Votre recherche

AbstractThe Canadian Land Data Assimilation System (CaLDAS) has been developed at the Meteorological Research Division of Environment Canada (EC) to better represent the land surface initial states in environmental prediction and assimilation systems. CaLDAS is built around an external land surface modeling system and uses the ensemble Kalman filter (EnKF) methodology. A unique feature of CaLDAS is the use of improved precipitation forcing through the assimilation of precipitation observations. An ensemble of precipitation analyses is generated by combining numerical weather prediction (NWP) model precipitation forecasts with precipitation observations. Spatial phasing errors to the NWP first-guess precipitation forecasts are more effective than perturbations to the precipitation observations in decreasing (increasing) the exceedance ratio (uncertainty ratio) scores and generating flatter, more reliable ranked histograms. CaLDAS has been configured to assimilate L-band microwave brightness temperature TB ...

Abstract The performance of adaptation measures depends on their robustness against various possible futures, with varying climate change impacts. Such impacts are driven by both climatic as well as non-climatic drivers. Risk dynamics are then important, as the avoided risk will determine the benefits of adaptation actions. It is argued that the integration of information on changing exposure and vulnerability is needed to make projections of future climate risk more realistic. In addition, many impact and vulnerability studies have used a top-down rather a technical approach. Whether adaptation action is feasible is determined by technical and physical possibilities on the ground, as well as local capacities, governance and preference. These determine the hard and soft limits of adaptation. Therefore, it is argued that the risk metrics outputs alone are not sufficient to predict adaptation outcomes, or predict where adaptation is feasible or not; they must be placed in the local context. Several of the current climate risk products would fall short of their promise to inform adaptation decision-making on the ground. Some steps are proposed to improve adaptation modelling in order to better incorporate these aspects.

Over the last decades, different methods have been used by hydrologists to extend observed hydro-climatic time series, based on other data sources, such as tree rings or sedimentological datasets. For example, tree ring multi-proxies have been studied for the Caniapiscau Reservoir in northern Quebec (Canada), leading to the reconstruction of flow time series for the last 150 years. In this paper, we applied a new hydro-climatic reconstruction method on the Caniapiscau Reservoir and compare the obtained streamflow time series against time series derived from dendrohydrology by other authors on the same catchment and study the natural streamflow variability over the 1881–2011 period in that region. This new reconstruction is based not on natural proxies but on a historical reanalysis of global geopotential height fields, and aims firstly to produce daily climatic time series, which are then used as inputs to a rainfall–runoff model in order to obtain daily streamflow time series. The performances of the hydro-climatic reconstruction were quantified over the observed period, and showed good performances, in terms of both monthly regimes and interannual variability. The streamflow reconstructions were then compared to two different reconstructions performed on the same catchment by using tree ring data series, one being focused on mean annual flows and the other on spring floods. In terms of mean annual flows, the interannual variability in the reconstructed flows was similar (except for the 1930–1940 decade), with noteworthy changes seen in wetter and drier years. For spring floods, the reconstructed interannual variabilities were quite similar for the 1955–2011 period, but strongly different between 1880 and 1940. The results emphasize the need to apply different reconstruction methods on the same catchments. Indeed, comparisons such as those above highlight potential differences between available reconstructions and, finally, allow a retrospective analysis of the proposed reconstructions of past hydro-climatological variabilities.

Abstract River confluences are characterized by a complex mixing zone with three‐dimensional (3D) turbulent structures which have been described as both streamwise‐oriented structures and Kelvin–Helmholtz (KH) vertical‐oriented structures. The latter are visible where there is a turbidity difference between the two tributaries, whereas the former are usually derived from mean velocity measurements or numerical simulations. Few field studies recorded turbulent velocity fluctuations at high frequency to investigate these structures, particularly at medium‐sized confluences where logistical constraints make it difficult to use devices such as acoustic doppler velocimeter (ADV). This study uses the ice cover present at the confluence of the Mitis and Neigette Rivers in Quebec (Canada) to obtain long‐duration, fixed measurements along the mixing zone. The confluence is also characterized by a marked turbidity difference which allows to investigate the mixing zone dynamics from drone imagery during ice‐free conditions. The aim of the study is to characterize and compare the flow structure in the mixing zone at a medium‐sized (~40 m) river confluence with and without an ice cover. Detailed 3D turbulent velocity measurements were taken under the ice along the mixing plane with an ADV through eight holes at around 20 positions on the vertical. For ice‐free conditions, drone imagery results indicate that large (KH) coherent structures are present, occupying up to 50% of the width of the parent channel. During winter, the ice cover affects velocity profiles by moving the highest velocities towards the centre of the profiles. Large turbulent structures are visible in both the streamwise and lateral velocity components. The strong correlation between these velocity components indicates that KH vortices are the dominating coherent structures in the mixing zone. A spatio‐temporal conceptual model is presented to illustrate the main differences on the 3D flow structure at the river confluence with and without the ice cover. © 2019 John Wiley & Sons, Ltd.

