Qualitative time trend analysis of ground water monitoring networks : An example from The Netherlands

The detection of significant (short-term) time trends is one of the major goals of ground water monitoring networks. These trends can be used to recognize active geochemical processes and potential environmental threats. This paper presents a case history of time trend analysis on macrochemical parameters of ground water quality. It shows the difficulties and traps that are generally encountered in such studies. The data used originated from the Dutch National Groundwater Quality Monitoring Network. This network is operative since 1979, and keeps track of the ground water composition at 350 locations at two depths (ca. 10 and 25 m below surface; general density, one location per 100 km(2)). Prior to the trend analysis the data set was divided into geochemically homogeneous groups using fuzzy c-means clustering. Each group represents a specific ground water type, characterized by a distinct source (seawater, surface water or precipitation) and a unique combination of dominant geochemical processes (e.g. mineralization of organic matter, carbonate dissolution and cation exchange).To study trends qualitatively, the concentrations of the various macro-constituents in ground water are correlated with time of sampling. The nonparametric and outlier insensitive Spearman rank correlation coefficient is computed per well screen. A frequency distribution of correlation coefficients is formed by combining the Spearman correlation coefficients of all individual wells within a homogeneous group. This distribution is tested for trends against the appropriate theoretical distribution of zero correlation by use of the Kolmogorov-Smirnov one-sample test. The type of trend is derived from the shape of the distribution.Most ground water types show statistically significant qualitative trends, of which many, however, are caused by changes in the sampling and analytical procedures over the monitoring period. After elimination of differences in limits of detection for NO3, total-P, and NH4, most trends in these compounds disappeared. In some water types trends for alkalinity, apparent trends for pH, Ec, and total-P are caused by variations in the laboratory practice, e.g. varying storage procedures, leading to erroneous analyses. Other parameters showed statistically significant trends, related to geochemical processes.The most interesting and most substantial trends are observed in the water type characterized by infiltrating rainwater with agricultural pollutants. In this water type the lowering ground water table induces lower rates of evapotranspiration, giving lower concentrations in time of conservative parameters (Cl, Na, Ca). The aerated zone is enlarged, resulting in increased oxidation of organic material, less efficient nutrient (NO3, K) uptake by plant roots, leading to increased ground water concentrations of nutrients. In other water types trends are quantitatively small. However, trends are not necessarily linear, and all should be closely monitored in future.