Bruno Merz

An analysis of the effects of spatial variability of soil and soil moisture on runoff

Hydrological variables and processes usually exhibit a large spatial variability. Often this variability includes aspects of organization and randomness. Because any hydrological modeling has to deal with the question of spatial variability, methods that quantify the effects of spatial variability are valuable. Moreover, it is important to identify the situations where the spatial variability can be reduced (e.g., by using an “effective” value). For a small and well-instrumented catchment in a loess area in southwest Germany effects of spatial variability of the initial soil moisture and soil hydraulic properties on the runoff are investigated. The analysis is performed with a process-oriented rainfall runoff model. It is shown that organization in spatial patterns of soil moisture and soil properties may have a dominant influence on the catchment runoff. The simulations suggest that spatial variability can result in a complex, event dependent, behavior. It cannot be expected that a model with inputs based on mean parameters or mean initial conditions leads to mean outputs for heterogeneous fields. The analysis of different events shows the changing influence of spatial variability on the runoff with changing storm size. For very small and for large events spatial variability plays a negligible role. A large influence is found for medium-sized events.

Insurability and Mitigation of Flood Losses in Private Households in Germany

In Germany, flood insurance is provided by private insurers as a supplement to building or contents insurance. This article presents the results of a survey of insurance companies with regard to eligibility conditions for flood insurance changes after August 2002, when a severe flood caused 1.8 billion euro of insured losses in the Elbe and the Danube catchment areas, and the general role of insurance in flood risk management in Germany. Besides insurance coverage, governmental funding and public donations played an important role in loss compensation after the August 2002 flood. Therefore, this article also analyzes flood loss compensation, risk awareness, and mitigation in insured and uninsured private households. Insured households received loss compensation earlier. They also showed slightly better risk awareness and mitigation strategies. Appropriate incentives should be combined with flood insurance in order to strengthen future private flood loss mitigation. However, there is some evidence that the surveyed insurance companies do little to encourage precautionary measures. To overcome this problem, flood hazards and mitigation strategies should be better communicated to both insurance companies and property owners.

A global analysis of temporal and spatial variations in continental water storage

[1] While continental water storage plays a key role in the Earth’s water, energy, and biogeochemical cycles, its temporal and spatial variations are poorly known, in particular, for large areas. This study analyzes water storage simulated with the Watergap Global Hydrology Model. The model represents four major storage compartments: surface water, snow, soil, and groundwater. Water storage variations are analyzed for the period 1961–1995 with 0.5 resolution, for the major global climate zones, and for the 30 largest river basins worldwide. Seasonal variations are the dominant storage change signal with maximum values in the marginal tropics and in snow-dominated high-latitude areas.

Effects of spatial variability on the rainfall runoff process in a small loess catchment

Abstract Numerous field experiments have revealed that hydrological processes and parameters can show considerable spatial variability. When modelling the rainfall runoff process, the influence of this variability on the runoff should be assessed. For regionalization purposes, it is an important question if and how this variability is reflected in the behaviour on a larger scale. A quasi-three-dimensional, process-oriented model is used to understand the influence of spatial variability on the runoff behaviour. The study area, “Neuenburger Pfad”, is a small loess catchment in southwestern Germany. Because of low infiltration capacity of the loess soil, runoff is produced by infiltration excess overland flow. Three examples are presented which elaborate on the effects of different types of spatial variability. The first example shows that an agricultural road plays a crucial role in the runoff behaviour of the investigated catchment. The second example studies the role of the spatial distribution of soil parameters. It demonstrates the importance of structured variability in heterogeneous fields. Purely random fields result in hydrographs similar to the homogeneous case, whereas fields with structured variability yield very different runoff. The third example is concerned with the effects of different soil moisture interpolations, which serve as initial state for the runoff model. The examples presented show that spatial variability can have a dominant influence on the rainfall runoff behaviour. For sound modelling, a close inspection of the particular catchment characteristics is necessary. Structured variability should be included in hydrological models because of the larger influence compared to stochastic variability. To understand the extent and the significance of catchment variability, an interdiciplinary teamwork should be fruitful.

Development of FLEMOcs - a new model for the estimation of flood losses in the commercial sector

Abstract The estimation of flood damage is an important component for risk-oriented flood design, risk mapping, financial appraisals and comparative risk analyses. However, research on flood-loss modelling, especially in the commercial sector, has not gained much attention so far. Therefore, extensive data about flood losses were collected for affected companies via telephone surveys after the floods of 2002, 2005 and 2006 in Germany. Potential loss determining factors were analysed. The new Flood Loss Estimation MOdel for the commercial sector (FLEMOcs) was developed on the basis of 642 loss cases. Losses are estimated depending on water depth, sector and company size as well as precaution and contamination. The model can be applied to the micro-scale, i.e. to single production sites as well as to the meso-scale, i.e. land-use units, thus enabling its countrywide application. Citation Kreibich, H., Seifert, I., Merz, B. & Thieken, A. H. (2010) Development of FLEMOcs – a new model for the estimation of flood losses in the commercial sector. Hydrol. Sci. J. 55(8), 1302–1314.

