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13 results for “critical zone”
Exploring the critical zone heterogeneity and the hydrological diversity using an integrated ecohydrological model in three contrasted long-term observatories
<p>These files provide useful data and supplementary material associated with the publication 'Exploring the critical zone heterogeneity and the hydrological diversity using an integrated ecohydrological model in three contrasted long-term observatories' (MNT information, atmospheric forcings, R scripts used to process and draw the graphs from the EcH2O-iso simulations, and observed water discharges).</p>
Critical Zone Observatory in Pianosa Island: Accumulation chambers n.1 and n.2 (27/03/2023-03/04/2024)
<p>The installed instrumentation allows CO2 flux measurements from soil (emission and absorption/uptake) by non steady state closed dynamic accumulation Chambers.</p> <p>The aim is to understand if the NEE (Net Ecosystem Exchange) is increasing or decreasing and which parameters most affect this important index. More over, the NEE parameter is extremely useful in climate models.</p> <p>In particular chamber n.1 is a dark chamber and measures the ecosystem respiration while chamber n.2 is a transparent chamber and measures the NEE. The difference between the flux measured by chamber n.2 and that measured by chamber n.1 allows to calculate the GPP (Gross Primary Production).</p> <p>The dataset includes the Net Ecosystem Exchange (NEE), Ecosystem Respiration (ER), air temperature and atmospheric pressure inside the chamber, soil temperature and soil humidity next to the chamber. It is also available the R2 of the regression line of the CO2 concentration versus time, of each chamber.</p> <p>The data was collected thanks to EU - Next Generation EU Mission 4 "Education and Research - Component 2: "From research to business" - Investment 3.1: "Fund for the realisation of an integrated system of research and innovation infrastructures" - Project IR0000032 - ITINERIS - Italian Integrated Environmental Research Infrastructures System - CUP B53C22002150006.</p>
Luquillo Critical Zone Observatory (LCZO) Data repository on HydroShare
Data archive for the Luquillo Critical Zone Observatory (LCZO), Puerto Rico. Active from 2009 to 2020. The archive is here: https://www.hydroshare.org/group/144 LCZO focuses on how Critical Zone processes and water balances differ in tropical landscapes with contrasting bedrock but similar climatic and environmental histories. Our infrastructure, sampling strategy, and data management system include watersheds underlain by granodiorite (GD) and volcaniclastic (VC) bedrock in the natural laboratory of the Luquillo Mountains, Puerto Rico. LCZO is one of ten NSF-supported critical zone observatories. The archive is here: https://www.hydroshare.org/group/144 An additional dataset on Forest and Ground Cover classification, DEM, and Beryllium-10 data for the Luquillo Experimental Forest has been published here: https://doi.org/10.4211/hs.0181f4621d184a89a625ee16dd9858a6 An additional datasets for LCZO -- Stream Water Chemistry, Meteorology -- Environmental Monitoring -- Luquillo Mountains -- (2014-Ongoing) https://www.hydroshare.org/resource/b05e1645887f4122a284719bb6cb70dc/ Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Southern Sierra Critical Zone Observatory (SSCZO), Providence Creek meteorological data, soil moisture and temperature, snow depth and air temperature
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Disentangling the impact of event- and annual-scale precipitation extremes on critical-zone hydrology in semiarid loess: A case study in apple tree plantation
<p>The dataset is the basic data of the author's paper ' Disentangling the impact of event-and annual-scale precipitation extremes on critical-zone hydrology in semiarid loess - a case study in apple tree plantation '. The main content of this paper is to study the hydrological effect of extreme precipitation on the critical area of semi-arid loess. Taking apple plantation as an example, the data set includes the soil moisture and soil temperature data monitored in the field and the apple tree transpiration data. The measured data are used to calibrate and verify the model used in this paper. The water vapor flux, apple tree evapotranspiration and soil leakage data of the simulated soil profile are also included to analyze the hydrological effect of extreme precipitation on the critical area of loess.</p>
