scholarly journals The analysis of time series of river water mineralization in the Dnipro basin with the use of theoretical laws of random variables distribution

2020 ◽  
Vol 29 (1) ◽  
pp. 166-175
Author(s):  
Valeriia A. Ovcharuk ◽  
Mariia E. Daus ◽  
Natalia S. Kichuk ◽  
Mariia I. Myroshnychenko ◽  
Yurii V. Daus
Keyword(s):  
Time Series ◽  
Statistical Methods ◽  
Small Rivers ◽  
The South ◽  
Statistical Parameters ◽  
Annual Average ◽  
Type Iii ◽  
Water Mineralization ◽  
Pearson Type

The analysis of current scientific work on the use of statistical methods in hydrochemical research has shown that this approach is sufficiently substantial, both in Ukraine and abroad. The purpose of this work is to determine the main statistical parameters and to research the possibility of applying theoretical laws of distribution to the time series of water mineralization.This research presents the results of the application of standard statistical methods of hydrometeorological information processing for data on water mineralization at 28 gauges of the Dnipro basin (within Ukraine) for the period from 1990 to 2015. The dynamics of the obtained statistical parameters (long-term annual average, coefficients of variation, asymmetry and autocorrelation) within the Dnipro basin in Ukraine has been analyzed. The average annual values of mineralization vary substantially within the studied part of the Dnipro basin - in the northern part the maximum value of the annual average mineralization is 447 mg/l, as it moves to the south, the mineralization increases and in the sub-basin of the Middle Dnipro it reaches a maximum of 971 mg/l; the highest values are observed in the south (sub-basin of the Lower Dnipro), where they can reach extremely high values for particular small rivers (the Solon River - Novopavlivka village, 3356 mg / l). The long-term variability of mineralization in the rivers of the studied area is insignificant, and the autocorrelation coefficients of the mineralization series are quite high, in most cases they are significant and tend to decrease from the sub-basin of the Prypyat’ river in the north to the sub-basin of the Lower Dnipro river in the south. Within the framework of the presented research, the possibility of using theoretical distribution curves known in hydrology to describe the series of river mineralization, using the example of the Dnipro basin, has also been analyzed. Using Pearson’s fitting criterion, the Pearson type III distributions and the three-parameter distributions by S.M.Krytsky and M.F.Menkel have been verified on their correspondence with the empirical series of mineralization. As a result, it was found that in 85% of cases the Pearson type III distribution can be used, and the three-parameter by S.M.Krytsky and M.F.Menkel can be used in 60% of cases.

Selective statistical estimates of multi-year monthly concentrations of biogenous pollution of small rivers of the Northwest zone of the Russian Federation

2020 ◽  
pp. 9-13
Author(s):  
Sergey Kovalenko
Keyword(s):  
Statistical Processing ◽  
Point Of View ◽  
Small Rivers ◽  
Statistical Parameters ◽  
Monthly Data ◽  
Statistical Estimates ◽  
Scientific Task ◽  
The Russian Federation ◽  
Agricultural Areas

The management of surface watercourses is an urgent scientific task. The article presents the results of statistical processing of long-term monthly data of field observations of hydrological and hydrochemical parameters along the Upper Yerga small river in the Vologda region. Sampling estimates of statistical parameters are obtained, autocorrelation and correlation analyzes are performed. The limiting periods from the point of view of pollution for water receivers receiving wastewater from drained agricultural areas are identified.

scholarly journals ON THE POSSIBILITY OF LONG-TERM FORECASTING OF SEASONAL HYDROMETEOROLOGICAL PHENOMENA

2020 ◽  
Vol 11 (2) ◽  
Author(s):  
Svetlana Morozova ◽  
Mariya Alimpieva
Keyword(s):  
Statistical Methods ◽  
European Part ◽  
The South ◽  
Term Forecast ◽  
Long Term Forecasting ◽  
Model Region ◽  
Three Phases

In present paper the expanding application possibility of physical-statistical methods in long-term forecast are viewed.A nonparametric discriminate analyzing model has been constructed on the South-East of EPR (European part ofRussia). The model is based on consideration of asynchronous bonds between the condition of circulating systems of theAtlantic-Eurasian hemisphere sector and the period of seasonal hydrotermeological events onset on South-East of ЕPR.This model allows distinguishing three cluster areas which associate with three phases of predicted event; commonly,only two cluster areas are distinguished. We would like to present results of predictions testing of training and controlsets. The conclusion of our model region appliance effectiveness is also represented in paper.

scholarly journals Potential and Challenges of Harmonizing 40 Years of AVHRR Data: The TIMELINE Experience

2021 ◽  
Vol 13 (18) ◽  
pp. 3618
Author(s):  
Stefan Dech ◽  
Stefanie Holzwarth ◽  
Sarah Asam ◽  
Thorsten Andresen ◽  
Martin Bachmann ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Observation Time ◽  
Sensor Data ◽  
High Temporal Resolution ◽  
Statistical Parameters ◽  
Medium Resolution ◽  
Long Time ◽  
Earth Observation Satellite

