scholarly journals Statistical Modeling of Extreme Rainfall in Southwest Western Australia

2005 ◽  
Vol 18 (6) ◽  
pp. 852-863 ◽  
Author(s):  
Y. Li ◽  
W. Cai ◽  
E. P. Campbell

Abstract Rainfall over southwest Western Australia (SWWA; 32°S southward and 118°E westward) has been decreasing over the past decades, putting further constraints on water resources in an already dry area. In this study, daily rainfall over five geographically dispersed and homogenized weather stations within SWWA are analyzed. A peak over threshold method from the extreme value theory is used to model daily rainfall above a given threshold. The Mann–Whitney–Pittitt (change point) test was applied to detect changes in annual, winter (May–October), and summer (November–April) maximum daily rainfall. Change points for winter extreme daily rainfall were found around 1965, based on different individual stations, with the extreme daily rainfall reduced since then. To demonstrate the degree of change in the winter extreme daily rainfall, at 1965 the data were stratified, and generalized Pareto distributions were fitted to the tails of the distributions for daily rainfall in the prechange period of 1930–65 (including 1965) and the postchange period of 1966–2001. The fitted tail distributions also allow the estimation of probabilities and return periods of the daily rainfall extreme. Results show that return periods for the winter extreme daily rainfall have increased after 1965, implying that winter daily rainfall extremes in SWWA are lower after 1965 than they were before. There has been vigorous debate as to what forces the drying trend, that is, whether it is part of multidecadal variability or whether it is driven by secular forcings, such as increasing atmospheric CO2 concentration. In this paper, statistical modeling is also used to identify possible associated changes in atmospheric circulation. It is found that there is a change point near 1965 in a dominant atmospheric circulation mode of the Antarctic Oscillation (AAO). The result offers qualified support for the argument that the AAO may contribute to the drying trend.

Author(s):  
Komi S. Klassou ◽  
Kossi Komi

Abstract Understanding how extreme rainfall is changing locally is a useful step in the implementation of efficient adaptation strategies to negative impacts of climate change. This study aims to analyze extreme rainfall over the middle Oti River Basin. Ten moderate extreme precipitation indices as well as heavy rainfall of higher return periods (25, 50, 75, and 100 years) were calculated using observed daily data from 1921 to 2018. In addition, Mann–Kendall and Sen's slope tests were used for trend analysis. The results showed decreasing trends in most of the heavy rainfall indices while the dry spell index exhibited a rising trend in a large portion of the study area. The occurrence of heavy rainfall of higher return periods has slightly decreased in a large part of the study area. Also, analysis of the annual maximum rainfall revealed that the generalized extreme value is the most appropriate three-parameter frequency distribution for predicting extreme rainfall in the Oti River Basin. The novelty of this study lies in the combination of both descriptive indices and extreme value theory in the analysis of extreme rainfall in a data-scarce river basin. The results are useful for water resources management in this area.


2021 ◽  
Vol 884 (1) ◽  
pp. 012018
Author(s):  
I G Tunas ◽  
H Azikin ◽  
G M Oka

Abstract Extreme rainfall is the main factor triggering flooding in various regions of the world including Indonesia. The increase in intensity and duration of current extreme rainfall is predicted as a result of global climate change. This paper aims to analyze the impact of extreme rainfall to the peak discharge of flood hydrographs at a watershed outlet in Palu, Sulawesi, Indonesia. Maximum daily rainfall data for the period 1990-1999 recorded at the Palu Meteorological Station, Central Sulawesi were selected using the Annual Maximum Series Method, and grouped into two types. Type I is the maximum daily rainfall data with extreme events and Type II is the maximum daily rainfall data without extreme events. Frequency analysis was applied to the two data groups using the best distribution method of: Normal, Normal Log, Pearson III Log, and Gumbel to obtain the design rainfall of each data group. In the next stage, the design rainfall transformation into a flood hydrograph is performed using the Nakayasu Synthetic Unit Hydrograph based on a number of return periods in one of the rivers flowing into Palu Bay, namely the Poboya River. The analysis results show that the design rainfall graphs with both extreme rainfall and without extreme rainfall are identical at the low return period and divergent at the high return period with a difference of up to 21.6% at the 1000-year return period. Correspondingly, extreme rainfall has a greater impact at the peak of the flood hydrograph with increasing return periods ranging from -1.28% to 26.81% over the entire return period.


