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1,035 results for “Reservoirs”
Invasion dynamics of quagga mussels within a Southern California reservoir and its spatially intermittent watershed
Since its discovery in Lake Mead, Nevada in 2007, the invasive quagga mussel (Dreissena rostriformis bugensis) spread throughout the lower Colorado River drainage and into connected Southern California water systems. In December 2013, quagga mussels were found in Lake Piru, California, a reservoir with no connection to the Colorado River drainage. An initial “boom” period occurred in the first year after colonization. High densities and settlement rates continued for three years while lake water levels were low and relatively stable, despite periodic removals of mussels from lake infrastructure. Mussels were initially restricted to hard substrates but were regularly found on soft sediments within two years of colonization. Storms in 2017 dramatically increased the lake level and deposited substantial sediment, which eliminated mussels on soft sediments and reduced the overall mussel population. Reproduction and juvenile settlement rebounded within 6 months, despite the low population of adult mussels in the lake. Environmental conditions, particularly fill status and water temperature, rather than adult density, appear to be the primary driver of veliger abundance in this system, while recruitment was primarily explained by veliger abundance. Elevated water releases from the reservoir increased the flux of veligers downstream and led to mussel recruitment >15 km downstream. Sustained establishment of quagga mussels downstream has not occurred in the Santa Clara River and seems unlikely due to the unstable habitat conditions. However, periodic downstream colonization increases the likelihood for the infestation to spread and impact agricultural and municipal water systems that receive water from the river.
Missouri reservoir profile data including temperature, depth, and oxygen profiles (1989-2022)
This dataset of limnological profiles starts in 1989 and is from 250 reservoirs in the state of Missouri (MO) in the USA collected by the University of Missouri Limnology Lab. Physical parameters derived from sensors include temperature and oxygen with depth. After 2017, sondes were upgraded to Yellow Springs Instruments (YSI) EXO3s; profiles include a range of physical, chemical, and biological parameters including depth, conductivity, pH, oxidative-reductive potential (ORP), chlorophyll a, phycocyanin (PC), phycoerythrin (PE), and turbidity. Most of the profiles were collected during the summer months (May-September) when the reservoirs were thermally stratified, but a few were taken during the rest of the year (October-April). The majority of profiles were taken at the deepest point in the reservoir directly up-reservoir of the dam. Sampling was conducted from a boat most of the time, but a few profiles were taken from bridges and docks. The bulk of the data come from the Statewide Lake Assessment Project (SLAP), funded by the Missouri Department of Natural Resources. The profiles are divided into a single file for 1989-2016 and then annual compiled datasets for 2017 and beyond. This data has been quality controlled for basic errors and any data outside of normal factory issued sensor ranges.
Time series of stable water isotopes (d18O, d2H) from Carvins Cove Reservoir in Southwestern Virginia, USA 2024-2025
Samples of stable water isotopes (delta 18O and delta 2H) were collected from surface waters and depth profiles in Carvins Cove Reservoir (Roanoke, Virginia, USA). Carvins Cove Reservoir is owned operated by the Western Virginia Water Authority as a primary drinking water source for Roanoke, Virginia. Samples were collected approximately monthly at two sites along a primary tributary and depth profiles at multiple transects within Carvins Cove Reservoir from May 2024 - April 2025. Additional isotope samples were analyzed from precipitation collected at the Carvins Cove Reservoir dam in 2024. Samples were analyzed using cavity ringdown spectroscopy and reported as deviation of concentration from that of Vienna standard mean ocean water. An Rmarkdown file to visualize the dataset accompanies the package.
