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299 results for “water analysis”
Datasets for the study "Hydro-economic analysis of infrastructure investment options within the Water-Energy-Food nexus in the Niger River basin"
<p>This is the dataset used in the study "Hydro-economic analysis of infrastructure investment options within the Water-Energy-Food nexus in the Niger River basin". This study has been conducted within the Department of Environmental Engineering at the Technical University of Denmark as a Master Thesis project. </p> <p>The dataset describes the water-energy-food nexus of the Niger River basin used as input to the open source single objective hydro-economic optimization model WHAT-IF. Note that the Energy Module is partly filled, but has not been used in the study (except the hydropower sheet).</p> <p>More information on data organization <a href="https://zenodo.org/record/2646476#.XxqORudS93g">here</a>.</p> <p>The model is documented in this <a href="https://hess.copernicus.org/articles/23/4129/2019/hess-23-4129-2019-discussion.html">publication</a>.</p> <p>The code is available on <a href="https://github.com/RaphaelPB/WHAT-IF">Github</a>.</p>
Analysis of the water-power nexus in the North, Eastern and Central African Power Pools
<p>This dataset underpins the report provided to the project "Analysis of the water-power nexus in the North, Eastern and Central African Power Pools"</p> <p>The report provides insights into the balance between energy supply and demand, power generation, total system costs, water consumption and withdrawal as well as carbon dioxide emissions for the North, Eastern and Central African power pools.</p>
Data for non-parametric analysis_Cumaceans in a shallow water
<p>Data for a non-parametric analysis of Cumaceans distribution collected in a shallow water hydrothermal system of Punta Mita. They coming from three vent sites.</p>
Figure 6 in Analysis of Carapas Width and Weight on Maturity Level of Swimming Crab (Portunus pelagicus) as Basis for Sustainable Resource Management in the Eastern Waters of Surabaya
Figure 6: Percentage of maturity level of female swimming crabs
Figure 5 in Analysis of Carapas Width and Weight on Maturity Level of Swimming Crab (Portunus pelagicus) as Basis for Sustainable Resource Management in the Eastern Waters of Surabaya
Figure 5. Percentage of spawning females Phase
Figure 4 in Analysis of Carapas Width and Weight on Maturity Level of Swimming Crab (Portunus pelagicus) as Basis for Sustainable Resource Management in the Eastern Waters of Surabaya
Figure 4: Sex ratio distribution of swimming crab
Figure 1 in Analysis of Carapas Width and Weight on Maturity Level of Swimming Crab (Portunus pelagicus) as Basis for Sustainable Resource Management in the Eastern Waters of Surabaya
Figure 1: Maturity level composition of swimming crab based on carapace width
Figure 3 in Analysis of Carapas Width and Weight on Maturity Level of Swimming Crab (Portunus pelagicus) as Basis for Sustainable Resource Management in the Eastern Waters of Surabaya
Figure 3: Average weight of swimming crab
Figure 2 in Analysis of Carapas Width and Weight on Maturity Level of Swimming Crab (Portunus pelagicus) as Basis for Sustainable Resource Management in the Eastern Waters of Surabaya
Figure 2: Average Carapace Width of Swimming Crab
Water will find its way: transport through narrow tunnels in hydrolases (water-protein interaction analysis)
<p>Repository including information on the analyses of water-protein interactions by MM/GBSA.</p> <p><strong>hal_mmgbsa_data.tar.gz</strong> - contains a minimal set of files necessary to recreate MM/GBSA calculations and also raw calculation results for Hal.<br><strong>epx_mmgbsa_data.tar.gz</strong> - contains a minimal set of files necessary to recreate MM/GBSA calculations and also raw calculation results for Epx.<br><strong>lip_mmgbsa_data.tar.gz</strong> - contains a minimal set of files necessary to recreate MM/GBSA calculations and also raw calculation results<strong> </strong>for Lip<strong>.