Daily Precipitation Changes over Large River Basins in China, 1960–2013

Lv, Aifeng; Jia, Shaofeng; Zhu, Wenxiang

doi:10.3390/w8050185

Cited by 16 publications

(11 citation statements)

References 44 publications

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“…Using the precipitation grid surface, the spatio-temporal analysis of precipitation occurrence frequency, mean precipitation depth and total precipitation depicts a significant decreasing trend of precipitation frequency, significant increasing trends of precipitation intensity, and a small upward trend in annual total precipitation over China, which is consistent with the result from previous researches at a national scale [29][30][31] . Though the results from previous studies showed consistent varying tendency and similar spatial distributions with the results in this www.nature.com/scientificreports www.nature.com/scientificreports/ work, there are a lot of discrepancies exists in the quantitative analysis and spatial distributions of rainfall.…”

Section: Discussionsupporting

confidence: 88%

Long-term spatio-temporal precipitation variations in China with precipitation surface interpolated by ANUSPLIN

Guo

Zhang

Meng

et al. 2020

Sci Rep

108

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Climate changes significantly impact environmental and hydrological processes. Precipitation is one of the most significant climatic parameters and its variability and trends have great influences on environmental and socioeconomic development. We investigate the spatio-temporal variability of precipitation occurrence frequency, mean precipitation depth, PVI and total precipitation in China based on long-term precipitation series from 1961 to 2015. As China's topography is diverse and precipitation is affected by topography strongly, ANUSPLIN can model the effect of topography on precipitation effectively is adopted to generate the precipitation interpolation surface. Mann-Kendall trend analysis and simple linear regression was adopted to examine long-term trend for these indicators. The results indicate ANUSPLIN precipitation surface is reliable and the precipitation variation show different regional and seasonal trend. For example, there is a sporadic with decreasing frequency precipitation trend in spring and a uniform with increasing frequency trend in summer in Yangtze Plain, which may affect spring ploughing and alteration of flood risk for this main rice-production areas of China. In northwestern China, there is a uniform with increasing precipitation frequency and intensity trend, which is beneficial for this arid region. Our study could be helpful for other counties with similar climate types. Climate changes, including change in regional precipitation pattern, have modified hydrological processes and will continue to reshape the hydrology. Precipitation is an important meteorological parameter, and is a key player in regional hydrological processes 1,2. It is an important natural source of water for vegetation, especially in dry regions, and its variability and trends have great influences on plant growth and crop production. Variation in total quantity and temporal variability of precipitation has significant effect on soil water supply, water stress as well as metabolic and physiological functions of vegetation, further determined the impact of precipitation variability on ecosystem structure 3. It is of practical interest to access how climate changes have altered precipitation spatially and temporally and therefore to improve our insight into precipitation variability analyses. Gauge-based precipitation is the main data source for precipitation. However, in situ precipitation data of rain gauge station are not always available. As precipitation measurements are scarce and the measuring stations are distributed unevenly in space, the rain gauge network might be inefficient in demonstrating the spatial distribution of precipitation and capturing precipitation events completely. Consequently, interpolation is introduced to examine the spatial distribution of precipitation. To assess the spatial variability and trends of precipitation indicators, the procedures of spatial interpolation broadly included two strategies, interpolating of the station indices directly and interpolating of the precipitation a...

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Section: Discussionsupporting

confidence: 88%

Long-term spatio-temporal precipitation variations in China with precipitation surface interpolated by ANUSPLIN

Guo

Zhang

Meng

et al. 2020

Sci Rep

108

View full text Add to dashboard Cite

show abstract

“…While previous researchers have studied changes in precipitation in the SRYR, they mostly focused on changes in average precipitation. Overall, the annual average precipitation in the SRYR increased at a rate of 11.4 mm/decade between 1957-2013 [26], which was greater than the rates at which the annual average precipitation increased on the Tibetan Plateau (3.8 mm/decade in 1961-2015 [30]) and in China (1.10 mm/decade in the period 1960-2013 [31]) increased. In addition, changes in precipitation in the SRYR also exhibit different characteristics on different temporal and spatial scales [32,33].…”

Section: Introductionmentioning

confidence: 78%

Analysis of Precipitation Extremes in the Source Region of the Yangtze River during 1960–2016

