Stochastic Modeling of Extreme Precipitation: a Regional Approach

Water Resources - 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...     

River Runoff and Probabilistic Forecast of the Caspian Sea Level

The main components ofthe Caspian Sea water balance and water level are assessed. Stochastic models of time series of the water balance components are proposed ustng morphometric dependences specified by creating and processing digital elevation models for the flooded areas. The sea level forecast is obtained by the method of simulation modeling based on algorithms for the generation of Markovian random sequences with non-Gaussian marginal distributions.     

Estimating hydrological characteristics in the Amu Darya River basin under climate change conditions

Under consideration are results of solving the problem of the river water content estimation under conditions of uncertainties of climate change forecasts and the catchment state with a reference to the Amu Darya River basin. When constructing regional climate models, one selected a multimodel approach using the results of several global models and a statistical downscaling method that made the climate scenarios more detailed. The estimates demonstrated that in the medium- and long-term perspective, the Amu Darya River runoff is expected to decrease. As a result of the Bayesian ideology application, using the calculations got with a total probability formula, a prognostic probability curve of an annual river runoff supply of the basin rivers was derived based on different weights given to the estimates of a mean value for different climate scenarios. Prognostic characteristics of the annual runoff for the Amu Darya basin rivers are estimated in a form acceptable for hydrologic and hydroeconomic application.     

Present-day variations of the minimum runoff of the Volga basin rivers

Carried out is the analysis of stationarity of minimum runoff series in summer and winter for the Volga basin rivers. Two conditionally homogeneous periods are singled out within the temporal variations of these characteristics, and the date of their change varies throughout the territory of the basin. The considerable rise in air temperature in winter on the whole territory of the Volga basin is demonstrated as a result of the analysis of meteorological parameters. The relationship between runoff variations and wintertime temperature variations is proposed for predicting the minimum runoff. The distribution of minimum values of runoff is computed using this dependence and the forecast method based on the sum of distributions.     

On the Forecast of Long-Term Changes in the Hydrological Regime of Rivers Using the Results of Climate Modeling

Water Resources - A method is proposed for probabilistic forecasting of river flow under non-stationary conditions based on the Bayesian approach and using the results of climatic system modeling....     

Characteristics of extreme precipitation events within the Amur river basin in summer 2013

We investigated the precipitation characteristics for the summer period of 2013 on the basis of analyzing the daily precipitation amounts according to observational data from the Russian and Chinese meteostations on the territory of the Amur river basin. An analysis is made of the synchronism in the fluctuations of long-term series of precipitation amounts for two summer months (July and August) by using a modified algorithm for a classification of the fields of hydrometeorological characteristics, such as cluster analysis. The study revealed a poor correlation of precipitation amounts in different parts of the basin. We analyzed the interannual fluctuations in absolute maxima of the consecutive precipitation amounts for different periods of time (from 1 to 30 days). It is shown that precipitation over the summer period of 2013 that caused a disastrous flood in the lower reaches of the Amur were extreme primarily as regards the territory encompassed and the flood duration, which was due to a combination of synoptic processes of a different genesis. It was found that the precipitation amounts for periods shorter than 19 days in 2013 were not extreme in terms of intensity. A comparison was made with the year 1984 when there also occurred a flood on the Amur but not as violent. Parameters of the probability curves for 2013 and 1984 are presented for long-term series of maximum precipitation amounts for the summation period of 7 and 30 days. It is concluded that for calculating the maximum possible precipitation amounts which are necessary for assessing the maximum possible floods, it is appropriate to consider synoptic situations with long-lasting precipitation rather than separate short-lasting storm rains.