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Hydrological response to climate change for Gilgel Abay River, in the Lake Tana Basin -Upper Blue Nile Basin of Ethiopia.

Dile YT, Berndtsson R, Setegn SG - PLoS ONE (2013)

Bottom Line: Climate change appears to have negligible effect on low flow conditions of the river.Overall, it appears that climate change will result in an annual increase in flow volume for the Gilgel Abay River.Moreover, it will help harnessing a significant amount of water for ongoing dam projects in the Gilgel Abay River Basin.

View Article: PubMed Central - PubMed

Affiliation: Stockholm Environment Institute, Stockholm, Sweden ; Stockholm Resilience Center, Stockholm University, Stockholm, Sweden.

ABSTRACT
Climate change is likely to have severe effects on water availability in Ethiopia. The aim of the present study was to assess the impact of climate change on the Gilgel Abay River, Upper Blue Nile Basin. The Statistical Downscaling Tool (SDSM) was used to downscale the HadCM3 (Hadley centre Climate Model 3) Global Circulation Model (GCM) scenario data into finer scale resolution. The Soil and Water Assessment Tool (SWAT) was set up, calibrated, and validated. SDSM downscaled climate outputs were used as an input to the SWAT model. The climate projection analysis was done by dividing the period 2010-2100 into three time windows with each 30 years of data. The period 1990-2001 was taken as the baseline period against which comparison was made. Results showed that annual mean precipitation may decrease in the first 30-year period but increase in the following two 30-year periods. The decrease in mean monthly precipitation may be as much as about -30% during 2010-2040 but the increase may be more than +30% in 2070-2100. The impact of climate change may cause a decrease in mean monthly flow volume between -40% to -50% during 2010-2040 but may increase by more than the double during 2070-2100. Climate change appears to have negligible effect on low flow conditions of the river. Seasonal mean flow volume, however, may increase by more than the double and +30% to +40% for the Belg (small rainy season) and Kiremit (main rainy season) periods, respectively. Overall, it appears that climate change will result in an annual increase in flow volume for the Gilgel Abay River. The increase in flow is likely to have considerable importance for local small scale irrigation activities. Moreover, it will help harnessing a significant amount of water for ongoing dam projects in the Gilgel Abay River Basin.

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SDSM downscaling procedure (modified from Wilby and Dawson [33]).
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pone-0079296-g002: SDSM downscaling procedure (modified from Wilby and Dawson [33]).

Mentions: Global Circulation Model (GCM) derived scenarios of climate change were used for predicting the future climates of the study area as they conform to criteria proposed by the Intergovernmental Panel on Climate Change (IPCC) [29]. The GCMs data are, however, too coarse in resolution to apply directly for impact assessment [30]. Thus, Statistical Down-Scaling Model (SDSM) was used to bridge this resolution gap. SDSM develops statistical relationships, based on multiple linear regression techniques, between large-scale (predictors) and local (predictand) climate [31–33]. The downscaling of GCMs data using SDSM was done following the procedures suggested by Wilby and Dawson [33]. The quality control option in SDSM was used for checking missing data and outliers. The screen variable option (a procedure in SDSM) was used to choose the appropriate downscaling predictor variables for model calibration. An unconditional process was selected for maximum and minimum temperature downscaling since the predictor-predictand process in temperature downscaling is not regulated by an intermediate process (cf. [33]). In unconditional models a direct link is assumed between the predictors and predictand (e.g., there is no intermediate process between maximum temperature (predictand) and near surface specific humidity (predictor)). While in conditional models, there is an intermediate process between predictors and predictand (e.g. precipitation amounts depend on the occurrence of wet-days, which in turn depend on regional-scale predictors such as humidity and atmospheric pressure). Thus for precipitation downscaling a conditional process was assumed. The significance level which tests the significance of predictor-predictand correlation was set to P-value <0.05. The model calibration process in SDSM was used to construct downscaled data based on multiple regression equations given daily weather data (predictand) and regional scale atmospheric variables (predictor). The ordinary least squares optimization technique was used to calibrate the model. The calibrated model was used to generate synthetic daily weather series using the observed atmospheric predictor variables and regression model weights. Validation in SDSM is evaluating the agreement between the generated weather series and an independent observed weather data excluded from model calibration process. The procedures of SDSM downscaling is provided in Figure 2.


