Extreme rainfall and drought events in Tamil Nadu, India

2020 ◽  
Vol 80 (3) ◽  
pp. 175-188
Author(s):  
R Rajkumar ◽  
CS Shaijumon ◽  
B Gopakumar ◽  
D Gopalakrishnan
Keyword(s):  
Tamil Nadu ◽  
Daily Rainfall ◽  
India Meteorological Department ◽  
Extreme Rainfall ◽  
Drought Severity ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Significance Level ◽  
Spatio Temporal ◽  
Temporal Dimensions

In the present study, we examined the exposure of the Tamil Nadu region, India, to droughts and extreme rainfall events using the Standardised Precipitation Evapotranspiration Index (SPEI) and a classification scheme based on daily rainfall. We used high-resolution temperature and rainfall observations from the India Meteorological Department for the period 1951-2016. The robustness of the results was tested using the Mann-Kendall trend (M-K) test and the Kolmogorov-Smirnov (K-S) test. During the study period, there were statistically significant increasing trends in drought area (90% significance level), maximum drought intensity (99% significance level) and maximum drought severity (99% significance level) over the Tamil Nadu region. There has also been an increase in the frequency and intensity of heavy rainfall events in recent years. The spatio-temporal dimensions of this study suggest an increasing exposure of this semi-arid, rain shadow region to severe droughts and extreme rainfall events in recent decades. The results provide sufficient grounds to substantiate the necessity of immediate interventions at the policy level.

scholarly journals Extreme rainfall events over Odisha state, India

MAUSAM ◽  
2021 ◽  
Vol 68 (1) ◽  
pp. 131-138
Author(s):  
S. PASUPALAK ◽  
G. PANIGRAHI ◽  
T. PANIGRAHI ◽  
S. MOHANTY ◽  
K. K. SINGH
Keyword(s):  
Heavy Rainfall ◽  
Hot Spot ◽  
Daily Rainfall ◽  
India Meteorological Department ◽  
Extreme Rainfall ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Rainfall Frequency ◽  
Before And After ◽  
Block Level

Extreme rainfall events are a significant cause of loss of life and livelihoods in Odisha. Objectives of the present study are to determine the trend of the extreme rainfall events during 1991-2014 and to compare the events between two periods before and after 1991. Block level daily rainfall data were used in identifying the extreme rainfall events, while district level aggregation was used in analysing the trend   in three categories, viz., heavy, very heavy and extremely heavy rainfall as per criteria given by India Meteorological Department (IMD). The state as a whole received one extremely heavy, nine very heavy, and forty heavy rainfall events in a year. When percentage of occurrence of each category out of the total extreme events over different districts was considered, maximum % of extremely heavy rainfall occurred in Kalahandi (5.8%), very heavy rainfall in Bolangir (23.8%) and heavy rainfall in Keonjhargarh (85.4%). Trend analysis showed that number of extreme rainfall events increased in a few districts, namely, Bolangir, Nuapada, Keonjhargarh, Koraput, Malkangiri, and Nawarangapur and did not change in other districts. In Puri district, extremely heavy rainfall frequency decreased. New all-time record high one-day rainfall events were observed in twenty districts during 1992 to 2014, surpassing the earlier records, which could be attributed to  climate change induced by  global warming. Interior south Odisha was found as the hot spot for extreme rainfalls.

The Influence of Geographical Factors on Extreme Rainfalls in Lampung Province

2019 ◽  
Vol 1 (1) ◽  
pp. 33
Author(s):  
M Welly
Keyword(s):  
Geographical Location ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Design Flood ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Ungauged Basin ◽  
Flood Discharge ◽  
Design Rainfall ◽  
Geographical Factors

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.

scholarly journals TRMM rainfall estimative coupled with Bell (1969) methodology for extreme rainfall characterization

2015 ◽  
Vol 369 ◽  
pp. 163-168 ◽  
Author(s):  
E. Schiavo Bernardi ◽  
D. Allasia ◽  
R. Basso ◽  
P. Freitas Ferreira ◽  
R. Tassi
Keyword(s):  
Temporal Distribution ◽  
Daily Rainfall ◽  
Tropical Rainfall Measuring Mission ◽  
Extreme Rainfall ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Remote Sensors ◽  
Indirect Measures ◽  
Equation Error ◽  
Convective Cells

