This paper proposes a novel chronically evaluated highest instantaneous priority next processor scheduling algorithm. The currently existing algorithms like first come first serve, shortest job first, round-robin, shortest remaining time first, highest response ratio next and varying response ratio priority algorithm have some problems associated with them. Some of them can lead to endless waiting or starvation and some of them like round-robin has problem of too many context switches and high waiting time associated with them. In the proposed algorithm, we have taken care of all such problems. As the novel algorithm is capable of achieving as good results as shortest remaining time first algorithm and also it will never lead to starvation.

Hare River watershed is located in the Abaya-Chamo sub-basin of the southern Ethiopian Rift Valley and drains to Lake Abaya. The study aims to determine the impacts of climate change on rainfall and flood frequency of Hare watershed. In the study the daily data values of rainfall and discharge from 1980-2006 was used based on stream flow measurements carried out by MWIE. The downscaled climate data such as, RCP4.5 and RCP8.5 was used for the future period assessment. Both rainfall and flood frequency analysis was performed using Log-Pearson type III methods for return periods (T) of T = 2 yrs, 5 yrs, 10 yrs, 25 yrs, 50 yrs and 100 yrs. The annual peak flow frequency analysis has been carried out for the future (2020s, 2050s and 2080s) periods using the U.S. Army Corps of Engineers Statistical Software Package (HEC-SSP). RCP8.5 scenario for all return period by 2050s and 2080s predicted an increasing the change in rainfall magnitude. RCP4.5 scenario for all return period by 2020s and 2050s predicted decreasing rainfall magnitude. RCPs scenario predicted the 100-years flood of the current climate seems to increase to a flood return period of (2 yrs, 5 yrs, 10 yrs, 25 yrs and 50 yrs). The rainfall frequency analysis shows climate change will have impact on the frequency and magnitude of rainfall intensity. The future change in rainfall magnitude clearly governs in peak flow magnitude and frequency. Uncertainty analysis is recommended to assess the uncertainty associated with the bias correction method.

Land use/land cover (LULC) change is one of the important factors which have direct impacts on watershed hydrology. The impact of LULC change on streamflow of Upper Awash watershed was carried out using Soil and Water Assessment Tool (SWAT). The LULC change analysis was performed by using unsupervised classification method using Earth Resources Data Analysis System (ERDAS) imagine 8.5 software. The study results showed that the watershed experienced significant LULC change during 1986 to 2009. SWAT model was calibrated for periods 1986 to 1999 and validated for the periods 2000 to 2009. SWAT model was calibrated and validated for the sensitivity of streamflow parameters. Consequently, ten parameters were identified to be sensitive. Further, this model was utilized to assess the impact of LULC change on streamflow for period 1986 to 2009. The result showed that there was a reasonable agreement between observed and simulated streamflow with coefficient of determination (R2) and Nash-Sutcliffe efficiency values 0.86 and 0.77 for calibration, and 0.84 and 0.76 for validation, respectively. The evaluation of SWAT hydrologic response unit (HRU) due to LULC change showed that monthly streamflow was increased by 16.13 % in wet months and decreased by 20.8 % in dry months between the years 1986 and 2000. While between the year 2000 and 2009, it was increased by 0.92 % and 5.82 % for wet and dry months, respectively. Similarly, surface runoff was found increased and groundwater decreased during the study period. Further, the calibrated model can be utilized to understand risk and reliability of different structures and analysis of climate change, water quality, and sediment yield. Hence, this type of study can be useful for sustainable development in the Upper Awash basin as well as in other regions of Ethiopia.