The physiographic approach is an integrated or ‘systems view’, predicated upon the spatial coupling between landscape attributes and the key processes governing water quality outcomes in surface and shallow groundwater. For example, the relationship between soil drainage class (attribute) and redox (process) can be used to predict soil denitrification potential. Unlike other mapping and classification approaches, the physiographic approach incorporates water quality, hydrochemical and/or hydrological response signals into a spatial format to identify, select, combine, and classify those landscape gradients that drive variation in water quality outcomes.
Areas characterised by similar process-attribute classes for both hydrology and redox are defined as Physiographic Attribute Gradients (PAG). Each PAG responds in a similar fashion at the process level to broadly equivalent land use pressures. Classification of the catchment into PAGs can be used to demonstrate that: (i) physiographic mapping enables estimation of the steady-state water composition of surface water and shallow unconfined groundwater with a high degree of confidence, and; (ii) process-attribute gradients and resultant PAGs are a powerful tool for informing and optimising efforts to improve water quality. These outcomes enable efforts to be matched to the process level controls over water quality at the land parcel scale.
Physiographic science results in an increased understanding of the landscape processes, which then allows for the implementation of management practices within the local and catchment-scale. Examples of ‘on the ground’ management practices that can be implemented and which are informed by physiographic science include: land use management practices (e.g., changes to nutrient and stock rates and inputs); implementation of physical mitigation measures (e.g., riparian planting of waterways; peak runoff structures to reduce sediment during high flow / rainfall events); optimisation of the timing of fertiliser and Farm Dairy Effluent irrigation, and provision of spatial context to existing farm extension programmes.
For more information on this project contact Clint (email@example.com)