scholarly journals Intensity–duration–frequency curves from remote sensing rainfall estimates: comparing satellite and weather radar over the eastern Mediterranean

2017 ◽  
Vol 21 (5) ◽  
pp. 2389-2404 ◽  
Author(s):  
Francesco Marra ◽  
Efrat Morin ◽  
Nadav Peleg ◽  
Yiwen Mei ◽  
Emmanouil N. Anagnostou

Abstract. Intensity–duration–frequency (IDF) curves are widely used to quantify the probability of occurrence of rainfall extremes. The usual rain gauge-based approach provides accurate curves for a specific location, but uncertainties arise when ungauged regions are examined or catchment-scale information is required. Remote sensing rainfall records, e.g. from weather radars and satellites, are recently becoming available, providing high-resolution estimates at regional or even global scales; their uncertainty and implications on water resources applications urge to be investigated. This study compares IDF curves from radar and satellite (CMORPH) estimates over the eastern Mediterranean (covering Mediterranean, semiarid, and arid climates) and quantifies the uncertainty related to their limited record on varying climates. We show that radar identifies thicker-tailed distributions than satellite, in particular for short durations, and that the tail of the distributions depends on the spatial and temporal aggregation scales. The spatial correlation between radar IDF and satellite IDF is as high as 0.7 for 2–5-year return period and decreases with longer return periods, especially for short durations. The uncertainty related to the use of short records is important when the record length is comparable to the return period ( ∼  50,  ∼  100, and  ∼  150 % for Mediterranean, semiarid, and arid climates, respectively). The agreement between IDF curves derived from different sensors on Mediterranean and, to a good extent, semiarid climates, demonstrates the potential of remote sensing datasets and instils confidence on their quantitative use for ungauged areas of the Earth.

2016 ◽  
Author(s):  
Francesco Marra ◽  
Efrat Morin ◽  
Nadav Peleg ◽  
Yiwen Mei ◽  
Emmanouil N. Anagnostou

Abstract. Intensity–Duration–Frequency (IDF) curves are widely used to quantify the probability of occurrence of rainfall extremes. The usual rain gauge based approach provides accurate curves for a specific location, but uncertainties arise when ungauged regions are examined or catchment scale information is required. Remotely sensed rainfall records, e.g. from weather radars and satellites, are recently becoming available, providing high resolution information on rainfall extremes at regional or even global scales: their uncertainty and implications on water resources applications urge to be investigated. This study compares IDF curves from radar and satellite (CMORPH) estimates over the Eastern Mediterranean (covering Mediterranean, semiarid and arid climates) and quantifies the uncertainty related to their limited record on varying climates. We show that radar identifies thicker tail distributions than satellite, in particular for short durations, and that the shape parameters depends on the spatial and temporal aggregation scales. The spatial correlation between radar-IDFs and satellite-IDFs is as high as 0.7 for 2–5 years return period and decreases with longer return periods, especially for short durations. The uncertainty related to the use of short records is important when the record length is comparable to the return period (~ 50 %, ~ 100 % and ~ 150 % for Mediterranean, semiarid and arid climates, respectively). The agreement between IDF curves derived from different sensors on Mediterranean and, to a good extent, semiarid climates, demonstrates the potential of remote sensing datasets and instils confidence on their quantitative use for ungauged areas of the Earth.


2000 ◽  
Vol 31 (4-5) ◽  
pp. 357-372 ◽  
Author(s):  
Jonas Elíasson

The M5 method, originally proposed by the Natural Resource Council in UK, is used for estimating precipitation in Iceland. In this method the M5 (24-hour precipitation with 5-year return period) is used as an index variable. Instead of the usual approach in estimating regional values of the coefficient of variation another coefficient, Ci is used. The M5 and the Ci define together a generalised distribution that can be utilised to estimate the statistical distribution of precipitation anywhere in the country. M5 maps have been prepared for this purpose by the Engineering Research Institute of the University of Iceland. Methods have been devised to derive PMP values from the M5 values. This paper describes the method and gives examples of calculation. It is also shown that the same CDF applies for the observations of shorter duration precipitation available in Iceland. By applying the principle of identical statistical distribution for standardised annual maxima of any duration, IDF (Intensity – Duration – Frequency) curves have been derived. This allows the IDF – values to be calculated on basis of M5 and Ci, which are the two-parameters that define the generalised precipitation distribution.