Hydrological response to climate change for Gilgel Abay River, in the Lake Tana Basin -Upper Blue Nile Basin of Ethiopia.

Dile YT, Berndtsson R, Setegn SG - PLoS ONE (2013)

SDSM downscaling procedure (modified from Wilby and Dawson [33]).
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3824061&req=5

pone-0079296-g002: SDSM downscaling procedure (modified from Wilby and Dawson [33]).
Mentions: Global Circulation Model (GCM) derived scenarios of climate change were used for predicting the future climates of the study area as they conform to criteria proposed by the Intergovernmental Panel on Climate Change (IPCC) [29]. The GCMs data are, however, too coarse in resolution to apply directly for impact assessment [30]. Thus, Statistical Down-Scaling Model (SDSM) was used to bridge this resolution gap. SDSM develops statistical relationships, based on multiple linear regression techniques, between large-scale (predictors) and local (predictand) climate [31–33]. The downscaling of GCMs data using SDSM was done following the procedures suggested by Wilby and Dawson [33]. The quality control option in SDSM was used for checking missing data and outliers. The screen variable option (a procedure in SDSM) was used to choose the appropriate downscaling predictor variables for model calibration. An unconditional process was selected for maximum and minimum temperature downscaling since the predictor-predictand process in temperature downscaling is not regulated by an intermediate process (cf. [33]). In unconditional models a direct link is assumed between the predictors and predictand (e.g., there is no intermediate process between maximum temperature (predictand) and near surface specific humidity (predictor)). While in conditional models, there is an intermediate process between predictors and predictand (e.g. precipitation amounts depend on the occurrence of wet-days, which in turn depend on regional-scale predictors such as humidity and atmospheric pressure). Thus for precipitation downscaling a conditional process was assumed. The significance level which tests the significance of predictor-predictand correlation was set to P-value <0.05. The model calibration process in SDSM was used to construct downscaled data based on multiple regression equations given daily weather data (predictand) and regional scale atmospheric variables (predictor). The ordinary least squares optimization technique was used to calibrate the model. The calibrated model was used to generate synthetic daily weather series using the observed atmospheric predictor variables and regression model weights. Validation in SDSM is evaluating the agreement between the generated weather series and an independent observed weather data excluded from model calibration process. The procedures of SDSM downscaling is provided in Figure 2.

Bottom Line: Climate change appears to have negligible effect on low flow conditions of the river.Overall, it appears that climate change will result in an annual increase in flow volume for the Gilgel Abay River.Moreover, it will help harnessing a significant amount of water for ongoing dam projects in the Gilgel Abay River Basin.

View Article: PubMed Central - PubMed

Affiliation: Stockholm Environment Institute, Stockholm, Sweden ; Stockholm Resilience Center, Stockholm University, Stockholm, Sweden.

ABSTRACT
Climate change is likely to have severe effects on water availability in Ethiopia. The aim of the present study was to assess the impact of climate change on the Gilgel Abay River, Upper Blue Nile Basin. The Statistical Downscaling Tool (SDSM) was used to downscale the HadCM3 (Hadley centre Climate Model 3) Global Circulation Model (GCM) scenario data into finer scale resolution. The Soil and Water Assessment Tool (SWAT) was set up, calibrated, and validated. SDSM downscaled climate outputs were used as an input to the SWAT model. The climate projection analysis was done by dividing the period 2010-2100 into three time windows with each 30 years of data. The period 1990-2001 was taken as the baseline period against which comparison was made. Results showed that annual mean precipitation may decrease in the first 30-year period but increase in the following two 30-year periods. The decrease in mean monthly precipitation may be as much as about -30% during 2010-2040 but the increase may be more than +30% in 2070-2100. The impact of climate change may cause a decrease in mean monthly flow volume between -40% to -50% during 2010-2040 but may increase by more than the double during 2070-2100. Climate change appears to have negligible effect on low flow conditions of the river. Seasonal mean flow volume, however, may increase by more than the double and +30% to +40% for the Belg (small rainy season) and Kiremit (main rainy season) periods, respectively. Overall, it appears that climate change will result in an annual increase in flow volume for the Gilgel Abay River. The increase in flow is likely to have considerable importance for local small scale irrigation activities. Moreover, it will help harnessing a significant amount of water for ongoing dam projects in the Gilgel Abay River Basin.

Show MeSH
Related in: MedlinePlus