TY - JOUR A1 - Barendrecht, Marlies H. A1 - Viglione, Alberto A1 - Kreibich, Heidi A1 - Merz, Bruno A1 - Vorogushyn, Sergiy A1 - Blöschl, G. T1 - The Value of Empirical Data for Estimating the Parameters of a Sociohydrological Flood Risk Model JF - Water resources research N2 - In this paper, empirical data are used to estimate the parameters of a sociohydrological flood risk model. The proposed model, which describes the interactions between floods, settlement density, awareness, preparedness, and flood loss, is based on the literature. Data for the case study of Dresden, Germany, over a period of 200years, are used to estimate the model parameters through Bayesian inference. The credibility bounds of their estimates are small, even though the data are rather uncertain. A sensitivity analysis is performed to examine the value of the different data sources in estimating the model parameters. In general, the estimated parameters are less biased when using data at the end of the modeled period. Data about flood awareness are the most important to correctly estimate the parameters of this model and to correctly model the system dynamics. Using more data for other variables cannot compensate for the absence of awareness data. More generally, the absence of data mostly affects the estimation of the parameters that are directly related to the variable for which data are missing. This paper demonstrates that combining sociohydrological modeling and empirical data gives additional insights into the sociohydrological system, such as quantifying the forgetfulness of the society, which would otherwise not be easily achieved by sociohydrological models without data or by standard statistical analysis of empirical data. Y1 - 2019 U6 - https://doi.org/10.1029/2018WR024128 SN - 0043-1397 SN - 1944-7973 VL - 55 IS - 2 SP - 1312 EP - 1336 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Sairam, Nivedita A1 - Schröter, Kai A1 - Lüdtke, Stefan A1 - Merz, Bruno A1 - Kreibich, Heidi T1 - Quantifying Flood Vulnerability Reduction via Private Precaution JF - Earth future N2 - Private precaution is an important component in contemporary flood risk management and climate adaptation. However, quantitative knowledge about vulnerability reduction via private precautionary measures is scarce and their effects are hardly considered in loss modeling and risk assessments. However, this is a prerequisite to enable temporally dynamic flood damage and risk modeling, and thus the evaluation of risk management and adaptation strategies. To quantify the average reduction in vulnerability of residential buildings via private precaution empirical vulnerability data (n = 948) is used. Households with and without precautionary measures undertaken before the flood event are classified into treatment and nontreatment groups and matched. Postmatching regression is used to quantify the treatment effect. Additionally, we test state-of-the-art flood loss models regarding their capability to capture this difference in vulnerability. The estimated average treatment effect of implementing private precaution is between 11 and 15 thousand EUR per household, confirming the significant effectiveness of private precautionary measures in reducing flood vulnerability. From all tested flood loss models, the expert Bayesian network-based model BN-FLEMOps and the rule-based loss model FLEMOps perform best in capturing the difference in vulnerability due to private precaution. Thus, the use of such loss models is suggested for flood risk assessments to effectively support evaluations and decision making for adaptable flood risk management. KW - flood loss KW - average treatment effect KW - matching methods KW - loss models KW - risk analysis KW - adaptation Y1 - 2019 U6 - https://doi.org/10.1029/2018EF000994 SN - 2328-4277 VL - 7 IS - 3 SP - 235 EP - 249 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Steirou, Eva A1 - Gerlitz, Lars A1 - Apel, Heiko A1 - Sun, Xun A1 - Merz, Bruno T1 - Climate influences on flood probabilities across Europe JF - Hydrology and earth system sciences : HESS N2 - The link between streamflow extremes and climatology has been widely studied in recent decades. However, a study investigating the effect of large-scale circulation variations on the distribution of seasonal discharge extremes at the European level is missing. Here we fit a climate-informed generalized extreme value (GEV) distribution to about 600 streamflow records in Europe for each of the standard seasons, i.e., to winter, spring, summer and autumn maxima, and compare it with the classical GEV distribution with parameters invariant in time. The study adopts a Bayesian framework and covers the period 1950 to 2016. Five indices with proven influence on the European climate are examined independently as covariates, namely the North Atlantic Oscillation (NAO), the east Atlantic pattern (EA), the east Atlantic-western Russian pattern (EA/WR), the Scandinavia pattern (SCA) and the polar-Eurasian pattern (POL). It is found that for a high percentage of stations the climate-informed model is preferred to the classical model. Particularly for NAO during winter, a strong influence on streamflow extremes is detected for large parts of Europe (preferred to the classical GEV distribution for 46% of the stations). Climate-informed fits are characterized by spatial coherence and