2004 ◽  
Vol 4 (3) ◽  
pp. 375-387 ◽  
Author(s):  
B. Mohymont ◽  
G. R. Demarée ◽  
D. N. Faka

Abstract. The establishment of Intensity-Duration-Frequency (IDF) curves for precipitation remains a powerful tool in the risk analysis of natural hazards. Indeed the IDF-curves allow for the estimation of the return period of an observed rainfall event or conversely of the rainfall amount corresponding to a given return period for different aggregation times. There is a high need for IDF-curves in the tropical region of Central Africa but unfortunately the adequate long-term data sets are frequently not available. The present paper assesses IDF-curves for precipitation for three stations in Central Africa. More physically based models for the IDF-curves are proposed. The methodology used here has been advanced by Koutsoyiannis et al. (1998) and an inter-station and inter-technique comparison is being carried out. The IDF-curves for tropical Central Africa are an interesting tool to be used in sewer system design to combat the frequently occurring inundations in semi-urbanized and urbanized areas of the Kinshasa megapolis.


2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Yabin Sun ◽  
Dadiyorto Wendi ◽  
Dong Eon Kim ◽  
Shie-Yui Liong

AbstractThe rainfall intensity–duration–frequency (IDF) curves play an important role in water resources engineering and management. The applications of IDF curves range from assessing rainfall events, classifying climatic regimes, to deriving design storms and assisting in designing urban drainage systems, etc. The deriving procedure of IDF curves, however, requires long-term historical rainfall observations, whereas lack of fine-timescale rainfall records (e.g. sub-daily) often results in less reliable IDF curves. This paper presents the utilization of remote sensing sub-daily rainfall, i.e. Global Satellite Mapping of Precipitation (GSMaP), integrated with the Bartlett-Lewis rectangular pulses (BLRP) model, to disaggregate the daily in situ rainfall, which is then further used to derive more reliable IDF curves. Application of the proposed method in Singapore indicates that the disaggregated hourly rainfall, preserving both the hourly and daily statistic characteristics, produces IDF curves with significantly improved accuracy; on average over 70% of RMSE is reduced as compared to the IDF curves derived from daily rainfall observations.


2016 ◽  
Author(s):  
Reza Ghazavi ◽  
Ali Moafi Rabori ◽  
Mohsen Ahadnejad Reveshty

Abstract. Estimate design storm based on rainfall intensity–duration–frequency (IDF) curves is an important parameter for hydrologic planning of urban areas. The main aim of this study was to estimate rainfall intensities of Zanjan city watershed based on overall relationship of rainfall IDF curves and appropriate model of hourly rainfall estimation (Sherman method, Ghahreman and Abkhezr method). Hydrologic and hydraulic impacts of rainfall IDF curves change in flood properties was evaluated via Stormwater Management Model (SWMM). The accuracy of model simulations was confirmed based on the results of calibration. Design hyetographs in different return periods show that estimated rainfall depth via Sherman method are greater than other method except for 2-year return period. According to Ghahreman and Abkhezr method, decrease of runoff peak was 30, 39, 41 and 42 percent for 5-10-20 and 50-year return periods respectively, while runoff peak for 2-year return period was increased by 20 percent.


Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1243 ◽  
Author(s):  
Andre Schardong ◽  
Slobodan P. Simonovic ◽  
Abhishek Gaur ◽  
Dan Sandink

Rainfall Intensity–Duration–Frequency (IDF) curves are among the most essential datasets used in water resources management across the globe. Traditionally, they are derived from observations of historical rainfall, under the assumption of stationarity. Change of climatic conditions makes use of historical data for development of IDFs for the future unreliable, and in some cases, may lead to underestimated infrastructure designs. The IDF_CC tool is designed to assist water professionals and engineers in producing IDF estimates under changing climatic conditions. The latest version of the tool (Version 4) provides updated IDF curve estimates for gauged locations (rainfall monitoring stations) and ungauged sites using a new gridded dataset of IDF curves for the land mass of Canada. The tool has been developed using web-based technologies and takes the form of a decision support system (DSS). The main modifications and improvements between version 1 and the latest version of the IDF_CC tool include: (i) introduction of the Generalized Extreme value (GEV) distribution; (ii) updated equidistant matching algorithm (QM); (iii) gridded IDF curves dataset for ungauged location and (iv) updated Climate Models.


