scholarly journals Flood frequency analysis of the Djetinja river

2010 ◽  
Vol 90 (2) ◽  
pp. 15-28 ◽  
Author(s):  
Dragana Milijasevic
Keyword(s):  
Water Resources ◽  
Water Level ◽  
Frequency Analysis ◽  
Drainage Basin ◽  
Flood Frequency ◽  
Water Levels ◽  
Flood Frequency Analysis ◽  
Extreme Water Levels ◽  
High Flows ◽  
Hydrological Forecast

Based on extreme water levels data, using the method of series, a forecast for protection of river has been accomplished, i.e. probable water level maximums of the Djetinja river at Sengolj were measured. High flows were analyzed with a probability from 0.01% to 99.9%. These probabilities indicate the occurrence of high flows of certain values once in 10.000, 1.000, 100, 33, 20 etc years. Applying a hydrological forecast, one can perceive the possibility for using water resources for various purposes, as well as protection of areas and people from flooding. A review of the greatest floods in the Djetinja drainage basin in the last hundred years is given in this paper. .

May long-term historical hydrological data be misleading for flood frequency analysis in current conditions of climate change?

2020 ◽  
Author(s):  
Alexandra Fedorova ◽  
Nataliia Nesterova ◽  
Olga Makarieva ◽  
Andrey Shikhov
Keyword(s):  
Climate Change ◽  
Water Level ◽  
Frequency Analysis ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Economic Damage ◽  
Irkutsk Region ◽  
Extreme Flood ◽  
The Town

<p>In June 2019, the extreme flash flood was formed on the rivers of the Irkutsk region originating from the East Sayan mountains. This flood became the most hazardous one in the region in 80 years history of observations.</p><p>The greatest rise in water level was recorded at the Iya River in the town of Tulun (more than 9 m in three days). The recorded water level was more than 5 m above the dangerous mark of 850 cm and more than 2.5 m above the historical maximum water level which was observed in 1984.</p><p>The flood led to the catastrophic inundation of the town of Tulun, 25 people died and 8 went missing. According to preliminary assessment, economic damage from the flood in 2019 amounted up to half a billion Euro.</p><p>Among the reasons for the extreme flood in June 2019 that are discussed are heavy rains as a result of climate change, melting of snow and glaciers in the mountains of the East Sayan, deforestation of river basins due to clearings and fires, etc.</p><p>The aim of the study was to analyze the factors that led to the formation of a catastrophic flood in June 2019, as well as estimate the maximum discharge of at the Iya River. For calculations, the deterministic distributed hydrological model Hydrograph was applied. We used the observed data of meteorological stations and the forecast values ​​of the global weather forecast model ICON. The estimated discharge has exceeded previously observed one by about 50%.</p><p>The results of the study have shown that recent flood damage was caused mainly by unprepared infrastructure. The safety dam which was built in the town of Tulun just ten years ago was 2 meters lower than maximum observed water level in 2019. This case and many other cases in Russia suggest that the flood frequency analysis of even long-term historical data may mislead design engineers to significantly underestimate the probability and magnitude of flash floods. There are the evidences of observed precipitation regime transformations which directly contribute to the formation of dangerous hydrological phenomena. The details of the study for the Irkutsk region will be presented.</p>

Flood frequency analysis for nonstationary annual peak records in an urban drainage basin

2009 ◽  
Vol 32 (8) ◽  
pp. 1255-1266 ◽  
Author(s):  
Gabriele Villarini ◽  
James A. Smith ◽  
Francesco Serinaldi ◽  
Jerad Bales ◽  
Paul D. Bates ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Drainage Basin ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Urban Drainage ◽  
Annual Peak

scholarly journals Flood frequency analysis of historical flood data under stationary and non-stationary modelling

2015 ◽  
Vol 19 (6) ◽  
pp. 2561-2576 ◽  
Author(s):  
M. J. Machado ◽  
B. A. Botero ◽  
J. López ◽  
F. Francés ◽  
A. Díez-Herrero ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Flood Frequency ◽  
City Council ◽  
Additive Models ◽  
Water Levels ◽  
Flood Frequency Analysis ◽  
Environmental Drivers ◽  
Historical Records ◽  
Nao Index ◽  
Flood Magnitude

Abstract. Historical records are an important source of information on extreme and rare floods and fundamental to establish a reliable flood return frequency. The use of long historical records for flood frequency analysis brings in the question of flood stationarity, since climatic and land-use conditions can affect the relevance of past flooding as a predictor of future flooding. In this paper, a detailed 400 yr flood record from the Tagus River in Aranjuez (central Spain) was analysed under stationary and non-stationary flood frequency approaches, to assess their contribution within hazard studies. Historical flood records in Aranjuez were obtained from documents (Proceedings of the City Council, diaries, chronicles, memoirs, etc.), epigraphic marks, and indirect historical sources and reports. The water levels associated with different floods (derived from descriptions or epigraphic marks) were computed into discharge values using a one-dimensional hydraulic model. Secular variations in flood magnitude and frequency, found to respond to climate and environmental drivers, showed a good correlation between high values of historical flood discharges and a negative mode of the North Atlantic Oscillation (NAO) index. Over the systematic gauge record (1913–2008), an abrupt change on flood magnitude was produced in 1957 due to constructions of three major reservoirs in the Tagus headwaters (Bolarque, Entrepeñas and Buendia) controlling 80% of the watershed surface draining to Aranjuez. Two different models were used for the flood frequency analysis: (a) a stationary model estimating statistical distributions incorporating imprecise and categorical data based on maximum likelihood estimators, and (b) a time-varying model based on "generalized additive models for location, scale and shape" (GAMLSS) modelling, which incorporates external covariates related to climate variability (NAO index) and catchment hydrology factors (in this paper a reservoir index; RI). Flood frequency analysis using documentary data (plus gauged records) improved the estimates of the probabilities of rare floods (return intervals of 100 yr and higher). Under non-stationary modelling flood occurrence associated with an exceedance probability of 0.01 (i.e. return period of 100 yr) has changed over the last 500 yr due to decadal and multi-decadal variability of the NAO. Yet, frequency analysis under stationary models was successful in providing an average discharge around which value flood quantiles estimated by non-stationary models fluctuate through time.

