STATISTICAL METHODS AND SAMPLING DESIGN FOR ESTIMATING STEP TRENDS IN SURFACE-WATER QUALITY1

ABSTRACT: This paper addresses two components of the problem of estimating the magnitude of step trends in surface water quality. The first is finding a robust estimator appropriate to the data characteristics expected in water-quality time series. The Hodges-Lehmann class of estimators is found to be robust in comparison to other nonparametric and moment-based estimators. A seasonal Hodges-Lehmann estimator is developed and shown to have desirable properties. Second, the effectiveness of various sampling strategies are examined using Monte Carlo simulation coupled with application of this estimator. The simulation is based on a large set of total phosphorus data from the Potomac River. To assure that the simulated records have realistic properties, the data are modeled in a multiplicative fashion incorporating flow, hysteresis, seasonal, and noise components. The results demonstrate the importance of balancing the length of the two sampling periods and balancing the number of data values between the two periods. The inefficiency of sampling at frequencies much in excess of 12 samples per year is demonstrated. Rotational sampling designs are discussed, and efficient designs, at least for this river and constituent, are shown to involve more than one year of active sampling at frequencies of about 12 per year.     

Evaluating the effects of spatial monitoring policy on groundwater quality portrayal

What size sample is sufficient for spatially sampling ambient groundwater quality? Water quality data are only as spatially accurate as the geographic sampling strategies used to collect them. This research used sequential sampling and regression analysis to evaluate groundwater quality spatial sampling policy changes proposed by California's Department of Water Resources. Iterative or sequential sampling of a hypothetical groundwater basin's water quality produced data sets from sample sizes ranging from 2.8% to 95% coverage of available point sample sites. Contour maps based on these sample data sets were compared to an original (control), mapped hypothetical data set, to determine at which point map information content and pattern portrayal are not improved by increasing sample sizes. Comparing series of contour maps of ground water quality concentration is a common means of evaluating the geographic extent of groundwater quality change. Comparisons included visual inspection of contout maps and statistical tests on digital versions of these map files, including correlation and regression products. This research demonstrated that, down to about 15% sample site coverage, there is no difference between contour maps produced from the different sampling strategies and the contout map of the original data set.     

A FIELD TECHNIQUE FOR WEIGHING BEDLOAD SAMPLES1

ABSTRACT: A technique for weighing bedload samples that was developed for laboratory use has been modified for field application. The technique involves determining the submerged weight of bedload samples as they are collected. The submerged weights are converted to dry weights from a knowledge of the specific gravity of the bedload material. The technique makes bedload transport data available immediately and eliminates costly and time-consuming steps involved with saving samples for laboratory analysis. Only samples designated for particle-size or other lab analyses need to be saved.     

Testing hypotheses about management to enhance habitat for feeding birds in a freshwater wetland

The level of water was manipulated in a freshwater wetland, with the aim of enhancing abundances of benthic animals and, ultimately, improving habitat for feeding birds (Japanese Snipe, Gallinago hardwickii). We tested whether these actions had the predicted and desired effects on benthic animals, by contrasting changes in two managed locations to one control location which was left unmanipulated. The number of taxa and abundances of chironomids decreased strongly and significantly in the manipulated locations, while the abundance of oligochaetes appeared to vary in a seasonal manner. Temporal variability of the structure and composition of assemblages was also increased in manipulated locations. Such effects have previously been suggested to indicate stress in benthic assemblages. Therefore, in contrast to what was predicted, managerial actions made benthic fauna less abundant and thus, less suitable as habitat for feeding birds. Several general lessons can be learned from these results. (1) Effects of managerial actions like these are difficult to predict a priori and can only be reliably evaluated with an experimental framework. (2) Because abundances of animals vary naturally, evaluations of managerial actions must include appropriate spatial replication. (3) Sampling at hierarchical temporal scales is important, because abundances of animals may vary in an unpredictable manner at short temporal scales and because changes in temporal variability may be a symptom of stress. (4) Combined use of uni- and multivariate techniques provides a comprehensive set of tools to assess the effects of restoration and creation of new habitats. Finally, these results emphasise the need for clear predictions about desired outcomes and specific experimental plans about how to test whether the desired results were achieved, before managerial actions are taken. Although this is often very difficult to achieve in real situations, it is necessary for practices of management to evolve on the basis of sound empirical experience.     

