Linking Flood Frequency To Long-term Water Balance: Incorporating Effects of Seasonality
01 Jan 2002-pp 5105
TL;DR: In this paper, a quasi-analytical derived flood frequency model is proposed to account for both types of seasonalities, including seasonal variability of storm characteristics and seasonality of rainfall and evapotranspiration.
Abstract: Derived flood frequency models can be used to study climate and land use change effects on the flood frequency curve. Intra-annual (i.e., within year) climate variability strongly impacts upon the flood frequency characteristics in two ways: in a direct way through the seasonal variability of storm characteristics and indirectly through the seasonality of rainfall and evapotranspiration which then affect the antecedent catchment conditions for individual storm events. In this paper we propose a quasi-analytical derived flood frequency model that is able to account for both types of seasonalities. The model treats individual events separately. It consists of a rainfall model with seasonally varying parameters. Increased flood peaks, as compared to block rainfall, due to random within-storm rainfall time patterns are represented by a factor that is a function of the ratio of storm duration and catchment response time. Event runoff coefficients are allowed to vary seasonally and include a random component. Their statistical characteristics are derived from long-term water balance simulations. The components of the derived flood frequency model are integrated in probability space to derive monthly flood frequency curves. These are then combined into annual flood frequency curves. Comparisons with Monte Carlo simulations using parameters that are typical of Austrian catchments indicate that the approximations used here are appropriate. We perform sensitivity analyses to explore the effects of the interaction of rainfall and antecedent soil moisture seasonalities on the flood frequency curve. When the two seasonalities are in phase, there is resonance, which increases the flood frequency curve dramatically. We are also able to isolate the contributions of individual months to the annual flood frequency curve. Monthly flood frequency curves cross over for the parameters chosen here, as extreme floods tend to mainly occur in summer while less extreme floods may occur throughout the year.
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01 Apr 2017
TL;DR: In this paper, a pragmatic approach was used to analyse the hydro-meteorological preconditions of historical damaging floods from 1980 to 2010 in sub-Saharan Africa, and the results indicated that bringing together weather and seasonal conditions can lead to improved flood risk preparedness.
Abstract: Abstract. Most flood early warning systems have predominantly focused on forecasting floods with lead times of hours or days. However, physical processes during longer timescales can also contribute to flood generation. In this study, we follow a pragmatic approach to analyse the hydro-meteorological pre-conditions of 501 historical damaging floods from 1980 to 2010 in sub-Saharan Africa. These are separated into (a) weather timescale (0–6 days) and (b) seasonal timescale conditions (up to 6 months) before the event. The 7-day precipitation preceding a flood event (PRE7) and the standardized precipitation evapotranspiration index (SPEI) are analysed for the two timescale domains, respectively. Results indicate that high PRE7 does not always generate floods by itself. Seasonal SPEIs, which are not directly correlated with PRE7, exhibit positive (wet) values prior to most flood events across different averaging times, indicating a relationship with flooding. This paper provides evidence that bringing together weather and seasonal conditions can lead to improved flood risk preparedness.
27 citations
DOI•
18 Nov 2020
TL;DR: In this paper, a review of extreme value theory under dependence and extreme value under dependence is presented, and a treatment of dependence and extremes in common modelling approaches is presented. But the authors do not discuss the relationship between extreme value and dependence.
Abstract: ................................................................................................................... 17 ΕΚΤΕΝΗΣ ΠΕΡΙΛΗΨΗ ................................................................................................... 18 1.INTRODUCTION ......................................................................................................... 32 1.1 Motivation .........................................................................................................32 1.2 Framing the research question .......................................................................33 1.3 Structure of thesis ............................................................................................35 1.4 Innovation points .............................................................................................36 2.STOCHASTIC DEPENDENCE DYNAMICS FROM THE PARENT PROCESS TO THE EXTREMES: A REVIEW ................................................................................................................ 37 2.1 Definitions in a stochastic framework ..........................................................37 Random variables, stochastic processes and timeseries ..............37 Distribution function and moments ...............................................38 Stationarity, cyclostationarity and ergodicity ..............................39 Dependence in time...........................................................................40 2.2 Second-order properties, scaling laws and HK dynamics .........................40 Climacogram and climacogram-based modelling ........................41 Scaling in time by the entropic view: from predictability to uncertainty .....................................................................................42 2.3 Dependence in extremes: theory and diagnostics .......................................43 The development of classic extreme value theory ........................43 Extreme value theory under dependence ......................................44 Other measures of extremal dependence .......................................47 Cases of stronger dependence .........................................................47 2.4 Treatment of dependence and extremes in common modelling approaches ............................................................................................................................48
19 citations
01 Jan 2019
TL;DR: In this article, a coupled human and natural system (CHANS) model is proposed to understand the impact of hydrological extremes and their societal impact in a changing environment, including droughts and floods, on a wide range of sectors including water availability, food security and energy production.
