Statistical Modeling of Spatial Extremes through Max-Stable Process Models: Application to Extreme Rainfall Events in South Africa

2021 ◽  
Vol 26 (10) ◽  
pp. 05021028
Author(s):  
Tadele Akeba Diriba ◽  
Legesse Kassa Debusho
2020 ◽  
Author(s):  
Jordan Richards ◽  
Jonathan Tawn

<div> <p>Fluvial flooding is caused by excessive rainfall sustained over extended periods of time and over spatial catchment areas. Although methodology for modelling excessive, or extreme, rainfall events is extensive and well researched, the same cannot be said about how the extremal properties of spatial and temporal aggregations of rainfall are related. We hope to rectify this by developing a methodology for modelling extremes at different spatio-temporal scales and which incorporates a wide range of dependence structures.</p> </div><div> <p>Research on modelling aggregated spatial extremes is ongoing, but here we present some interesting first-order behavior for the tails of aggregates of (dependent) variables. Marginally these variables are assumed to have GPD tails and we focus on exploring how properties of the dependence structure influence the tail properties of the aggregate. The implications of our theoretical results for statistical purposes will be discussed.</p> </div><div> <p> </p> </div>


2007 ◽  
Vol 135 (3) ◽  
pp. 1128-1150 ◽  
Author(s):  
A. T. Singleton ◽  
C. J. C. Reason

Abstract Investigations of extreme rainfall events in the southern African region are limited by the paucity of the observational network. Furthermore, the lack of full radar coverage for South Africa makes quantitative precipitation estimation difficult. Therefore, numerical modeling represents the most effective method for improving the understanding of the mechanisms that contribute to extreme rainfall events in this region with the caveat that accurate validation of model simulations is hampered by the limited observations in the region. This paper describes an intense cutoff low event over South Africa that led to record rainfall and flash flooding along the south coast of the country and adjoining hinterland. Analyses from the Global Forecast System model showed that the cutoff aloft was accompanied by a strong low-level jet (LLJ) impinging onto the south coast where rainfall was heaviest, and that lapse rates were steep in the lower troposphere. Simulations of the event were carried out using a numerical model [i.e., the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5)], which showed that severe convection occurred over the ocean on the right-hand side of the LLJ, and at its leading edge where it impinged on the coastal topography. This topography was also very important in providing additional forcing for the ascent of moist air. A factor separation technique was used to show that surface heat fluxes from the warm sea surface temperature (SST) of the Agulhas Current were important in enhancing low-level cyclogenesis, and that topography was important in maintaining the position of the low-level coastal depression, which led to favorable conditions for rainfall remaining in the same area for an extended period of time. It is suggested that improved representation of the tight topographic and SST gradients of the southern African region in NWP models or postprocessing systems would help to provide more accurate forecasts of the amount and location of heavy precipitation during cutoff low events where surface forcing is important.


2020 ◽  
Author(s):  
Katelyn Johnson ◽  
Jeff Smithers

<p>The estimation of design rainfalls and design floods are required by engineers and hydrologists to design and quantify the risk of failure of hydraulic structures. Extreme design rainfall quantities such as high-return period rainfalls and the probable maximum precipitation (PMP) are needed to design high-hazard hydraulic structures. In South Africa, previous design rainfall estimates have been produced up to the 200 year return period. PMP estimates were last determined nearly 50 years ago based on only 30 years of data. Most studies on extreme rainfall reported are based on frequency analysis assuming stationary conditions. Previous studies in South Africa have assumed a stationary climate. However, the assumption of a stationary climate in rainfall and flood frequency analysis has been challenged owing to evidence of climate change. Recent literature indicates that the magnitude and frequency of extreme rainfall events has been changing and this is likely to continue in future. Hence, methods to account for trends in extreme rainfall events in a changing environment need to be developed. In addition, the concept of PMP, particularly as used for the design and safety evaluation of large dams in South Africa, is being challenged with the recommendation that high-return period design rainfalls be used in these assessments. The aims of this study are: (i) to estimate extreme design rainfall values, with a focus on return periods greater than 200 years, (ii) to update PMP estimates using updated data and modernised methods, and (iii) to account for non-stationary climate data in the estimation of these extreme rainfall events in South Africa. Frequency analysis using LH-moments, which more accurately fit the upper tail of distributions, have been used to estimate high-return period design rainfalls. Regular L-moments are shown to overestimate the extreme rainfall quantities when compared to LH-moments by giving undue favour to outliers. PMP estimates have been determined using a storm maximisation and transposition approach. Radial Basis Functions (RFBs) have been used to transpose PMP estimates to ungauged locations, producing PMPs for the entire country. Approximately 80 % of the new PMPs are greater than the previous estimates. This is probably due to the many limitations of the old approach and differences used in the new approach, indicating that the new approach undertaken in this study may provide improved estimates. The PMP represents the upper limit of extreme rainfall, however, comparisons of high-return period rainfalls to the PMP show that the PMP is sometimes exceeded by the high-return period rainfalls. To develop methods to estimate extreme design rainfall events in a non-stationary climate, this study explores the impacts of climate drivers, such as the Southern Oscillation Index (SOI), and changes in atmospheric variables, such as dew point temperature, on high-return period rainfalls and the PMP.</p>


