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45 results for “hillslope”
Upland Hillslope Groundwater Subsidy Affects Low-flow Storage-Discharge Relationship
<p>The package provides data and codes used in the following publication " Upland Hillslope Groundwater Subsidy Affects Low-flow Storage-Discharge Relationship". The publication is now under review in Water Resources Research Journal</p>
Porous tension-cup lysimeter depths and soil water chemistry from 9 Hillslope Project sites in Macon County, North Carolina, within the Upper Little Tennessee River Basin
Porous tension-cup lysimeters were installed at 9 sites throughout Macon County beginning in 2011. Sites represented a gradient of land use, including relatively undisturbed forests, valley bottomlands in agriculture, and mountain developments. Eighteen lysimeters were placed at each site - 9 were shallow lysimeters located in the A horizon and 9 were deep lysimeters located in the B horizon. Collections were made every other week and samples were composited monthly for chemistry. The depths of the lysimeters were noted.
Maximum soil depths from 9 Hillslope Project sites in Macon County, North Carolina, within the Upper Little Tennessee River Basin
Maximum soil depths were assessed as part of the soil bulk density and soil chemistry studies at the hillslope plots in Macon County, North Carolina. There were 9 hillslope representing a gradient of development, including forested, valley agriculture, and mountain housing developments. A soil probe was used to estimate the maximum soil depth of each of the 12 10 x 10-m plots at each site.
Tree, shrub, and herb data from 10 Hillslope Project sites located in Macon County, North Carolina, within the Upper Little Tennessee River Basin
Vegetation was surveyed on 10 sites in the upper Little Tennessee River watershed in Macon County, North Carolina during the summer of 2012. The sites represent a gradient of development, including forested sites, agricultural sites, and exurban sites. All woody vegetation >2.5 cm diameter at breast height (DBH) was measured and identified within twelve 10 x 10 m plots at each site. Woody shrubs >0.5 m in height and <2.5 cm DBH were counted and identified within a 1x10 m transect in each plot. Herbs and woody plants <0.5m in height were identified and percent cover estimated in 3 1 x 1 m subplots located within each of the larger 10 x 10 m plots.
GIS vector data for sample locations and plots associated with the Hillslope Study in Macon County, NC
The Hillslope Study sites represent a gradient of landscapes, including forested, valley agriculture, and mountain housing developments. These locations and plots were used to collect samples of various matrices for numerous analyses at differing intervals. The data set consists of Open Office spreadsheet and other files that document all the Hillslope Study locations.
Coweeta hillslope soil model drainage experiments 2016-17
This data file has Time (days) and Outflow (liters/day) for all iterations of the drainage experiments (i.e., original circa 1963, experiment replicates circa 2016-2017, and HYDRUS model simulations circa 2016) performed on the experimental hillslope soil model described in Hewlett and Hibbert (1963) at Coweeta Hydrologic Laboratory.
SGS-LTER CPER Hillslope Soil Spatial Variability on the Central Plains Experimental Range, Nunn, Colorado, USA 1983-1984
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/83515. CPER Hillslope Soil Spatial Variability - Pedons were characterized along three parallel transects, spaced at approximate 40 m intervals perpendicular to a hillslope at the CPER. Pedons were described at 7 landscape positions along each transect: summit, shoulder, upper backslope, middle backslope, lower backslope, footslope, and toeslope. Pedons were described by genetic horizon according to the standards of the National Cooperative Soil Survey. Analyses included: particle size; organic C; total N; organic and total P. Bulk Density was estimated using particle size and organic C data, according to: Rawls, W.J. 1983. Estimating soil bulk density from particle size analysis and organic matter content. Soil Sci. 135: 123-125.
