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182 results for “Hydrological Data”
Terrestrial water data synthesis for hydrological catchments around the world in the Anthropocene
<p>We here synthesise hydro-climatic data reported by previous studies for 65 hydrological catchments around the world [1-7] for further meta-analysis of how water fluxes of precipitation (P), runoff (R), and actual evapotranspiration (ET) on land change in the Anthropocene epoch, from before to after its start in the 1950's [8]. These water flux changes alter how much water ends up sustaining crops and other plants (evapotranspiration) and how much remains for the lateral water flows (runoff) through the landscape and the societal water uses and ecosystems they support. How this partitioning changes as integral part of global change is key for water and food security, and life on land and below water around the world’s land areas and coasts. </p> <p>To distinguish the impacts of direct human drivers on evapotranspiration and runoff changes based on instrumental data for wide-ranging water, human-activity and climate conditions around the world, the 65 study catchments are divided in two comparative sets. One set includes 52 large catchments, selected from two previous data compilations and studies [1,2] and is in the data files referred to as the world set of catchments. The study periods are 1901–2008 for 21 [2] and 1930–1979 for the other 31 [1] of these catchments. The second set includes 13 catchments selected from previous studies [3-7] of both the water flux changes and associated dominant human drivers of these for time periods that are largely consistent with those for the world set of catchments (within 1901-2016); this is in the data files referred to as the known human-shifted set of catchments. The dominant direct human drivers of water-flux changes in these catchments include expanded/intensified rainfed agriculture (RA), irrigated agriculture (IA), or dams and reservoirs for engineered flow regulation (FR), as listed and cited for each known human-shifted catchment in the data files. </p> <p>For each study catchment, we have quantified and report in the data files long-term average P, R and ET values over the total study period and changes in period-average values between two subperiods within it. The subperiods are 1901–1954 and 1955–2008 for 21 [2], and 1930–1954 and 1955–1979 for the other 31 [1] world catchments, and largely consistent for the known human-shifted catchments [3-7] (as listed in the data files). Each study catchment is also classified as water or energy limited by quantifying the associated Budyko-based aridity index PET/P, where PET is potential evapotranspiration. Average PET is estimated as PET≈325+21T+0.9T<sup>2</sup> where T is long-term annual and catchment average surface temperature in °C, calculated from monthly temperature data in the previous catchment studies [1-7]. The resulting PET/P index classifies actual ET/P in each catchment as energy limited for average PET/P < 1 or water limited for average PET/P > 1, as listed in the data files.</p> <p>Other catchment information included in the data files, uploaded in both pdf and xlsx formats, include source references, catchment name, area and station ID and continent and latitude location. Overall, this dataset provides a wide-ranging sample of catchment-wise related, water balance-constrained local-regional changes in average P, R and ET under major RA, IA, FR developments (known for the second human-shifted set of catchments [3-7]) and various other human-activity and climate developments around the world from before to after the Anthropocene start in the 1950’s [8]. </p>
FISHPASS ASSESSMENT PLAN LONG-TERM MONITORING OF HYDROLOGIC AND WATER QUALITY DATA
The Great Lakes Fishery Commissions’ (GLFC) FishPass project seeks to reconnect the waterscape for only desired species (i.e., selective passage) by integrating a multitude of existing and novel passage techniques and technologies. The probability of a fish passing through a sorting system is dependent on environmental conditions and a fish’s motivation ─ its internal state in relation to environmental stimuli. While fish decision making abilities introduce complexity to the sorting operations, they also provide an opportunity to exploit behavioral tendencies and abilities to achieve selective sorting. The FishPass Assessment Plan details a monitoring program aimed at quantifying fish movement and sorting capabilities associated with both individual mechanisms and integrated sorting systems. The results of the monitoring program will be used to inform future adjustments to the selection of techniques and technologies and their configuration to optimize passage of desirable species while blocking and/or removing undesirable species. A key component to the Assessment Plan is the long-term monitoring of abiotic variables in and around FishPass. This data set contains the hydrologic (e.g., river discharge, water level) and water quality data (e.g., temperature, specific conductivity, conductivity, and turbidity) collected at mostly static stations throughout the Boardman/Ottaway River. The dataset is updated annually. These data are collected until the initiation and/or substantial completion of the FishPass structure. Collection of this type of data are expected to continue after FishPass construction completion but modifications to the extent and location of monitoring stations are anticipated. As a result, a new dataset will be updated in the future containing all long term hydrologic and water quality monitoring post construction. R. Swanson, GLFC Assessment Biologist, is primarily responsible for maintaining the monitoring equipment, data retrieval, quality assuran
Summer 2016 hydrology and water chemistry data at Second Creek, a sulfate-impacted riparian wetland in northeast Minnesota
Hydrological and water chemistry data were collected at Second Creek, a riparian wetland study site near Aurora, MN, to understand sulfur and methane processes. Data were collected over the summer of 2016. Hydrological data were collected using temperature probes and pressure transducers installed in surface water gauges and shallow piezometers. Water chemistry was analyzed in surface water samples and porewater samples collected with “peepers” (passive diffusive samplers).
