108 research outputs found
Estimation of design floods using univariate and multivariate flood frequency approach with regard to one wet year
The determination of design discharges and flood waves volumes is an important aspect of river engineering. \ud
The univariate annual maximum (AM), peaks\ud
-ove\ud
r-threshold (POT) and multivariate copula methods were \ud
used in this hydrologic study to investigate the impact of one wet year on the estimation of flood-\ud
related \ud
design variables. The flood frequency analyses (FFA) were performed using daily and hourly discharge data \ud
from three torrential streams in Slovenia where several flash floods occurred in the last decade. The results \ud
of the study indicate that the use of daily discharge data is inappropriate in case of torrential streams because \ud
the loss on informat\ud
ion when compared to hourly hydrologic data is significant. The consideration of one \ud
wet year in the data sample has influence on the relationship between design variable and return period; \ud
however this influence is generally smaller than influence of the selected method to perform the FFA
Flood frequency analysis with peaks over threshold method and annual maximum series method
Floods are natural and dynamic phenomenon. Floods in Slovenia are mostly caused by intensive\ud
rainfall. Active and passive flood mitigations are performed to lower flood threat. Floods can endanger\ud
human lives, therefore effective and quality flood frequency analysis are important and in addition\ud
they are also precondition for flood mitigations.\ud
Flood frequency analysis can be carried out with annual maximum series method or peaks over\ud
threshold method. The main advantage of annual maximum series method is simplicity. Independence\ud
criterion and threshold selection are two important properties of POT method. Due to these difficulties\ud
POT method remains unpopular and underemployed in the practice of design flood estimation. POT\ud
sample is compounded from all peaks above a certain threshold level. Annual maximum series sample\ud
contains only maximum flood of each year.\ud
First part of graduation thesis consist theoretical background of partial duration and annual maximum\ud
series methods. Goodness of fit tests which can be used for testing hypothesis and distributions\ud
comparison are introduced. Confidence intervals are also discussed in thesis.\ud
In practical part of thesis flood frequency analysis are performed. Data from gauging station Litija 1\ud
on river Sava was used for analysis. Some frequently used probability distributions and three different\ud
parameter estimation techniques were used. Method of moments, method of L-moments and\ud
maximum likelihood method were applied to Litija 1 data. POT analyses were carried out for different\ud
threshold values and influence of threshold selection on analysis results was discussed. Goodness of fit\ud
tests were used for determination of the best fit distribution and for comparison of parameter\ud
estimation techniques. We tried to define the optimal threshold value. Analyses results were compared\ud
and we find out that POT method gave better results as annual maximum series method. Log-Pearson\ud
type 3 distribution with parameters estimated with method of L-moments gave the best fit to data.\ud
Method of L-moments gave better results in most of the applied probability distributions as method of\ud
moments and maximum likelihood method
Flood frequency analysis with peaks over threshold method and annual maximum series method
Poplave so redek in izredno dinamičen pojav. V Sloveniji se poplave praviloma dogajajo zaradi
intenzivnih padavin. Za zmanjšanje ogroženosti pred poplavami izvajamo aktivne in pasivne ukrepe,
za katere potrebujemo verjetnostne analize visokih vod. Ker lahko poplave ogrožajo tudi človeška
življenja, je potrebno verjetnostne analize izvesti kvalitetno in zanesljivo.
Verjetnostna analiza visokih vod se najpogosteje dela z metodo letnih maksimumov ali z metodo
vrednosti konic nad izbrano mejno vrednostjo - pragom (POT metodo). Metoda letnih maksimumov je
precej enostavna za uporabo, medtem ko je pri POT metodi potrebno izbrati ustrezne pogoje
neodvisnosti in določiti primerno vrednost praga. Prav zaradi teh lastnosti se POT metoda v praksi
uporablja redkeje kot metoda letnih maksimumov. Pri POT analizi upoštevamo vse dogodke nad
določeno vrednostjo praga. Pri metodi letnih maksimumov vzorec sestavljajo le največji letni pretoki.
V diplomski nalogi je najprej predstavljeno teoretično ozadje obeh metod ter njune prednosti in
slabosti. Sledi opis statističnih testov, ki se lahko uporabijo za določitev najustreznejše porazdelitvene
funkcije ali testiranje hipotez in enačbe, s katerimi lahko določimo intervale zaupanja za ocenjene
vrednosti pretokov.
