Impact of climate change on rainfall variability in the Blue Nile basin

Afandi, Gamal Salah El; El-Mahdy, Mohamed El-Sayed

doi:10.1016/j.aej.2021.08.056

Cited by 28 publications

(19 citation statements)

References 43 publications

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“…Belay et al (2021) also found similar result that nonsignificant and less variable average decadal rainfall was observed between 1987 and 2019 over the northwestern parts of the country. The result is also in agreement with Mohamed et al (2022) who observed a further reduction of mean annual and Kiremt rainfall by 1149.4 mm and 783.7 mm respectively in the Blue Nile Basin during the 1981-2018 compared to the preceding decades.…”

Section: Discussionsupporting

confidence: 92%

“…Bekele et al (2017a, b) and Cheung et al (2008) found high seasonal rainfall variability respectively for most of the stations located in the Awash River Basin and throughout Ethiopia and the results agree with the current study. Moreover, a very recent study conducted by Mohamed et al (2022) reported more inter-annual variability of Bega rainfall than Kiremt seasons (Coefficient of Variation (CV) of Bega > Belg > Kiremt seasons) in the Blue Nile Basin.…”

Section: Discussionmentioning

confidence: 99%

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Climate trend analysis for a semi-arid Borana zone in southern Ethiopia during 1981–2018

2022

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Background Understanding the climate variability at local scale could help suggest local adaptation responses to manage climate associated risks. This paper analyzed the variability and trend of climate in semi-arid Borana zone of southern Ethiopia over the period 1981–2018 using Mann–Kendall (MK) test, Sen’s Slope Estimator (SEE) and inverse distance weighted (IDW) interpolation technique. Gridded (4 km * 4 km) climate data (daily precipitation, daily maximum temperature (Tmax) and minimum temperature (Tmin)) were collected from National Meteorology Agency (NMA) of Ethiopia. Results The results revealed the study area received a mean monthly precipitation of 39.19 mm and a monthly mean Tmax and Tmin of 29.66 °C and 16.31 °C were observed respectively. Rainfall shows a significant increasing trend during August, October and November and extremely variable during December, January and February where CV > 100%. Tmax shows a significant warming trend during August but January, February, August and October exhibited similar trend for Tmin. Rainfall and Tmin shows a significant trend during Meher and no trend for the rest of the seasons. Mean annual rainfall shows a significant increase where no trend observed for both Tmax and Tmin at this timescale. Decadal rainfall and Tmin exhibited no trend but Tmax show significant warming trend during 2001–2010 decade. Better rainfall and cooler temperature were observed in the north central, northeastern and northwestern whereas the southeastern and southwestern regions were drier and warmer. Conclusion Rainfall is highly variable than temperature both at temporal and spatial scales in Borana. The intensity of rainfall decreases from the northeastern and northwestern parts towards the southwest while temperature increased from the north central parts towards the southwest for Tmax and the southeast for Tmin. The effect of topography is substantial for the local scale variability observed in the study area. Internal variability is observed at temporal and spatial scales and therefore any adaptation responses to local climate variability should consider the microscale climate.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Climate trend analysis for a semi-arid Borana zone in southern Ethiopia during 1981–2018

2022

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“…Then the lag-1 serial correlation method is applied to check for autocorrelation in the series (Onyutha et al 2016;Ali et al 2019;Mehta and Yadav 2021). The series without any autocorrelation are subjected to Mann Kendall (MK) and Spearman's rank correlation (SRC) test to determine the existence of the trend and its direction (Mallick et al;Patakamuri et al 2020;Mohamed et al 2021;Mehta et al 2022). The magnitude and change point of the trend is determined by Sen's slope estimator (SSE) and Sequential Mann Kendall (SQMK) tests, respectively (Partal and Kahya 2006;Karpouzos et al 2010;Bari et al 2016;Rahman et al 2017).…”

Section: Methodsmentioning

confidence: 99%

“…The SAI, which is used to investigate the nature of trends and identify dry and wet years, is another technique for measuring rainfall variability (Harka et al 2021;Mohamed et al 2021).…”

Section: Standardized Anomaly Index (Sai)mentioning

confidence: 99%

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Spatiotemporal Rainfall Variability and Trend Analysis of Shimsha River Basin, India

Bharath

Maddamsetty

Manjunatha

et al. 2023

Environ Sci Pollut Res

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The current study aims to determine the variability and trend in rainfall data. From 1989 to 2018, daily rainfall data was gathered for the Shimsha basin, a sub-basin of the Cauvery basin in Karnataka, India, and aggregated into annual, seasonal, and monthly rainfall totals as well as the number of rainy days. In this study, the time series are subjected to statistical methods to examine rainfall variability and trend. The mean, standard deviation, skewness, kurtosis, coefficient of variation (CV), and Standardized Anomaly Index (SAI) are all used in the preliminary and variability analysis. To understand the rainfall distribution characteristics, Kurtosis and skewness were used. To identify homogenous and serially independent series, homogeneity and serial correlation tests were used. Mann-Kendall (MK) and Spearman's rank correlation (SRC) tests were performed to identify the trend in the homogenous and serially independent series. Sen's slope (SS) technique is applied to quantify the amount of the trend, and the Sequential Mann-Kendall (SQMK) test was used to assess the trend change point. The statistical tests indicated in this work were performed using open-source R packages such as "trend," "modifiedmk" and "trendchange". The study area's average rainfall was 801.86 mm, and CV ranges from 43.3% to 22.27%. The basin receives the highest rainfall in southwest monsoon season (SWM) followed by post-monsoon, summer, and winter seasons, respectively.Out of 162 series, 11-time series were found to be non-homogeneous and were omitted. Then out of 151 homogeneous series, 21 series showed a significant increasing trend while 99 and 31 series showed a little rising and declining trend, respectively. The study's results will help in water resource management, agricultural planning and socioeconomic development in the area.

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Performance evaluation of CMIP6 climate models for selecting a suitable GCM for future precipitation at different places of Tamil Nadu

2023

Environ Monit Assess

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Impact of climate change on rainfall variability in the Blue Nile basin

Cited by 28 publications

References 43 publications

Climate trend analysis for a semi-arid Borana zone in southern Ethiopia during 1981–2018

Climate trend analysis for a semi-arid Borana zone in southern Ethiopia during 1981–2018

Spatiotemporal Rainfall Variability and Trend Analysis of Shimsha River Basin, India

Performance evaluation of CMIP6 climate models for selecting a suitable GCM for future precipitation at different places of Tamil Nadu

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