</strong></p> <p>In each archive structure is:<br> {supercluster_id}: - supercluster directory<br> {event_nr}_{rounded_radius}: - transport event directory<br> renum.pdb -pdb file containing protein, water of interest and 8 Angstrom radius sphere of surrounding waters<br> water.txt - file denoting water ID for water of interest in the renum.pdb file<br> binding_[implicit|explicit].dat - file containing MMGBSA results for full implicit and partial explicit system<br> decomposition_[implicit|explicit].dat - file containing MMGBSA decomposition results for full implicit and partial explicit system<br> info_{supercluster_id}.csv - file containing descriptions of transport events in supercluster (columns: event_name, radius, frame, simulation, water_id)</p> <p><strong>results.tar.gz </strong>- contains csv files generated by <em>script collect_data_minimal.py</em> for each protein for full implicit and partial explicit solvent. Columns in those csv file are: event_name, supercluster, radius, frame, simulation, water_id, delta_total, delta_van_der_waals, delta_electrostatic, delta_G_solv</p> <p><strong>scripts.tar.gz</strong> - contains following scripts<br> read_transport_events.py<br> prep_inputs.py<br> run_MMGBSA_single.sh<br> collect_data_minimal.py<br> plot_bin.py</p> <p>To recreate MMGBSA calculations with provided inputs one should:<br>$ python read_transport_events.py [Hal.dat|Epx.dat|Lip.dat] > selection.txt<br>Prepare transport events information in a compatible format. Binary transport events databases are available in the repository.</p> <p>$ python prep_inputs.py selection.txt - {absolute output path} {supercluster_id} 1 <br>Prepare parm and coordinate file for each supercluster id included in computation. Last argument 1 point script to resume preparations from renum.pdb files.</p> <p>$ bash run_MMGBSA_single.sh {residue_count}<br>Runs MMGBSA for both partial explicit and fully implicit systems. Needs to be run for each event in each supercluster.<br>residue_count should be set to 293 for hal, 319 for epx, and 534 for lip.</p> <p>$ python collect_data_minimal.py [hal|epx|lip]/{supercluster_id} [hal|epx|lip]/info_{supercluster_id}.csv [0|1] >> output.csv<br>Gathers data from MMGBSA calculations for a single supercluster into csv file. <br>Last argument should be 0 for fully implicit system, 1 for partial explicit system.</p> <p>$ python plot_bin.py {hal_implicit_csv} {hal_explicit_csv} {epx_implicit_csv} {epx_explicit_csv} {lip_implicit_csv} {lip_explicit_csv}<br>Results visualization. Produces "combined.png".</p>
Data and Software for "Probabilistic Trade-offs Analysis for Sustainable and Equitable Management of Climate-Induced Water Risks"
<p><span>Research data supporting the study "Probabilistic trade-offs analysis for sustainable and equitable management of climate-induced water risks"</span></p> <p><span>This repository provides data of the Stochastic Dual Dynamic Programming (SDDP) model, and the output results of the simulations of the various policies and climate scenarios considered in this study, as well as the code used for postprocessing and visualizing the results.</span></p> <p><strong><span>Contents</span></strong></p> <ol> <li><strong><span>Data: Model Inputs</span></strong><span><br>This folder contains the physical river network, reservoir and water demand, and economic data derived from the observed database.<br>The key files are:</span></li> <ul> <li><span>Input_HydrologicalData</span></li> <li><span>Input_SystemData</span></li> </ul> <li><strong><span>Results: Model Output Analysis</span></strong><span><br>This folder includes outputs from the Stochastic Dual Dynamic Programming (SDDP) model under various policies and climate scenarios. The results showcase optimized sectoral water use, including irrigated areas, hydropower generation, and allocations for agriculture, energy, and urban demands across spatial locations (upstream and downstream).<br>Key files include:</span></li> <ul> <li><strong><span>SDDP Model Outputs</span></strong><span> (MATLAB format): </span></li> <ul> <li><span>EnergyPriority_Baseline.mat</span></li> <li><span>EnergyPriority_2070.mat</span></li> <li><span>EnergyPriority_2100.mat</span></li> <li><span>AgriculturePriority_Baseline.mat</span></li> <li><span>AgriculturePriority_2070.mat</span></li> <li><span>AgriculturePriority_2100.mat</span></li> </ul> <li><strong><span>Extracted Model Results</span></strong><span> (Excel format): </span></li> <ul> <li><span>Organized for each policy and climate scenario to facilitate analysis.</span></li> </ul> </ul> <li><strong><span>Software: Data Analysis and Visualization</span></strong><span><br>Python scripts designed for outputs data analysis and visualization are included to reproduce the primary figures from the study.<br>Scripts provided:</span></li> <ul> <li><span>CDF_outflow.py</span><span>: Analyzes cumulative distribution functions for river discharge.</span></li> <li><span>CDF_sectors.py</span><span>: Examines sectoral water use distributions.</span></li> <li><span>PCP_SI.py</span><span>: Generates Parallel Coordinate Plots for trade-offs analysis.</span></li> </ul> <li><strong><span>Instructions: README File</span></strong><span><br>A comprehensive README file explains:</span></li> <ul> <li><span>Details of model input data.</span></li> <li><span>Instructions to interpret the SDDP model outputs.</span></li> </ul> </ol> <p><strong><span>Instructions:</span></strong><span><br></span><span>The Python scripts process Excel files from the model output results folder to generate and visualize the figures for the paper. Each step is clearly documented within the scripts.</span></p>
