Managers of water resources in arid and semi-arid regions must allocate increasingly variable surface water supplies and limited groundwater resources. This challenge is leading to a new generation of detailed computational models that can link multiple sources to a wide range of demands. Detailed computational models of complex natural-human systems can help decision makers allocate scarce natural resources such as water. This article describes a virtual watershed model, the Los Alamos Distributed Hydrologic System (LADHS), which contains the essential physics of all elements of a regional hydrosphere and allows feedback between them. Unlike real watersheds, researchers can perform experiments on virtual watersheds, produce them relatively cheaply (once a modeling framework is established), and run them faster than real time. Furthermore, physics-based virtual watersheds do not require extensive tuning and are flexible enough to accommodate novel boundary conditions such as land-use change or increased climate variability. Essentially, virtual watersheds help resource managers evaluate the risks of alternatives once uncertainties have been quantified.

The article describes recent progress in atomic and molecular level modeling and simulation of nanoscale materials and processes, as well as efforts by the US National Science Foundation's Network ...

Combining a geographic information system's spatial analysis functions and comprehensive fuzzy sets lets researchers evaluate and analyze the ecological suitability of olive tree cultivation in Sic...

Hardware improvements do little to improve real productivity in scientific programming. Indeed, the dominant barriers to productivity improvement are now in the software processes. To break the gri...

This year marks the 20th anniversary of this magazine (if you follow the Computers in Physics branch of the family), and the 15th year i've had the privilege of writing for it as it happens, we made a big deal of it being the 10th anniversary in 1997, with a special logo on each issue and a series of articles about the way things were 10 years before and how they might be 10 years hence (that is, now). A particular treat was a round-table discussion held by the editors and presented in the November/December issue (Computers in Physics, vol. 11, no. 6, 1997)

An approach derived from information-theoretic principles can help researchers build stochastic microstructural models. This approach involves extracting topological information from microstructural samples and using this information to build a stochastic model. To generate huge databases of stochastic material models, the authors thus propose using an information-learning algorithm to train a network for statistical outputs

A system's evolution over time can be described with a set of equations called a dynamical system. In this installment, we use a dynamical system to model the life cycle of flour beetles to estimate key parameters that describe their behavior

This special issue of CiSE highlights various aspects of and outstanding problems in stochastic modeling of complex systems. The techniques covered include stochastic spectral methods, the information-theoretic approach, and sensitivity analysis for uncertainty quantification. Two application articles-one in the field of ecology and the other in the field of manufacturing design-emphasize the diversity of research disciplines in which the ability to handle uncertainty is crucial to obtaining reliable science-based predictions