Irrigation water management practices are the main strategies to improve water productivity. This research work was focused to study the performance of alternate and paired row furrow irrigation systems at three levels of irrigation (100%, 75%, and 50% of crop evapotranspiration) using different water productivity indicators for onion crops. The experiment had six treatments and replicated three times to evaluate the analysis of variance in SAS software. Water productivity indicators like crop water use efficiency, field water use efficiency, and field water expense efficiency were determined through bulb yield and water which were used by the crop. The crop yield was expressed as the total yield of onion bulbs, and crop water use was expressed as crop evapotranspiration (ETc), gross depth of irrigation, and water expense. The estimated maximum values of crop water use efficiency, field water use efficiency, and field water expense efficiency were 11.941, 16.152, and 9.361 kg m−3, respectively, for paired row furrow irrigation with 50% ETc. The performance of the paired row furrow irrigation system in crop yield and water use was better as compared to the alternate furrow irrigation system at all levels of irrigation.

The yield response factor (Ky) at different crop growth stages for different varieties of teff is important to identify the sensitivity stage to water stress for irrigation water management. However, Ky is affected by crop variety and agroclimatic conditions, but there has been no study for different varieties of teff. Therefore, this study focused on the determination of Ky for different varieties of teff. In total, 18 treatments were designed as randomized complete block design and replicated three times. Crop evapotranspiration was measured using a weighing‐type lysimeter. Yield response factors were determined as a function of yield and crop evapotranspiration at each crop growth stage of teff. Accordingly, the stagewise Ky for the Tseday teff variety was 0.32, 0.39, 0.55 and 0.06 and for the Quncho teff variety 0.19, 0.24, 0.56 and 0.03 for the vegetative, flowering, yield formation and ripening growth stages, respectively. The seasonal Ky values for Tseday and Quncho were 1.30 and 1.11, respectively. Therefore, water stress during the yield formation growth stage is not recommended, whereas it is possible to adopt irrigation water stress at the ripening growth stage to save water. The saved water will be used for the extension of irrigable agricultural areas.

This study aims to evaluate water availability under changing climate scenarios in the Woybo catchment, Ethiopia. The bias-corrected outputs of multiple climate models’ ensemble mean were employed for the 2050 and 2080s against the reference period (1976–2005) under representative concentration pathways (RCPs) for both RCP4.5 and RCP8.5 scenarios. A semi-distributed physically based Hydrologic Engineering Center of Hydrologic Modeling System (HEC-HMS) was used to perform rainfall–runoff simulation. The projected rainfall and temperatures of the watershed will increase in the far future. The predictions from ensemble means of multiple climate models indicated that rainfall of the watershed will likely increase by 25% in the 2050s and 19% in the 2080s under RCP4.5 and RCP8.5, respectively. The discharge projection for the ensemble mean of all climate models shows an increment up to 20 and 19% under RCP 4.5 and RCP8.5, respectively, in the 2050s, whereas it will decline up to 15 and 28% in 2080s, under RCP4.5 and RCP8.5, respectively. This research plays a great role to reduce the impacts of changing climate for sustainable water resources management.

Ethiopia is a growing country which is in need of scientific ground for land use planning and agricultural-based economy. Evaluation of land use/land cover (LULC) changes helps for proper scheduling and use of natural resources with safe administration in accordance with time and dynamic population growth of the country, specifically in the study area. One of the detailed and useful ways to develop land use evaluation and classification maps is the use of geospatial techniques such as remote sensing and geographic information systems (GIS). The main focus of this study is to evaluate the dynamics of land use and land cover (LULC) changes in the Abelti Watershed, Omo-Gibe River basin, Ethiopia. Maximum likelihood algorithm approach supervised classification method was used for identifying the LULC changes using satellite data to know LULC changes in the watershed. Quantifications of spatial and temporal dynamics of land use/cover changes were accomplished by using three satellite images of 2000, 2010, and 2017 and classifying them via a supervised classification algorithm by using Earth Resources and Development System (ERDAS) software and finally applying the postclassification change detection technique was performed by using ArcGIS 10.3. From the LULC analysis, the increase was observed in the agricultural area and settlement area from 2000 to 2017. On the other hand, shrub land followed a declining trend during the study period. However, forest and bare land followed variable trends during the study period in which forest declined from 2000 to 2010 but increased from 2010 to 2017 and bare land increased from 2000 to 2010 and declined from 2010 to 2017. Generally, the driving force behind this change was population growth, rapid urbanization, and deforestation which resulted in a wide range of environmental impacts, including degraded habitat quality in the watershed.