Comparison of catchment grouping methods for flow duration curve estimation at ungauged sites in France

The study aims at estimating flow duration curves (FDC) at ungauged sites in France and quantifying the associated uncertainties using a large dataset of 1080 FDCs. The interpolation procedure focuses here on 15 percentiles standardised by the mean annual flow, which is assumed to be known at each site. In particular, this paper discusses the impact of different catchment grouping procedures on the estimation of percentiles by regional regression models. <br><br> In a first step, five parsimonious FDC parametric models are tested to approximate FDCs at gauged sites. The results show that the model based on the expansion of Empirical Orthogonal Functions (EOF) outperforms the other tested models. In the EOF model, each FDC is interpreted as a linear combination of regional amplitude functions with spatially variable weighting factors corresponding to the parameters of the model. In this approach, only one amplitude function is required to obtain a satisfactory fit with most of the observed curves. Thus, the considered model requires only two parameters to be applicable at ungauged locations. <br><br> Secondly, homogeneous regions are derived according to hydrological response, on the one hand, and geological, climatic and topographic characteristics on the other hand. Hydrological similarity is assessed through two simple indicators: the concavity index (IC) representing the shape of the dimensionless FDC and the seasonality ratio (SR), which is the ratio of summer and winter median flows. These variables are used as homogeneity criteria in three different methods for grouping catchments: (i) according to an a priori classification of French Hydro-EcoRegions (HERs), (ii) by applying regression tree clustering and (iii) by using neighbourhoods obtained by canonical correlation analysis. <br><br> Finally, considering all the data, and subsequently for each group obtained through the tested grouping techniques, we derive regression models between physiographic and/or climatic variables and the two parameters of the EOF model. Results on percentile estimation in cross validation show that a significant benefit is obtained by defining homogeneous regions before developing regressions, particularly when grouping methods make use of hydrogeological information

Mapping mean and variance of runoff in a river basin

International audienceThe study presents an approach to depict the two first order moments of runoff as a function of area (and thus on a map). The focal point is the mapping of the statistical properties of runoff q=q(A,D) in space (area A) and time (time interval D). The problem is divided into two steps. Firstly the first order moment (the long term mean value) is analysed and mapped applying an interpolation procedure for river runoff. In a second step a simple random model for the river runoff process is proposed for the instantaneous point runoff normalised with respect to the long term mean. From this model theoretical expressions for the time-space variance-covariance of the inflow to the river network are developed, which then is used to predict how the second order moment vary along rivers from headwaters to the mouth. The observation data are handled in the frame of a hydrological information system HydroDem, which allows displaying the results either in the form of area dependence of moments along the river branches to the basin outlet or as a map of the variation of the moments across the basin space. The findings are demonstrated on the example of the Moselle drainage basin (French part)

Reconstruction d'ensemble des événements spatio-temporels d'étiage extrême en France depuis 1871

International audienceThe 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 140-year 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 spatio-temporal 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

Precipitation forecasting through an analog sorting technique: a comparative study

This study aims at comparing two quantitative precipitation forecasting techniques based on the meteorological analogy concept. Method A considers first a selection of analogous situations at synoptic scale. Second a subset of the most similar situations in terms of hygrometry is extracted. Method B extends method A by two innovative ways, which are restricting the search for analogues with temperature information instead of the common season criterion, and exploiting the information about vertical motion considering vertical velocity. Forecasts are evaluated in a perfect prognosis context and in operational conditions as well, by mean of verification measures (Continuous Ranked Probability Skill Score and scores computed from contingency tables). Results of the case study in France show that: (1) there is an increase in forecast skill when temperature and vertical velocity are included in the procedure, (2) it is possible to anticipate rainfall events up to one week ahead and (3) the introduction of new variables such as vertical velocity may be useless beyond few days ahead if the forecast of the weather model is not reliable

Mapping mean monthly runoff pattern using EOF analysis

International audienceRunoff generation in a forested catchment (0.18 km2) was simulated using a quasi-three-dimensional rainfall-runoff model. The model was formulated over a finite grid where water movement was assumed to be dominantly vertical in the unsaturated soil zone and horizontal in the saturated soil. The vertical soil moisture distribution at each grid cell was calculated using a conceptual approximation to the one-dimensional Richards equation. The approximation allowed the use of a simple soil surface boundary condition and an efficient solution to the water table elevation over the finite grid. The approximation was coupled with a two-dimensional ground water model to calculate lateral soil water movement between the grid cells and exfiltration over saturated areas, where runoff was produced by the saturation-excess mechanism. Runoff was an input to a channel network, which was modelled as a nonlinear reservoir. The proposed approximation for the vertical soil moisture distribution in unsaturated soil compared well to a numerical solution of the Richards equation during shallow water table conditions, but was less satisfactory during prolonged dry periods. The simulation of daily catchment outflow was successful with the exception of underprediction of extremely high peak flows. The calculated water table depth compared satisfactorily with the measurements. An overall comparison with the earlier results of tracer studies indicated that the modelled contribution of direct rainfall/snowmelt in streamflow was higher than the isotopically traced fraction of event-water in runoff. The seasonal variation in the modelled runoff-contributing areas was similar to that in the event-water-contributing areas from the tracer analysis

