profiling areas of ground water contamination by pesticides in california: phase ii – evaluation and modification of a statistical model

A well sampling study was conducted to evaluate anempirical approach to classifying areasof land in California as vulnerable to ground watercontamination by pesticides (Troiano et al., 1994). Wells were sampled from sections of land that had noprevious detections of pesticideresidues. The sections had been classified into vulnerablesoil clusters or into a not-classified groupusing a procedure based on Principal Components Analysis(PCA). Grape, citrus, and olive growingareas of Fresno and Tulare Counties were targeted, areas wherepre-emergence herbicide residues hadbeen detected in well water. Overall, herbicide residues weredetected in 75 of 176 sampled wells, ahigh frequency of detection in relation to results fromprevious targeted well sampling studies. Sinceresidues were also detected in the not-classified group, theclassification procedure was modified usingan approach based on Canonical Variates Analysis (CVA). Moresections were classified intovulnerable soil clusters with the CVA approach than with thePCA method. Data from two otherexplanatory variables, depth to ground water and amount ofpesticide used per section, were includedto illustrate how additional information can be incorporatedinto this approach of identifying vulnerable areas.     

HEAVY RAINFALL DISTRIBUTIONS BY SEASON IN LOUISIANA: SYNOPTIC INTERPRETATIONS AND QUANTILE ESTIMATES1

ABSTRACT: In most studies, quantile estimates of extreme 24-hour rainfall are given in annual probabilities. The probability of experiencing an excessive storm event, however, differs throughout the year. As a result, this paper explored the differences between heavy rainfall distributions by season in Louisiana. It was concluded by using the Kruskal-Wallis and Mann-Whitney tests that the distribution of heavy rainfall events differs significantly between particular seasons at the sites near the Gulf Coast. Furthermore, seasonal frequency curves varied dramatically at the four sites examined. Mixed distributions within these data were not found to be problematic, but the mechanisms that produced the events were found to change seasonally. Extreme heavy rainfall events in winter and spring were primarily generated by frontal weather systems, while summer and fall events had high proportions of events produced by tropical disturbances and airmass (free-convective) conditions.     

NUTRIENT CONCENTRATION CRITERIA AND CHARACTERIZATION OF PATTERNS IN TROPHIC STATE FOR RIVERS IN HETEROGENEOUS LANDSCAPES1

ABSTRACT: A method is demonstrated for the development of nutrient concentration criteria and large scale assessment of trophic state in environmentally heterogeneous landscapes. The method uses the River Environment Classification (REC) as a spatial framework to partition rivers according to differences in processes that control the accrual and loss of algae biomass. The method is then applied to gravel bed rivers with natural flow regimes that drain hilly watersheds in New Zealand's South Island. An existing model is used to characterize trophic state (in terms of chlorophyll a as a measure of maximum biomass) using nutrient concentration, which controls the rate of biomass accrual, and flood frequency, which controls biomass loss. Variation in flood frequency was partitioned into three classes, and flow data measured at 68 sites was used to show that the classes differ with respect to flood frequency. Variation in nutrient concentration was partitioned at smaller spatial scales by subdivision of higher level classes into seven classes. The median of flood frequency in each of the three higher level classes was used as a control variable in the model to provide spatially explicit nutrient concentration criteria by setting maximum chlorophyll a to reflect a desired trophic state. The median of mean monthly soluble reactive phosphorus and soluble inorganic nitrogen measured at 68 water quality monitoring sites were then used to characterize the trophic state of each of the seven lower level classes. The method models biomass and therefore allows variation in this response variable to provide options for trophic state and the associated nutrient concentrations to achieve these. Thus it is less deterministic than using reference site water quality. The choice from among these options is a sociopolitical decision, which reflects the management objectives rather than purely technical considerations.     

