Soil carbon sequestration to mitigate climate change

Hydrologic analyses often involve the evaluation of soil water infiltration, conductivity, storage, and plant-water relationships. To define the hydrologic soil water effects requires estimating soil water characteristics for water potential and hydraulic conductivity using soil variables such as texture, organic matter (OM), and structure. Field or laboratory measurements are difficult, costly, and often impractical for many hydrologic analyses. Statistical correlations between soil texture, soil water potential, and hydraulic conductivity can provide estimates sufficiently accurate for many analyses and decisions. This study developed new soil water characteristic equations from the currently available USDA soil database using only the readily available variables of soil texture and OM. These equations are similar to those previously reported by Saxton et al. but include more variables and application range. They were combined with previously reported relationships for tensions and conductivities and the effects of density, gravel, and salinity to form a comprehensive predictive system of soil water characteristics for agricultural water management and hydrologic analyses. Verification was performed using independent data sets for a wide range of soil textures. The predictive system was programmed for a graphical computerized model to provide easy application and rapid solutions and is available at http://hydrolab.arsusda. gov/soilwater/Index.htm.

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Soil Water Characteristic Estimates by Texture and Organic Matter for Hydrologic Solutions

This report describes the RETC computer code for analyzing the soil water retention and hydraulic conductivity functions of unsaturated soils. These hydraulic properties are key parameters in any quantitative description of water flow into and through the unsaturated zone of soils. The program uses the parametric models of Brooks-Corey and van Genuchten to represent the soil water retention curve, and the theoretical pore-size distribution models of Mualem and Burdine to predict the unsaturated hydraulic conductivity function from observed soil water retention data. The report gives a detailed discussion of the different analytical expressions used for quantifying the soil water retention and hydraulic conductivity functions. A brief review is also given of the nonlinear least-squares parameter optimization method used for estimating the unknown coefficients in the hydraulic models. Several examples are presented to illustrate a variety of program options. The program may be used to predict the hydraulic conductivity from observed soil water retention data assuming that one observed conductivity value (not necessarily at saturation) is available. The program also permits one to fit analytical functions simultaneously to observed water retention and hydraulic conductivity data. The report serves as both a user manual and reference document. Detailed information is given on the computer program along with instructions for data input preparation and sample input and output files. A listing of the source code is also provided.

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The RETC code for quantifying the hydraulic functions of unsaturated soils

Microwave radiometry at low frequencies (L-band: 1.4 GHz, 21 cm) is an established technique for estimating surface soil moisture and sea surface salinity with a suitable sensitivity. However, from space, large antennas (several meters) are required to achieve an adequate spatial resolution at L-band. So as to reduce the problem of putting into orbit a large filled antenna, the possibility of using antenna synthesis methods has been investigated. Such a system, relying on a deployable structure, has now proved to be feasible and has led to the Soil Moisture and Ocean Salinity (SMOS) mission, which is described. The main objective of the SMOS mission is to deliver key variables of the land surfaces (soil moisture fields), and of ocean surfaces (sea surface salinity fields). The SMOS mission is based on a dual polarized L-band radiometer using aperture synthesis (two-dimensional [2D] interferometer) so as to achieve a ground resolution of 50 km at the swath edges coupled with multiangular acquisitions. The radiometer will enable frequent and global coverage of the globe and deliver surface soil moisture fields over land and sea surface salinity over the oceans. The SMOS mission was proposed to the European Space Agency (ESA) in the framework of the Earth Explorer Opportunity Missions. It was selected for a tentative launch in 2005. The goal of this paper is to present the main aspects of the baseline mission and describe how soil moisture will be retrieved from SMOS data.

Soil moisture retrieval from space: the Soil Moisture and Ocean Salinity (SMOS) mission

応用水文 = Applied hydrology

Macroporosity to Characterize Spatial Variability of Hydraulic Conductivity and Effects of Land Management

