scholarly journals Data analysis reveals that extreme events have increased the flood inundations in the Taquari River´s Valley, southern Brazil

2021 ◽  
Vol 1 (1) ◽  
pp. 16-25
Author(s):  
Francisco Manoel Wohnrath Tognoli ◽  
Sabrina Deconti Bruski ◽  
Thiago Peixoto de Araujo

Flood inundations represent more than 62% of the deaths caused by natural disasters in Brazil. The dataset comprises the records of the Encantado´s pluviometric station, a municipality located beside the margin of the Taquari River in southern Brazil, which comprises the rainfall time series (n = 36,466) over 78 years, from April 1943 to December 2020. Complementary datasets also include the annual volume of precipitation per year and the level reached by the Taquari River during 44 flood inundations since 1941. The number of events is subsampled because only 32 years have the complete record of the river level. Three of the five major flood inundations at Encantado occurred after 2001, and the more severe flood recorded the maximum level of the Taquari River (20,27 meters) on July 8th, 2020. Thirty-four percent of all flood inundations in the city were recorded between 2011 and 2020. The months of July to October record 70% of all the events, but there is no record of floods in February and December throughout the data series. The human occupation of the floodplain has been fast in the last decades, and most of the urban area has a potential risk of being affected by flood inundations. Moreover, extreme rainfall events and flood events have been more frequent in the last 30 years. This database can contribute as a starting point for developing predictive models and verifying a possible correlation of floods with extreme events and global climatic changes.

2017 ◽  
Vol 18 (3) ◽  
pp. 611-623 ◽  
Author(s):  
Ali Hamidi ◽  
Naresh Devineni ◽  
James F. Booth ◽  
Amana Hosten ◽  
Ralph R. Ferraro ◽  
...  

Abstract Extreme rainfall events, specifically in urban areas, have dramatic impacts on society and can lead to loss of life and property. Despite these hazards, little is known about the city-scale variability of heavy rainfall events. In the current study, gridded stage IV radar data from 2002 to 2015 are employed to investigate the clustering and the spatial variability of simultaneous rainfall exceedances in the greater New York area. Multivariate clustering based on partitioning around medoids is applied to the extreme rainfall events’ average intensity and areal extent for the 1- and 24-h accumulated rainfall during winter (December–February) and summer (June–August) seasons. The atmospheric teleconnections of the daily extreme event for winter and summer are investigated using compositing of ERA-Interim. For both 1- and 24-h durations, the winter season extreme rainfall events have larger areal extent than the summer season extreme rainfall events. Winter extreme events are associated with deep and organized circulation patterns that lead to more areal extent, and the summer events are associated with localized frontal systems that lead to smaller areal extents. The average intensities of the 1-h extreme rainfall events in summer are much higher than the average intensities of the 1-h extreme rainfall events in winter. A clear spatial demarcation exists within the five boroughs in New York City for winter extreme events. Resultant georeferenced cluster maps can be extremely useful in risk analysis and green infrastructures planning as well as sewer systems’ management at the city scale.


2011 ◽  
Vol 24 (7) ◽  
pp. 1913-1921 ◽  
Author(s):  
Mateus da Silva Teixeira ◽  
Prakki Satyamurty

Abstract A new approach to define heavy and extreme rainfall events based on cluster analysis and area-average rainfall series is presented. The annual frequency of the heavy and extreme rainfall events is obtained for the southeastern and southern Brazil regions. In the 1960–2004 period, 510 (98) and 466 (77) heavy (extreme) rainfall events are identified in the two regions. Monthly distributions of the events closely follow the monthly climatological rainfall in the two regions. In both regions, annual heavy and extreme rainfall event frequencies present increasing trends in the 45-yr period. However, only in southern Brazil is the trend statistically significant. Although longer time series are necessary to ensure the existence of long-term trends, the positive trends are somewhat alarming since they indicate that climate changes, in terms of rainfall regimes, are possibly under way in Brazil.


