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Journal ArticleDOI

A Conterminous United States Multilayer Soil Characteristics Dataset for Regional Climate and Hydrology Modeling

01 Jan 1998-Earth Interactions (American Meteorological Society)-Vol. 2, Iss: 2, pp 1-26
TL;DR: 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 soil
Citations
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Journal ArticleDOI
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).
Abstract: This paper addresses and documents 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). The concept adopted here is that the land surface model should be able to provide not only reasonable diurnal variations of surface heat fluxes as surface boundary conditions for coupled models, but also correct seasonal evolutions of soil moisture in the context of a long-term data assimilation system. In a similar way to that in which the modified Oregon State University land surface model (LSM) has been used in the NCEP global and regional forecast models, it is implemented in MM5 to facilitate the initialization of soil moisture. Also, 1-km resolution vegetation and soil texture maps are introduced in the coupled MM5–LSM system to help identify vegetation/water/soil characteristics at fine scales and capture the feedback of these land surface forcings. A monthly varying climatological 0.15° × 0.15° green ...

4,405 citations


Cites methods from "A Conterminous United States Multil..."

  • ...The soil texture is determined by using the 1-km resolution multilayer 16-category soil characteristics dataset developed by Miller and White (1998), which is based on the U.S. Department of Agriculture’s State Soil Geographic Database and provides information on the soil texture, bulk density,…...

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Journal ArticleDOI
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.
Abstract: A frequently encountered difficulty in assessing model-predicted land–atmosphere exchanges of moisture and energy is the absence of comprehensive observations to which model predictions can be compared at the spatial and temporal resolutions at which the models operate. Various methods have been used to 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, comparison of model-predicted runoff with observed streamflow, and comparison of model predictions of soil moisture with spatial averages of point observations. While these approaches have provided useful model diagnostic information, the observation-based products used in the comparisons typically are inconsistent with the model variables with which they are compared—for example, observations are for points or a...

1,368 citations

Journal ArticleDOI
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.
Abstract: [1] Results are presented from the multi-institution partnership to develop a real-time and retrospective North American Land Data Assimilation System (NLDAS). NLDAS consists of (1) four land models executing in parallel in uncoupled mode, (2) common hourly surface forcing, and (3) common streamflow routing: all using a 1/8° grid over the continental United States. The initiative is largely sponsored by the Global Energy and Water Cycle Experiment (GEWEX) Continental-Scale International Project (GCIP). As the overview for nine NLDAS papers, this paper describes and evaluates the 3-year NLDAS execution of 1 October 1996 to 30 September 1999, a period rich in observations for validation. The validation emphasizes (1) the land states, fluxes, and input forcing of four land models, (2) the application of new GCIP-sponsored products, and (3) a multiscale approach. The validation includes (1) mesoscale observing networks of land surface forcing, fluxes, and states, (2) regional snowpack measurements, (3) daily streamflow measurements, and (4) satellite-based retrievals of snow cover, land surface skin temperature (LST), and surface insolation. The results show substantial intermodel differences in surface evaporation and runoff (especially over nonsparse vegetation), soil moisture storage, snowpack, and LST. Owing to surprisingly large intermodel differences in aerodynamic conductance, intermodel differences in midday summer LST were unlike those expected from the intermodel differences in Bowen ratio. Last, anticipating future assimilation of LST, an NLDAS effort unique to this overview paper assesses geostationary-satellite-derived LST, determines the latter to be of good quality, and applies the latter to validate modeled LST.

1,192 citations

Journal ArticleDOI
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.
Abstract: Seasonal hypoxia in the northern Gulf of Mexico has been linked to increased nitrogen fluxes from the Mississippi and Atchafalaya River Basins, though recent evidence shows that phosphorus also influences productivity in the Gulf. We developed a spatially explicit and structurally detailed SPARROW water-quality model that reveals important differences in the sources and transport processes that control nitrogen (N) and phosphorus (P) delivery to the Gulf. Our model simulations indicate that agricultural sources in the watersheds contribute more than 70% of the delivered N and P. However, corn and soybean cultivation is the largest contributor of N (52%), followed by atmospheric deposition sources (16%); whereas P originates primarily from animal manure on pasture and rangelands (37%), followed by corn and soybeans (25%), other crops (18%), and urban sources (12%). The fraction of in-stream P and N load delivered to the Gulf increases with stream size, but reservoir trapping of P causes large local- and re...

