Quantifying Long‐Term and Event‐Scale Baseflow Effects across the Flood Frequency Curve

2020 ◽  
Vol 56 (5) ◽  
pp. 868-881
Author(s):  
Patricia Spellman ◽  
Veronica Webster
Keyword(s):  
Flood Frequency ◽  
Frequency Curve ◽  
Event Scale

scholarly journals Do Long-Term Natural Disasters Influence Social Trust? Empirical Evidence from China

2021 ◽  
Vol 18 (14) ◽  
pp. 7280
Author(s):  
Yao Li ◽  
Haoyang Li ◽  
Jianqing Ruan
Keyword(s):  
Natural Disasters ◽  
Natural Disaster ◽  
Social Trust ◽  
Geographical Location ◽  
Household Survey ◽  
Flood Frequency ◽  
Psychological Characteristics ◽  
The North ◽  
The Impact

The natural environment is one of the most critical factors that profoundly influences human races. Natural disasters may have enormous effects on individual psychological characteristics. Using China’s long-term historical natural disaster dataset from 1470 to 2000 and data from a household survey in 2012, we explore whether long-term natural disasters affect social trust. We find that there is a statistically significant positive relationship between long-term natural disaster frequency and social trust. We further examine the impact of long-term natural disaster frequency on social trust in specific groups of people. Social trust in neighbors and doctors is stronger where long-term natural disasters are more frequent. Our results are robust after we considering the geographical difference. The effect of long-term natural disasters remains positively significant after we divide the samples based on geographical location. Interestingly, the impact of long-term flood frequency is only significant in the South and the impact of long-term drought frequency is only significant in the North.

scholarly journals Stochastic semi-continuous simulation for extreme flood estimation in catchments with combined rainfall–snowmelt flood regimes

2014 ◽  
Vol 14 (5) ◽  
pp. 1283-1298 ◽  
Author(s):  
D. Lawrence ◽  
E. Paquet ◽  
J. Gailhard ◽  
A. K. Fleig
Keyword(s):  
Frequency Analysis ◽  
Probabilistic Model ◽  
Extreme Precipitation ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Continuous Simulation ◽  
Weather Patterns ◽  
Extreme Flood ◽  
Flood Estimation

Abstract. Simulation methods for extreme flood estimation represent an important complement to statistical flood frequency analysis because a spectrum of catchment conditions potentially leading to extreme flows can be assessed. In this paper, stochastic, semi-continuous simulation is used to estimate extreme floods in three catchments located in Norway, all of which are characterised by flood regimes in which snowmelt often has a significant role. The simulations are based on SCHADEX, which couples a precipitation probabilistic model with a hydrological simulation such that an exhaustive set of catchment conditions and responses is simulated. The precipitation probabilistic model is conditioned by regional weather patterns, and a bottom–up classification procedure was used to define a set of weather patterns producing extreme precipitation in Norway. SCHADEX estimates for the 1000-year (Q1000) discharge are compared with those of several standard methods, including event-based and long-term simulations which use a single extreme precipitation sequence as input to a hydrological model, statistical flood frequency analysis based on the annual maximum series, and the GRADEX method. The comparison suggests that the combination of a precipitation probabilistic model with a long-term simulation of catchment conditions, including snowmelt, produces estimates for given return periods which are more in line with those based on statistical flood frequency analysis, as compared with the standard simulation methods, in two of the catchments. In the third case, the SCHADEX method gives higher estimates than statistical flood frequency analysis and further suggests that the seasonality of the most likely Q1000 events differs from that of the annual maximum flows. The semi-continuous stochastic simulation method highlights the importance of considering the joint probability of extreme precipitation, snowmelt rates and catchment saturation states when assigning return periods to floods estimated by precipitation-runoff methods. The SCHADEX methodology, as applied here, is dependent on observed discharge data for calibration of a hydrological model, and further study to extend its application to ungauged catchments would significantly enhance its versatility.

scholarly journals Regional Flood Frequency Analysis using Dimensionless Index Flood Method

2020 ◽  
Vol 6 (12) ◽  
pp. 2425-2436
Author(s):  
Andy Obinna Ibeje ◽  
Ben N. Ekwueme
Keyword(s):  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Accurate Estimation ◽  
Frequency Curve ◽  
Model Framework ◽  
Index Flood ◽  
Extreme Flood ◽  
Regional Flood Frequency Analysis ◽  
Spatially Distributed ◽  
Regional Flood Frequency

Hydrologic designs require accurate estimation of quartiles of extreme floods. But in many developing regions, records of flood data are seldom available. A model framework using the dimensionless index flood for the transfer of Flood Frequency Curve (FFC) among stream gauging sites in a hydrologically homogeneous region is proposed.  Key elements of the model framework include: (1) confirmation of the homogeneity of the region; (2) estimation of index flood-basin area relation; (3) derivation of the regional flood frequency curve (RFFC) and deduction of FFC of an ungauged catchment as a product of index flood and dimensionless RFFC. As an application, 1983 to 2004 annual extreme flood from six selected gauging sites located in Anambra-Imo River basin of southeast Nigeria, were used to demonstrate that the developed index flood model: , overestimated flood quartiles in an ungauged site of the basin.  It is recommended that, for wider application, the model results can be improved by the availability and use of over 100 years length of flood data spatially distributed at critical locations of the watershed. Doi: 10.28991/cej-2020-03091627 Full Text: PDF

scholarly journals Climatic and basin factors affecting the flood frequency curve: PART II – A full sensitivity analysis based on the continuous simulation approach combined with a factorial experimental design

