Improving debris flow monitoring in Taiwan by using high-resolution rainfall products from QPESUMS

Debris flow is commonly initiated by torrential rain and its triggering is correlated to the hydrological, geological, and geomorphic conditions on site. In spite of the important effects of geology and topography, rainfall characteristic is the main external triggering factor to debris flow and is a predominant parameter for real-time monitoring. Due to the scarcity of sufficient spatial ground-based rainfall data in hill areas, quantitative precipitation estimation using remote-sensing techniques such as radar and satellite is needed for debris flow pre-warning. The QPESUMS (Quantitative Precipitation Estimation and Segregation Using Multiple Sensors) system was acquired to retrieve spatial rainfall data during the rainfall period from June 30 to July 6 in 2004 when Typhoon Mindulle and southwesterly flow struck Taiwan. The retrieved data were used for setting up the debris flow monitoring algorithm. With the aid of multiple platforms of meteorological observations, a rainfall threshold isohyet in a pilot area was mapped for debris flow monitoring. The rainfall monitoring algorithm based on QPESUMS provides more detailed information than the limited number of ground-based rainfall stations for interpreting the spatial distributions of rainfall events, and therefore is more suitable for debris-flow monitoring.

[1]  N. Caine,et al.  The Rainfall Intensity - Duration Control of Shallow Landslides and Debris Flows , 1980 .

[2]  Witold F. Krajewski,et al.  Evaluating NEXRAD Multisensor Precipitation Estimates for Operational Hydrologic Forecasting , 2000 .

[3]  G. Wieczorek,et al.  Effect of rainfall intensity and duration on debris flows in central Santa Cruz Mountains, California , 1987 .

[4]  Victor Koren,et al.  Comparing Mean Areal Precipitation Estimates from NEXRAD and Rain Gauge Networks , 1999 .

[5]  Cheng-shang Lee,et al.  A Climatology Model for Forecasting Typhoon Rainfall in Taiwan , 2006 .

[6]  George H. Leavesley,et al.  Prediction of a Flash Flood in Complex Terrain. Part II: A Comparison of Flood Discharge Simulations Using Rainfall Input from Radar, a Dynamic Model, and an Automated Algorithmic System , 2000 .

[7]  Chen Chien-Yuan,et al.  Rainfall duration and debris-flow initiated studies for real-time monitoring , 2005 .

[8]  Baxter E. Vieux,et al.  Operational deployment of a physics-based distributed rainfall-runoff model for flood forecasting in Taiwan , 2003 .

[9]  Jan M. H. Hendrickx,et al.  GIS-based NEXRAD Stage III precipitation database: automated approaches for data processing and visualization , 2005, Comput. Geosci..

[10]  P. Frattini,et al.  Soil slips and debris flows on terraced slopes , 2003 .

[11]  W. M. Brown,et al.  Real-Time Landslide Warning During Heavy Rainfall , 1987, Science.

[12]  Preliminary maps showing rainfall thresholds for debris-flow activity, San Francisco Bay region, California , 1997 .