A Conterminous United States Multilayer Soil Characteristics Dataset for Regional Climate and Hydrology Modeling
D. A. Miller,R. A. White +1 more
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In this paper, the authors developed a multilayer soil characteristics dataset for the conterminous United States (CONUS-SOIL) that specifically addresses the need for soil physical and hydraulic property information over large areas.Abstract:
Soil information is now widely required by many climate and hydrology models and soil-vegetation-atmosphere transfer schemes. This pa- per describes the development of a multilayer soil characteristics dataset for the conterminous United States (CONUS-SOIL) that specifically addresses the need for soil physical and hydraulic property information over large areas. The State Soil Geographic Database (STATSGO) developed by the U.S. De- partment of Agriculture-Natural Resources Conservation Service served as the starting point for CONUS-SOIL. Geographic information system and Perl computer programming language tools were used to create map coverages of soil properties including soil texture and rock fragment classes, depth-to-bed- rock, bulk density, porosity, rock fragment volume, particle-size (sand, silt, and clay) fractions, available water capacity, and hydrologic soil group. In- terpolation procedures for the continuous and categorical variables describing these soil properties were developed and applied to the original STATSGO data. In addition to any interpolation errors, the CONUS-SOIL dataset reflects the limitations of the procedures used to generate detailed county-level soilread more
Citations
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Journal ArticleDOI
Mercury in soils of the conterminous United States: patterns and pools
Connor I. Olson,Ben M. Geyman,Colin P. Thackray,David P. Krabbenhoft,Michael T. Tate,Elsie M. Sunderland,Charles T. Driscoll +6 more
TL;DR: In this paper , the authors present a spatial analysis of soil mercury from a large soil survey (three horizons, ∼4800 sites) across the conterminous United States conducted by the U.S. Geological Survey.
Proceedings ArticleDOI
Context-aware Deep Representation Learning for Geo-spatiotemporal Analysis
TL;DR: In this article, a semi-supervised attention-based deep representation model was proposed to extract spatial and temporal variations in the geo-spatiotemporal data for crop yield prediction.
Journal ArticleDOI
An Evapotranspiration Assimilation Method Based on Ensemble Kalman Filter and A Trous Wavelet
TL;DR: In this paper, a perturbed ensemble Kalman filter (PEKF) and a trous wavelet transform (AWT) integrated method are proposed to implement the evapotranspiration assimilation.
ReportDOI
Physical properties of highly organic soils and their importance to mobility considerations
TL;DR: In this paper, the generalized plate theories, including failure criteria, for linear elastic, plastic, and modified plastic are presented, and the authors discuss the need for better mobility predictions in regions where seasonality is important and highly organic soils are prevalent.
4.4 Development of a 30-Year Soil Moisture Climatology for Situational Awareness and Public Health Applications
TL;DR: In this article, a soil moisture climatology over the CONUS at high spatial resolution is presented to provide a valuable source of soil moisture information to the CDC for monitoring conditions that could favor the development of Valley Fever.
References
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Journal ArticleDOI
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