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ROOT _ScienceBase Catalog __National and Regional Climate Adaptation Science Centers ___South Central CASC ____FY 2016 Projects
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This project facilitated the implementation of a multiyear project to understand how climate variability and management practices influence soil microbial and nutrient dynamics within a no-till cotton production system with stubble management. Three fields at the R.N. Hooper farm in Petersburgh, TX were used for this project and continue to be monitored with funds from Cotton Inc. The three fields are center-pivot irrigated to compensate for rainfall variability as needed and depending upon water availability. The three fields were planted into the following crops for 2017 : Field 1 – corn following cotton; Field 2 – cotton following corn, and Field 3 – Wheat/mixed summer cover following wheat. The sizes of the...
Categories: Data;
Tags: Agroecosystems,
Landscapes,
Other Landscapes,
Soil Health,
Soil Microbial Dynamics,
The U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS) was used to assess the effects of changing climate and land disturbance on seasonal streamflow in the Rio Grande Headwaters (RGHW) region. Three applications of PRMS in the RGHW were used to simulate 1) baseline effects of climate (see RGHW-PRMS_baseline_input.zip), 2) effects of bark-beetle induced tree mortality (see RGHW-PRMS_BB_input.zip), and 3) effects of wildfire (see RGHW-PRMS_fire_input.zip), on components of the hydrologic cycle by hydrologic response unit (HRU) and subsequent seasonal streamflow runoff from April through September for water years 1980 through 2017. PRMS input files (control, climate-by-hru, data, parameter, dynamic...
Categories: Data;
Tags: Data Visualization & Tools,
Del Norte,
Rio Grande,
Rivers, Streams and Lakes,
Science Tools For Managers,
This file summarizes the data found in RG_obs_PTSWEQ.csv used in the analysis of the contribution of precipitation, temperature, and SWE to the interannual variability of runoff generation in the Rio Grande headwaters.
Global climate models (GCMs) are numerically complex, computationally intensive, physics-based research tools used to simulate our planet’s inter-connected climate system. In addition to improving the scientific understanding of how the large-scale climate system works, GCM simulations of past and future climate conditions can be useful in applied research contexts. When seeking to apply information from global-scale climate projections to address local- and regional-scale climate questions, GCM-generated datasets often undergo statistical post-processing generally known as statistical downscaling (hereafter, SD). There are many different SD techniques, with all using information from observations to address GCM...
Categories: Data;
Types: NetCDF OPeNDAP Service;
Tags: climate,
climate change,
climate projections,
climatologyMeteorologyAtmosphere,
dataset,
A new version of USGS’s FORE-SCE model was used to produce unprecedented landscape projections for four ecoregions in the Great Plains (corresponding to the area represented by the Great Plains Landscape Conservation Cooperative). The projections are characterized by 1) high spatial resolution (30-meter cells), 2) high thematic resolution (29 land use and land cover classes), 3) broad spatial extent (covering much of the Great Plains), 4) use of real land ownership boundaries to ensure realistic representation of landscape patterns, and 5) representation of both anthropogenic land use and natural vegetation change. A variety of scenarios were modeled from 2014 to 2100, with decadal timesteps (i.e., 2014, 2020, 2030,...
The U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS) was used to assess the effects of changing climate and land disturbance on seasonal streamflow in the Rio Grande Headwaters (RGHW) region. Three applications of PRMS in the RGHW were used to simulate 1) baseline effects of climate (see RGHW-PRMS_baseline_simulation.zip), 2) effects of bark-beetle induced tree mortality (see RGHW-PRMS_BB_simulation.zip), and 3) effects of wildfire (see RGHW-PRMS_fire_simulation.zip), on components of the hydrologic cycle by hydrologic response unit (HRU) and subsequent seasonal streamflow runoff from April through September for water years 1980 through 2017. Select PRMS output variables for each simulation are...
Categories: Data;
Tags: Data Visualization & Tools,
Del Norte,
Rio Grande,
Rivers, Streams and Lakes,
Science Tools For Managers,
Coastal wetland ecosystems are expected to migrate landward in response to accelerated sea-level rise. However, due to differences in topography and coastal urbanization extent, estuaries vary in their ability to accommodate wetland migration. The landward movement of wetlands requires suitable conditions, such as a gradual slope and land free of urban development. Urban barriers can constrain migration and result in wetland loss (coastal squeeze). For future-focused conservation planning purposes, there is a pressing need to quantify and compare the potential for wetland landward movement and coastal squeeze. For 41 estuaries in the northern Gulf of Mexico (i.e., the USA gulf coast), we quantified and compared...
Categories: Data;
Types: Citation,
Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Alabama,
Florida,
Gulf of Mexico,
Louisiana,
Mississippi,
Categories: Data
This data release supports the study by Sexstone and others (2020) and contains simulation output from SnowModel (Liston and Elder, 2006), a well-validated process-based snow modeling system. Simulations are for water years 1984 through 2017 (October 1, 1983 through September 30, 2017) across a 11,200 square kilometer model domain in the San Juan Mountains of southwestern Colorado, United States that encompasses the Rio Grande Basin headwaters (HUC8 13010001). This data release also contains supporting field-based snow and meteorological station observations collected within the model domain during water years 2016 and 2017 that were used to evaluate SnowModel simulations. Sexstone and others (2020) provide details...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Colorado,
Rio Grande headwaters,
USGS Science Data Catalog (SDC),
Upper Rio Grande,
climatology,
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