TY - JOUR
T1 - Utility of Quantitative Precipitation Estimates for high resolution hydrologic forecasts in mountain watersheds of the Colorado Front Range
AU - Moreno, Hernan A.
AU - Vivoni, Enrique
AU - Gochis, David J.
N1 - Funding Information:
This research was supported by the National Weather Service Office of Hydrologic Development (Grant NWS-NWSPO-2007-2000799). D.J.G. also receives support from the National Science Foundation through its support of the National Center for Atmospheric Research. We thank the following providers of data products: AmeriFLUX and Mesowest networks, Colorado Division of Water Resources, NOAA Center for Satellite Applications and Research, and the Center for Hydrometeorology and Remote Sensing at University of California, Irvine. We particularly appreciate the comments of Pedro Restrepo (National Weather Service) on earlier versions of the manuscript. Two reviewers provided excellent comments that helped improve the manuscript.
PY - 2012/5/17
Y1 - 2012/5/17
N2 - Quantitative Precipitation Estimates (QPEs) can serve as input to distributed hydrologic models to issue flood and flash flood forecasts in mountain watersheds. Improvements in flood predictions are expected as the quality of radar, multisensor and satellite observations improves. In this study, we assess the value of ten different high resolution QPEs (hourly, 4-km) in four study basins of the Colorado Front Range using a calibrated distributed hydrologic model as a verification tool. To evaluate QPE skill, we compared the precipitation properties at the site (i.e., rain gauge location), basin-average and regional scales and evaluated their influence on the simulated basin response, including the outlet discharge, runoff mechanisms and seasonal water balance. We also analyzed the value of gridded QPEs with respect to uniform forcing derived from rain gauges. Results reveal that radar and multisensor QPEs lead to improved hydrologic model performance compared to simulations driven with rain gauge data only with respect to the observed streamflow. Satellite QPEs exhibit lower overall streamflow simulation skill compared with estimates derived from radar-based QPEs, but are preferable to assuming uniform forcing from nearby rain gauges in the mountain settings studied here. However, satellite QPEs preserve the fundamental properties of the basin response, including a simple scaling relation between the relative spatial variability of runoff and its magnitude. As a result, satellite QPE products open new avenues for forecasting in regions with limited access and sparse observations.
AB - Quantitative Precipitation Estimates (QPEs) can serve as input to distributed hydrologic models to issue flood and flash flood forecasts in mountain watersheds. Improvements in flood predictions are expected as the quality of radar, multisensor and satellite observations improves. In this study, we assess the value of ten different high resolution QPEs (hourly, 4-km) in four study basins of the Colorado Front Range using a calibrated distributed hydrologic model as a verification tool. To evaluate QPE skill, we compared the precipitation properties at the site (i.e., rain gauge location), basin-average and regional scales and evaluated their influence on the simulated basin response, including the outlet discharge, runoff mechanisms and seasonal water balance. We also analyzed the value of gridded QPEs with respect to uniform forcing derived from rain gauges. Results reveal that radar and multisensor QPEs lead to improved hydrologic model performance compared to simulations driven with rain gauge data only with respect to the observed streamflow. Satellite QPEs exhibit lower overall streamflow simulation skill compared with estimates derived from radar-based QPEs, but are preferable to assuming uniform forcing from nearby rain gauges in the mountain settings studied here. However, satellite QPEs preserve the fundamental properties of the basin response, including a simple scaling relation between the relative spatial variability of runoff and its magnitude. As a result, satellite QPE products open new avenues for forecasting in regions with limited access and sparse observations.
KW - Convective precipitation
KW - Distributed hydrologic model
KW - Flood forecasting
KW - Remote sensing
KW - Satellite rainfall
KW - Watershed hydrology
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U2 - 10.1016/j.jhydrol.2012.03.019
DO - 10.1016/j.jhydrol.2012.03.019
M3 - Article
AN - SCOPUS:84860388353
SN - 0022-1694
VL - 438-439
SP - 66
EP - 83
JO - Journal of Hydrology
JF - Journal of Hydrology
ER -