Application of curve-fitting techniques to develop numerical calibration procedures for a river water quality model

River water quality models are often constrained by a lack of understanding of model structures and complicated estimation procedures for unknown parameters. This paper demonstrates a new calibration strategy by setting up a simple model structure for river water quality. The unknown parameters of RWQM were calibrated through the use of small river water quality data sets. In order to facilitate the calibration procedure, data reconstruction and parameter estimation were performed by the systematic application of cubic smoothing spline, polynomial curve-fitting and nonlinear least squares. The quality of calibrated parameters was estimated by developing a sensitivity ranking system. The variation of model outputs showed a slight difference at a sensitivity index of less than 10% and a significant difference at a sensitivity index of more than 50%. The one-way analysis of variance showed a large p-value of 0.8431, indicating that differences between model data and measured data means are not significant. The calibrated model responses and their statistical envelopes were in good agreement with the river water quality data. A MATLAB GUI platform was developed to perform numerical and graphical analysis, which can be used as a relatively simple but robust calibration tool to support model application and data analysis.

A hybrid monitoring and modelling approach to assess the contribution of sources of glyphosate and AMPA in large river catchments

Large river catchments with mixed land use capture pesticides from many sources, and degradable pesticides are converted during downstream transport. Unravelling the contribution of pesticide source and the effect of degradation processes is a challenge in such areas. However, insight and understanding of the sources is important for targeted management, especially when water is abstracted from the river for drinking water production. The river Meuse is such a case. A long-term monitoring data set was applied in a modelling approach for assessing the contribution of waste water treatment plants (WWTPs) and tributaries (sub-basins) to surface water contamination, and to evaluate the effect of decay on the downstream concentrations of glyphosate and AMPA at the point of drinking water abstraction. The results show that WWTPs are important contributors for glyphosate and AMPA in large river catchments with mixed land uses. In the studied area, the river Meuse in the Netherlands, the relative contribution of WWTP effluents is above 29% for glyphosate and around 12% for AMPA. Local industries are found to be potentially big contributors of AMPA. Glyphosate entering the river system is gradually converted to AMPA and other degradation productions, which results in downstream loads that are considerably lower than the sum of all influxes. In summer when the travel time is longer due to lower discharge, the first order decay of glyphosate in the river Meuse is estimated to result in about 50% reduction of the downstream glyphosate concentrations over a river stretch of 250km. The contribution of glyphosate decay to the observed AMPA concentrations ranges between 2% and 10%. Contributions are sensitive to seasonal variations in discharge that influence the concentrations through dilution and degradation.