2000 ◽  
Vol 4 (3) ◽  
pp. 483-498 ◽  
Author(s):  
M. Franchini ◽  
A. M. Hashemi ◽  
P. E. O’Connell
Keyword(s):  
Sensitivity Analysis ◽  
Soil Moisture ◽  
Experimental Design ◽  
Probability Distribution ◽  
Flood Frequency ◽  
Rainfall Regime ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Factorial Experimental Design ◽  
Frequency Curve

Abstract. The sensitivity analysis described in Hashemi et al. (2000) is based on one-at-a-time perturbations to the model parameters. This type of analysis cannot highlight the presence of parameter interactions which might indeed affect the characteristics of the flood frequency curve (ffc) even more than the individual parameters. For this reason, the effects of the parameters of the rainfall, rainfall runoff models and of the potential evapotranspiration demand on the ffc are investigated here through an analysis of the results obtained from a factorial experimental design, where all the parameters are allowed to vary simultaneously. This latter, more complex, analysis confirms the results obtained in Hashemi et al. (2000) thus making the conclusions drawn there of wider validity and not related strictly to the reference set selected. However, it is shown that two-factor interactions are present not only between different pairs of parameters of an individual model, but also between pairs of parameters of different models, such as rainfall and rainfall-runoff models, thus demonstrating the complex interaction between climate and basin characteristics affecting the ffc and in particular its curvature. Furthermore, the wider range of climatic regime behaviour produced within the factorial experimental design shows that the probability distribution of soil moisture content at the storm arrival time is no longer sufficient to explain the link between the perturbations to the parameters and their effects on the ffc, as was suggested in Hashemi et al. (2000). Other factors have to be considered, such as the probability distribution of the soil moisture capacity, and the rainfall regime, expressed through the annual maximum rainfalls over different durations. Keywords: Monte Carlo simulation; factorial experimental design; analysis of variance (ANOVA)

On Hydrologic Similarity: 1. Derivation of the Dimensionless Flood Frequency Curve

1986 ◽  
Vol 22 (11) ◽  
pp. 1549-1554 ◽  
Author(s):  
Eric F. Wood ◽  
Charles S. Hebson
Keyword(s):  
Flood Frequency ◽  
Frequency Curve

Spatially smooth regional estimation of the flood frequency curve (with uncertainty)

2011 ◽  
Vol 408 (1-2) ◽  
pp. 67-77 ◽  
Author(s):  
F. Laio ◽  
D. Ganora ◽  
P. Claps ◽  
G. Galeati
Keyword(s):  
Flood Frequency ◽  
Frequency Curve ◽  
Regional Estimation

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>

Dynamics of seepage mobile inventory in forest and agricultural soils - Results from a comparative multi-year lysimeter study

2020 ◽  
Author(s):  
Katharina Lehmann ◽  
Robert Lehmann ◽  
Kai Uwe Totsche
Keyword(s):  
Land Use ◽  
Agricultural Soils ◽  
Field Studies ◽  
Critical Zone ◽  
Soil Monitoring ◽  
Event Scale ◽  
Weather Events ◽  
Physico Chemical

<p>The mobile inventory in soil seepage is of fundamental importance for soil development and for functioning of subsurface ecosystem compartments. The mobile inventory may encompass inorganic, organo-mineral and organics, dissolved and colloidal, but also particulate matter and microbiota. Still unknown are the conditions and factors that trigger the release and export of seepage-contained mobile matter within soil, and its translocation through the subsurface of the critical zone. Long-term and high-resolution field studies that includes the mobile particulate inventory are essentially lacking. To overcome this knowledge gap, we established long-term soil monitoring plots in the Hainich Critical Zone Exploratory (HCZE; NW-Thuringia, central Germany). Soil seepage from 22 tension-supported lysimeters in topsoil and subsoil, covering different land use (forest, pasture, cropland) in the topographic recharge area of the HCZE, was collected and analyzed by a variety of analytical methods (physico-/chemical and spectroscopic) on a regular (biweekly) and event-scale cycle. With our study we proved that substances up to a size of 50 µm are mobile in the soils. The material spectra comprised minerals, mineral-organic particulates, diverse bioparticles and biotic detritus. Atmospheric forcing was found to be the major factor triggering the translocation of the mobile inventory. Especially episodic infiltration events during hydrological winter seasons (e.g. snow melts) with high seepage volume influences seepage hydrochemistry (e.g. pH, EC) and is important for transport of mobile matter to deeper compartments. Seasonal events cause mobilization of significant amounts of OC. On average, 21% of the total OC of the seepage was particulate (>0.45 µm). Furthermore, our results suggest that the formation environment and the geopedological setting (soil group, parent rock, land use) are controlling factors for the composition and the amount of soil-born mobile inventory. Our study provides evidence for the importance of the mobile inventory fraction >0,45 µm for soil element dynamics and budgets and highlights the role of weather events on soil and subsoil development and subsurface ecosystem functioning.</p>

scholarly journals Concentration-discharge relationships vary among hydrological events, reflecting differences in event characteristics