Quantifying the physical alterations of river reaches using a regional river morphology reference model. A step towards river restoration.

River engineeringRiver habitat management and restoratio

SCOPE Climate: a 142-year daily high-resolution ensemble meteorological reconstruction dataset over France

SCOPE Climate (Spatially COherent Probabilistic Extended Climate dataset) is a 25-member ensemble of 142-year daily high-resolution reconstructions of precipitation, temperature, and Penman–Monteith reference evapotranspiration over France, from 1 January 1871 to 29 December 2012. SCOPE Climate provides an ensemble of 25 spatially coherent gridded multivariate time series. It is derived from the statistical downscaling of the Twentieth Century Reanalysis (20CR) by the SCOPE method, which is based on the analogue approach. SCOPE Climate performs well in comparison to both dependent and independent data for precipitation and temperature. The ensemble aspect corresponds to the uncertainty related to the SCOPE method. SCOPE Climate is the first century-long gridded high-resolution homogeneous dataset available over France and thus has paved the way for improving knowledge on specific past meteorological events or for improving knowledge on climate variability, since the end of the 19th century. This dataset has also been designed as a forcing dataset for long-term hydrological applications and studies of the hydrological consequences of climate variability over France. SCOPE Climate is freely available for any non-commercial use and can be downloaded as NetCDF files from https://doi.org/10.5281/zenodo.1299760 for precipitation, https://doi.org/10.5281/zenodo.1299712 for temperature, and https://doi.org/10.5281/zenodo.1251843 for reference evapotranspiration.</p

Unraveling the Developmental and Genetic Mechanisms Underpinning Floral Architecture in Proteaceae

Proteaceae are a basal eudicot family with a highly conserved floral groundplan but which displays considerable variation in other aspects of floral and inflorescence morphology. Their morphological diversity and phylogenetic position make them good candidates for understanding the evolution of floral architecture, in particular the question of the homology of the undifferentiated perianth with the differentiated perianth of core eudicots, and the mechanisms underlying the repeated evolution of zygomorphy. In this paper, we combine a morphological approach to explore floral ontogenesis and a transcriptomic approach to access the genes involved in floral organ identity and development, focusing on Grevillea juniperina, a species from subfamily Grevilleoideae. We present developmental data for Grevillea juniperina and three additional species that differ in their floral symmetry using stereomicroscopy, SEM and High Resolution X-Ray Computed Tomography. We find that the adnation of stamens to tepals takes place at early developmental stages, and that the establishment of bilateral symmetry coincides with the asymmetrical growth of the single carpel. To set a framework for understanding the genetic basis of floral development in Proteaceae, we generated and annotated de novo a reference leaf/flower transcriptome from Grevillea juniperina. We found Grevillea homologs of all lineages of MADS-box genes involved in floral organ identity. Using Arabidopsis thaliana gene expression data as a reference, we found homologs of other genes involved in floral development in the transcriptome of G. juniperina. We also found at least 21 class I and class II TCP genes, a gene family involved in the regulation of growth processes, including floral symmetry. The expression patterns of a set of floral genes obtained from the transcriptome were characterized during floral development to assess their organ specificity and asymmetry of expression

Usefulness of the Reversible Jump Markov Chain Monte Carlo Model in Regional Flood Frequency Analysis

Regional flood frequency analysis is a convenient way to reduce estimation uncertainty when few data are available at the gauging site. In this work, a model that allows a non-null probability to a regional fixed shape parameter is presented. This methodology is integrated within a Bayesian framework and uses reversible jump techniques. The performance on stochastic data of this new estimator is compared to two other models: a conventional Bayesian analysis and the index flood approach. Results show that the proposed estimator is absolutely suited to regional estimation when only a few data are available at the target site. Moreover, unlike the index flood estimator, target site index flood error estimation seems to have less impact on Bayesian estimators. Some suggestions about configurations of the pooling groups are also presented to increase the performance of each estimator