Zhou

Liang

Zhao

et al. 2018

Water

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The source region of the Yangtze River (SRYR) on the central Tibetan Plateau has seen one of the most significant increases in temperature in the world. Climate warming has altered the temporal and spatial characteristics of precipitation in the SRYR. In this study, we analyzed the temporal trends and spatial distributions of extreme precipitation in the SRYR during 1960–2016 using 11 extreme precipitation indices (EPIs) derived from daily precipitation data collected at five meteorological stations in the region. The trends in the EPIs were estimated using the linear least squares method, and their statistical significance was assessed using the Mann–Kendall test. The results show the following. Temporally, the majority of SRYR EPIs (including the simple daily intensity index, annual maximum 1-day precipitation (RX1day), annual maximum 5-day precipitation (RX5day), very wet day precipitation, extremely wet day precipitation, number of heavy precipitation days, number of very heavy precipitation days, and number of consecutive wet days) exhibited statistically nonsignificant increasing trends during the study period, while annual total wet-day precipitation (PRCPTOT) and the number of wet days exhibited statistically significant increasing trends. In addition, the number of consecutive dry days (CDD) exhibited a statistically significant decreasing trend. For the seasonal EPIs, the PRCPTOT, RX1day, and RX5day all exhibited nonsignificant increasing trends during the wet season, and significant increasing trends during the dry season. Spatially, changes in the annual and wet season EPIs in the study area both exhibited significant differences in their spatial distribution. By contrast, changes in dry season PRCPTOT, RX1day, and RX5day exhibited notable spatial consistency. These three indices exhibited increasing trends at each station. Moreover, there was a statistically significant positive correlation between the annual PRCPTOT and each of the other EPIs (except CDD). However, the contribution of extreme precipitation to annual PRCPTOT exhibited a nonsignificant decreasing trend.

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“…Following Liu et al [ 50 ], a precipitation event during the rainy season is defined as a day with daily precipitation ≥0.1 mm. Based on CMA standards, daily precipitation is classified into four grades: very heavy ( p ≥ 50 mm), heavy (25 ≤ p < 50 mm), moderate (10 ≤ p < 25 mm), light (0.1 ≤ p < 10 mm) [ 31 , 51 ]. The number of precipitation days and precipitation amount are generally applied to describe the precipitation characteristics in this study.…”

Section: Methodsmentioning

confidence: 99%

Observed Changes of Rain-Season Precipitation in China from 1960 to 2018

Zhang

Zang

Shen

et al. 2021

IJERPH

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Precipitation during the main rain season is important for natural ecosystems and human activities. In this study, according to daily precipitation data from 515 weather stations in China, we analyzed the spatiotemporal variation of rain-season (May–September) precipitation in China from 1960 to 2018. The results showed that rain-season precipitation decreased over China from 1960 to 2018. Rain-season heavy (25 ≤ p < 50 mm/day) and very heavy (p ≥ 50 mm/day) precipitation showed increasing trends, while rain-season moderate (10 ≤ p < 25 mm/day) and light (0.1 ≤ p < 10 mm/day) precipitation showed decreasing trends from 1960 to 2018. The temporal changes of precipitation indicated that rain-season light and moderate precipitation displayed downward trends in China from 1980 to 2010 and rain-season heavy and very heavy precipitation showed fluctuant variation from 1960 to 2018. Changes of rain-season precipitation showed clear regional differences. Northwest China and the Tibetan Plateau showed the largest positive trends of precipitation amount and days. In contrast, negative trends were found for almost all precipitation grades in North China Plain, Northeast China, and North Central China. Changes toward drier conditions in these regions probably had a severe impact on agricultural production. In East China, Southeast China and Southwest China, heavy and very heavy precipitation had increased while light and moderate precipitation had decreased. This result implied an increasing risk of flood and mudslides in these regions. The advance in understanding of precipitation change in China will contribute to exactly predict the regional climate change under the background of global climate change.

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Daily Precipitation Changes over Large River Basins in China, 1960–2013

Cited by 16 publications

References 44 publications

Long-term spatio-temporal precipitation variations in China with precipitation surface interpolated by ANUSPLIN

Long-term spatio-temporal precipitation variations in China with precipitation surface interpolated by ANUSPLIN

Analysis of Precipitation Extremes in the Source Region of the Yangtze River during 1960–2016

Observed Changes of Rain-Season Precipitation in China from 1960 to 2018

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