Evaluating the effects of spatial monitoring policy on groundwater quality portrayal

Abstract

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 contour maps and statistical tests on digital versions of these map files, including correlation and regression products. This research demonstrated that, clown to about 15% sample site coverage, there is no difference between contour maps produced from the different sampling strategies and the contour map of the original data set.How many groundwater sample sites are necessary to determine and map groundwater quality in a basin? This is not only a statistical question, since it is often more useful to know the geographical distribution of water quality variables than it is to know the mean values of a basin. Careful sampling is necessary to determine the source areas and distribution of pollutants or toxic natural constituents. The goal of this research is to motivate scientists and natural resources managers to consider the effect of sampling designs when designing and implementing groundwater quality monitoring programs and when making decisions based on visual and statistical interpretations of groundwater quality data and water quality contour maps.

Spatial Sampling Strategies for Mapping a Volcanic Ground Water Plume in Sierra Valey, California

“…For the purposes of this experiment, however, it was assumed that the number of original data points (57, 45, and 63) was a sufficient density at 15%, or about five wells per township (the original grid resolution was 1 well per mi 2 or per 2.6 km 2) . This density was tested and established for ground water quality by Beach (1990;Luzzadder-Beach 1995) and corroborates results by Rouhani (1985) for sampling ground water depths. Other findings in the literature support the notion that ground water quality sample sizes need not be large to be statistically accurate (Hsueh and Rajagopal 1988).…”

“…Although small ground water quality databases can be statistically efficient (Beach 1987(Beach , 1990Hsueh and Rajagopal 1988;Luzzadder-Beach 1995), databases that are too small are useless for determining and mapping both temporal and spatial patterns. Although 15% sampling density (about five wells per township) was shown to be sufficient in Beach's (1990;Luzzadder-Beach 1995) controlled, hypothetical studies and by Rouhani (1985), the maps produced by Strategies 2 and 3 of this real-world study of Sierra Valley did not adequately reproduce basin spatial patterns of electrical conductivity's changes through time. Their respective spatial sampling densities were simply too coarse.…”

“…A key challenge to assessing ground water quality accurately is determining the most appropriate field sampling design for mapping ground water quality. Previous research has studied two important considerations of best sampling designs: the most efficient number of sampling locations in a ground water basin and geographic pattern of these locations (Ward 1981;Nelson and Ward 1981;Pfannkuch 1982;Rouhani 1985Rouhani , 1986Rajagopal 1986Rajagopal , 1987Beach 1987Beach , 1990Hsueh and Rajagopal 1988;Loaiciga 1989;Natarajan and Rajagopal 1994;Luzzadder-Beach 1995). A third consideration that has received less attention is the temporal dimension in spatial sampling of ground water quality, including both the time intervals between sampling events, and measuring patterns of water quality change over time.…”

Deriving Natural Background Levels of Arsenic at the Meso-Scale Using Site-Specific Datasets: An Unorthodox Method

“…Essential for the definition of NBLs, besides methods and protocols, is the availability of a set of hydrogeochemical data representative of the pristine groundwater composition, including the concentration of the pollutant/contaminant of interest and major ions, as well as the physicochemical parameters of water. The higher the quality, quantity, and homogeneous distribution of the data, the more accurate the NBL definition and the disentanglement of processes that cause pollutant release in groundwater [6][7][8]. The dataset is most often acquired with dedicated monitoring campaigns in pre-existing or new boreholes and springs (feasible for relatively small areas in the order of 100 km 2 ) [9][10][11][12][13] or from groundwater quality monitoring networks implemented at the national level [14][15][16][17][18] or, as for Italy, at the scale of administrative regions [8,[19][20][21][22][23][24].…”