2021 ◽  
Author(s):  
Andrea Abbate ◽  
Laura Longoni ◽  
Monica Papini

<p>In the field of hydrogeological risk, rainfalls represent the most important triggering factor for superficial terrain failures such as shallow landslides, soil slips and debris flow. The availability of local rain gauges measurements is fundamental for defining the cause-effect relationship for predicting failure scenarios. Unfortunately, these hydrogeological phenomena are typical triggered over mountains regions where the density of the ground-based meteorological network is poor, and the local effects caused by mountains topography can change dramatically the spatial and temporal distribution of rainfall. Therefore, trying to reconstruct a representative rainfall field across mountain areas is a challenge but is a mandatory task for the interpretation of triggering causes. We present a reanalysis of an ensemble of extreme rainfall events happened across central Alps and Pre-Alps, in the northern part of Lombardy Region, Italy. We have investigated around some critical aspects such as their intensity and persistency also proposing a modelling of their meteorological evolution, using the Linear Upslope-Rainfall Model (LUM). We have considered this model because it is designed for describing the mechanism of orographic precipitation intensification that was identified as the main cause of that extreme events. To test and calibrate the LUM model we have considered local rain gauges data because they represent the effective rainfall poured on the ground. These punctual data are generally considered for landslide assessment, in particular for rainfall induced phenomena such as shallow landslides and debris flows. Considering our test cases, the results obtained have shown that the LUM has been able to reproduce accurately the rainfall field. In this regard, LUM model can help to address further information around those ungauged area where rainfall estimation could be critical for evaluating the hazard. We are conscious that our and other studies around this topic would be propaedeutic in the next future for the adoption of an integrated framework among the real-time meteorological modelling and the hydrogeological induced risk assessment and prevision.</p>


Author(s):  
Carlo Montes ◽  
Nachiketa Acharya ◽  
Quamrul Hassan

This work focuses on the analysis of the performance of satellite-based precipitation products for monitoring extreme rainfall events. Five precipitation products are inter-compared and evaluated in capturing indices of extreme rainfall events during 1998-2019 considering four indices of extreme rainfall. Satellite products show a variable performance, which in general indicates that the occurrence and amount of rainfall of extreme events can be both underestimated or overestimated by the datasets in a systematic way throughout the country. Also, products that consider the use of ground truth data have the best performance.


Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2201
Author(s):  
Jinn-Chyi Chen ◽  
Wen-Shun Huang

This study examined the conditions that lead to debris flows, and their association with the rainfall return period (T) and the probability of debris flow occurrence (P) in the Chenyulan watershed, central Taiwan. Several extreme events have occurred in the Chenyulan watershed in the past, including the Chi-Chi earthquake and extreme rainfall events. The T for three rainfall indexes (i.e., the maximum hourly rainfall depth (Im), the maximum 24-h rainfall amount (Rd), and RI (RI = Im× Rd)) were analyzed, and the T associated with the triggering of debris flows is presented. The P–T relationship can be determined using three indexes, Im, Rd, and RI; how it is affected and unaffected by extreme events was developed. Models for evaluating P using the three rainfall indexes were proposed and used to evaluate P between 2009 and 2020 (i.e., after the extreme rainfall event of Typhoon Morakot in 2009). The results of this study showed that the P‒T relationship, using the RI or Rd index, was reasonable for predicting the probability of debris flow occurrence.


2021 ◽  
Author(s):  
Moses.A Ojara ◽  
Yunsheng Lou ◽  
Hasssen Babaousmail ◽  
Peter Wasswa

Abstract East African countries (Uganda, Kenya, Tanzania, Rwanda, and Burundi) are prone to weather extreme events. In this regard; the past occurrence of extreme rainfall events is analyzed for 25 stations following the Expert Team on Climate Change Detection and Indices (ETCCDI) regression method. Detrended Fluctuation Analysis (DFA) is used to show the future development of extreme events. Pearson’s correlation analysis is performed to show the relationship of extreme events between different rainfall zones and their association with El Niño -Southern Oscillation (ENSO and Indian Ocean dipole (IOD) IOD-DMI indices. Results revealed that the consecutive wet day's index (CWD) was decreasing trend in 72% of the stations analyzed, moreover consecutive dry days (CDD) index also indicated a positive trend in 44% of the stations analyzed. Heavy rainfall days index (R10mm) showed a positive trend at 52% of the stations and was statistically significant at a few stations. In light of the extremely heavy rainfall days (R25mm) index, 56% of the stations revealed a decreasing trend for the index and statistically significant trend at some stations. Further, a low correlation coefficient of extreme rainfall events in the regions; and between rainfall extreme indices with the atmospheric teleconnection indices (Dipole Mode Index-DMI and Nino 3.4) (r = -0.1 to r = 0.35). Most rainfall zones showed a positive correlation between the R95p index and DMI, while 5/8 of the rainfall zones experienced a negative correlation between Nino 3.4 index and the R95p. In light of the highly variable trends of extremes events, we recommend planning adaptation and mitigation measures that consider the occurrence of such high variability. Measures such as rainwater harvesting, stored and used during needs, planned settlement, and improved drainage systems management supported by accurate climate and weather forecasts is highly advised.


