China
Africa
Explore chapters and articles related to this topic
2
Published in Eric W. Harmsen, Megh R. Goyal, Flood Assessment, 2017
Short-term rainfall forecasts have commonly been made using Quantitative Precipitation Forecasting (QPF). The introduction of QPF in flood warning systems has been recognized to play a fundamental role. QPF is not an easy task, with rainfall being one of the most difficult elements of the hydrological cycle to forecast [24], and great uncertainties still affect the performances of stochastic and deterministic rainfall prediction models [86]. Currently, this capability does not exist in western Puerto Rico, and it is needed because of the potential for flooding in certain areas (e.g., in flood plains near the principal rivers of the region).
Improving operational flood forecasting in monsoon climates with bias-corrected quantitative forecasting of precipitation
Published in International Journal of River Basin Management, 2019
Md Safat Sikder, Faisal Hossain
For flood-prone countries, precipitation forecasting is the most critical factor for improving the skill of flood forecasting for such large river basins dominated by the monsoon (Coe 2000). Forecasting of precipitation is needed to increase the lead time of a flood forecast beyond the time of concentration of the river basin. Hereafter, we shall use flood forecast with flow forecast to imply the same physical phenomenon. If we assume that nowcast estimated precipitation (such as satellite multi-sensor precipitation products) provides the most reliable source of precipitation for large river basins, the lead time will remain limited to the hydrologic time of concentration of flow. Thus, one of the most common practices for increasing the flood forecasting lead time beyond the time of concentration is to use Numerical Weather Prediction (NWP) models (Cloke and Pappenberger 2009, Nam et al. 2014, Yucel et al. 2015). NWP models can quantitatively forecast precipitation and their use are becoming widespread among operational flood agencies as data on meteorological forcings and computational resources are more widely available (e.g. Jasper et al. 2002, Liguori et al. 2012, Liu et al. 2015). In this study, NWP forecast precipitation is considered synonymous with Quantitative Precipitation Forecast (QPF).
A Brief review of flood forecasting techniques and their applications
Published in International Journal of River Basin Management, 2018
Sharad Kumar Jain, Pankaj Mani, Sanjay K. Jain, Pavithra Prakash, Vijay P. Singh, Desiree Tullos, Sanjay Kumar, S. P. Agarwal, A. P. Dimri
The critical meteorological input in FF is observed and/or forecasted precipitation (Krzysztofowicz 1999, Marty et al. 2013). Forecasted precipitation is typically derived from quantitative precipitation forecasts (QPF) by numerical weather prediction (NWP). The grid size of NWP can be a major source of error in rainfall forecast, which is further aggravated by the positional error of these grids. Even observed precipitation can have significant uncertainties. Rain gauges sample a very small area and there can be large gaps between them, which can translate into large precipitation errors, particularly in mountainous areas (Stanton et al. 2016). Weather radars can sample large areas but do not directly measure rainfall and there are issues with conversion from reflectivity to rainfall (Catchlove et al. 2005). Flood producing storm events typically occur at highly localized scales (<10 km²) and may not be captured by gridded remotely sensed products, such as TRMM (Stanton et al. 2016).