Hillslope Roughness Reveals Forest Sensitivity to Extreme Winds (Codes and Data)
<p>These are data are python scripts for creating figures in Doane et al., 2022 (Hillslope Roughness Reveals Forest Sensitivity to Extreme Winds). </p>
Data and model output for "Evidence of subsurface control on the coevolution of hillslope morphology and runoff generation"
<p>Data, model output, and scripts supporting the manuscript:</p> <p>Litwin, D. G., & Harman, C. J. (2024) Evidence of subsurface control on the coevolution of hillslope morphology and runoff generation. <em>Water Resources Research</em>, 60, e2024WR037301. https://doi.org/10.1029/2024WR037301</p>
Data from: Interplay between rainfall and hillslope hydrology determines drought resistance of tropical vegetation
<p><span>Droughts are predicted to increase in both frequency and intensity by the end of the 21st century, but ecosystem response is not expected to be uniform. At the landscape scale, ecosystem response to drought is highly heterogeneous. Here we assess the importance of the hill-to-valley hydrologic gradient in shaping vegetation hydraulic properties related to drought resistance for three locations across a rainfall seasonality gradient in South America. For this, we use hydraulic traits related to xylem resistance to embolism and compare the functional composition and diversity of tree communities. We show that the hydrologic gradient systematically selects for community assemblages that are more vulnerable to embolism in valleys, regardless of rainfall. Under the same rainfall regime, diversity in resistance to embolism is higher on hills than valleys, suggesting that strategies to cope with drought are more important on hills. With increasing seasonality, diversity in embolism resistance increases on hills and decreases in valleys. Our results show that differential groundwater access from hilltops to valleys select for distinctive hydraulic properties, potentially explaining species turnover along topographical gradients. Incorporating this relationship might improve the representation of vegetation in climate models and the prediction of how different communities will respond to extreme droughts.</span></p>
Data for 'Rethinking variability in bedrock rivers: sensitivity of hillslope sediment supply to precipitation events modulates bedrock incision during floods'
<p>This is the repository for model code, sample data, and plotting scripts for the OTTER model for Python.</p> <p>The file OTTERPy.py contains the actual model code</p> <p>The file OTTERPlottingFuncs.py contains a few scripts for plotting model results.</p> <p>The four sample data files in the repository are results from two long (1.5million model year) runs at different rock uplift rates which took several days to run on the IU Bloomington Quartz supercomputing cluster. This data should be viewed and plotted using the OTTERPlottingFuncs.py script. See that code for information on how to select which model to plot.</p> <p> </p> <pre><code>Glossary of variables - this is pretty close to exhaustive, there are a probably a couple of throwaway variables not listed here. a: Sternberg's law multiplier Ah: drainage area from Hack's Law (m^2) beta: fraction of sediment transported as bedload from 0 to 1 D: grain size at each node (m) dA: change in drainage area from node to node (m^2) depth_thresh: sediment depth at which bedrock erosion can occur Do: initial grain size Do: grain size at headwaters (m) dQs: change in sediment supply from node to node dt: time step (years) dx: space step (m) dz_b: bedrock erosion at each node dz_s: change in sed depth dz_b_t: bedrock erosion saved through time dz_b_store: bedrock erosion stored dz_s_store: sed depth change stored eQ: exponent for scaling Qw from Ah eroded_sedsup: sediment created by bedrock erosion eW: exponent for scaling W from Qw F: fractional bedrock exposure g: gravitational acceleration (M/s^2) H: water depth Hc: Hack's Law constant He: Hack's law Exponent initial_sedsup: Sediment supply in first 10k yr (equal to uplift) kf: bedrock erodibility kQ: constant for scaling Qw from Ah kv: parameter controlling discharge variability - Crave & Davy, 2001. Lower kv is more variable kw: lateral bedrock erosion constant kWid: constant for scaling W from Qw last_z: elevation at channel mouth lmbda: sediment porosity n: manning's roughness coefficient onlyonce: changes from 0 to 1 to make sure the uplift pulse only happens one time onoff: turns sediment on and off entirely onoffsedvar: turns stochastic sediment on and off Qs: sediment supply along the length of the river Qs_down: downstream sediment flux at each node Qt: sediment transport capacity Qw: water discharge Qwo: initial water discharge QwScale: array of scalar multipliers for Qw, from the chosen distribution R: effective density of submerged sediment rho_w: density of water (kg/m^3) rho_s: density of sediment (kg/m^3) savesteps: at what time should we save outputs? sed_depth: depth of seidment at each node (m) SedStore: storing snapshots of sediment thickness through time slope: river gradient (negative usually) SlopeStore: storing snapshots of channel slope through time tarray: array of model time tau_b: basal shear stress tau_c: critical shields criterion for initiation of sediment motion time: model duration (years) topo: channel elevation (bedrock + sediment) upinc: size up uplift pulse, as a multiplier of initial uplift rate upinctime: when should the pulse happen? (years) uplift: uplift field across the entire domain uprate: initial uplift rate, if using constant uplift across domain W: channel width WidthStore: storing snapshots of channel width through time Wo: initial channel width yr2sec: number of seconds in a year z: bedrock channel elevation ZStore: storing snapshots of bedrock elevation through time</code></pre>