Author(s):  
Douglas Schaefer

Variations in temperature and precipitation are both components of climate variability. Based on coral growth rates measured near Puerto Rico, the Caribbean was 2–3ºC cooler during the “Little Ice Age” during the seventeenth century (Winter et al. 2000). At the millennial scale, temperature variations in tropical regions have been inferred to have substantial biological effects (such as speciation and extinction), but not at the multidecadal timescales considered here. My focus is on precipitation variability in particular, because climate models examining effects of increased greenhouse gases suggest greater changes in precipitation than in temperature patterns in tropical regions. Some correspondence between both the El Niño–Southern Oscillation (ENSO) and the Northern Atlantic Oscillation (NAO) and average temperatures and total annual precipitation have been reported for the LTER site at Luquillo (Greenland 1999; Greenland and Kittel 2002), but those studies did not refer to extreme events. Based on climate records for Puerto Rico since 1914, Malmgren et al. (1997) found small increases in air temperature during El Niño years and somewhat greater total rainfall during the positive phase of the NAO. Similar to ENSO, the NAO index is characterized by differences in sea-level atmospheric pressure, in this case based on measurements in Iceland and Portugal (Walker and Bliss 1932). Its effects on climate have largely been described in terms of temperature and precipitation anomalies in countries bordering the North Atlantic (e.g., Hurrell 1995). Puerto Rico is in the North Atlantic hurricane zone, and hurricanes clearly play a major role in precipitation variability. The association between extreme rainfall events and hurricanes is discussed in detail in this chapter. I examine the degree to which extreme rainfall events are associated with hurricanes and other tropical storms. I discuss whether the occurrence of these extreme events has changed through time in Puerto Rico or can be linked to the recurrent patterns of the ENSO or the NAO. I examine the 25-year daily precipitation record for the Luquillo LTER site, the 90-year monthly record from the nearest site to Luquillo with such a long record, Fajardo, and those of the two other Puerto Rico stations with the longest daily precipitation records, Manati and Mayaguez (figure 8.1).


2016 ◽  
Vol 29 (16) ◽  
pp. 5915-5934 ◽  
Author(s):  
Á. G. Muñoz ◽  
L. Goddard ◽  
S. J. Mason ◽  
A. W. Robertson

Abstract Potential and real predictive skill of the frequency of extreme rainfall in southeastern South America for the December–February season are evaluated in this paper, finding evidence indicating that mechanisms of climate variability at one time scale contribute to the predictability at another scale; that is, taking into account the interference of different potential sources of predictability at different time scales increases the predictive skill. Part I of this study suggested that a set of daily atmospheric circulation regimes, or weather types, was sensitive to these cross–time scale interferences, conducive to the occurrence of extreme rainfall events in the region, and could be used as a potential predictor. At seasonal scale, a combination of those weather types indeed tends to outperform all the other candidate predictors explored (i.e., sea surface temperature patterns, phases of the Madden–Julian oscillation, and combinations of both). Spatially averaged Kendall’s τ improvements of 43% for the potential predictability and 23% for real-time predictions are attained with respect to standard models considering sea surface temperature fields alone. A new subseasonal-to-seasonal predictive methodology for extreme rainfall events is proposed based on probability forecasts of seasonal sequences of these weather types. The cross-validated real-time skill of the new probabilistic approach, as measured by the hit score and the Heidke skill score, is on the order of twice that associated with climatological values. The approach is designed to offer useful subseasonal-to-seasonal climate information to decision-makers interested not only in how many extreme events will happen in the season but also in how, when, and where those events will probably occur.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Reginaldo Moura Brasil Neto ◽  
Celso Augusto Guimarães Santos ◽  
Jorge Flávio Casé Braga da Costa Silva ◽  
Richarde Marques da Silva ◽  
Carlos Antonio Costa dos Santos ◽  
...  

