Ralf Merz

Time stability of catchment model parameters: Implications for climate impact analyses

[1] Climate impact analyses are usually based on driving hydrological models by future climate scenarios, assuming that the model parameters calibrated to past runoff are representative of the future. In this paper we calibrate the parameters of a conceptual rainfall-runoff model to six consecutive 5 year periods between 1976 and 2006 for 273 catchments in Austria and analyze the temporal change of the calibrated parameters. The calibrated parameters representing snow and soil moisture processes show significant trends. For example, the parameter controlling runoff generation doubled, on average, in the 3 decades. Comparisons of different subregions, comparisons with independent data sets, and analyses of the spatial variability of the model parameters indicate that these trends represent hydrological changes rather than calibration artifacts. The trends can be related to changes in the climatic conditions of the catchments such as higher evapotranspiration and drier catchment conditions in the more recent years. The simulations suggest that the impact on simulated runoff of assuming time invariant parameters can be very significant. For example, if using the parameters calibrated to 1976 – 1981 for simulating runoff for the period 2001 – 2006, the biases of median flows are, on average, 15% and the biases of high flows are about 35%. The errors increase as the time lag between the simulation and calibration periods increases. The implications for hydrologic prediction in general and climate impact analyses in particular are discussed.

A regional analysis of event runoff coefficients with respect to climate and catchment characteristics in Austria

[1] In this paper we analyze the controls on the spatiotemporal variability of event runoff coefficients. A total of about 64,000 events in 459 Austrian catchments ranging from 5 to 10000 km 2 are analyzed. Event runoff coefficients vary in space, depending on the long-term controls such as climate and catchment formation. Event runoff coefficients also vary in time, depending on event characteristics such as antecedent soil moisture and event rainfall depth. Both types of controls are analyzed separately in the paper. The spatial variability is analyzed in terms of a correlation analysis of the statistical moments of the runoff coefficients and catchment attributes. Mean runoff coefficients are most strongly correlated to indicators representing climate such as mean annual precipitation and the long-term ratio of actual evaporation to precipitation through affecting long-term soil moisture. Land use, soil types, and geology do not seem to exert a major control on runoff coefficients of the catchments under study. The temporal variability is analyzed by comparing the deviation of the event runoff coefficients from their mean depending on event characteristics. The analysis indicates that antecedent soil moisture conditions control runoff coefficients to a higher degree than does event rainfall. The analysis also indicates that soil moisture derived from soil moisture accounting schemes has more predictive power for the temporal variability of runoff coefficients than antecedent rainfall.

Linking flood frequency to long‐term water balance: Incorporating effects of seasonality

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.

Regional calibration of catchment models: Potential for ungauged catchments

[1] We present a novel iterative regional calibration (IRC) method in which the model parameters of a number of catchments are calibrated simultaneously. The method exploits the spatial correlations of the parameters to condition their a priori distribution for each catchment. We use a sample of 320 catchments in Austria over a period of 22 years to test the method. The results indicate that the IRC method allows us to reliably calibrate the conceptual hydrologic model used here. The novel method reduces the uncertainty of most parameters as compared to local calibration. This is demonstrated by more consistent model parameters in two independent calibration periods and by an analysis of their spatial variability. Jackknife cross validation indicates that the IRC method tends to improve runoff simulation performance for ungauged catchments as compared to traditional regionalization, although the gain is small in absolute terms.

Managing the effects of multiple stressors on aquatic ecosystems under water scarcity. The GLOBAQUA project

Water scarcity is a serious environmental problem in many European regions, and will likely increase in the near future as a consequence of increased abstraction and climate change. Water scarcity exacerbates the effects of multiple stressors, and thus results in decreased water quality. It impacts river ecosystems, threatens the services they provide, and it will force managers and policy-makers to change their current practices. The EU-FP7 project GLOBAQUA aims at identifying the prevalence, interaction and linkages between stressors, and to assess their effects on the chemical and ecological status of freshwater ecosystems in order to improve water management practice and policies. GLOBAQUA assembles a multidisciplinary team of 21 European plus 2 non-European scientific institutions, as well as water authorities and river basin managers. The project includes experts in hydrology, chemistry, biology, geomorphology, modelling, socio-economics, governance science, knowledge brokerage, and policy advocacy. GLOBAQUA studies six river basins (Ebro, Adige, Sava, Evrotas, Anglian and Souss Massa) affected by water scarcity, and aims to answer the following questions: how does water scarcity interact with other existing stressors in the study river basins? How will these interactions change according to the different scenarios of future global change? Which will be the foreseeable consequences for river ecosystems? How will these in turn affect the services the ecosystems provide? How should management and policies be adapted to minimise the ecological, economic and societal consequences? These questions will be approached by combining data-mining, field- and laboratory-based research, and modelling. Here, we outline the general structure of the project and the activities to be conducted within the fourteen work-packages of GLOBAQUA.

