Catchment sensitivity and resilience to contaminants
It has been widely recognized that changes in climate will have far-reaching implications for environmental sustainability. It is also likely that concurrent alterations such as changes in landuse and population will put further pressure on sustainable use of environmental resources. The impacts of interactions between these association changes however have not been extensively considered. Our lab investigates the important question of how changes in climate and landuse interact to have consequences on water quality, aquatic biodiversity, water availability – and explores possible management avenues.
Due to uncertainty in future conditions, it has been difficult for resource managers to have confidence that decisions taken now will remain effective in the long term. By investigating responses of resources to a wide range of plausible changes in driving variables, the Crossman Lab is developing a framework where decisions can be based on assessments of an areas’ resilience to change, rather than relying solely on a perception of that the change is likely to be.
To effectively manage our future resources, the importance of first understanding the relationships between the key variables driving environmental responses is clear. This is known as catchment sensitivity analysis. In Collaboration with researchers from Oxford University and the Swedish University of Agriculture, we have determined that catchment sensitivity is primarily determined by landuse, geology and climate drivers. Changes in these drivers impact freshwater ecosystems health, and availability of ecosystem services. Most importantly, our lab has determined that environmental responses to driving variables are not static, but change over time – meaning it is important to consider the effects of long-term integrated changes.
Using a combination of real-time sensors and a suite of process-based models (INtegrated CAtchment models (INCA) and PERSiST) the Crossman lab is working to further our understanding of spatial and temporal variability in interactions between driving variables and environmental responses (Sensitivity). The goal is to facilitate identification of areas at greatest risk from future land use and climate change, and to assist with the development of adaptive and resilient management strategies. This bottom-up climate and landuse impacts approach supports the development of economically robust management solutions.