Trends In Extreme Rainfall Events Research Articles

Assessment of extreme rainfall events over the Indian subcontinent during the historical and future projection periods based on CMIP6 simulations

AbstractThe impact of climatic change on the summer monsoon season is studied to understand the rainfall pattern towards the end of the century utilizing the Coupled Model Intercomparison Project, Phase 6 (CMIP6) released by the World Climate Research Programme (WCRP). The analysis of model simulations from CMIP6 was carried out using 64 years of the historical period (1951–2014) and future projections till the end of the century (2015–2100). The models are compared with observed daily rainfall data from the APHRODITE (Asian Precipitation‐Highly‐Resolved Observational Data Integration Towards Evaluation). The analysis revealed that most of the models show an overestimation in the annual cycle of rainfall in the historical period; however, a few of them underestimate the values. The majority of them capture the onset signal of the summer monsoon in early June, along with a good seasonality in the daily rainfall climatology. The simulations that are coherent with the observational data sets are selected on the basis of the Taylor diagram for future projections in four scenarios (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5). The projections of the aforementioned scenarios are taken from the model outputs of EC‐Earth3‐Veg‐LR, INM‐CM4‐8, INM‐CM5‐0, MIROC‐ES2L and MPI‐ESM1‐2‐HR. The selected models exhibit far greater agreement among the 30 models when it comes to the features of rainfall during the summer monsoon. We have given more emphasis on summer monsoon rainfall in the historical and future projection periods since the trends are becoming more chaotic, as reported in observational studies. Over the Indian subcontinent, all of the chosen scenarios show an increased frequency of intense rainfall events with varying decadal and multidecadal features. Central India and west coastal belts are showing positive trends in extreme rainfall events towards the end of the century. At the turn of the century, the southern peninsular region experienced a decline in monsoon precipitation, whereas central India experienced an increase. The severity of rainfall variations during the monsoon season and trends in extremes are increasing as we move from the low‐emission scenario to the high‐emission scenario.

The Temporal Trend Analysis of Extreme Rainfall Events in Ga-West District of Accra, Ghana

The increasing frequency and impacts of flooding in the world have been blamed on global warming and climate change together with other anthropogenic factors. However some studies maintain the recent increase in flooding globally is mainly due to increasing extreme precipitation or rainfalls. In Ghana also, some researchers, technocrats and ordinary people believe that the recent increase in flooding in the city of Accra is resulting from increasing occurrence of extreme rainfall events, attributed to climate change. But this view was contested by other researchers who attributed the increasing flooding events purely to anthropogenic factors. This study, therefore, analyzed the temporal trend of extreme rainfall events from 1970 to 2009 to ascertain whether extreme rainfall events have been increasing significantly over the period under review in Ga West District to warrant the increasing flood events in the study area. A Manual Mann-Kendall Statistical Trend Test Table was used to analyze extreme 24hour maximum rainfall events which were extracted from secondary rainfall data procured from Ghana Meteorological Agency(GMet) for the Airport Weather Station as proxy data. Since the major raining season occurs from April to July in southern Ghana, the annual number of days of these extreme 24hour maximum rainfall events for the four months were extracted from the raw data for each year, from 1970 to 2009 for temporal trend analysis at the p=0.05 level of significance. The hypothesis of the study was as follows: i) Null hypothesis (H 0 ): there was no monotonic trend in the extreme 24-hour maximum rainfall events in the study area. ii) Alternative hypothesis (H 1 ): there was a monotonic trend in the extreme 24hour maximum rainfall events in the study area. The study found that Z=0.0058 which was less than Z (1- p / 2 ) = 1.96 at p=0.05 significant level. The null hypothesis (H 0 ) was, therefore accepted and the alternative hypothesis rejected. The acceptance of the null hypothesis shows that there was no statistically significant increase in extreme 24hour maximum rainfall events in the study area. The study, therefore, concluded that since there was no statistically significant increasing trend in extreme 24 hour maximum rainfall events, extreme rainfall events could not be the reason for the increasing flooding in the study area as some believed, but rather anthropogenic factors, or a combination of both. Keywords : Mann-Kendal statistical trend test, extreme 24hour maximum rainfall, anthropogenic factors, climate change, temporal analysis DOI: 10.7176/JEES/10-12-05 Publication date: December 31 st 2020

