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5,371 results for “Flow”
Data from: Independently evolved and gene flow‐accelerated pesticide resistance in two‐spotted spider mites
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Data for: Amazonian birds in more dynamic habitats have less population genetic structure and higher gene flow
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Data from: Inversions dominate evolution in the European Sardine (Sardina pilchardus) amid strong gene flow
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Flows of invasive ants worldwide to the United States
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Data from: Understanding species boundaries that arise from complex histories: Gene flow across the speciation continuum in the spotted whiptail lizards
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Data for: Water system simulation modeling with hydropower optimization and environmental flows: An example with Pywr
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Time-varying flow-ecology relationships for an endangered fish population: Longfin Smelt in the San Francisco Estuary
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Data and scripts for the colour analysis from: Gene flow throughout the evolutionary history of a colour polymorphic and generalist clownfish
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Data for: Parameter selection and optimization of a computational network model of blood flow in single-ventricle patients
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The Influence of Flow on Creek Chub (Semotilus atromaculatus) Movement in an Intermittent Urban Headwater Stream
Fish movement in freshwater streams is often tied to patterns of flow, especially when the stream is intermittent, flashy, or some combination thereof. This relationship between flow and fish movement is exacerbated in small urban streams in impervious surface-dominated watersheds that lead to extreme flow conditions. This study focused on the response of Creek Chub (Semotilus atromaculatus), a common pioneer fish species in eastern North America, to flow events of various sizes in a small intermittent urban headwater stream. Our primary goals were to determine 1) the level of Creek Chub movement occurring in an intermittent headwater stream, 2) the influence of flow on movement direction and magnitude, 3) the degree of variation in individual movement behavior, and 4) mortality rates in the system. The study used PIT tagging and telemetry surveys to monitor Creek Chub movement over a six-month period. We found that individual Creek Chub in our study system were generally mobile (71%), but usually moved short distances only; however, a few individuals moved much farther, with a maximum single movement of 521 m. Moderate or major flow events increased the probability and magnitude of Creek Chub movement, and neither upstream nor downstream movement was favored. Movement was variable among individual fish and fish were able to respond to large and small flow events to move among habitats. Finally, we observed relatively high, but episodic, mortality in our study site, potentially related to pollution events. Evidence of elevated mortality emphasizes the importance of movement in highly disturbed streams, as it may enable recolonization after local extirpation.
Dataset on sub-daily vertical profiles of physicochemical parameters and chlorophyll concentration in El Val reservoir, together with its daily meteorological data, storage state and downstream flow (2018-2022).
This dataset contains the physicochemical parameters and chlorophyll concentration of El Val reservoir (province of Zaragoza, Spain), together with its meteorological conditions, the water level, the stored volume and the flow rate of the effluent, the Queiles River, a few meters downstream of the dam. These data are useful to feed deterministic, data driven or hybrid hydrological models with different purposes, like the identification of the impact of meteorological conditions on the physicochemical properties of the reservoir, like the thermal stratification, as well as the assessment of different management strategies in the reservoir. The original data were collected by the Confederación Hidrográfica del Ebro (CHE) and were published in real time through the web page of the Ebro Automatic Water Quality Information System (SAICA Ebro by its initials in Spanish) and the Ebro Automatic Hydrographic Information System (SAIH Ebro by its initials in Spanish). Then, the CHE curated the data that are finally available to the citizens under request by variable and date. In order to facilitate their availability and reuse, these data have been gathered, pre-processed and packaged in the form of datasets. Specifically, they are structured in four data tables: vertical profiles of physicochemical data in the reservoir, meteorological data in the same basin, water level and stored water volume in the reservoir and water flow rate of the Queiles River downstream of the reservoir.