Flood frequency hydrology: 3. A Bayesian analysis

extraordinary 2002 flood event are compared for the 622 km 2 Kamp river in northern Austria. Although this outlier significantly affects the flood frequency estimates if only local flood data are used (60% difference for the 100 year flood), the effect is much reduced if all additional information is used (only 3% difference). The Bayesian analysis also shows that the estimated uncertainty is significantly reduced when more information is used (for the 100 year return period, the 90% credible intervals range reduces from 140% to 31% of the corresponding flood peak estimate). Further analyses show that the sensitivity of the flood estimates to the assumptions made on one piece of information is small when all pieces of information are considered together. While expanding information beyond the systematic flood record is sometimes considered of little value in engineering hydrology because subjective assumptions are involved, the results of this study suggest that the extra information (temporal, spatial, and causal) may outweigh the uncertainty caused by these assumptions.

Scale effects in conceptual hydrological modeling

[1] We simulate the water balance dynamics of 269 catchments in Austria ranging in size from 10 to 130,000 km 2 using a semidistributed conceptual model with 11 parameters based on a daily time step. The simulation results suggest that the Nash-Sutcliffe model efficiencies increase over the scale range of 10 and 10,000 km 2 . The scatter of the model performances decreases with catchment scale, particularly the volume errors. This implies that the model simulates the long-term water balance more reliably as one goes up in scale. Most calibrated parameters do not change with catchment scale, but there is a trend with catchment area of the upper and lower envelope curves of some parameters. We also examine time scale effects. Calibration efficiencies decrease and verification efficiencies increase with the number of years available for calibration. The change in efficiencies is largest between 1 and 5 years used for calibration. This suggests that a calibration period of 5 years captures most of the temporal hydrological variability, so this would be the minimum for achieving a reasonable predictive model performance. The correlation of model parameters between different calibration periods, as a measure of the degree to which parameters can be identified, increases with increasing length of the calibration period. For some parameters, the correlation increases beyond 5 years of calibration. This suggest that although runoff may be simulated well using 5 years of calibration, some parameters may not be well constrained and hence internal state variables and fluxes may still be associated with larger uncertainties than with a larger calibration period.

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.

Hydrology under change: an evaluation protocol to investigate how hydrological models deal with changing catchments

Abstract Testing hydrological models under changing conditions is essential to evaluate their ability to cope with changing catchments and their suitability for impact studies. With this perspective in mind, a workshop dedicated to this issue was held at the 2013 General Assembly of the International Association of Hydrological Sciences (IAHS) in Göteborg, Sweden, in July 2013, during which the results of a common testing experiment were presented. Prior to the workshop, the participants had been invited to test their own models on a common set of basins showing varying conditions specifically set up for the workshop. All these basins experienced changes, either in physical characteristics (e.g. changes in land cover) or climate conditions (e.g. gradual temperature increase). This article presents the motivations and organization of this experiment—that is—the testing (calibration and evaluation) protocol and the common framework of statistical procedures and graphical tools used to assess the model performances. The basins datasets are also briefly introduced (a detailed description is provided in the associated Supplementary material).

Comparative analysis of the seasonality of hydrological characteristics in Slovakia and Austria.

Abstract The main objective of this study is to compare the seasonality of selected precipitation and runoff characteristics in Austria and Slovakia. Monthly seasonality indices are analysed to interpret the long-term climatic behaviour, while the seasonality of extremes is analysed to understand flood occurrence. The analysis is based on mean monthly precipitation data at 555 (Austria) and 202 (Slovakia) stations, annual maximum daily precipitation at 520 (Austria) and 56 (Slovakia) stations, and mean monthly runoff and annual maximum floods at 258 (Austria) and 85 (Slovakia) gauging stations. The results suggest that the seasonality of the selected hydrological characteristics is an important indicator of flood processes, but varies considerably in space. The seasonality of extreme flood events and, hence flood processes, tends to change with the flood magnitude. This change is more pronounced in the lowland and hilly regions than it is in the mountains. Both in Austria and Slovakia, decades of flood seasonality exist.