Seasonal distribution patterns of precipitation on the territory of West Sayan Ridge and their consideration in runoff modeling

Abstract

Specific height dependences of the precipitation based on the daily meteodata analysis (for the period 1970–1985) were obtained for Western Sayan, which is under conditions of insufficient data provided by the scarce network of stations. Analysis revealed that the annual precipitation sum is characterized by closer dependence than seasonal precipitation. It has been generally observed that the linear correlation has the highest reliability for the southern macroslope of the ridge. At the same time the dependence of the northern slope is primarily determined by height: distribution of precipitation is defined by logarithmic function. Thus, the low mountain pluviometric gradient (below 500 m) is characterized by a quick increase in precipitation (in the warm period the gradient reaches a value of 100 mm/100 m). As for the mid-mountain parts (above 1300 m), gradients of warm and cold periods do not exceed 2 mm/100 m. Reliability of identified dependences has been confirmed by model calculations. All the modelled objects and periods were selected considering the existence and availability of both hydrological and meteorological data — the river Us and Amyl basins (right tributaries of Yenisei, Krasnoyarsk district, Russia) which represent typical runoff conditions for the semi-arid and semi-humid areas of the Western Sayan. The investigation also found that the application of seasonal pluviometric gradients during runoff modeling has improved the convergence of calculated and obtained hydrographs. It was shown that taking into account vertical pluviometric gradients turned out to be more significant for semi-arid regions. And furthermore, it has improved the quality of runoff modeling notably for periods characterized by the least value of Nash-Sutcliffe criteria, and reduced the amount of years with improper quality of calculation. This is especially important under conditions of insufficient hydrometeorological data.