V praktičnem delu naloge smo za vodomerno postajo Litija 1 na reki Savi naredili verjetnostno analizo
visokovodnih konic z metodo letnih maksimumov in s POT metodo. Pri verjetnostni analizi smo
uporabili različne najpogosteje uporabljene porazdelitvene funkcije in tri različne načine ocenjevanja
parametrov porazdelitev: metodo momentov, metodo L-momentov in metodo največjega verjetja. POT
metodo smo naredili za različne vrednosti praga in analizirali vpliv vrednosti praga na rezultate. Z
uporabo testov smo določili porazdelitveno funkcijo in metodo ocenjevanja parametrov, ki sta dali
najboljše rezultate. Na podlagi priporočil različnih tujih avtorjev, smo poskušali določiti optimalno
vrednost praga. Rezultate POT metode in metode letnih maksimumov smo primerjali in ugotovili, da
je POT metoda dala boljše rezultate kot metoda letnih maksimumov. Pri metodi letnih maksimumov
se je za najbolj učinkovito izkazala logaritemsko Pearsonova porazdelitev tipa 3, kjer so bili parametri
ocenjeni z metodo L-momentov. Rezultati metode L-momentov so bili pri večini porazdelitev boljši,
kot rezultati metode momentov in metode največjega verjetja.Floods are natural and dynamic phenomenon. Floods in Slovenia are mostly caused by intensive
rainfall. Active and passive flood mitigations are performed to lower flood threat. Floods can endanger
human lives, therefore effective and quality flood frequency analysis are important and in addition
they are also precondition for flood mitigations.
Flood frequency analysis can be carried out with annual maximum series method or peaks over
threshold method. The main advantage of annual maximum series method is simplicity. Independence
criterion and threshold selection are two important properties of POT method. Due to these difficulties
POT method remains unpopular and underemployed in the practice of design flood estimation. POT
sample is compounded from all peaks above a certain threshold level. Annual maximum series sample
contains only maximum flood of each year.
First part of graduation thesis consist theoretical background of partial duration and annual maximum
series methods. Goodness of fit tests which can be used for testing hypothesis and distributions
comparison are introduced. Confidence intervals are also discussed in thesis.
In practical part of thesis flood frequency analysis are performed. Data from gauging station Litija 1
on river Sava was used for analysis. Some frequently used probability distributions and three different
parameter estimation techniques were used. Method of moments, method of L-moments and
maximum likelihood method were applied to Litija 1 data. POT analyses were carried out for different
threshold values and influence of threshold selection on analysis results was discussed. Goodness of fit
tests were used for determination of the best fit distribution and for comparison of parameter
estimation techniques. We tried to define the optimal threshold value. Analyses results were compared
and we find out that POT method gave better results as annual maximum series method. Log-Pearson
type 3 distribution with parameters estimated with method of L-moments gave the best fit to data.
Method of L-moments gave better results in most of the applied probability distributions as method of
moments and maximum likelihood method
Fluvial transport of suspended sediments related to other hydrologic processes
Razumevanje in poznavanje procesov, ki sestavljajo vodni oziroma hidrološki ter erozijskosedimentacijski
krog, ki se medsebojno prepletata, je pomembno z vidika varstva pred naravnimi nesrečami ter zagotavljanja ustreznih pogojev za življenje (npr. pitna voda). V doktorski disertaciji
so obravnavani naslednji procesi:
uvialno premeščanje suspendiranih snovi, površinski
odtok vode, padavine ter erozijski procesi.
V disertaciji so najprej opisani in predstavljeni hidrološki procesi, sledi opis merskih metod, ki
so bile uporabljene za izvedbo meritev. Nadalje je podan opis obravnavanih porečij vključno
z eksperimentalnim porečjem, kjer so se meritve z visoko frekvenco vzorčenja izvajale v okviru
doktorske disertacije, sledi opis uporabljenih statistično-matematičnih metod, ki so bile uporabljene
za analizo podatkov, pri tem je poudarek na funkcijah kopula, ki omogočajo hkratno
analizo dveh ali več v naravi bolj ali manj odvisnih spremenljivk. V zadnjem poglavju prvega
dela disertacije pa so prikazane osnove modeliranja erozije tal s poudarkom na modelu WATEM/
SEDEM.
