Advancing national climate change risk assessment to deliver national adaptation plans.

A wide range of climate vulnerability and risk assessments have been implemented using different approaches at different scales, some with a broad multi-sectoral scope and others focused on single risks or sectors. This paper describes the novel approach to vulnerability and risk assessment which was designed and put into practice in the United Kingdom's Second Climate Change Risk Assessment (CCRA2) so as to build upon its earlier assessment (CCRA1). First, we summarize and critique the CCRA1 approach, and second describe the steps taken in the CCRA2 approach in detail, providing examples of how each was applied in practice. Novel elements of the approach include assessment of both present day and future vulnerability, a focus on the urgency of adaptation action, and a structure focused around systems of receptors rather than conventional sectors. Both stakeholders and reviewers generally regarded the approach as successful in providing advice on current risks and future opportunities to the UK from climate change, and the fulfilment of statutory duty. The need for a well-supported and open suite of impact indicators going forward is highlighted.This article is part of the theme issue 'Advances in risk assessment for climate change adaptation policy'.

River channel conveyance capacity adjusts to modes of climate variability.

River networks are typically treated as conduits of fixed discharge conveyance capacity in flood models and engineering design, despite knowledge that alluvial channel networks adjust their geometry, conveyance, planform, extent and drainage density over time in response to shifts in the magnitude and frequency of streamflows and sediment supply. Consistent relationships between modes of climate variability conducive to wetter-/drier-than-average conditions and changes in channel conveyance have never been established, hindering geomorphological prediction over interannual to multidecadal timescales. This paper explores the relationship between river channel conveyance/geometry and three modes of climate variability (the El Niño-Southern Oscillation, Atlantic Multidecadal Oscillation, and Arctic Oscillation) using two-, five- and ten-year medians of channel measurements, streamflow, precipitation and climate indices over seven decades in 67 United States rivers. We find that in two thirds of these rivers, channel capacity undergoes coherent phases of expansion/contraction in response to shifts in catchment precipitation and streamflow, driven by climate modes with different periodicities. Understanding the sensitivity of channel conveyance to climate modes would enable better river management, engineering design, and flood predictability over interannual to multidecadal timescales.

Risks posed by climate change to the delivery of Water Framework Directive objectives in the UK.

The EU Water Framework Directive (WFD) is novel because it integrates water quality, water resources, physical habitat and, to some extent, flooding for all surface and groundwaters and takes forward river basin management. However, the WFD does not explicitly mention risks posed by climate change to the achievement of its environmental objectives. This is despite the fact that the time scale for the implementation process and achieving particular objectives extends into the 2020s, when climate models project changes in average temperature and precipitation. This paper begins by reviewing the latest UK climate change scenarios and the wider policy and science context of the WFD. We then examine the potential risks of climate change to key phases of the River Basin Management Process that underpin the WFD (such as characterisation of river basins and their water bodies, risk assessments to identify pressures and impacts, programmes of measures (POMs) options appraisal, monitoring and modelling, policy and management activities). Despite these risks the WFD could link new policy and participative mechanisms (being established for the River Basin Management Plans) to the emerging framework of national and regional climate change adaptation policy. The risks are identified with a view to informing policy opportunities, objective setting, adaptation strategies and the research agenda. Key knowledge gaps have already been identified during the implementation of the WFD, such as the links between hydromorphology and ecosystem status, but the overarching importance of linking climate change to these considerations needs to be highlighted. The next generation of (probabilistic) climate change scenarios will present new opportunities and challenges for risk analysis and policy-making.

Impacts of climate change on in-stream nitrogen in a lowland chalk stream: an appraisal of adaptation strategies.

The impacts of climate change on nitrogen (N) in a lowland chalk stream are investigated using a dynamic modelling approach. The INCA-N model is used to simulate transient daily hydrology and water quality in the River Kennet using temperature and precipitation scenarios downscaled from the General Circulation Model (GCM) output for the period 1961-2100. The three GCMs (CGCM2, CSIRO and HadCM3) yield very different river flow regimes with the latter projecting significant periods of drought in the second half of the 21st century. Stream-water N concentrations increase over time as higher temperatures enhance N release from the soil, and lower river flows reduce the dilution capacity of the river. Particular problems are shown to occur following severe droughts when N mineralization is high and the subsequent breaking of the drought releases high nitrate loads into the river system. Possible strategies for reducing climate-driven N loads are explored using INCA-N. The measures include land use change or fertiliser reduction, reduction in atmospheric nitrate and ammonium deposition, and the introduction of water meadows or connected wetlands adjacent to the river. The most effective strategy is to change land use or reduce fertiliser use, followed by water meadow creation, and atmospheric pollution controls. Finally, a combined approach involving all three strategies is investigated and shown to reduce in-stream nitrate concentrations to those pre-1950s even under climate change.