AbstractDroughts are complex natural phenomena that influence society's development in different aspects; therefore, monitoring their behavior and future trends is a useful task to assist the management of natural resources. In addition, the use of satellite-estimated rainfall data emerges as a promising tool to monitor these phenomena in large spatial domains. The Tropical Rainfall Measuring Mission (TRMM) products have been validated in several studies and stand out among the available products. Therefore, this work seeks to evaluate TRMM-estimated rainfall data's performance for monitoring the behavior and spatiotemporal trends of meteorological droughts over Paraíba State, based on the standardized precipitation index (SPI) from 1998 to 2017. Then, 78 rain gauge-measured and 187 TRMM-estimated rainfall time series were used, and trends of drought behavior, duration, and severity at eight time scales were evaluated using the Mann–Kendall and Sen tests. The results show that the TRMM-estimated rainfall data accurately captured the pattern of recent extreme rainfall events that occurred over Paraíba State. Drought events tend to be drier, longer-lasting, and more severe in most of the state. The greatest inconsistencies between the results obtained from rain gauge-measured and TRMM-estimated rainfall data are concentrated in the area closest to the coast. Furthermore, long-term drought trends are more pronounced than short-term drought, and the TRMM-estimated rainfall data correctly identified this pattern. Thus, TRMM-estimated rainfall data are a valuable source of data for identifying drought behavior and trends over much of the region.


2019 ◽  
Vol 12 (5) ◽  
pp. 1757
Author(s):  
Mariana Caroline Gomes de Lima ◽  
Thais Emanuelle Monteiro Dos Santos Souza ◽  
Valéria Sandra de Oliveira Costa ◽  
Carlos Eduardo Santos De Lima ◽  
Josimar Vieira Dos Reis ◽  
...  

A erosão hídrica é um dos grandes problemas que atingem regiões com potenciais agrícolas e áreas com propensão para deslizamento de terras. A chuva é considerada o fator climático que exerce maior influência no processo erosivo, especialmente nos trópicos por causa da sua distribuição temporal, espacial, características físicas e duração. Este trabalho teve como objetivo determinar o padrão hidrológico e o índice de erosividade  no sertão Pernambucano, visando contribuir com informações estratégicas para gestão agrícola e ambiental na região. Foram utilizados dados pluviométricos horários de 2000 a 2017 localizados no município de Petrolina, disponibilizados pela (APAC). A partir dos dados da precipitação, utilizou-se o aplicativo Climap 3.0 para avaliar os eventos extremos de precipitação e o padrão hidrológico, bem como determinou-se por meio de equações o índice de erosividade para a região. No período analisado os maiores valores da precipitação ocorreram entre os meses de janeiro e abril e identificou-se 8 anos consecutivos de seca na região. Os resultados apontam que houve tendências significativas nas séries de dados, a erosividade foi considerada fraca a moderada em sua maioria, e o padrão hidrológico mais frequente foi o padrão intermediário, resultando uma alta suscetibilidade dos solos da região em sofrer erosão hídrica.Evaluation of hydroclimatic pattern and erosivity Sertão of Pernambuco A B S T R A C T Water erosion is one of major problems affecting regions with agricultural potential and landslide-prone areas. Rain is considered the climatic factor that exerts greatest influence on erosive process, especially in tropics because its temporal, spatial distribution, physical characteristics and duration. This work purpose to determine  hydrological pattern and erosivity index in Pernambucano Sertão,  to contribute with strategic information for agricultural and environmental management in region. Rainfall data from 2000 to 2017 located in city of Petrolina, provided by (APAC) were used. From the rainfall data, the Climap 3.0  was used to evaluate the extreme rainfall events and  hydrological pattern, as well  to determine through equations the erosivity index for  region. During  analyzed period the highest rainfall values occurred between January and April and 8 consecutive years of drought were identified in region. The results indicate that there were significant trends in data series, erosivity was considered weak to moderate mostly, and most frequent hydrological pattern was the intermediate pattern, resulting in high susceptibility of region's soils to water erosion.Keywords: climate variability, hydrological pattern, extreme indexes.


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