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28 results for “environmental flows”
Data for "Globally widespread and increasing violations of environmental flow envelopes"
<p>Data and code for</p> <p><strong>Globally widespread and increasing violations of environmental flow envelopes</strong></p> <p>Vili Virkki*#, Elina Alanärä#, Miina Porkka, Lauri Ahopelto, Tom Gleeson, Chinchu Mohan, Lan Wang-Erlandsson, Martina Flörke, Dieter Gerten, Simon N. Gosling, Naota Hanasaki, Hannes Müller Schmied, Niko Wanders, and Matti Kummu*</p> <p># equal contribution to the article<br> * Correspondence to: Vili Virkki (vili.virkki@aalto.fi), Matti Kummu (matti.kummu@aalto.fi)</p> <p><br> link to published version: https://hess.copernicus.org/articles/26/3315/2022/</p> <p><strong>Please cite the published version of the article when using these data.</strong></p> <p><strong>See readme.txt in data for a detailed description of attached files.</strong></p>
Data for: Water system simulation modeling with hydropower optimization and environmental flows: An example with Pywr
<p>This dataset was used in the CenSierraPywr model created for the project "Optimizing Hydropower Operations While Sustaining Ecosystem Functions in a Changing Climate", for the California Energy Commission. Specifically, this data is to support reproducibility of the article describing the basic methods (Rheinheimer et al., in review). The model was built in Pywr, an open-source, linear programming-based Python package for modeling basin-scale water systems in the Central Sierra Nevada, California. Here, we focus on the Stanislaus and Upper San Joaquin River basins as they have high elevation hydropower typically operated to maximize revenue. CenSierraPywr consists of daily water allocations that include both hydroeconomic drivers for hydropower and more advanced environmental flows. Piecewise linear electricity prices from simulated hourly price data are used to drive discretionary hydropower, while environmental flows include the addition of ramping rates. Hydrological inputs include runoff data at the sub-basin level, based on the historical (1950 to 2011) daily gridded (1/16 degree) runoff data generated by the Variable Infiltration Capacity (VIC) hydrologic model developed by Livneh et al. (2013), forced with observed meteorological data and bias-corrected using local gauge data. All data inputs for reproducibility of CenSierraPywr for the Stanislaus and Upper San Joaquin Rivers are included, including original and preprocessed electricity and hydrological data and management-related data specific to certain hydropower projects or facilities.</p>
Environmental Flows Turbine Optimization
<p>This is a dataset of the results from determining the capacity (MW) of potential minimum flow turbines based on available environmental flows. This includes the turbine capacity from two methods of data processing, as well as the iterative screening envelopes to determine locations of likely opportunities for implementing these environmental flow turbines. </p> <p>Cite this dataset as well as the manuscript by the authors that is available through Renewable and Sustainable Energy Reviews.</p>
Fig. 5 in Application of the physical habitat simulation for fish species to assess environmental flows in an Atlantic Forest Stream in South-eastern Brazil
Fig. 5. Average habitat suitability index –HSI– in the upper and lower reach of the riacho São Pedro, for the three fish species.
Fig. 6 in Application of the physical habitat simulation for fish species to assess environmental flows in an Atlantic Forest Stream in South-eastern Brazil
Fig. 6. Weighted usable area (WUA) in the upper and lower reach of the riacho São Pedro, for the three fish species.
Fig. 4 in Application of the physical habitat simulation for fish species to assess environmental flows in an Atlantic Forest Stream in South-eastern Brazil
Fig. 4. Habitat suitability curves for depth (m), mean water column velocity (m/s) and type of substrate for the three fish species in the riacho São Pedro. Substrate types are; 1- large boulder, 2- boulder, 3- cobble, 4- gravel, 5- fine gravel, 6- sand and 7- vegetation.