Data from: Interplay between rainfall and hillslope hydrology determines drought resistance of tropical vegetation
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Data from: Using a trait-based approach for assessing the vulnerability and resilience of hillslope seep wetland vegetation cover to disturbances in the Tsitsa River catchment, Eastern Cape, South Africa
<p>Hill slope seep wetlands are ecologically and economically important ecosystems as they supply a variety of ecosystem services to society. In South Africa, livestock grazing is recognised as one of the most important disturbance factors changing the structure and function of hill slope seep wetlands. This study sought to investigate the potential effect of livestock grazing on the resilience and vulnerability of hillslope seep wetland vegetation cover using a trait based approach (TBA). Changes in vegetation cover were used as a surrogate for indicating grazing intensity. The degree of human disturbances was assessed using the Anthropogenic Activity Index (AAI). A TBA was developed using seven plant traits, resolved into 27 trait attributes. Based on the developed approach, plant species were grouped into vulnerable and resilient groups in relation to grazing pressure. It was then predicted that species belonging to the vulnerable group would be less dominant at the highly disturbed sites, as well as in the winter season when grazing pressure is at its peak. The approach developed enabled accurate predictions of the responses of hillslope plant species to grazing pressure seasonally, but spatially, only for the summer season. The predicted responses during the winter season across sites did not match the observed results, which could be attributed to the difficulty in species identification and accurate estimation of vegetation cover during winter. Overall, the approach developed here provides a general framework for applying the TBA and can thus be tested and applied elsewhere.</p>
Representative Hillslope Geomorphic Parameters 0.9x1.25
A dataset of global geomorphic parameters for use in land models having a representative hillslope parameterization.
Simulations Supporting 'Representing Intra-Hillslope Lateral Subsurface Flow in the Community Land Model', JAMES, 2019
<p>CLM5 Simulations used for the paper "Representing Intra-Hillslope Lateral Subsurface Flow in the Community Land Model". Files are in NetCDF format.</p> <p>Filenames beginning with 'RME_' contain single point simulations for the Reynolds Mountain East catchment. Filenames beginning with 'Global_' contains global simulations used in the sensitivity study. Filenames beginning with 'surfdata_' contain input surface data files used in CLM5 Hillslope simulations.</p>
Description of Mont-Vert hillslope database: measured properties along soil cores and associated metadata
<p>This dataset includes data and metadata of twenty soil cores collected in Mont-Vert banana plantation (Le Robert, Martinique, France) in February 2023. These data were collected in order to study the chlordecone (an organochlorine insecticide) redistribution along a cultivated hillslope. To this end, radiocesium activities (artificial radionuclide) and chlordecone concentrations were measured in soil core subsamples (5-cm increments). </p>
Geomechanical and hydrogeological models for different hillslopes and tectonic stresses
<p>This dataset contains the data used in the manuscript “Impacts of stress-dependent hydraulic properties on hillslope-scale groundwater flow”. The geomechanical models (RS_SXX) can be open with RS2 - Rocsience, and the hydrogeological models can be open using MODFLOW softwares (flopy recomended).</p>
Codes and dataset used in the manuscript entitled "Quantifying time-variant travel time distribution by multi-fidelity model in hillslope under nonstationary hydrologic conditions"
<p>This contains the codes and dataset for the manuscript entitled "Quantifying time-variant travel time distribution by multi-fidelity model in hillslope under nonstationary hydrologic conditions". Detailed information about the dataset is described in the Readme.txt file.</p>
Data from: Using a trait-based approach for assessing the vulnerability and resilience of hillslope seep wetland vegetation cover to disturbances in the Tsitsa River catchment, Eastern Cape, South Africa
Open the record for dataset details and reuse information.
State of Iowa hydrological network (90m hillslopes)
<p>This dataset covers State of Iowa (USA), decomposed into 600,000 hillslopes using the algorithm developed by Mantilla and Gupta (2005). The data is organized as a hierarchical network structure.</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
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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
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