Abstract
Abstract. Long lead time flood forecasting is very important for large watershed flood mitigation as it provides more time for flood warning and emergency responses. The latest numerical weather forecast model could provide 1–15-day quantitative precipitation forecasting products in grid format, and by coupling this product with a distributed hydrological model could produce long lead time watershed flood forecasting products. This paper studied the feasibility of coupling the Liuxihe model with the Weather Research and Forecasting quantitative precipitation forecast (WRF QPF) for large watershed flood forecasting in southern China. The QPF of WRF products has three lead times, including 24, 48 and 72 h, with the grid resolution being 20 km × 20 km. The Liuxihe model is set up with freely downloaded terrain property; the model parameters were previously optimized with rain gauge observed precipitation, and re-optimized with the WRF QPF. Results show that the WRF QPF has bias with the rain gauge precipitation, and a post-processing method is proposed to post-process the WRF QPF products, which improves the flood forecasting capability. With model parameter re-optimization, the model's performance improves also. This suggests that the model parameters be optimized with QPF, not the rain gauge precipitation. With the increasing of lead time, the accuracy of the WRF QPF decreases, as does the flood forecasting capability. Flood forecasting products produced by coupling the Liuxihe model with the WRF QPF provide a good reference for large watershed flood warning due to its long lead time and rational results.
Highlights
Watershed flood forecasting is one of the most important non-engineering measures for flood mitigation (Tingsanchali, 2012; Li et al, 2002), and significant progress in watershed flood forecasting has been made in the past decades (Borga et al, 2011; Moreno et al, 2013)
The Weather Research and Forecasting quantitative precipitation forecast (WRF quantitative precipitation forecast (QPF)) has a similar precipitation pattern to that estimated by rain gauges, but overestimates the averaged watershed precipitation, and the longer the Weather Research and Forecasting (WRF) QPF lead time, the higher the precipitation overestimation
The model parameters optimized with rain gauge precipitation and the WRF QPF are different, so different parameter values will result in different model performances
Summary
Watershed flood forecasting is one of the most important non-engineering measures for flood mitigation (Tingsanchali, 2012; Li et al, 2002), and significant progress in watershed flood forecasting has been made in the past decades (Borga et al, 2011; Moreno et al, 2013). The developed numerical weather prediction models in the past decades could provide a longer lead time quantitative precipitation forecast (QPF) product in grid format. The QPF produced by numerical weather prediction model forecasts precipitation in grid format, which provides detailed precipitation distribution information over watersheds. As the distributed hydrological model calculates the hydrological process at grid scale, so the computation time needed for running the distributed hydrological model is huge even for a small watershed This limits the model’s application in watershed flood forecasting, in a large watershed. Flood forecasting products produced by coupling the Liuxihe model with the WRF QPF provide a good reference for large watershed flood warning due to their long lead time and rational results
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