Exceptional weather in the midlands, UK, during 1988-1990 results in the rapid acidification of an upland stream.

Numerous catchment studies have identified the control exerted by hydrological processes on short-term (within a year) fluctuations in surface water acidity. Because discharge is, in turn, a function of broad climate parameters, there has been growing interest in the potential impact of changing precipitation and temperature regimes on water chemistry. The exceptionally warm and arid period 1988-1990 provided an opportunity to investigate the response of an acidic catchment in the East Midlands to an extreme climate scenario. The results obtained from three years of intensive monitoring indicated that between 1988 and 1990 there was a fourfold increase of the surface-water acidity at several observation sites within the Beacon catchment, Charnwood Forest, Leicestershire. As well as providing an indication of currently extreme hydrochemical conditions which in the near future may become the norm, these observations also have a bearing on the validity of long-term predictions derived from process-orientated models.

Inductive learning approaches to rainfall-runoff modelling.

Trying to model the rainfall-runoff process is a complex activity as it is influenced by a number of implicit and explicit factors--for example, precipitation distribution, evaporation, transpiration, abstraction, watershed topography, and soil types. However, this kind of forecasting is particularly important as it is used to predict serious flooding, estimate erosion and identify problems associated with low flow. Inductive learning approaches (e.g. decision trees and artificial neural networks) are particularly well suited to problems of this nature as they can often interpret underlying factors (such as seasonal variations) which cannot be modelled by other techniques. In addition, these approaches can easily be trained on the explicit factors (e.g. rainfall) and the inexplicit factors (e.g. abstraction) that affect river flow. Inductive learning approaches can also be extended to account for new factors that emerge over a period of time. This paper evaluates the application of decision trees and two artificial neural network models (the multilayer perceptron and the radial basis function network) to river flow forecasting in two flood prone UK catchments using real hydrometric data. Comparisons are made between the performance of these approaches and conventional flood forecasting systems.

Nocturnal river water temperatures: Spatial and temporal variations.

Nocturnal water temperature (Tw) affects the behaviour of aquatic biota and metabolism of whole rivers. However, night-time water temperature (nTw) is poorly understood because spot samples are typically taken during daylight hours, or Tw series are aggregated in ways that mask sub-daily properties. This paper examines 15-minute measurements of Tw and air temperature (Ta) collected at 36 sites in the Rivers Dove and Manifold, English Peak District. Data were stratified by day and night then analysed using hysteresis, auto-correlation and logistic regression techniques. Daily hysteresis loops show lagged responses between nTw and previous daylight air temperatures (dTa), plus the influence of groundwater and discharge variations. Logistic regression models were modified using a seasonal factor and explained between 80 and 94% of the variance in daily maximum nTw; minimum nTw were predicted with less skill, particularly for headwater sites in summer. Downstream variations in model parameters also reflect the influence of groundwater and/or riparian shade, and prevailing weather conditions. A case is presented where an intense summer storm resulted in the propagation of a thermal wave that produced maximum Tw at some sites during hours of darkness. Hence, our findings show that Tw management by riparian shade has to be seen in a catchment wide context, with anticipated benefits normalised for weather variability, extreme rainfall events, local influence of groundwater, and channel structures.

Evidence needed to manage freshwater ecosystems in a changing climate: turning adaptation principles into practice.

It is widely accepted that climate change poses severe threats to freshwater ecosystems. Here we examine the scientific basis for adaptively managing vulnerable habitats and species. Our views are shaped by a literature survey of adaptation in practice, and by expert opinion. We assert that adaptation planning is constrained by uncertainty about evolving climatic and non-climatic pressures, by difficulties in predicting species- and ecosystem-level responses to these forces, and by the plasticity of management goals. This implies that adaptation measures will have greatest acceptance when they deliver multiple benefits, including, but not limited to, the amelioration of climate impacts. We suggest that many principles for biodiversity management under climate change are intuitively correct but hard to apply in practice. This view is tested using two commonly assumed doctrines: "increase shading of vulnerable reaches through tree planting" (to reduce water temperatures); and "set hands off flows" (to halt potentially harmful abstractions during low flow episodes). We show that the value of riparian trees for shading, water cooling and other functions is partially understood, but extension of this knowledge to water temperature management is so far lacking. Likewise, there is a long history of environmental flow assessment for allocating water to competing uses, but more research is needed into the effectiveness of ecological objectives based on target flows. We therefore advocate more multi-disciplinary field and model experimentation to test the cost-effectiveness and efficacy of adaptation measures applied at different scales. In particular, there is a need for a major collaborative programme to: examine natural adaptation to climatic variation in freshwater species; identify where existing environmental practice may be insufficient; review the fitness of monitoring networks to detect change; translate existing knowledge into guidance; and implement best practice within existing regulatory frameworks.