ALBERT

Description: Forest riparian zones are a major in control of surface water quality. Base cation (BC) concentrations, fluxes, and cycling in the riparian zone merit attention because of increasing concern of negative consequences for re-acidification of surface waters from future climate and forest harvesting scenarios. We present a two-year study of BC and silica (Si) flow-weighted concentrations from 13 riparian zones and 14 streams in a boreal catchment in northern Sweden. The Riparian Flow-Concentration Integration Model (RIM) was used to estimate riparian zone flow-weighted concentrations and tested to predict the stream flow-weighted concentrations. Spatial variation in BC and Si concentrations as well as in flow-weighted concentrations was related to differences in Quaternary deposits, with the largest contribution from lower lying silty sediments and the lowest contribution from wetland areas higher up in the catchment. Temporal stability in the concentrations of most elements, a remarkably stable Mg / Ca ratio in the soil water and a homogeneous mineralogy suggest that the stable patterns found in the riparian zones are a result of distinct mineralogical upslope groundwater signals integrating the chemical signals of biological and chemical weathering. Stream water Mg / Ca ratio indicates that the signal is subsequently maintained in the streams. RIM gave good predictions of Ca, Mg, and Na flow-weighted concentrations in headwater streams. The difficulty in modelling K and Si suggests a stronger biogeochemical influence on these elements. The observed chemical dilution effect with flow in the streams was related to variation in groundwater levels and element concentration profiles in the riparian zones. This study provides a first step toward specific investigations of the vulnerability of riparian zones to changes induced by forest management or climate change, with focus on BC or other compounds.

Description: Climate-induced drought events have a significant influence on sulphate export from forested catchments in central Ontario, subsequently delaying the recovery of surface waters from acidification. In the current study, a model chain that employed a statistical downscaling model, a hydrological model and two hydrochemical models was used to forecast the chemical recovery of Plastic Lake sub-catchment 1 (PC1) from acidification under proposed deposition reductions and the A2 emission scenario of the Intergovernmental Panel on Climate Change. Any predicted recovery in stream acid neutralising capacity and pH owing to deposition reductions were clearly offset by large acid effluxes from climate-induced drought events. By 2100, ANC is predicted to show large variations ranging between 10 and −30 μmolc L−1. Similarly, predicted pH in 2100 is lower (〉0.05 of a pH unit) than the value simulated for 2000 (pH 4.35). Despite emission reductions, the future scenario paints a bleak picture of reacidification at PC1 to levels commensurate with those of the late 1970s. The principal process behind this reacidification is the oxidation of previously stored (reduced) sulphur compounds in wetlands during periods of low-flow (or drought), with subsequent efflux of sulphate upon re-wetting. Simulated catchment runoff under the A2 emissions scenario predictes increased intensity and frequency of low-flow events from approximately 2030 onwards. The Integrated Catchments model for Carbon indicated that stream DOC concentrations at PC1 will also increase under the future climate scenario, with temperature being the principal driver. Despite the predicted (significant) increase in DOC, pH is not predicted to further decline (beyond the climate-induced oxidation scenario), instead pH shows greater variability throughout the simulation. As echoed by many recent studies, hydrochemical models and model frameworks need to incorporate the drivers and mechanisms (at appropriate time-scales) that affect the key biogeochemical processes to reliably predict the impacts of climate change.

Description: This contribution closes this special issue of Hydrology and Earth System Sciences concerning the assessment of nitrogen dynamics in catchments across Europe within a semi-distributed Integrated Nitrogen model for multiple source assessment in Catchments (INCA). New developments in the understanding of the factors and processes determining the concentrations and loads of nitrogen are outlined. The ability of the INCA model to simulate the hydrological and nitrogen dynamics of different European ecosystems is assessed and the results of the first scenario analyses investigating the impacts of deposition, climatic and land-use change on the nitrogen dynamics are summarised. Consideration is given as to how well the model has performed as a generic tool for describing the nitrogen dynamics of European ecosystems across Arctic, Maritime, Continental and Mediterranean climates, its role in new research initiatives and future research requirements. Keywords: nitrogen, nitrate, ammonium, phosphorus, catchments, streams, rivers, river basins