Changing Trends in Rainfall Extremes in the Metropolitan Area of São Paulo: Causes and Impacts

This study analyses observed trends in extreme rainfall events in the Metropolitan Area of São Paulo (MASP). Rainfall data sets with more than 60 years of record in MASP are used. In MASP, extreme rainfall events represent hydro meteorological hazards that trigger flash floods and landslides. Changes in rainfall extremes can be partly due to natural climate variability. In addition, it can also be related to global warming and/or urbanization. Total annual precipitation and the number of days with precipitation of 20 mm exhibit the largest significant increase during 1930-2019. This is better noticed during summer. This tendency is also noticed in the number of days with precipitation of 100 mm or more. Therefore, the positive trend in annual precipitation is mainly due to an increase in the frequency of extreme precipitation events. On the other hand, our analysis shows that the number of consecutive dry days increased. Though these results appear to be contradictory, they indicate an important climate change in recent times. Intense precipitation is concentrated in few days, separated by longer dry spells. The focus is on how atmospheric circulation variations are contributing to these changes. During 1960-2019 the South Atlantic Subtropical Anticyclone has intensified and slightly moved southwestward of its normal position. This change influences the transport of humidity and therefore impact precipitation. This can explain the increase in the precipitation extremes in the MASP. However, other atmospheric systems may also be important.

Trends in extreme rainfall and hydrogeometeorological disasters in the Metropolitan Area of São Paulo: a review

Our paper reviews recent progress in the study and understanding of observed trends in extreme rainfall events in the Metropolitan Area of São Paulo (MASP). These are discussed in relation to hydrometeorological hazards that trigger natural disasters, such as flash floods, landslides, and droughts, that affect the population and local economies. A review of the most updated literature on rainfall and extremes in the MASP shows a significant increase in the total volume of rainy-season rainfall during the last seven decades. While there were practically no days with heavy rain (more than 50mm) in the 1950s, these days have been occurring two to five times a year in the last 10 years. This, together with the inappropriate occupation of risky areas, such as slopes and banks of watercourses, leads to inundation, flooding, and landslides. Changes in extremes can be partly due to natural climate variability but can also be related to global warming and/or urbanization. There is ample evidence of an increasing risk of rainfall-related hazards in the MASP. This is particularly so for landslides in vulnerable areas. Exposure will continue to lead to risk increases. This calls for significant improvement in climate and disaster risk reduction and management efforts in the MASP region.

Trend of extreme rainfall events using suitable Global Circulation Model to combat the water logging condition in Kolkata Metropolitan Area

Kolkata Metropolitan Area (KMA) is one of the most densely populated areas in the world, where extreme precipitation events result in frequent waterlogging and flood inundation conditions which can adversely affect the city. In this study, we evaluate the nature and trend of annual-maximum precipitation events by employing suitable Global Circulation Models (GCMs). The trend of observed annual maximum daily rainfall from 1901 to 2013 has been analysed through linear regression, recurrence period and multi-decadal oscillation. The results show that the observed rainfall of the given region follows the natural variability and oscillation trend. TRMM time-series data (2000–2019) is employed to validate the ground-station data series using Modified Mann Kendall and Sen’s Slope estimator test, which shows a correlation of 0.88. In addition, suitable bias-corrected GCMs have been selected to estimate the future precipitation in the given study area. Analysis of future rainfall for the period of 2071–2100 revealed that the RCPs are showing an increase in the extreme precipitation intensity by 1.5, 2.3 and 3 times considering RCP 4.5, 6.0 and 8.5 scenarios respectively. The presented results serve as the preliminary data for future planning and designing efficient flood management strategies in the given area to combat water-logging in KMA.

