Optimization of River Sampling: Application to Nutrients Distribution in Tagus River Estuary.

Abstract

The assessment of river water pollution trends is affected by the seasonal variation of river conditions, the variability of pollution sources, the heterogeneity of pollutants distribution, the representativeness/uncertainty of sampling, and the uncertainty of sample analysis. This work presents a methodology to model the uncertainty of river water sampling based on available information about the spatial distribution of the studied parameter in the river. The uncertainty from "single sampling" (SS) or by production of a composite sample by mixing m subsamples collected randomly (RS) or in a line that crosses the sampling circle (LS) was studied. This methodology was applied to the determination of nutrients (NO x, NO2, PO4, and SiO2) in an area of the Tagus River estuary with a range of about 350 m. This methodology can be applied to the determination of the mean value of other parameters in other river areas requiring a previous study of system heterogeneity. The spatial distribution of nutrients in the studied river area was characterized from the analysis of 10 samples collected at known geographical coordinates. The system heterogeneity was described by a three-dimensional ( x, y, z) surface with x and y variables for samples positions and z variable representing the measured nutrient levels. The randomization of this surface for the uncertainty of coordinates and repeatability of nutrient concentration measurement, using Monte Carlo simulations, allowed estimation of the uncertainty of the three sampling strategies: SS, RS, and LS. The uncertainty from RS and LS is equivalent and significantly smaller than that from SS when at least three subsamples are mixed in the composite sample. The sampling relative standard uncertainty ranged from 0.31% to 4.4%, producing nutrient concentration estimates in the river area with a relative expanded uncertainty from 5.9% to 10% with approximately 95% confidence level (coverage factor of 2). The used spreadsheet is available as Supporting Information.