Local adaptation practice in response to climate change in the Bilate River Basin, Southern Ethiopia

Abstract

The study was conducted in the Bilate River Watershed. Bilate River is one of the inland rivers of Ethiopia that drains in to the northern watershed of the Lake Abaya-Chamo Drainage Basin which forms part of the Main Ethiopian Rift and in turn is part of an active rift system of the Great Rift Valley in Africa. This study examined the extent and nature of rainfall variability from recorded data while estimation of evapotranspiration was derived from recorded weather data. Future climate scenarios of precipitation and temperature for the Bilate Watershed were also generated. Analysis of rainfall variability was made by the rainfall anomaly index, coefficient of variance and Precipitation Concentration Index. The FAO-56 reference ET (ETo) approach was used to determine the amount of evapotranspiration. Estimation of the onset and the end of the growing season, and the length of the growing period was done using Instat software. The results show that mean annual rainfall of the upper (2307 m.a.s.l), middle (1772 m.a.s.l) and lower (1361 m.a.s.l) altitude zones of the watershed are in the order of 1100 mm, 1070 mm and 785 mm with CV of 12%, 15% and 17% respectively. Based on the rainfall data record of the latest 30 years, there was a high temporal anomaly in rainfall between 1980 and 2013. The wettest years recorded a Rainfall Anomaly Index of +5, +6 and +8 for stations in the upper, middle and lower altitude zones respectively, where the driest year recorded value is -5 in all the stations. The average onset date of rainfall for the upper zone is April 3+ 8 days, for the middle zone April 10 + 10 days and for the lower zone April 11+ 11 days with CV of 23%, 26% and 29% respectively. The average end dates of the rainy season in the upper and middle zones are October 3+ 5 days and September 25+ 7 days with CV 5% and 7%. The main rainy season ends earlier in the lower zone; it is on July 12 + 10 days with CV of 14%. Climate change scenarios were generated for two Representative Concentration Pathways (RCPs): RCP 4.5 and RCP 8.5 using 20 GCMs from CMIP5 bias-corrected under three future time slices, near-term (2010-2039), mid-century (2040-2069) and end-century (2071-2099). Rainfall is projected to increase in total amount under all-time slices and emissions pathways but with pronounced inter and intra-variability. Minimum temperature will significantly increase during mid-century by 1.810C (RCP 4.5) and xiii 2.550C (RCP 8.5) and by 2.10C (RCP 4.5) and 4.270C (RCP8.5) during end-century. The projected increase in maximum temperature during mid-century is 1.430C under RCP 4.5 and 1.99 0C under RCP 8.5 and during end-century by 1.650C under RCP 4.5 and 3.50C under RCP8.5 during end-century. The Soil and Water Assessment Tool (SWAT) model was selected to simulate stream flow of the watershed. The Alaba Kulito gauging station monthly stream flows from 1990 to 1996 and 1997 to 2002 were used for stream flow calibration and validation respectively. The respective statistical results of the coefficient of determination (R2), Nash–Sutcliffe coefficient (NSE) and percent bias (PB) are 0.79, 0.78 and 0.56 for the calibration period and 0.64, 0.60 and -21.7 for the validation period which show that the model predicted the stream flow at the Alaba Kulito gauging station reasonably. The annual stream flow increased progressively throughout the century for all time periods under both RCP scenarios. The increases under RCP 8.5 scenario are the larger compared to RCP 4.5 scenarios, approximately 42.42% during the 2080s period. The six GCMs selected to see the uncertainties related to GCMs suggest that the river flow will change by small amounts of −6.18 to 7.83% change compared with the baseline. The simulated runoff in the Bilate River depends on the projected amount of rainfall embedded in the GCM structures selected to simulate the future climate and is less dependent on the local temperature increment. The study also assessed the farmers‘ perceptions of the changes on climatic variables and their adaptation options to the impacts of climate variability and change. The determinant factors that influence the choice of farmers to climate change adaptation were also investigated. Above 92% of the surveyed farm households perceived variability and change in climatic variables but 59% of the households participated in one or other of the six major adaptation strategies which most prevailed inside farmers of the watershed. Changing crop variety, using water harvesting scheme, intensifying irrigation, using cover crop or/and mulching, reducing the number of livestock owned and getting offfarm jobs are the main adaptation strategies used by the farming households. The results from the binary logistic model further showed that age and educational level of the household head, farm size and the income level of the household are household characteristics that significantly affect the choice of adaptation options, while access to climate information in the form of seasonal forecasts and local agro ecology are other factors that determined the selection of adaptation methods by the farming households in the study area. The main constraints to adaptation to climate change in the study area were seen to be the knowledge gap in the form of lack of information, shortage of labour and minimal land size. These were the three most explained constraints to climate change as explained by responding household heads.