Spatiotemporal Variations of Extreme Precipitation under a Changing Climate in the Three Gorges Reservoir Area (TGRA)

Lü, Mingquan; Jiang, Yi; Chen, Xunlai; Chen, Ji‐Long; Wu, Shengjun; Jun, Liu

doi:10.3390/atmos9010024

Cited by 15 publications

(11 citation statements)

References 60 publications

(51 reference statements)

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“…It has no limitation of the data set distribution; therefore, it can be applied to data with missing values or non‐normal distributions without being affected by the outliers. Such advantages make MK test one of the most commonly used methods to investigate temporal trends in hydroclimate parameters (Su et al ., 2006; Modarres and Sarhadi, 2009; Lupikasza, 2010; Ahani et al ., 2012; Bartolomeu et al ., 2016; Lü et al ., 2018; Rahimi and Hejabi, 2018). However, in order to eliminate the influence of significant autocorrelation in the series of data, the researchers employed the modified MK test, in which the series were prewhitened (Jahani et al ., 2018).…”

Section: Methodsmentioning

confidence: 99%

“…A total of 11 popular extreme indices are defined by Expert Team on Climate Change Detection and Indices (ETCCDI; Zhang et al ., 2011). They have been widely used to assess extreme precipitation and have helped to quantify the variability and impact of extreme events (Frei et al ., 2006; Zhang et al ., 2011; Tramblay et al ., 2013; Bohlinger and Sorteberg, 2018; Kim et al ., 2018; Lü et al ., 2018; Mahbod et al ., 2019). These indices are based on either frequency or intensity.…”

Section: Introductionmentioning

confidence: 99%

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Trend analysis of extreme precipitation events across Iran using percentile indices

Mahbod

Rafiee

2020

Intl Journal of Climatology

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Although a number of studies have been conducted on extreme precipitation trends in different parts of the world including Iran, a great number of such studies have reported only the total amount of daily precipitation greater than a certain percentage (e.g., 95%) of the long term data (R95p), ignoring other useful indices. To address this research gap, we used other modified indices, namely R95tot (fractional contribution of very wet days to annual total amounts), R95tt (fractional contribution of very wet days to the total annual obtained from fitted gamma probability distribution), and RS95 (same as R95tt except that it uses Weibull distribution and very wet days defined by 95 percentage of an individual year) by which the spatial and temporal changes of very wet days across Iran was assessed, 1985–2013. In addition, to evaluate the effect of the selected distribution on the results, a new index‐(RS95gm)—was introduced and reported. This index is similar to RS95, except that it uses gamma distribution instead of Weibull. According to trend analysis of R95p, R95tot, and R95tt, reduced frequency of extreme precipitation events was detected in some northwest, west and northeast parts of Iran. On the contrary, RS95 (RS95gm) results showed a higher frequency of extreme events across Iran. It was also demonstrated that while R95p, R95tot, and R95tt were unequivocally affected by changes in the mean wet‐day/ annual total precipitation, RS95 (RS95gm) was more influenced by changes in the distributional shape, showing more stable trends. Although RS95 and RS95gm were highly correlated with only 19% difference on average, their trend analysis results were not completely consistent (70% agreement). Thus, it may be concluded that any changes in statistical distribution in the calculation of the RS95 would have a considerable effect on whether the obtained trend is significant or not.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Trend analysis of extreme precipitation events across Iran using percentile indices

Mahbod

Rafiee

2020

Intl Journal of Climatology

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“…With the precipitation conditions in the Three Gorges Reservoir area changing in recent years (Zhao and Shepherd 2012;Li et al 2011;Lü et al 2018), some landslides in the reservoir area have also "woken up" during the "sleeping period." For instance, the Dahe landslide in Wuxi County, Chongqing Province, occurred on October 21, 2017 (the volume was approximately 6,000,000 m 3 , and 9 people were missing), and the Yanguan landslide in Zigui County, Yichang City, occurred in the Three Gorges Reservoir area on October 27, 2017 (the volume was approximately 2,100,000 m 3 , and no casualties were reported).…”

Section: Introductionmentioning

confidence: 99%

Effect of climate change induced extreme precipitation on landslide activity in the Three Gorges Reservoir, China

