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Winter freeze damage affects fruit production regularly in the northern part of North America. This situation, which is related to climatic conditions, financially affects fruit producers and limits the affected areas to the use of cultivars that are freeze-resistant but do not always yield a sufficient market return. The purpose of this study is to conduct an experiment with a newly developed numerical model (W5L+) and its associated snow cover module to evaluate the effects of the projected climatic change on the risk of winter freeze damage to apple trees. The model W5L+ quantifies the risk of freeze damage occurrence at defined locations based on local meteorological records or projections. Risk quantification is achieved by screening daily meteorological time series with pre-identified parameters that are known to be proxies for conditions that result in freeze-damage. The model was parameterized using historical meteorological records from apple orchards in Farnham, southern Québec, and descriptions of regional winter freeze damaging events that were recorded between 1920 and 2005. In 82% of the years studied, the model was able to identify correctly the order of magnitude of the recorded freeze events. During the same period, results suggest that extremely low temperatures and prolonged periods of low temperatures were responsible for the majority of damaging events. When used with climatic projections downscaled from a global climate model (GCM), the model predicted a decrease in freeze risk for apple trees at the Farnham orchards in the next 60 years. This trend is due to a decrease in extreme cold events as well as in prolonged periods of low temperature. The present study demonstrates the potential of the W5L+ modeling approach in studying the impact of climate change on the occurrence of damaging freezes. However, the predictions need to be verified by using the model with a large range of agro-climatic conditions and climate projections. [ABSTRACT FROM AUTHOR]

The objective of this research is to characterize the variability of trace metals in the Rio Santa watershed based on synoptic sampling applied at a large scale. To that end, we propose a combination of methods based on the collection of water, suspended sediments, and riverbed sediments at different points of the watershed within a very limited period. Forty points within the Rio Santa watershed were sampled between June 21 and July 8, 2013. Forty water samples, 36 suspended sediments, and 34 riverbed sediments were analyzed for seven trace metals. The results, which were normalized using the USEPA guideline for water and sediments, show that the Rio Santa water exhibits Mn concentrations higher than the guideline at more than 50% of the sampling points. As is the second highest contaminating element in the water, with approximately 10% of the samples containing concentrations above the guideline. Sediments collected in the Rio Santa riverbed were heavily contaminated by at least four of the tested elements at nearly 85% of the sample points, with As presenting the highest normalized concentration, at more than ten times the guideline. As, Cd, Fe, Pb, and Zn present similar concentration trends in the sediment all along the Rio Santa.The findings indicate that care should be taken in using the Rio Santa water and sediments for purposes that could affect the health of humans or the ecosystem. The situation is worse in some tributaries in the southern part of the watershed that host both active and abandoned mines and ore-processing plants.

Quantifying groundwater flow at seepage faces is crucial because seepage faces influence the hydroecology and water budgets of watersheds, lakes, rivers and oceans, and because measuring groundwater fluxes directly in aquifers is extremely difficult. Seepage faces provide a direct and measurable groundwater flux but there is no existing method to quantitatively image groundwater processes at this boundary. Our objective is to determine the possibilities and limitations of thermal imagery in quantifying groundwater discharge from discrete seeps. We developed a conceptual model of temperature below discrete seeps, observed 20 seeps spectacularly exposed in three dimensions at an unused limestone quarry and conducted field experiments to examine the role of diurnal changes and rock face heterogeneity on thermal imagery. The conceptual model suggests that convective air-water heat exchange driven by temperature differences is the dominant heat transfer mechanism. Thermal imagery is effective at locating and characterizing the flux of groundwater seeps. Areas of active groundwater flow and ice growth can be identified from thermal images in the winter, and seepage rates can be differentiated in the summer. However, the application of thermal imagery is limited by diverse factors including technical issues of image acquisition, diurnal changes in radiation and temperature, and rock face heterogeneity. Groundwater discharge rates could not be directly quantified from thermal imagery using our observations but our conceptual model and experiments suggest that thermal imagery could quantify groundwater discharge when there are large temperature differences, simple cliff faces, non-freezing conditions, and no solar radiation., (© 2016, National Ground Water Association.)