Effects of Hurricane Opal on foliar chemistry and insect herbivores at the Coweeta Hydrologic Laboratory in 1997: foliar chemistry data
Hurricane damage results in tree mortality and variation in both light and nutrient availability for the individuals that remain. In turn, resource availability influences the interactions between plants and insect herbivores. We report effects of Hurricane Opal on the phenolic chemistry and levels of defoliation on surviving trees at the Coweeta Hydrologic Laboratory in North Carolina. We measured foliar astringency, hydrolysable tannins, and condensed tannins in the foliage of red maple and red oak saplings in hurricane damaged and undamaged sites. We estimated inorganic nitrogen and phosphorus availability in the soil, and the accumulated leaf area removed by insect herbivores. The foliar astringency of both red maple and red oak was higher in sites damaged by the hurricane. Later in the growing season, condensed tannin levels were significantly higher in the foliage of red oak in damaged sites. There were no consistent differences in ammonium, nitrate, or phosphate availability between damaged and undamaged sites. Despite higher foliar astringency of trees in sites damaged by Hurricane Opal, levels of defoliation by insect herbivores were higher in damaged than in control sites on both tree species. Apparent increases in putative defensive compounds following hurricane damage did not protect trees from herbivory.
Soil respiration and precipitation data at resin bag sites on canopy gradient sites at the Coweeta Hydrologic Laboratory in 1998 (dataset 1056)
We tested whether inputs from canopy herbivores would affect soil processes such as respiration, nutrient cycling, and decomposition along an elevation gradient. The five treatments we used were frass additions, throughfall additions, removal of all litter that fell during the study, removal of greenfall that fell during the study, and controls. Soil respiration was significantly reduced on low and mid elevation sites in litter exclusion, greenfall exclusion and throughfall addition treatments (from 0.846 g CO2/m2/h for controls to 0.618, 0.667, and 0.708 g CO2/m2/h, respectively, for the three treatments).
Riparian study: hourly microclimate data from the Coweeta Hydrologic Laboratory from 1994 to 2007
This data set contains air temperature and soil temperature data from the control (hurricane) slope and treatment (manual rhododendron removal) slope on watershed 56 at Coweeta Hydrologic Laboratory. The arrays of thermocouple sensors are arranged along transects that are parallel to the stream channel and 1, 5, and 15 m uphill for each slope. Data were collected from 1994 to 2007 when dataloggers were removed.