Phosphorus concentrations and flow data, Old Woman Creek, Ohio, 2015-2023
The Old Woman Creek National Estuarine Research Reserve is located in Huron, Ohio (USA), along the southern shore of Lake Erie. Old Woman Creek is a fourth order stream that flows through a 0.6 km² wetland complex during its last 2 stream km, and surface connectivity between the stream and lake is mediated by a barrier sand beach that can open and close depending on flow, wind, waves, and precipitation. The Reserve has been measuring water quality in Old Woman Creek since 1980. Data presented in this package represent a small part of this long-term monitoring used in the study by Anderson et al. (2024, http://dx.doi.org/10.2139/ssrn.4947733) titled "We know less about phosphorus retention in constructed wetlands than we think we do: A quantitative literature synthesis". This study aims to identify gaps in our collective understanding of structural wetland features, monitoring methods, and long-term trajectories in restored and constructed wetlands. It uses the Old Woman Creek data presented in this data package to test different sampling frequencies to determine how sampling approach affects observed trends in total phosphorus loading. The data in this package include total phosphorus concentrations collected at the Inlet and Outlet of Old Woman Creek between 2015 and 2023. Total phosphorus concentrations were collected between 1 and 3 times per day at the Inlet and once per day to once per week at the Outlet, depending on streamflow. Additionally, flow data measured at 15-minute intervals at the stream Outlet between 2020 and 2023 are also included. This Outlet flow data corresponds well with flow measurements made by the United States Geological Survey (USGS) at the stream Inlet. While the Inlet flow data is not included in this package, it was used in the study by Anderson et al. (2024) and can be obtained from USGS's website by searching for gauge number 04199155. Additional data from the Old Woman Creek National Estuarine Research Reserve long-term water qualit
Sitka Debris Flow Inundation Model
This raster file contains the results of a debris flow inundation model that simulated 100,000+ debris flows from potential initiation sites across an area near Sitka, AK. Initiation locations were selected based on a landslide initiation susceptibility raster, and calibrated to debris flows which were triggered during a 2015 storm. Results were smoothed using a 50 meter gaussian filter.
Sap Flow in the Soil Freezing Study at the Hubbard Brook Experimental Forest, 2010
The climate is changing in many temperate forests with the amount of forest area dominated by sugar maple experiencing an insulating snowpack expected to shrink between 49 and 95% compared to 1951-2005 values. A reduced snowpack and increased depth and duration of soil frost can injure fine roots, which are essential for plant water uptake. Water uptake is a crucial component of ecosystem functioning because this process strongly impacts other biological processes, such as primary productivity and nutrient uptake. We evaluated the effects of changing winter climate, including snow and soil frost dynamics, by measuring sap flow rates in the Soil Freezing Study plots at the Hubbard Brook Experimental Forest. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station. Analysis of these data are published in: Harrison, J.L., Reinmann, A.B., Maloney, A.S. et al. Transpiration of Dominant Tree Species Varies in Response to Projected Changes in Climate: Implications for Composition and Water Balance of Temperate Forest Ecosystems. Ecosystems (2020). https://doi.org/10.1007/s10021-020-00490-y
Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Forest: Sap Flow
Sap flow was measured on all Climate Change Across Seasons Experiment (CCASE) plots. There are six plots total (each 11 x 14m). Two are warmed 5 degrees C throughout the growing season (Plots 3 and 4). Two others are warmed 5 degrees C in the growing season and have snow removed during winter to induce soil freezing and then warming cables turn on to create thaws; Each soil freeze/thaw cycles includes 72-hours of soil freezing followed by 72-hours of thaw (Plots 5 and 6). Four kilometers (2.5 mi) of heating cable are buried in the soil to warm these four plots. Two additional plots serve as controls for our experiment (Plots 1 and 2). This data set includes sap flow measurements for 2015 and 2017 growing seasons. These sap flow data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Ecosystem-Scale Rainfall Manipulation in a Piñon-Juniper Forest at the Sevilleta National Wildlife Refuge, New Mexico: Sap Flow Data (2006-2013)