scholarly journals Flood frequency analysis of historical flood data under stationary and non-stationary modelling

2015 ◽  
Vol 12 (1) ◽  
pp. 525-568 ◽  
Author(s):  
M. J. Machado ◽  
B. A. Botero ◽  
J. López ◽  
F. Francés ◽  
A. Díez-Herrero ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Flood Frequency ◽  
City Council ◽  
Additive Models ◽  
Water Levels ◽  
Flood Frequency Analysis ◽  
Environmental Drivers ◽  
Exceedance Probability ◽  
Nao Index ◽  
Flood Magnitude

Abstract. Historical records are an important source of information about extreme and rare floods with a great value to establish a reliable flood return frequency. The use of long historic records for flood frequency analysis brings in the question of flood stationarity, since climatic and land-use conditions can affect the relevance of past flooding as a predictor of future flooding. In this paper, a detailed 400 year flood record from the Tagus River in Aranjuez (Central Spain) was analysed under stationary and non-stationary flood frequency approaches, to assess their implications on hazard studies. Historical flood records in Aranjuez were obtained from documents (Proceedings of the City Council, diaries, chronicles, memoirs, etc.), epigraphic marks, and indirect historical sources and reports. The water levels associated with different floods (derived from descriptions or epigraphic marks) were computed into discharge values using a one-dimensional hydraulic model. Secular variations on flood magnitude and frequency, found to respond to climate and environmental drivers, showed a good correlation between high values of historical flood discharges and a negative mode of the North Atlantic Oscillation index (NAO index). Over the systematic gauge record (1913–2008), an abrupt change on flood magnitude was produced in 1957 due to constructions of three major reservoirs in the Tagus headwaters (Bolarque, Entrepeñas and Buendia) controlling 80% of the watershed surface draining to Aranjuez. Two different models were used for the flood frequency analysis: (a) a stationary model estimating statistical distributions incorporating imprecise and categorical data based on maximum likelihood estimators; (b) a time–varying model based on "generalized additive models for location, scale and shape" (GAMLSS) modelling, that incorporates external covariates related to climate variability (NAO index) and catchment hydrology factors (in this paper a reservoir index; RI). Flood frequency analysis using documentary data (plus gauged record) improved the estimates of the probabilities of rare floods (return intervals of 100 year and higher). Under non-stationary modelling flood occurrence associated with an exceedance probability of 0.01 (i.e. return period of 100 year) has changed over the last 500 year due to decadal and multi-decadal variability of the NAO. Yet, frequency analysis under stationary models was successful on providing an average discharge around which value flood quantiles estimated by non-stationary models fluctuate through time.

scholarly journals Integrating Monte Carlo and the Hydrodynamic Model for Predicting Extreme Water Levels in River Systems

2018 ◽  
Author(s):  
Wen-Cheng Liu ◽  
Hong-Ming Liu
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Water Level ◽  
Engineering Design ◽  
Frequency Analysis ◽  
Hydrodynamic Model ◽  
Water Levels ◽  
Return Periods ◽  
River Systems ◽  
Extreme Water Levels

Estimates of extreme water level return periods in river systems are crucial for hydraulic engineering design and planning. Recorded historical water level data of Taiwan’s rivers are not long enough for traditional frequency analyses when predicting extreme water levels for different return periods. In this study, the integration of a one-dimensional flash flood routing hydrodynamic model with the Monte Carlo simulation was developed to predict extreme water levels in the Danshuei River system of northern Taiwan. The numerical model was calibrated and verified with observed water levels using four typhoon events. The results indicated a reasonable agreement between the model simulation and observation data. Seven parameters, including the astronomical tide and surge height at the mouth of the Danshuei River and the river discharge at five gauge stations, were adopted to calculate the joint probability and generate stochastic scenarios via the Monte Carlo simulation. The validated hydrodynamic model driven by the stochastic scenarios was then used to simulate extreme water levels for further frequency analysis. The design water level was estimated using different probability distributions in the frequency analysis at five stations. The design high-water levels for a 200-year return period at Guandu Bridge, Taipei Bridge, Hsin-Hai Bridge, Da-Zhi Bridge, and Chung-Cheng Bridge were 2.90 m, 5.13 m, 6.38 m, 6.05 m, and 9.94 m, respectively. The estimated design water levels plus the freeboard are proposed and recommended for further engineering design and planning.

scholarly journals Flood Frequency Analysis for the Annual Peak Flows Simulated by an Event-Based Rainfall-Runoff Model in an Urban Drainage Basin

Water ◽  
2014 ◽  
Vol 6 (12) ◽  
pp. 3841-3863 ◽  
Author(s):  
Jeonghwan Ahn ◽  
Woncheol Cho ◽  
Taereem Kim ◽  
Hongjoon Shin ◽  
Jun-Haeng Heo
Keyword(s):  
Frequency Analysis ◽  
Drainage Basin ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Urban Drainage ◽  
Rainfall Runoff ◽  
Annual Peak ◽  
Rainfall Runoff Model ◽  
Event Based ◽  
Runoff Model
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