Litter decomposition data from the Coweeta Hydrologic Laboratory from 1993 to 1995
Litter bags (5 X 5 cm, 1mm nylon mesh) were filled with 5 0.2 g of air dried litter from R. maximum or Q. prinus (two dominant tree species in the watershed). The bags were then placed upon the soil surface along transects 1, 5, and 15 meters upslope from the stream (as described for microbial C and N). Bags were placed in the field in December, 1993. Three replicate bags of each litter type were collected from both sites and all transects, every three months. Upon retrieval, leaves were dried and cleaned of any residual soil particles. Samples were then weighed to determine percent weight loss, over time. In these data files, litter decomp studies are saved by species (Q. prinus or R. max) and then by distance from the stream (1, 5, or 15 meters). The # of days column is the amount of time the bags were in the field. % weight remaining is> the proportion of weight upon collection to initial weight. This is followed by the average % weight remaining for each collection date and its standard deviation. The average C/N is the C/N ratio for the litterbags, by collection date. The total C and N for litter was determined using the Carlo Erba Total C and N analyzer.
Riparian zone seedling establishment, growth, dynamics, and the influence of Rhododendron maximum soil moisture: forest floor data at the Coweeta Hydrologic Laboratory from 1997 to 2000
The effect of Rhododendron maximum, a dominate species in the riparian zones of the Southern Appalachians, on carbon, water, and nutrients en route to the streams is an ongoing study in the LTER research program at Coweeta Hydrologic Laboratory. To study seedling establishment, growth, and dynamics in riparian zones one m2 quadrats have been established. There are four sites which include one treatment site, where the rhododendron has been removed from the riparian zone, one hurricane site, where there is extensive disturbance from Hurricane Opal, and two control sites, one upslope from the treatment site and one upstream from the hurricane site. Each of these fours sites have ten randomly located natural regeneration one m2 quadrats as well as four randomly located replicates of three adjacent one m2 quadrats. In each of the three adjacent quadrats, the litter was removed from the lower half to determine the effect of litter on the germination and growth of seedlings. Two of the adjacent quadrats have been broadcast seeded with Acer rubrum, Liriodendron tulipifera, and Quercus rubra. In one of the two quadrats that have been broadcast seeded, a predator exclusion mesh screen, 1m x 1/2m with " openings, has been installed in the quadrat to determine the effect of small mammal predation on regeneration. Quadrats were installed on 24 April 1997 and an initial vegetation survey was conducted in May 1997. All seedlings were permanently tagged at this time and quadrat physical characteristics such as slope, aspect, and distance from stream were recorded. Broadcast seeding was done on 21 May 1997. Each year censuses will be conducted in spring and fall on each quadrat and seedling species, density, age, and annual height growth will be recorded. This project will help to document the effect of Rhododendron maximum on regeneration in the riparian areas as well as the effect of hurricane disturbance on regeneration.
Riparian study: soil water chemistry (lysimeters) yearly data (1993 to 1997) at the Coweeta Hydrologic Laboratory
These measurements are a part of a near-stream vegetation manipulation experiment conducted on WS 56 at Coweeta. The purpose of the project is to determine the effect of removal of streamside Rhododendron maximum on the export of nutrients and organic matter, on microbial community function, on downslope coarse woody debris transport, on seedling regeneration, and on microclimatic variables such as soil temperature and soil moisture. Two experimental hillslope transects that span topographic flowpaths from a local highpoint to the stream were instrumented with lysimeters in two soil horizons, the BA (20-25 cm deep) and the B (40-50 cm deep). The vegetation cut was conducted on the "treatment slope" in Aug 1995. Shortly thereafter, Oct 1995, hurricane Opal blew down a significant number of canopy trees on the "control slope." Due to this natural disturbance, the project was adjusted to contrast the effects of natural vs human disturbance - a bank of lysimeters above the cut area was unaffected and now serve as the control data for the project. The treatment slope has been renamed the "cut slope" and the hurricane impact slope has been renamed the "storm slope." The project uses a terrain-fitted hillslope hydrology model (TAPES-C, IHDM4 hybrid) to account for water flux and nutrient loading from the hillslope before and after the cut and storm impacts.
Ecology and Evolutionary Biology Field Trip at the Coweeta Hydrologic Laboratory (Watershed 18) in 2004: Aquatic Invertebrates (Adult) data
As part of an educational project, we intend to conduct a short "bioblitz" that will focus on 4 major groups of organisms: (1) vertebrates, especially birds and salamanders; (2) the local flora, especially fungi, trees, and any herbaceous species present this early; (3) aquatic invertebrates; (4) terrestrial invertebrates. Data will be compared to available lists of taxa from Coweeta and Great Smoky Mountains National Park.
