Trend Analysis of Rainfall Time Series in Shanxi Province, Northern China (1957–2019)

Gao, Feng; Wang, Yunpeng; Chen, Xiaoling; Yang, Wu

doi:10.3390/w12092335

Cited by 29 publications

(29 citation statements)

References 67 publications

(107 reference statements)

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“…The H o describes that the whole time series data are independent and equally distributed. Opposite to this, the H 1 confirms the existence of a rising or declining trend in the time series rainfall data (Gao et al 2020). The SR test (D) and the standardized test Z SR are numerically derived as;…”

Section: Spearman's Rho (Sr) Trend Testmentioning

confidence: 70%

Trend analysis of historical and future precipitation projections over a diverse topographic region of Khyber Pakhtunkhwa using SDSM

Rahman

Munawar

et al. 2022

Journal of Water and Climate Change

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This study focuses on the spatio-temporal analysis of rainfall variability, trend patterns, and projected changes using GCM CCSM4 for RCP4.5 and RCP8.5 in Khyber Pakhtunkhwa. The historical rainfall variability (1971–2018), trend, and magnitude were assessed using Mann–Kendall and Spearman's Rho. In addition, to downscale GCMs data of precipitation at the regional level of Khyber Pakhtunkhwa, SDSM conditional sub-model was applied. The monthly Mann–Kendall and Spearman's Rho trend test results revealed that most of the meteorological stations located in the northeastern mountains recorded decreasing trend while Parachinar observed an increasing trend in almost all months except December. The trend results for seasonal rainfall showed a decreasing trend in winter, spring, and summer in the north and northeastern parts of Khyber Pakhtunkhwa whereas an increasing trend was observed in all seasons at Parachinar. The RCP4.5 projections depicted an increase in precipitation especially in the monsoon-dominating regions in comparison to the western disturbances, while decreasing rainfall projection was observed in RCP8.5. The projections for the summer and winter seasons depicted an increasing trend till the mid-century but in the latter half, a decline is registered. Such seasonal changes may initially cause flooding followed by drought, which calls for effective water management strategies.

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Section: Spearman's Rho (Sr) Trend Testmentioning

confidence: 70%

Trend analysis of historical and future precipitation projections over a diverse topographic region of Khyber Pakhtunkhwa using SDSM

Rahman

Munawar

et al. 2022

Journal of Water and Climate Change

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“…A negative and positive value of Sen's estimator indicates a downward and an upward trend in the time series analysis, respectively ( Gao et al., 2020 ).…”

Section: Methodsmentioning

confidence: 99%

Evidences of climate change presences in the wettest parts of southwest Ethiopia

Gemeda

Korecha²,

Garedew

2021

Heliyon

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Climate change has been identified as a major challenge of rainfed agriculture. To contextualize whether there is climate change footprint, identification of rainfall and temperature trend at regional and local scale is helpful for designing long-term adaptation and mitigation strategies. The present study therefore aims to assess evidences of climate change presences in terms of, climate variability and trend in the wettest parts of Southwest Ethiopia. Daily and monthly historical gridded rainfall and temperature data (1983–2016) of ten stations were provided by Ethiopian National Metrological Agency. Moreover, long years historical recorded climate data of Nekemte and Bedele (1971–2020) and Sekoru (1981–2020) were used in the present study. Coefficient of variation, the Mann-Kendall non-parametric statistical test and Sen's slope estimator, linear regression analysis and the precipitation concentration index were applied to detect the presence of climate change in the southwest parts of Ethiopia. In this study, the trend package of open R software employed for trend identification and rate of change per year. The results indicate that the annual rainfall has declining trend at five stations with statistically significant at one station while the mean maximum and minimum temperature shows a statistically significant increasing trend at eight and six stations, respectively. At a seasonal scale, the amount of rainfall in the main rainy season (June to August) is dominated by a downward trend (eight out of ten stations) while, the autumn season (September to November) shows an increasing trend in all stations with statistically significant at one station. The precipitation concentration index analysis revealed that inconsistent and significantly irregular precipitation is observed at six stations (60%) of the ten stations. This study concludes that the climate of the wettest parts of Ethiopia is getting warmer and the amount of rainfall in the main rainy season has declined in the vast majority of the study area.

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“…When there is a trend, a positive serial correlation causes the null hypothesis of no trend to be incorrectly rejected (type I error). Similar to this, when there is a negative serial correlation, the null hypothesis of no trend is accepted, even when it is wrong (type II error) [37,38]. Lag-1 serial correlation coefficients are computed to examine the data for serial correlation.…”

Section: Testing For Serial Correlationmentioning

confidence: 98%

Trends in climatic and hydrological parameters in the Ajora-Woybo watershed, Omo-Gibe River basin, Ethiopia

2022

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The identification of hydro-meteorological trends is essential for analyzing climate change and river discharge at the watershed level. The Ajora-Woybo watershed in Ethiopia was studied for long-term trends in rainfall, temperature, and discharge at the annual, monthly, and seasonal time scales. The rainfall and temperature data extend 1990 to 2020, whereas the discharge data span from1990 to 2015. The Pettitt and Standard Normal Homogeneity Test (SNHT) tests were used to determine homogeneity. The Mann–Kendall and Sen's slope tests, as well as numerous variability measures, were then employed for trend analysis. The degree of relationship between climate variables and river discharge was determined using Pearson correlation coefficients (r). Inhomogeneity was discovered in annual rainfall data from the Angacha and Areka stations. Rainfall and discharge showed insignificant trends over time, with increasing and decreasing variability across stations. Monthly rainfall decreasing trends were observed to be significantly falling in February and March. Rainfall and runoff increase just insignificantly during the Kiremt season. On the other hand, minimum, maximum, and mean annual temperatures showed significant trends with annual increases of 0.01 °C, 0.04 °C, and 0.025 °C, respectively. In this study, the relationships between discharge and temperature and rainfall were found to be moderate and minimal, respectively. Generally, the results of the long-term examination of the hydrological and climate parameters in the watershed show that water resources vary throughout and over time. As a result, designing strategies require due attention. Article highlights Hydrological and meteorological parameters are essential for analyzing trends in water resource and climate change at the watershed level. Mann-Kendall and Sen's slope tests, along with a number of variability measures, were utilized in conjunction with the time series analysis approach for trend analysis. The analysis of the rainfall, temperature, and discharge in the watershed's data generally demonstrates how the availability of water resource varies over time. Designing suitable plans for water resource management and sustainable development in the watershed is therefore essential.

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Trend Analysis of Rainfall Time Series in Shanxi Province, Northern China (1957–2019)

Cited by 29 publications

References 67 publications

Trend analysis of historical and future precipitation projections over a diverse topographic region of Khyber Pakhtunkhwa using SDSM

Trend analysis of historical and future precipitation projections over a diverse topographic region of Khyber Pakhtunkhwa using SDSM

Evidences of climate change presences in the wettest parts of southwest Ethiopia

Trends in climatic and hydrological parameters in the Ajora-Woybo watershed, Omo-Gibe River basin, Ethiopia

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