V drugem delu disertacije so prikazani rezultati različnih terenskih meritev (npr. meritve
uvialnega
premeščanja suspendiranih snovi, padavin, pretokov, erozije tal), izvedena je analiza
povezanosti
uvialnega premeščanja suspendiranih snovi z drugimi hidrološkimi procesi, prikazani
so rezultati modeliranja erozije tal ter uporabe funkcij kopula.
Ugotovili smo, da imajo padavinski dogodki velikih intenzitet nadpovprečen vpliv na procese
sproščanja, premeščanja in odlaganja erozijskega materiala. Količine premeščenega materiala so
lahko pri teh dogodkih nekaj velikostnih razredov večje od dolgoletnega povprečja. V Sloveniji
do nastopa konice
uvialno premeščenih suspendiranih snovi večinoma prihaja pred nastopom
konice pretoka, pri tem pa so časovne razlike večinoma relativno majhne (do 1 dneva). Nadalje
se količine
uvialno premeščenih suspendiranih snovi v slovenskih vodotokih večinoma zmanjšujejo, kar je lahko posledica različnih vzrokov, kot sta zaraščanje površja zaradi opuščanja
kmetijske obdelave ter zapiranje rudnikov. Z aplikacijo modela WATEM/SEDEM na 5 porečjih
v Sloveniji je bilo ugotovljeno, da se koeficient odplavljanja zmanjšuje z večanjem prispevnega
območja. Funkcije kopula pa so bile uporabljene za multivariatne verjetnostne analize poplavnih
dogodkov, kjer smo hkrati upoštevali konice pretokov, volumne visokovodnih valov ter trajanja
visokovodnih valov, poleg tega pa smo funkcije kopula uporabili tudi za analizo podatkov o
suspendiranih snoveh ter za ocenjevanje vrednosti
uvialno premeščenih suspendiranih snovi na
podlagi podatkov o pretokih in padavinah.Understanding and knowledge about the processes that define water or hydrologic cycle and
erosion-sedimentation cycle (these two cycles are inter-connected) is important in order to ensure
safety during natural disasters and to provide suffcient conditions for life (e.g. drinkable
water). In the presented thesis we investigated next processes:
uvial transport of suspended
sediments, surface runoff, rainfall and erosion processes.
Firstly, the investigated hydrological processes are described, then the measuring methods
are presented. Further, the investigated catchments including experimental catchment where
high-frequency measurements were performed are described, in the next section the statisticalmathematical
tools that were used for data analysis are shown. The emphasis was given to
the copula functions that can be used for simultaneous study of two or more (in)dependent
variables that define the environmental process. In the last section of the first part of thesis,
the basic concepts of soil erosion modelling are presented where the emphasis was given to the
WATEM/SEDEM model that can be used for soil erosion modelling.
In the second part of the thesis, results of field measurements are presented (e.g. measurements
of
uvial transport of suspended sediments, rainfall, discharge and soil erosion), analysis of connection
between
uvial transport of suspended sediments and other hydrological processes was
carried out, soil erosion modelling results are described and application of copula functions is
shown on practical examples.
The main conclusions are: rainfall events that have large rainfall intensities have significant impact
on erosion, transport and deposition processes. During these kinds of events the suspended
sediment budgets can be for a few orders of magnitude larger than the long-term annual rates. In
Slovenia the peak of the suspended sediment transport mostly occurs before the peak discharge
but the time differences are rather small (up to 1 day). Moreover, the trends in the transport of
suspended sediments in Slovenian streams are mostly negative (all statistically significant trends
are negative). Reasons for this can be: closing of mines or foresterisation (abandoning of farming
due to urbanisation). Application of the WATEM/SEDEM model showed that sediment delivery
ratio decreases with increasing catchment area. Moreover, copula functions were used for
multivariate
ood frequency analysis where peak discharge, hydrograph volume and hydrograph
duration were considered in the analysis. Moreover, copula functions were also used to analyse
suspended sediment data and for the estimation of the suspended sediment values based on the
measured discharge and rainfall values
Design Rainfall in Engineering Applications with Focus on the Design Discharge
Design hyetograph or design storm definition is one of the most important parts of the design discharge determination in case of ungauged catchments. Design hyetograph duration and temporal rainfall distribution can have large impact on the peak discharge values and the shape of the runoff hydrograph. The influence of these two factors on the design runoff values is presented in the case study of the Glinščica River catchment that covers 16.85 km2 and it is located in central part of Slovenia, Europe. A combination of Huff and intensity-duration-frequency (IDF) curves is used to construct the design hyetograph for the presented case study. The duration of the design storm is determined by the catchment time of concentration. The results are compared to the Natural Resources Conservation Service (NRCS) curves and the so-called frequency storm method. The hydrological modeling result that was carried out using the hydrologic modeling system (HEC-HMS) software indicates that differences among different methods should not be neglected. For the 10-year return period, differences in the peak discharge values can be larger than 10%, while even larger differences can be expected for longer return periods. Some studies showed that these can be larger than 50%. Therefore, the guidelines on how to construct the design hyetograph are presented