814 citations

Journal ArticleDOI
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.
Abstract: . We describe Global Atmosphere 3.0 (GA3.0): a configuration of the Met Office Unified Model (MetUM) developed for use across climate research and weather prediction activities. GA3.0 has been formulated by converging the development paths of the Met Office's weather and climate global atmospheric model components such that wherever possible, atmospheric processes are modelled or parametrized seamlessly across spatial resolutions and timescales. This unified development process will provide the Met Office and its collaborators with regular releases of a configuration that has been evaluated, and can hence be applied, over a variety of modelling regimes. We also describe Global Land 3.0 (GL3.0): a configuration of the JULES community land surface model developed for use with GA3.0. This paper provides a comprehensive technical and scientific description of the GA3.0 and GL3.0 (and related GA3.1 and GL3.1) configurations and presents the results of some initial evaluations of their performance in various applications. It is to be the first in a series of papers describing each subsequent Global Atmosphere release; this will provide a single source of reference for established users and developers as well as researchers requiring access to a current, but trusted, global MetUM setup.

803 citations

References
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Journal ArticleDOI
TL;DR: Van Genuchten et al. as mentioned in this paper proposed a closed-form analytical expression for predicting the hydraulic conductivity of unsaturated soils based on the Mualem theory, which can be used to predict the unsaturated hydraulic flow and mass transport in unsaturated zone.
Abstract: A new and relatively simple equation for the soil-water content-pressure head curve, 8(h), is described in this paper. The particular form of the equation enables one to derive closedform analytical expressions for the relative hydraulic conductivity, Kr, when substituted in the predictive conductivity models of N.T. Burdine or Y. Mualem. The resulting expressions for Kr(h) contain three independent parameters which may be obtained by fitting the proposed soil-water retention model to experimental data. Results obtained with the closed-form analytical expressions based on the Mualem theory are compared with observed hydraulic conductivity data for five soils with a wide range of hydraulic properties. The unsaturated hydraulic conductivity is predicted well in four out of five cases. It is found that a reasonable description of the soil-water retention curve at low water contents is important for an accurate prediction of the unsaturated hydraulic conductivity. Additional Index Words: soil-water diffusivity, soil-water retention curve. van Genuchten, M. Th. 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J. 44:892-898. T USE OF NUMERICAL MODELS for simulating fluid flow and mass transport in the unsaturated zone has become increasingly popular the last few years. Recent literature indeed demonstrates that much effort is put into the development of such models (Reeves and Duguid, 1975; Segol, 1976; Vauclin et al., 1979). Unfortunately, it appears that the ability to fully characterize the simulated system has not kept pace with the numerical and modeling expertise. Probably the single most important factor limiting the successful application of unsaturated flow theory to actual field problems is the lack of information regarding the parameters entering the governing transfer equations. Reliable estimates of the unsaturated hydraulic conductivity are especially difficult to obtain, partly because of its extensive variability in the field, and partly because measuring this parameter is time-consuming and expensive. Several investigators have, for these reasons, used models for calculating the unsaturated conductivity from the more easily measured soil-water retention curve. Very popular among these models has been the Millington-Quirk method (Millington and Quirk, 1961), various forms of which have been applied with some success in a number of studies (cf. Jackson et al., 1965; Jackson, 1972; Green and Corey, 1971; Bruce, 1972). Unfortunately, this method has the disadvantage of producing tabular results which, for example when applied to nonhomogeneous soils in multidimensional unsaturated flow models, are quite tedious to use. Closed-form analytical expressions for predicting 1 Contribution from the U. S. Salinity Laboratory, AR-SEA, USDA, Riverside, CA 92501. Received 29 June 1979. Approved 19 May I960. 'Soil Scientist, Dep. of Soil and Environmental Sciences, University of California, Riverside, CA 92521. The author is located at the U. S. Salinity Lab., 4500 Glenwood Dr., Riverside, CA 92502. the unsaturated hydraulic conductivity have also been developed. For example, Brooks and Corey (1964) and Jeppson (1974) each used an analytical expression for the conductivity based on the Burdine theory (Burdine, 1953). Brooks and Corey (1964, 1966) obtained fairly accurate predictions with their equations, even though a discontinuity is present in the slope of both the soil-water retention curve and the unsaturated hydraulic conductivity curve at some negative value of the pressure head (this point is often referred to as the bubbling pressure). Such a discontinuity sometimes prevents rapid convergence in numerical saturated-unsaturated flow problems. It also appears that predictions based on the Brooks and Corey equations are somewhat less accurate than those obtained with various forms of the (modified) Millington-Quirk method. Recently Mualem (1976a) derived a new model for predicting the hydraulic conductivity from knowledge of the soil-water retention curve and the conductivity at saturation. Mualem's derivation leads to a simple integral formula for the unsaturated hydraulic conductivity which enables one to derive closed-form analytical expressions, provided suitable equations for the soil-water retention curves are available. It is the purpose of this paper to derive such expressions using an equation for the soil-water retention curve which is both continuous and has a continuous slope. The resulting conductivity models generally contain three independent parameters which may be obtained by matching the proposed soil-water retention curve to experimental data. Results obtained with the closedform equations based on the Mualem theory will be compared with observed data for a few soils having widely varying hydraulic properties. THEORETICAL Equations Based on Mualem's Model The following equation was derived by Mualem (1976a) for predicting the relative hydraulic conductivity (Kr) from knowledge of the soil-water retention curve

22,781 citations


"A Conterminous United States Multil..." refers methods in this paper

  • ...The BD is often used as a predictive variable in PTFs that predict soil water retention properties ( Tietje and Tapkenhinrichs, 1993 )....