Techniques for accuracy assessment of tree locations extracted from remotely sensed imagery

Remotely sensed imagery is becoming a common source of environmental data. Consequently, there is an increasing need for tools to assess the accuracy and information content of such data. Particularly when the spatial resolution of imagery is fine, the accuracy of image processing is determined by comparisons with field data. However, the nature of error is more difficult to assess. In this paper we describe a set of tools intended for such an assessment when tree objects are extracted and field data are available for comparison. These techniques are demonstrated on individual tree locations extracted from an IKONOS image via local maximum filtering. The locations of the extracted trees are compared with field data to determine the number of found and missed trees. Aspatial and spatial (Voronoi) analysis methods are used to examine the nature of errors by searching for trends in characteristics of found and missed trees. As well, analysis is conducted to assess the information content of found trees.     

Pastoral farmland habitat diversity in south-east Ireland

In this study, habitat surveys were undertaken on 50 grass-based farms in SE Ireland and data digitised onto aerial photography. Additional data i.e. stocking rates, and participation (or otherwise) in the Irish Rural Environment Protection Scheme (REPS) were collected and analysed as possible explanatory variables for farm habitat composition.Results indicated that approximately 14.3% of the land area of sampled farms comprised of semi-natural habitat types, a proportion substantially greater than has been reported for many other European countries. The most frequently recorded semi-natural habitats included, field boundaries, scrub, and deciduous and riparian woodlands.Multivariate analysis of farm habitat configuration showed a strong dichotomy between dairy and non-dairy farming systems. Habitats such as intensively managed grassland and built ground were closely associated with dairy-based enterprises. In contrast, the incidence of other habitat types was associated with non-dairy and/or REPS participating enterprises. The ecological quality of field boundaries as assessed by the Field Boundary Evaluation and Grading System (FBEGS) Index was significantly greater on dairy, compared with dry-stock farms.This dichotomy in farm habitat composition is not reflected within current Agri-Environment (AE) policy. Integration of locally important drivers of habitat diversity into the design and implementation of AE policy, is integral to the successful performance of AE schemes.     

Development and application of long-term sublethal whole sediment tests with Arenicola marina and Corophium volutator using Ivermectin as the test compound

Short-term whole sediment tests using the amphipod Corophium volutator and the polychaete Arenicola marina are now routinely used in Europe to assess the acute toxicity of marine sediments. However, there is still a need to develop longer-term assays which measure effects on sublethal endpoints that are more relevant to predicting impacts at the population level. The effect of increasing exposure times and measuring additional endpoints such as growth, on the sensitivity of these assays was investigated. The test compound used was the chemotherapeutant Ivermectin (IVM), used in aquaculture to treat sea lice infestations. IVM was found to be acutely toxic to both test organisms. Extending the lugworm test to 100 days increased sensitivity of survival by a factor of three; a significant reduction in casting rate was observed at concentrations an order of magnitude lower. This assay shows potential for detecting the sublethal effects of low concentrations of sediment contaminants. Increasing the exposure time did not seem to affect the sensitivity of the amphipod, but further method development is required.     

An improvement selection methodology for key performance indicators

Key performance indicators (KPIs) are critical measures for determining the health of a manufacturing plant in relationship to the plant’s goals. In today’s competitive environment, manufacturers cannot be careless about their business; in fact, they must ensure that their KPIs are effective and use them to make improvements when necessary. This paper describes a method for suggesting improvements to a manufacturer’s KPIs, based on the results achieved from a workshop to score the KPI on a number of predefined criteria. The approach uses a prospect theory approach to weight the scoring. Different problem formulations were derived that allow for both recommendations for improvements and the recommendations for disinvestments to over-performing KPIs. The authors applied the developed approach to two workshop outputs, each from independent manufacturers, and the results highlighted the significant difference between the two manufacturers in terms of improvement priorities and KPI assessment. The optimal improvement suggestions were compared to those found through a fast heuristic. It was determined that given the underlying assumptions of the approach that the heuristic solutions were just as adequate as the optimal ones.