EFFECTS OF TOPOGRAPHY AND SOIL PROPERTIES ON RECHARGE AT TWO SITES IN AN AGRICULTURAL FIELD1

ABSTRACT: Field experiments were conducted from 1992 to 1995 to estimate ground water recharge rates at two sites located within a 2.7‐hectare agricultural field. The field lies in a sand plain setting in central Minnesota and is cropped continuously in field corn. The sites are located at a topographically high (upland) site and a topographically low (lowland) site in an effort to quantify the effects of depression focusing of recharge. Three site‐specific methods were used to estimate recharge rates: well hydrograph analysis, chlorofluorocarbon age dating, and an unsaturated zone water balance. All three recharge methods indicated that recharge rates at the lowland site (annual average of all methods of 29 cm) exceeded those at the upland site (annual average of 18 cm). On an annual basis, estimates by the individual methods ranged from 12 to 44 percent of precipitation at the upland site and from 21 to 83 percent at the lowland site. The difference in recharge rates between the sites is primarily attributed to depression focusing of surface water runon at the lowland site. However, two other factors were also important: the presence of thin lamellae at the upland site, and coarser textured soils below a depth of 1.5 m at the lowland site.     

Cross-combined composite sampling designs for identification of elevated regions

Analyzing soils for contaminants can be costly. Generally, discrete samples are gathered from within a study area, analyzed by a laboratory and the results are used in a site-specific statistical analysis. Because of the heterogeneities that exist in soil samples within study areas, a large amount of variability and skewness may be present in the sample population. This necessitates collecting a large number of samples to obtain reliable inference on the mean contaminant concentration and to understand the spatial patterns for future remediation. Composite, or Incremental, sampling is a commonly applied method for gathering multiple discrete samples and physically combining them, such that each combination of discrete samples requires a single laboratory analysis, which reduces cost and can improve the estimates of the mean concentration. While incremental sampling can reduce cost and improve mean estimates, current implementations do not readily facilitate the characterization of spatial patterns or the detection of elevated constituent regions within study areas. The methods we present in this work provide efficient estimation and inference for the mean contaminant concentration over the entire spatial area and enable the identification of high contaminant regions within the area of interest. We develop sample design methodologies that explicitly define the characteristics of these designs (such as sample grid layout) and quantify the number of incremental samples that must be obtained under a design criteria to control false positive and false negative (Type I and II) decision errors. We present the sample design theory and specifications as well as results on simulated and real data.     

Statistical Evaluation of Variables Affecting Occurrence of Hydrocarbons in Aquifers Used for Public Supply,California

The variables affecting the occurrence of hydrocarbons in aquifers used for public supply in California were assessed based on statistical evaluation of three large statewide datasets; gasoline oxygenates also were analyzed for comparison with hydrocarbons. Benzene is the most frequently detected (1.7%) compound among 17 hydrocarbons analyzed at generally low concentrations (median detected concentration 0.024 μg/l) in groundwater used for public supply in California; methyl tert‐butyl ether (MTBE) is the most frequently detected (5.8%) compound among seven oxygenates analyzed (median detected concentration 0.1 μg/l). At aquifer depths used for public supply, hydrocarbons and MTBE rarely co‐occur and are generally related to different variables; in shallower groundwater, co‐occurrence is more frequent and there are similar relations to the density or proximity of potential sources. Benzene concentrations are most strongly correlated with reducing conditions, regardless of groundwater age and depth. Multiple lines of evidence indicate that benzene and other hydrocarbons detected in old, deep, and/or brackish groundwater result from geogenic sources of oil and gas. However, in recently recharged (since ~1950), generally shallower groundwater, higher concentrations and detection frequencies of benzene and hydrocarbons were associated with a greater proportion of commercial land use surrounding the well, likely reflecting effects of anthropogenic sources, particularly in combination with reducing conditions.     