Earth Observation satellite data allows for the monitoring of the surface of our planet at predefined intervals covering large areas. However, there is only one medium resolution sensor family in orbit that enables an observation time span of 40 and more years at a daily repeat interval. This is the AVHRR sensor family. If we want to investigate the long-term impacts of climate change on our environment, we can only do so based on data that remains available for several decades. If we then want to investigate processes with respect to climate change, we need very high temporal resolution enabling the generation of long-term time series and the derivation of related statistical parameters such as mean, variability, anomalies, and trends. The challenges to generating a well calibrated and harmonized 40-year-long time series based on AVHRR sensor data flown on 14 different platforms are enormous. However, only extremely thorough pre-processing and harmonization ensures that trends found in the data are real trends and not sensor-related (or other) artefacts. The generation of European-wide time series as a basis for the derivation of a multitude of parameters is therefore an extremely challenging task, the details of which are presented in this paper.

scholarly journals Time Series Decomposition of the Daily Outdoor Air Temperature in Europe for Long-Term Energy Forecasting in the Context of Climate Change

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1569
Author(s):  
Santiago Moreno-Carbonell ◽  
Eugenio F. Sánchez-Úbeda ◽  
Antonio Muñoz
Keyword(s):  
Time Series ◽  
Outdoor Air ◽  
Annual Average ◽  
Energy Forecasting ◽  
Average Temperature ◽  
Time Series Decomposition ◽  
Temperature Forecasting ◽  
Term Energy ◽  
Annual Average Temperature

Temperature is widely known as one of the most important drivers to forecast electricity and gas variables, such as the load. Because of that reason, temperature forecasting is and has been for years of great interest for energy forecasters and several approaches and methods have been published. However, these methods usually do not consider temperature trend, which causes important error increases when dealing with medium- or long-term estimations. This paper presents several temperature forecasting methods based on time series decomposition and analyzes their results and the trends of 37 different European countries, proving their annual average temperature increase and their different behaviors regarding trend and seasonal components.

Trend of stream temperature and its drivers over the past 55 years in a large European River basin

2021 ◽  
Author(s):  
Hanieh Seyedhashemi ◽  
Florentina Moatar ◽  
Jean-Philippe Vidal ◽  
Dominique Thiery ◽  
Céline Monteil ◽  
...  
Keyword(s):  
River Basin ◽  
Air Temperature ◽  
Cold Water ◽  
Stream Temperature ◽  
Small Rivers ◽  
The South ◽  
Massif Central ◽  
The Past ◽  
Temperature Trends

<p>Air temperature has been increasing all around the world over the past decades. Owing to its sensitivity to air temperature, it is consequently expected that stream temperature experiences an increase as well. However, due to paucity of long-term stream temperature data, assessments of the magnitude of such trends in relation with landscape and hydrological changes have remained scarce.</p><p>The present study used a physically-based thermal model (T-NET: Temperature-NETwork), coupled with a semi-distributed hydrological model (EROS) to reconstruct past daily stream temperatures and discharges at the scale of the Loire River basin in France (10<sup>5</sup> km<sup>2</sup> with 52278 reaches). The ability of both models to reconstruct long-term trends was assessed at 44 gauging stations and 11 stream temperature stations.  </p><p>T-NET simulations over the 1963-2017 period show that there has been a significant increasing trend in stream temperatures for at least 70% of reaches in all seasons (median=0.36 °C/decade). Significantly increasing trends are more prominent in spring (Mar-May) and summer (Jun-Aug) with a median increase of 0.37 °C (0.11 to 0.8°C) and 0.42°C (0.14 to 1 °C) per decade, respectively. For 81 % of reaches, annual stream temperature trends are greater than annual air temperature trends (median ratio=1.21; interquartile ranges: 1.06-1.44). Greater increases in stream temperature in spring and summer are found in the south of the basin, mostly in the Massif Central (up to 1°C/decade) where greater increase in air temperature (up to 0.67 °C/decade) and greater decrease in discharge (up to -16%/decade) occur jointly. The increase of stream temperature is also higher in large rivers compared to small rivers where riparian vegetation shading mitigate the increase in temperature. For the majority of reaches, changes in stream temperature, air temperature, and discharge significantly intensified in the late 1980s.</p><p>These climate-induced changes in the annual and seasonal stream temperature could help us to explain shifts in the phenology and geographical distribution of cold-water fish especially in the south of the basin where trends are more pronounced.</p>

scholarly journals Analysis of Hydrologic Data Using Pearson Type III Distribution

1978 ◽  
Vol 9 (1) ◽  
pp. 31-42 ◽  
Author(s):  
V. M. Shaligram ◽  
V. S. Lele
Keyword(s):  
Confidence Intervals ◽  
Peak Flow ◽  
Likelihood Method ◽  
Short Term ◽  
Type Iii ◽  
Design Engineers ◽  
Pearson Type ◽  
Gumbel’S Distribution ◽  
Pearson Type Iii Distribution

