Eric Sauquet

Regional methods for trend detection: Assessing field significance and regional consistency

This paper describes regional methods for assessing field significance and regional consistency for trend detection in hydrological extremes. Four procedures for assessing field significance are compared on the basis of Monte Carlo simulations. Then three regional tests, based on a regional variable, on the regional average Mann-Kendall test, and a new semiparametric approach, are tested. The latter was found to be the most adequate to detect consistent changes within homogeneous hydro-climatic regions. Finally, these procedures are applied to France, using daily discharge data arising from 195 gauging stations. No generalized change was found at the national scale on the basis of the field significance assessment of at-site results. Hydro-climatic regions were then defined, and the semiparametric procedure applied. Most of the regions showed no consistent change, but three exceptions were found: in the northeast flood peaks were found to increase, in the Pyrenees high and low flows showed decreasing trends, and in the Alps, earlier snowmelt-related floods were detected, along with less severe drought and increasing runoff due to glacier melting. The trend affecting floods in the northeast was compared to changes in rainfall, using rainfall-runoff simulation. The results showed flood trends consistent with the observed rainfall.

A regional Bayesian POT model for flood frequency analysis

Flood frequency analysis is usually based on the fitting of an extreme value distribution to the local streamflow series. However, when the local data series is short, frequency analysis results become unreliable. Regional frequency analysis is a convenient way to reduce the estimation uncertainty. In this work, we propose a regional Bayesian model for short record length sites. This model is less restrictive than the index flood model while preserving the formalism of “homogeneous regions”. The performance of the proposed model is assessed on a set of gauging stations in France. The accuracy of quantile estimates as a function of the degree of homogeneity of the pooling group is also analysed. The results indicate that the regional Bayesian model outperforms the index flood model and local estimators. Furthermore, it seems that working with relatively large and homogeneous regions may lead to more accurate results than working with smaller and highly homogeneous regions.

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.

Extrapolation of rating curves by hydraulic modelling, with application to flood frequency analysis

Abstract This paper illustrates the importance of taking into account the potential errors in discharge estimation in the assessment of extreme floods. First, a summary of the main difficulties encountered in extrapolating rating curves for flood discharge is provided. Then a sensitivity analysis is carried out using a hydraulic modelling approach, applied to eight Mediterranean catchments, and yielding an envelope curve for the stage–discharge relationship, Q(H). To assess the influence of errors in the flood discharge on the uncertainty in estimating extreme floods, a Bayesian framework including a multiplicative error on the rating curve was applied. Its application on two catchments for which historical data are available for the period (1741–2004) shows that ignoring the rating curve errors may lead to an unduly optimistic reduction in the final uncertainty in estimation of flood discharge quantiles. Moreover, the quantile values are also affected by taking into account the rating curve errors. Citation Lang, M., Pobanz, K., Renard, B., Renouf, E. & Sauquet, E. (2010) Extrapolation of rating curves by hydraulic modelling, with application to flood frequency analysis. Hydrol. Sci. J. 55(6), 883–898.

Modeling all exceedances above a threshold using an extremal dependence structure: Inferences on several flood characteristics

Flood quantile estimation is of great importance for several types of engineering studies and policy decisions. However, practitioners must often deal with the limited availability of data and with short-length observation series. Thus, the information must be used optimally. During the last decades, to make better use of available data, inferential methodology has evolved from annual maxima modeling to peaks over a threshold. To mitigate the lack of data, peaks over a threshold are sometimes combined with additional information, mostly regional or historical information. However, the most important information for the practitioner remains the data available at the target site. In this study, a model that allows inference on the whole time series is introduced. In particular, the proposed model takes into account the dependence between successive extreme observations using an appropriate extremal dependence structure. Results show that this model leads to more accurate flood peak quantile estimates than conventional estimators. In addition, as the time dependence is taken into account, inferences on other flood characteristics can be performed. An illustration is given with flood duration data. Our analysis shows that the accuracy of the proposed models to estimate flood duration is related to specific catchment characteristics. Some suggestions to increase the flood duration predictions are presented.