2019 ◽  
Vol 8 (4) ◽  
pp. 85
Author(s):  
Faithful C. Onwuegbuche ◽  
Alpha B. Kenyatta ◽  
Steeven B. Affognon ◽  
Exavery P. Enock ◽  
Mary O. Akinade

Climate change has brought about unprecedented new weather patterns, one of which is changes in extreme rainfall. In Kenya, heavy rains and severe flash floods have left people dead and displaced hundreds from their settlements. In order to build a resilient society and achieve sustainable development, it is paramount that adequate inference about extreme rainfall be made. To this end, this research modelled and predicted extreme rainfall events in Kenya using Extreme Value Theory for rainfall data from 1901-2016. Maximum Likelihood Estimation was used to estimate the model parameters and block maxima approach was used to fit the Generalized Extreme Value Distribution (GEVD) while the Peak Over Threshold method was used to fit the Generalized Pareto Distribution (GPD). The Gumbel distribution was found to be the optimal model from the GEVD while the Exponential distribution gave the optimal model over the threshold value. Furthermore, prediction for the return periods of 10, 20, 50 and 100 years were made using the return level estimates and their corresponding confidence intervals were presented. It was found that increase in return periods leads to a corresponding increase in return levels. However, the GPD gave higher return levels for 10 and 20 years compared to GEVD. While, for higher return periods 50 and 100 years, the GEVD gave higher return levels compared to the GPD. Model diagnostics using probability, density, quantile and return level plots indicated that the models provided were a good fit for the data.


2009 ◽  
Vol 48 (3) ◽  
pp. 502-516 ◽  
Author(s):  
Pao-Shin Chu ◽  
Xin Zhao ◽  
Ying Ruan ◽  
Melodie Grubbs

Abstract Heavy rainfall and the associated floods occur frequently in the Hawaiian Islands and have caused huge economic losses as well as social problems. Extreme rainfall events in this study are defined by three different methods based on 1) the mean annual number of days on which 24-h accumulation exceeds a given daily rainfall amount, 2) the value associated with a specific daily rainfall percentile, and 3) the annual maximum daily rainfall values associated with a specific return period. For estimating the statistics of return periods, the three-parameter generalized extreme value distribution is fit using the method of L-moments. Spatial patterns of heavy and very heavy rainfall events across the islands are mapped separately based on the aforementioned three methods. Among all islands, the pattern on the island of Hawaii is most distinguishable, with a high frequency of events along the eastern slopes of Mauna Kea and a low frequency of events on the western portion so that a sharp gradient in extreme events from east to west is prominent. On other islands, extreme rainfall events tend to occur locally, mainly on the windward slopes. A case is presented for estimating return periods given different rainfall intensity for a station in Upper Manoa, Oahu. For the Halloween flood in 2004, the estimated return period is approximately 27 yr, and its true value should be no less than 13 yr with 95% confidence as determined from the adjusted bootstrap resampling technique.


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.


Author(s):  
Guillaume Chagnaud ◽  
Geremy Panthou ◽  
Theo Vischel ◽  
Thierry Lebel

Abstract The West African Sahel has been facing for more than 30 years an increase in extreme rainfalls with strong socio-economic impacts. This situation challenges decision-makers to define adaptation strategies in a rapidly changing climate. The present study proposes (i) a quantitative characterization of the trends in extreme rainfalls at the regional scale, (ii) the translation of the trends into metrics that can be used by hydrological risk managers, (iii) elements for understanding the link between the climatology of extreme and mean rainfall. Based on a regional non-stationary statistical model applied to in-situ daily rainfall data over the period 1983-2015, we show that the region-wide increasing trend in extreme rainfalls is highly significant. The change in extreme value distribution reflects an increase in both the mean and variability, producing a 5%/decade increase in extreme rainfall intensity whatever the return period. The statistical framework provides operational elements for revising the design methods of hydraulic structures which most often assume a stationary climate. Finally, the study shows that the increase in extreme rainfall is more attributable to an increase in the intensity of storms (80%) than to their occurrence (20%), reflecting a major disruption from the decadal variability of the rainfall regime documented in the region since 1950.


2010 ◽  
Vol 7 (4) ◽  
pp. 4957-4994 ◽  
Author(s):  
R. Deidda

Abstract. Previous studies indicate the generalized Pareto distribution (GPD) as a suitable distribution function to reliably describe the exceedances of daily rainfall records above a proper optimum threshold, which should be selected as small as possible to retain the largest sample while assuring an acceptable fitting. Such an optimum threshold may differ from site to site, affecting consequently not only the GPD scale parameter, but also the probability of threshold exceedance. Thus a first objective of this paper is to derive some expressions to parameterize a simple threshold-invariant three-parameter distribution function which is able to describe zero and non zero values of rainfall time series by assuring a perfect overlapping with the GPD fitted on the exceedances of any threshold larger than the optimum one. Since the proposed distribution does not depend on the local thresholds adopted for fitting the GPD, it will only reflect the on-site climatic signature and thus appears particularly suitable for hydrological applications and regional analyses. A second objective is to develop and test the Multiple Threshold Method (MTM) to infer the parameters of interest on the exceedances of a wide range of thresholds using again the concept of parameters threshold-invariance. We show the ability of the MTM in fitting historical daily rainfall time series recorded with different resolutions. Finally, we prove the supremacy of the MTM fit against the standard single threshold fit, often adopted for partial duration series, by evaluating and comparing the performances on Monte Carlo samples drawn by GPDs with different shape and scale parameters and different discretizations.


