Statistical Assessment of Rainfall Characteristics in Upper Blue Nile Basin over the Period from 1953 to 2014

Samy, Abeer; Ibrahim, Mona G.; Mahmod, Wael Elham; Fujii, Manabu; Eltawil, Amr B.; Daoud, Waled

doi:10.3390/w11030468

Cited by 29 publications

(17 citation statements)

References 33 publications

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“…Furthermore, our findings are in line with other similar studies, which revealed observed trend changes in the Ethiopian highlands and elsewhere, with a mean annual temperature increase range between 0.028 • C and 1.65 • C from 1955 to 2016 [63,64]. In contrast, Samy et al [65] reported a significant decreasing trend in rainfall in the southwestern part of the Upper Blue Nile basin. SPI results indicated that all the three watersheds were affected by drought episodes in 1984/1985, 1987/1988, 1992/1993, 2000/2001, 2010/2011, and 2015/2016, which is in line with other research results of drought experiences in Ethiopia [9,66].…”

Section: Exposuresupporting

confidence: 93%

Communities’ Livelihood Vulnerability to Climate Variability in Ethiopia

et al. 2019

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Ethiopia has experienced more than 10 major drought episodes since the 1970s. Evidence has shown that climate change exacerbates the situation and presents a daunting challenge to predominantly rain-fed agricultural livelihoods. The aim of this study was to analyze the extent and sources of smallholder famers’ livelihood vulnerability to climate change/variability in the Upper Blue Nile basin. We conducted a household survey (n = 391) across three distinct agroecological communities and a formative composite index of livelihood vulnerability (LVI) was constructed. The Mann–Kendall test and the standard precipitation index (SPI) were employed to analyze trends of rainfall, temperature, and drought prevalence for the period from 1982 to 2016. The communities across watersheds showed a relative difference in the overall livelihood vulnerability index. Aba Gerima (midland) was found to be more vulnerable, with a score of 0.37, while Guder (highland) had a relatively lower LVI with a 0.34 index score. Given similar exposure to climate variability and drought episodes, communities’ livelihood vulnerability was mainly attributed to their low adaptive capacity and higher sensitivity indicators. Adaptive capacity was largely constrained by a lack of participation in community-based organizations and a lack of income diversification. This study will have practical implications for policy development in heterogeneous agroecological regions for sustainable livelihood development and climate change adaptation programs.

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Section: Exposuresupporting

confidence: 93%

Communities’ Livelihood Vulnerability to Climate Variability in Ethiopia

et al. 2019

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“…Upper Blue Nile River (locally known as Abay) Basin is located in the northwestern part of Ethiopia between 7 • 45 and 12 • 45 N and 34 • 05 and 39 • 45 E and has a drainage area of about 176,652 km 2 [10,13]. The topography of the UBNB (UBNB) is composed of hills, highlands, valleys, and rock peaks.…”

Section: Study Areamentioning

confidence: 99%

“…Water 2021, 13, x FOR PEER REVIEW 3 of 25 area of about 176,652 km 2 [10,13]. The topography of the UBNB (UBNB) is composed of hills, highlands, valleys, and rock peaks.…”

Section: Study Areamentioning

confidence: 99%

“…Previous studies [8][9][10][11][12] on the impacts of climate change in the Nile basin come up with highly variable findings. Some of the plausible reasons are the higher variability of rainfall in the basin, insufficiency in temporal and spatial extent of analyzed data, different statistical measures used in each study [11,13]. GCMs cannot even agree on the signs; some have a positive sign (increase) and others have a negative sign (decrease) in the same region of study from different studies.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of Past and Future Climate Trends under CMIP6 Scenarios for the UBNB (Abay), Ethiopia

Alaminie

Tilahun

Addisu

et al. 2021

Water

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Climate predictions using recent and high-resolution climate models are becoming important for effective decision-making and for designing appropriate climate change adaptation and mitigation strategies. Due to highly variable climate and data scarcity of the upper Blue Nile Basin, previous studies did not detect specific unified trends. This study discusses, the past and future climate projections under CMIP6-SSPs scenarios for the basin. For the models’ validation and selection, reanalysis data were used after comparing with area-averaged ground observational data. Quantile mapping systematic bias correction and Mann–Kendall trend test were applied to evaluate the trends of selected CMIP6 models during the 21st century. Results revealed that, ERA5 for temperature and GPCC for precipitation have best agreement with the basin observational data, MRI-ESM2-0 for temperature and BCC-CSM-2MR for precipitation were selected based on their highest performance. The MRI-ESM2-0 mean annual maximum temperature for the near (long)-term period shows an increase of 1.1 (1.5) °C, 1.3 (2.2) °C, 1.2 (2.8) °C, and 1.5 (3.8) °C under the four SSPs. On the other hand, the BCC-CSM-2MR precipitation projections show slightly (statistically insignificant) increasing trend for the near (long)-term periods by 5.9 (6.1)%, 12.8 (13.7)%, 9.5 (9.1)%, and 17.1(17.7)% under four SSPs scenarios.

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“…The 30 m resolution digital elevation model of the NASA Shuttle Radar Topographic Mission (SRTM) ( Figure 1) depicts that the highest elevations, exceeding ASL by 4000 m, are centered on the eastern part of the basin and steadily decline in the direction of the western exit of the basin, where the altitude is almost 483 m ASL. The majority of the UBN basin flow occurs between June and September, with the outflow from Lake Tana accounting for about 7% [36]. Teleconnections strongly influence the basin's climate, with the ENSO as a primary driver of interannual precipitation variability in the basin [37], followed by the Indian Ocean and the Gulf of Guinea [38,39].…”

Section: Study Areamentioning

confidence: 99%

Application of Artificial Neural Networks in Forecasting a Standardized Precipitation Evapotranspiration Index for the Upper Blue Nile Basin

Mulualem

Liou

2020

Water

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The occurrence frequency of drought has intensified with the unprecedented effect of global warming. Knowledge about the spatiotemporal distributions of droughts and their trends is crucial for risk management and developing mitigation strategies. In this study, we developed seven artificial neural network (ANN) predictive models incorporating hydro-meteorological, climate, sea surface temperatures, and topographic attributes to forecast the standardized precipitation evapotranspiration index (SPEI) for seven stations in the Upper Blue Nile basin (UBN) of Ethiopia from 1986 to 2015. The main aim was to analyze the sensitivity of drought-trigger input parameters and to measure their predictive ability by comparing the predicted values with the observed values. Statistical comparisons of the different models showed that accurate results in predicting SPEI values could be achieved by including large-scale climate indices. Furthermore, it was found that the coefficient of determination and the root-mean-square error of the best architecture ranged from 0.820 to 0.949 and 0.263 to 0.428, respectively. In terms of statistical achievement, we concluded that ANNs offer an alternative framework for forecasting the SPEI drought index.

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Statistical Assessment of Rainfall Characteristics in Upper Blue Nile Basin over the Period from 1953 to 2014

Cited by 29 publications

References 33 publications

Communities’ Livelihood Vulnerability to Climate Variability in Ethiopia

Communities’ Livelihood Vulnerability to Climate Variability in Ethiopia

Evaluation of Past and Future Climate Trends under CMIP6 Scenarios for the UBNB (Abay), Ethiopia

Application of Artificial Neural Networks in Forecasting a Standardized Precipitation Evapotranspiration Index for the Upper Blue Nile Basin

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