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  • ...Tietje and Tapkenhinrichs ( Tietje and Tapkenhinrichs, 1993 ) differentiate among the methods for deriving PTFs....

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31 Dec 1963

5,311 citations


"A Conterminous United States Multil..." refers methods in this paper

  • ...The most frequently applied models that require functional parameters are based on the work of Brooks and Corey (Brooks and Corey, 1964), Campbell (Campbell, 1974), Clapp and Hornberger (Clapp and Hornberger, 1978), and van Genuchten (van Genuchten, 1980)....

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Journal ArticleDOI
TL;DR: In this paper, a power function relating soil moisture and hydraulic conductivity is used to derive a formula for the wetting front suction required by the Green-Ampt equation.
Abstract: The soil moisture characteristic may be modeled as a power curve combined with a short parabolic section near saturation to represent gradual air entry. This two-part function—together with a power function relating soil moisture and hydraulic conductivity—is used to derive a formula for the wetting front suction required by the Green-Ampt equation. Representative parameters for the moisture characteristic, the wetting front suction, and the sorptivity, a parameter in the infiltration equation derived by Philip (1957), are computed by using the desorption data of Holtan et al. (1968). Average values of the parameters, and associated standard deviations, are calculated for 11 soil textural classes. The results of this study indicate that the exponent of the moisture characteristic power curve can be predicted reasonably well from soil texture and that gradual air entry may have a considerable effect on a soil's wetting front suction.

2,273 citations


"A Conterminous United States Multil..." refers methods in this paper

  • ...The most frequently applied models that require functional parameters are based on the work of Brooks and Corey (Brooks and Corey, 1964), Campbell (Campbell, 1974), Clapp and Hornberger (Clapp and Hornberger, 1978), and van Genuchten (van Genuchten, 1980)....

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Journal ArticleDOI
TL;DR: In this article, the results from the recent statistical analyses were used to calculate water potentials for a wide range of soil textures, then these were fit by multivariate analyses to provide continuous potential estimates for all inclusive textures.
Abstract: Soil-water potential and hydraulic conductivity relationships with soil-water content are needed for many plant and soil-water studies. Measurement of these relationships is costly, difficult, and often impractical. For many purposes, general estimates based on more readily available information such as soil texture are sufficient. Recent studies have developed statistical correlations between soil texture and selected soil potentials using a large data base, and also between selected soil textures and hydraulic conductivity. The objective of this study was to extend these results by providing mathematical equations for continuous estimates over broad ranges of soil texture, water potentials, and hydraulic conductivities. Results from the recent statistical analyses were used to calculate water potentials for a wide range of soil textures, then these were fit by multivariate analyses to provide continuous potential estimates for all inclusive textures. Similarly, equations were developed for unsaturated hydraulic conductivities for all inclusive textures. While the developed equations only represent a statistical estimate and only the textural influence, they provide quite useful estimates for many usual soil-water cases. The equations provide excellent computational efficiency for model applications and the textures can be used as calibration parameters where field or laboratory soil water characteristic data are available. Predicted values were successfully compared with several independent measurements of soil-water potential.

1,877 citations


"A Conterminous United States Multil..." refers background in this paper

  • ...A number of studies have tested and evaluated these PTFs using a wide variety of soil physical property information in a range of settings (Arya and Paris, 1981; Kern, 1995b; Saxton et al., 1986; Rawls et al., 1991; Vereecken et al., 1990)....

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Journal ArticleDOI
TL;DR: In this article, the unsaturated hydraulic conductivity function for soil can be calculated directly from a moisture retention function and a single measurement of hydraulic conductivities at some water content, and agreement of k calculated using this procedure with experimentally determined conductivities for five soil samples was found to be at least as good as with other calculation procedures.
Abstract: The unsaturated hydraulic conductivity function for soil can be calculated directly from a moisture retention function and a single measurement of hydraulic conductivity at some water content. If the moisture retention function can be represented by Y = Y,(0/0,)-b, where Y is the air entry water potential, 9, is the saturated water content, and 6 is an emperically determined constant, then the hydraulic conductivity is given by k = k,(O/O,)2b+8, where k. is the saturated hydraulic conductivity. Agreement of k calculated using this procedure with experimentally determined conductivities for five soil samples was found to be at least as good as with other calculation procedures

1,555 citations


"A Conterminous United States Multil..." refers methods in this paper

  • ...The most frequently applied models that require functional parameters are based on the work of Brooks and Corey (Brooks and Corey, 1964), Campbell (Campbell, 1974), Clapp and Hornberger (Clapp and Hornberger, 1978), and van Genuchten (van Genuchten, 1980)....

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