2020 ◽  
Author(s):  
Julia L. A. Knapp ◽  
Jana von Freyberg ◽  
Bjørn Studer ◽  
Leonie Kiewiet ◽  
James W. Kirchner
Keyword(s):  
Trace Metals ◽  
Major Ions ◽  
Low Frequency ◽  
Solute Concentration ◽  
Biologically Active ◽  
Concentration Data ◽  
Event Scale ◽  
Wide Range ◽  
Insight Into

Abstract. Studying the response of streamwater chemistry to changes in discharge can provide valuable insights into how catchments store and release water and solutes. Previous studies have determined concentration-discharge (cQ) relationships from long-term, low-frequency data of a wide range of solutes. These analyses, however, provide little insight into the coupling of solute concentrations and flow during individual hydrologic events. Event-scale cQ relationships have rarely been investigated across a wide range of solutes and over extended periods of time, and thus little is known about differences and similarities between event-scale and long-term cQ relationships. Differences between event-scale and long-term cQ behavior may provide useful information about the processes regulating their transport through the landscape. Here we analyze cQ relationships of 14 different solutes, ranging from major ions to trace metals, as well as electrical conductivity, in the Swiss Erlenbach catchment. From a 2-year time series of sub-hourly solute concentration data we determined long-term cQ relationships for each solute and compared them to cQ relationships of 30 individual events. The long-term cQ behavior of groundwater-sourced solutes was representative of their cQ behavior during hydrologic events. Other solutes, however, exhibited very different cQ patterns at the event and long-term scale. This was particularly true for trace metals as well as atmospheric and/or biologically active solutes, many of which exhibited highly variable cQ behavior from one event to the next. Most of this inter-event variability in cQ behavior can be explained by factors such as catchment wetness, season, event size, input concentrations, and event-water contributions. We present an overview of the processes regulating different groups of solutes, depending on their origin in and pathways through the catchment. Our analysis thus provides insight into controls on solute variations at the hydrologic event scale.

scholarly journals Stochastic Hybrid Event Based and Continuous Approach to Derive Flood Frequency Curve

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1931
Author(s):  
Alvaro Sordo-Ward ◽  
Ivan Gabriel-Martín ◽  
Paola Bianucci ◽  
Giuseppe Mascaro ◽  
Enrique R. Vivoni ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Hybrid Method ◽  
Peak Flow ◽  
Weather Generator ◽  
Flood Frequency ◽  
Storm Events ◽  
Frequency Curve ◽  
Continuous Simulation ◽  
Event Based ◽  
Frequency Curves

This study proposes a methodology that combines the advantages of the event-based and continuous models, for the derivation of the maximum flow and maximum hydrograph volume frequency curves, by combining a stochastic continuous weather generator (the advanced weather generator, abbreviated as AWE-GEN) with a fully distributed physically based hydrological model (the TIN-based real-time integrated basin simulator, abbreviated as tRIBS) that runs both event-based and continuous simulation. The methodology is applied to Peacheater Creek, a 64 km2 basin located in Oklahoma, United States. First, a continuous set of 5000 years’ hourly weather forcing series is generated using the stochastic weather generator AWE-GEN. Second, a hydrological continuous simulation of 50 years of the climate series is generated with the hydrological model tRIBS. Simultaneously, the separation of storm events is performed by applying the exponential method to the 5000- and 50-years climate series. From the continuous simulation of 50 years, the mean soil moisture in the top 10 cm (MSM10) of the soil layer of the basin at an hourly time step is extracted. Afterwards, from the times series of hourly MSM10, the values associated to all the storm events within the 50 years of hourly weather series are extracted. Therefore, each storm event has an initial soil moisture value associated (MSM10Event). Thus, the probability distribution of MSM10Event for each month of the year is obtained. Third, the five major events of each of the 5000 years in terms of total depth are simulated in an event-based framework in tRIBS, assigning an initial moisture state value for the basin using a Monte Carlo framework. Finally, the maximum annual hydrographs are obtained in terms of maximum peak-flow and volume, and the associated frequency curves are derived. To validate the method, the results obtained by the hybrid method are compared to those obtained by deriving the flood frequency curves from the continuous simulation of 5000 years, analyzing the maximum annual peak-flow and maximum annual volume, and the dependence between the peak-flow and volume. Independence between rainfall events and prior hydrological soil moisture conditions has been proved. The proposed hybrid method can reproduce the univariate flood frequency curves with a good agreement to those obtained by the continuous simulation. The maximum annual peak-flow frequency curve is obtained with a Nash–Sutcliffe coefficient of 0.98, whereas the maximum annual volume frequency curve is obtained with a Nash–Sutcliffe value of 0.97. The proposed hybrid method permits to generate hydrological forcing by using a fully distributed physically based model but reducing the computation times on the order from months to hours.

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