Assessment of the spatial heterogeneity of weathering rates in upland catchments using the sodium dominance index and its significance in integrated catchment management.

The sodium dominance index was developed to quantify weathering rates and critical loads in Scotland, where atmospheric aerosols of maritime origin dominate over biogeochemical weathering in providing base cation inputs to catchment soils and drainage waters. High sodium dominance in river or lake water indicates low weathering rate. Here, this concept is evaluated using intensive temporal and spatial sampling strategies in two substantial catchments, one in Scotland and the other in central England, with particular reference to detection of groundwater inputs, and to possible problems from road salting in the calibration. In the Dee network, the spatial distribution of sodium dominance reflects the distribution of soil parent material geology, but land use also influences the equations. It is postulated that road density, via winter road salting, influences the sodium dominance calibration in lowland agricultural areas. Although road salting can also be problematic in some upland areas, the index still can provide clear indication of the likely severity of acid flush events in remote upland streams. In the Etherow catchment, sodium dominance varies markedly, sometimes over relatively small distances, reflecting soil type distribution, the occurrence of ground-water inputs to streams, and the influence of water in tributaries above the sampling point.

Calcite saturation in the River Dee, NE Scotland.

The spatial and temporal variations in calcite (calcium carbonate) solubility within the Dee basin of NE Scotland were assessed using water chemistry data gathered from a network of 59 sites monitored for water quality from June 1996 to May 1997. Calcite solubility, expressed in terms of a saturation index (SIcalcite), was determined from measured streamwater pH, Gran alkalinity and calcium concentrations and water temperature. In general, the waters of the Dee system are undersaturated with respect to calcite, though the saturation index is higher during the summer months indicating a dependency on flow conditions and biological activity. Under low-flow conditions, the streamwaters are dominated by water derived from the lower soil horizons and deeper groundwater stores and therefore, ions such as Gran alkalinity and calcium are at their highest concentrations as they are derived mainly from bedrock weathering. The influence of biological activity on the carbonate system is also evident as the observed pH and estimated EpCO2 values indicate strong seasonal patterns, with the highest pH and lowest EpCO2 values occurring during the summer low-flow periods. Only at three sites in the lowland region of the catchment, during the summer low-flow period, are the waters oversaturated. As such, the Dee system represents an extreme 'end-member' case when compared to many UK rivers that span both under- and oversaturated conditions during the year. Regression analysis highlights a systematic change in the SIcalcite-pH relationship in a broad east-west direction across the Dee system. At sites draining the relatively impermeable upland areas, the regression of SIcalcite against pH gives a straight line with a gradient in the range 1.6-2.4. Correspondingly, under the most extreme alkaline conditions found at sites draining lowland agricultural areas, a straight-line relationship exists but with a gradient of unity. It is concluded that these changes in the SIcalcite-pH relationship are due to variations in the bicarbonate system induced by the flow conditions and biological activity. Given the waters are undersaturated, then calcite precipitation and hence phosphorus co-precipitation cannot occur within the water column.

Modelling instream nitrogen variability in the Dee catchment, NE Scotland.

The Integrated Nitrogen in CAtchments model (INCA) was applied to the River Dee, Aberdeenshire, NE Scotland. To a first approximation the model was able to simulate the annual mean streamwater NO3-N concentrations observed along the length of the main channel. This provided the basis for using INCA to subsequently explore the effects of N deposition and land use management on streamwater NO3-N concentrations and loads. On an annual timescale, the model predictions suggest that NO3-N concentrations will decrease by 5% following a 20% reduction in fertiliser application. Furthermore, model results also suggest that a 50% increase in N deposition will cause a 15% increase in the streamwater NO3-N concentrations. The utility of INCA as a tool for catchment management is discussed, current limitations are highlighted and possible improvements are suggested.

Riparian zone influence on stream water chemistry at different spatial scales: a GIS-based modelling approach, an example for the Dee, NE Scotland.

A geographical information system (GIS-ARC/INFO) was used to collate existing spatial data sets on catchment characteristics to predict stream water quality using simple empirical models. The study, based on the river Dee catchment in NE Scotland, found that geological maps and associated geochemical information provided a suitable framework for predicting chemical parameters associated with acidification sensitivity (including alkalinity and base cation concentrations). In particular, it was found that in relatively undisturbed catchments, the parent material and geochemistry of the riparian zone, when combined with a simple hydrological flow path model, could be used to accurately predict stream water chemistry at a range of flows (Q95 to > Q5) and spatial scales (1-1000 km2). This probably reflects the importance of the riparian zone as an area where hydrological inputs to stream systems occur via flow paths in the soil and groundwater zones. Thus, evolution of drainage water chemistry appears to retain the geochemical characteristics of the riparian area as it enters the channel network. In more intensively managed catchments, riparian land use is a further influential factor, which can be incorporated into models to improve predictions for certain base cations. The utility in providing simple hydrochemical models, based on readily available data sets, to assist environmental managers in planning land use in catchment systems is discussed.