Abstract
Assessment of the hydrological parameters of the Kalako waterfall on the Tinkisso-Dabola River by the 42-year data reconstruction method from 1971 to 2012. The year of calculation of hydrological parameters is 1989. The values of hydrological parameters (precipitation heights, flow volume and monthly flow) in this year from the site of Kalako determined, are zero in the months of December, January and February. They are minimal during the months of February (8.0 mm, 2.72×10<sup>6</sup> m<sup>3</sup> and 1.04 m<sup>3</sup>/s), April (29.1 mm, 9.89×10<sup>6</sup> m<sup>3</sup> and 3.81 m<sup>3</sup>/s) and November (8.9 mm, 3.02×10<sup>6</sup> m<sup>3</sup> and 1.16 m<sup>3</sup>/s). This results in a very small amount of water during these periods. On the other hand, during the period from May to October, the hydrological parameters of the site are important, with the maximum values observed in September (333.42 mm, 113.02×10<sup>6</sup> m<sup>3</sup> and 43.75 m<sup>3</sup>/s). These results show that, during the year of calculation, seven (7) months (April, May, June, July, August, September and October) out of twelve (12) of the Kalako site are very favorable for the production of hydroelectric power.
Highlights
Rain is essential for water balance studies as well as flow forecasting and simulation since it is used as input to hydrological models
The determination of the main hydrological parameters of a hydroelectric dam site is a function of the coefficients of variability, of the asymmetry, theoretical module and flow
The comparison of the sum of the mean annual rainfall (∑ IJK 1324,95) with the sum of the annual precipitation of the reconstructed data, reveals that the year 1989 with a total of 1339.8mm is best indicated as the year of calculation
Summary
Rain is essential for water balance studies as well as flow forecasting and simulation since it is used as input to hydrological models. Rain and flow are variable elements in time and space. A good spatio-temporal representation of flow and rainfall information is crucial for projections of hydroelectric dam construction [1]. Numerous studies have shown that the spatial and temporal variability of rainfall events can be significant. This rain is typically measured by rain gauges, which measure the amount of water precipitated at one point. The efficiency of these interpolation methods will be conditioned by the sampling of this variable in time and space [2]
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