Low flow response surfaces for drought decision support: a case study from the UK

Droughts are complex natural hazards, and planning future management is complicated by the difficulty of projecting future drought and low flow conditions. This paper demonstrates the use of a response surface approach to explore the hydrological behavior of catchments under a range of possible future conditions. Choosing appropriate hydrological metrics ensures that the response surfaces are relevant to decision-making. Examples from two contrasting English catchments show how low flows in different catchments respond to changes in rainfall and temperature. In an upland western catchment, the Mint, low flows respond most to rainfall and temperature changes in summer, but in the groundwater dominated catchment of the Thet, changes in spring rainfall have the biggest impact on summer flows. Response surfaces are useful for understanding long-term changes, such as those projected in climate projections, but they may also prove useful in drought event management, where possible future conditions can be plotted onto the surface to understand the range of conditions the manager faces. Developing effective response surfaces requires considerable involvement and learning from catchment decision-makers at an early stage, and this should be considered in any planned application.

Ensemble reconstruction of spatio-temporal extreme low-flow events in France since 1871

The length of streamflow observations is generally limited to the last 50 years even in data-rich countries like France. It therefore offers too small a sample of extreme low-flow events to properly explore the long-term evolution of their characteristics and associated impacts. To overcome this limit, this work first presents a daily 140year ensemble reconstructed streamflow dataset for a reference network of near-natural catchments in France. This dataset, called SCOPE Hydro (Spatially COherent Probabilistic Extended Hydrological dataset), is based on (1) a probabilistic precipitation, temperature, and reference evapotranspiration downscaling of the Twentieth Century Reanalysis over France, called SCOPE Climate, and (2) continuous hydrological modelling using SCOPE Climate as forcings over the whole period. This work then introduces tools for defining spatio-temporal extreme low-flow events. Extreme low-flow events are first locally defined through the sequent peak algorithm using a novel combination of a fixed threshold and a daily variable threshold. A dedicated spatial matching procedure is then established to identify spatiotemporal events across France. This procedure is furthermore adapted to the SCOPE Hydro 25-member ensemble to characterize in a probabilistic way unrecorded historical events at the national scale. Extreme low-flow events are described and compared in a spatially and temporally homogeneous way over 140 years on a large set of catchments. Results highlight well-known recent events like 1976 or 1989– 1990, but also older and relatively forgotten ones like the 1878 and 1893 events. These results contribute to improving our knowledge of historical events and provide a selection of benchmark events for climate change adaptation purposes. Moreover, this study allows for further detailed analyses of the effect of climate variability and anthropogenic climate change on low-flow hydrology at the scale of France.

Flow intermittence and ecosystem services in rivers of the Anthropocene

Intermittent rivers and ephemeral streams (IRES) are watercourses that cease flow at some point in time and space. Arguably Earths most widespread type of flowing water, IRES are expanding where Anthropocenic climates grow drier and human demands for water escalate.However, IRES have attracted far less research than perennial rivers and are undervalued by society, jeopardizing their restoration or protection. Provision of ecosystem services by IRES is especially poorly understood, hindering their integration into management plans in most countries.We conceptualize how flow intermittence governs ecosystem service provision and transfers at local and river-basin scales during flowing, non-flowing and dry phases. Even when dry or not flowing, IRES perform multiple ecosystem services that complement those of nearby perennial rivers.Synthesis and applications. Conceptualizing how flow intermittence in rivers and streams governs ecosystem services has applied a socio-ecological perspective for validating the ecosystem services of intermittent rivers and ephemeral streams. This can be applied at all flow phases and in assessing impacts of altered flow intermittence on rivers and their ecosystem services in the Anthropocene.

Flow regimes in Intermittent Rivers and Ephemeral Streams

The defining feature of all intermittent rivers and ephemeral streams (hereafter, IRES) is that they cease flow at some time. Many IRES dry to isolated pools but flow often continues through the hyporheic sediments below the streambed. If dry conditions persist, hyporheic flows may also cease and the streambed dries completely. Consequently, the flow regimes (e.g., frequency, magnitude, duration, and timing of flow events) of IRES and the presence of water are typically more variable than in nearby equivalent-sized perennial rivers and streams. This highly variable flow regime, especially intermittence, has major implications for the physicochemistry, biota, ecological processes, and management of IRES. Flow regimes of IRES have been primarily characterized using data from gauging stations, supplemented by diverse methods such as wet-dry mapping, various forms of imagery, and modeling. Flow data are often summarized as hydrological metrics such as variance in frequency, duration, timing, and rate of onset of intermittence that have been used to classify flow regimes of many of the world’s rivers. Such classifications reveal that IRES are globally abundant and that intermittence is increasing across much of the world, largely owing to climatic drying and water abstraction.

Spatial Verification of Ensemble Precipitation: An Ensemble Version of SAL

AbstractSpatial verification methods able to handle high-resolution ensemble forecasts and analysis ensembles are increasingly required because of the increasing development of such ensembles. An e...