A comprehensive disaster impact assessment of extreme rainfall events under climate change: a case study in Zheng-wen river basin, Taiwan

2016 ◽  
Vol 75 (7) ◽  
Author(s):  
Tingyeh Wu ◽  
Hsin-Chi Li ◽  
Shaio-Pin Wei ◽  
Wei-Bo Chen ◽  
Yung-Ming Chen ◽  
...  
2016 ◽  
Vol 78 (9-4) ◽  
Author(s):  
Mazlina Alang Othman ◽  
Nor Azazi Zakaria ◽  
Aminuddin Ab. Ghani ◽  
Chun Kiat Chang ◽  
Ngai Weng Chan

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


2008 ◽  
Vol 14 (7) ◽  
pp. 1600-1608 ◽  
Author(s):  
PHILIP A. FAY ◽  
DAWN M. KAUFMAN ◽  
JESSE B. NIPPERT ◽  
JONATHAN D. CARLISLE ◽  
CHRISTOPHER W. HARPER

2020 ◽  
Vol 25 (5) ◽  
pp. 05020005
Author(s):  
Taesam Lee ◽  
Chanyoung Son ◽  
Mieun Kim ◽  
Sangeun Lee ◽  
Sunkwon Yoon

2017 ◽  
Vol 8 (3) ◽  
pp. 388-411 ◽  
Author(s):  
Hamed Tavakolifar ◽  
Ebrahim Shahghasemi ◽  
Sara Nazif

Climate change has impacted all phenomena in the hydrologic cycle, especially extreme events. General circulation models (GCMs) are used to investigate climate change impacts but because of their low resolution, downscaling methods are developed to provide data with high enough resolution for regional studies from GCM outputs. The performance of rainfall downscaling methods is commonly acceptable in preserving average characteristics, but they do not preserve the extreme event characteristics especially rainfall amount and distribution. In this study, a novel downscaling method called synoptic statistical downscaling model is proposed for daily precipitation downscaling with an emphasis on extreme event characteristics preservation. The proposed model is applied to a region located in central Iran. The results show that the developed model can downscale all percentiles of precipitation events with an acceptable performance and there is no assumption about the similarity of future rainfall data with the historical observations. The outputs of CCSM4 GCM for two representative concentration pathways (RCPs) of RCP4.5 and RCP8.5 are used to investigate the climate change impacts in the study region. The results show 40% and 30% increase in the number of extreme rainfall events under RCP4.5 and RCP8.5, respectively.


Author(s):  
J. R. Santillan ◽  
A. M. Amora ◽  
M. Makinano-Santillan ◽  
J. T. Marqueso ◽  
L. C. Cutamora ◽  
...  

In this paper, we present a combined geospatial and two dimensional (2D) flood modeling approach to assess the impacts of flooding due to extreme rainfall events. We developed and implemented this approach to the Tago River Basin in the province of Surigao del Sur in Mindanao, Philippines, an area which suffered great damage due to flooding caused by Tropical Storms Lingling and Jangmi in the year 2014. The geospatial component of the approach involves extraction of several layers of information such as detailed topography/terrain, man-made features (buildings, roads, bridges) from 1-m spatial resolution LiDAR Digital Surface and Terrain Models (DTM/DSMs), and recent land-cover from Landsat 7 ETM+ and Landsat 8 OLI images. We then used these layers as inputs in developing a Hydrologic Engineering Center Hydrologic Modeling System (HEC HMS)-based hydrologic model, and a hydraulic model based on the 2D module of the latest version of HEC River Analysis System (RAS) to dynamically simulate and map the depth and extent of flooding due to extreme rainfall events. The extreme rainfall events used in the simulation represent 6 hypothetical rainfall events with return periods of 2, 5, 10, 25, 50, and 100 years. For each event, maximum flood depth maps were generated from the simulations, and these maps were further transformed into hazard maps by categorizing the flood depth into low, medium and high hazard levels. Using both the flood hazard maps and the layers of information extracted from remotely-sensed datasets in spatial overlay analysis, we were then able to estimate and assess the impacts of these flooding events to buildings, roads, bridges and landcover. Results of the assessments revealed increase in number of buildings, roads and bridges; and increase in areas of land-cover exposed to various flood hazards as rainfall events become more extreme. The wealth of information generated from the flood impact assessment using the approach can be very useful to the local government units and the concerned communities within Tago River Basin as an aid in determining in an advance manner all those infrastructures (buildings, roads and bridges) and land-cover that can be affected by different extreme rainfall event flood scenarios.


2018 ◽  
Author(s):  
Ruksana H. Rimi ◽  
Karsten Haustein ◽  
Emily J. Barbour ◽  
Sarah N. Sparrow ◽  
Sihan Li ◽  
...  

Abstract. Anthropogenic climate change is likely to increase the frequency of extreme weather events in future. Previous studies have robustly shown how and where climate change has already changed the risks of weather extremes. However, developing countries have been somewhat underrepresented in these studies, despite high vulnerability and limited capacities to adapt. How additional global warming would affect the future risks of extreme rainfall events in Bangladesh needs to be addressed to limit adverse impacts. Our study focuses on understanding and quantifying the relative risks of seasonal extreme rainfall events in Bangladesh under the Paris Agreement temperature goals of 1.5 °C and 2 °C warming above pre-industrial levels. In particular, we investigate the influence of anthropogenic aerosols on these risks given their likely future reduction and resulting amplification of global warming. Using large ensemble regional climate model simulations from weather@home under different forcing scenarios, we compare the risks of rainfall events under pre-industrial (natural), current (actual), 1.5 °C, and 2.0 °C warmer and greenhouse gas only (anthropogenic aerosols removed) conditions. We find that the risk of a 1 in 100 year rainfall event has already increased significantly compared with pre-industrial levels across parts of Bangladesh, with additional increases likely for 1.5 and 2.0 degree warming (of up to 5.5 times higher, with an uncertainty range of 3.5 to 7.8 times). Impacts were observed during both the pre-monsoon and monsoon periods, but were spatially variable across the country in terms of the level of impact. Results also show that reduction in anthropogenic aerosols plays an important role in determining the overall future climate change impacts; by exacerbating the effects of GHG induced global warming and thereby increasing the rainfall intensity. We highlight that the net aerosol effect varies from region to region within Bangladesh, which leads to different outcomes of aerosol reduction on extreme rainfall statistics, and must therefore be considered in future risk assessments. Whilst there is a substantial reduction in the impacts resulting from 1.5 °C compared with 2 °C warming, the difference is spatially and temporally variable, specifically with respect to seasonal extreme rainfall events.


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