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39 results for “hydrological processes”
Terrestrial-Stream Biodiversity Litter Processing Datasets from Watershed 20 within the Coweeta Hydrologic Laboratory
Although litter decomposition is a fundamental ecological process, most of our understandings comes from studies of single-species decay. Recently, litter-mixing studies have tested whether monoculture data can be applied to mixed-litter systems. These studies have mainly attempted to detect non-additive effects of litter mixing, which address potential consequences of random species loss -- the focus is not on which species are lost, but the decline in diversity per se. Under global change, species loss is likely to be non-random, with some species more vulnerable to extinction than others. Under such scenarios, the effects of individual species (additivity) as well as of species interactions (non-additivity) on decomposition rates are of interest. To examine potential impacts of non-random species loss on ecosystems, we studied additive and non-additive effects of litter mixing on decomposition. A full-factorial litterbag experiment was conducted using four deciduous leaf species, from which mass loss and nitrogen content were measured. This study was conducted at the Coweeta Hydrologic Laboratory in Watershed 20 on Ball Creek that drains into Coweeta Creek, a tributary of the Little Tennessee River. Data were analyzed using a statistical approach that first looks for additive identiy effects based on the presence or absence of species and then significant species interactions occurring beyond those. It partitions non-additive effects into those caused by richness and/ or composition. This approach addresses questions key to understanding the potential effects of species loss on ecosystem processes. If additive effects dominate, the consequences for decomposition dynamics will be predictable based on our knowledge of individual species, but not statistically predictable if non-additive effects dominate.
Rosalia: An experimental research site to study hydrological processes in a forest catchment - data repository
<p>This repository is a supplement to the paper <strong>Fürst, J., et al. (2021). “Rosalia: an experimental research site to study hydrological processes in a forest catchment.” Earth Syst. Sci. Data 13(8): 4019-4034.</strong></p> <p>Experimental watersheds have a long tradition as research sites in hydrology and have been used as far back as the late 19<sup>th</sup> and early 20<sup>th</sup> century. The University of Natural Resources and Life Sciences Vienna (BOKU) has been operating the experimental research forest site called “Rosalia” with an area of 950 ha since 1875 to support and facilitate research and education. Recently, BOKU researchers from various disciplines extended the “Rosalia” instrumentation towards a full ecological-hydrological experimental watershed. The overall objective is to implement a multi-scale, multi-disciplinary observation system that facilitates the study of water, energy and solute transport processes in the soil-plant-atmosphere continuum.</p> <p>This repository contains the datasets collected by a monitoring network of 4 discharge gauging stations, 7 rain-gauges, together with observations of air and water temperature, relative humidity and conductivity. In four profiles, soil water content and temperature are recorded in different depths. In 2019, additionally a program to collect isotopic data in precipitation and discharge was started. On one site, also Nitrate, TOC and turbidity are monitored. All data collected since 2015, including in total 56 high resolution time series data (10 min sampling interval), are provided to the scientific community.</p>
Dataset for the article "Development of an integrated socio-hydrological modeling framework for assessing the impacts of shelter location arrangement and human behaviors on flood evacuation processes"
<p>This dataset include the data needed to create the socio-hydrological model to simulate human evacuation processes via a transportation network before a flood hits the residential area. Source code, in JAVA, for generating households in the agent-based model are also provided. </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>
Fig. 13 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 13: The effect of hydrodynamics inside the Y-Cave, the location behind section B-B' (Fig. 2) at 5.5 m of depth, where the unusually coloured sediment sample was collected for analysis.
Fig. 12 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 12: Limestone tablets from the three representative sites after the 1-year exposure period: A) with bioaccumulation at site 1; B) corroded at site 3; C) abraded at site 6 (Fig. 3, Tab. 1).
Fig. 11 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 11: Cave features: A) stalactites in the chamber with the air pocket (section C-C'); B) submerged stalagmites and flowstones with a lack of marine cave biota (section C-C'); C) submerged scallops (asymmetrical, cuspate, oyster-shell-shaped dissolution depressions in the cave walls used as an indicator of flow direction; Murphy, 2012), (section D-D'); D) corroded cave walls (section F-F').
Fig. 5 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 5: The annual variation of temperature along the Y-Cave (from August 23–27, 2003 to July 4/October 8, 2004). Measurement positions are given in Fig. 3 and depths in Table 1.
Fig. 10 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 10: The mass (m.f.) and volume fractions (v.f.) of four sediment categories in the sediment sample collected behind section B-B' (Fig. 2), at 5.5 m of depth inside the Y-Cave; A) detrital terrigenous sediment>4 mm, B) mixed biogenic and terrigenous detritus, C) shells of gastropod Homalopoma sanguineum, D) other biogenic material – shells, tests and skeletons of other marine organisms.