form patterns that resemble relations between the climate indices and seasonal precipitation, suggesting a prominent role of the considered circulation modes for flood generation. For certain regions, such as northwestern Scandinavia and the British Isles, yearly variations of the mean seasonal climate indices result in considerably different extreme value distributions and thus in highly different flood estimates for individual years that can also persist for longer time periods. Y1 - 2019 U6 - https://doi.org/10.5194/hess-23-1305-2019 SN - 1027-5606 SN - 1607-7938 VL - 23 IS - 3 SP - 1305 EP - 1322 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - He, Zhihua A1 - Unger-Shayesteh, Katy A1 - Vorogushyn, Sergiy A1 - Weise, Stephan M. A1 - Kalashnikova, Olga A1 - Gafurov, Abror A1 - Duethmann, Doris A1 - Barandun, Martina A1 - Merz, Bruno T1 - Constraining hydrological model parameters using water isotopic compositions in a glacierized basin, Central Asia JF - Journal of hydrology N2 - Water stable isotope signatures can provide valuable insights into the catchment internal runoff processes. However, the ability of the water isotope data to constrain the internal apportionments of runoff components in hydrological models for glacierized basins is not well understood. This study developed an approach to simultaneously model the water stable isotopic compositions and runoff processes in a glacierized basin in Central Asia. The fractionation and mixing processes of water stable isotopes in and from the various water sources were integrated into a glacio-hydrological model. The model parameters were calibrated on discharge, snow cover and glacier mass balance data, and additionally isotopic composition of streamflow. We investigated the value of water isotopic compositions for the calibration of model parameters, in comparison to calibration methods without using such measurements. Results indicate that: (1) The proposed isotope-hydrological integrated modeling approach was able to reproduce the isotopic composition of streamflow, and improved the model performance in the evaluation period; (2) Involving water isotopic composition for model calibration reduced the model parameter uncertainty, and helped to reduce the uncertainty in the quantification of runoff components; (3) The isotope-hydrological integrated modeling approach quantified the contributions of runoff components comparably to a three-component tracer-based end-member mixing analysis method for summer peak flows, and required less water tracer data. Our findings demonstrate the value of water isotopic compositions to improve the quantification of runoff components using hydrological models in glacierized basins. KW - Water stable isotope KW - Isotope-hydrological integrated modeling KW - Quantification of runoff components KW - Glacierized basins Y1 - 2019 U6 - https://doi.org/10.1016/j.jhydrol.2019.01.048 SN - 0022-1694 SN - 1879-2707 VL - 571 SP - 332 EP - 348 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Rözer, Viktor A1 - Kreibich, Heidi A1 - Schröter, Kai A1 - Müller, Meike A1 - Sairam, Nivedita A1 - Doss-Gollin, James A1 - Lall, Upmanu A1 - Merz, Bruno T1 - Probabilistic Models Significantly Reduce Uncertainty in Hurricane Harvey Pluvial Flood Loss Estimates JF - Earths future N2 - Pluvial flood risk is mostly excluded in urban flood risk assessment. However, the risk of pluvial flooding is a growing challenge with a projected increase of extreme rainstorms compounding with an ongoing global urbanization. Considered as a flood type with minimal impacts when rainfall rates exceed the capacity of urban drainage systems, the aftermath of rainfall-triggered flooding during Hurricane Harvey and other events show the urgent need to assess the risk of pluvial flooding. Due to the local extent and small-scale variations, the quantification of pluvial flood risk requires risk assessments on high spatial resolutions. While flood hazard and exposure information is becoming increasingly accurate, the estimation of losses is still a poorly understood component of pluvial flood risk quantification. We use a new probabilistic multivariable modeling approach to estimate pluvial flood losses of individual buildings, explicitly accounting for the associated uncertainties. Except for the water depth as the common most important predictor, we identified the drivers for having loss or not and for the degree of loss to be different. Applying this approach to estimate and validate building structure losses during Hurricane Harvey using a property level data set, we find that the reliability and dispersion of predictive loss distributions vary widely depending on the model and aggregation level of property level loss estimates. Our results show that the use of multivariable zero-inflated beta models reduce the 90% prediction intervalsfor Hurricane Harvey building structure loss estimates on average by 78% (totalling U.S.