This article considers the possibility of using probabilistic models to analyze the maximal flow discharges of rivers in order to obtain reliable calculated statistical characteristics for basins with poorly studied hydrological features. The research was performed by the example of Cisbaikalia, which is characterized by a flood regime of river flow. It is found that floods in the study area most often occur in summer (July−August), are associated with the climatic characteristics of the region, and are often destructive. The analysis of the maximal flow of rivers is based on data from the Roshydromet observation network. The series of maximal water discharges are checked for homogeneity and, in general, no disturbances in the steady state of runoff caused by climate changes are detected. A generalized distribution of extremes is proposed as the main probabilistic model; it is recommended to determine its parameters on the basis of the group analysis. The integrated approach has been applied for the first time; it combines conventional methods of hydrological calculations, which are most often used to refine the characteristics obtained for the runoff in the zone of extreme values: the apparatus for truncation of distributions; joint analysis of data; a reduction formula with the reduction of the drain modulus value not only to the area of 200 km 2 , but also to the mean height of basins in the region; and the frequency probability method for estimation of obtained results. These methods are recommended by regulatory documents for discharge calculations and are most often individually used. The comprehensive approach described by the authors enables us to take into account the features of the runoff formation in the zone of extreme values and obtain more accurate values of characteristic quantiles of a given probability of excess for use in design on poorly studied rivers of the region.

Methodological approaches and results of estimation of peak flow characteristics of the Iya River taking into account the extreme rainfall flood in the town of 2019, that led to the catastrophic flood in Tulun (the Irkutsk region), are considered. A hydrodynamic model considering the impact of hydraulic structures is proposed to determine the peak flow and to calculate flooding levels. The characteristics of peak flow are determined by various methods, including those considering several floods per year. It is recommended to obtain design values by generalizing the results of several methods of hydrological calculations.

The study is focused on examining and simulating the formation processes of the runoff and pollution export in the case of Rostov (Rostov Velikii), a town in the Volga basin. The diffuse runoff from Rostov territory and its spatial distribution were evaluated for the following components: ammonium, total iron, oil products, sulfates, chlorides, suspended matter, as well as COD and BOD5. The main conclusions and recommendations are based on the authors' experimental studies and simulation with the use of SWMM software complex (storm water management model), as well as long-term engineering studies of urban conditions in the case of underflooding under various projects.

Data on the maximal runoff of rivers in the Don Basin during spring flood are generalized, the cases of nonstationarity of time series are identified along with periods when such changes have taken place. The obtained results are used to evaluate the characteristics of maximal flow of spring flood under nonstationary conditions with the use of Bayesian approach. The results are given as a map of the depths of maximal runoff of spring flood with 1% exceedance probability and recommended for hydrological calculations when designing water-management facilities.

The problem of obtaining the estimated statistical characteristics of maximum river discharge is considered, taking account of its maximally possible values. The solution method is based on reviewing the distributions bounded from above, i.e., having an upper bound. The extreme value of the discharge, characterized by the error in its determination, is used as the value of the upper limit. The calculated distribution function (probability curve) is derived using a Bayesian approach.

A generalized step-by-step statistical method for calculating the maximal precipitation sums of low probability is proposed. The method is applied to the case of daily precipitation for the Amur River basin. Refined statistical characteristics of maximum daily precipitation for the warm period are obtained. A map of daily precipitation of 1% exceedance probability is compiled over the territory of the Amur River. The obtained quantiles of the daily maximum precipitation are compared with probable maximum precipitation values obtained using WMO methodology.

The series of the maximum annual water level in the Amur River are long enough but non-uniform. The need is substantiated in dividing the series of the maximum water level into two uniform periods and in using the certain period (with the duration of more than 35 years) for the subsequent statistical analysis. This is the period which indicates the formation conditions of runoff and maximum water levels including the anthropogenic load (runoff control).

The problem of approximating the probability distribution of maximum water discharges during rain-induced floods is considered. A truncation procedure applied to the analyzed samples is shown to yield acceptable results. The application of a procedure of joint data analysis demonstrated that sample truncation at the median is optimal as a trade-off between approximation quality and information loss.

Statistically treated data of long-term observational series (>30 years) for 66 rivers are used to study the character of distribution of water flow maximums during rain-induced floods in Maritime Territory, Russia. Two probability models are discussed: generalized Pareto distribution (for the domain of very large values) and generalized distribution of extremums (for the rest of the range). The issue of optimal conjunction point of these distributions is discussed. The problem of increasing the accuracy of distribution parameter estimates through data grouping is considered.

An experimental study was made of the emission of spectral lines of Cu I, Cu II, Ne I, and Ne II. The absolute and relative intensities were investigated as well as the influence of the spontaneous radiation on the stimulated emission from a Cu laser. The integrated radiation spectrum of the plasma and its composition were also studied. The influence of some elementary processes on the simulated emission and the effect of the plasma composition on the laser efficiency were considered.