English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Cette étude a été réalisée dans le cadre d'un projet multidisciplinaire sur la gestion et la protection de l'habitat des salmonidés et sur l'évaluation des perturbations que subissent les habitats de ces poissons dans les eaux courantes suite aux coupes forestières et à la construction de routes. Afin d'identifier les voies d'écoulement responsables de la qualité des eaux de surface d'un petit bassin versant forestier, une étude approfondie a été entreprise sur l'évolution de la qualité de l'eau de pluie lors de son passage à travers la phytocénose et la couverture pédologique jusqu'au ruisseau. La signature chimique des compartiments du bassin versant servira d'intrant quant à l'application et l'analyse du modèle EMMA (end-members mixing analysis).La signature chimique de l'eau du ruisseau s'explique par un graphe x-y (graphe de mélange) sur lequel la composition chimique des compartiments et celle du ruisseau sont reportées. Si trois compartiments circonscrivent la signature chimique du cours d'eau, alors on peut émettre l'hypothèse que ces compartiments se mélangent de façon conservatrice pour donner la qualité des eaux de surface du bassin versant. Plusieurs traceurs (conductivité électrique, SO42-, Cl-, NO3-, K+, Alt et Fet) naturels n'ont pas servi à l'identification des compartiments parce que le modèle ne tient pas compte de certaines conditions, tels l'activité biologique, l'état hydrique des profils, etc. Seuls le pH, Na+, Ca2+, Mg2+ et SiO2 se sont avérés des traceurs utiles. La nappe phréatique a été incluse par défaut dans le modèle puisqu'il était connu qu'elle assurait la base de l'écoulement du cours d'eau en tout temps de l'année. Les sols de la plaine d'inondation semblent également prendre part à la qualité de l'eau du ruisseau, particulièrement les horizons B podzoliques, lesquels sont saturés d'eau pendant toute la période sans gel. C'est donc dire que l'écoulement de l'eau souterraine et l'écoulement hypodermique au niveau des horizons B de la plaine d'inondation sont les voies d'écoulement qui expliquent le mieux la qualité des eaux de surface du bassin versant.Toutefois, la séparation de l'hydrogramme par l'équation du bilan massique a montré qu'un modèle à trois réservoirs (nappe phréatique, horizons B des versants sud et nord) ne peut pas donner des résultats satisfaisants quant à la simulation de la charge chimique des eaux de surface. Le modèle élimine systématiquement trop de compartiments pouvant s'avérer explicatifs de la qualité de l'eau du ruisseau. Un modèle mécaniste développé à partir des variations du niveau de la nappe phréatique, de la conductivité hydraulique et de la composition chimique des solutions de sol permettrait de reproduire plus rigoureusement l'hydrogramme du ruisseau. Le modèle EMMA demeure tout de même un bon outil pour réfuter ou confirmer une hypothèse de recherche car il met clairement en relation la composition chimique des compartiments à celle du ruisseau et enlève parfois tout doute quant à l'action d'un processus susceptible d'alimenter le cours d'eau.Intense forest harvesting is suspected as a cause of soil acidification. Inputs of acidity into the soil system may lead to high concentrations of metal ion species in the soil solution and surface waters. Some of these metal ions, e.g., Al3+, can cause toxic responses to fish and aquatic invertebrates. Timber-induced soil and surface water acidification is considered to be a short-lived phenomenon during the growing season following the cut. Vegetation loss could mean increased frequency of high Al3+ and H+concentrations in stream water rather than increased mean levels.Many types of tracers are useful for hydrograph separation. Isotopic (e.g., deuterium and tritium) and natural chemical tracers (e.g., pH, Cl-, SiO2) have been used extensively to interpret chemical data gathered in catchment studies. The ability of computer simulation models to reproduce the hydrograph and chemical species in streamwater varies. In some cases, the use of too many hydrological parameters (i.e., over-parameterization) can make the validation of reactions responsible for streamwater chemistry almost impossible. Recently, advances in hydrological modelling have been made by considering that streamwater chemistry is a mixture of groundwater and soil solutions at different depths. One model that originates from this hypothesis is EMMA (end-member mixing analysis). Chemical species that are variable with depth within a same soil profile were shown to be highly correlated with streamwater discharge. Generally, chemical species that show high concentrations in surface horizons increase in streamwater during high flow, whereas chemical species found in high concentrations in lower horizons are higher during low flow. In order to identify end-members that can potentially contribute to streamwater chemistry of a small catchment in central New Brunswick, we investigated the chemistry changes of rainwater entering the catchment, passing through vegetation and soils and reaching the stream channel. The chemical composition of the catchment's end-members will serve as input in order to run and analyse the EMMA model. Furthermore, a better knowledge of water flowpaths that dominate in the catchment could be valuable