DC2 High resolution future hydrological data for Sweden
<p>Hourly river flow and total runoff were computed for the southern part of Sweden using the hourly version of a high resolution hydrological model S-HYPE, which is operationally used by SMHI. The model was calibrated and validated using radar based hourly precipitation and an operationally used hourly reanalysis temperature data. Projection of the impact of climate change was performed by running the model with hourly forcing data from an ensemble of EURO-COREX climate model simulations over 1971 - 2100. Four GCM-RCM combinations were used under two emission scenarios, RCP4.5 and RCP8.5. The results can be used to assess the risk of riverine flooding in areas located along a small to meso-scale river basin. The results can, in particular, be used to assess the risk of flash flooding that can result from heavy precipitation of short duration.</p>
Hydrological controls of slope response to precipitation - Code and Data
<p>This repository contains the dataset and codes used in the study of sloping soil response to precipitation through machine learning analysis. The dataset includes synthetic data of precipitation, soil moisture, and groundwater level mimicking field observations conducted in a experimental field. The codes include scripts for data preprocessing, analysis, and visualization. Here you will find: The dataset used to build a random forest (RF) model (01_RF_dataset.csv), the script for building the model (01_RF_model.py) using the sciki-learn library in Python (<a href="https://scikit-learn.org/stable/index.html">https://scikit-learn.org/stable/index.html</a>), the dataset for the cluster analysis (SyntheticData.mat) and the script for the analysis using the k-means clustering technique implemented in Matlab (<a href="https://it.mathworks.com/help/stats/kmeans.html">https://it.mathworks.com/help/stats/kmeans.html</a>).</p><p>The data and the codes in the present repository are part of the research entitled "Understanding hydrologic controls of sloping soil response to precipitation through machine learning analysis applied to synthetic data", published in Hydrology and Earth System Sciences - HESS journal. More details can be found for now in the paper preprint: Roman Quintero DC, Marino P, Santonastaso GF, Greco R (2023). Understanding hydrologic controls of sloping soil response to precipitation through machine learning analysis applied to synthetic data. EGUsphere: 1-41. DOI: 10.5194/EGUSPHERE-2022-1078</p>
What can radar-based measures of subglacial hydrology tell us about basal shear stress? A case study at Thwaites Glacier, West Antarctica (Interpolated Data)
<p>This dataset accompanies the paper 'What can radar-based measures of subglacial hydrology tell us about basal shear stress? A case study at Thwaites Glacier, West Antarctica' in Journal of Glaciology, and can be used alongside the code found on Github (https://github.com/rohaizharis/inversion_radar2022) to reproduce the figures. The dataset consists of ice-penetrating radar data (specularity and relative reflectivity) and basal shear stress inversions that have been linearly interpolated onto radar flight tracks.</p>
Data for: Assessing hydrology, biogeochemistry and organic micropollutants in an urban stream-aquifer system: an interdisciplinary dataset
