The objective was to develop a hydrological assessment for a planned run-of-river hydropower plant in the Lukhra river basin in Georgia. There is no observed river discharge data available. Hence, the assessment was developed based on hydrological simulations of the basin using the SPHY model (Terink et al., 2015) and expert knowledge obtained through previous projects with discharge simulations in the Nakra and Mestiachala river basins in Georgia. State-of-the-art global datasets were used for the biophysical input requirements (e.g. temperature and precipitation) of the hydrological model. The Lukhra basin and a subbasin in the Nakra basin (Utviri) share similar physical characteristics (e.g. slope, area, length of river, difference in elevation, Gravelius coefficient, hypsometric curve) and biophysical characteristics (e.g. temperature and precipitation). Hence, similar model parameters were used as in the calibrated model obtained in the Nakra basin (Kaune et al., 2019) with additional tuning made for Lukhra of one key model parameter on snow dynamics. The main output is the daily river discharge in the Lukhra river (at 1325 m.a.s.l.) for a long representative period of 30 years (1989-2019) and monthly average discharge including the median, 75th and 90th percentile, and the corresponding flow duration curve for the hydropower plant location. In addition, the contribution of rainfall, snow, and baseflow to the river discharge was quantified.
This hydrological assessment delivered river flow estimates for an intake location of a potential hydropower plant in the Lukhra river, Georgia. The assessment included a tuning of a hydrological model based on knowledge of neighboring basins, daily river discharge simulation for an extended period of record (1989-2019), and the derived flow duration curves and statistics to evaluate the flow operation of hydropower turbines. The daily flow calculations for the site can be used in the hydropower calculations, and to assess the overall profitability of the planned investment, considering energy prices, demand, etc.
In the Lukhra basin, snow model parameters were tuned to obtain accurate river flow predictions. Also, the latest technology of remote sensing data on precipitation and temperature (product ERA5-Land) was used to reduce potential errors in flow estimates. Even though these flow estimates are useful for short-medium term evaluations on profitability of the planned investment, climate change pose a challenge for long-term evaluations. Snow-fed systems, such as the Lukhra basin, are driven by a complex combination of temperature and precipitation. Due to future increasing temperature, and changing rainfall patterns, snow cover dynamics change under climate warming. This can lead to shifts in the flows, like a reduction in lowest flows, and higher discharge peaks when the hydrological system shifts towards a more rainfall-runoff influenced system (Lutz et al. 2016). This can jeopardize the sustainability of the project on the long-term. To provide a better understanding of future river flows, it is recommended to develop a climate change impact assessment.