Missouri reservoir profile data including depth, temperature, oxygen, photopigments, conductivity, pH, turbidity, and oxidative-reductive potential starting in 2023
This dataset of annual limnological profiles starts in 2023 and is from reservoirs in the state of Missouri (MO) in the USA collected by the University of Missouri Limnology Lab. Physical parameters derived from sensors include temperature and oxygen with depth. Sondes used were Yellow Springs Instruments (YSI) EXO3s; profiles include a range of physical, chemical, and biological parameters including depth, conductivity, pH, oxidative-reductive potential (ORP), chlorophyll a, phycocyanin (PC), and turbidity. After May 2024, the turbidity sensor was replaced with a phycoerythrin (PE) sensor. Most of the profiles were collected during the summer months (May-September) when the reservoirs were thermally stratified, but a few were taken during the rest of the year (October-April). The majority of profiles were taken at the deepest point in the reservoir directly up-reservoir of the dam. Sampling was conducted from a boat. The bulk of the data come from the Statewide Lake Assessment Project (SLAP), funded by the Missouri Department of Natural Resources. The profiles are divided into single files for each year. This data has been quality controlled for basic errors and any data outside of normal factory issued sensor ranges.
Missouri reservoir water quality data from the Statewide Lake Assessment Program (SLAP), the Lakes of Missouri Volunteer Program (LMVP), and the Reservoir Observer Student Scientists (ROSS) program
This dataset of limnological water quality data continues from Jones et al., 2024, starting in 2017 until 2021. It is from 195 reservoirs, the majority of which are in the state of Missouri (MO) in the USA collected by the University of Missouri Limnology Lab. Water quality parameters analyzed in the MU Limnology Lab during this time frame include: areal pigment absorption coefficient, alkalinity, alpha (light utilization efficiency P-E parameter), ammonium (NH4), ammonium-debt, anatoxin, chlorophyll a (corrected and uncorrected for pheophytins), chloride, cylindrospermopsin, seston d13C, seston d15N, dissolved turbidity, dissolved organic carbon, Ek (light saturation P-E parameter), FVFM (maximum quantum yield of PSII for photochemistry), gross primary production, microcystin, nitrate & nitrite (NO3), nitrate-debt, particulate nitrogen, particulate phosphorus, phosphorus-debt, pheophytin, particulate carbon, particulate inorganic matter, particulate organic matter, phycocyanin (PHYCO), saxitoxin, Secchi disk depth, silica, soluble reactive phosphorus, total dissolved nitrogen (TDN), total dissolved phosphorus (TDP), total nitrogen (TN), total phosphorus (TP), total suspended solids (TSS), and urea. Most of the samples were collected during the summer months (May-September) when the reservoirs were thermally stratified, but a few were taken during the rest of the year (October-April). The majority of samples were taken at the deepest point in the reservoir directly up-reservoir of the dam. Sampling was conducted from a boat most of the time, but a few samples were taken from shorelines and drinking water treatment intake pipes. Most of the data come from the Statewide Lake Assessment Project (SLAP) and the Lakes of Missouri Volunteer Program (LMVP) funded by the Missouri Department of Natural Resources. This data represents duplicate or triplicate water samples collected from either the water surface, integrated over the depth of the epilimnion, or from discrete dep
Missouri reservoir water quality data (2022 - current) from the Statewide Lake Assessment Program (SLAP)
This dataset of limnological water quality data continues from North et al., 2025, starting in 2022 until present. The data is from reservoirs, primarily within the state of Missouri (MO) in the USA collected by the University of Missouri Limnology Lab. Water quality parameters analyzed in the MU Limnology Lab during this time frame include: ammonium (NH4), anatoxin, chlorophyll a (corrected and uncorrected for pheophytins), chloride, cylindrospermopsin, dissolved organic carbon, microcystin, nitrate & nitrite (NO3), pheophytin, particulate inorganic matter, particulate organic matter, phycocyanin, saxitoxin, Secchi disk depth, total dissolved nitrogen (TDN), total dissolved phosphorus (TDP), total nitrogen (TN), total phosphorus (TP), total suspended solids, and urea. Most of the samples were collected during the summer months (May-September) when the reservoirs were thermally stratified, but a few were taken during the rest of the year (October-April). The majority of samples were taken at the deepest point in the reservoir directly up-reservoir of the dam. Sampling was conducted from a boat most of the time, but a few samples were taken from shorelines and drinking water treatment intake pipes. The bulk of the data come from the Statewide Lake Assessment Project (SLAP), funded by the Missouri Department of Natural Resources. This data represents duplicate or triplicate water samples collected from either the water surface, integrated over the depth of the epilimnion, or from discrete depths in the hypolimnion.
