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Depth profiles of water biogeochemical properties were collected with SeaBird Electronics (SBE) Conductivity, Temperature, and Depth (CTD) profilers from 2013-2024 at five drinking water reservoirs in southwestern Virginia, USA. The study reservoirs are: Beaverdam Reservoir (Vinton, Virginia), Carvins Cove Reservoir (Roanoke, Virginia), Falling Creek Reservoir (Vinton, Virginia), Gatewood Reservoir (Pulaski, Virginia), and Spring Hollow Reservoir (Salem, Virginia). Beaverdam, Carvins Cove, Falling Creek, and Spring Hollow Reservoirs are owned and operated by the Western Virginia Water Authority as primary or secondary drinking water sources for Roanoke, Virginia, and Gatewood Reservoir is a drinking water source for the town of Pulaski, Virginia. The dataset consists of CTD depth profiles measured at the deepest site of each reservoir adjacent to the dam as well as other upstream reservoir sites. The profiles were collected approximately fortnightly in the spring months, weekly in the summer and early autumn, and monthly in the late autumn and winter. Beaverdam Reservoir, Carvins Cove Reservoir, and Falling Creek Reservoir were sampled every year in the dataset (2013-2024); Spring Hollow Reservoir was only sampled 2013-2017 and 2019; and Gatewood Reservoir was only sampled in 2016. Data availability differs across years due to additional sensors that have been added or replaced over time. From 2013-2016, profiles were taken with a CTD equipped with an SBE 43 Dissolved Oxygen sensor and an ECO FLNTU sensor for turbidity and chlorophyll. From 2017-2024, profiles were taken with a CTD equipped with an SBE 43 Dissolved Oxygen sensor, an ECO FLNTU sensor for turbidity and chlorophyll, a PAR-LOG ICSW sensor for photosynthetically active radiation, and a SBE 27 pH and ORP (oxidation-reduction potential) sensor. In 2022 and 2023, profiles were also taken with an additional CTD equipped with an SBE 43 Dissolved Oxygen sensor; an ECO Triplet Scattering Fluorescence sensor for CDOM, phycocyanin, and phycoerythrin; an ECO FLNTU sensor for turbidity and chlorophyll; and PAR-LOG ICSW for photosynthetically active radiation. All variables were measured every 0.25 seconds, resulting in depth profiles at approximately ten centimeter resolution. Maximum cast depth is not necessarily equal to site depth; see methods for more information. 

Abstract PurposeHypolimnetic hypoxia has become increasingly prevalent in stratified water bodies in recent decades due to climate change. One primary sink of dissolved oxygen (DO) is sediment oxygen uptake ($${J}_{{O}_{2}}$$ $J_{O_2}$). On the water side of the sediment–water interface (SWI),$${J}_{{O}_{2}}$$ $J_{O_2}$is controlled by a diffusive boundary layer (DBL), a millimeter-scale layer where molecular diffusion is the primary transport mechanism. In previous studies, the DBL was determined by visual inspection, which is subjective and time-consuming. Material and methodsIn this study, a computational procedure is proposed to determine the SWI and DBL objectively and automatically. The procedure was evaluated for more than 300 DO profiles in the sediment of three eutrophic water bodies spanning gradients of depth and surface area. Synthetic DO profiles were modeled based on sediment characteristics estimated by laboratory experiments. The procedure was further verified adopting the synthetic profiles. Results and discussionThe procedure, which was evaluated for both measured and synthetic DO profiles, determined the SWI and DBL well for both steady and non-steady state DO profiles. A negative relationship between DBL thickness and aeration rates was observed, which agrees with existing literatures. ConclusionsThe procedure is recommended for future studies involving characterizing DBL to improve efficiency and consistency. 

Depth profiles of temperature, dissolved oxygen, conductivity, specific conductance, chlorophyll a, and turbidity were collected with a CTD (Conductivity, Temperature, and Depth) profiler fitted with a SBE 43 Dissolved Oxygen sensor and an ECO Triplet Fluorometer and Backscattering Sensor from 2013 to 2022. From 2017-2022, pH and oxidation-reduction potential (ORP) were also collected with a SBE 27 pH and O.R.P. (redox) sensor. CTD profiles were collected in five drinking water reservoirs in southwestern Virginia, USA. All variables were measured every 0.25 seconds, resulting in depth profiles at approximately ten centimeter resolution. The five study reservoirs are: Beaverdam Reservoir (Vinton, Virginia), Carvins Cove Reservoir (Roanoke, Virginia), Falling Creek Reservoir (Vinton, Virginia), Gatewood Reservoir (Pulaski, Virginia), and Spring Hollow Reservoir (Salem, Virginia). Beaverdam, Carvins Cove, Falling Creek, and Spring Hollow Reservoirs are owned and operated by the Western Virginia Water Authority as primary or secondary drinking water sources for Roanoke, Virginia, and Gatewood Reservoir is a drinking water source for the town of Pulaski, Virginia. The dataset consists of CTD depth profiles measured at the deepest site of each reservoir adjacent to the dam as well as well as other upstream reservoir sites. The profiles were collected approximately fortnightly in the spring months, weekly in the summer and early autumn, and monthly in the late autumn and winter. Beaverdam Reservoir, Carvins Cove Reservoir, and Falling Creek Reservoir were sampled every year in the dataset (2013-2022); Spring Hollow Reservoir was not in sampled in 2018 or 2020–2022; and Gatewood Reservoir was only sampled in 2016. 

