Modeling The Impact Of Climate And Land Useland Cover Change On Hydrological Responses In Lake Tana Basin Ethiopia

Environmental pressure resulting from interlinked climate and land use land cover (LULC) changernis increasingly threatening water resources. Evaluating the effect of climate and LULC change onrnwatershed hydrology has become an important research topic for developing appropriate strategiesrnfor the water resources sector. Recently, hydrological impact assessments focused on separaternimpacts of either LULC or climate change. However, both LULC and climate have been changedrnsignificantly since the mid-20th century, and in most parts of the world, including Ethiopia, thernchange will continue in the future. Hence, the focus of this study was to model the impact of LULCrnand climate change on hydrologic processes. Additionally, the climate model’s sensitivity to landuse data and land surface model (LSM) was investigated. The study was conducted in the LakernTana basin which located in northern Ethiopia. The Lake Tana basin is the headwater of the UpperrnBlue Nile basin having a catchment area of 15,140 km2rn. This study mainly focused on the majorrntributaries rivers including Gilgel Abay, Gumara, Ribb, and Megech watershed.rnLULC changes are one of the main human-induced factors influencing the hydrological process.rnThe SWAT hydrological model was calibrated and validated using static land-use (SLU) andrndynamic land-use (DLU) setup to evaluate the impact of LULC changes on the hydrologicalrnprocesses and parameters in Gumara watershed (case study watershed). The SLU setup used singlernland-use data (1985), whereas the DLU setup used four land-use data (1985, 1995, 2005, andrn2015). Results from the LULC study showed that expansion of agriculture (11.1%) and decreasernof forest (2.3%) and shrub-land (8.8%) occurred between 1985 and 2015. SWAT model with DLUrnsetup showed a slightly higher performance than SLU setup, particularly during the calibrationrnperiod. The LULC data for 2015 showed an overall increase in surface runoff (11.6 mm) and peakrnflow (2.4 m3rn/s) and a decrease in evapotranspiration relative to 1985 LULC data. The incorporationrnof DLU into the SWAT model results in a more realistic representation of changes in temporalrnland-use, thus improving the accuracy of estimation of temporal and spatial hydrologicalrnprocesses. Therefore, hydrological modelers should take into account the temporal dynamics ofrnLULC data to improve model simulation performance.rnBesides LULC change, climate change could be a threat to the water resource sector. In order tornaccurately simulate climate data, the Weather Research and Forecasting (WRF) model parametersrnwere chosen on local bases, in particular land-use data and LSM. The result indicated that rnviirnsimulations of temperature and rainfall were sensitive to the choice of LSM and land-use data. Therncombination of updated new land-use (NLU) with Rapid Update Cycle (RUC) and ThermalrnDiffusion (TD) produced very small cold bias (0.27 °C) and warm bias (0.20 °C) for maximumrnand minimum temperature, respectively, whereas rainfall simulation with NLU and Noahrnconfiguration produced the lowest mean bias (2.39 mm/day). The WRF model had limitations inrnterms of detection ability during the occurrence of heavy rainfall. Overall, results suggested thatrnthe application of updated land-use data substantially improved the performance of the WRFrnmodel in simulating temperature and rainfall. The study would provide valuable support inrnidentifying suitable LSM and land-use data that can accurately predict the climate variables in thernBlue Nile basin.rnLake Tana basin is vulnerable to climate change and variability. Climate data for the baselinern(2005-2015) and future period (2045-2055) under two Representative Concentration Pathwaysrn(RCP) scenarios (RCP4.5 and RCP8.5) were simulated using the WRF model. The SWAT modelrnwas used to investigate the impacts of climate change on the four main tributary watersheds of thernLake Tana basin: Gilgel Abay, Gumara, Ribb, and Megech. The result showed that projectedrnchanges in rainfall vary with seasons and watershed under both scenarios. On average, underrnRCP4.5 and RCP8.5 scenarios, the mean annual rainfall may increase by 7.9% and 21.1%,rnrespectively. Minimum temperature may increase by 1.4 °C and 1.9 °C while maximumrntemperature may increase by 1.4 °C and 2.4 °C under RCP4.5 and RCP8.5 scenarios, respectively.rnClimate change under RCP4.5 and RCP8.5 scenarios can increase streamflow by 7.2% and 33%rnand evapotranspiration by 11.2% and 15.2%, respectively. The findings provide valuable insightsrnto implement appropriate water management strategies to mitigate and adapt the negative impactsrnof climate change and variability.rnThe effect of LULC and climate change on Gumara watershed hydrology was assessed usingrnprojected LULC and climate data. Three future LULC scenarios (BAU, EFL, and EIC) wererndeveloped using Land-use Change Evaluation Module in QGIS, based on hypothetical scenarios.rnProjected climate data were simulated using the WRF model under the RCP4.5 and RCP8.5. Thernresult showed that BAU scenario can increase surface runoff by 5.1% and decrease base-flow byrn6.5% without altering streamflow and evapotranspiration noticeably. On the contrary, EIC andrnEFL scenarios can decrease streamflow by 12.5% and 5.2%, and surface runoff by 7.9% and 10%, rnviiirnrespectively, and increase evapotranspiration by 4.9% and 8.9%, respectively. Climate changernunder RCP8.5 can increase streamflow, surface runoff and evapotranspiration significantly byrn34.3%, 51.8%, and 12.2%, respectively. The simulated SF, SR and ET may increase significantlyrnunder the combination of all three land-use and RCP8.5 scenarios. The findings suggested thatrnclimate change may have a greater effect on hydrologic responses than land-use change. Thernexpansion of agriculture (BAU) and the wetter climate (RCP8.5) would exacerbate flooding, whilernthe expansion of irrigation and forest offset SF increase. The findings from this study can be usefulrnto decision-makers and planners in the design of adaptive measures to LULC and climate changes.

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