Water SA ◽  
2019 ◽  
Vol 45 (3 July) ◽  
Author(s):  
KA Johnson ◽  
JC Smithers

The estimation of design rainfalls is necessary to estimate the exceedance probabilities of extreme floods required to design hydraulic structures and to quantify the risk of failure of these structures. New approaches to estimating extreme rainfall events are being developed internationally. This paper reviews methods for estimating design rainfalls, particularly extreme events, in South Africa and internationally, and highlights the need to update methods used for estimating extreme rainfall events in South Africa as a platform for future research.


2019 ◽  
Vol 1 (1) ◽  
pp. 33
Author(s):  
M Welly

Many people in Indonesia calculate design rainfall before calculating the design flooddischarge. The design rainfall with a certain return period will eventually be convertedinto a design flood discharge by combining it with the characteristics of the watershed.However, the lack of a network of rainfall recording stations makes many areas that arenot hydrologically measured (ungauged basin), so it is quite difficult to know thecharacteristics of rain in the area concerned. This study aims to analyze thecharacteristics of design rainfall in Lampung Province. The focus of the analysis is toinvestigate whether geographical factors influence the design rainfall that occurs in theparticular area. The data used in this study is daily rainfall data from 15 rainfallrecording stations spread in Lampung Province. The method of frequency analysis usedin this study is the Gumbel method. The research shows that the geographical location ofan area does not have significant effect on extreme rainfall events. The effect of risingearth temperatures due to natural exploitation by humans tends to be stronger as a causeof extreme events such as extreme rainfall.Keywords: Influence, geographical, factors, extreme, rainfall.


2013 ◽  
Vol 31 (3) ◽  
pp. 413 ◽  
Author(s):  
André Becker Nunes ◽  
Gilson Carlos Da Silva

ABSTRACT. The eastern region of Santa Catarina State (Brazil) has an important history of natural disasters due to extreme rainfall events. Floods and landslides are enhancedby local features such as orography and urbanization: the replacement of natural surface coverage causing more surface runoff and, hence, flooding. Thus, studies of this type of events – which directly influence life in the towns – take on increasing importance. This work makes a quantitative analysis of occurrences of extreme rainfall events in the eastern and northern regions of Santa Catarina State in the last 60 years, through individual analysis, considering the history of floods ineach selected town, as well as an estimate through to the end of century following regional climate modeling. A positive linear trend, in most of the towns studied, was observed in the results, indicating greater frequency of these events in recent decades, and the HadRM3P climate model shows a heterogeneous increase of events for all towns in the period from 2071 to 2100.Keywords: floods, climate modeling, linear trend. RESUMO. A região leste do Estado de Santa Catarina tem um importante histórico de desastres naturais ocasionados por eventos extremos de precipitação. Inundações e deslizamentos de terra são potencializados pelo relevo acidentado e pela urbanização das cidades da região: a vegetação nativa vem sendo removida acarretando um maior escoamento superficial e, consequentemente, em inundações. Desta forma, torna-se de suma importância os estudos acerca deste tipo de evento que influencia diretamente a sociedade em geral. Neste trabalho é realizada uma análise quantitativa do número de eventos severos de precipitação ocorridos nas regiões leste e norte de Santa Catarina dos últimos 60 anos, por meio de uma análise pontual, considerandoo histórico de inundações de cada cidade selecionada, além de uma projeção para o fim do século de acordo com modelagem climática regional. Na análise dos resultados observou-se uma tendência linear positiva na maioria das cidades, indicando uma maior frequência deste tipo de evento nas últimas décadas, e o modelo climático HadRM3P mostra um aumento heterogêneo no número de eventos para todas as cidades no período de 2071 a 2100.Palavras-chave: inundações, modelagem climática, tendência linear.


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