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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Coupling an Advanced Land Surface–Hydrology Model with the Penn State–NCAR MM5 Modeling System. Part I: Model Implementation and Sensitivity
Fei Chen,Jimy Dudhia +1 more
TL;DR: In this paper, the authors address and document a number of issues related to the implementation of an advanced land surface-hydrology model in the Penn State-NCAR fifth-generation Mesoscale Model (MM5).
Journal ArticleDOI
A Long-Term Hydrologically Based Dataset of Land Surface Fluxes and States for the Conterminous United States*
TL;DR: In this paper, the authors evaluate the land surface schemes in coupled models, including comparisons of model-predicted evapotranspiration with values derived from atmospheric water balances, comparison of model predicted energy and radiative fluxes with tower measurements during periods of intensive observations, and contrast of model predictions of soil moisture with spatial averages of point observations.
Journal ArticleDOI
The multi-institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system
Kenneth E. Mitchell,Dag Lohmann,Paul R. Houser,Eric F. Wood,John Schaake,Alan Robock,Brian Cosgrove,Justin Sheffield,Qingyun Duan,Lifeng Luo,Lifeng Luo,R. Wayne Higgins,Rachel T. Pinker,J. Dan Tarpley,Dennis P. Lettenmaier,Curtis H. Marshall,Curtis H. Marshall,Jared Entin,Ming Pan,Wei Shi,Victor Koren,Jesse Meng,Jesse Meng,Bruce H. Ramsay,Andrew A. Bailey +24 more
TL;DR: A real-time and retrospective North American Land Data Assimilation System (NLDAS) is presented in this article, which consists of four land models executing in parallel in uncoupled mode, common hourly surface forcing, and common streamflow routing: all using a 1/8° grid over the continental United States.
Journal ArticleDOI
Differences in phosphorus and nitrogen delivery to the Gulf of Mexico from the Mississippi River Basin.
Richard B. Alexander,Richard A. Smith,Gregory E. Schwarz,Elizabeth W. Boyer,Jacqueline V. Nolan,John W. Brakebill +5 more
TL;DR: A spatially explicit and structurally detailed SPARROW water-quality model reveals important differences in the sources and transport processes that control nitrogen (N) and phosphorus (P) delivery to the Gulf of Mexico and indicates the diversity of management approaches required to achieve efficient control of nutrient loads.
Journal ArticleDOI
The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations
David N. Walters,Anthony J. Baran,Anthony J. Baran,Ian A. Boutle,M. E. Brooks,Paul Earnshaw,John M. Edwards,Kalli Furtado,Peter Hill,Adrian Lock,James Manners,Cyril J. Morcrette,Jane Mulcahy,Claudio Sanchez,Chris Smith,Rachel Stratton,Warren Tennant,Lorenzo Tomassini,Kwinten Van Weverberg,Simon Vosper,Martin Willett,J. Browse,Andrew C. Bushell,Kenneth S. Carslaw,Mohit Dalvi,Richard Essery,Nicola Gedney,Steven C. Hardiman,Ben Johnson,Colin E. Johnson,Andrew Jones,Colin Jones,Graham Mann,Sean Milton,Heather Rumbold,Alistair Sellar,Masashi Ujiie,Michael Whitall,Keith D. Williams,M. Zerroukat +39 more
TL;DR: The Global Atmosphere 3.0 (GA3.0) as mentioned in this paper is a configuration of the Met Office Unified Model (MetUM) developed for use across climate research and weather prediction activities.
References
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Journal ArticleDOI
Geographic Patterns of Soil Water-Holding Capacity in the Contiguous United States
TL;DR: In this paper, the water-holding capacity of the 50- to 150-cm depth interval of the United Nations soil map of the world was estimated using the Rawls model and the Saxton model.
Journal Article
Soil geographic data bases
TL;DR: The Soil Survey has established three soil geographic data bases representing different scales of soil mapping as mentioned in this paper, each data base links digitized soil map unit delineations with computerized data for each map unit, giving the proportionate extent of the component soils and their properties.
Journal ArticleDOI
Comparison of available soil water capacity estimated from topography and soil series information
TL;DR: In this article, the authors presented a simple and generalized method to predict Available Soil Water Capacity (ASWC-TOP) for a given area using a topographic index, defined as ln(α/tanβ), where α is the upslope area draining past a certain point per unit width of slope, and β is the local surface slope angle.
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Spatial variability of digital soil maps and its impact on regional ecosystem modeling
TL;DR: In this article, the authors discuss the practical difficulties encountered in using generalized regional soils maps such as the U.S. Soil Conservation Service State Soil Geographic Data Base (STATSGO) for landscape to regional level ecosystem modeling.