Developing Intensity-Duration-Frequency (IDF) Curves From Satellite-Based Precipitation: Methodology and Evaluation

被引:78
作者
Ombadi, Mohammed [1 ]
Phu Nguyen [1 ,2 ]
Sorooshian, Soroosh [1 ]
Hsu, Kuo-lin [1 ,3 ]
机构
[1] Univ Calif Irvine, Ctr Hydrometeorol & Remote Sensing, Dept Civil & Environm Engn, Irvine, CA 92697 USA
[2] Nong Lam Univ, Dept Water Management, Ho Chi Minh City, Vietnam
[3] Natl Taiwan Ocean Univ, Ctr Excellence Ocean Engn, Keelung, Taiwan
基金
美国国家科学基金会;
关键词
PROBABILITY WEIGHTED MOMENTS; POINT RAINFALL; RADAR; TRANSFORMATION; PARAMETERS; TIME;
D O I
10.1029/2018WR022929
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页码:7752 / 7766
页数:15
相关论文
共 55 条
[31]   A mathematical framework for studying rainfall intensity-duration-frequency relationships [J].
Koutsoyiannis, D ;
Kozonis, D ;
Manetas, A .
JOURNAL OF HYDROLOGY, 1998, 206 (1-2) :118-135
[32]   PROBABILITY WEIGHTED MOMENTS COMPARED WITH SOME TRADITIONAL TECHNIQUES IN ESTIMATING GUMBEL PARAMETERS AND QUANTILES [J].
LANDWEHR, JM ;
MATALAS, NC ;
WALLIS, JR .
WATER RESOURCES RESEARCH, 1979, 15 (05) :1055-1064
[33]   Intensity-duration-frequency curves from remote sensing rainfall estimates: comparing satellite and weather radar over the eastern Mediterranean [J].
Marra, Francesco ;
Morin, Efrat ;
Peleg, Nadav ;
Mei, Yiwen ;
Anagnostou, Emmanouil N. .
HYDROLOGY AND EARTH SYSTEM SCIENCES, 2017, 21 (05) :2389-2404
[34]   Use of radar QPE for the derivation of Intensity-Duration-Frequency curves in a range of climatic regimes [J].
Marra, Francesco ;
Morin, Efrat .
JOURNAL OF HYDROLOGY, 2015, 531 :427-440
[35]  
Martin D., 2013, NOAA ATLAS 14, V8
[36]   THE KOLMOGOROV-SMIRNOV TEST FOR GOODNESS OF FIT [J].
MASSEY, FJ .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1951, 46 (253) :68-78
[37]  
Matern B., 1986, SPATIAL VARIATION
[38]   Capabilities of satellite precipitation datasets to estimate heavy precipitation rates at different temporal accumulations [J].
Mehran, Ali ;
AghaKouchak, Amir .
HYDROLOGICAL PROCESSES, 2014, 28 (04) :2262-2270
[39]   Evaluation of the PERSIANN-CDR Daily Rainfall Estimates in Capturing the Behavior of Extreme Precipitation Events over China [J].
Miao, Chiyuan ;
Ashouri, Hamed ;
Hsu, Kuo-Lin ;
Sorooshian, Soroosh ;
Duan, Qingyun .
JOURNAL OF HYDROMETEOROLOGY, 2015, 16 (03) :1387-1396
[40]  
Mineo C., 2018, J HYDROL, V230, P55, DOI [10. 1016/S0022-1694(00)00170-0, DOI 10.1016/S0022-1694(00)00170-0]