Keywords
natural resource management policy, quantitative spatial data analysis, integrated modelling, decision support
Start Date
1-7-2006 12:00 AM
Abstract
There has been a recent trend in natural resource management decision making toward target setting and the use of models to identify geographic priorities to meet those targets. However, measurable and quantitative targets for assessing progress toward achieving management and policy goals tend not to be established. This may be due in large part to a lack of clarity in data and model availability, and geographic prioritisation processes. The long history of extensive human activity and modification of natural resources in the Murray Darling Basin of southern Australia has led to a myriad of natural resource management problems, particularly dryland salinity and biodiversity decline. The Lower Murray Landscapes Futures (LMLF) project was conceived in recognition of the need to urgently reverse the declining state of the region through better informed natural resource management planning, policy and decision making. The LMLF project is a multi-organisation and multi-catchment effort to apply integrated natural resource management within the lower Murray Darling Basin. A central component is the integration of social, economic and biophysical research methods and models and a synthesis and expansion of targets. The aim of this paper is to highlight lessons learned from efforts to integrate targets, models and decision support tools for natural resource management policy and planning. Challenges have arisen during the project, particularly during data preparation, model design, and in the production of outputs suitable for communicating to a wide and varied audience.
Challenges Encountered During Integrated Modelling Across Multiple Catchments
There has been a recent trend in natural resource management decision making toward target setting and the use of models to identify geographic priorities to meet those targets. However, measurable and quantitative targets for assessing progress toward achieving management and policy goals tend not to be established. This may be due in large part to a lack of clarity in data and model availability, and geographic prioritisation processes. The long history of extensive human activity and modification of natural resources in the Murray Darling Basin of southern Australia has led to a myriad of natural resource management problems, particularly dryland salinity and biodiversity decline. The Lower Murray Landscapes Futures (LMLF) project was conceived in recognition of the need to urgently reverse the declining state of the region through better informed natural resource management planning, policy and decision making. The LMLF project is a multi-organisation and multi-catchment effort to apply integrated natural resource management within the lower Murray Darling Basin. A central component is the integration of social, economic and biophysical research methods and models and a synthesis and expansion of targets. The aim of this paper is to highlight lessons learned from efforts to integrate targets, models and decision support tools for natural resource management policy and planning. Challenges have arisen during the project, particularly during data preparation, model design, and in the production of outputs suitable for communicating to a wide and varied audience.