Systematic review and meta-analysis: water type and temperature affect environmental DNA decay metadata
<p>Environmental DNA (eDNA) has been used in a variety of ecological studies and management applications. The rate at which eDNA decays has been widely studied but at present it is difficult to disentangle study-specific effects from factors that universally affect eDNA degradation. To address this, a systematic review and meta-analysis was conducted on aquatic eDNA studies. Analysis revealed eDNA decayed faster at higher temperatures and in marine environments (as opposed to freshwater). DNA type (mitochondrial or nuclear) and fragment length did not affect eDNA decay rate, although a preference for < 200 bp sequences in the available literature means this relationship was not assessed with longer sequences (<em>e.g.</em> > 800 bp). At present, factors such as ultraviolet light, pH, and microbial load lacked sufficient studies to feature in the meta-analysis. Moving forward, we advocate researching these factors to further refine our understanding of eDNA decay in aquatic environments. This dryad entry contains the metadata which formed the basis for the meta-analysis.</p>
Data from: Girth increment changes in response to soil water availability in lowland dipterocarp forest in Borneo: an individualistic time-series analysis
<p><span>Time-series data offer a way of investigating the causes driving ecological processes as phenomena. To test for possible differences in water relations between species of different forest structural guilds at Danum (Sabah, NE Borneo), daily stem girth increments (gthi), of 18 trees across six species were regressed individually on soil moisture potential (SMP) and temperature (TEMP), accounting for temporal autocorrelation (in GLS-arima models), and compared between a wet and a dry period. The best-fitting significant variables were SMP the day before and TEMP the same day. The first resulted in a mix of positive and negative coefficients, the second largely positive ones. An adjustment for dry-period showers was applied. Interactions were stronger in dry than wet period. Negative relationships for overstorey trees can be interpreted in a reversed causal sense: fast transporting stems depleted soil water and lowered SMP. Positive relationships for understorey trees meant they took up most water at high SMP. The unexpected negative relationships for these small trees may have been due to their roots accessing deeper water supplies (if SMP was inversely related to that of the surface layer), and this was influenced by competition with larger neighbour trees. A tree-soil flux dynamics manifold may have been operating. Patterns of mean diurnal girth variation were more consistent among species, and time-series coefficients were negatively related to their maxima. Expected differences in response to SMP in the wet and dry periods did not clearly support a previous hypothesis differentiating drought and non-drought tolerant understorey guilds. Trees within species showed highly individual responses when tree size was standardized. Data on individual root systems and SMP at several depths are needed to get closer to the mechanisms that underlie the tree-soil water phenomena in these tropical forests. Neighborhood stochasticity importantly creates varying local environments experienced by individual trees.</span></p>
Data from: Improving governance outcomes for water quality: insights from participatory social network analysis for chalk stream catchments in England
<p>Globally important chalk streams in England are in poor ecological health, in part due to inadequate water quality. Addressing this issue requires an understanding of the governance systems that surround water quality. The complexity and uncertainty inherent in hydrological systems has led to the emergence of integrated and adaptive forms of governance. In these multi-actor governance systems, the structure of the relationships between actors (the social network) has been shown to affect governance processes and outcomes.</p> <p>Using participatory social network analysis, we mapped and analysed the social networks for the River Test and River Itchen in Hampshire, UK, to identify actors and their roles, determine the network characteristics, and identify interventions to improve governance.</p> <p>Although the results suggest a well connected network of actors from the state, private sector and civil society, we find that decision making is not decentralised. Bureaucratic governance by central state actors dominates. However, trust in these central state actors and private actors in the networks is low, which undermines collaboration and co-ordination in the network.</p> <p>Devolving authority to local actors, building trust in the networks, and improving connections to important actors could help to improve governance outcomes for water quality.</p>
