Introduction: Climate change will either improve, reduce, or shift its appropriate climatic habitat of a particular species, which could result in shifts from its geographical range. Predicting the potential distribution through MaxEnt modeling has been developed as an appropriate tool for assessing habitat distribution and resource conservation to protect bamboo species. Methods: Our objective is to model the current and future distribution of Oxytenanthera abyssinica (A. Richard) based on three representative concentration pathways (RCP) (RCP2.6, RCP4.5, and RCP8.5) for 2050s and 2070s using a maximum entropy model (MaxEnt) in Northern Ethiopia. For modeling procedure, 77 occurrence records and 11 variables were retained to simulate the current and future distributions of Oxytenanthera abyssinica in Northern Ethiopia. To evaluate the performance of the model, the area under the receiver operating characteristic (ROC) curve (AUC) was used. Results: All of the AUCs (area under curves) were greater than 0.900, thereby placing these models in the "excellent" category. The jackknife test also showed that precipitation of the coldest quarter (Bio19) and precipitation of the warmest quarter (Bio18) contributed 66.8% and 54.7% to the model. From the area of current distribution, 1367.51 km 2 (2.52%), 7226.28 km 2 (13.29%), and 5377.26 km 2 (9.89%) of the study area were recognized as high, good, and moderate potential habitats of Oxytenanthera abyssinica in Northern Ethiopia, and the high potential area was mainly concentrated in Tanqua Abergele (0.70%), Kola Temben (0.65%), Tselemti (0.60%), and Tsegede (0.31%). Kafta Humera was also the largest good potential area, which accounts for 2.75%. Compared to the current distribution, the total area of the high potential regions and good potential regions for Oxytenanthera abyssinica under the three RCPs (RCP2.6, RCP4.5, and RCP8.5) would increase in the 2050s and 2070s. However, the total area of the least potential regions under the three RCPs (RCP2.6, RCP4.5, and RCP8.5) in 2050s and 2070s would decrease. Conclusion: This study can provide vital information for the protection, management, and sustainable use of Oxytenanthera abyssinica, the resource to address the global climate challenges.

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This research aimed to use WetSpass model to estimate long-term average annual and seasonal groundwater recharge for Birki watershed (45 km 2) in northern Ethiopia using long-term (10 years) hydro-meteorological and biophysical (soil, land use, topography, slope and groundwater depth) data of the watershed. Both primary and secondary input data were collected using field survey and disk-based data collection methods. The model was used to understand the groundwater recharge potential of the given area for wise utilization, proper management and future planning of the water resource. The results showed that, summer (rainy season) recharge ranges from 0 to 41.09 mm/year with mean value of 24.1 mm/year (96.5%), winter (dry season) recharge ranges from 0 to 1.9 mm/year with mean value of 0.8 mm/year (3.5%) and yearly recharge ranges from 0 to 42.6 mm/year with mean value of 24.9 mm/year. Ten years of mean annual precipitation 573 mm contributed to 7.4% as recharge to the groundwater, 7.1% of surface runoff and 85.5% lost as evapotranspiration. Annually, 1.1205 million m 3 water recharges into the groundwater table as recharge from the precipitation for the entire watershed area. Annually on average 0.17 m 3 /d/ha groundwater can be extracted safely without depleting the groundwater. Understanding the groundwater recharge of the Birki watershed is important for management, proper utilization and future planning of water resources for sustainable management. It is also good baseline information for water resource experts and policymakers of the region for further investigation of water resources, design, and developmental activities and for planning purpose.

Introduction: Dispersed trees such as Oxytenanthera abyssinica (A. Rich.) and Dalbergia melanoxylon (Guill. & Perr.) which are objectively maintained or planted on farmland provide a significant contribution to soil fertility improvement. However, there was no quantitative information on the level of soil nutrient additions of these trees to the soil system. Methods: This study was conducted on the farmers' fields in Kafta Humera district, Tigray region (northern Ethiopia), where mature stands of O. abyssinica and D. melanoxylon trees exist. Radial distance-based soil sampling (under the canopy, near to canopy, and far from canopy) was adopted to quantify the role of these trees on soil fertility improvement. Soil parameters tested were soil reaction (pH), total nitrogen (TN), available phosphorus (AvP), electrical conductivity (EC), cation exchange capacity (CEC), and organic carbon (OC). Results: There was a negative linear relationship between the radial distance of the O. abyssinica tree trunk and soil TN, OC, CEC, and AvP contents but not for pH. Similarly, negative linear relationship between distance from D. melanoxylon and TN, OC, and AvP was obtained. The average total nitrogen (0.26% and 0.13%), available phosphorus (7.21 ppm and 6.37 ppm), and organic carbon (1.73% and 1.02%) contents were respectively higher under the tree canopies of O. abyssinica and D. melanoxylon compared with the adjacent open canopies. The amount of soil OC, TN, AvP, and CEC under O. abyssinica tree species was also significantly higher by 69%, 100%, 13%, and 42% compared to that of D. melanoxylon tree species. However, the amount of EC and soil pH was significantly lower by 57% and 19%, respectively. Conclusion: In general, O. abyssinica and D. melanoxylon added a significant amount of nutrients to the soil. Thus, retaining these important tree species on farmland played a positive role in replenishing soil fertility for resource-constrained households so as to reduce chemical fertilizer amendments.

This study aims to estimate long-term average annual and seasonal water balance components for Birki watershed using WetSpass model with the integrated geospatial modeling approach with ten years’ hydro-meteorological and biophysical data of the watershed. Both primary and secondary data were collected using both field survey and disk-based data collection methods. The WetSpass model was used for data analysis purposes. The finding showed that in the summer season the annual groundwater recharge is 24.1 mm year-1 (96.5%), winter season mean groundwater recharge is 0.8 mm year-1 (3.5%) and yearly mean groundwater recharge is 24.9 mm year-1, Surface runoff yearly mean value is 40.6 mm year-1, Soil evaporation yearly mean value is 10.8 mm year-1, Evapotranspiration yearly mean value is 60.8 mm year-1, Intersection loss yearly mean value is 17 mm year-1, and Transpiration loss yearly value is 6.8 mm year-1 in the entire watershed. The mean annual precipitation, which is 573 mm, is contributed to 7.4%, 7.1% and 85.5% recharge to the groundwater, to surface runoff, and evapotranspiration, respectively. Annually 1.1205 million m3 water recharges into the groundwater table as recharge from the precipitation on the entire watershed. The contribution of this study could be used as baseline information for regional water resource experts, policy makers and researchers for further investigation. It can also be concluded that integrated WetSpass and GIS-based models are good indicators for estimating and understanding of water balance components in a given watershed to implement an integrated watershed management plan for sustainable utilization and sustainable development.