<p>Accompanying data for data article "Assessing hydrology, biogeochemistry and organic micropollutants in an urban stream-aquifer system: a comprehensive dataset" of Popp et al., JGR:Biogeosciences.</p> <p><br>In this repository, all data described in Table 1 of the manuscript can be found, except for the data already published by Popp et al., 2020, ES&T, doi: 10.1021/acs.est.9b05393. These data can be freely accessed in ERIC (Eawag Research Data Institutional Collection): doi.org/10.25678/0001JD. </p> <p>Data are structured the following way:<br>1_logger-data: time series of logger data (water temperature, water levels, electrical conductivity and pH [the latter only for the stream]) obtained at the stream Chriesbach and piezometers P1 and P4;<br>2_tracer-data: time series of nutrients, ions, and other tracer data obtained at the stream Chriesbach, the piezometers (P1, P4, P5) and the regional groundwater well (reg-gw); <br>3_micropollutant_data: time series of organic micropolluntants obtained at the stream Chriesbach, P1, P4, P5 and the regional groundwater well (reg-gw);<br>4_R-script: R script used for statistical analysis and to create the plots shown in the manuscript.</p> <p>Units, estimated uncertainties or other measures of uncertainty such as limits of quantification are provided in the respective files. Each subfolder contains its own readme file with relevant metadata. </p> <p>Coordinates (WGS84): <br>Location Latitude Longitude<br>Stream logger monitoring 47.404613 8.6113<br>Stream sampling 47.404459 8.607777<br>Piezometer 1 (P1) 47.4044 8.6080<br>Piezometer 4 (P4) 47.4044 8.6078<br>Piezometer 5 (P5) 47.404392 8.607619<br>Regional groundwater 47.40501 8.60822</p>
CESM2 land output data for study on hydrological impacts of large-scale forest expansion
<p>This repository contains the land output data from CESM2 which was generated in the study investigating the hydrological impacts of global-scale forestation. The datasets cover the period 2015-2100. The files are labelled according to the experiments they were generated from (base, MF (Max Forest) and No LULCC). Output fields are as follows:</p> <p>discharge_plus_runoff: surface water availability (river discharge plus surface runoff), units m^-3 s^-1</p> <p>EFLX_LH_TOT: total latent heat flux from land to atmosphere, units W m^-2</p> <p>QFLX_EVAP_TOT: total evapotranspiration (canopy evaporation plus canopy transpiration plus soil evaporation), units kg m^-2 s^-1</p> <p>SOILLIQ: soil liquid water content, units kg m^-2</p> <p>SW_surface_albedo: surface albedo, units fraction</p> <p>TSA: 2m air temperature, units K</p> <p>VEGWP: vegetation water potential, units m</p> <p> </p> <p>All data were generated and processed by James A. King.</p>
CESM2 atmosphere output data for study on hydrological impacts of large-scale forest expansion
<p>This repository contains the atmosphere output data from CESM2 which was generated in the study investigating the hydrological impacts of global-scale forestation, for the Max Forest scenario. The datasets cover the period 2015-2100. Output fields are as follows:</p> <p>CCN3: concentration of cloud condensation nuclei at 0.1% supersaturation, units cm^-3</p> <p>CLDLOW: cloud fraction integrated between 1200-700 hPa, units fraction of grid cell</p> <p>CONCLD: convective cloud cover, units fraction of grid cell</p> <p>GCLDLWP: grid cell cloud water path, units kg m^-2</p> <p>LWCF_d1: clean longwave cloud forcing, units W m^-2</p> <p>OMEGA: vertical velocity, units Pa s^-1</p> <p>PRECT: total precipitation, units m s^-1</p> <p>SWCF_d1: clean shortwave cloud forcing, units W m^-2</p> <p>V: meridional wind, units m s^-1</p> <p> </p> <p>All data were generated and processed by James A. King.</p>
CESM2 atmosphere output data for study on hydrological impacts of large-scale forest expansion
<p>This repository contains the atmosphere output data from CESM2 which was generated in the study investigating the hydrological impacts of global-scale forestation, for the base scenario. The datasets cover the period 2015-2100. Output fields are as follows:</p> <p>CCN3: concentration of cloud condensation nuclei at 0.1% supersaturation, units cm^-3</p> <p>CLDLOW: cloud fraction integrated between 1200-700 hPa, units fraction of grid cell</p> <p>CONCLD: convective cloud cover, units fraction of grid cell</p> <p>GCLDLWP: grid cell cloud water path, units kg m^-2</p> <p>LWCF_d1: clean longwave cloud forcing, units W m^-2</p> <p>OMEGA: vertical velocity, units Pa s^-1</p> <p>PRECT: total precipitation, units m s^-1</p> <p>SWCF_d1: clean shortwave cloud forcing, units W m^-2</p> <p>V: meridional wind, units m s^-1</p> <p> </p> <p>All data were generated and processed by James A. King.</p>