Abstract: Hydrological extremes, in the form of droughts and floods, have huge impacts on a wide range of sectors including, most prominently, water availability, food security, and energy production, among others. The expectation of heightened drought and flood risk under climate change, coupled with burgeoning population growth and rapid economic development, poses unprecedented challenges for societies to boost resilience to these natural hazards, mitigate their extreme impact, and develop effective and actionable solutions towards sustainable development. The objective of this dissertation is to advance our understanding of these hydroclimate risks and their societal impact in a changing environment through a coupled human and natural system (CHANS). Chapter 2 and 3 diagnose the changing characteristics of droughts and floods from a climate perspective. Chapter 2 compiles the first Global Drought and Flood Catalogue (GDFC) to provide long-term, consistent and robust estimates of drought and flood hazards. This state-of-the-art catalogue acts as a basis for us to understand current risks and how they may change in the future. Based on GDFC, Chapter 3 develops a novel statistical framework to examine the often overlooked but important risk of coincident droughts and floods. Chapter 4 and 5 focus on the human dimension of the CHANS. Using a physical framework, Chapter 4 conducts attribution analysis to disentangle how climate variability and human interventions (e.g., water use, irrigation, reservoir operation) intensify or mitigate the recent California drought. Taking a further step, Chapter 5 aims to incorporate human behaviors and decisions – which are currently unrepresented – into a large-scale hydrological model to investigate how individuals’ decisions and their behavioral heterogeneity affect the dynamics of the CHANS. Chapter 6 develops a hydro-economic model to identify possible solutions and optimal development pathways towards better management of water-related trade-offs (i.e., energy produciii tion and irrigation in California) and environmental sustainability (i.e., groundwater depletion). The integrated modeling platform developed in this thesis can be used to balance trade-offs among conflicting objectives and quantify the potential space for improving current water management strategies, especially under severe hydrological extremes.
8 citations
Cites background from "Linking Flood Frequency To Long-ter..."
..., soil moisture and snowpack conditions) can be related to changing flood risk (Sivapalan et al., 2005), which can also drive drought persistence through reductions in recycled precipitation (e....
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TL;DR: In this paper , the authors provide a coherent overview of the processes causing heavy flood tails and the implications for science and practice and propose nine hypotheses on the mechanisms causing heavy tails in flood peak distributions related to processes in the atmosphere, the catchment, and the river system.
Abstract: Statistical distributions of flood peak discharge often show heavy tail behavior, that is, extreme floods are more likely to occur than would be predicted by commonly used distributions that have exponential asymptotic behavior. This heavy tail behavior may surprise flood managers and citizens, as human intuition tends to expect light tail behavior, and the heaviness of the tails is very difficult to predict, which may lead to unnecessarily high flood damage. Despite its high importance, the literature on the heavy tail behavior of flood distributions is rather fragmented. In this review, we provide a coherent overview of the processes causing heavy flood tails and the implications for science and practice. Specifically, we propose nine hypotheses on the mechanisms causing heavy tails in flood peak distributions related to processes in the atmosphere, the catchment, and the river system. We then discuss to which extent the current knowledge supports or contradicts these hypotheses. We also discuss the statistical conditions for the emergence of heavy tail behavior based on derived distribution theory and relate them to the hypotheses and flood generation mechanisms. We review the degree to which the heaviness of the tails can be predicted from process knowledge and data. Finally, we recommend further research toward testing the hypotheses and improving the prediction of heavy tails.
7 citations
09 Mar 2020
TL;DR: In this article, the authors analyzed the characteristics and process controls of statistical moments of annual maximum peak discharges, including the mean annual flood (MAF), the coefficient of variation (CV), and the coefficients of skewness (CS), for flood series in Europe.
Abstract:
Characteristics and process controls of statistical moments of annual maximum peak discharges, including the mean annual flood (MAF), the coefficient of variation (CV) and the coefficient of skewness (CS), are analyzed for flood series in Europe. The data set consists of observations from 2370 catchments with an average record length of 48 years. The controls are identified by investigating dependencies between the flood moments and catchment area, flood seasonality, climate and catchment characteristics in five regions. The covariates providing the most explanatory power for within-region variability are identified in a regression framework. Preliminary results indicate: MAF and CV are strongly correlated with hydroclimatic catchments characteristics, and to a lesser degree with topography and land use. In the Atlantic region, precipitation is the most important control on the spatial patterns of MAF and CV; in the Mediterranean it is precipitation and aridity; and in Northeastern Europe it is air temperature.
7 citations
References
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1,251 citations
01 Jan 1993
1,004 citations
"Linking Flood Frequency To Long-ter..." refers background in this paper
...Differences in flood processes related to rain-fed (in summer and autumn) and snowmelt driven (spring) floods have received attention in North America and Europe [Waylen and Woo, 1982; Stedinger et al., 1992]....
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TL;DR: In this article, the authors simulate the water balance dynamics of 308 catchments in Austria using a lumped conceptual model involving 11 calibration parameters for two non-overlapping 11-year periods of daily runoff data and compare regionalisation methods for estimating the model parameters in ungauged catchments, in terms of the model performance.
639 citations
"Linking Flood Frequency To Long-ter..." refers methods in this paper
...In Figure 3b the runoff coefficient has been estimated through the application of a variant of the HBV model [Merz and Blöschl, 2003, 2004] and is defined as the direct runoff divided by the sum of rainfall and melt input, averaged over each month and averaged over 30 years of record (thick lines)....
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TL;DR: Time distribution relations have been developed for heavy storms on areas ranging up to 400 square miles and presented in probability terms to provide quantitative information on interstorm variability and to provide average and extreme relations for various applications of the findings.
Abstract: Time distribution relations have been developed for heavy storms on areas ranging up to 400 square miles and presented in probability terms to provide quantitative information on interstorm variability and to provide average and extreme relations for various applications of the findings. It was found that the relations could be represented best by relating per cent of storm rainfall to per cent of total storm time and grouping the data according to the quartile in which rainfall was heaviest. The individual effects of mean rainfall, storm duration, and other storm factors were small and erratic in behavior when the foregoing analytical technique was used. Basin area had a small but consistent effect upon the time distribution. The derived relations are applicable to the Midwest and other areas of similar climate and topography. They can be used in conjunction with published information on spatial distributions and other storm parameters to construct storm models for hydrologic applications.
568 citations
"Linking Flood Frequency To Long-ter..." refers methods in this paper
...The mean storm rainfall intensity is disaggregated further to hourly intensity patterns using stochastically generated mass curves [Huff, 1967], as shown later....
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