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23 results on '"Woyessa, Yali E."'

10. Assessment of climate change impact and comparison of downscaling approaches: a case study in a semi-arid river basin.

Author

Woyessa, Yali E.

Subjects
DOWNSCALING (Climatology), GREENHOUSE gases, WATERSHEDS, ATMOSPHERIC models, WATER supply, CLIMATE change, SPATIAL resolution
Abstract

Rapid population increase, industrialization and pollution are putting a strain on available and diminishing freshwater resources. Recent climate projections suggest a drop of up to 10 % in precipitation in most of Southern Africa by 2050. The main aim of this paper is to assess the impact of climate change on water resources in a semi-arid river basin in South Africa using two downscaling approaches: statistical downscaling (SDE) and dynamic downscaling (CORDEX) approaches. Both SDE and CORDEX data were derived from the GCM simulations of the Coupled Model Inter-comparison Project Phase-5 (CMIP5) and across two greenhouse gas emission scenarios known as Representative Concentration Pathways (RCP) 4.5 and 8.5 with a spatial resolution 25 km × 25 km for SDE and 50 km × 50 km for CORDEX. Four GCM models were used for both approaches. SWAT hydrological model was run using these data for a period of 2020 to 2050. Varied results were obtained depending on the type of climate model used, but generally, the trends were similar in most cases. For SDE approach, the multi-model average showed a possible decrease in precipitation (by 14 %), a decrease in water yield (by 15 %) and an increase in potential evapotranspiration (by 10 %). For CORDEX data, the multi-model average showed a possible decrease in precipitation (up to - 3 %), a decrease in water yield (up to - 13 %) and an increase in potential evapotranspiration (ET) (up to + 22 %). The latter is indicative of possible drought spells between rainy events. The SDE approach showed much more pronounced decrease of precipitation and water yield compared to the CORDEX approach. This difference could be attributed to the difference in spatial resolution of the two downscaling approaches. However, it is expected that the results of this study could assist in policy formulation to mitigate the negative impact of climate change in the region. [ABSTRACT FROM AUTHOR]

Published
2024
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16. Reliability of NASA NEX-GDDP Dataset in Reproducing Climatological Mean Temperature and Precipitation over the Gibe III Watershed, Omo-Gibe Basin, Ethiopia.

Author

Gebremichael, Abiy, Kebede, Asfaw, and Woyessa, Yali E.

Subjects
WATERSHEDS, ATMOSPHERIC models, TEMPERATURE, SPATIAL resolution, WATER supply
Abstract

Background: The challenge of climate variability is a major problem for developing and using water resources. Scarcity of climate data compounds the problem and undermines the efforts to acquire updated information for predicting climate change and reduce its risks. Objective: The objective of the study was to evaluate and select the best climate models having NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset for Gibe III watershed. Material and Methods: NEX-GDDP data of precipitation and temperature with spatial resolution of 0.25° x 0.25° of ten CMIP5 models was, evaluated against observed data of eight stations distributed in the Watershed. Results: The models showed a consistent and reasonable pattern for mean monthly total precipitation and mean temperature (max and min). The mean monthly precipitation of all models against observation also resulted to R² of 0.71 to 0.99 and the Nash-Sutcliffe efficiency (NSE) value of 0.66 to 0.99. Mean annual precipitation of model ensemble mean over the watershed against observation spatially varied between -100 and 100 mm underestimating at the northern and southern tips of watershed while overestimating at central and northeastern parts. The mean maximum and minimum temperature varied from -1.6 °C to +2.9 °C and 0.4 °C to 3.8 °C, respectively. Conclusion: The result indicates that, selecting climate models' ensemble mean could provide higher confidence in climate change projection than choosing a specific model for an entire watershed. Based on evaluation metrics and long-term mean annual rainfall, NEX-GDDP dataset of CSIRO-MK3-6-0, MIROC5, MPI-ESM-MR, NorESM1-M, MIROC5 and GFDL-ESM2M models reasonably simulated the mean annual rainfall at Shebe, Sodo, Jimma, Hosaina, Sokoru and Woliso stations respectively for uses of climate change projection in the Watershed. The reliability of NEX-GDDP dataset for the climate models need seasonal basis study in the future at the Watershed since this study did not conduct seasonal data analysis. [ABSTRACT FROM AUTHOR]

Published
2022

20. Application of SWAT model to evaluate the water balance of an arid catchment

Author

Mengistu, Achamyeleh Girma, Van Rensburg, L. D., Woyessa, Yali E., Mengistu, Achamyeleh Girma, Van Rensburg, L. D., and Woyessa, Yali E.

Abstract

The hydrologic processes and their behaviours in arid and semi-arid areas are poorly understood and differ highly from humid/sub-humid areas. Hydrologic models play critical roles in understanding such complex processes. However, the application of hydrologic models is limited due to the unavailability or scarcity of data for model calibration, uncertainty and validation procedures. Therefore, this study was aimed at evaluating the application of the Soil and Water Assessment Tool (SWAT model) in simulating the components of water balance in an arid and semi-arid catchment. Moreover, the spatio-temporal variabilities of the different components of the water balance were quantified and analysed. The intensity of water stress was also evaluated in the catchment. All the components of the catchment water balance in this study were estimated using the SWAT model. The regionalization with physical similarity approach was adopted here for the calibration, uncertainty and validation processes due to the unavailability of streamflow data in the study catchment. Based on the sensitivity analysis, the top sixteen parameters were calibrated, from which the first three (the base flow alpha factor, curve number II and initial depth of water in the shallow aquifer) were found to be the most sensitive parameters, at p < 0.01. The result for model uncertainty also indicated acceptable values of both the R-factor (0.8) and P-factor (0.7), which is the average of the calibration and validation periods. Regarding the model performance evaluation, four statistical indicators were used, namely the Nash-Sutcliffe Coefficient (NS), the coefficient of determination (R2), the percent bias (PBIAS), and the ratio of the root mean squared error to the standard deviation of measured data (RSR). The results showed that all the model performance indicators were in fairly acceptable ranges; taking the average of calibration and validation periods, NS was 0.76; R2 was 0.78; and RSR was 0.49. The PB, Kolomela Mine

Published
2019

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