Spatiotemporal analysis of precipitation trends during 1961–2010 in Hubei province, central China

Wang, Ranghui; Li, Cheng

doi:10.1007/s00704-015-1426-x

Cited by 37 publications

(20 citation statements)

References 34 publications

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“…It has been widely used to quantify heat waves, drought, torrential and accumulated precipitation amount (e.g. Skansi et al 2013, Stephenson et al 2014, Wang and Li 2015).…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, we used the Pettitt test (Pettitt 1979) to detect abrupt change points in the time series of precipitation and indexes. A similar approach has been applied to identify regional trends and change points in Asia , Duan et al 2015, Wang and Li 2015.…”

Section: Methodsmentioning

confidence: 99%

“…The number of reported extreme precipitation and related flood events has increased significantly over the last twenty years (Tanoue et al 2016, Silva Dias et al 2013, Boers et al 2014, Espinoza et al 2014. Mountainous areas have different characteristics (e.g., shape, extension, altitude, and vegetation cover), and vary greatly among climate regimes both spatially and temporally (Beniston 2003, Kohler and Maselli 2009, Skansi et al 2013, Tramblay et al 2013, Stephenson et al 2014, Wang and Li 2015.…”

Section: Introductionmentioning

confidence: 99%

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Recent precipitation trends, flash floods and landslides in southern Brazil

Ávila

Justino

Wilson

et al. 2016

Environ. Res. Lett.

113

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In order to understand the rising number of flash floods and landslides in the densely populated region of southeastern Brazil, this study analyzes the spatial and temporal changes in precipitation from 1978 to 2014. We focus on the sensitivity of mountainous regions, specifically the Rio de Janeiro (RJMR) and Santa Catarina (SCMR) regions. Daily rainfall observations are aggregated into annual and seasonal indexes, and RClimdex is used to evaluate a suite of precipitation and extreme event indexes. Results show positive annual and seasonal precipitation trends during all seasons except for the winter season in the RJMR. Diverse change points in their time series, spatial differences in the trends at individual stations, and trends associated with elevation suggest that despite the close proximity of these two regions, climate impacts are not uniform across all of southeastern Brazil. The majority of precipitation-related indexes present positive trends, especially in the extreme precipitation indexes (PRCPTOT, RX1day, Rx5day and R30 mm). Statistically significant positive correlations are discovered between landslides/flash floods events and annual maximum 1-day and 5-day consecutive precipitation, and these indexes may be useful indicators of natural hazard events for this region.

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“…It has been widely used to quantify heat waves, drought, torrential and accumulated precipitation amount (e.g. Skansi et al 2013, Stephenson et al 2014, Wang and Li 2015).…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Recent precipitation trends, flash floods and landslides in southern Brazil

Ávila

Justino

Wilson

et al. 2016

Environ. Res. Lett.

113

View full text Add to dashboard Cite

show abstract

“…Finally, a quality control evaluation and a homogeneity assessment of daily precipitation data were performed using the software packages RclimDex and RHtests V4 (http://etccdi.pacificclimate.org/software.shtml). These two programs have been widely used in the quality control, homogenization, and extreme index classification of precipitation data [12,[34][35][36][37][38]. The processes of quality control evaluation and homogeneity assessment include (1) identifying errors in the precipitation data, such as precipitation values below 0 mm; (2) searching for outliers, where we choose 3 standard deviations as the threshold for a fineresolution quality control of the data; (3) using plots of generalized data in RclimDex to visually inspect the data and further identify outliers and a variety of other problems that may cause errors or bias in analysing changes in the seasonal cycles or variance of the data; and (4) using RHtestsV3 to detect artificial shifts that could exist in a time series.…”

Section: Study Region and Data Sourcesmentioning

confidence: 99%

Spatial and Temporal Variability in the Precipitation Concentration in the Upper Reaches of the Hongshui River Basin, Southwestern China

Huang

Wang

Xiao

et al. 2018

Advances in Meteorology

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The statistical characteristics of precipitation play important roles not only in flood and drought risk assessments but also in water resource management. This paper implements a statistical analysis to study the spatial and temporal variability in precipitation in the upper reaches of the Hongshui River basin (UHRB), southwestern China, by analysing time series of daily precipitation from 18 weather stations during the period of 1959 to 2015. To detect precipitation concentrations and the associated patterns, three indices, the precipitation concentration index (PCI), precipitation concentration degree (PCD), and precipitation concentration period (PCP), were used. The relationships between the precipitation concentration indices (PCI, PCD, and PCP) and geographic variables (latitude, longitude, and elevation), large-scale atmospheric circulation indices, and summer monsoon indices were investigated to identify specific dependencies and spatial patterns in the precipitation distribution and concentration. The results show that high PCI values were mainly observed in the northeastern portion of the basin, whereas low PCI values were mainly detected in the southwest. The Mann-Kendall test results demonstrate that the majority of the UHRB is characterized by nonsignificant trends in the PCI, PCD, and PCP from 1959 to 2015. The PCP results reveal that rainfall in the UHRB mainly occurs in summer months, and the rainy season arrives earlier in the eastern UHRB than in the western UHRB. Additionally, the PCD results indicate that the rainfall in the western UHRB is more dispersed throughout the year than that in the eastern UHRB. Compared with other geographical factors, longitude is the most important variable that governs the spatial distribution and variations in annual precipitation and the precipitation concentration indices. Due to a combination of topography, the Indian subtropical high, and monsoon weakening, precipitation may be more concentrated in one period, especially in the eastern part of the basin, which increases the risk of drought.

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“…The Pettitt test can not only judge the location and number of the abrupt change, but also estimate the significance of the abrupt change [18,44]. The Pettitt test is considered as a powerful and useful method for obtaining the abrupt change points in characterizing the trends of climate data [23]. The test statistic U t,n is given by:…”

Section: Coefficients Of Variationmentioning

confidence: 99%

Variability of Spatially Grid-Distributed Precipitation over the Huaihe River Basin in China

Yan

et al. 2017

Water

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This study investigates spatial characteristics of annual and decadal precipitation in the Huaihe River basin. Daily precipitation data, obtained from meteorological gauges, are analyzed for a 51-year period, from 1961 to 2011. Precipitation is analyzed in grids (5 km 2 ) with respect to temporal variability. The spatial distribution and intensity of annual rainfall (mm/10 year), determined by the linear regression method, reveals a slight increase of 3 mm/10 year over the basin. However, the trend did not present a significant change at 95% significance level in the most of basin. Precipitation is mostly increasing for each ten-year periods during the total 51 years. The annual precipitation randomicity was calculated from the non-uniform coefficient Cv (coefficient of variation) test and showed a significant non-uniform spatial distribution, indicating that randomicity of annual rainfall was the moderate variability. The Pettitt test determined that the abrupt change points occurred mainly in 1965, 1975 and 2002. Wavelet analysis showed that cyclic variations appeared almost every 5 to 10 years, accounting for 36% of the basin area. Meanwhile, these cycles tended to be delimited by the abrupt change points. This study aims to provide insights for water resources management, mitigation of climate change effects and water supply in the Huaihe River basin and surrounding watersheds.

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Spatiotemporal analysis of precipitation trends during 1961–2010 in Hubei province, central China

Cited by 37 publications

References 34 publications

Recent precipitation trends, flash floods and landslides in southern Brazil

Recent precipitation trends, flash floods and landslides in southern Brazil

Spatial and Temporal Variability in the Precipitation Concentration in the Upper Reaches of the Hongshui River Basin, Southwestern China

Variability of Spatially Grid-Distributed Precipitation over the Huaihe River Basin in China

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