Water is the principle limiting factor in dryland cropping systems. Surface soil physical properties influence infiltration and cropping systems under no-till management may affect these properties through residue addition. The objectives of this study were: (i) to determine how cropping intensity and topographic position affect soil bulk density, porosity, sorptivity, and aggregate stability in the surface 2.5 cm of soils at three eastern Colorado sites; and (ii) to relate these properties to crop residue returned to the soil surface. No-till cropping systems had been in place on three slope positions, at three sites, for 12 yr prior to this study. Wheat (Triticum aestivum L.)-corn (Zea mays L.)-fallow (WCF) and continuous cropping (CC) systems were compared with wheat-fallow (WF) on summit and toeslope positions at two sites (Sterling and Stratton), and at the third site (Walsh) wheat-sorghum [Sorghum bicolor (L.) Moench]-fallow (WSF) replaced WCF. Cropping systems (CC and WCF or WSF) that returned more crop residue decreased bulk density and increased total and effective porosities compared with WF. Site and slope positions that produced more crop residue also improved these properties. However, sorptivity developed no significant differences as a result of cropping system. Macroaggregates made up a higher percentage of total aggregates in CC and WCF or WSF compared with WF in proportion to residue added and were also a function of clay content of the soil at different sites and slope positions. These factors enhance the potential for greater infiltration and hence greater water availability for crops.

Surface Soil Physical Properties After Twelve Years of Dryland No-Till Management

Water resources and water use efficiency in the North China Plain: Current status and agronomic management options

Broad-based regression equations of Rawls and associates were investigated for estimating the spatially variable soil water contentmatric potential relationships in a 1.6-ha watershed (Udertic Paleustolls) from soil textural and structural properties, with and without one or two known values of the relationships. Also examined were a simple log-log line based on two known values and estimates obtained from one known value for each relationship and a complete relationship for one case using the similar-media scaling concept. The results were compared with measurements on 189 soil cores representing different sites and horizons. With the equations based on soil texture, bulk density and organic matter content, the soil water contents calculated at different matric potentials were generally larger than the measured values. The mean relative error ranged from 8 to 29%, with the standard deviation of errors ranging from 17 to 36%. The model which incorporated one measured soil water content (at — 1500 kPa potential) as an additional independent variable, did not improve the results much. The model which incorporated two measured soil water contents (at — 33 and — 1500 kPa potentials) as additional variables reduced the errors in calculated values considerably. A simple log-log line drawn through the two known points gave nearly the same accuracy. The estimates from the method of scaling were better than those from the model based on textural and structural variables alone; the mean relative error in the calculated water contents ranged from — 0.96 to 9.10%, and the standard deviation of errors was also reduced. Additional Index Words: soil water storage, spatial variability of soil water properties, watershed modeling. View complete article To view this complete article, insert Disc 4 then click button8

Estimating Soil Water Characteristics from Simpler Properties or Limited Data1

The environmental modeling community has historically been concerned with the proliferation of models and the effort associated with collective model development tasks (e.g., code generation, data transformation, etc.). Environmental modeling frameworks (EMFs) have been developed to address this problem, but much work remains before EMFs are adopted as mainstream modeling tools. Environmental model development requires both scientific understanding of environmental phenomena and software developer proficiency. EMFs support the modeling process through streamlining model code development, allowing seamless access to data, and supporting data analysis and visualization. EMFs also support aggregation of model components into functional units, component interaction and communication, temporal-spatial stepping, scaling of spatial data, multi-threading/multi-processor support, and cross-language interoperability. Some EMFs additionally focus on high-performance computing and are tailored for particular modeling domains such as ecosystem, socio-economic, or climate change research. The Object Modeling System Version 3 (OMS3) EMF employs new advances in software framework design to better support the environmental model development process. This paper discusses key EMF design goals/constraints and addresses software engineering aspects that have made OMS3 framework development efficacious and its application practical, as demonstrated by leveraging software engineering efforts outside of the modeling community and lessons learned from over a decade of EMF development. Software engineering approaches employed in OMS3 are highlighted including a non-invasive lightweight framework design supporting component-based model development, use of implicit parallelism in system design, use of domain specific language design patterns, and cloud-based support for computational scalability. The key advancements in EMF design presented herein may be applicable and beneficial for other EMF developers seeking to better support environmental model development through improved framework design.

L. R. Ahuja

Papers

Macroporosity to Characterize Spatial Variability of Hydraulic Conductivity and Effects of Land Management

Surface Soil Physical Properties After Twelve Years of Dryland No-Till Management

Water resources and water use efficiency in the North China Plain: Current status and agronomic management options

Estimating Soil Water Characteristics from Simpler Properties or Limited Data1

A software engineering perspective on environmental modeling framework design