information for the Department of Fisheries and Oceans, who, in 1990, initiated a multidisciplinary project on 1) the protection and management of the salmonid habitat, and 2) the effects of forest harvesting and road construction on the freshwater habitats of these fish. Harvest operations are planned from 1996 until 1999.Streamwater chemistry is explained by a x-y graph (mixing diagram) on which the end-members and streamwater chemical composition are plotted. Because end-member chemistry is stable over time and space, mean values of tracers are plotted on the mixing diagram. Streamwater chemical compositions have all been plotted on the graph since they vary significantly with flow. If the chemical composition of three end-members enclose the streamwater chemical composition, then it can be assumed that these end-members mix conservatively to produce streamwater chemistry. If two chemical species mix non-conservatively, then the model will not accurately indicate the relative contribution of each end-member. Generally, the mixing diagram does not validate conservative mixing, but it can be used to test a mixing hypothesis. For example, if streamwater chemistry falls largely outside the end-members chemical composition, then at least one end-member is incorrectly characterized (or missing), or the end-members do not mix conservatively. The relative contribution of selected end-members are obtain from the mass balance equation: CtQt=C1Q1 + C2Q2 + C3Q3, where 1, 2 and 3 refer to the three end-members, C1,2 and 3 are the soil water concentrations of conservative elements for each end-member, and Q1,2 and 3 are the amounts of soil water for a given end-member. With this equation, the concentrations of a number of elements for each end-member (C1, C2, C3) are used simultaneously to estimate a single value for each Q1, Q2 and Q3. Since we want to quantify the contribution of each end-member to the total stream discharge, i.e., the mix of the three end- members, Qt is set to 1. Once values for Q1, Q2 and Q3 are calculated, the results are interpreted in terms of a hydrograph separation to show the contribution from each end-member to the overall stream discharge. Two soil toposequences that correspond to typical soil profiles along the northern and southern hillslopes were selected. From June to November 1995, wet deposition, throughfall, soil solutions at four depths and streamwater were collected. Samples were analyzed for pH, electrical conductivity, Na+, Ca2+, Mg2+, K+, SO42-, Cl-, NO3-, SiO2 , Alt and Fet.Many natural tracers (electrical conductivity, SO42-, Cl-, NO3-, K+, Alt and Fet) have not been used to identify end-members because the model does not always consider adequately some conditions or processes that go on in the catchment, e.g., biological activity and Eh. Because they vary considerably with depth, solution pH, Na+, Ca2+, Mg2+ and SiO2 have been shown to be useful tracers. Groundwater has been included in every diagram as one of the three end-members mixing conservatively to produce streamwater since it is certain that it contributes a large portion to the total discharge under any hydrological condition. Soils along the stream seem to contribute the rest of the streamwater chemistry, particularly B horizons which are submerged all summer by groundwater. Thus, groundwater and subsurface flow at the base of the soil profiles along the stream seem to be the principal flow mechanisms that control streamwater chemistry in the catchment. However, hydrograph separation shows that a three end-member model (i.e., groundwater, B horizons from the northern and southern hillslopes) is not enough to simulate streamwater chemistry. Saturated subsurface flow in the B horizons from both sides of the stream should contribute approximately the same amount to the total discharge since groundwater affects both end- members throughout the growing season. In that respect, groundwater level fluctuations at this depth of the soil profiles should not be considered as a cause of this discrepancy. What can be said at this point is that one end-member that is incorrectly defined in space, and that has a similar chemical composition to saturated subsurface flow coming from the southern hillslope, is the primary source (with groundwater) of stream discharge during events. It is thus better to interpret this information in terms of solution type rather than in terms of physical origin (northern or southern hillslope). In this manner, the stream water is provided by both hillslopes.In conclusion, the model eliminates systematically too many end-members that could partially explain streamwater chemistry. Results show that a more complex mixture is necessary to reproduce streamwater chemistry. A mechanistic model based on groundwater level fluctuations, hydraulic conductivity and soil solution chemistry would possibly have better success in reproducing the stream hydrograph. However, EMMA remains a useful tool to refute or confirm the possible action of a flow mechanism by correlating the chemical composition of end-members with streamwater chemistry

revue des sciences de l'eau

Identification des compartiments responsables de la qualité des eaux de surface d'un petit bassin versant du centre du Nouveau-Brunswick (Canada): application et analyse du modèle hydrochimique EMMA