Determining the role of eudaimonic values in conservation behavior

Values are the fundamental reasons why people engage in conservation behaviors. Recent research has called for a more refined approach to studying values in a way that accounts for the concept of eudaimonia. However, the empirical properties for a eudaimonic value scale have not been tested given that previous investigations have remained at the theoretical level. Drawing from an on-site survey of visitors to Denali National Park and Preserve, Alaska, we used a latent profile analysis to better understand the expression of multiple values of nature. Specifically, we segmented respondents by their value orientations with a particular focus on evaluating eudaimonic and hedonic values, alongside the established dimensions of altruistic, biospheric, and egoistic values. We identified 4 distinct subgroups defined by value orientations and validated these subgroups based on measures of conservation behavior and sociodemographic characteristics (e.g., age). These results indicated campaign messaging should harness a combination of eudaimonic, biospheric, and altruistic values to propel individual behavior. We also observed that hedonic and egoistic values defined how people related to nature and played a role, albeit less pronounced, in motivating them to take action. Our study is one of the first efforts to operationalize eudaimonia in a conservation context; thus, we have opened a new avenue for protected-area managers to align their strategies with the underlying values of stakeholders.     

Uncertainty assessment of mapping mercury contaminated soils of a rapidly industrializing city in the Yangtze River Delta of China using sequential indicator co-simulation

Accurate characterization of heavy-metal contaminated areas and quantification of the uncertainties inherent in spatial prediction are crucial for risk assessment, soil remediation, and effective management recommendations. Topsoil samples (0–15 cm) (n = 547) were collected from the Zhangjiagang suburbs of China. The sequential indicator co-simulation (SIcS) method was applied for incorporating the soft data derived from soil organic matter (SOM) to simulate Hg concentrations, map Hg contaminated areas, and evaluate the associated uncertainties. High variability of Hg concentrations was observed in the study area. Total Hg concentrations varied from 0.004 to 1.510 mg kg⁻¹ and the coefficient of variation (CV) accounts for 70%. Distribution patterns of Hg were identified as higher Hg concentrations occurred mainly at the southern part of the study area and relatively lower concentrations were found in north. The Hg contaminated areas, identified using the Chinese Environmental Quality Standard for Soils critical values through SIcS, were limited and distributed in the south where the SOM concentration is high, soil pH is low, and paddy soils are the dominant soil types. The spatial correlations between Hg and SOM can be preserved by co-simulation and the realizations generated by SIcS represent the possible spatial patterns of Hg concentrations without a smoothing effect. Once the Hg concentration critical limit is given, SIcS can be used to map Hg contaminated areas and quantitatively assess the uncertainties inherent in the spatial prediction by setting a given critical probability and calculating the joint probability of the obtained areas.     

Effects of elevated carbon dioxide and ozone on the growth and yield of potatoes (Solanum tuberosum) grown in open-top chambers

Potato (Solanum tuberosum cv. Bintje) was grown in open-top chambers under three carbon dioxide (ambient and seasonal mean concentrations of 550 and 680 mumol mol-1 CO2) and two ozone concentrations (ambient and an 8 h day-1 seasonal mean of 50 nmol mol-1 O3) between emergence and final harvest. Periodic non-destructive measurements were made and destructive harvests were carried out at three key developmental stages (24, 49 and 101 days after emergence) to establish effects on growth and tuber yield. Season-long exposure to elevated O3 reduced above-ground dry weight at final harvest by 8.4% (P < 0.05), but did not affect tuber yields. There was no significant interaction between CO2 and O3 for any of the growth and yield variables examined. Non-destructive analyses revealed no significant effect of elevated CO2 on plant height, leaf number or green leaf area ratio. However, destructive harvests at tuber initiation and 500 degrees Cd after emergence showed that above-ground dry weight (8 and 7% respectively) and tuber yield (88 and 44%) were significantly increased (P < 0.05) in the 550 mumol mol-1 CO2 treatment. Responses to 550 and 680 mumol mol-1 CO2 were not significantly different for most parameters examined, suggesting the existence of an upper limit to the beneficial influence of CO2 enrichment. Significant effects on above-ground dry weight and tuber yield were no longer apparent at final harvest, although tuber numbers were increased (P < 0.05) under elevated CO2, particularly in the smaller size categories. The results show that the O3 treatment imposed was insufficient to reduce tuber yields and that, although elevated CO2 enhanced crop growth during the early stages of the season, this beneficial effect was not sustained to maturity.