Climate models predict that water limited regions around the world will become drier and warmer in the near future, including southwestern North America. We developed a large-scale experimental system that allows testing of the ecosystem impacts of precipitation changes. Four treatments were applied to 1600 m2 plots (40 m × 40 m), each with three replicates in a piñon pine (Pinus edulis) and juniper (Juniper monosperma) ecosystem. These species have extensive root systems, requiring large-scale manipulation to effectively alter soil water availability.  Treatments consisted of: 1) irrigation plots that receive supplemental water additions, 2) drought plots that receive 55% of ambient rainfall, 3) cover-control plots that receive ambient precipitation, but allow determination of treatment infrastructure artifacts, and 4) ambient control plots. Our drought structures effectively reduced soil water potential and volumetric water content compared to the ambient, cover-control, and water addition plots. Drought and cover control plots experienced an average increase in maximum soil and air temperature at ground level of 1-4° C during the growing season compared to ambient plots, and concurrent short-term diurnal increases in maximum air temperature were also observed directly above and below plastic structures. Our drought and irrigation treatments significantly influenced tree predawn water potential, sap-flow, and net photosynthesis, with drought treatment trees exhibiting significant decreases in physiological function compared to ambient and irrigated trees.  Supplemental irrigation resulted in a significant increase in both plant water potential and xylem sap-flow compared to trees in the other treatments. This experimental design effectively allows manipulation of plant water stress at the ecosystem scale, permits a wide range of drought conditions, and provides prolonged drought conditions comparable to historical droughts in the past – drought events for w
Characterizing the groundwater flow pathways and recharge sources of a desert inter-dune aquifer system by geophysical approaches and multiple isotopes (B, H and O)
<p>Major cations and anions, and H, O, and B isotope data of South Sumujaran Lake of Badain Jaran Desert, China</p>
RCP8.5-ECEARTH-RACMO-LARSIM_ME Climate Flow Projection Data for German Waterways
<p>The datasets provided here were produced as part of the IMPREX project for work package 4, task 4 „<em>Improving prediction on the climate scale</em>“ and work package 9, task 3 “<em>Case studies</em>”. Analysis of the datasets are published in Deliverable 4.4 „<em>Estimation of hazards based on improved representation of highly vulnerable water resources of strategic importance on the climate scale</em>“ (Falloon et al 2019). The aim was to study the impact of internal climate model variability and bias correction method on the climate change signal of relevant flow indicators for the German waterways Rhine, Elbe and Danube.</p> <p>To assess the impact of internal variability of the global climate model on future changes of flow, precipitation, temperature and global radiation of the 16-member ensemble generated with the RCM KNMI-RACMO2 driven by the GCM EC-EARTH 2.3 provided by WP3 of IMPREX were used. EC-EARTH was run 16 times from 1850 to 2100, each member starting from a slightly different initial state, under forcing of historical emissions until 2005 and the RCP8.5 greenhouse gas concentration pathway from 2006 onwards. Each of the EC-EARTH members was subsequently dynamically downscaled using KNMI-RACMO2 on a 0.11° (~12 km) resolved domain (Aalbers et al. 2018).</p> <p>To correct the systematic model biases of climate models different bias correction methods were applied: (1) no bias correction, (2) linear scaling (Lenderink et al. 2007) and (3) quantile-quantile mapping (Piani et al. 2010). Bias correction relationships were derived for five-day periods (for each variable and location, in total 73 bias correction relationships were derived) including 13 days before and after the considered five-day period (total window size was 31 days) from the observations and values of the regional climate simulations. The period used to estimate the bias correction relationships was 1971-2000.