thumbnail

Statistical Methods and Sampling Design for Estimating Step Trends in Surface-Water Quality

Water Resources Bulletin

By:
DOI: 10.1111/j.1752-1688.1988.tb00899.x

Links

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 J. L. Hodges-E. L. 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 is 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.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Statistical Methods and Sampling Design for Estimating Step Trends in Surface-Water Quality
Series title:
Water Resources Bulletin
DOI:
10.1111/j.1752-1688.1988.tb00899.x
Volume
24
Issue:
3
Year Published:
1988
Language:
English
Publisher:
American Water Resources Association
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
First page:
493
Last page:
503
Number of Pages:
11