Fig. 4 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 4: Living communities inside the Y-Cave: A) the entrance part of the cave, vertical wall, depth 9 m, biocenosis of semi-dark caves (GSO, see text for explanation of acronym) dominated by numerous sponge species; B) the entrance part of the cave, ceiling, depth 6 m, GSO dominated by scleractinian coral Leptopsammia pruvoti; C) the entrance part of the cave, overhang, depth 7 m, GSO dominated by scleractinian coral Madracis pharensis; D) the entrance part of the cave, vertical wall (near the bottom), depth 9 m, GSO, a large specimen of the orange sponge Agelas oroides dominates the photo; E) the middle part of the cave, in front of the section C-C', bottom, depth 10 m, a massive white specimen of the sponge Chondrosia reniformis; F) the middle part of the cave, between sections C-C' and D-D', vertical wall and overhang, depth 5 m, the transition from GSO to biocenosis of caves and ducts in total darkness (GO, see text for explanation of acronym), the community is dominated by serpulids; G) the middle part of the cave, between sections C-C' and D-D', vertical wall, depth 5 m, transition from GSO to GO, a dense population of brachiopod Novocrania anomala, encrusting sponge Placospongia decorticans and serpulids; H) the end part of the cave, near the section G-G', vertical wall with overhang and horizontal shelf, depth 6 m, GO with scarce calcareous sponges and serpulids (see Fig. 2 for position of the sections).
Fig. 1 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 1: The non-linear relationship between CO and Ca2+ con2 centrations in H 2O-CO2-CaCO3 solution. Each mixture (e.g. C) of the saturated solutions A and B lies on the straight line between them in the zone of undersaturation with respect to calcite, producing an aggressive solution that dissolves the surrounding carbonate (after Gabrovšek & Dreybrodt (2010)).
Fig. 8 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 8: Temperature, salinity and depth profiles recorded with the CTD probe during a dive inside the Y-Cave (August 27, 2003), 1 – vertical profile at the cave opening; 2 – vertical profile inside the cave entrance part; 3 – vertical profile at the turning point, section C-C'; 4 to 6 – vertical profiles in the inner part of the cave: 4 at approximately section E-E', 5 at approximately section G-G' and 6 at approximately section H-H'.
Fig. 3 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 3: The positions of temperature and light intensity data loggers inside the Y-Cave (dark circles - temperature data loggers; white circles - light intensity data loggers). Four loggers with their photosensitive cell facing upwards are marked with a black dot; the remaining cells were positioned to face the entrance of the cave.
Fig. 9 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 9: Variation of light intensity over a period of 11 days (June 19–30, 2006) at representative sites within the Y-Cave (Fig. 3): logger 1 – the entrance of the cave; logger 4 – the central part of the cave; logger 10 – the innermost part of the cave.
Fig. 6 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 6: The comparison of the tidal (solid line) and temperature (dashed line) fluctuation from February 2–8, 2004. Temperature records are from logger 4 (Fig. 3), and tides from the nearest tide gauge in Zadar port.
Fig. 7 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 7: Vertical temperature profiles inside and outside the YCave taken with the CTD probe (August 27, 2003); the profile labelled with a dotted line was taken at approximately section H-H', the profile labelled with a solid line at approximately section G-G'.
Fig. 2 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 2: The location, cross-section and layout of the Y-Cave on Dugi Otok Island, Croatia, with characteristic profiles.
Dataset for: Hydrological processes in East African tropical montane headwater catchments influenced by land use
<p>This dataset contains high-resolution (10-minute interval) data for nitrate (concentration and load), precipitation and discharge at four measurement stations (NF, SHA, TTP, OUT) in the South West Mau, Kenya, as well as trace element data and stable isotopes of water for rainfall and stream water samples. The data was used to investigate the influence of land use on hydrological processes through time series analysis (<a href="http://doi.org/10.1002/2017WR021592">Jacobs et al. 2018a</a>), end member mixing analysis and estimation of the young water fraction (<a href="http://doi.org/10.5194/hess-22-4981-2018">Jacobs et al. 2018b</a>).</p>
MONITORING AND MODELING OF HYDROLOGICAL PROCESSES IN THE SEMIARID REGION OF BRAZIL: THE CARIRI EXPERIMENTAL BASINS
<p><strong>DATASET DESCRIPTION</strong> - Two experimental basins – the Cariri basins – were installed in a typically semiarid region in the State of Paraíba, Brazil, for obtaining reliable estimates of runoff and soil erosion in different scales to evaluate the influence of the human activities and other factors over the processes of runoff and erosion. In the first basin, located in the municipality of Sumé, the field studies were carried out at three different scales: four micro-basins with an area of around 0.5 ha; nine standard Wischmeier-type erosion plots of 100 m<sup>2</sup> and seven sample plots of 1 m<sup>2</sup>. The experimental units had varied vegetal cover and management and, except the sample plots, were subjected to natural rainfall events only, and were monitored from 1982 to 1991. The total runoff and total sediment yield were determined for each of the events of precipitation. The installations of the second basin, in the near municipality of São João do Cariri, were planned for the continuation of the studies initiated at Sumé, and include erosion plots (100 m<sup>2</sup>), micro-basins, and sub-basins, which are being monitored for runoff and sediment production up to now. Among them, two nested micro-basins were monitored to detect any scale effect at the micro-basin level. Nearly 600 events of natural precipitation, that produced runoff in at least one of the experimental units, have been registered. This bulk of data was utilised to evaluate the influence of various factors, including cultivation practices. The data collected so far has been successfully used to calibrate hydrological models for plots and micro-basins. Parameters have been tested by means of cross validations among micro-basins and sub-basins.