Fig. 3 in Application of the physical habitat simulation for fish species to assess environmental flows in an Atlantic Forest Stream in South-eastern Brazil
Fig. 3. Frequencies of habitat availability by classes of depth (m), mean velocity (m/s) and type of substrate (1- large boulder; 2- boulder; 3- cobble; 4- gravel; 5- fine gravel; 6- sand and 7- vegetation), obtained by direct survey in the riacho São Pedro.
Fig. 1 in Application of the physical habitat simulation for fish species to assess environmental flows in an Atlantic Forest Stream in South-eastern Brazil
Fig. 1. Map of the rio Guandu basin, with indication of the studied reach in riacho São Pedro. Solid dash = small substation of CEDAE (Water and Sewer Treatment Works of Rio de Janeiro State). WTP: Water Treatment Plant.
Fig. 2 in Application of the physical habitat simulation for fish species to assess environmental flows in an Atlantic Forest Stream in South-eastern Brazil
Fig. 2. Isometric view of the cross-sections in the two target reaches of the riacho São Pedro. Grey color indicates water; solid line indicates the contour of the cross-section (in wet areas and banks).
Safe and Just Earth Systems Boundaries for Surface Water: Hydrologic Alteration of Environmental Flows
<p>Title: <strong>Safe and Just Earth Systems Boundaries for Surface Water: Hydrologic Alteration of Environmental Flows</strong> Author: Pamela A. Green (<a href="mailto:pg@pamelaagreen.com">pg@pamelaagreen.com</a>), Advanced Science Research Center, CUNY, New York, NY USA <a href="https://orcid.org/0009-0006-7803-8182">https://orcid.org/0009-0006-7803-8182</a></p> <p>The python Jupyter Notebook <strong>SafeJustEarthSysBnd_EstressCUNY-Griffith2022-23.ipynb</strong> and accompanying data sets represent spatial modelling for development of the safe and just surface water target for Working Group 3 of the Earth Commission for the Earth Commission Long Report and the "Safe and Just Earth Systems Boundaries" publication. The surface water target includes spatial modelling of the extent of global-scale hydrological alteration of environmental flows.</p> <p>All input datasets required to run the model are located under the <strong>ModelInput</strong> folder with raster data in zipped format to minimize space requirements. The code extracts the zipped files and then deletes the uncompressed files upon completion. All model outputs are located under the <strong>ModelOutput</strong> folder.</p> <p>Please reference the <strong>README.xlsx</strong> file for a full listing of the model input and output data files.</p>
Data for: Water system simulation modeling with hydropower optimization and environmental flows: An example with Pywr
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Data from: Does gene flow aggravate or alleviate maladaptation to environmental stress in small populations?
Environmental change can expose populations to unfamiliar stressors, and maladaptive responses to those stressors may result in population declines or extirpation. Although gene flow is classically viewed as a cause of maladaptation, small and isolated populations experiencing high levels of drift and little gene flow may be constrained in their evolutionary response to environmental change. We provide a case study using the model Trinidadian guppy system that illustrates the importance of considering non-adaptive forces (i.e., gene flow and genetic drift) when predicting (mal)adaptive response to acute stress. We compared population genomic patterns and acute stress responses of inbred guppy populations from headwater streams either with or without a recent history of gene flow from a more diverse mainstem population. Compared to 'no-gene flow' analogues, we found that populations with recent gene flow showed higher genomic variation and increased stress tolerance – but only when exposed to a stress familiar to the mainstem population (heat shock). All headwater populations showed similar responses to a familiar stress in headwater environments (starvation) regardless of gene flow history, whereas exposure to an entirely unfamiliar stress (copper sulphate) showed population-level variation unrelated to environment or recent evolutionary history. Our results suggest that (mal)adaptive responses to acutely stressful environments are determined in part by recent evolutionary history and in part by previous exposure. In some cases, gene flow may provide the variation needed to persist, and eventually adapt, in the face of novel stress.
Warming increases environmental DNA (eDNA) removal rates in flowing waters
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Data from: Does gene flow aggravate or alleviate maladaptation to environmental stress in small populations?
