Challenges in modelling the sediment retention ecosystem service to inform an ecosystem account – Examples from the Mitchell catchment in northern Australia

Abstract

A systems analysis perspective related to soil science is necessary to achieve many of the sustainability targets articulated by the United Nations Sustainable Development Goals (SDGs). The System of Environmental-Economic Accounting - Ecosystem Accounting (SEEA-EA) framework is the international statistical standard for quantifying both the contributions that ecosystems make to the economy, and the impacts of economic activity on ecosystems. However, due to the difficulty of obtaining empirical data on ecosystem service flows, in many cases such quantification is informed by ecosystem service models. Previous research on the Mitchell catchment, Queensland Australia provided a novel opportunity to quantify the implications of using a model of hillslope erosion and sediment delivery in isolation (as represented in one of the most frequently used ecosystem service models - InVEST), by comparing such estimates against multiple lines of local empirical data, and a more comprehensive representation of locally important erosion and deposition processes through a sediment budget model. Estimates of the magnitude of hillslope erosion modelled using an approach similar to InVEST and the calibrated sediment budget differed by an order of magnitude. If an uncalibrated InVEST-type model was used to inform the relative distribution of erosion magnitude, findings suggest the incorrect erosion process would be identified as the dominant contributor to suspended sediment loads. However, the sediment budget model could only be calibrated using data on sediment sources and sinks that had been collected through sustained research effort in the catchment. A comparable level of research investment may not be available to inform ecosystem service assessments elsewhere. Findings for the Mitchell catchment demonstrate that practitioners should exercise caution when using model-derived estimates of the sediment retention ecosystem service, which have not been calibrated and validated against locally collected empirical data, to inform an ecosystem account and progress towards achieving the SDGs.