Subscribe to our Newsletter and get informed about new publication regulary and special discounts for subscribers!

ILNS > Volume 74 > Geographic Pattern as a Determinant Factor of...
< Back to Volume

Geographic Pattern as a Determinant Factor of Interlinking Climatic and Hydrological Components of the Natural Resources

Full Text PDF


Some of the practical implications of the previously identified geographic patterns linking climate rate of surface temperature with the fractal dimension of a multi-year series of runoff, are presented. The statistical data, showing a role of coefficient of kurtosis at classification of distributions of density of probability in a range of air temperatures from –5 to 27 degrees Celsius are given. It is empirically established that statistical distributions of long-term average annual runoff series for the temperature zone with prevailing high values of the fractal dimension correspond to beta-distributions of type II and when plotted on the K. Pearson diagram this type is distinguished from probability density curves in other temperature zones by kurtosis (statistically significant). It is revealed that ignoring the coefficient of kurtosis means not taking into account the climatic component of natural resources. The results of the study can be used to assess the reliability of hydraulic structures and in the field of water management.


International Letters of Natural Sciences (Volume 74)
E. V. Gaidukova and V. V. Kovalenko, "Geographic Pattern as a Determinant Factor of Interlinking Climatic and Hydrological Components of the Natural Resources", International Letters of Natural Sciences, Vol. 74, pp. 49-55, 2019
Online since:
March 2019

[1] Set of Rules 33-101-2003, Determination of the main calculated hydrological characteristics, Moscow, State Building of Russia, 2004. (In Russian).

[2] V.V. Kovalenko, Partially infinite modelling: basis, examples, paradoxes, Polytechnic, St. Petersburg, Russian Federation, 2005. (In Russian).

[3] V.I. Naidenov, Nonlinear dynamics of surface land waters, Science, Moscow, Russian Federation, 2004. (In Russian).

[4] V.V. Kovalenko et al., Forecasting the changes in the fractal dimension of the long-term river flow, Geography and Natural Resources. 4 (2008) 136–143. (In Russian).

[5] F. Takens, Detecting strange attractors in turbulence, Lect. Notes in Match, Berlin, Springer, 1981, p.336–381.

[6] V.V. Kovalenko, E.V. Gaidukova, Influence of climatological norms of the surface air temperature on the fractal dimensionality of the series of long-term river discharge, Doklady Earth Sciences. 439(2) (2011) 1183–1185..


[7] S.N. Kritsky, M.F. Menkel, On the techniques for studying random fluctuations of river runoff, Proceedings of NRU GUGMS. 4 (1946) 3–32. (In Russian).

[8] V.V. Kovalenko, Theoretical and experimental substantiation of the correlation between the fractal dimension of long-term flow series and the climatic norm of surface air temperature, Doklady Earth Sciences. 444(2) (2012) 666–670..


[9] A.K. Mitropolsky, Technique of statistical calculations, Science, Moscow, USSR, 1971. (In Russian).

[10] V. Kovalenko, E. Gaidukova, A. Kachalova, An opportunity of application of excess factor in hydrology, Hydrology and Earth System Sciences Discussions. 9 (2012), 13635-13649..


[11] V.I. Tikhonov, Statistical radio engineering, Radio and Communication, Moscow, USSR, 1982. (In Russian).

Show More Hide
Cited By:
This article has no citations.