Abstract Globally significant quantities of carbon (C), nitrogen (N), and phosphorus (P) enter freshwater reservoirs each year. These inputs can be buried in sediments, respired, taken up by organisms, emitted to the atmosphere, or exported downstream. While much is known about reservoir-scale biogeochemical processing, less is known about spatial and temporal variability of biogeochemistry within a reservoir along the continuum from inflowing streams to the dam. To address this gap, we examined longitudinal variability in surface water biogeochemistry (C, N, and P) in two small reservoirs throughout a thermally stratified season. We sampled total and dissolved fractions of C, N, and P, as well as chlorophyll-a from each reservoir’s major inflows to the dam. We found that heterogeneity in biogeochemical concentrations was greater over time than space. However, dissolved nutrient and organic carbon concentrations had high site-to-site variability within both reservoirs, potentially as a result of shifting biological activity or environmental conditions. When considering spatially explicit processing, we found that certain locations within the reservoir, most often the stream–reservoir interface, acted as “hotspots” of change in biogeochemical concentrations. Our study suggests that spatially explicit metrics of biogeochemical processing could help constrain the role of reservoirs in C, N, and P cycles in the landscape. Ultimately, our results highlight that biogeochemical heterogeneity in small reservoirs may be more variable over time than space, and that some sites within reservoirs play critically important roles in whole-ecosystem biogeochemical processing. 

Sediment traps were deployed to assess the mass and composition (iron, manganese, total organic carbon, and total nitrogen) of settling particulates in the water column of two drinking water reservoirs—Beaverdam Reservoir and Falling Creek Reservoir, both located in Vinton, Virginia, USA. Sediment traps were deployed at two depths in each reservoir to capture both epilimnetic and hypolimnetic (total) sediment flux. The particulates were collected from the traps approximately fortnightly from April to December from 2018 to 2022, then filtered, dried, and analyzed for either iron and manganese or total organic carbon and total nitrogen. Beaverdam and Falling Creek are owned and operated by the Western Virginia Water Authority as primary or secondary drinking water sources for Roanoke, Virginia. The sediment trap dataset consists of logs detailing the sample filtering process, the mass of dried particulates from each filter, and the raw concentration data for iron (Fe) and manganese (Mn), total organic carbon (TOC) and total nitrogen (TN). The final products are the calculated downward fluxes of solid Fe, Mn, TOC and TN during the deployment periods. 

Rapid changes in climate and land use are having substantial and interacting impacts on lake water quality around the world. Here, we synthesized time-series data for dissolved oxygen, temperature, chlorophyll-a, total phosphorus, total nitrogen, and dissolved organic carbon at multiple depths in 822 lakes to facilitate analyses of these changes. The dataset extends from 1921–2022, with a median data duration of 29 years (range 5-102) and a median of 5 unique sampling dates per year at each lake. Lakes in the dataset have a median depth of 12.5 m (range 1.5–480 m), median surface area of 85.4 ha (range: 0.5–237000 ha) and median elevation of 264 m (range: -215–2804). The lakes are located in 18 countries across 5 continents, with latitudes ranging from -42.6 to 68.3. To facilitate interoperability with other large-scale datasets, each lake is linked to a unique hydroLAKES lake ID when possible (n = 683). 

Abstract Water level drawdowns are increasingly common in lakes and reservoirs worldwide as a result of both climate change and water management. Drawdowns can have direct effects on physical properties of a waterbody (e.g., by altering stratification and light dynamics), which can interact to modify the waterbody's biology and chemistry. However, the ecosystem‐level effects of drawdown remain poorly characterized in small, thermally stratified reservoirs, which are common in many regions of the world. Here, we intensively monitored a small eutrophic reservoir for 2 years, including before, during, and after a month‐long drawdown that reduced total reservoir volume by 36%. During drawdown, stratification strength (maximum buoyancy frequency) and surface phosphate concentrations both increased, contributing to a substantial surface phytoplankton bloom. The peak in phytoplankton biomass was followed by cascading changes in surface water chemistry associated with bloom degradation, with sequential peaks in dissolved organic carbon, dissolved carbon dioxide, and ammonium concentrations that were up to an order of magnitude higher than the previous year. Dissolved oxygen concentrations substantially decreased in surface waters during drawdown (to 41% saturation), which was associated with increased total iron and manganese concentrations. Combined, our results illustrate how changes in water level can have cascading effects on coupled physical, chemical, and biological processes. As climate change and water management continue to increase the frequency of drawdowns in lakes worldwide, our results highlight the importance of characterizing how water level variability can alter complex in‐lake ecosystem processes, thereby affecting water quality. 

The opportunity to participate in and contribute to emerging fields is increasingly prevalent in science. However, simply thinking about stepping outside of your academic silo can leave many students reeling from the uncertainty. Here, we describe 10 simple rules to successfully train yourself in an emerging field, based on our experience as students in the emerging field of ecological forecasting. Our advice begins with setting and revisiting specific goals to achieve your academic and career objectives and includes several useful rules for engaging with and contributing to an emerging field.