The influence of the choice of method on the results of frequency analysis of peaks, volumes and durations of flood waves of the Sava river in Litija
Complex hydrological events such as floods always appear as a consequence of several correlated random\ud
variables (peak, volume, duration). Therefore single-variable frequency analysis can only provide limited\ud
assessment of these events. To fully understand all three variables and their relationship, a multivariate\ud
statistical approach is necessary. A precondition for such an approach is a complete analysis of all individual\ud
variables. 58 years of data from gauging station Litija on the Sava River were analyzed. Peaks, volumes and\ud
durations of flood waves were considered in the flood frequency analysis. Statistical and graphical tests were\ud
used to assess performance of the most commonly used distribution functions and parameter estimation\ud
techniques. Log-Pearson III distribution gave the best results in case of peaks and durations of flood waves\ud
and Pearson III distribution in case of volumes. Method of L-moments, which has not yet been used in\ud
Slovenian hydrological practice, gave the best estimation of parameters for most distributions
Comparison between classical univariate frequency analysis and bivariate analysis with copula
Frequency analyses are a basis for designing discharge estimations. Univariate flood frequency analyses are usually applied in hydrological practice. Hydrological processes are multivariate, however multivariate analyses are needed. Copula function can be used for multivariate modelling. Classical univariate flood frequency analyses are a precondition for the copula analyses. Flood frequency analyses were made on the annual maximum series data from gauging station Litija on the Sava River. Three copulas from the Archimedean family were used; parameters were estimated with method of moments (based on the Kendall correlation coefficient). Some joint return periods were calculated and compared with the univarite return periods. Differences between return periods were not negligible. In the case of a flood event in 1990, which was the largest in the observed period, TAND was 92 years and TOR was 17 years. Univariate return periods lay between these two values. Statistical and graphical performance measures were used to choose the best fit copula function. Gumbel-Hougaard copula gave better results than Clayton and Frank copulas
Does it really rain more often on weekends than on weekdays? A case study for Slovenia
The article presents the results of precipitation and aerosol (PM10) data analyses in Slovenia. Analyses of rainfall data for some areas of Slovenia, such as the Ljubljana Basin, Zasavje, Šalek Valley, Celje Basin, and the coastal area, suggest that rain on the weekend is more frequent than on weekdays; nevertheless, these deviations are not statistically significant. A comparison of three separate decades showed that the pattern of weekly rainfall in the 21st century is different than that in the last period of the 20th century. The weekly cycle of PM10 for the considered stations is quite similar to that of some of the more contaminated regions of the world. Furthermore, the connection between PM10 and precipitation in most of the analyzed cases was statistically significant
Short-term streamflow forecasting using the feature-enhanced regression model
Reservoir inflow forecasting is extremely important for the management of a reservoir. In practice, accurate forecasting depends on the feature learning performance. To better address this issue, this paper proposed a feature-enhanced regression model (FER), which combined stack autoencoder (SAE) with long short-term memory (LSTM). This model had two constituents: (1) The SAE was constructed to learn a representation as close as possible to the original inputs. Through deep learning, the enhanced feature could be captured sufficiently. (2) The LSTM was established to simulate the mapping between the enhanced features and the outputs. Under recursive modeling, the patterns of correlation in the short term and dependence in the long term were considered comprehensively. To estimate the performance of the FER model, two historical daily discharge series were investigated, i.e., the Yangtze River in China and the Sava Dolinka River in Slovenia. The proposed model was compared with other machine-learning methods (i.e., the LSTM, SAE-based neural network, and traditional neural network). The results demonstrated that the proposed FER model yields the best forecasting performance in terms of six evaluation criteria. The proposed model integrates the deep learning and recursive modeling, and thus being beneficial to exploring complex features in the reservoir inflow forecasting. Moreover, for smaller catchments with significant torrential characteristics, more data are needed (e.g., at least 20 years) to effectively train the model and to obtain accurate flood-forecasting results
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