Long term limnological measurements in Acton Lake, a southwest Ohio reservoir, and its inflow streams: 1992-2023
Long-term data were collected from Acton Lake and its inflow streams on a suite of physical, chemical and biological variables. The data are collected as part of long-term research investigating how Acton Lake, a eutrophic reservoir, responds to changes in ecosystem subsidies of detritus (sediments) and nutrients. Our data span 31 years, from 1992-2023, although for some parameters the data set spans a shorter time frame within this period. In three of Acton Lake’s inflow streams, collectively constituting ~86% of the lake’s watershed, we include data on hourly stream discharge, as well as concentrations of suspended sediments, ammonium-N, nitrate+nitrite-N, and soluble reactive phosphorus (P). Data on the concentrations of these constituents were collected at various time scales depending on stream discharge (usually every 6-8 hours during storms, every 1-3 days during baseflow). In Acton Lake, we collected data on several parameters from an “outflow” site, at the deepest part of the lake where the water column is usually thermally stratified in summer. Vertical profile data were collected for temperature, dissolved oxygen, photosynthetically active radiation (PAR), and chlorophyll. Depth profile data were collected at 0.5 or 1 m intervals (depending on depth and year), usually weekly from April or May until September or October. In addition, data for several parameters were obtained from “integrated samples” that collect water from the lake surface to the bottom of the euphotic zone (defined as the depth at which PAR equals 1% of surface PAR) with a tube or pump. Parameters for which integrated data are presented include chlorophyll; suspended solids; non-volatile suspended solids; particulate (seston) carbon, nitrogen and phosphorus; and total nitrogen and total phosphorus. We also collected Secchi depth data, using standard methods. Larval fish were collected in the top 1-3 meter stratum of the water column with a metered net to generate estimates of lake-wide l
University of Kansas Field Station: Water level and ice cover at Frank B. Cross Reservoir (Kansas, USA) 1993 - 2016
This database is from regular monitoring of water level and surface ice cover at Frank B. Cross Reservoir, a small freshwater impoundment in northeastern Kansas (USA). Cross Reservoir, located at the University of Kansas Field Station near Lawrence (KS), has a 3-ha surface area and a maximum depth of 12 m. Measurements of water elevation and estimates of ice cover were made at semi-monthly intervals (i.e., roughly every two weeks). The first data were taken in December 1993, shortly after the reservoir was constructed and first filled to capacity. Water levels were measured relative to a permanent water control structure. Ice cover observations were visual estimates of the percent (%) surface of the reservoir covered with ice. Water level measurements and ice cover estimates are made at the same time. This database is updated periodically and maintenance is ongoing.
Ice cover data for Falling Creek Reservoir and Beaverdam Reservoir, Vinton, Virginia, USA for December 2013-December 2022
Ice cover was recorded at Falling Creek Reservoir and Beaverdam Reservoir (both located in Vinton, Virginia, USA) using multiple methods. The ice cover record for Falling Creek Reservoir began in the winter of 2013-2014 and Beaverdam Reservoir beginning in the winter of 2020-2021. Falling Creek Reservoir and Beaverdam Reservoir are owned and operated by the Western Virginia Water Authority as a primary and secondary drinking water source, respectively, for Roanoke, Virginia. These two reservoirs are some of the southernmost waterbodies in the United States that exhibit ice cover during the winter. Given incipient climate change, Falling Creek Reservoir and Beaverdam Reservoir's ice cover data represent an important record of warming for waterbodies in the southeastern United States. Ice cover presence was assessed using multiple methods: visual observation of ice spanning the deep hole (from an observer standing on a reservoir's dam); visual observation via an automated camera deployed near the deep hole; water temperature data from a profile of sensors deployed at a reservoir's deepest site; upwelling shortwave radiation and albedo measured by a meteorological station deployed on a metal structure located over Falling Creek Reservoir's deep hole; and dissolved oxygen sensors deployed at multiple depths at the deep hole of both reservoirs.