Abstract. The lack of rainfall data in Brazil, and, in particular, in Rio Grande do Sul State (RS), hinders the understanding of the spatial and temporal distribution of rainfall, especially in the case of the more complex extreme events. In this context, rainfall's estimation from remote sensors is seen as alternative to the scarcity of rainfall gauges. However, as they are indirect measures, such estimates needs validation. This paper aims to verify the applicability of the Tropical Rainfall Measuring Mission (TRMM) satellite information for extreme rainfall determination in RS. The analysis was accomplished at different temporal scales that ranged from 5 min to daily rainfall while spatial distribution of rainfall was investigated by means of regionalization. An initial test verified TRMM rainfall estimative against measured rainfall at gauges for 1998–2013 period considering different durations and return periods (RP). Results indicated that, for the RP of 2, 5, 10 and 15 years, TRMM overestimated on average 24.7% daily rainfall. As TRMM minimum time-steps is 3 h, in order to verify shorter duration rainfall, the TRMM data were adapted to fit Bell's (1969) generalized IDF formula (based on the existence of similarity between the mechanisms of extreme rainfall events as they are associated to convective cells). Bell`s equation error against measured precipitation was around 5–10%, which varied based on location, RP and duration while the coupled BELL+TRMM error was around 10–35%. However, errors were regionally distributed, allowing a correction to be implemented that reduced by half these values. These findings in turn permitted the use of TRMM+Bell estimates to improve the understanding of spatiotemporal distribution of extreme hydrological rainfall events.

scholarly journals Trend and spatial variability of 1-day extreme rainfall from 1980 - 2015: study at the adminisitrative area of UPT PSDA Pasuruan

2019 ◽  
Vol 8 (1) ◽  
pp. 29
Author(s):  
Indarto Indarto
Keyword(s):  
Spatial Variability ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Statistical Test ◽  
Rainfall Event ◽  
Rainfall Data ◽  
Rainfall Events ◽  
Significance Level ◽  
Main Input ◽  
Crossing Test

This study aims to analyze trends,  shift and spatial variability of extreme-rainfall in the area of UPT PSDA Pasuruan. The daily rainfall data from 64 stations from 1980 until 2015 were used as main input. The 1-day extreem rainfall data is determined as the maximum annual of 24-hour rainfall events.  The statistical  analysis using Mann-Kendall, Rank-Sum, and Median Crossing Test using significance level α = 0,05. The spatial variability of extrem rainfall data is described using average annual 24-hour rainfall during the periods of record. Each station is represented by one value. The values are then interpolated using IDW interpolation methods to maps the spatial variability of extreem rainfall event.  The results show the value of statistical test for each stations that show the existing  trend, shift, or randomness of data. The result also produce thematic maps show the spatial variability of extreme rainfall and the value of each trend.

Extreme rainfall events during and following heatwaves

2021 ◽  
Author(s):  
Christoph Sauter ◽  
Christopher White ◽  
Hayley Fowler ◽  
Seth Westra
Keyword(s):  
Natural Hazards ◽  
Rainfall Intensity ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Rainfall Extremes ◽  
Average Rainfall ◽  
Time Of Year ◽  
The Impact

<p>Heatwaves and extreme rainfall events are natural hazards that can have severe impacts on society. The relationship between temperature and extreme rainfall has received scientific attention with studies focussing on how single daily or sub-daily rainfall extremes are related to day-to-day temperature variability. However, the impact multi-day heatwaves have on sub-daily extreme rainfall events and how extreme rainfall properties change during different stages of a heatwave remains mostly unexplored.</p><p>In this study, we analyse sub-daily rainfall records across Australia, a country that experiences severe natural hazards on a frequent basis, and determine their extreme rainfall properties, such as rainfall intensity, duration and frequency during SH-summer heatwaves. These properties are then compared to extreme rainfall properties found outside heatwaves, but during the same time of year, to examine to what extent they differ from normal conditions. We also conduct a spatial analysis to investigate any spatial patterns that arise.</p><p>We find that rainfall breaking heatwaves is often more extreme than average rainfall during the same time of year. This is especially prominent on the eastern and south-eastern Australian coast, where frequency and intensity of sub-daily rainfall extremes show an increase during the last day or the day immediately after a heatwave. We also find that although during heatwaves the average rainfall amount and duration decreases, there is an increase in sub-daily rainfall intensity when compared to conditions outside heatwaves. This implies that even though Australian heatwaves are generally characterised by dry conditions, rainfall occurrences within heatwaves are more intense.</p><p>Both heatwaves and extreme rainfall events pose great challenges for many sectors such as agriculture, and especially if they occur together. Understanding how and to what degree these events co-occur could help mitigate the impacts caused by them.</p>

