Multi-criterion GIS-based Assessment of Wetlands: Clarence Catchment, Australia

Abstract

The Clarence River catchment with an area of 22 700 km² is the largest coastal catchment in NSW. The catchment contains many wetlands that provide critical habitat to a great diversity of plants, invertebrates, fish, birds, and mammals. They serve as nursery grounds for many economically important fish species. But many of the wetland areas in the Clarence catchment are under threat from development. The Upper North Coast Catchment Management Board blueprint targets the identification and prioritisation of wetlands for rehabilitation as an important priority for management in the Clarence River Catchment. However, there is a lack of objective information on wetland condition or importance that could be used to inform management decisions. In this study a GIS-based wetland assessment and rehabilitation prioritization methodology was developed. 14 GIS datasets that describe: wetland location and character; protected areas; and potential threats were collated and registered to a common mapping system (UTM 56). With the aid of a wetland assessment expert these datasets were processed to create 16 wetland assessment variables. The wetland expert then provided a weighting for each variable according to the direction and magnitude of the likely influence it may have on wetland condition. For example the wetlands that fall under RAMSAR protection were weighted as highly protected, while wetlands that were heavily affected by hydrological modification were weig hted as highly vulnerable. Finally, a multi-criterion decision-making method, TOPSIS (the Technique for Order Preference by Similarity to Ideal Solution) was used to integrate the variables, ranking the wetlands according to their distance from both the worst condition and the best condition. Once the TOPSIS program was constructed a number of scenarios were run to appraise the condition of each wetland and determine the priority for rehabilitation. To assess the robustness of the method a sensitivity analysis was conducted comparing the result of different weightings, distance measures and normalization techniques. The results of this analysis show that the method is robust even though parameters like variable weightings are necessarily subjective. It is concluded that the methodology developed in this study is a fast, cost-effective, and flexible wetland assessment and prioritization approach. It provides a screening tool to help prioritize wetlands for further investigation.