Keswick Reservoir Temperature Profile Data (2017-2019)
This dataset contains the Keswick Reservoir temperature profile data collected by using remote logging thermistors (temperature loggers) attached to a cable system at the log boom above Keswick Dam in three monitoring seasons in 2017, 2018 and 2019. Field data monitoring installation was performed by U.S. Bureau of Reclamation (Reclamation), with support from Watercourse Engineering, Inc. (Watercourse) as part of the Shasta Lake and Keswick Reservoir Flow and Temperature Modeling study conducted by Watercourse in cooperation with Reclamation. All data were collected using HOBO Water Temperature Pro v2 Data Loggers and reported to 0.01oF.
Impact on pressure in above zone monitoring interval from unintentional CO2 release from a CCS reservoir
<p>The data set was created by running dynamic numerical simulations with the CMG-software on a static geologic model. It consists of simulations of 16 different CO2 release scenarios from a subsurface storage formation and describes the change in pressure in the above zone monitoring interval over time. The data are daily means of the pressure over a period of 1001 days and are defined on a 160x160 grid. It contains data from 4 release locations where for each location it is simulated 4 different release rates.</p>
Dataset: Effects of high altitude reservoirs on the structure and function of lotic ecosystems: a case study in Italy
<p>Supporting data for "Effects of high altitude reservoirs on the structure and function of lotic ecosystems: a case study in Italy"</p> <p>Macroinvertebrate community composition</p> <p>Water chemical characteristics</p> <p>Daily mean water temperature and daily temperature variations</p> <p>Results of the leaf bags experiments</p>
ERCOT Reservoir Watershed Delineations and Inflow Scenarios
<p>This dataset includes daily runoff totals for historical (reanalysis) and future (GCM simulations) climate. The scenarios are generated for upstream watersheds of 44 reservoirs that supply water for thermal plant cooling throughout the Electric Reliability Council of Texas (ERCOT) power grid region. These data are derived from 1/24 degree gridded CONUS-scale hydrological simulations. Runoff projections are masked to delineated watershed areas (included as shape files) and summed across grid cells within the target watershed. These data may be aggregated to monthly scale to produce unregulated inflow scenarios for ERCOT reservoirs. Reservoir attributes and storage records are included in a supplementary excel spreadsheet. Please see README.txt for further details.</p>
Carbon dioxide, methane, and chemical data from Batang Ai reservoir
<p>The dataset contains biogeochemical in situ field measurements taken in Batang Ai reservoir (located on the Borneo Island, Malaysia). Samples were taken over four sampling campaigns from 2016 to 2018. Data was used to analyse carbon dioxide and methane flux patterns and to calculate the carbon footprint of the reservoir in the paper: “The carbon footprint of a Malaysian tropical reservoir: measured versus modeled estimates highlight the underestimated key role of downstream processes” (<a href="https://doi.org/10.5194/bg-17-1-2020">https://doi.org/10.5194/bg-17-1-2020</a>).</p> <p>Data were also used to calculate budgets of CO2 and CH4 in the epilimnion of Batang Ai reservoir in the paper: “Changing sources and processes sustaining surface CO2 and CH4 fluxes along a tropical river to reservoir system” (<a href="https://doi.org/10.5194/bg-2020-258">https://doi.org/10.5194/bg-2020-258</a>).</p>
Global Reservoir Evaporation Dataset
<p>This dataset contains the monthly evaporation rate and volumes for 7242 reservoirs from March 1984 to December 2016 across the world. The evaporation rate was calculated using the three datasets viz. (1) TerraClimate; (2) ERA5; (3) Princeton Global Forcings. The surface area of these reservoirs is obtained from the Global reservoir surface area dataset (GRSAD). The detailed descriptions for this dataset are presented in Tian et al (2021,2022). The basic information of the global reservoirs was provided by the Global Reservoir and Dam Database (GRanD).<br> When using the data, please cite the following references:<br> Tian, W., Liu, X., Wang, K., Bai, P., Liu, C., & Liang, X. (2022). Estimation of Global Reservoir Evaporation Losses. Journal of Hydrology, 127524.<br> Tian, W., Liu, X., Wang, K., Bai, P., & Liu, C. (2021). Estimation of reservoir evaporation losses for China. Journal of Hydrology, 596, 126142.</p>