Aggregation of Spatial Extremes

2020 ◽  
Author(s):  
Jordan Richards ◽  
Jonathan Tawn
Keyword(s):  
Extreme Rainfall ◽  
Dependence Structure ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Spatial Extremes ◽  
Catchment Areas ◽  
Wide Range ◽  
Dependent Variables ◽  
Spatio Temporal ◽  
Theoretical Results

<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>

scholarly journals The impact of atmospheric rivers on rainfall in New Zealand

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jingxiang Shu ◽  
Asaad Y. Shamseldin ◽  
Evan Weller
Keyword(s):  
New Zealand ◽  
Austral Summer ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Detection Algorithm ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Atmospheric Rivers ◽  
Hydrological Hazards ◽  
The Impact

AbstractThis study quantifies the impact of atmospheric rivers (ARs) on rainfall in New Zealand. Using an automated AR detection algorithm, daily rainfall records from 654 rain gauges, and various atmospheric reanalysis datasets, we investigate the climatology of ARs, the characteristics of landfalling ARs, the contribution of ARs to annual and seasonal rainfall totals, and extreme rainfall events between 1979 and 2018 across the country. Results indicate that these filamentary synoptic features play an essential role in regional water resources and are responsible for many extreme rainfall events on the western side of mountainous areas and northern New Zealand. In these regions, depending on the season, 40–86% of the rainfall totals and 50–98% of extreme rainfall events are shown to be associated with ARs, with the largest contributions predominantly occurring during the austral summer. Furthermore, the median daily rainfall associated with ARs is 2–3 times than that associated with other storms. The results of this study extend the knowledge on the critical roles of ARs on hydrology and highlight the need for further investigation on the landfalling AR physical processes in relation to global circulation features and AR sources, and hydrological hazards caused by ARs in New Zealand.

scholarly journals Spatio-temporal Variability and Trends of Mean and Extreme Rainfall Events in the Sudano-sahelian Region of Cameroon

2021 ◽  
Author(s):  
Ibrahim NJOUENWET ◽  
Lucie A. Djiotang Tchotchou ◽  
Brian Odhiambo Ayugi ◽  
Guy Merlin Guenang ◽  
Derbetini A. Vondou ◽  
...  
Keyword(s):  
Climate Change ◽  
Extreme Rainfall ◽  
Temporal Variations ◽  
Annual Rainfall ◽  
Drought Risk ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Precipitation Concentration ◽  
Spatio Temporal ◽  
The Impact

Abstract The Sudano-Sahelian region of Cameroon is mainly drained by the Benue, Chari and Logone rivers, which are very useful for water resources, especially for irrigation, hydropower generation, and navigation. Long-term changes in mean and extreme rainfall events in the region may be of crucial importance in understanding the impact of climate change. Daily and monthly rainfall data from twenty-five synoptic stations in the study area from 1980 to 2019 and extreme indices from the Expert Team on Climate Change Detection and Indices (ETCCDI) measurements were estimated using the non-parametric Modified Mann-Kendall test and the Sen slope estimator. The precipitation concentration index (PCI), the precipitation concentration degree (PCD), and the precipitation concentration period (PCP) were used to explore the spatio-temporal variations in the characteristics of rainfall concentrations. An increase in extreme rainfall events was observed, leading to an upward trend in mean annual. Trends in consecutive dry days (CDD) are significantly increasing in most parts of the study area. This could mean that the prevalence of drought risk is higher in the study area. Overall, the increase in annual rainfall could benefit the hydro-power sector, agricultural irrigation, the availability of potable water sources, and food security.

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