S-199 Assessment of ground-water quality trends under the U.S. Geological Survey National Water-Quality Assessment Program (NAWQA) included the analysis of samples collected on a quarterly basis for 1 yr between 2001 and 2005. he purpose of this quarterly sampling was to test the hypothesis that variations in the concentration of water-quality parameters of selected individual wells could demonstrate that the intra- annual variation was greater or less than the decadal changes observed for a trend network. Evaluation of more than 100 wells over this period indicates that 1 yr of quarterly sampling is not adequate to address the issue of intra-annual variation because variations seem to be random and highly variable between different wells in the same networks and among networks located in different geographical areas of the USA. In addition, the data from only 1 yr makes it impossible to assess whether variations are due to univariate changes caused by land use changes, hydrologic variations due to variable recharge, or variations caused by ground-water pumping. hese data indicate that funds allocated to this activity can be directed to the collection of more effective trend data, including age dating of all wells in the NAWQA network using multiple techniques. Continued evaluation of data and updating of monitoring plans of the NAWQA program is important for maintaining relevance to national goals and scientific objectives. Evaluation of Intra-annual Variation in U.S. Geological Survey National Water Quality Assessment Ground Water Quality Data Michael R. Rosen,* Frank D. Voss, and Jorge A. Arufe USGS T he U.S. Geological Survey National Water Quality Assessment (NAWQA) program samples ground-water wells for water quality at different spatial and temporal scales (Rosen and Lapham, 2008). Determining the most cost effective and scientifically beneficial temporal sampling period is essential to being able to adequately assess changes in ground-water quality (Rosen, 2004). Although optimization techniques have been developed for high- intensity local sampling programs for contaminant plumes (e.g., Barcelona et al., 1989; Herrera and Pinder, 2005), optimization techniques for large networks are less common. A study of the effect of temporal variability during sample collection on analysis of spatial variability was conducted over an area of approximately 20 km 2 in Ohio (Ritzi et al., 1993), but this study was designed to assess whether the length of time it took to sample a spatially distributed set of wells induced greater variability than the inherent spatial variability in the water-quality parameters analyzed. However, in all of these studies, intense sampling, on the order of one sample every 1 wk, were undertaken to determine optimal sampling periods. One component of the NAWQA ground-water quality sampling plan is to sample five wells in a 30-well network on a quarterly basis (see Rosen and Lapham, 2008) to determine if this intra-annual varia- tion (of selected parameters) could be used to demonstrate whether decadal changes in water quality were greater or less than the intra-an- nual variation. Quarterly sampling was designed to be conducted in 1 yr within the decadal sampling period. However, these data were not collected to establish an optimal temporal sampling strategy. Sampling for only 1 yr (four sampling points) limits the ability to conduct statis- tical tests on the data set, but the number of wells sampled nationwide (>100 wells) allows a comparison of intra-annual variations in differ- ent land use settings and geographic areas. Quarterly sampling (the collection of samples once every 3 mo for 1 yr) was deemed important in the NAWQA ground-water trends design because the magnitude of change within a single year may be greater than long-term changes. For example, using Monte Carlo sim- ulations, Yue et al. (2002) showed that the power of the Mann-Ken- dall test to detect trends depends on the preselected significance level, the absolute magnitude of the trend, the number of observations, and the amount of variation within the interval of interest. his means that for any site that displays seasonal change in chemistry that is simi- Abbreviations: AgLUS, agricultural land use study; LUS, land use study; MAS, major aquifer study; NAWQA, National Water-Quality Assessment Program; UrLUS, urban land use study; VOCs, volatile organic compounds. M.R. Rosen, USGS, 2730 North Deer Run Rd., Carson City, NV 89701. F.D. Voss, USGS, 934 Broadway, Suite 300, Tacoma, WA 98402. J.A. Arufe, USGS, 160 N. Stephanie St., Henderson, NV 89074. Copyright © 2008 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including pho- tocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Published in J. Environ. Qual. 37:S-199–S-208 (2008). doi:10.2134/jeq2007.0052 Received 29 Jan. 2007. *Corresponding author (mrosen@usgs.gov). © ASA, CSSA, SSSA 677 S. Segoe Rd., Madison, WI 53711 USA SPECIAL SUBMISSIONS