Abstract
Temperature and precipitation trend fluctuations influence the components of the hydrological cycle and the availability of water supplies and result shift in the balance of lake water (lake level). Lake Tana is one of the water resources potential providing many services and threatened by human-induced and natural factors in Upper Blue Nile Basin, Ethiopia. So assessing the impacts of climate change on this water resource is a primary activity for water resource managers, researchers, and stakeholders to understand its potential for the water resource. This study was therefore conducted to examine the implications of the influence of climate change on the water balance of Lake Tana (water level) using potential simulated climate production downscaled by a regional CORDEX climate model powered by GCM-RCM ensembles under the Eastern Africa domain CIMP5 archive (AFR44) and RCP scenarios (RCP4.5, and RCP8.5) for future climate data prediction. Quantile mapping has been used to correct temperature biases, and power transformation was applied for rainfall correction. The performance of the HBV model was evaluated through calibration and validation using objective functions (relative volume error (RVE), Nash-Sutcliffe Efficiency (NSE) and provide RVE of 3.7%, −1.27%, 1.05%, −0.72%, 8.9% and −0.68 during calibration and RVE of −1.5%, 6.93%, −3.04%,8.796%, −5.89% and 8.5% during validation for Gumara, Kiltie, Koga, Gilgel Abay, Megech and Rib respectively. While the model provided NS of 0.79, 0.63, 0.72, 0.803, 0.68 and 0.797 during calibration and NSE of 0.8, 0.64, 0.7, 0.82, 0.801 and 0.82 during validation for Gumara, Kiltie, Koga, Gilgel Abay, Megech, and Rib respectively. The simulated Lake level showed adequate agreement to the observed with NS and RVE of 0.7 and 6.44% respectively. The result showed that lake evaporation and rainfall increase for all future scenarios. The ungauged surface inflow is also increased shortly scenarios while gauged surface inflow increased for RCP4.5 (the 2070s) and RCP8.5 (2040s) and decreased for RCP4.5 (2040s) and RCP8.5 (2070s). The decrease in gauged surface water inflow is due to a decrease in inflow for Gilgel Abay, Koga and Gumara gauged catchments. The results showed that the Lake storage will decrease in all future scenarios of all-time horizons. As the study's revealed climate model minimized the level of uncertainty, especially with the use of more RCMs than GCMs, future studies should therefore use more than one regional climate model and also use fine resolution data like (CMIP 6).
Highlights
According to Maghsood et al, (2019) Climate instability in the world can be defined in terms of temperature rise, sea-level rise, precipitation change, and severe drought and flooding
Evaporation over the lake indicates a systemic rise throughout the entire period in the future scenario (Figure 7)
This study shows that there is a hydrological influence on the Lake water balance from climate change
Summary
The Lake Tana basin covers approximately 15000km area from which the Lake Tana covers an area of approximately 3000 km. The basin consists of wide-area coverage of ungauged catchments and has altitude varying from 1784 at the Lake Tana level and to about 3400m in the mountainous area of the eastern part of the lake in Ribb catchment. There is great uncertainty regarding the contribution of ungauged catchments of the basin to the Lake Tana water balance components. Among the different approaches for calibrating the model to identify the optimum parameter set; manual calibration is functional for this model. Calibration of model parameters is done from (1988-1996) for Koga catchment, (1997-2002) for Kiltie catchment, and (1988-1999) for the reaming gauged catchments of LTSB following a procedure specified in the SMHI manual using 2/3 of the year for calibration and 1/3 of the total year data for validation purpose. Recession coefficient for upper response box Measures of none-linearity to the response of the upper reservoir Maximum capillary flow from the upper response box to soil moisture zone (mm/day)
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