2020 ◽  
Vol 35 (2) ◽  
pp. 357-374
Author(s):  
Paulo Miguel de Bodas Terassi ◽  
José Francisco de Oliveira Júnior ◽  
Givanildo de Gois ◽  
Bruno Serafini Sobral ◽  
Emerson Galvani ◽  
...  

Abstract The knowledge of intensity and frequency of rainfall allows establishing predictive measures to minimize impacts caused by high volume of rainfall totals in a region. Therefore, the objective is to evaluate daily rainfall for Paraná slope of the Itararé watershed (PSIW) and to verify the spatiotemporal trend of intense and extreme daily rainfall. Rainfall data from 14 stations collected from 1976 to 2012 were used with less than 4% of data faults. Multivariate analysis based on cluster analysis technique (CA) was used applying the Euclidean distance for the identification of homogeneous groups, and the quantiles technique to classify daily rainfall. The Mann-Kendall (MK) test was used to identify trends for annual rainfall totals, annual number of rainy days (ANRD) and for the occurrence of intense (R95p) and extreme (R99p) rainfall. The CA technique identified three rainfall groups (HG I, II and III). Given the latitudinal position of the area, rainfall at the southern sector is characterized by its greater similarities with the subtropical climate, whereas in the North sector there is a consistent reduction of rainfall totals in autumn and, especially, during winter months, which are characteristic of the tropical climate. The MK test identified the downward trend of ANRD, with greater significance for the south-centered sectors of the basin. The observed trends for the intense (R95p) and extreme (R99p) daily rainfall show the predominance of reduction for the Southwest and central sector, followed by a significant increase in the Southeast and North sectors of the PSIW.


2006 ◽  
Vol 19 (10) ◽  
pp. 1948-1969 ◽  
Author(s):  
Matthew H. England ◽  
Caroline C. Ummenhofer ◽  
Agus Santoso

Abstract Interannual rainfall extremes over southwest Western Australia (SWWA) are examined using observations, reanalysis data, and a long-term natural integration of the global coupled climate system. The authors reveal a characteristic dipole pattern of Indian Ocean sea surface temperature (SST) anomalies during extreme rainfall years, remarkably consistent between the reanalysis fields and the coupled climate model but different from most previous definitions of SST dipoles in the region. In particular, the dipole exhibits peak amplitudes in the eastern Indian Ocean adjacent to the west coast of Australia. During dry years, anomalously cool waters appear in the tropical/subtropical eastern Indian Ocean, adjacent to a region of unusually warm water in the subtropics off SWWA. This dipole of anomalous SST seesaws in sign between dry and wet years and appears to occur in phase with a large-scale reorganization of winds over the tropical/subtropical Indian Ocean. The wind field alters SST via anomalous Ekman transport in the tropical Indian Ocean and via anomalous air–sea heat fluxes in the subtropics. The winds also change the large-scale advection of moisture onto the SWWA coast. At the basin scale, the anomalous wind field can be interpreted as an acceleration (deceleration) of the Indian Ocean climatological mean anticyclone during dry (wet) years. In addition, dry (wet) years see a strengthening (weakening) and coinciding southward (northward) shift of the subpolar westerlies, which results in a similar southward (northward) shift of the rain-bearing fronts associated with the subpolar front. A link is also noted between extreme rainfall years and the Indian Ocean Dipole (IOD). Namely, in some years the IOD acts to reinforce the eastern tropical pole of SST described above, and to strengthen wind anomalies along the northern flank of the Indian Ocean anticyclone. In this manner, both tropical and extratropical processes in the Indian Ocean generate SST and wind anomalies off SWWA, which lead to moisture transport and rainfall extremes in the region. An analysis of the seasonal evolution of the climate extremes reveals a progressive amplification of anomalies in SST and atmospheric circulation toward a wintertime maximum, coinciding with the season of highest SWWA rainfall. The anomalies in SST can appear as early as the summertime months, however, which may have important implications for predictability of SWWA rainfall extremes.


Sign in / Sign up

Export Citation Format

Share Document