Green infrastructure systems can be selected methodically considering watershed parameters, then the existing urban water network, and surrounding land uses.

Abstract:Optimal operation of reservoirs is very essential for water resource planning and management, but it is very challenging and complicated when dealing with climate change impacts. The objective of this paper was to assess existing and future hydropower operation at the Tekeze reservoir in the face of climate change. In this study, a calibrated and validated Soil and Water Assessment Tool (SWAT) was used to model runoff inflow into the Tekeze hydropower reservoir under present and future climate scenarios. Inflow to the reservoir was simulated using hydro-climatic data from an ensemble of downscaled climate data based on the Coordinated Regional climate Downscaling Experiment over African domain (CORDEX-Africa) with Coupled Intercomparison Project Phase 5 (CMIP5) simulations under Representative Concentration Pathway (RCP)4.5 and RCP8.5 climate scenarios. Observed and projected inflows to Tekeze hydropower reservoir were used as input to the US Army Corps of Engineer's Reservoir Evaluation System Perspective Reservoir Model (HEC-ResPRM), a reservoir operation model, to optimize hydropower reservoir release, storage and pool level. Results indicated that climate change has a clear impact on reservoir inflow and showed increase in annual and monthly inflow into the reservoir except in dry months from May to June under RCP4.5 and RCP8.5 climate scenarios. HEC-ResPRM optimal operation results showed an increase in Tekeze reservoir power storage potential up to 25% and 30% under RCP4.5 and RCP8.5 climate scenarios, respectively. This implies that Tekeze hydropower production will be affected by climate change. This analysis can be used by water resources planners and mangers to develop reservoir operation techniques considering climate change impact to increase power production.

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This study examines the performance of multimodel numerical simulations and multiobservational databases focusing on seasonal cycles and spatial variations of precipitation over Ethiopia. Seven regional climate models (RCMs) driven by the European Center for Medium Range Weather Forecasting (ECMWF) Interim reanalysis (ERA-Interim) and generated in the framework of COordinated Regional climate Downscaling EXperiment (CORDEX) project, and four observational databases computed using different interpolation techniques and blending strategies were evaluated against typical observational database produced by Climate Research Unit (CRU) over Ethiopia on monthly basis. All were produced at 48.8 km grid resolution for the period 1989-2008. The preliminary results showed that ensembles [multimodel ensemble (MME) + multiobservational ensemble (MOE)] were as good as CRU in reproducing the temporal variability and the geographical distribution of precipitation. Comparison of seasonal means and temporal correlation results revealed that there were good agreements between ensembles and CRU at each grid point and in close proximity to each other. Results of rotated principal components (RPCs), rotated empirical orthogonal functions (REOFs), and the associated power spectra showed that every ensemble's element was able to simulate the seasonal cycles and homogeneous precipitation zones of CRU reasonably well. Excessive and deficient rainfall periods, which were seen in every ensemble's RPCs, matched CRU historical records. BackgroundClimate models are perpetually ameliorated and upgraded to higher and higher grid resolution with the intention of reproducing climate variables at finer scale. However, as climate model resolution tends to be finer, the noise on grid cells is likely to happen. Uncertainty in climate model is becoming much of the present interest as poor performance in present climate conditions is linked with outliers in the future projection (Knutti et al., 2010;Brands et al., 2011). Despite the fact that RCMs are downscaling tools aspired to upgrade the modelling of local physical processes, they are highly sensitive to model formulation, grid resolution, numerical schemes, and other physical parameterizations and result, therefore, in differences in downscaling skills (Fowler and Ekström, 2009;Maraun et al., 2010). There is growing evidence that regions and seasons showing the greatest model biases in the simulation of climate variables are often those with the greatest intermodel differences (Frei et al., 2006;Fowler et al., 2007;Maraun et al., 2010). Before using RCMs for future studies, it is believed that * Correspondence to: D. T. Reda, Department of Physics, College of Natural Science, Addis Ababa University, Addis Ababa, Ethiopia. E-mail: daniell.tsegay@gmail.com they should pass through some evaluation mechanisms. To address this issue, several climate modelling groups from around the world have been downscaling global climate models (GCMs) to regional scale using their own model setup. The aim ...

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Awash river has been impaired by various types of pollution owing to waste released from different socio-economic activities in its basin. This research was aimed at evaluating its quality status with respect to drinking and irrigation water uses. Based on accessibility and land use severity, 17 sample sites were chosen along the river and sampling was done twice in each of the dry and wet seasons. Thereafter, both onsite and offsite water quality analyses were undertaken following standard procedures. Canadian Council of Ministers of Environment Water Quality Index (CCME WQI) was applied to compute the water quality indices. Accordingly, the drinking and irrigation water quality indices of the upper basin were found to be 34.79 and 46.39 respectively, which were in the poor and marginal categories of the Canadian water quality ranking. Meanwhile, the respective indices for the middle/lower basin, which were 32.25 and 62.78, lie in the poor and fair ranges of the ranking. Although the difference in the dataset used for the two cases and natural purification in the course of the river might contribute to the difference in WQI, it is generally conceivable that the water quality of the river is below the good rank. Establishment of wastewater treatment plants and storm water quality management at hotspot areas are recommended to improve the quality.

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This study aims to assess the impact of climate change on the water resources of the Upper Blue Nile basin using an integrated climate and hydrological model. The impact of climate change on water resources is being assessed using the regional climate model (RCM) under the representative concentration pathway (RCP4.5 and RCP8.5) scenarios and the Soil and Water Assessment Tool (SWAT) hydrological model. Future climate scenarios have been developed for the 2030s (2021–2040) and the 2050s (2041–2060). The study found that the projected rainfall shows a decreasing trend and is not statistically significant, while the temperature shows an increasing trend and is statistically significant. Due to the sharp rise in temperature, the annual evapotranspiration increased by about 10.4%. This and the declining trend of rainfall will reduce streamflow up to 54%, surface runoff up to 31%, and water yield up to 31%. Climate change causes seasonal and annual fluctuations in the water balance components. However, the projected seasonal changes are much greater than the annual changes. Therefore, the results of this study will be useful to basin planners, policymakers, and water resources managers in developing adaptation strategies to offset the adverse effects of climate change in the Upper Blue Nile basin.