Mapping Three‐Dimensional Water‐Quality Data in the Chesapeake Bay Using Geostatistics1

Abstract:  Data interpretation and visualization software tools with geostatistical capabilities were adapted, customized, and tested to assist the Chesapeake Bay Program in improving its water‐quality modeling protocols. Tools were required to interpolate, map, and visualize three‐dimensional (3D) water‐quality data, with the capability to determine estimation errors. Components of the software, originally developed for ground‐water modeling, were customized for application in estuaries. Additional software components were developed for retrieval, and for pre‐ and post‐ processing of data. The Chesapeake Bay Program uses the 3D mapped data for input to the Bay water‐quality model that projects the future health of the Bay and its tidal tributary system. In determining water‐quality attainment criteria, 3D kriging estimation errors are needed as a statistical measure of uncertainty. Furthermore, given the high cost of installing and operating new monitoring stations, geostatistical techniques can assist the Chesapeake Bay Program in the identification of suitable data collection locations. Following the evaluation, selection, and development of the software components phase, 3D ordinary kriging techniques with directional semi‐variograms to account for anisotropy were successfully demonstrated for mapping 3D fixed station water‐quality data, such as dissolved oxygen and salinity. Additionally, an improved delineation tool was implemented to simulate the upper and lower pycnocline boundary surfaces allowing the segregation of the interpolated 3D data into three separate zones for a better characterization of the pycnocline layer.     

Estimation of the spatial covariance in Universal Kriging: Application to forest inventory

This paper presents a simple least squares procedure for estimating the spatial covariance and compares it with the numerically more difficult restricted maximum likelihood procedure. Thereafter, it compares design-based and kriging techniques for the estimation of spatial averages in the context of double sampling, as used in forest inventory, where terrestrial sample plots are combined with auxiliary information based on aerial photographs. A case study illustrates the theory.     

Prenatal diagnosis and psychological distress: Amniocentesis or chorionic villus biopsy?

The psychological reactions of 211 women undergoing prenatal diagnosis (PND) with amniocentesis (group A, n = 122) or chorionic villus biopsy (group V, n = 90) were exmained by questionnaires and interviews. The distress experienced while waiting for the test, during the test procedure, and while waiting for the result was reported by the women, both in questionnaires and in interviews. In the questionnaires, no difference between the two diagnostic methods was observed. In the interviews, however, the women undergoing amniocentesis appeared significantly more distressed by the procedure. In group A 97 per cent and in group V 100 per cent wished a method which, like chorionic villus biopsy, could be used in the first weeks of pregnancy. The risk of miscarriage was, as described in other studies, regarded as a serious threat by the pregnant women.     

Evaluating Alternative Temporal Survey Designs for Monitoring Wetland Area and Detecting Changes Over Time in California

Evaluation of wetland extent and changes in extent is a foundation of many wetland monitoring and assessment programs. Probabilistic sampling and mapping provides a cost‐effective alternative to comprehensive mapping for large geographic areas. One unresolved challenge for probabilistic or design‐based approaches is how best to monitor both status (e.g., extent at a single point in time) and trends (e.g., changes in extent over time) within a single monitoring program. Existing wetland status and trends (S&T) monitoring programs employ fixed sampling locations; however, theoretical evaluation and limited implementation in other landscape monitoring areas suggest that alternative designs could increase statistical efficiency and overall accuracy. In particular, designs that employ both fixed and nonfixed sampling locations (alternately termed permanent and temporary samples), termed sampling with partial replacement (SPR), are considered to efficiently and effectively balance monitoring current status with detection of trends. This study utilized simulated sampling to assess the performance of fixed sampling locations, SPR, and strictly nonfixed designs for monitoring wetland S&T over time. Modeled changes in wetland density over time were used as inputs for sampling simulations. In contrast to previous evaluations of SPR, the results of this study support the use of a fixed sampling design and show that SPR may underestimate both S&T.