Trends in extreme rainfall events in Sri Lanka, 1961 - 2010

Many parts of Sri Lanka are vulnerable to extreme rainfall events leading to floods and droughts. This study was focused on a trend analysis of climate extremes derived from daily rainfall records. The daily rainfall data from 13 meteorological stations representing different geographical regions in Sri Lanka for the period 1961–2010 were chosen. The analysis was carried out separately for summer half year (March-August) and winter half year (September-February) to capture the possible changes in two growing seasons, Yala and Maha. Magnitudes of trends were derived using linear regression analysis while the statistical significance was determined using the Mann-Kendall test. Spatial maps were used to study the regional differences in climate extremes. Extreme rainfall events were found to be isolated events without coherent increasing or decreasing trends. However, statistically significant increasing (decreasing) trends were observed for number of dry days (wet days) ranging from 1.1 to 3.1 days/decade in most parts of the island during the summer half year, except for the coastal areas of the dry zone. No increasing or decreasing trends in extremes were observed for the winter half year. Based on the analysis, it was concluded that there is widespread climate change leading to increasing (decreasing) dry days (wet days) during the summer half year receiving rainfall predominantly from the South-West monsoon. However, mixed results were obtained for the winter half year.

The human cost of global warming: Deadly landslides and their triggers (1995–2014)

Worldwide, landslides incur catastrophic and significant economic and human losses. Previous studies have characterized the patterns in landslides' fatalities, from all kinds of triggering causes, at a continental or global scale, but they were based on data from periods of <10 years. The research herein presented hypothesizes that climate change associated with extreme rainfall and population distribution is contributing to a higher number of deadly landslides worldwide. This study maps and identified deadly landslides in 128 countries and it encompasses their role, for a 20 years' period from January/1995 to December/2014, considered representative for establishing a relationship between landslides and their meteorological triggers. A database of georeferenced landslides, their date, and casualties' information, duly validated, was implemented. A hot spot analysis for the daily record of landslide locations was performed, as well as a percentile-based approach to evaluate the trend of extreme rainfall events for each occurrence. The relationship between casualty, population distribution, and rainfall was also evaluated. For 20 years, 3876 landslides caused a total of 163,658 deaths and 11,689 injuries globally. They occurred most frequently between June and December in the Northern Hemisphere, and between December and February in the Southern Hemisphere. A significant global rise in the number of deadly landslides and hotspots across the studied period was observed. Analysis of daily rainfall confirmed that more than half of the events were in areas exposed to the risk of extreme rainfall. The relationships established between extreme rainfall, population distribution, seasonality, and landslides provide a useful basis for efforts to model the adverse impacts of extreme rainfall due to climate change and human activities and thus contribute towards a more resilient society.

Assessing climatic trends of extreme rainfall indices over northeast Bangladesh

This study analyzes the trends of extreme rainfall indices over northeast Bangladesh for the period of 1984 to 2016 for the pre-monsoon and monsoon seasons. The research was framed as part of a project co-producing knowledge of climate variability and impacts through collaboration between scientific and local communities in northeast Bangladesh, which found pre-monsoon and monsoon rainfall to be most important. With access to a greater number of rainfall stations than previous work in northeast Bangladesh, we investigated trends in extreme rainfall events using the Mann–Kendall trend test and Sen’s slope estimator. To appraise the quality of the data, we used the Standard Normal Homogeneity and the Pettitt tests to check its homogeneity. Among the seven stations, only Sunamganj was found inhomogeneous, and was not considered for trend analysis. All indices of rainfall extremes showed a decreasing trend in both seasons, with the most significant decrease during the monsoon. Importantly, we saw a decreasing trend in the seasonal total rainfall and consecutive wet days, whereas there was an increasing trend in consecutive dry days. Moreover, we saw a decreasing trend in 1-day maximum rainfall, 5-day maximum rainfall, the intensity of the daily rainfall over 25 mm during the pre-monsoon and 50 mm during monsoon, which together may indicate a future decrease in the magnitude and intensity of flash floods and monsoon floods. If this trend continues, the northeast Bangladesh may suffer from water stress, which could affect the lives and livelihoods of communities living there.

