scholarly journals Riverbed Migrations in Western Taiwan under Climate Change

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1631 ◽  
Author(s):  
Yi-Chiung Chao ◽  
Chi-Wen Chen ◽  
Hsin-Chi Li ◽  
Yung-Ming Chen

In recent years, extreme weather phenomena have occurred worldwide, resulting in many catastrophic disasters. Under the impact of climate change, the frequency of extreme rainfall events in Taiwan will increase, according to a report on climate change in Taiwan. This study analyzed riverbed migrations, such as degradation and aggradation, caused by extreme rainfall events under climate change for the Choshui River, Taiwan. We used the CCHE1D model to simulate changes in flow discharge and riverbed caused by typhoon events for the base period (1979–2003) and the end of the 21st century (2075–2099) according to the climate change scenario of representative concentration pathways 8.5 (RCP8.5) and dynamical downscaling of rainfall data in Taiwan. According to the results on flow discharge, at the end of the 21st century, the average peak flow during extreme rainfall events will increase by 20% relative to the base period, but the time required to reach the peak will be 8 h shorter than that in the base period. In terms of the results of degradation and aggradation of the riverbed, at the end of the 21st century, the amount of aggradation will increase by 33% over that of the base period. In the future, upstream sediment will be blocked by the Chichi weir, increasing the severity of scouring downstream. In addition, due to the increased peak flow discharge in the future, the scouring of the pier may be more serious than it is currently. More detailed 2D or 3D hydrological models are necessary in future works, which could adequately address the erosive phenomena created by bridge piers. Our results indicate that not only will flood disasters occur within a shorter time duration, but the catchment will also face more severe degradation and aggradation in the future.

2021 ◽  
Author(s):  
Ibrahim NJOUENWET ◽  
Lucie A. Djiotang Tchotchou ◽  
Brian Odhiambo Ayugi ◽  
Guy Merlin Guenang ◽  
Derbetini A. Vondou ◽  
...  

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.


Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 564
Author(s):  
Yung-Ming Chen ◽  
Chi-Wen Chen ◽  
Yi-Chiung Chao ◽  
Yu-Shiang Tung ◽  
Jun-Jih Liou ◽  
...  

Affected by climate change owing to global warming, the frequency of extreme rainfall events has gradually increased in recent years. Many studies have analyzed the impacts of climate change in various fields. However, uncertainty about the scenarios they used is still an important issue. This study used two and four multi-scenarios at the base period (1979–2003) and the end of the 21st century (2075–2099) to collect the top-ranking typhoons and analyze the rainfall conditions of these typhoons in two catchments in northern Taiwan. The landslide-area characteristics caused by these typhoons were estimated using empirical relationships, with rainfall conditions established by a previous study. In addition to counting landslide-area characteristics caused by the typhoons of each single scenario, we also used the ensemble method to combine all scenarios to calculate landslide-area characteristic statistics. Comparing the statistical results of each single scenario and the ensembles, we found that the ensemble method minimized the uncertainty and identified the possible most severe case from the simulation. We further separated typhoons into the top 5%, 5%–10%, and 10%–15% to confirm possible changes in landslide-area characteristics under climate change. We noticed that the uncertainty of the base period and the end of the 21st century almost overlapped if only a single scenario was used. In contrast, the ensemble approach successfully distinguished the differences in both the average values of landslide-area characteristics and the 95% confidence intervals. The ensemble results indicated that the landslide magnitude triggered by medium- and high-level typhoons (top 5%–15%) will increase by 24%–29% and 125%–200% under climate change in the Shihmen Reservoir catchment and the Xindian River catchment, respectively, while landslides triggered by extreme-level typhoons (top 5%) will increase by 8% and 77%, respectively. Still, the uncertainty of landslide-area characteristics caused by extreme typhoon events is slightly high, indicating that we need to include more possible scenarios in future work.


2021 ◽  
Author(s):  
Jun Xie ◽  
Thomas Coulthard

<p>Mass movement such as landslides and rock fall is a prominent source of sediment in active mountain belt. Earthquake triggered landslides can generate substantial loose sediment and have significant geomorphic effects on long term landscape evolution. More importantly, these landslide impacts to land surface vary a lot due to the divergence of landslide characteristics and surrounding environment settings. Downslope and downstream transport of sediment into the channel network is fairly sensitive to climatic perturbations especially for extreme rainfall events. A wide variety of studies attempt to quantify or determine the contribution of landslide generated material to gross sediment budget and the corresponding retention time scale of landslide generated deposit in the mountain basin, whereas no established techniques can explicitly fingerprint/track landslide derived sediment. In this study, we first generated the hourly future extreme rainfall under two emission scenario (RCP4.5, RCP8.5) using ‘NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP)’ dataset. A new tracing function is incorporated into CAESAR-lisflood to track the landslide derived sediment footprint and dynamics in response to climate change. The landscape evolution at the Hongxi catchment, which is suffered tremendous damage from Wenchuan earthquake (Ms 8.0), are then simulated using CAESAR-lisflood under two climate scenarios. The results show that more than 80 percent of material generated by seismic landslides are still retained at the hillslope even after a sufficient time (e.g. 100 year). This study is to compare the spatial-temporal evolution pattern of landslides-derived sediment under two climatic scenarios (RCP4.5, RCP8.5), thus probing into the landslide generated sediment transport and budget respond to the climate change especially the impact of extreme rainfall events. Numerical modelling can provide a quick and effective tool for broad scale predictions of sediment produced by landslide events under different climatic predictions, which is of great importance for seismic induced disaster protection and reduction under climate change.</p>


Geologija ◽  
2021 ◽  
Vol 64 (2) ◽  
pp. 159-171
Author(s):  
Mateja JEMEC AUFLIČ ◽  
Gašper BOKAL ◽  
Špela KUMELJ ◽  
Anže MEDVED ◽  
Mojca DOLINAR ◽  
...  

Slovenia is affected by extreme and intense rainfall that triggers numerous landslides every year, resulting in significant human impact and damage to infrastructure. Previous studies on landslides have shown how rainfall patterns can influence landslide occurrence, while in this paper, we present one of the first study in Slovenia to examine the impact of climate change on landslides in the mid-21st century. To do this, we used the Representative Concentration Pathway (RCP) 4.5 climate scenario and future climatology simulated by six climate models that differed from each other as much as possible while representing measured values of past climate variables as closely as possible. Based on baseline period (1981-2010) we showed the number of days with exceedance of rainfall thresholds and the area where landslides may occur more frequently in the projection period (2041-2070). We found that extreme rainfall events are likely to occur more frequent in the future, which may lead to a higher frequency of landslides in some areas.


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

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.


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