also use soil dielectric properties to determine . These alternative sensors have received relatively little inde-Widespread interest in soil water content (, m 3 m Ϫ3 ) information pendent study; and critical practical issues related to for both management and research has led to the development of a calibration methodology and application have not been variety of soil water content sensors. In most cases, critical issues addressed. related to sensor calibration and accuracy have received little independent study. We investigated the performance of the Hydra Probe soil The Hydra Probe is an example of the alternative water sensor with the following objectives: (i) quantify the intersensors now available. 1 It is currently in widespread use sensor variability, (ii) evaluate the applicability of data from two (e.g., the Soil Climate Analysis Network of the Natural commonly used calibration methods, and (iii) develop and test two Resource Conservation Service) and has proven to be multi-soil calibration equations, one general, "default" calibration robust under a variety of field conditions. Previous reequation and a second calibration that incorporates the effects of soil search demonstrated that Hydra Probe measurements properties. The largest deviation in the real component of the relative are precise and accurate in fluids with known dielectric dielectric permittivity (ε r ) determined with the Hydra Probe using 30 properties and highly correlated with in soils, indicatsensors in ethanol corresponded to a water content deviation of about ing the potential of the instrument for quantitative mea-0.012 m 3 m Ϫ3 , indicating that a single calibration could be generally surement (Seyfried and Murdock, 2004). It was also applied. In layered (wet and dry) media, ε r determined with the Hydra Probe was different from that in uniform media with the same water found that the calibration relationship varied considercontent. In uniform media, was a linear function of ͌ε r . We used ably among soils and that the manufacturer-supplied this functional relationship to describe individual soil calibrations and calibrations were not accurate for some soils. Important the multi-soil calibrations. Individual soil calibrations varied indepenpractical considerations regarding the use of the Hydra dently of clay content but were correlated with dielectric loss. When Probe remain. These include: (i) the degree of variation applied to the 19-soil test data set, the general calibration outperin response among different sensors (i.e., the inter-senformed manufacturer-supplied calibrations. The average difference, sor variability), which determines if sensor specific calievaluated between ε r ϭ 4 and ε r ϭ 36, was 0.019 m 3 m Ϫ3 for the general brations are required, (ii) the optimal experimental equation and 0.013 m 3 m Ϫ3 for the loss-corrected equation.83712;

Although there is increasing use of eco-labeling, conditions under which eco-labels can command price premiums are not fully understood. In this article, we demonstrate that the certification of environmental practices by a third party should be analyzed as a strategy distinct from-although related to-the disclosure of the eco-certification through a label posted on the product. By assessing eco-labeling and eco-certification strategies separately, researchers can identify benefits associated with the certification process, such as improved reputation in the industry or increased product quality, independently from those associated with the actual label. In the context of the wine industry, we show that eco-certification leads to a price premium while the use of the eco-label does not.

Abstract:Although soil processes affect the timing and amount of streamflow generated from snowmelt, they are often overlooked in estimations of snowmelt-generated streamflow in the western USA. The use of a soil water balance modelling approach to incorporate the effects of soil processes, in particular soil water storage, on the timing and amount of snowmelt generated streamflow, was investigated. The study was conducted in the Reynolds Mountain East (RME) watershed, a 38 ha, snowmeltdominated watershed in southwest Idaho. Snowmelt or rainfall inputs to the soil were determined using a well established snow accumulation and melt model (Isnobal ). The soil water balance model was first evaluated at a point scale, using periodic soil water content measurements made over two years at 14 sites. In general, the simulated soil water profiles were in agreement with measurements (P < 0Ð05) as further indicated by high R 2 values (mostly >0Ð85), y-intercept values near 0, slopes near 1 and low average differences between measured and modelled values. In addition, observed soil water dynamics were generally consistent with critical model assumptions. Spatially distributed simulations over the watershed for the same two years indicate that streamflow initiation and cessation are closely linked to the overall watershed soil water storage capacity, which acts as a threshold. When soil water storage was below the threshold, streamflow was insensitive to snowmelt inputs, but once the threshold was crossed, the streamflow response was very rapid. At these times there was a relatively high degree of spatial continuity of satiated soils within the watershed. Incorporation of soil water storage effects may improve estimation of the timing and amount of streamflow generated from mountainous watersheds dominated by snowmelt.

Abstract:Soil is a critical intermediary of water flux between precipitation and stream flow. Characterization of soil water content (Â, m 3 m 3 ) may be especially difficult in mountainous, snow-dominated catchments due to highly variable water inputs, topography, soils and vegetation. However, individual sites exhibit similar seasonal dynamics, suggesting that it may be possible to describe spatial variability in terms of temporally stable relationships. Working in a 0Ð36 km 2 headwater catchment, we: (i) described and the spatial variability of  over a 2 year period, (ii) characterized that variability in terms of temporal stability analysis, and (iii) related changes in temporally stable soil water patterns to stream flow generation. Soil water data were collected for 2 years at representative sites and quantified in terms of  and water storage to a depth of 75 cm (S 75 , cm). Both S 75 and  were normally distributed in space on all measurement dates. Spatial variability was high relative to other studies, reflecting catchment heterogeneity. However, the ranking of S 75 values displayed temporal stability for all site locations, seasonally and annually. This stability was attributed to soil texture. Further temporal analysis indicated that estimates of catchment mean and standard deviation of S 75 may be characterized with relatively few measurements. Finally, we used temporal linear regression to define catchment soil water conditions related to stream-flow generation. Static, high S 75 conditions in late winter and early spring indicate that stream-flow response is highly sensitive to inputs, whereas static, low S 75 conditions in late summer and early fall indicate minimum stream-flow sensitivity to water inputs. The fall transition was marked by uniform S d across the catchment. The late spring transition was marked by nonuniform S 75 decreases, with the highest S 75 sites decreasing most. Threshold S 75 values identifying catchment sensitivity to water input were identified.

In recent years a number of soil water monitoring instruments have been developed and made commercially available. These instruments generally respond to the complex soil dielectric permittivity and operate at frequencies between 10 and 150 MHz. Although there is some evidence that these instruments are sensitive to temperature change in certain soils, little empirical data exists describing the degree of this sensitivity. We quantified temperature effects on both the real and imaginary components of the complex permittivity for 19 soils collected around the United States using the Hydra Probe soil water sensor, which operates at 50 MHz. We found that the real component response ranged from positive to negative such that the effect of a 40°C temperature change resulted in a maximum apparent water content change of ± 0.028 m3 m−3 among soils. The effect of temperature on the imaginary component was as much as six times greater than on the real component, changing about 2% °C−1, which is similar to that observed for electrical conductivity. The high imaginary component sensitivity to temperature is probably responsible for the high temperature sensitivity noted for commercial soil water sensors because they generally respond to a composite of both components. In addition, there was a strong linear correlation (R2 = 0.81) between the effect of temperature on the calculated soil water content and the magnitude of the imaginary component. While this relationship suggests the possibility of calculating temperature effects on Hydra Probe–calculated soil water content in the field, it applies only to saturated soil conditions at present.