner; Ann Stewart

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Carl L. Unkrich

United States Department of Agriculture

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Soni Yatheendradas

Goddard Space Flight Center

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D. C. Goodrich

United States Department of Agriculture

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David C. Goodrich

Agricultural Research Service

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Christopher S. Magirl

United States Geological Survey

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Erik Pytlak

National Oceanic and Atmospheric Administration

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