A new version of the Integrated Nitrogen in Catchments model (INCA) was developed and tested using flow and streamwater nitrate concentration data collected from the River Kennet during 1998. INCA is a process-based model of the nitrogen cycle in the plant/soil and instream systems. The model simulates the nitrogen export from different land-use types within a river system, and the in-stream nitrate and ammonium concentrations at a daily time-step. The structure of the new version differs from the original, in that soil-water retention volumes have been added and the interface adapted to permit multiple crop and vegetation growth periods and fertiliser applications. The process equations are now written in terms of loads rather than concentrations allowing a more robust tracking of mass conservation when using numerical integration. The new version is able to reproduce the seasonal dynamics observed in the streamwater nitrogen concentration data, and the loads associated with plant/soil system nitrogen processes reported in the literature. As such, the model results suggest that the new structure is appropriate for the simulation of nitrogen in the River Kennet and an improvement on the original model. The utility of the INCA model is discussed in terms of improving scientific understanding and catchment management.

This study focuses on spatial variability of throughfall water and chemistry and forest floor water content within a Douglas fir (Pseudotsuga menziesii, Franco L.) forest plot. Spatial patterns of water and chemistry (NH 4 + , NO 3 -, SO 4 2-, Cl -, Mg 2+ , Ca 2+ , Na + and K + ) were compared and tested for stability over time. The spatial coefficient of variation (CV) was between 18 and 26% for amounts of throughfall water and ions, and 17% for forest floor water content. Concentrations and amounts of all ions were correlated significantly. Ion concentrations were negatively correlated with throughfall water amounts, but, except for NH 4 + , there was no such relation between throughfall water and ion amounts. Spatial patterns of throughfall water fluxes and forest floor water contents were consistent over time; patterns of ion fluxes were somewhat less stable. Because of the spatial variability of forest floor thickness and drainage, it was not possible to relate patterns in throughfall water directly to patterns in water content. The spatial variability of throughfall nitrogen and forest floor water contents can cause significant variability in NO 3 -production within the plot studied.

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The production of fresh drinking water from brackish groundwater by reverse osmosis (BWRO) is becoming more attractive, even in temperate climates. For successful application of BWRO, the following approach is advocated: (1) select brackish source groundwater with a large volume and a composition that will yield a concentrate (waste water) with low mineral saturation; (2) maintain the feed water salinity at a constant level by pumping several wells with different salinities; (3) keep the permeate-to-concentrate ratio low, to avoid supersaturation in the concentrate; (4) keep the system anoxic (to avoid oxidation reactions) and pressurized (to prevent formation of gas bubbles); and (5) select a confined aquifer for deep well injection where groundwater quality is inferior to the membrane concentrate. This approach is being tested at two BWRO pilot plants in the Netherlands. Research issues are the pumping of a stable brackish source water, the reverse osmosis system performance, membrane fouling, quality changes in the target aquifer as a result of concentrate disposal, and clogging of the injection well. First evaluations of the membrane concentrate indicate that it is crucial to understand the kinetics of mineral precipitation on the membranes, in the injection wells, and in the target aquifer.

The value of nitrogen (N) field measurements for the calibration of parameters of the INCA nitrogen in catchment model is explored and quantified. A virtual catchment was designed by running INCA with a known set of parameters, and field measurements were selected from the model run output. Then, using these measurements and the Shuffled Complex Evolution Metropolis algorithm (SCEM-UA), four of the INCA model parameters describing N transformations in the soil were optimised, while the measurement uncertainty was increased in subsequent steps. Considering measurement uncertainty typical for N field studies, none of the synthesised datasets contained sufficient information to identify the model parameters with a reasonable degree of confidence. Parameter equifinality occurred, leading to considerable uncertainty in model parameter values and in modelled N concentrations and fluxes. Fortunately, combining the datasets in a multi-objective calibration was found to be effective in dealing with these equifinality problems. With the right choice of calibration measurements, multi-objective calibrations resulted in lower parameter uncertainty. The methodology applied in this study, using a virtual catchment free of model errors, is proposed as a useful tool foregoing the application of a N model or the design of a N monitoring program. For an already gauged catchment, a virtual study can provide a point of reference for the minimum uncertainty associated with a model application. When setting up a monitoring program, it can help to decide what and when to measure. Numerical experiments indicate that for a forested, N-saturated catchment, a fortnightly sampling of NO 3 and NH 4 concentrations in stream water may be the most cost-effective monitoring strategy.