Validation of General Climate Models (GCMs) over Upper Blue Nile River Basin, Ethiopia

Bokke, Andualem Shigute; Taye, Meron Teferi; Willems, Patrick; Siyoum, Shimelis Asefu

doi:10.4236/acs.2017.71006

Cited by 13 publications

(7 citation statements)

References 9 publications

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“…We can conclude that the Delta results are more representative than most of the GCM runs, and the performance of temperature was much better than that of precipitation ( Figure 4). Similar results were also provided by Fang et al [83] in the Kaidu River Basin and Bokke et al [84] in the Nile River Basin. The results demonstrate that the precipitation uncertainty is larger than temperature uncertainty in GCMs [85].…”

Section: Results Of Hydrological Modellingsupporting

confidence: 79%

Multi–Model Ensemble Approaches to Assessment of Effects of Local Climate Change on Water Resources of the Hotan River Basin in Xinjiang, China

Luo

Meng

et al. 2017

Water

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Abstract:The effects of global climate change threaten the availability of water resources worldwide and modify their tempo-spatial pattern. Properly quantifying the possible effects of climate change on water resources under different hydrological models is a great challenge in ungauged alpine regions. By using remote sensing data to support established models, this study aimed to reveal the effects of climate change using two models of hydrological processes including total water resources, peak flows, evapotranspiration, snowmelt and snow accumulation in the ungauged Hotan River Basin under future representative concentration pathway (RCP) scenarios. The results revealed that stream flow was much more sensitive to temperature variation than precipitation change and increased by 0.9-10.0% according to MIKE SHE or 6.5-10.5% according to SWAT. Increased evapotranspiration was similar for both models with a range of 7.6-31.3%. The snow-covered area shrank from 32.5% to 11.9% between the elevations of 4200-6400 m, respectively, and snow accumulation increased when the elevation exceeded 6400 m above sea level (asl). The results also suggested that the fully distributed and semi-distributed structures of these two models strongly influenced the responses to climate change. The study proposes a practical approach to assess the climate change effect in ungauged regions.

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Section: Results Of Hydrological Modellingsupporting

confidence: 79%

Multi–Model Ensemble Approaches to Assessment of Effects of Local Climate Change on Water Resources of the Hotan River Basin in Xinjiang, China

Luo

Meng

et al. 2017

Water

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“…As mentioned by Ref. [ 14 ] GCM/RCM model performance based on monthly time series is evaluated using RMSE, percent of bias, correlation, and Nash Sutcliffe Efficiency (NSE) criteria. (1) , (2) , (3) , (4) ) depicts RMSE, % of biased, correlation and NSE.…”

Section: Methodsmentioning

confidence: 99%

Climate change impact on water resources availability in the kiltie watershed, Lake Tana sub-basin, Ethiopia

Wubneh

Worku

Chekol

2023

Heliyon

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“…The median of the CV values from the RCM grid cells in each. According to [3,4,6,13] the measures are as follow:…”

Section: Accuracy Of Rainfall Simulations From Climate Modelsmentioning

confidence: 99%

Future Water Availability Under Representative Concentration Pathways Scenario in Baro Basin, Ethiopia

Ebissa¹

2021

WROS

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The objective in this study was to assess future water availability in the upper part of the Baro basin in Southwest Ethiopia through the Representative Concentration Pathway (RCP 4.5) scenario. HBV-96 rainfall-runoff model was calibrated and validated for historical records of streamflow. The estimated NSE and RVE values are 0.91 and -6.76% during calibration period (1996)(1997)(1998)(1999)(2000)(2001)(2002) and validation period (2003)(2004)(2005) values are 0.72 and 9.78% respectively. Dynamically downscaled climate model outputs were obtained from four models through the CORDEX-Africa program. The four climate models were evaluated using a suite of statistical measures such as bias, Root Mean Squared Error (RMSE) and Coefficient of Variation (CV). The bias of the simulated rainfall varies between -4.20% and -25.39% suggesting underestimation. In terms of bias, EC-Earth performs best while HadGEM2-ES performs worst. In terms of RMSE, MPI-ESM-LR performs worst while CM5A-MR performs best. All the four GCMs projections showed that the maximum temperature will likely increase by 2.08°C (MPI-ESM-LR) to 2.52°C (CM5A-MR) and minimum temperature will also likely increase by 1.65°C (EC-Earth) to 2.78°C (HadGM2-ES) in the Baro basin in medium-term (2041-2070) for the RCP4.5 scenario. However, the annual rainfall amount will likely decrease by 7.34% (CM5A-MR) to 17.42% (HaDGEM2-ES) and with a likely increase in annual potential evapotranspiration. The maximum streamflow reduction was projected for the rainy season (Kiremt) by up to 28.36% (CM5A-MR). The annual streamflow is projected to decline by up to 35.2% during 2050s. The findings of this study indicate that climate change under the RCP4.5 scenario will have a significant implication to water availability in the Baro basin.

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Validation of General Climate Models (GCMs) over Upper Blue Nile River Basin, Ethiopia

Cited by 13 publications

References 9 publications

Multi–Model Ensemble Approaches to Assessment of Effects of Local Climate Change on Water Resources of the Hotan River Basin in Xinjiang, China

Multi–Model Ensemble Approaches to Assessment of Effects of Local Climate Change on Water Resources of the Hotan River Basin in Xinjiang, China

Climate change impact on water resources availability in the kiltie watershed, Lake Tana sub-basin, Ethiopia

Future Water Availability Under Representative Concentration Pathways Scenario in Baro Basin, Ethiopia

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