A Rainfall Intensity-Duration Threshold for Mass Movement in Badulla, Sri Lanka

Mass movement in Sri Lanka is mainly triggered by heavy rainfall. International literature is rich of works defining rainfall intensity-duration models to identify the rainfall threshold for various types of Mass movement. However, studies have not focused to establish a relationship between intensity and duration of rainfall in Sri Lanka. Therefore, this study focused to establish rainfall intensity-duration models to identify the rainfall threshold for mass movements in Badulla district in Sri Lanka, where forty four (44) rainfall events that resulted in same number of landslides during the last three decades were considered. Results indicate the rainfall threshold relationship fits to the log linear model of the exponential function, I = α&#183D-β. The constructed I-D curve revealed that short duration ( 54 mm/h) in rainfall events can potentially trigger the landslide. However, long-duration (>8 h) and low-intensity (<25 mm/h) in rainfall events may also trigger mass movements in Badulla. As per the results, most mass movements occur during northeast monsoons and inter-monsoons. In general, higher mean rainfall intensities trigger the debris flows, while long-duration rainfall events can trigger both landslides and debris flow. When compared to Sri Lankan mass movements triggering threshold intensities are fairly higher than the global threshold values. It confirms that within Badulla, mass movements are triggered by very high intense and/or long duration rainfalls events only. Further, time series analysis of the rainfall events shows an upward trend of extreme rainfall events, which increased landslide occurring frequency in last six (6) years.

A new approach to temporal modelling for landslide hazard assessment using an extreme rainfall induced-landslide index

An ever-increasing trend of extreme rainfall events in South Korea due to climate change is causing shallow landslides and shallow landslide induced debris flows in the mountains that cover 70% of the total land area of the nation. These catastrophic, gravity-driven processes cost the government several billion won in losses, and attendant fatalities, every year. The most common type of landslide observed is the shallow landslide occurring at 1–3m depth, which may mobilize into a catastrophic debris flow. A landslide early warning system encompassing different scale-based stages is used to predict potential areas for both the landslide types. Current study focusing on the first stage landslide hazard assessment at regional or medium scale requires the development of spatially evolving landslide hazard maps for both types of landslides based on the real-time rainfall. However, lack of complete landslide inventory data motivates the development of temporal and spatial models as independent components of the landslide hazard. Most of the existing temporal assessment schemes traditionally rooted in recurrence-based concepts does not consider soil factors and are not suitable to be incorporated in to the landslide early warning system since real-time rainfall cannot be considered. This motivated the development of a new probabilistic temporal model termed the extreme rainfall-induced landslide index. The probabilistic index was developed in Gangwon Province through a logistic regression using four factors; namely, continuous rainfall, 20-days antecedent rainfall, saturated hydraulic conductivity, and storage capacity. The developed model exhibited high area under the curve (AUC) values of 82% and 91% obtained for the training and validation curves, exhibiting good performance of the statistical index. Also, a high performance susceptibility model (training and validation AUC values of 96% and 94%, respectively) was developed using a logistic regression analysis, for Deokjeok-ri Creek, located in Gangwon province. Assuming the independence of the hazard components, a dynamic hazard index (DHI) was established through a joint probability of both the well validated models. The DHI was used to study the evolution of landslide hazard for the July 2006 extreme rainfall-induced landslide events in Deokjeok-ri Creek.