</p> <p>The hydrological model applied is called LARSIM-ME (ME – MittelEuropa = Central Europe) and is based in the model software LARSIM (Large Area Runoff SImulation Model) originally developed by Ludwig & Bremicker (2006). LARSIM-ME covers the catchments of the rivers Rhine, Elbe, Weser/Ems, Odra and Upper Danube. The total catchment size simulated by the model is approximately 800,000 km². The spatial resolution is 5 km x 5 km and the computational time-step is daily. As observed meteorological forcings, precipitation, air temperature and global radiation from the HYRAS data set (Rauthe et al. 2013) available for the 5 km x 5 km model grid and the period 1951-2015 were used. The hydrological model was calibrated using the automatic calibration scheme Shuffled Complex Evolution SCE-UA algorithm (Duan et al. 1994). For more details about the model see Meißner et al. (2017).</p> <p>The meteorological variables air temperature, precipitation and global radiation produced by the KNMI RACMO-EC-EARTH 16 member ensemble (period 1951-2100) were interpolated to a 25 km x 25 km grid and afterwards bias corrected with respect to the observation data (HYRAS) used for calibration of the hydrological model LARSIM. From this 25 km x 25 km grid the bias corrected variables were downscaled to the 5 km x 5 km model grid of LARSIM using monthly background climatology fields on the 5 km x 5 km target grid of the HYRAS dataset. The bias-corrected and downscaled data was then used as meteorological forcing of LARSIM to calculate flow projections for the rivers Rhine, Elbe and Upper Danube (up to the German/Austrian border).</p> <p><strong>Dataset Q_OBS_DE.nc:</strong></p> <p>Mean daily observed flow of the gauges Kaub, Koeln, Ruhrort / Rhine, Pfelling, Hofkirchen / Danube, Desden, Magdeburg Strombruecke, Neu-Darchau / Elbe for the period 1951–2017 stored as variable <em><strong>q_obs(time=24472, stations=8)</strong></em>.</p> <p>Data originate from the database of gauge measurements of the Federal Waterways and Shipping Administration (WSV). These data were quality checked and published by the gauge-operating WSV offices. Nevertheless, data errors and inconsistencies cannot be ruled out completely, so that neither the WSV nor the BfG do accept any liability for the correctness and completeness of the data. Data source: "German Federal Waterways and Shipping Administration (WSV)", provided by the German Federal Institute of Hydrology (BfG)</p> <pre><code>float q_obs(time=24472, stations=8); :units = "m3/s"; :_FillValue = -9999.0f; // float :long_name = "observed streamflow"; :coordinates = "lat lon";</code></pre> <p><strong>Dataset Q_HYRAS_LME.nc:</strong></p> <p>Mean daily simulated flow of the hydrological model LARSIM-ME forced by observed meteorology from the HYRAS dataset stored as variable <em><strong>q_sim (time=23741, stations=8)</strong></em>. Period 1951-2015, Gauges Kaub, Koeln, Ruhrort / Rhine, Pfelling, Hofkirchen / Danube, Desden, Magdeburg Strombruecke, Neu-Darchau / Elbe.</p> <pre><code>float q_sim(time=23741, stations=8); :units = "m3/s"; :_FillValue = -9999.0f; // float :long_name = "simulated streamflow"; :coordinates = "lat lon";</code></pre> <p><strong>Q_RCP85_ECEARTH_RACMO_[bc]_LME.nc:</strong></p> <p>Mean daily projected flow of the hydrological model LARSIM-ME forced by 16 realizations of RCP8.5-ECEARTH-RACMO stored as variable <em><strong>q_sim(time=54787, realization=16, stations=8)</strong></em>, first dimension time, second dimension realization and third dimension stations. Bias correction of meteorological forcings [bc]: NOBC: no bias correction, LS: linear scaling, QQMAP Quantile-Quantile Mapping. Period 1951-2100, Gauges Kaub, Koeln, Ruhrort / Rhine, Pfelling, Hofkirchen / Danube, Desden, Magdeburg Strombruecke, Neu-Darchau / Elbe.