Reservoir water quality deterioration due to deforestation emphasizes the indirect effects of global change
<p><strong>This repository contains the dataset linked to the following publication:</strong></p> <p><strong>Article title:</strong> Reservoir water quality deterioration due to deforestation emphasizes the indirect effects of global change</p> <p><strong>Journal title: </strong>Water Research</p> <p><strong>Article Number: </strong>WR_118721</p> <p><strong>doi: </strong>https://doi.org/10.1016/j.watres.2022.118721</p> <p><strong>Abstract: </strong>Deforestation is currently a widespread phenomenon and a growing environmental concern in the era of rapid climate change. In temperate regions, it is challenging to quantify the impacts of deforestation on the catchment dynamics and downstream aquatic ecosystems such as reservoirs and disentangle these from direct climate change impacts, let alone project future changes to inform management. Here, we tackled this issue by investigating a unique catchment-reservoir system with two reservoirs in distinct trophic states (meso‑ and eutrophic), both of which drain into the largest drinking water reservoir in Germany. Due to the prolonged droughts in 2015–2018, the catchment of the mesotrophic reservoir lost an unprecedented area of forest (exponential increase since 2015 and ca. 17.1% loss in 2020 alone). We coupled catchment nutrient exports (HYPE) and reservoir ecosystem dynamics (GOTM-WET) models using a process-based modeling approach. The coupled model was validated with datasets spanning periods of rapid deforestation, which makes our future projections highly robust. Results show that in a short-term time scale (by 2035), increasing nutrient flux from the catchment due to vast deforestation (80% loss) can turn the mesotrophic reservoir into a eutrophic state as its counterpart. Our results emphasize the more prominent impacts of deforestation than the direct impact of climate warming in impairment of water quality and ecological services to downstream aquatic ecosystems. Therefore, we propose to evaluate the impact of climate change on temperate reservoirs by incorporating a time scale-dependent context, highlighting the indirect impact of deforestation in the short-term scale. In the long-term scale (e.g. to 2100), a guiding hypothesis for future research may be that indirect effects (e.g., as mediated by catchment dynamics) are as important as the direct effects of climate warming on aquatic ecosystems.<br> </p> <p><strong>Data description</strong><br> by Xiangzhen Kong (xiangzhen.kong@ufz.de; xzkong@niglas.ac.cn)<br> 2022-06-20</p> <p>1. Discharge in the streams from 2010 to 2021 at YRZ site, and from 2010 to 2020 at YHZ_Q site.</p> <ul> <li>File name: dat_discharge_stream_YRZ_YHZ_2010_2021_daily.csv</li> <li>Note: The data is at daily basis but also available at 15-min high frequency basis, which can be requested from the authors.</li> </ul> <p>2. Nitrate concentration in the streams from 2011 to 2019 at both YRZ and YHZ_Q sites.</p> <ul> <li>File name: dat_nitrate_stream_YRZ_YHZ_2011_2019_daily.csv</li> <li>Note: The data is at daily basis but also available at 15-min high frequency basis, which can be requested from the authors.</li> </ul> <p>3. Water quality data in the inflows from 2010 to 2021 at biweekly basis, from YRZ and YHZ_WQ sites.</p> <ul> <li>File name: dat_waterquality_stream_YRZ_YHZ_2010_2021_biweekly.csv</li> <li>Note: The data is at biweekly basis, measured at the depth of 0.5m under water surface, from both probe and lab.</li> </ul> <p>4. Water quality data in the predams from 2010 to 2021 at biweekly basis, from YR1 and YH1 sites.</p> <ul> <li>File name: dat_waterquality_predams_YR1_YH1_2010_2021_biweekly.csv</li> <li>Note: The data is at biweekly basis, measured at the depth of 0.5m under water surface, from both probe and lab.</li> </ul> <p>5. Water quality data in the predams from 2010 to 2015 at biweekely basis, from YR3 and YH3 sites.</p> <ul> <li>File name: dat_waterquality_predams_YR3_YH3_2010_2015_biweekly.csv</li> <li>Note: The data is at biweekly basis, measured at various water depth, only from lab.</li> </ul> <p>6. CTD and BBE probe profile data in the predams from 2010 to 2015 at biweekely basis, from YR3 and YH3 sites.</p> <ul> <li>Note: Data stored in the folder "probe_profiles_predam_YR3_YH3_2010_2015_biweekly". The data is at biweekly basis, measured at various water depths. The measurements include water temperature (Celcius), DO (mg/L), Chl-a (mg/m3), bluegreen, green and diatom (all in Chl-a, mg/m3)</li> </ul>
