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676 results for “hydrology”
Thermodynamic and hydrological drivers of the subsurface thermal regime in Central Spain: open data and code
<p>Quality controlled temperature data at daily resolution at CTS, HRR, HYS, NVC, RSI and SGV and the most relevant codes for data processing used in:</p> <p>García-Pereira, F., González-Rouco, J. F., Schmid, T., Melo-Aguilar, C, Vegas-Cañas, C., Steinert, N. J., Roldán-Gómez, P. J., Cuesta-Valero, F. J., García-García, A., Beltrami, H., and de Vrese, H.: "Thermodynamic and hydrological drivers of the subsurface thermal regime in Central Spain". Earth Surf. Dynam., submitted, 2023.</p> <p>All data can be also freely obtained for research from the original data sources, GuMNet (https://www.ucm.es/gumnet/) and AEMET (https://www.aemet.es/en/datos_abiertos). Further details of the code are available upon request to the corresponding author (Félix García-Pereira, felgar03@ucm.es).</p>
Accompanying data for the open-source book Modeling of Hydrological Systems in Semi-Arid Central Asia
<p>This data set is used to reproduce examples in the open-source book <a href="https://hydrosolutions.github.io/caham_book/">"Modeling of Hydrological Systems in Semi-Arid Central Asia"</a> which is part of a free course on hydrological modeling in Central Asia. The course teaches how to use publicly available data to implement a hydrological model for climate impact studies (Marti et al., 2023). </p> <p>To use the data set to reproduce the examples in the book: Download the book from https://doi.org/10.5281/zenodo.6350042 and this data set to the same hierarchical level in your file system: </p> <p>|- caham_book<br> |- caham_data<br> |- AmuDarya<br> |- central_asia_domain<br> |- student_case_study_basins<br> |- SyrDarya</p> <p>You will need a working installation of R (https://www.r-project.org/) and a GUI (e.g. Posit, formerly RStudio https://posit.co/) to reproduce the scripted examples in the book. Once your software is set up, you can proceed to run the examples. </p> <p> </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>
Implementation of GR hydrological models in 95 near-natural catchments across Chile
<p>All the files included here contain the data and calibration results produced for the paper "Exploring parameter (dis)agreement due to calibration metric selection in conceptual rainfall-runoff models" accepted for publication in Hydrological Sciences Journal (HSJ). This database summarizes the calibrated parameter sets for the GR4J, GR5J and GR6J conceptual rainfall-runoff models, all coupled to the CemaNeige snow module (i.e., GRXJ + CemaNeige = GRXJCN), using 12 objective functions. The models are configured for 95 near-natural catchments located in Continental Chile. Each basin is identified by a unique code registered in the National Water Bank (BNA by its acronym in Spanish) by the Chilean Water Bureau (DGA; https://dga.mop.gob.cl/). Meteorological forcings and hypsometric curves for each basin studied are also included.</p> <p>The information is organized as follows:</p> <p>- "01 Forcings" : It includes a "Comma-separated value" file (".csv") per basin (according to the notation "BNA code.csv") which contains daily time series of precipitation (P; mm/d), temperature (°C) and potential evapotranspiration (E; mm/d) for the period 1980-01-01 to 2017-12-31. The daily runoff observations (Q; mm/d) and snow water equivalent (SWE; mm) from Cortés et al. (2017) are included. P and T are estimated from the basin-scale average of the CR2Met v2.0 gridded product, while E was calculated using Oudin's formula.<br> - "02 Hypsometry" : It includes a "Comma-separated value" file (".csv") per basin with elevation (in m a.s.l.) vs. area below elevation (in percentage) in the format required by GR models ("BNA code.csv" notation), and the full hypsometric curve ("BNA code_original.csv" notation) retrieved from the SRTM DEM clipped to the basin of interest.<br> - "03 Calibrated parameters": It includes one sub-directory per basin, containing a summary of the calibrated parameters for each combination of model structure (GR4JCN, GR5JCN and GR6JCN) and objective function.</p> <p>Additionally, we include the following "Comma-separated value" (i.e., ".csv") files:</p> <p>- "BNA_select.csv": list of case study basins (BNA code and name).<br> - "Catchment_attributes_CAMELS-CL.csv": catchments attributes directly obtained from CAMELS-CL.<br> - "Catchment_attributes.csv": catchments attributes used for this study. Note that this file contains re-calculated values for climatic attributes. </p>
Statistical blending of global-gridded climatological products: an approach to inverse hydrological model
