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. (c) 2006 Elsevier B.V. All rights reserved.

Integrated modelling of climate change impacts on water resources and quality in a lowland catchment: River Kennet, UK

An integrated approach to climate change impact assessment is explored by linking established models of regional climate (SDSM), water resources (CATCHMOD) and water quality (INCA) within a single framework. A case study of the River Kennet illustrates how the system can be used to investigate aspects of climate change uncertainty, deployable water resources, and water quality dynamics in upper and lower reaches of the drainage network. The results confirm the large uncertainty in climate change scenarios and freshwater impacts due to the choice of general circulation model (GCM). This uncertainty is shown to be greatest during summer months as evidenced by large variations between GCM-derived projections of future tow river flows, deployable yield from groundwater, severity of nutrient flushing episodes, and Long-term trends in surface water quality. Other impacts arising from agricultural land-use reform or delivery of EU Water Framework Directive objectives under climate change could be evaluated using the same framework. (c) 2006 Elsevier B.V. All rights reserved.

A surface energy perspective on climate change

A surface forcing response framework is developed that enables an understanding of time-dependent climate change from a surface energy perspective. The framework allows the separation of fast responses that are unassociated with global-mean surface air temperature change (ΔT), which is included in the forcing, and slow feedbacks that scale with ΔT. The framework is illustrated primarily using 2 × CO2 climate model experiments and is robust across the models. For CO2 increases, the positive downward radiative component of forcing is smaller at the surface than at the tropopause, and so a rapid reduction in the upward surface latent heat (LH) flux is induced to conserve the tropospheric heat budget; this reduces the precipitation rate. Analysis of the time-dependent surface energy balance over sea and land separately reveals that land areas rapidly regain energy balance, and significant land surface warming occurs before global sea temperatures respond. The 2 × CO2 results are compared to a solar increase experiment and show that some fast responses are forcing dependent. In particular, a significant forcing from the fast hydrological response found in the CO2 experiments is much smaller in the solar experiment. The different fast response explains why previous equilibrium studies found differences in the hydrological sensitivity between these two forcings. On longer time scales, as ΔT increases, the net surface longwave and LH fluxes provide positive and negative surface feedbacks, respectively, while the net surface shortwave and sensible heat fluxes change little. It is found that in contrast to their fast responses, the longer-term response of both surface energy fluxes and the global hydrological cycle are similar for the different forcing agents.

Robust dynamics of Amazon dieback to climate change with perturbed ecosystem model parameters

Climate change science is increasingly concerned with methods for managing and integrating sources of uncertainty from emission storylines, climate model projections, and ecosystem model parameterizations. In tropical ecosystems, regional climate projections and modeled ecosystem responses vary greatly, leading to a significant source of uncertainty in global biogeochemical accounting and possible future climate feedbacks. Here, we combine an ensemble of IPCC-AR4 climate change projections for the Amazon Basin (eight general circulation models) with alternative ecosystem parameter sets for the dynamic global vegetation model, LPJmL. We evaluate LPJmL simulations of carbon stocks and fluxes against flux tower and aboveground biomass datasets for individual sites and the entire basin. Variability in LPJmL model sensitivity to future climate change is primarily related to light and water limitations through biochemical and water-balance-related parameters. Temperature-dependent parameters related to plant respiration and photosynthesis appear to be less important than vegetation dynamics (and their parameters) for determining the magnitude of ecosystem response to climate change. Variance partitioning approaches reveal that relationships between uncertainty from ecosystem dynamics and climate projections are dependent on geographic location and the targeted ecosystem process. Parameter uncertainty from the LPJmL model does not affect the trajectory of ecosystem response for a given climate change scenario and the primary source of uncertainty for Amazon 'dieback' results from the uncertainty among climate projections. Our approach for describing uncertainty is applicable for informing and prioritizing policy options related to mitigation and adaptation where long-term investments are required.

The impact of climate change on daily precipitation statistics for Jordan and Israel

A regional climate model is used to investigate changes in Israel and Jordan precipitation at the end of the 21st century on daily to monthly timescales. The model predicts that this region will get significantly drier at the peak of the rainy season, reflecting a reduction in both the frequency and duration of rainy events. These changes may be associated with a reduction in the strength of the Mediterranean storm track

Impacts of climate change scenarios on dissolved oxygen in the River Thames, UK

A water quality model is used to assess the impact of possible climate change on dissolved oxygen (DO) in the Thames. The Thames catchment is densely populated and, typically, many pressures are anthropogenic. However, that same population also relies on the river for potable water supply and as a disposal route for treated wastewater. Thus, future water quality will be highly dependent on future activity. Dynamic and stochastic modelling has been used to assess the likely impacts on DO dynamics along the river system and the probability distributions associated with future variability. The modelling predictions indicate that warmer river temperatures and drought act to reduce dissolved oxygen concentrations in lowland river systems

African climate change: Taking the shorter route

Numerous factors are associated with poverty and underdevelopment in Africa, including climate variability. Rainfall, and climate more generally, are implicated directly in the United Nations “Millennium Development Goals” to eradicate extreme poverty and hunger, and reduce child mortality and incidence of diseases such as malaria by the target date of 2015. But, Africa is not currently on target to meet these goals. We pose a number of questions from a climate science perspective aimed at understanding this background: Is there a common origin to factors that currently constrain climate science? Why is it that in a continent where human activity is so closely linked to interannual rainfall variability has climate science received little of the benefit that saw commercialization driving meteorology in the developed world? What might be suggested as an effective way for the continent to approach future climate variability and change? We make the case that a route to addressing the challenges of climate change in Africa rests with the improved management of climate variability. We start by discussing the constraints on climate science and how they might be overcome. We explain why the optimal management of activities directly influenced by interannual climate variability (which include the development of scientific capacity) has the potential to serve as a forerunner to engagement in the wider issue of climate change. We show this both from the perspective of the climate system and the institutions that engage with climate issues. We end with a thought experiment that tests the benefits of linking climate variability and climate change in the setting of smallholder farmers in Limpopo Province, South Africa.