Quantification of uncertainties in flood risk assessments

Abstract By a common definition, flood risk assessments are comprised of two parts: a hazard and vulnerability assessment. The hazard assessment investigates the extent and magnitude of usually large flood events, which are associated to a certain exceedance probability, whereas the vulnerability part assesses the impact of the flooding on specified targets, e.g., building, people or infrastructure. Being inherently speculative flood risk assessments should always be accompanied by an uncertainty assessment in order to assist consequent decision properly. In this paper a dynamic‐probabilistic method is proposed, which enables a cumulated flood risk assessment of a complete river reach considering dike failures at all dike locations. The model uses simple but computational efficient modules to simulate the complete process chain of flooding. These modules are embedded into a Monte Carlo framework thus enabling a risk assessment which is physically based thus mapping the real flooding process, and which is also probabilistic and not based on scenarios. The model also provides uncertainty estimates by quantifying various epistemic uncertainty sources of the hazard as well as the vulnerability part in a second layer of Monte Carlo simulations. These uncertainty estimates are associated to defined return intervals of the model outputs, i.e., the derived flood frequencies at the end of the reach and the risk curves for the complete reach, thus providing valuable information for the interpretation of the results. By separating single uncertainty sources a comparison of the contribution of different uncertainty sources to the overall predictive uncertainty in terms of derived flood frequencies and monetary risks could be performed. This revealed that the major uncertainties are extreme value statistics, resp. the length of the data series used and the discharge‐stage relation used for the transformation of discharge into water levels in the river.

Changing climate shifts timing of European floods

Flooding along the river Will a warming climate affect river floods? The prevailing sentiment is yes, but a consistent signal in flood magnitudes has not been found. Blöschl et al. analyzed the timing of river floods in Europe over the past 50 years and found clear patterns of changes in flood timing that can be ascribed to climate effects (see the Perspective by Slater and Wilby). These variations include earlier spring snowmelt floods in northeastern Europe, later winter floods around the North Sea and parts of the Mediterranean coast owing to delayed winter storms, and earlier winter floods in western Europe caused by earlier soil moisture maxima. Science, this issue p. 588 see also p. 552 Climate change is affecting the timing of river flooding across Europe. A warming climate is expected to have an impact on the magnitude and timing of river floods; however, no consistent large-scale climate change signal in observed flood magnitudes has been identified so far. We analyzed the timing of river floods in Europe over the past five decades, using a pan-European database from 4262 observational hydrometric stations, and found clear patterns of change in flood timing. Warmer temperatures have led to earlier spring snowmelt floods throughout northeastern Europe; delayed winter storms associated with polar warming have led to later winter floods around the North Sea and some sectors of the Mediterranean coast; and earlier soil moisture maxima have led to earlier winter floods in western Europe. Our results highlight the existence of a clear climate signal in flood observations at the continental scale.

How useful are complex flood damage models

We investigate the usefulness of complex flood damage models for predicting relative damage to residential buildings in a spatial and temporal transfer context. We apply eight different flood damage models to predict relative building damage for five historic flood events in two different regions of Germany. Model complexity is measured in terms of the number of explanatory variables which varies from 1 variable up to 10 variables which are singled out from 28 candidate variables. Model validation is based on empirical damage data, whereas observation uncertainty is taken into consideration. The comparison of model predictive performance shows that additional explanatory variables besides the water depth improve the predictive capability in a spatial and temporal transfer context, i.e., when the models are transferred to different regions and different flood events. Concerning the trade-off between predictive capability and reliability the model structure seem more important than the number of explanatory variables. Among the models considered, the reliability of Bayesian network-based predictions in space-time transfer is larger than for the remaining models, and the uncertainties associated with damage predictions are reflected more completely.

Charting unknown waters—On the role of surprise in flood risk assessment and management

Unexpected incidents, failures, and disasters are abundant in the history of flooding events. In this paper, we introduce the metaphors of terra incognita and terra maligna to illustrate unknown and wicked flood situations, respectively. We argue that surprise is a neglected element in flood risk assessment and management. Two sources of surprise are identified: (1) the complexity of flood risk systems, represented by nonlinearities, interdependencies, and nonstationarities and (2) cognitive biases in human perception and decision making. Flood risk assessment and management are particularly prone to cognitive biases due to the rarity and uniqueness of extremes, and the nature of human risk perception. We reflect on possible approaches to better understanding and reducing the potential for surprise and its adverse consequences which may be supported by conceptually charting maps that separate terra incognita from terra cognita, and terra maligna from terra benigna. We conclude that flood risk assessment and management should account for the potential for surprise and devastating consequences which will require a shift in thinking.

Attribution of streamflow trends in snow and glacier melt-dominated catchments of the Tarim River, Central Asia

Observed streamflow of headwater catchments of the Tarim River (Central Asia) increased by about 30% over the period 1957–2004. This study aims at assessing to which extent these streamflow trends can be attributed to changes in air temperature or precipitation. The analysis includes a data-based approach using multiple linear regression and a simulation-based approach using a hydrological model. The hydrological model considers changes in both glacier area and surface elevation. It was calibrated using a multiobjective optimization algorithm with calibration criteria based on glacier mass balance and daily and interannual variations of discharge. The individual contributions to the overall streamflow trends from changes in glacier geometry, temperature, and precipitation were assessed using simulation experiments with a constant glacier geometry and with detrended temperature and precipitation time series. The results showed that the observed changes in streamflow were consistent with the changes in temperature and precipitation. In the Sari-Djaz catchment, increasing temperatures and related increase of glacier melt were identified as the dominant driver, while in the Kakshaal catchment, both increasing temperatures and increasing precipitation played a major role. Comparing the two approaches, an advantage of the simulation-based approach is the fact that it is based on process-based relationships implemented in the hydrological model instead of statistical links in the regression model. However, data-based approaches are less affected by model parameter and structural uncertainties and typically fast to apply. A complementary application of both approaches is recommended.