Description: Dissolved organic carbon concentrations ([DOC]) in surface waters are increasing in many regions of Europe and North America. These increases are likely driven by a combination of changing climate, recovery from acidification and change in severity of winter storms in coastal areas. INCA-C, a process-based model of climate effects on surface water [DOC], was used to explore the mechanisms by which changing climate controls seasonal to inter-annual patterns of [DOC] in the lake and outflow stream of a small Finnish catchment between 1990 and 2003. Both production in the catchment and mineralization in the lake controlled [DOC] in the lake. Concentrations in the catchment outflow were controlled by rates of DOC production in the surrounding organic soils. The INCA-C simulation results were compared to those obtained using artificial neural networks (ANN). In general, "black box" ANN models provide better fits to observed data but process-based models can identify the mechanism responsible for the observed pattern. A statistically significant increase was observed in both INCA-C modelled and measured annual average [DOC] in the lake. This suggests that some of the observed increase in surface water [DOC] is caused by climate-related processes operating in the lake and catchment. However, a full understanding of surface water [DOC] dynamics can only come from catchment-scale process-based models linking the effects of changing climate and deposition on aquatic and terrestrial environments.

Description: Hydrological processes determine the transport of nutrients and passage of diffuse pollution. Consequently, catchments are likely to exhibit individual hydrochemical responses (sensitivities) to climate change, which are expected to alter the timing and amount of runoff, and to impact in-stream water quality. In developing robust catchment management strategies and quantifying plausible future hydrochemical conditions it is therefore equally important to consider the potential for spatial variability in, and causal factors of, catchment sensitivity, as it is to explore future changes in climatic pressures. This study seeks to identify those factors which influence hydrochemical sensitivity to climate change. A perturbed physics ensemble (PPE), derived from a series of global climate model (GCM) variants with specific climate sensitivities was used to project future climate change and uncertainty. Using the INtegrated CAtchment model of Phosphorus dynamics (INCA-P), we quantified potential hydrochemical responses in four neighbouring catchments (with similar land use but varying topographic and geological characteristics) in southern Ontario, Canada. Responses were assessed by comparing a 30 year baseline (1968–1997) to two future periods: 2020–2049 and 2060–2089. Although projected climate change and uncertainties were similar across these catchments, hydrochemical responses (sensitivities) were highly varied. Sensitivity was governed by quaternary geology (influencing flow pathways) and nutrient transport mechanisms. Clay-rich catchments were most sensitive, with total phosphorus (TP) being rapidly transported to rivers via overland flow. In these catchments large annual reductions in TP loads were projected. Sensitivity in the other two catchments, dominated by sandy loams, was lower due to a larger proportion of soil matrix flow, longer soil water residence times and seasonal variability in soil-P saturation. Here smaller changes in TP loads, predominantly increases, were projected. These results suggest that the clay content of soils could be a good indicator of the sensitivity of catchments to climatic input, and reinforces calls for catchment-specific management plans.

Description: Runoff generation processes and pathways vary widely between catchments. Credible simulations of solute and pollutant transport in surface waters are dependent on models which facilitate appropriate, catchment-specific representations of perceptual models of the runoff generation process. Here, we present a flexible, semi-distributed landscape-scale rainfall-runoff modelling toolkit suitable for simulating a broad range of user-specified perceptual models of runoff generation and stream flow occurring in different climatic regions and landscape types. PERSiST (the Precipitation, Evapotranspiration and Runoff Simulator for Solute Transport) is designed for simulating present-day hydrology; projecting possible future effects of climate or land use change on runoff and catchment water storage; and generating hydrologic inputs for the Integrated Catchments (INCA) family of models. PERSiST has limited data requirements and is calibrated using observed time series of precipitation, air temperature and runoff at one or more points in a river network. Here, we apply PERSiST to the river Thames in the UK and describe a Monte Carlo tool for model calibration, sensitivity and uncertainty analysis.

Description: Climate-induced drought events have a significant influence on sulphate export from forested catchments in central Ontario, subsequently delaying the recovery of surface waters from acidification. In the current study, a model chain that employed a statistical downscaling model, a hydrological model and two hydrochemical models was used to forecast the chemical recovery of Plastic Lake sub-catchment 1 (PC1) from acidification under proposed deposition reductions and the A2 emission scenario of the Intergovernmental Panel on Climate Change. Any predicted recovery in stream acid neutralising capacity and pH owing to deposition reductions were clearly offset by large acid effluxes from climate-induced drought events. By 2100, ANC is predicted to show large variations ranging between 10 and −30 μmolc L−1. Similarly, predicted pH in 2100 is lower (〉0.05 of a pH unit) than the value simulated for 2000 (pH 4.35). Despite emission reductions, the future scenario paints a bleak picture of reacidification at PC1 to levels commensurate with those of the late 1970s. The principal process behind this reacidification is the oxidation of previously stored (reduced) sulphur compounds in wetlands during periods of low-flow (or drought), with subsequent efflux of sulphate upon re-wetting. Simulated catchment runoff under the A2 emissions scenario predictes increased intensity and frequency of low-flow events from approximately 2030 onwards. The Integrated Catchments model for Carbon indicated that stream DOC concentrations at PC1 will also increase under the future climate scenario, with temperature being the principal driver. Despite the predicted (significant) increase in DOC, pH is not predicted to further decline (beyond the climate-induced oxidation scenario), instead pH shows greater variability throughout the simulation. As echoed by many recent studies, hydrochemical models and model frameworks need to incorporate the drivers and mechanisms (at appropriate time-scales) that affect the key biogeochemical processes to reliably predict the impacts of climate change.

