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The USGS Forecasting Scenarios of Land-use Change (FORE-SCE) model was used to produce an agricultural biofuel scenarios for the Northern Glaciated Plains, from 2012 to 2030. The modeling used parcel data from the USDA's Common Land Unit (CLU) data set to represent real, contiguous ownership and land management units. A Monte Carlo approach was used to create 50 unique replicates of potential landscape conditions in the future, based on a agricultural scenario from the U.S. Department of Energy's Billion Ton Update. The data are spatially explicit, covering the entire Northern Glaciated Plains ecoregions (an EPA Level III ecoregion), with a spatial resolution of 30-meters and 22 unique land-cover classes (including...
Types: Citation,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: FORE-SCE,
Great Plains,
Land Cover,
Minnesota,
Model,
In this study, we combined two actual evapotranspiration datasets (ET), one obtained from a root zone water balance model and another from an energy balance model, to partition annual ET into green (rainfall-based) and blue (surface/groundwater) water sources. Time series maps of green water ET (GWET) and blue water ET (BWET) are produced for the conterminous United States (CONUS) over 2001–2015.
Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008-2013. In this investigation we wanted to expand the temporal coverage of the NASS CDL archive back to 2000 by creating yearly NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million crop sample records to train a classification tree algorithm and to develop a crop classification model (CCM). The model was used to create...
Types: Citation;
Tags: Conterminous United States,
Crop Cover,
Cropland Data Layers,
Decision Tree Classifier,
NASS CDL,
Historical (1984-2014) Landsat-based ET maps were generated for Palo Verde Irrigation District (PVID) and eight other sub-basins in parts of Middle and Lower Central Valley, California. A total of 3,396 Landsat images were processed using the Operational Simplified Surface Energy balance (SSEBop) model that integrates weather and remotely sensed images to estimate monthly and annual ET within the study areas over the 31 years. Model output evaluation and validation using gridded-flux data and water balance ET approaches indicated relatively strong association between SSEBop ET and validation datasets. Historical trend analysis of seven agro-hydrologic variables were done using the Seasonal Mann-Kendall test.
The landscape of the conterminous United States has changed dramatically over the last 200 years, with agricultural land use, urban expansion, forestry, and other anthropogenic activities altering land cover across vast swaths of the country. While land use and land cover (LULC) models have been developed to model potential future LULC change, few efforts have focused on recreating historical landscapes. Researchers at the US Geological Survey have used a wide range of historical data sources and a spatially explicit modeling framework to model spatially explicit historical LULC change in the conterminous United States from 1992 back to 1938. Annual LULC maps were produced at 250-m resolution, with 14 LULC classes....
This dataset provides an assessment of the differential heating in the Indian Ocean (IO) and the subsequent modulation of the Ganges and Brahmaputra precipitation. Indo-Pacific sea surface temperature dynamics play a prominent role in Asian summer monsoon variability. Using 28 years of remote sensing observations, we demonstrate that (i) the tropical west-east differential heating in the IO influences the Ganges precipitation and (ii) the north-south differential heating in the IO influences the Brahmaputra precipitation. The El Niño phase induces warming in the warm pool of the IO and exerts more influence on Ganges precipitation than Brahmaputra precipitation. The analyses indicate that both the magnitude and...
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