</p> <pre><code>float q_sim(time=54787, realization=16, stations=8); :units = "m3/s"; :_FillValue = -9999.0f; // float :long_name = "projected streamflow"; :coordinates = "lat lon";</code></pre> <p><strong>Literature</strong></p> <p>Aalbers, E. E., G. Lenderink, E. van Meijgaard & B. J. J. M. van den Hurk (2018): Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability? Climate Dynamics 50(11), 4745-4766</p> <p>Duan, Q., S. Sorooshian & V. K. Gupta (1994): Optimal use of the SCE-UA global optimization method for calibrating watershed models. Journal of Hydrology 158(3–4), 265-284</p> <p>Falloon, P., K. Williams, J. Andreu, A. Solera, S. Suárez-Almiñana, B. Klein, D. Meissner, J. Hunink, J. Eekhout & J. de Vente (2019): Estimation of hazards based on improved representation of highly vulnerable water resources of strategic importance on the climate scale. Deliverable 4.4, IMPREX - Improving Predictions of Hydrological Extremes - Grant Agreement Number 641811, <a href="https://imprex.eu/system/files/generated/files/resource/imprex-deliverablereport-d4-4-final-1.pdf">https://imprex.eu/system/files/generated/files/resource/imprex-deliverablereport-d4-4-final-1.pdf</a></p> <p>Lenderink, G., A. Buishand & W. van Deursen (2007): Estimates of future discharges of the river Rhine using two scenario methodologies: direct versus delta approach. Hydrology and Earth System Sciences 11(3), 1143-1159</p> <p>Ludwig, K. & M. Bremicker (2006): The Water Balance Model LARSIM –Design, Content and Applications. 22. C. Leibundgut, S. Demuth and J. Lange (Eds), Freiburger Schriften zur Hydrologie, Institut für Hydrologie, Universität Freiburg im Breisgau, Freiburg, 141 pp.</p> <p>Meißner, D., B. Klein & M. Ionita (2017): Development of a monthly to seasonal forecast framework tailored to inland waterway transport in central Europe. Hydrol. Earth Syst. Sci. 21(12), 6401</p> <p>Piani, C., J. O. Haerter & E. Coppola (2010): Statistical bias correction for daily precipitation in regional climate models over Europe. Theoretical and Applied Climatology 99(1-2), 187-192</p> <p>Rauthe, M., H. Steiner, U. Riediger, A. Mazurkiewicz & A. Gratzki (2013): A Central European precipitation climatology - Part I: Generation and validation of a high-resolution gridded daily data set (HYRAS). Meteorologische Zeitschrift 22(3), 235-256</p>
Model data for "Flow Separation and Increased Drag Coefficient in Estuarine Channels with Curvature"
<p>These are the model data we generated using ROMS and analyzed for the journal article "Increased Drag Coefficient in Estuarine Channels with Curvature". Files include 8 sinuous channel models and 2 straight channels. sinuous_channel_1.nc and straight_channel_1.nc are the pair of models analyzed in section 3. sinuous_channel_1_avg.nc and straight_channel_1_avg.nc are the one-hour average result. sinuous_channel_2_avg.nc and straight_channel_2_avg.nc are the pair of deep channel models. sinuous_channel_3_avg.nc and others are the other different sinuous channel models.</p>
Supporting Datasets produced in Allen et al. (2020) Timing of Landsat Overpasses Effectively Captures Flow Conditions of Large Rivers
<p><strong>Supporting Datasets produced in Allen et al. (2020) Timing of Landsat Overpasses Effectively Captures Flow Conditions of Large Rivers </strong></p> <p>Published in <em>Remote Sensing </em>(DOI coming soon)</p> <p><strong>Description:</strong></p> <p>These CSV tables contain daily discharge data of large rivers measured by USGS gauges. We used overpass timing and cloud cover information for Landsat 5, 7, and 8 over a 35-year study period. Code that was used to produce, process and analyze these data can be found in the following code repository: <a href="https://github.com/geoallen/ROTFL">https://github.com/geoallen/ROTFL</a></p> <p><strong>About the data:</strong></p> <p>Each column contains data from an individual gauge. The column name is the USGS gauge number. If the gauge number (column name) is 7 digits, it is understood that the number begins with a zero (all gauge numbers are 8 digits; this is only important if you are re-downloading data). </p> <p>All tables are equal dimensions. The position of a discharge measurement in the DischargeValues table can be used to look up it’s date recorded/qualification code in the Dates and Codes tables as every row-col combination refers to the same measurement. </p> <p>Measurements span data range: 1984-01-01 to 2019-08-13 <br> DischargeValues = Discharge recorded in cubic feet per second <br> DischargeDates = Unix date that discharge measurement was recorded on. <br> DischargeCodes = Daily Value Qualification Code </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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.