</p> <p><strong>FILENAMES </strong>– The data files are divided into three categories: Description of the equipment utilized for collecting data and their locations, the data collected from the monitored experimental basins and another with maps, figures and pictures. The file names are designated with the basin name and the content. The files describing the equipment comprise: BASINNAME_DATADESCRIPTION, where BASINNAME could be EBS or EBSJC. The files with the data collected in the experimental basins are denominated like: BASINNAME_DATANAME. The DATANAME will be one of the three that may be, precipitation, runoff and sediment yield, or climatologic data. The file with maps and other information are identified as: BASINNAME_GEOPHYSICDATANAME, and BASINNAME_PICTURES. The geophysical data refer to topographic data, soil data, land cover and the drainage network. Graphs, pictures, etc., are included in the PICTURES file.</p> <p><strong>DATAFORMAT </strong>– The data file about equipment and localization as well as the data collected in experimental units are of the type “. csv”, the geophysical data are of either “.dwg” or “.shp”. The figures and picture are in the format: .jpeg, .png or .tif.</p> <p><strong>ACKNOWLEDGEMENTS </strong>– SUDENE – the Superintendency for the Development of the Northeast of Brazil with the cooperation of ORSTOM – the French Government Agency for Technical Cooperation Overseas was responsible for implementing the program of Representative and Experimental Basins in the region beginning in the decade of 1970. Pierre Audry, Eric Cadier, Jean Leprun and Michel Molinier, hydrologists and soil scientists from France played key roles in the selection of site, installation of experimental units and beginning the operation of the EBS. Beronildo Freitas was the engineer from SUDENE responsible for technical coordination and administration. The contributions of other researchers and technical people have been listed by Srinivasan and Galvão (2003). The installation of the research catchment at São João de Cariri had the valuable collaboration of GTZ, the cooperation Agency of the Government of Germany. Dr. Ing Ubald Koch was responsible for getting all the equipment, installing them and conducting research work along with the members of the Hydrology Research Group of the Federal Universities of Paraiba and Campina Grande. Late prof. Manoel Gilberto de Barros efficiently coordinated the field work. Eduardo Figueiredo, Celso Santos and Ricardo Aragão have made note worthy contributions. The Ministry of Science and Technology of Brazil has provided the bulk of the financial support needed for the operation of the basins, through its main funding agencies of CNPq (National Council for Development of Science and Technology) and FINEP (Agency for Financing research Studies and Projects).</p>
Enhancing understanding of the hydrological cycle via pairing of process‐oriented and isotope ratio tracers
<p>This dataset contains monthly average output files from the iCAM6 simulations used in the manuscript "Enhancing understanding of the hydrological cycle via pairing of process-oriented and isotope ratio tracers," in review at the Journal of Advances in Modeling Earth Systems. A file corresponding to each of the tagged and isotopic variables used in this manuscript is included. Files are at 0.9° latitude x 1.25° longitude, and are in NetCDF format. Data from two simulations are included: 1) a simulation where the atmospheric model was "nudged" to ERA5 wind and surface pressure fields, by adding an additional tendency (see section 3.1 of associated manuscript), and 2) a simulation where the atmospheric state was allowed to freely evolve, using only boundary conditions imposed at the surface and top of atmosphere.</p> <p>Specific information about each of the variables provided is located in the "usage notes" section below.</p> <p>Associated article abstract:</p> <p>The hydrologic cycle couples the Earth's energy and carbon budgets through evaporation, moisture transport, and precipitation. Despite a wealth of observations and models, fundamental limitations remain in our capacity to deduce even the most basic properties of the hydrological cycle, including the spatial pattern of the residence time (RT) of water in the atmosphere and the mean distance traveled from evaporation sources to precipitation sinks. Meanwhile, geochemical tracers such as stable water isotope ratios provide a tool to probe hydrological processes, yet their interpretation remains equivocal despite several decades of use. As a result, there is a need for new mechanistic tools that link variations in water isotope ratios to underlying hydrological processes. Here we present a new suite of "process-oriented tags," which we use to explicitly trace hydrological processes within the isotopically enabled Community Atmosphere Model, version 6 (iCAM6). Using these tags, we test the hypotheses that precipitation isotope ratios respond to parcel rainout, variations in atmospheric RT, and preserve information regarding meteorological conditions during evaporation. We present results for a historical simulation from 1980 to 2004, forced with winds from the ERA5 reanalysis. We find strong evidence that precipitation isotope ratios record information about atmospheric rainout and meteorological conditions during evaporation, but little evidence that precipitation isotope ratios vary with water vapor RT. These new tracer methods will enable more robust linkages between observations of isotope ratios in the modern hydrologic cycle or proxies of past terrestrial environments and the environmental processes underlying these observations.<br> </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
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.