|Australia is an
arid environment. Water availability controls almost all aspects of
environmental behaviour. Environmental activity concentrates spatially
in the “oases” of available water. These oases range from a
few metres on a hillslope (due to soil variability) up to entire river
reaches. Water availability and environmental response also varies with
time. In dry periods many environmental process senesce, reactivating
only when water is available. The temporal variability arises
from two sources. The first source is natural variability over decadal
to millenial timescales driven by the interactions between ocean,
atmosphere and terrestrial interactions and solar forcings. The second
source is that more recently climate change threatens not only to dry
many areas of Australia on average but also change the time and space
availability of water. Available data suggest that both the
absolute magnitude of the change and the rate of change of
environmental indicators are greater than anything experienced in the
last 640,000 years. It is unclear how fast, in what form, or even
whether, the environment can adjust to this rapid change. Assessing the
potential effect of climate change on water availability is a Grand
Challenge that our grouping is addressing. To address these issues
requires a coordinated approach over a range of research disciplines,
and using a variety of techniques. Only a large coordinated group can
deliver this range of skills. Our research program has 3 foci.
The first focus is a data driven program to assess what the historical record says about recent climate extremes (e.g. drought, recent hot years, etc ) and their driving processes. One of C2IM areas of expertise is in reconstrucion from paleodata of late holocene climate. An example project is the high resolution (weekly to monthly) reconstruction of rainfall (and El Nino cycles) for the last 1000 years using speleothems. A question that these data can answer is whether the recent drought, which is the worst for the instrumental (last 100 years) record, is unusual in the reconstructed 1000 year record and is it indicative of a changing climate? If so can we use these data to assess the rate of change? There are other palaeodata time series in which we are also internationally recognised and which provide insight into other aspects of climate. These include (1) coastal landforms to infer ocean wave height and direction, and wind direction and speed, (2) Antarctic ice core geochemical and isotope data to infer extratropical temperature and climate regimes, (3) geochemistry of corals to infer sea-surface temperature and salinity, and (4) sediments in rivers, lakes and floodplains to infer extreme runoff. Together these techniques provide a powerful suite of tools for understanding the range over which the Australian climate has historically fluctuated, the causal mechanisms and the response of the Australian environment to these fluctuations. They are also a physical analog of the potential impact of climate change.
However, the palaeodata are limited. Even with recent advances we cannot resolve individual rainfall events, which is required to fully understand hydrology (i.e. runoff). Disaggregation (an empirical technique sometimes called scaling analysis) must then be used on the palaeodata to provide the required resolution. Moreover the rates and magnitude of predicted climate change are larger than have occurred in the historical record (~640,000 years), requiring extrapolation beyond the observed range in the record. In both cases we need to better understand the physics (i.e. feedbacks and interactions) of the environmental processes.
The second focus is thus a process synthesis program to better understand how environmental processes operate. While this program has elements of traditional hydrology and climatology, novel thrusts are in the exciting new areas of nonlinear dynamical systems and remote sensing. In recent years the complexity of hydrology models and climate surface-atmospheric transfer schemes has increased in a (largely unsuccessful) attempt to better understand climate feedbacks. An alternative approach is to understand equilibria and optimal behaviour in the nonlinear environmental system so that we can use universal behaviour (e.g. spatial patterns) to simplify these models while still capturing physical response. C2IM is an international pioneer in using this approach for geomorphology and hydrology (e.g. SIBERIA model) and current research focuses on spatial patterns of soils and vegetation. While environmental remote sensing has existed for more than 20 years it’s only in the last 10 with new, water focussed, satellites (NASA: TRMM, AMSR; ESA ERS, future SMOS) that it has impacted on hydrology; e.g. daily spatially distributed soil moisture and rainfall. C2IM is an Australian leader in the use of these data for hydrology and climate modelling. Moreover, the spatial patterns created by our nonlinear models, which are indicative of process, are also testable using remote sensing data.
The first two foci provide us with a greater scientific understanding of climate variability and environmental response, and the potentiial impact of climate change . They provide the solid scientific foundation upon which we can make decisions and policy to manage climate change impact. However, there is a need for management tools that specifically reflect the novel technical challenges of managing climate change impacts, and the insights developed in the first two foci.
The third focus of C2IM is thus on the development of management tools. Many members of C2IM are currently involved in such activities for the eWater CRC. We are pursuing a number of new initiatives that are not part of the CRC agenda. The CRC is heavily focussed on management of water infrastructure primarily, though not exclusively, for urban water supply. The data being used by these models is primarily the instrumental record, which is only 100 years long at best, and in many cases much shorter, and which is relatively geographically sparse. Incorporation of the palaeodata and infilling of the sparse data network will require sophisticated new statistical techniques (e.g. BATEA pioneered by C2IM members) which will allow more reliable assessment of infrastructure management decisions reflecting the long lifespans (typically >100 years) of dams. Other management tool activities by C2IM members include (1) seasonal climate forecast model based on ENSO, SOI, and solar characteristics, (2) risk assessment of failure of nuclear/hazardous waste containment structures from runoff and erosion, and (3) data assimilation of soil moisture measurements (both satellite and field data) in short range regional and global weather forecast models.