ANALYSIS OF TRENDS OF EXTREME RAINFALL EVENTS USING MANN KENDALL TEST: A CASE STUDY IN PAHANG AND KELANTAN RIVER BASINS

Climate change leads to changes in rainfall and extreme event. This phenomenon has already begun to transform the rainfall patterns in Malaysia. It was clearly proven when the northern and eastern states of Peninsular Malaysia such as Kelantan, Terengganu, Pahang, Perak and Johor were hit by the catastrophic floods in December 2014, events that have been described as the worst in decades. Although there are a number of studies in climate change and extreme rainfall events in Malaysia, there are still large knowledge gaps about their relationship. Understanding the shifts and predicting changing trends in rainfall distribution is needed for predicting and managing the floods. In this paper, Mann Kendall (MK) test and Sen's Slope estimator are employed to determine the trend of extreme rainfall events of various storm durations in the Pahang and Kelantan river basins. The results indicate that annual maximum daily rainfall for Pahang River basin and Kelantan River basin increased throughout 45 years. Results show that the percentage of stations with statistically significant trend (at 0.05 significance level) in the Kelantan River basin are higher compared to the Pahang River basin. Percentage of stations showing increasing trends were much higher for short duration rainfall (10, 30 and 60 minutes and 3 hours) compared to long duration rainfall (6, 12, 24, 48, 120 and 240 hours). This study will be useful for planning, designing and managing floods and stormwater systems in this area

Trend Analysis for Extreme Rainfall at Sub-Daily and Daily Timescales in Côte d’Ivoire

Extreme rainfall events are meteorological hazards that cause great damage and many casualties in the world. This paper examines the trends in extreme rainfall from 10 sub-daily time series and 44 daily time series in Côte d’Ivoire. Rainfall data were converted into indices. In total, six (6) indices were used for daily extreme rainfall and one (1) index for sub-daily extreme rainfall (15 to 240 min). Two statistical tests for trend detection were used to evaluate the possible trend in these precipitation data. The first is a Mann-Kendall non-parametric trend test, used to evaluate the existence of monotonic trends. The second is a linear regression method, based on a parametric approach to trend detection. Results show that very few statistically significant decreasing trends can be detected at the sub-daily and daily timescales. Some decreasing trends in extreme rainfall events were localized in the south and southeast. These results could enhance the implementation of adaptation systems to flood risk.

A hybrid feature selection algorithm integrating an extreme learning machine for landslide susceptibility modeling of Mt. Woomyeon, South Korea

An ever-increasing trend of extreme rainfall events in South Korea owing to climate change is causing shallow landslides and debris flows in mountains that cover 70% of the total land area of the nation. These catastrophic, gravity-driven processes cost the government several billion KRW (South Korean Won) in losses in addition to fatalities every year. The most common type of landslide observed is the shallow landslide, which occurs at 1–3m depth, and may mobilize into more catastrophic flow-type landslides. Hence, to predict potential landslide areas, susceptibility maps are developed in a geographical information system (GIS) environment utilizing available morphological, hydrological, geotechnical, and geological data. Landslide susceptibility models were developed using 163 landslide points and an equal number of nonlandslide points in Mt. Woomyeon, Seoul, and 23 landslide conditioning factors. However, because not all of the factors contribute to the determination of the spatial probability for landslide initiation, and a simple filter or wrapper-based approach is not efficient in identifying all of the relevant features, a feedback-loop-based hybrid algorithm was implemented in conjunction with a learning scheme called an extreme learning machine, which is based on a single-layer, feed-forward network. Validation of the constructed susceptibility model was conducted using a testing set of landslide inventory data through a prediction rate curve. The model selected 13 relevant conditioning factors out of the initial 23; and the resulting susceptibility map shows a success rate of 85% and a prediction rate of 89.45%, indicating a good performance, in contrast to the low success and prediction rate of 69.19% and 56.19%, respectively, as obtained using a wrapper technique.

Trends in Extreme Rainfall Events in Tasmania, Australia

Trends in Extreme Rainfall Events in Tasmania, Australia

Trends in Extreme Rainfall Events in Tasmania, Australia

Trends in Extreme Rainfall Events in Tasmania, Australia

Trends in Extreme Rainfall Events in Tasmania, Australia

Trends in Extreme Rainfall Events in Tasmania, Australia

Trends in Extreme Rainfall Events in Tasmania, Australia

Trends in Extreme Rainfall Events in Tasmania, Australia

Trends in Extreme Rainfall Events in Tasmania, Australia

Trends in Extreme Rainfall Events in Tasmania, Australia

Trends in Extreme Rainfall Events in Tasmania, Australia

Trends in Extreme Rainfall Events in Tasmania, Australia

Trends in Extreme Rainfall Events in Tasmania, Australia

Trends in Extreme Rainfall Events in Tasmania, Australia