2014 ◽  
Vol 18 (12) ◽  
pp. 5093-5107 ◽  
Author(s):  
G. Panthou ◽  
T. Vischel ◽  
T. Lebel ◽  
G. Quantin ◽  
G. Molinié

Abstract. Intensity–duration–area–frequency (IDAF) curves are increasingly demanded for characterising the severity of storms and for designing hydraulic structures. Their computation requires inferring areal rainfall distributions over the range of space scales and timescales that are the most relevant for hydrological studies at catchment scale. In this study, IDAF curves are computed for the first time in West Africa, based on the data provided by the AMMA-CATCH Niger network, composed of 30 recording rain gauges having operated since 1990 over a 16 000 km2 area in south-western Niger. The IDAF curves are obtained by separately considering the time (intensity–duration–frequency, IDF) and space (areal reduction factor, ARF) components of the extreme rainfall distribution. Annual maximum intensities are extracted for resolutions between 1 and 24 h in time and from point (rain gauge) to 2500 km2 in space. The IDF model used is based on the concept of scale invariance (simple scaling) which allows the normalisation of the different temporal resolutions of maxima series to which a global generalised extreme value (GEV) is fitted. This parsimonious framework allows one to use the concept of dynamic scaling to describe the ARF. The results show that coupling a simple scaling in space and time with a dynamical scaling that relates to space and time allows one to satisfactorily model the effect of space–time aggregation on the distribution of extreme rainfall.


2005 ◽  
Vol 36 (3) ◽  
pp. 269-280 ◽  
Author(s):  
L. Bengtsson

The runoff from real 3 cm thick sedum-moss roofs and from laboratory roof plots in southern Sweden is measured and analysed. Real rains and artificial storms are used for the analysis. The probability of high runoff is compared with the probability of high precipitation intensity. Intensity–duration–frequency curves for runoff are derived and it is found that the runoff of 1.5 year return period corresponds to rain of 0.4 year return period. The storage of water in the soil–vegetation cover on the roof is determined. The storage at field capacity, when runoff is initiated, is about 9 mm. Water in excess of that is temporary stored during storms. The runoff distribution during prolonged storms can be related to the mean rain intensity over 20–30 min. The influence of the slope and length of the roof on the runoff peak is investigated as is the effect of the drainage layer. Neither slope nor length seems to significantly influence the runoff distribution, which indicates that the vertical percolation process through the vegetation and the soil dominates the rainfall–runoff process. The presence of a drainage layer below the soil results in somewhat faster runoff compared to when there is no drainage layer, and thus results in an increased runoff peak.


Author(s):  
Gabriela Rezende de Souza ◽  
Italoema Pinheiro Bello ◽  
Luiz Fernando Coutinho de Oliveira ◽  
Flavia Vilela Corrêa

This study created thematic heavy rainfall maps for Brazil, with durations of 5-, 30-, 60- and 120 minutes and 5 years of return period (T). The intensity-duration-frequency (IDF) relationships used were compiled from studies found in the literature (798 locations) and derived for 4411 rainfall gauges available in the Hidroweb information system, totaling 5209 rainfall data collected. To derive IDF relationships, Gumbel's probability distributions were used, with parameters estimated by the method of moments. Distribution adequacy was verified by the Kolmogorov-Smirnov test. Rainfall-intensity values obtained by IDF relationships were spatialized in Geographic Information Systems, allowing elaboration of the thematic maps. Thematic maps enable obtain rainfall intensities for places without rain gauge data and/or precarious time-series data. Therefore, these maps are a great tool for the design of hydraulic structures related to urban and rural micro-drainage.


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