Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
3
datasets available to search
ShareScore release 0.9.0
Dataset results
3 results for “Water Sustainability Climate”
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>
Data for "Early planting adaptation makes the coupled food-water system more sustainable under climate change"
<p>Data for submission "Early planting adaptation makes the coupled food-water system more sustainable under climate change"</p><p>All data are in netcdf format and can be read in ncl, python, R code capacity.</p><p> </p><p><strong>geo_em.d01.conus.corn:</strong></p><p>Domain setup file for the Noah-MP crop model in the US corn belt. Lat/lon location specified by "XLAT_<i>M" and "XLONG_M</i>" variable and corn planting area specified by "CROPTYPE" variable.</p><p> </p><p>Three zip files are uploaded containing data from model simulations and county-level yield and irrigation record:</p><p><strong>Yield_data.zip:</strong></p><p>yield data from model simulations (denoted by three scenarios, CTRL, PGW, TAVE), with irrigation (irr), and from USDA NASS (NASS).</p><p><strong>Irrigation_data.zip:</strong></p><p>Irrigation amount data from three scenarios (CTRL, PGW, TAVE for early planting), and from USGS water use record (2005 and 2010).</p><p><strong>TempPrecPET.zip:</strong></p><p>temperature and precipitation and potential evapotranspiration data (PET) for the CTRL and PGW climate scenarios. </p>
Agricultural adaptation to reconcile food security and water sustainability under climate change: the case of cereals in Iran
<p>In this study, we simulate the crop yield and water footprint (WF) of major food crops of Iran on irrigated and rainfed croplands for the historical and the future climate. We assesse the effects of three agricultural adaptation strategies to climate change in terms of potential blue water savings. We then evaluate to what extent these savings can reduce unsustainable blue WF. We find that cereal production increases under climate change in both irrigated and rainfed croplands (by 2.6-3.1 and 1.4-2.3 million t y<sup>-1</sup>, respectively) due to increased yields (6.6%-78.7%). Simultaneously, the unit WF (m<sup>3</sup> t<sup>-1</sup>) tends to decrease in most scenarios. However, the annual consumptive water use increases in both irrigated and rainfed croplands (by 0.3-1.8 and 0.5-1.7 billion m<sup>3</sup> y<sup>-1</sup>, respectively). This is most noticeable in the arid regions, where consumptive water use increases by roughly 70% under climate change. Off-season cultivation is the most effective adaptation strategy to alleviate additional pressure on blue water resources, with blue water savings of 14-15 billion m<sup>3</sup> y<sup>-1</sup>. The second most effective is WF benchmarking, which results in blue water savings of 1.1-3.5 billion m<sup>3</sup> y<sup>-1</sup>. The early planting strategy is less effective, but still leads to blue water savings of 1.7-1.9 billion m<sup>3</sup> y<sup>-1</sup>. In the same order of effectiveness, these three strategies can reduce blue water scarcity and unsustainable blue water use in Iran under current conditions. However, we find that these strategies do not mitigate water scarcity in all provinces per se, nor all months of the year.</p>
ScienceDex guides
Understand access before you commit
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.