cost-benefit analysis data of the Wuxikou water control project
<p>A cost-benefit analysis (CBA) data for evaluating the long-term profitability and economic benefits of Wuxikou Water Control Project.</p>
Supporting dataset: "Analysis of tide and offshore storm-induced water table fluctuations for structural characterization of a coastal island aquifer"
<p>Included in this repository are supporting field data and final model input files used to produce the results of the manuscript:</p> <p>Trglavcnik, V., Morrow, D., Weber, K. P., Li, L., & Robinson, C. E. (2017), "Analysis of tide and offshore storm-induced water table fluctuations for structural characterization of a coastal island aquifer."</p> <p>This dataset contains:</p> <ul> <li>SableIsland_data.xlsx <ul> <li>Data used to produce figures in the above manuscript. </li> </ul> </li> <li>Final_SS.zip <ul> <li>Input files for the final model (see Figure 3 in manuscript), steady-state SEAWAT simulation. </li> </ul> </li> <li>Final_PBC.zip <ul> <li>Input files for the final model, transient SEAWAT simulation with a sinusoidal tidal boundary implemented by the Periodic Boundary Condition package (developed for MODFLOW by Post, 2011).</li> </ul> </li> </ul> <p>All data and files are licensed under Creative Commons Attribution Share Alike 4.0 International.</p> <p> </p> <p> </p>
Data and code for "Large-scale remote sensing analysis reveals an increasing coupling of grassland vitality to atmospheric water demand"
<p>Data and code for <br>"Large-scale remote sensing analysis reveals an increasing coupling of grassland vitality to atmospheric water demand"</p> <p>All R code used for the analysis is provided in the folder <em>code</em>. <br>Data and intermediate results are provided or stored in the folders <em>data </em>and <em>tmp_data</em>.<br>All results including figures will be stored in the folder <em>results</em>. </p> <p>R version: 4.3.1</p> <p>To carry out the entire analysis the code should be run in the provided order:</p> <p>1) Code to run non-metric multidimensional scaling (NMDS) for habitat groups and <br>produce Fig. 1b (habitat map and legend for Fig 1a: data/eunis_gl_habitat_ger_990m.tif,eunis_gl_habitat_ger_990m_legend.clr)<br> <br>2) Code to generate grassland vitality maps and time series from 1985 to 2021 (Fig. 3). <br>Grassland vitality maps on 30m for all grasslands in Germany provided in data/glv_1985-2021.zip.</p> <p>3) Code to model relation of grassland vitality to five drought indices (VPD, temperature, CWB, soil moisture, precipitation),<br>output are Fig. 4, Fig. S1, Tab. 1.</p> <p>4) Code for trend analysis of drought sensitivity based on 5-, 10-, and 15-year moving windows, output are Fig. 5, Fig. S2. </p> <p>5) Code to model drought sensitivity of grassland habitat groups and habitat types, output are Fig. 6 and table with sensitivity per habitat type. </p>
Bio-physicochemical Parameters of Water Quality Analysis in Dass LGA, Northeastern Nigeria
<p>The data consist of 20 groundwater samples collected randomly in Dass LGA for water quality assessment. The data has 14 biophysicochemical parameters including:<br>1.pH = The pH value of the samples</p> <p>2. Temp = Temperature of the samples</p> <p>3. TBD = Turbidity of the samples</p> <p>4. Colr = Colour of the water</p> <p>5. TDS = Total Dissolved Solids</p> <p>6. EC = Electrical Conductivity</p> <p>7. TH = Total Hardness</p> <p>8. Al- = Aluminum</p> <p>9. F- = Fluoride</p> <p>10. Fe- = Iron</p> <p>11. NO3 = Nitrate</p> <p>12. Mn = Manganese</p> <p>13. TCC = Total Coliform Count</p> <p>14. FCC = Fecal Coliform Count </p> <p>Other parametrs recorded include Location (Lat/Lon), Name of community, Sample Name, Altitude, Depth, Source of pollution, Distance to pollution source </p>
Fig 3 in Analysis of catch results per effort of catching red snapper (Lutjanus sp) in the waters of Lewalu village, Northwest Alor, Alor Regency
Fig 3: Graph of the Relationship of Arrest Trips in Each Month
Fig 1 in Analysis of catch results per effort of catching red snapper (Lutjanus sp) in the waters of Lewalu village, Northwest Alor, Alor Regency
Fig 1: Proportion of fishing gear to catch
ScienceDex guides
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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)
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.