$3.8 billion) compared to commonly used models. KW - pluvial flooding KW - loss modeling KW - urban flooding KW - probabilistic KW - Hurricane Harvey KW - climate change adaptation Y1 - 2019 U6 - https://doi.org/10.1029/2018EF001074 SN - 2328-4277 VL - 7 IS - 4 SP - 384 EP - 394 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Winter, Benjamin A1 - Schneeberger, Klaus A1 - Dung, N. V. A1 - Huttenlau, M. A1 - Achleitner, S. A1 - Stötter, J. A1 - Merz, Bruno A1 - Vorogushyn, Sergiy T1 - A continuous modelling approach for design flood estimation on sub-daily time scale JF - Hydrological sciences journal = Journal des sciences hydrologiques N2 - Design flood estimation is an essential part of flood risk assessment. Commonly applied are flood frequency analyses and design storm approaches, while the derived flood frequency using continuous simulation has been getting more attention recently. In this study, a continuous hydrological modelling approach on an hourly time scale, driven by a multi-site weather generator in combination with a -nearest neighbour resampling procedure, based on the method of fragments, is applied. The derived 100-year flood estimates in 16 catchments in Vorarlberg (Austria) are compared to (a) the flood frequency analysis based on observed discharges, and (b) a design storm approach. Besides the peak flows, the corresponding runoff volumes are analysed. The spatial dependence structure of the synthetically generated flood peaks is validated against observations. It can be demonstrated that the continuous modelling approach can achieve plausible results and shows a large variability in runoff volume across the flood events. KW - derived flood frequency KW - continuous modelling KW - temporal disaggregation KW - flood hazard KW - synthetic flood events Y1 - 2019 U6 - https://doi.org/10.1080/02626667.2019.1593419 SN - 0262-6667 SN - 2150-3435 VL - 64 IS - 5 SP - 539 EP - 554 PB - Routledge, Taylor & Francis Group CY - Abingdon ER - TY - JOUR A1 - Wendi, Dadiyorto A1 - Merz, Bruno A1 - Marwan, Norbert T1 - Assessing hydrograph similarity and rare runoff dynamics by cross recurrence plots JF - Water resources research N2 - This paper introduces a novel measure to assess similarity between event hydrographs. It is based on cross recurrence plots (CRP) and recurrence quantification analysis (RQA), which have recently gained attention in a range of disciplines when dealing with complex systems. The method attempts to quantify the event runoff dynamics and is based on the time delay embedded phase space representation of discharge hydrographs. A phase space trajectory is reconstructed from the event hydrograph, and pairs of hydrographs are compared to each other based on the distance of their phase space trajectories. Time delay embedding allows considering the multidimensional relationships between different points in time within the event. Hence, the temporal succession of discharge values is taken into account, such as the impact of the initial conditions on the runoff event. We provide an introduction to cross recurrence plots and discuss their parameterization. An application example based on flood time series demonstrates how the method can be used to measure the similarity or dissimilarity of events, and how it can be used to detect events with rare runoff dynamics. It is argued that this methods provides a more comprehensive approach to quantify hydrograph similarity compared to conventional hydrological signatures. KW - runoff dynamics KW - cross recurrence plot in hydrology KW - rare flood dynamics KW - hydrograph similarity KW - time delay embedding for runoff series Y1 - 2019 U6 - https://doi.org/10.1029/2018WR024111 SN - 0043-1397 SN - 1944-7973 VL - 55 IS - 6 SP - 4704 EP - 4726 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Tarasova, Larisa A1 - Merz, Ralf A1 - Kiss, Andrea A1 - Basso, Stefano A1 - Blöchl, Günter A1 - Merz, Bruno A1 - Viglione, Alberto A1 - Plötner, Stefan A1 - Guse, Björn A1 - Schumann, Andreas A1 - Fischer, Svenja A1 - Ahrens, Bodo A1 - Anwar, Faizan A1 - Bárdossy, András A1 - Bühler, Philipp A1 - Haberlandt, Uwe A1 - Kreibich, Heidi A1 - Krug, Amelie A1 - Lun, David A1 - Müller-Thomy, Hannes A1 - Pidoto, Ross A1 - Primo, Cristina A1 - Seidel, Jochen A1 - Vorogushyn, Sergiy A1 - Wietzke, Luzie T1 - Causative classification of river flood events JF - Wiley Interdisciplinary Reviews : Water N2 - A wide variety of processes controls the time of occurrence, duration, extent, and severity of river floods. Classifying flood events by their causative processes may assist in enhancing the accuracy of local and regional flood frequency estimates and support the detection and interpretation of any changes in flood occurrence and magnitudes. This paper provides a critical review of existing causative classifications of instrumental and preinstrumental series of flood events, discusses their validity and applications, and identifies opportunities for moving toward more comprehensive approaches. So far no unified definition of causative mechanisms of flood events exists. Existing frameworks for classification of instrumental and preinstrumental series of flood events adopt different perspectives: hydroclimatic (large-scale circulation patterns and atmospheric state at the time of the event), hydrological (catchment scale precipitation patterns and antecedent catchment state), and hydrograph-based (indirectly considering generating mechanisms through their effects on hydrograph characteristics). All of these approaches intend to capture the flood generating mechanisms and are useful for characterizing the flood processes at various spatial and temporal scales. However, uncertainty analyses with respect to indicators, classification methods, and data to assess the robustness of the classification