Zhu

Song

et al. 2020

Bull Eng Geol Environ

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Climate change has caused an increase in extreme rainfall and snowfall in many parts of the world. For example, in the Three Gorges Reservoir area, annual precipitation has gradually increased and the occurrence of heavy precipitation events has become more frequent. As the reservoir water level rises in October, the high water combined with heavy precipitation creates a "special hydrological environment," which recently caused the Yanguan landslide. The Yanguan landslide is a large-scale soil landslide that has undergone two slides, pushed the Yanguan Road Bridge into the reservoir, and caused serious damage to roads and buildings. In the present study, the combined effects of high water and heavy precipitation on landslide deformation characteristics (movement patterns and evolution processes) have been analyzed and a stability evaluation was conducted through a field investigation and numerical simulation. To comparatively analyze these combined effects of high water and heavy precipitation, a two-dimensional finite element model was created, and four cases of the hydrological environment were calculated with the model. Results show that the factor of safety was maintained in the range of 1.013 to 1.059 before the precipitation conditions changed. However, as heavy precipitation increased in October 2017 (reaching 356.4 mm in 1 month), this "special hydrological environment" potentially decreased the FoS to 0.948, which is 9.6% lower than that observed under normal conditions, and helped drive the Yanguan landslide activity. The analysis of these various combined effects can also indicate the impacts of climate change on landslides in other areas of the Three Gorges Reservoir.

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“…On the other hand, the precipitation changes in the TGRR as induced by TGD are mainly investigated through station measurements, satellite datasets, and numerical simulations. For instance, Lü et al (2018) identified an increasing trend of extreme precipitation during 1959-2013 in the TGRR based on weather station data and the Tropical Rainfall Measuring Mission (TRMM) dataset. With the hypothesis of relatively local impacts, they concluded that the TGD has no detectable influence on extreme precipitation in the TGRR.…”

mentioning

confidence: 99%

“…This study also suggested that the climate effect of the TGD is on regional scale (~100 km) rather than on local scale (~10 km) as found in previous studies. In general, the long-term impact of the TGD on the TGRR precipitation is relatively weak, as suggested by both observational data and numerical simulations (Miller et al, 2005;Li et al, 2017;Lü et al, 2018), and is likely dominated by the interannual (natural) climate variability (Xiao et al, 2010;Li et al, 2017). However, considering the dynamic interplay between local impacts and regional/global climate change, detecting the underlying drivers of TGRR rainfall change based solely on local or regional precipitation data can be very challenging.…”

mentioning

confidence: 99%

Moisture sources contribute to precipitation change in the Three Gorges Reservoir Region during 1979–2015

Li¹,

Wang²,

Hui³

et al. 2020

Preprint

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Abstract. Precipitation change in the Three Gorges Reservoir Region (TGRR) plays a critical role in the operation and regulation of the Three Gorges Dam (TGD) as well as the protection of residents and properties. The potential impacts of the TGD on local and regional circulation patterns, especially the precipitation patterns, have received considerable attention since its construction. However, how the moisture transport affects the precipitation change in the TGRR spatially and temporally remains obscure. In this study, we investigate the long-term moisture sources of precipitation as well as their contributions to the precipitation change over the TGRR using an atmospheric moisture tracking model. Results suggest that although with seasonal variation, the moisture contributing to the TGRR precipitation primarily originate from the areas southwest of the TGRR dominated by the Indian summer monsoon. In particular, the sources with the highest annual moisture contribution are the southwestern part of the Yangtze River Basin and the southeastern tip of the Tibetan Plateau (TP). On average, 41 %, 56 %, and 3 % of the TGRR precipitation originate from ocean, land, and local recycling, respectively. In addition, the decreased precipitation over the TGRR during 1979–2015 is mainly attributed to the significantly decreased moisture contribution from the source regions southwest of the TGRR (especially around the southeastern tip of the TP). Compared to dry years, the higher precipitation in the TGRR during wet years is contributed by the extra moisture from the southwestern source regions delivered by the intensified southwesterly monsoon winds.

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Spatiotemporal Variations of Extreme Precipitation under a Changing Climate in the Three Gorges Reservoir Area (TGRA)

Cited by 15 publications

References 60 publications

Trend analysis of extreme precipitation events across Iran using percentile indices

Trend analysis of extreme precipitation events across Iran using percentile indices

Effect of climate change induced extreme precipitation on landslide activity in the Three Gorges Reservoir, China

Moisture sources contribute to precipitation change in the Three Gorges Reservoir Region during 1979–2015

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