Southern Sierra Critical Zone Observatory (SSCZO), Wolverton Creek meteorological data, soil moisture and temperature
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Influence of Subsurface Critical Zone Structure on Hydrological Partitioning in Mountainous Headwater Catchments [Dataset]
<p>There are the data and code for the paper:Influence of Subsurface Critical Zone Structure on Hydrological Partitioning in Mountainous Headwater Catchments</p>
Catchment scale soil variably in Marshall Gulch, Santa Catalina Mountains Critical Zone Observatory (CZO), Arizona, 2012
The quantification and prediction of soil properties is fundamental to further understanding the Critical Zone (CZ). In this study we aim to quantify and predict soil properties within a forested catchment, Marshall Gulch, AZ. Input layers of soil depth (modeled), slope, Saga wetness index, remotely sensed normalized difference vegetation index (NDVI) and national agriculture imagery program (NAIP) bands 3/2 were determined to account for 95% of landscape variance and used as model predictors. Target variables including soil depth (cm), carbon (kg/m 2 ), clay (%), Na flux (kg/m 2 ), pH, and strain are predicted using multivariate linear step-wise regression models. Our results show strong correlations of soil properties with the drainage systems in the MG catchment. We observe deeper soils, higher clay content, higher carbon content, and more Na loss within the drainages of the catchment in contrast to the adjacent slopes and ridgelines.
Snow-Off Digital Terrain Model (DTM) from 2010 LiDAR for the Boulder Creek Critical Zone Observatory (CZO), Colorado
This 1m Digital Terrain Model (DTM) is a snow-off DTM derived from bare-ground Light Detection and Ranging (LiDAR) point cloud data from August 2010 for the Boulder Creek Critical Zone Observatory (CZO), near Boulder Colorado. This dataset is better suited for derived layers such as slope angle, aspect, and contours. The DTM was created from 1,375 LiDAR point cloud tiles subsampled from 10 points/m2 to 1-meter postings, acquired by the National Center for Airborne Laser Mapping (NCALM) project. This data was collected in collaboration between the Boulder Creek CZO and NCALM, both funded by the National Science Foundation (NSF). The DTM has the functionality of a map layer for use in Geographic Information Systems (GIS) or remote sensing software. Total area imaged is 598.92 km^2. The LiDAR point cloud data was acquired with an Optech Gemini Airborne Laser Terrain Mapper (ALTM) and mounted in a Piper Twin PA-31 Chieftain with Inertial Measurement Unit (IMU) at a flying height of 600 m. Data from four GPS (Global Positioning System) ground stations were used for aircraft trajectory determination. The continuous DTM surface was created by mosaicing and then kriging 0.5 x 1 km LiDAR point cloud LAS-formated tiles using Golden Software's Surfer 8 Kriging algorithm. Horizontal accuracy is at least, but usually better than, 11 cm RMSE at 1 sigma and vertical accuracy is 5-30 cm RMSE at 1 sigma. The layer is available in IMAGINE format approx. 4 GB of data. It has a UTM zone 13 projection, with a NAD83 horizonal datum and a NAVD88 vertical datum, with FGDC-compliant metadata. A shaded relief model was also generated. A similar layer, the Digital Surface Model (DSM), is a first-stop elevation layer. Accessory layers consist of index map layers for point cloud tiles and flight lines, each with detailed attribute information such as acquisition date and tile file name. The DTM is available through an unrestricted public license. Other LiDAR DSMs, DTMs, and point cloud data ava
Near-Surface Full-Waveform Inversion Reveals Bedrock Control on Critical Zone Architecture Resources
<p>Near-Surface Full-Waveform Inversion Reveals Bedrock Control on Critical Zone Architecture Resources</p> <p> </p>
Supplemental data - Ancient clays support contemporary biogeochemical activity in the Critical Zone
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Spatiotemporal transcriptome analysis reveals critical roles for mechano-sensing genes at the border zone in remodeling after myocardial infarction
GEO Series GSE176092. Mus musculus. 1118 samples. Type: Expression profiling by high throughput sequencing.
Response of hydrological processes to event- and annual-scale precipitation extremes in the critical zone of the hillside surface
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