are rarely performed which limits the transferability across different geographic regions. It is argued that more rigorous testing is needed. There are opportunities for extending classification methods to include indicators of space-time dynamics of rainfall, antecedent wetness, and routing effects, which will make the classification schemes even more useful for understanding and estimating floods. This article is categorized under: Science of Water > Water Extremes Science of Water > Hydrological Processes Science of Water > Methods KW - flood genesis KW - flood mechanisms KW - flood typology KW - historical floods KW - hydroclimatology of floods Y1 - 2019 U6 - https://doi.org/10.1002/wat2.1353 SN - 2049-1948 VL - 6 IS - 4 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Nguyen Le Duy, A1 - Nguyen Viet Du, A1 - Heidbüchel, Ingo A1 - Meyer, Hanno A1 - Weiler, Markus A1 - Merz, Bruno A1 - Apel, Heiko T1 - Identification of groundwater mean transit times of precipitation and riverbank infiltration by two-component lumped parameter models JF - Hydrological processes N2 - Groundwater transit time is an essential hydrologic metric for groundwater resources management. However, especially in tropical environments, studies on the transit time distribution (TTD) of groundwater infiltration and its corresponding mean transit time (mTT) have been extremely limited due to data sparsity. In this study, we primarily use stable isotopes to examine the TTDs and their mTTs of both vertical and horizontal infiltration at a riverbank infiltration area in the Vietnamese Mekong Delta (VMD), representative of the tropical climate in Asian monsoon regions. Precipitation, river water, groundwater, and local ponding surface water were sampled for 3 to 9 years and analysed for stable isotopes (delta O-18 and delta H-2), providing a unique data set of stable isotope records for a tropical region. We quantified the contribution that the two sources contributed to the local shallow groundwater by a novel concept of two-component lumped parameter models (LPMs) that are solved using delta O-18 records. The study illustrates that two-component LPMs, in conjunction with hydrological and isotopic measurements, are able to identify subsurface flow conditions and water mixing at riverbank infiltration systems. However, the predictive skill and the reliability of the models decrease for locations farther from the river, where recharge by precipitation dominates, and a low-permeable aquitard layer above the highly permeable aquifer is present. This specific setting impairs the identifiability of model parameters. For river infiltration, short mTTs (<40 weeks) were determined for sites closer to the river (<200 m), whereas for the precipitation infiltration, the mTTs were longer (>80 weeks) and independent of the distance to the river. The results not only enhance the understanding of the groundwater recharge dynamics in the VMD but also suggest that the highly complex mechanisms of surface-groundwater interaction can be conceptualized by exploiting two-component LPMs in general. The model concept could thus be a powerful tool for better understanding both the hydrological functioning of mixing processes and the movement of different water components in riverbank infiltration systems. KW - bank infiltration KW - groundwater KW - lumped parameter model KW - mean transit time KW - Mekong Delta KW - stable isotopes Y1 - 2019 U6 - https://doi.org/10.1002/hyp.13549 SN - 0885-6087 SN - 1099-1085 VL - 33 IS - 24 SP - 3098 EP - 3118 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Kurths, Jürgen A1 - Agarwal, Ankit A1 - Shukla, Roopam A1 - Marwan, Norbert A1 - Maheswaran, Rathinasamy A1 - Caesar, Levke A1 - Krishnan, Raghavan A1 - Merz, Bruno T1 - Unravelling the spatial diversity of Indian precipitation teleconnections via a non-linear multi-scale approach JF - Nonlinear processes in geophysics N2 - A better understanding of precipitation dynamics in the Indian subcontinent is required since India's society depends heavily on reliable monsoon forecasts. We introduce a non-linear, multiscale approach, based on wavelets and event synchronization, for unravelling teleconnection influences on precipitation. We consider those climate patterns with the highest relevance for Indian precipitation. Our results suggest significant influences which are not well captured by only the wavelet coherence analysis, the state-of-the-art method in understanding linkages at multiple timescales. We find substantial variation across India and across timescales. In particular, El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) mainly influence precipitation in the south-east at interannual and decadal scales, respectively, whereas the North Atlantic Oscillation (NAO) has a strong connection to precipitation, particularly in the northern regions. The effect of the Pacific Decadal Oscillation (PDO) stretches across the whole country, whereas the Atlantic Multidecadal Oscillation (AMO) influences precipitation particularly in the central arid and semi-arid regions. The proposed method provides a powerful approach for capturing the dynamics of precipitation and, hence, helps improve precipitation forecasting. Y1 - 2019 U6 - https://doi.org/10.5194/npg-26-251-2019 SN - 1023-5809 SN - 1607-7946 VL - 26 IS - 3 SP - 251 EP - 266 PB - Copernicus CY - Göttingen ER -