CESM2 land use data for study on hydrological impacts of large-scale forest expansion
<p>This repository contains the land use/ land cover input data for CESM2 which was used in the study investigating the hydrological impacts of global-scale forestation. The datasets cover the period 2000-2100. The files correspond to experiments described in the study as follows:</p> <p> </p> <p>Base: landuse.timeseries_0.9x1.25_SSP1-2.6_78pfts_CMIP6_simyr2000-2100_c220715.nc</p> <p>Max Forest: landuse.timeseries_0.9x1.25_hist_78pfts_SSPRFAFRS_SSP1_edit_xarray_4_simyr2000-2100_c221024.nc</p> <p>No LULCC: landuse.timeseries_0.9x1.25_hist_78pfts_SSPNOLULCC_3_simyr2000-2100_c221025.nc</p> <p> </p> <p>Files were created in collaboration by James A. King, James Weber, Peter Lawrence, and Stephanie Roe.</p> <p> </p>
CESM2 atmosphere output data for study on hydrological impacts of large-scale forest expansion
<p>This repository contains the atmosphere output data from CESM2 which was generated in the study investigating the hydrological impacts of global-scale forestation, for the No LULCC scenario. The datasets cover the period 2015-2100. Output fields are as follows:</p> <p>CCN3: concentration of cloud condensation nuclei at 0.1% supersaturation, units cm^-3</p> <p>CLDLOW: cloud fraction integrated between 1200-700 hPa, units fraction of grid cell</p> <p>CONCLD: convective cloud cover, units fraction of grid cell</p> <p>GCLDLWP: grid cell cloud water path, units kg m^-2</p> <p>LWCF_d1: clean longwave cloud forcing, units W m^-2</p> <p>OMEGA: vertical velocity, units Pa s^-1</p> <p>PRECT: total precipitation, units m s^-1</p> <p>SWCF_d1: clean shortwave cloud forcing, units W m^-2</p> <p>V: meridional wind, units m s^-1</p> <p> </p> <p>All data were generated and processed by James A. King.</p>
1-km high resolution model outputs using the WRF and WRF-Hydro model Raw data from the manuscipt "Process-based Atmosphere-Hydrology-Malaria Modeling: Performance for Spatio-temporal Malaria Transmission Dynamics in Sub-Saharan Africa "
<p>Here we provide the model outputs from the numerical climate model WRF (Weather Research and Forecasting) and its hydrological coupled model WRF-Hydro for the Health and Demographic Surveillance Systems (HDSS) site regions of Nouna in Burkina Faso. Model results are used for investigating the influence of surface hydrology representation, environmental and climate-sensitive driver factors on malaria incidence.<br>The experiments use the following model configuration: 1km horizontal resolution with 200*200 grid points, WSM6 microphysics, ACM2 PBL, and RRTM & Dudhia radiation scheme. WRF uses the Noah LSM, and WRF-Hydro uses the Noah LSM with enhanced lateral hydrological description (https://ral.ucar.edu/projects/wrf_hydro/overview). These simulations were conducted in the Karlsruhe Steinbuch Centre for Computing (SCC) Horeka.</p> <p>Model outputs are provided in daily step (originally derived from the hourly output). Filename with "wrf-hydro_pr_2000-2020_d02-1km.nc" provides Precipitation,<br>n mm/day"wrf-hydro_tas_2000-2020_d02-1km.nc" provides mean temperature in Celsius, "wrf-hydro_tasmax_2000-2020_d02-1km.nc" provides maximum temperature in Celsius, "wrf-hydro_tasmin_2000-2020_d02-1km.nc" provides minmum temperature in Celsius, "wrf-hydro_dtr_2000-2020_d02-1km.nc" provides diurnal temperature ranges in Celius, "wrf-hydro_rh_2000-2020_d02-1km.nc" provides relative humudity in % and "wrf-hydro_sw_2000-2020_d02-1km.nc" provides the surface hydrology.</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.