Several top‐down and bottom‐up forces have been put forward to explain variable infestation rates of zooplankton by epibionts. Among top‐down forces, fish predation affects epibiont prevalence on zooplanktonic organisms, either by eliminating more conspicuous, heavily burdened individuals, or by reducing population size of zooplankton hosts, with consequences for substrate availability for epibionts. However, detailed experimental‐based information on the effects of top‐down forces is still lacking. Among bottom‐up forces, light can potentially control populations of photosynthetic epibionts. Therefore, both changes in light penetration in the water column and the vertical position of hosts in the water column could affect the photic conditions in which epibionts live and could thus control their population growth. We tested experimentally the hypothesis that both light limitation and fish predation affect epibiont burden on zooplankton. Moreover, we also tested the hypothesis that zooplanktivorous fish affect the prevalence and burden of the epibiotic alga Colacium sp. (Euglenida) on zooplankton not only by direct predation, but also by affecting the vertical distribution of zooplankton. We analyzed Colacium burden on two zooplankton genera that responded differently to the presence of zooplanktivorous fish by altering their daytime vertical distributions, thus exposing photosynthetic epibionts to different light conditions. Colacium burden on the two zooplankton genera was also compared between enclosures with different degrees of light limitation. Our results suggest that (1) ambient light limitation has the potential to reduce the burden of photosynthetic epibionts on zooplankton in natural conditions, and (2) zooplankton behavior (e.g., daytime refuge use to escape fish predation) can reduce the burden by exposing photosynthetic epibionts to suboptimal light conditions.

1.Refuges that reduce fish‐induced mortality of zooplankton are considered to be key factors in controlling phytoplankton growth in lake ecosystems. In order to better understand the role of physical refuges for zooplankton on zooplanktivorous fish‐plankton relationships, an enclosure experiment was run in a mesotrophic lake. Even‐link systems (zooplankton and phytoplankton) and odd‐link systems (zooplanktivorous fish, zooplankton and phytoplankton) were established. We also established an odd‐link system with a physical refuge for zooplankton where fish predation was limited in the upper half of the enclosure. 2.Fish negatively affected density and mean body length of herbivorous zooplankton and total zooplankton, filtering rates with some intermediate effects in the presence of the refuge. A clear refuge effect was observed for the dominant herbivore, Ceriodaphnia . On the other hand, the refuge seemed to increase the vulnerability of those taxa that aggregated in upper layers of the water column. Grazing was thus reduced in both odd‐link systems. 3.The lack of significant correlation between nutrient availability and phytoplankton biomass in enclosures suggested a top‐down control of algal growth in our experimental systems. In both odd‐link systems (‘fish’ and ‘refuge’) phytoplankton biomass was significantly enhanced, and transparency was reduced in comparison with the even‐link system.

Abstract The mean transit time (MTT) is an important descriptor of water storage and release dynamics in watersheds. Although MTT studies are numerous for many regions around the world, they are rare for prairie watersheds where seasonally cold or dry conditions require adequate methodological choices towards MTT estimation, especially regarding the handling of sparse data records and tracer selection. To examine the impact of such choices, we used timeseries of δ 18 O and δ 2 H from two contrasted years (2014 and 2015) and relied on two metrics and two modelling methods to infer MTTs in prairie watersheds. Our focus was on nested outlets with different drainage areas, geologies, and known run‐off generation mechanisms. The damping ratio and young water fraction (i.e., the fraction of streamflow with transit times lesser than 3 months) metrics, as well as the sine‐wave modelling and time‐based convolution modelling methods, were applied to year‐specific data. Results show that young water fractions and modelled MTT values were, respectively, larger and smaller in 2014, which was a wet year, compared with that in 2015. In 2014, most outlets had young water fractions larger than 0.5 and MTT values lesser than 6 months. The damping ratio, young water fraction, and sine‐wave modelling methods led to convergent conclusions about watershed water storage and release dynamics for some of the monitored sites. Contrasting results were, however, obtained when the same method was applied using δ 2 H instead of δ 18 O, due to differing evaporation fractionation, or when the time‐based convolution modelling method was used. Some methods also failed to provide any robust results during the dry year (i.e., 2015), highlighting the difficulty in inferring MTTs when data are sparse due to intermittent streamflow. This study therefore allowed the formulation of empirical recommendations for MTT estimation in prairie environments as a function of data availability and antecedent wetness conditions.

Abstract Reference evapotranspiration (ETo) is one of the most important factors in the hydrologic cycle and water balance studies. In this study, the performance of three simple and three wavelet hybrid models were compared to estimate ETo in three different climates in Iran, based on different combinations of input variables. It was found that the wavelet-artificial neural network was the best model, and multiple linear regression (MLR) was the worst model in most cases, although the performance of the models was related to the climate and the input variables used for modeling. Overall, it was found that all models had good accuracy in terms of estimating daily ETo. Also, it was found in this study that large numbers of decomposition levels via the wavelet transform had noticeable negative effects on the performance of the wavelet-based models, especially for the wavelet-adaptive network-based fuzzy inference system and wavelet-MLR, but in contrast, the type of db wavelet function did not have a detectable effect on the performance of the wavelet-based models.