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Can environmental flows moderate riparian invasions? The influence of seedling morphology and density on scour losses in experimental floods
Predicting plant mortality during floods remains a key area of uncertainty for both river managers and ecologists, particularly how flood hydraulics and sediment dynamics interact with the plants’ own traits to influence their vulnerability to scour and burial. The three datasets in this archive were collected from a series of flume experiments that took place at the University of California, Berkeley’s Richmond Field Station. The flume experiments are part of a larger study, funded by NSF (EAR#1024820) that quantified reciprocal effects and feedbacks between riparian seedlings and river morphodynamics, using sand-bed rivers in the U.S. Southwest as the reference system. To quantify different plant species’ vulnerability to flooding across a range of plant sizes, patch densities, and sediment condition (equilibrium transport versus sediment deficit), we ran 10 experimental floods using live seedlings of cottonwood and tamarisk, which have contrasting morphologies. The three datasets include: 1. Plant responses (dislodgement or burial) to the experimental floods and plant size (e.g. stem height, root length, and dry weight) for all plants tested during the flume runs (N = 484, comprising 326 cottonwood and 158 tamarisk); 2. Plant morphological traits (e.g. frontal area, bending force, and root diameter) for a random subset of seedlings (n = 90, comprising 47 cottonwood and 43 tamarisk); and 3. Frontal area density for the same seedling subset.
Global environmental flow requirement estimates based on multimodel simulations
<p><a href="../api/files/5d8d266f-99bd-4351-8c7a-684f0bc0df90/global_natural_discharge_multimodel_medians.nc4">global_natural_discharge_multimodel_medians.nc4</a>: multimodel medians of simulations of monthly naturalized streamflow during 1971-2010 provided by six global hydrological models (DBH, H08, LPJmL, MATSIRO, PCR-GLOBWB, and WaterGAP), derived from the ISIMIP2a dataset (https://doi.org/10.5880/PIK.2017.010).</p> <p>Global environmental flow requirement estimated with different methods: Qxx (Q90, Q50), Smakhtin (Smakhtin et al. 2004), Tennant (Tennant 1976), Tessmann (Tessmann 1980), VMF (variable monthly flow, Pastor et al. 2014). The unit for the EFR data is m3 s-1.</p> <p>Related reference<br>Liu, X., Liu, W., Liu, L., Tang, Q., Liu, J., & Yang, H. (2021). Environmental flow requirements largely reshape global surface water scarcity assessment. Environmental Research Letters, 16(10), 104029.</p>
Data From "Radar-Based Deep Learning for Debris Flow Identification amid the Environmental Disturbances"
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Data from: Coronary blood flow influences tolerance to environmental extremes in fish
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Data from: Divergent natural selection with gene flow along major environmental gradients in Amazonia: insights from genome scans, population genetics and phylogeography of the characin fish Triportheus albus
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Productivity of riparian Populus forests: satellite assessment along a prairie river with an environmental flow regime
<p>In semi-arid regions, the growth and survival of cottonwoods (riparian Populus species) depend on river water supplementing the limited precipitation. Indicators of growth and productivity are needed to assess how altered streamflow regimes on regulated rivers impact cottonwood trees and the riparian forest ecosystems they support. Satellite imagery from the Landsat program was used to make historical assessments of ecosystem productivity in a riparian cottonwood forest along a regulated prairie river in southern Alberta, Canada from 1984 to 2020, with an environmental flow regime that increased the minimum flows implemented in 1993. A version of the near-infrared reflectance of vegetation scaled with incoming sunlight (NIRvP) was calculated from Landsat images to provide a proxy for primary production. NIRvP was validated against gross primary production measurements from eddy covariance and cottonwood basal area increment measurements from tree ring analyses. Streamflow and weather data were used to assess what environmental conditions drive year-to-year variations in NIRvP.</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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