Monitoring and Verifying Changes of Organic Carbon in Soil

Changes in soil and vegetation management can impact strongly on the rates of carbon (C) accumulation and loss in soil, even over short periods of time. Detecting the effects of such changes in accumulation and loss rates on the amount of C stored in soil presents many challenges. Consideration of the temporal and spatial heterogeneity of soil properties, general environmental conditions, and management history is essential when designing methods for monitoring and projecting changes in soil C stocks. Several approaches and tools will be required to develop reliable estimates of changes in soil C at scales ranging from the individual experimental plot to whole regional and national inventories. In this paper we present an overview of soil properties and processes that must be considered. We classify the methods for determining soil C changes as direct or indirect. Direct methods include field and laboratory measurements of total C, various physical and chemical fractions, and C isotopes. A promising direct method is eddy covariance measurement of CO₂ fluxes. Indirect methods include simple and stratified accounting, use of environmental and topographic relationships, and modeling approaches. We present a conceptual plan for monitoring soil C changes at regional scales that can be readily implemented. Finally, we anticipate significant improvements in soil C monitoring with the advent of instruments capable of direct and precise measurements in the field as well as methods for interpreting and extrapolating spatial and temporal information.     

Editorial

Natural Resources Research -     

Pitfalls in Nonlinear Inversion

— We discuss and illustrate graphically with simple 2-D problems, four common pitfalls in geophysical nonlinear inversion. The first one establishes that the Lagrange multiplier, used to incorporate a priori information in the geophysical inverse problem, should be the largest value still compatible with a reasonable data fitting. This procedure should be used only when the interpreter is sure about the importance of the a priori information used to stabilize the inverse problem relative to the geophysical observations. Because this is rarely the case, the user should use the smallest Lagrange multiplier still producing stable solutions. The second pitfall is an attempt to automatically estimate the Lagrange multiplier by decreasing it along the iterative process used to solve the nonlinear optimization problem. Consequently, at the last iteration, the Lagrange multiplier may be so small that the problem may become ill-posed and any computed solution in this case is meaningless. The third pitfall is related to the incorporation of a priori information by a technique known as “Jumping.” This formulation, from the viewpoint of the class of Acceptable Gradient Methods, is incomplete and may lead to a premature halt in the iteration, and, consequently, to solutions far from the true one. Finally, the fourth pitfall is an inadequate convergence criterion which stops the iteration when the data misfit drops just below the noise level, irrespective of the fact that the functional to be minimized may not have attained its minimum. This means that the a priori information has not been completely incorporated, so that this stopping criterion partially neutralizes the effect of the stabilizing functional, and opens the possibility of obtaining unstable, meaningless estimates.     

The CP 2 Analytical Plotter

This paper examines the rationale behind the design and development of the CP 2 analytical plotter and shows how the final product, in terms of both hardware and software, has been influenced by the needs of a commercial air survey company.     

Efficient time truncation in two-dimensional bem analysis of transient wave propagation problems

An efficient time truncation algorithm for transient two-dimensional wave propagation analysis by the boundary element method is proposed. First the complete (without any truncation) formulation is reviewed and subsequently time truncation concepts are discussed. Three applications are presented, where the efficiency of complete and truncated algorithms is compared. The most important conclusions inferred from the numerical analyses are: (i) time truncation errors can be controlled and made as small as required and (ii) time truncation algorithms lead to considerable savings in both CPU time and storage area.