In agriculture-dominant watersheds, riparian ecosystems provide a wide array of benefits such as reducing soil erosion, filtering chemical compounds, and retaining sediments. Traditionally, the boundaries of riparian zones could be estimated from Digital Elevation Models (DEMs) or field surveys. In this study, we used an Unmanned Aerial Vehicle (UAV) and photogrammetry method to map the boundaries of riparian zones. We first obtained the 3D digital surface model with a UAV. We applied the Vertical Distance to Channel Network (VDTCN) as a classifier to delineate the boundaries of the riparian area in an agricultural watershed. The same method was also used with a low-resolution DEM obtained with traditional photogrammetry and two more LiDAR-derived DEMs, and the results of different methods were compared. Results indicated that higher resolution UAV-derived DEM achieved a high agreement with the field-measured riparian zone. The accuracy achieved (Kappa Coefficient, KC = 63%) with the UAV-derived DEM was comparable with high-resolution LiDAR-derived DEMs and significantly higher than the prediction accuracy based on traditional low-resolution DEMs obtained with high altitude aerial photos (KC = 25%). We also found that the presence of a dense herbaceous layer on the ground could cause errors in riparian zone delineation with VDTCN for both low altitude UAV and LiDAR data. Nevertheless, the study indicated that using the VDTCN as a classifier combined with a UAV-derived DEM is a suitable approach for mapping riparian zones and can be used for precision agriculture and environmental protection over agricultural landscapes.

This article relates epilithic dry- and wet-seasonal bacterial biofilm composition to water quality along Río de la Sabana near Acapulco, Mexico. Samples were taken from various locations including nearly pristine upland locations, adjacent to residential floodplain developments, and immediately upstream from an estuarine lagoon. Bacterial composition was identified through sequential DNA analysis at the phylum, class, order, and family levels, with most of these categorized as heterotrophs, autotrophs, denitrifiers, nitrogen fixers, pathogens, and/or potential bioremediators based on generalized literature-sourced assignments. The results were interpreted in terms of location by extent of effluent pollution, and by dry versus wet seasonal changes pertaining to biofilm composition, related bacterial functions, and the following water quality parameters: temperature, pH, dissolved oxygen, biological and chemical oxygen demand, fecal and total bacteria counts, methylene blue active substances, electrical conductivity, and nitrite, nitrate, ammonium, sulfate, and phosphate concentrations. It was found that epilithic bacterial biofilm diversity was richest during the wet season, was more varied in abundance along the upland locations, and was dominated byProteobacteriaandBacteroideteswith bioremediation and pathogen functions along effluent-receiving river locations. Low-abundance families associated with anaerobic and denitrifying functions were more prevalent during the wet season, while low-abundance families associated with aerobic, N₂-fixing and pH-elevating functions were more prevalent during the dry season.

This article focuses on analyzing the Geological Survey of Canada (GSC) data for total mercury concentrations (THg) in lake and stream sediments. The objective was to quantify how sediment THg varies by (i) sediment organic matter, determined by loss on ignition (LOI) at 500^∘C, (ii) atmospheric Hg deposition (atm.Hgdep) as derived from the Global/Regional Atmospheric Heavy Metals Model GRAHM2005, and (iii) mean annual precipitation and mean monthly July and January temperatures (TJuly,TJan). Through regression analyses and averaging by National Topographic System tiles (NTS, 1:250,000 scale), it was found that 40, 70, and 80% of the sediment THg, LOI, and atm.Hgdepvariations were, respectively, related to precipitation,TJuly, andTJan. In detail, lake sediment THg was related to atm.Hgdepand precipitation, while stream sediment THg was related to sediment LOI andTJuly. Plotting sediment THg versus sediment LOI revealed a curvilinear pattern, with highest Hg concentrations at intermediate LOI values. Analysing the resulting 10th and 90th log₁₀THg percentiles within each 10% LOI class from 0 to 100% revealed that (i) atm.Hgdepcontributed to the organic component of sediment THg and (ii) this was more pronounced for lakes than for streams.

Defining stream channels in a watershed is important for assessing freshwater habitat availability, complexity, and quality. However, mapping channels of small tributary streams becomes challenging due to frequent channel change and dense vegetation coverage. In this study, we used an Unmanned Aerial Vehicle (UAV) and photogrammetry method to obtain a 3D Digital Surface Model (DSM) to estimate the total in-stream channel and channel width within grazed riparian pastures. We used two methods to predict the stream channel boundary: the Slope Gradient (SG) and Vertical Slope Position (VSP). As a comparison, the same methods were also applied using low-resolution DEM, obtained with traditional photogrammetry (coarse resolution) and two more LiDAR-derived DEMs with different resolution. When using the SG method, the higher-resolution, UAV-derived DEM provided the best agreement with the field-validated area followed by the high-resolution LiDAR DEM, with Mean Squared Errors (MSE) of 1.81 m and 1.91 m, respectively. The LiDAR DEM collected at low resolution was able to predict the stream channel with a MSE of 3.33 m. Finally, the coarse DEM did not perform accurately and the MSE obtained was 26.76 m. On the other hand, when the VSP method was used we found that low-resolution LiDAR DEM performed the best followed by high-resolution LiDAR, with MSE values of 9.70 and 11.45 m, respectively. The MSE for the UAV-derived DEM was 15.12 m and for the coarse DEM was 20.78 m. We found that the UAV-derived DEM could be used to identify steep bank which could be used for mapping the hydrogeomorphology of lower order streams. Therefore, UAVs could be applied to efficiently map small stream channels in order to monitor the dynamic changes occurring in these ecosystems at a local scale. However, the VSP method should be used to map stream channels in small watersheds when high resolution DEM data is not available.

This article focusses on the bio-monitoring of total Hg (THg), sulfur (TS) and carbon (TC) concentrations and pool sizes in forest vegetation and soil layers within the context of a maritime-to-inland transect study in southwestern New Brunswick. This transect stretches from the Grand Manan Island in the Bay of Fundy to the mainland coast (Little Lepreau to New River Beach) and 100 km northward to Fredericton. Along the Bay, frequent summer fogs are thought to have led to increased THg concentrations in forest vegetation and soils such that island THg > coast THg > inland THg concentrations. Transect sampling was done in two phases: (i) a general vegetation and soil survey, and (ii) focusing on specific soil layers (forest floor, top portion of the mineral soils), and select moss and mushrooms species. By way of multiple regression, it was found that soil, moss and mushroom THg and TS were strongly related to one another, with THg decreasing from the island to the inland locations. The accumulated Hg pool within the mineral soil, however, far exceeded (i) the estimated THg pools of the forest biomass (trees, moss and mushrooms) and the forest floor, and (ii) the literature-reported and case-study inferred net input/output rates for annual atmospheric Hg deposition and sequestration, Hg volatilization, and Hg leaching. Partitioning the total soil Hg pool into geogenically and atmospherically derived portions suggested that mineral soils in temperate to boreal forest regions have accumulated and retained atmospherically derived Hg over thousand years and more. These results are summarized in terms of further guiding forest THg monitoring and modelling efforts in terms of specific vegetation and soil sampling targets

Modelling and mapping critical loads and exceedances for the Georgia Basin, British Columbia, using a zero base-cation depletion criterion