资源环境科技发展态势分析平台

Given the continuous advancement in the retrieval of precipitation from satellites, it is important to develop methods that incorporate satellite-based precipitation data sets in the design and planning of infrastructure. This is because in many regions around the world, in situ rainfall observations are sparse and have insufficient record length. A handful of studies examined the use of satellite-based precipitation to develop intensity-duration-frequency (IDF) curves; however, they have mostly focused on small spatial domains and relied on combining satellite-based with ground-based precipitation data sets. In this study, we explore this issue by providing a methodological framework with the potential to be applied in ungauged regions. This framework is based on accounting for the characteristics of satellite-based precipitation products, namely, adjustment of bias and transformation of areal to point rainfall. The latter method is based on previous studies on the reverse transformation (point to areal) commonly used to obtain catchment-scale IDF curves. The paper proceeds by applying this framework to develop IDF curves over the contiguous United States (CONUS); the data set used is Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks - Climate Data Record (PERSIANN-CDR). IDFs are then evaluated against National Oceanic and Atmospheric Administration (NOAA) Atlas 14 to provide a quantitative estimate of their accuracy. Results show that median errors are in the range of (17-22%), (6-12%), and (3-8%) for one-day, two-day and three-day IDFs, respectively, and return periods in the range (2-100) years. Furthermore, a considerable percentage of satellite-based IDFs lie within the confidence interval of NOAA Atlas 14.

Plain Language Summary Intensity-duration-frequency (IDF) curves are used for the design of infrastructure. At any specific location, the rainfall intensity can be obtained for a given duration and frequency of occurrence (known as return period). Development of IDF curves is based on probabilistic analysis of past records of extreme rainfall. However, in many regions around the world, particularly in developing countries, such records are not available either due to limited spatial coverage of ground rainfall gauges, short record length, or poor data quality. Satellite-based precipitation is an alternative source that can be utilized to develop IDF curves since it has near global coverage and high spatiotemporal resolution. In this paper, we explore the use of satellite-based precipitation products in developing IDF curves by providing a framework that accounts for the characteristics of satellite-based precipitation. Furthermore, we develop IDF curves for the contiguous United States (CONUS) and evaluate them using National Oceanic and Atmospheric Administration (NOAA) Atlas 14 as a benchmark. The results demonstrate that IDFs derived from satellite-based precipitation are of good accuracy. The methods used in this study have the potential to be extended and applied in other regions in the absence of in situ rainfall observations.