Description: Dissolved organic carbon concentrations ([DOC]) in surface waters are increasing in many regions of Europe and North America. These increases are likely driven by a combination of changing climate, recovery from acidification and change in severity of winter storms in coastal areas. INCA-C, a process-based model of climate effects on surface water [DOC], was used to explore the mechanisms by which changing climate controls seasonal to inter-annual patterns of [DOC] in the lake and outflow stream of a small Finnish catchment between 1990 and 2003. Both production in the catchment and mineralization in the lake controlled [DOC] in the lake. Concentrations in the catchment outflow were controlled by rates of DOC production in the surrounding organic soils. The INCA-C simulation results were compared to those obtained using artificial neural networks (ANN). In general, "black box" ANN models provide better fits to observed data but process-based models can identify the mechanism responsible for the observed pattern. A statistically significant increase was observed in both INCA-C modelled and measured annual average [DOC] in the lake. This suggests that some of the observed increase in surface water [DOC] is caused by climate-related processes operating in the lake and catchment. However, a full understanding of surface water [DOC] dynamics can only come from catchment-scale process-based models linking the effects of changing climate and deposition on aquatic and terrestrial environments.

Description: Hydrological processes determine the transport of nutrients and passage of diffuse pollution. Consequently, catchments are likely to exhibit individual hydrochemical responses (sensitivities) to climate change, which is expected to alter the timing and amount of runoff, and to impact in-stream water quality. In developing robust catchment management strategies and quantifying plausible future hydrochemical conditions it is therefore equally important to consider the potential for spatial variability in, and causal factors of, catchment sensitivity, as to explore future changes in climatic pressures. This study seeks to identify those factors which influence hydrochemical sensitivity to climate change. A perturbed physics ensemble (PPE), derived from a series of Global Climate Model (GCM) variants with specific climate sensitivities was used to project future climate change and uncertainty. Using the Integrated Catchment Model of Phosphorus Dynamics (INCA-P), we quantified potential hydrochemical responses in four neighbouring catchments (with similar land use but varying topographic and geological characteristics) in southern Ontario, Canada. Responses were assessed by comparing a 30 year baseline (1968–1997) to two future periods: 2020–2049 and 2060–2089. Although projected climate change and uncertainties were similar across these catchments, hydrochemical responses (sensitivity) were highly varied. Sensitivity was governed by soil type (influencing flow pathways) and nutrient transport mechanisms. Clay-rich catchments were most sensitive, with total phosphorus (TP) being rapidly transported to rivers via overland flow. In these catchments large annual reductions in TP loads were projected. Sensitivity in the other two catchments, dominated by sandy-loams, was lower due to a larger proportion of soil matrix flow, longer soil water residence times and seasonal variability in soil-P saturation. Here smaller changes in TP loads, predominantly increases, were projected. These results suggest that the clay content of soils could be a good indicator of the sensitivity of catchments to climatic input, and reinforces calls for catchment-specific management plans.

Description: While runoff is often a first-order control on water quality, runoff generation processes and pathways can vary widely between catchments. Credible simulations of solute and pollutant transport in surface waters are dependent on models which facilitate appropriate representations of perceptual models of the runoff generation process. With a few exceptions, models used in solute transport simulations enforce a single, potentially inappropriate representation of the runoff generation process. Here, we present a flexible, semi-distributed landscape scale rainfall-runoff model suitable for simulating a broad range of user-specified perceptual models of runoff generation and stream flow occurring in different climatic regions and landscape types. PERSiST, the Precipitation, Evapotranspiration and Runoff Simulator for Solute Transport; is designed for simulating present day conditions and projecting possible future effects of climate or land use change on runoff, catchment water storage and solute transport. PERSiST has limited data requirements and is calibrated using observed time series of precipitation, air temperature and runoff at one or more points in a river network. Here, we present a first application of the model to the Thames River in the UK and describe a Monte Carlo tool for parameter optimization and sensitivity analysis.