<p>The growing use of global-scale environmental products in hydro-climatic modeling (with different assumptions, resolutions, and precisions) has increased the variety of their applications and the complications of their uncertainties and evaluations. Researchers have recently turned to statistical blending (fusion) of these products to achieve optimal modeling while avoiding difficulties. The proposed statistical blending in this study includes five large-scale and satellite precipitation (Climate Hazards Group Infrared Precipitation with Stations (CHIRPS), ERA5-Land of ECMWF (ERA), Integrated Multi-Satellite Retrievals for GPM (IMERG), Tropical Rainfall Measuring Mission (TRMM), and Terra) and evapotranspiration (Global Land Evaporation Amsterdam Model (GLEAM), SSEBop, Moderate Resolution Imaging Spectroradiometer (MODIS), Terra, and ERA) products committed in three modeling scenarios. The blending procedures are organized using a conceptual water balance model to achieve the best precipitation and evapotranspiration results for the conceptual production of streamflow using hydrological inverse modeling. Based on the results, the proposed blending procedures of precipitation and evapotranspiration improved the performance of the model using different statistical metrics. In addition, the results show the conformity of the pattern and behavior of the blended precipitation calculated using the moving least square method in the study area. This happened by changing the estimation based on <em>in situ</em> values, particularly in cold months considering the orographic/snow effects. The combining method provides a good fusion procedure to improve the realistic estimation of precipitation and evapotranspiration in ungagged watersheds as well<strong>.</strong></p>
Multi-model Ensemble for Robust Verification of hydrological modeling in Japan (MERV-Jp)
<p>MERV-Jp is the dataset of meteorological forcing and multi-model runoff simulation in 135 (ver1.1) / 87 (ver2.0) Japanese basins, and contributes to carrying out a large sample rainfall-runoff simulation in Japan. In addition, MERV-Jp can be used as a benchmark to evaluate user's hydrological modeling. <br> The detailed description of MERV-Jp can be found at "Y. Sawada, S. Okugawa and T. Kimizuka (2022): Multi-model ensemble benchmark data for hydrological modeling in Japanese river basins, Hydrological Research Letters, 16, 73-79" (https://doi.org/10.3178/hrl.16.73).</p>
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).
Hydrologic response units (base units for PRMS streamflow model), Andrews Experimental Forest, 1993
Hydrologic Response Units are used as base units for the Precipitation-Runoff Modeling System (PRMS) streamflow model. Created by Alok Sikka as part of landscape runoff modeling.
Litterfall on the elevational gradient (Group 1) at Coweeta Hydrologic Laboratory from 1992 to 1993
Null Hypothesis: Litterfall weights not statistically different between plots on the altitudinal gradient.
Litterfall on the elevational gradient (Group 2) focusing on Rhododendrum leaf litter from the Coweeta Hydrologic Laboratory from 1994 to 1995
Null Hypothesis: Litterfall weights not statistically different between plots on the altitudinal gradient.
Litterfall on the elevational gradient (Group 3) from the Coweeta Hydrologic Laboratory in 1995
Null Hypothesis: Litterfall weights not statistically different between plots on the altitudinal gradient.
Litterfall on the elevational gradient (Group 4) with a focus on greenfall from the Coweeta Hydrologic Laboratory in 1995
Null Hypothesis: Litterfall weights not statistically different between plots on the altitudinal gradient.
Litterfall on the elevational gradient (Group 5) from the Coweeta Hydrologic Laboratory in 1995
Null Hypothesis: Litterfall weights not statistically different between plots on the altitudinal gradient.
Litterfall on the elevational gradient (Group 6) from the Coweeta Hydrologic Laboratory from 1995 to 1996
Null Hypothesis: Litterfall weights not statistically different between plots on the altitudinal gradient.
Litterfall on the elevational gradient (Group 7) in the Coweeta Hydrologic Laboratory from 1996 to 1998
Null Hypothesis: Litterfall weights are not statistically different between plots on the altitudinal gradient.
Dendrometer Band Measurements from the Coweeta LTER Terrestrial Gradient Sites, Coweeta Hydrologic Laboratory, Otto, North Carolina.
Trees for this project were banded with aluminum bands and growth increment markers to accurately measure tree growth at multiple times during the year. Trees were located on each of the five terrestrial gradient plots. Tree species, initial diameter, and subsequent calculated diameters are included for each tree.
Fine root dynamics along an elevational gradient in the southern Appalachian mountains in the Coweeta Hydrologic Laboratory from 1993 to 1994
Annual rates of fine root mass appearance and disappearance were calculated from samples of fine roots taken in soil cores over time on the five gradient plots.
Fine root dynamics along an elevational gradient in the southern Appalachian mountains in the Coweeta Hydrologic Laboratory from 1994 to 1995 (lengths of fine root segments)
The lengths of fine root segments visible in photographs of roots growing against the windows of minirhizotron boxes were measured.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.