Data Set for "Alteration's control on frictional behavior and the depth of the ductile shear zone in geothermal reservoirs in volcanic arcs" I: Lesser Antilles Volcanic Arc
<p>Data set for the 48 friction experiments performed for gouge samples (altered andesitic rocks) from the Lesser Antilles used in the manuscript, "Alteration's control on frictional behavior and the depth of the ductile shear zone in geothermal reservoirs in volcanic arcs". This data set can be used in combination with the data set for the Cascades used in the same manuscript (doi:10.5281/zenodo.10964936). This large combined data set (of 108 frictional experiments) represents a unique opportunity to systematically study frictional behaviour in the framework of rate and state. All samples are tested in wet and dry conditions at 10, 30, and 50 MPa with velocity steps and slide-hold-slides. These two data sets have the further advantage of being performed with exactly the same protocol (same run in, same initial gouge thickness, same velocity steps, same hold periods), in the same machine, by the same operator (or by an operator who was trained and supervised by the original operator). </p>
IN02054 Water Reservoir Inscription of Amsuvarma. Sanskrit XML file, draft epidoc edition
<p>IN02054 Water Reservoir Inscription of Amsuvarma. Sanskrit XML file (without metadata). Draft epidoc edition to be incorporated into 'Siddham' archive</p>
Global Reservoir Geometry Database
<p>This is a global-scale reservoir storage-area-depth dataset including 6,824 major reservoirs. For each reservoir, the storage-area-depth relationships were derived from an optimal geometric shape selected iteratively from five possible regular geometric shapes that minimizes the error of total storage and surface area estimation. This algorithm has been applied to 6,800 reservoirs included in the Global Reservoir and Dam database (GRanD). The relative error between the estimated and observed total storage is no more than 5% and 50% for 66% and 99% of all GRanD reservoirs, respectively. More importantly, the storage-depth profiles derived from the approximated reservoir geometry compared well with remote sensing based estimation at 40 major reservoirs from previous studies, and ground-truth measurements for 34 reservoirs in the United States and China.</p>
Roles of irrigation and reservoir operations in modulating terrestrial water and energy budgets in the Indian sub-continental river basins
<p>We have simulated water budget and energy budget over Indian subcontinental basins, using three scenarios from the Variable Infiltration Capacity (VIC) model by including irrigation and reservoir practices in it:</p> <p>1). No irrigation and reservoir (VIC-NATURAL)<br> 2). Free irrigation and no reservoir (VIC-FREE)<br> 3). Reservoir and restricted irrigation (VIC-MANAGED)</p> <p>Here, we have shared results in below folders.</p> <p>Fig1: Annual precipitation (P) and reservoir locations used in study.<br> Fig2: Satellite (MODIS and GLEAM) based annual evapotranspiration (ET) and VIC-MANAGED simulated annual ET.<br> Fig3: Annual land surface temperature (LST) from MODIS, AATSR and VIC-MANAGED.<br> Fig4: Mean monthly observed and simulated reservoir storage.<br> Fig5: P, ET, total runoff (TR) and LST from one grid.<br> Fig6: Annual ET change between VIC-NATURAL and VIC-MANAGED run.<br> Fig7: Same as Fig6 but for TR.<br> Fig8: Same as Fig6 but for LST.<br> Fig9: Annual ET change between VIC-FREE and VIC-MANAGED run.<br> Fig10: Annual latent heat flux and sensible heat flux change between VIC-NATURAL and VIC-MANAGED run.</p> <p>More detail is available in "Roles of irrigation and reservoir operations in modulating terrestrial water and energy budgets in the Indian sub-continental river basins" paper in JGR-Atmosphere. Or contact at harsh.lovekumar.shah@iitgn.ac.in</p> <p>Harsh Shah</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.