Over the oceans, approximately 90% of net radiation produces evaporation (Budyko, 1974), primarily in the tropics. Over continents, net radiation heats the surface, evaporates water from water bodies or moist soils, or provides plants with energy to remove water from soils (Pitman, 2003; Istanbulluoglu and Bras, ANALYSISAt the watershed scale, soil moisture is the major control for rainfall-runoff response, especially where saturation excess runoff processes dominate. From the ecological point of view, the pools of soil moisture are fundamental ecosystem resources providing the transpirable water for plants. In drylands particularly, soil moisture is one of the major controls on the structure, function, and diversity in ecosystems. In terms of the global hydrological cycle, the overall quantity of soil moisture is small, ∼0.05%; however, its importance to the global energy balance and the distribution of precipitation far outweighs its physical amount. In soils it governs microbial activity that aff ects important biogeochemical processes such as nitrifi cation and CO 2 production via respiration. During the past 20 years, technology has advanced considerably, with the development of diff erent electrical sensors for determining soil moisture at a point. However, modeling of watersheds requires areal averages. As a result, point measurements and modeling grid cell data requirements are generally incommensurate. We review advances in sensor technology, particularly emerging geophysical methods and distributed sensors, aimed at bridging this gap. We consider some of the data analysis methods for upscaling from a point to give an areal average. Finally, we conclude by off ering a vision for future research, listing many of the current scientifi c and technical challenges.

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Relationships between leaf wetness and plant diseases have been studied for centuries. The progress and risk of many bacterial, fungal, and oomycete diseases on a variety of crops have been linked to the presence of free water on foliage and fruit under temperatures favorable to infection. Whereas the rate parameters for infection or epidemic models have frequently been linked with temperature during the wet periods, leaf wetness periods of specific time duration are necessary for the propagule germination of most phytopathogenic fungi and for their penetration of plant tissues. Using these types of relationships, disease-warning systems were developed and are now being used by grower communities for a variety of crops. As a component of Integrated Pest Management, disease-warning systems provide growers with information regarding the optimum timing for chemical or biological management practices based on weather variables most suitable for pathogen dispersal or host infection. Although these systems are robust enough to permit some errors in the estimates or measurements of leaf wetness duration, the need for highly accurate leaf wetness duration data remains a priority to achieve the most efficient disease management.

[1] Accurate estimates of biomass are imperative for understanding the global carbon cycle. However, measurements of biomass and water in the biomass are difficult to obtain at a scale consistent with measurements of mass and energy transfer,~1 km, leading to substantial uncertainty in dynamic global vegetation models. Here we use a novel cosmic ray neutron method to estimate a stoichiometric predictor of ecosystem-scale biomass and biomass water equivalent over tens of hectares. We present two experimental studies, one in a ponderosa pine forest and the other in a maize field, where neutron-derived estimates of biomass water equivalent are compared and found consistent with direct observations. Given the new hectometer scale of nondestructive observation and potential for continuous measurements, we anticipate this technique to be useful to many scientific disciplines.

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