Computation of reliable and precise long term estimates from the available short term hydrologic records is often a challenging task for the design engineers/hydrologists. Peak flow magnitudes relating to ‘sixteen’ streams were utilised for deriving long term estimates using Maximum likelihood method (Gumbel 1941 and Panchang et al. 1962). The results revealed that most of peak flows were underestimated and their departures from the respective prototype magnitudes were of the order of 10 to 40 per cent. These peak flow magnitudes were graduated by the Pearson type III distribution with the result that a perfect calibration (departure within 1 per cent only) was achieved for three streams. For remaining streams the departures were reduced and were within 20 per cent. The precision of the estimates, deduced from the use of the Pearson type III distribution, was ascertained by evaluating the confidence intervals for these estimates. For three cases the confidence intervals (deduced from the latter distribution) were smaller than their counterparts deduced from the Gumbel's distribution. For the remaining streams' data, the confidence intervals were nearly double those obtained with the Gumbel's distribution. Thus to achieve conformity between prototype and model (using the Pearson type III distribution), one has to be content with even slightly less precise estimates, but which are, otherwise, realistic.

Trends and Characteristics of Hydrological Time Series in Finland

2003 ◽  
Vol 34 (1-2) ◽  
pp. 71-90 ◽  
Author(s):  
Veli Hyvärinen
Keyword(s):  
Time Series ◽  
Water Temperature ◽  
The South ◽  
Lake Ice ◽  
The North ◽  
Long Term Trends ◽  
Time Series Analyses ◽  
Water Stage ◽  
In The Beginning

Hydrological time series analyses made in Finland up to 2001 show the following: 1) Precipitation has been increasing in southern and central Finland, and also in the north in winter, during the period 1911-2000. There are, however, no harmonized analyses of areal precipitation to show the exact increase. 2) The annual maximum of the areal water equivalent of snow has been increasing in eastern and northern Finland but decreasing in the south and west during the period 1947-2001. 3) The winter runoff has generally been increasing strongly in southern and slightly in central Finland during the 20th century. In northern Lapland there are no signs of increase in winter or annual flow. Annual discharge in the south and west has also increased to some extent. 4) The existing analyses show no signs of long-term trends in annual evapotranspiration. 5) Long-term fluctuations of water stage have been observed in the major groundwater formations. 6) The series of the date of ice break-up in the river Tornionjoki - starting in 1693 – shows that in recent decades the ice cover of the river has broken up about two weeks earlier than in the beginning of the period. 6) Lake ice maximum thickness series show no noticeable trend. 7) Lake water temperature in south-eastern Finland seems to have been increasing slightly during the period starting in 1924; in central and northern Finland no trends in water temperature have been observed.

ASSESSMENT HARMONIZATION PROBLEMS OF THE LONG RETURN PERIOD FLOODS ON THE DANUBE RIVER

2020 ◽  
Author(s):  
Pavla Pekárová ◽  
◽  
Pavol Miklánek ◽  
Veronika Bačová Mitková ◽  
Marcel Garaj ◽  
...  
Keyword(s):  
Time Series ◽  
Distribution Function ◽  
Return Period ◽  
Danube River ◽  
Type Iii ◽  
The Danube River ◽  
Pearson Type ◽  
Measured Time ◽  
Design Values ◽  
Pearson Type Iii Distribution

One of the basic problems of the flood hydrology was (and still is) the solution of the relationship between peak discharges of the flood waves and probability of their return period. The assessment of the design values along the Danube channel is more complicated due to application of different estimation methods of design values in particular countries downstream the Danube. Therefore, it is necessary to commence the harmonization of the flood design values assessment methods. All methods of estimating floods with a very long return period are associated with great uncertainties. Determining of the specific value of the 500- or 1000-year floods for engineering practice is extremely complex. Nowadays hydrologists are required to determine not only the specific design value of the flood, but it is also necessary to specify confidence intervals in which the flow of a given 100-, 500-, or 1000-year flood may occur with probability, for example, 90 %. The assessment of the design values Qmax can be done by several methods. In this study we have applied the statistical methods based on the assessment of the distribution function of measured time series of the maximum annual discharge. In order to apply regionalization methods for the estimation of the distribution function in this study we used only one distribution - the Pearson Type III distribution with logarithmic transformation of the data (log Pearson Type III distribution - LP3 distribution). To estimate regional skew coefficient for the Danube River we use 20 Qmax measured time series from water gauges along the Danube River from Germany to Ukraine. We firstly analyzed the occurrence of historic floods in several stations along the Danube River. Then we search relationship between the parameter of skewness of the log Pearson type III distribution function and runoff depth, altitude, or basin area in all 20 water gauge. Skewness coefficients of the LP3 distribution in the stations along the Danube River vary between –0.4 and 0.86.

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