A new approach to modeling the sediment retention service (InVEST 3.0): Case study of the Cape Fear catchment, North Carolina, USA

There is a growing call for ecosystem services models that are both simple and scientifically credible, in order to serve public and private sector decision-making processes. Sediment retention receives particular interest given the impact of this service on water quality. We developed a new version of the sediment retention model for the InVEST (Integrated Valuation of Environmental Services and Tradeoffs) tool to address previous limitations and facilitate model uncertainty assessment. We tested the model in the Cape Fear basin, North Carolina (NC), performing sensitivity analyses and assessing its ability to detect the spatial variability in sediment retention service for eight subcatchments. The main advantages of the revised model include the use of spatially-explicit, globally available input data, and the explicit consideration of hydrological connectivity in the landscape. The sensitivity analyses in the study catchment identified the erosivity and erodibility factors, together with the cover factor for agricultural land as the most influential parameter for sediment export. Relative predictions, representing the spatial variability in sediment exports, were correctly represented by the model. Absolute sediment exports were also highly correlated with observations, although their interpretation for socio-economic assessments is more uncertain without local knowledge of the dominant erosion processes. This work confirms that the sediment connectivity approach used in the revised InVEST model has great potential to quantify the sediment retention service. Although resources to conduct model calibration and testing are typically scarce, these practices should be encouraged to improve model interpretation and for confident application in different decision-making contexts. Without calibration, the InVEST sediment model still provides relevant information for ecosystem services assessments, especially in decision contexts that involve ranking of sediment export areas, such as spatial prioritization of conservation, development or restoration activities, taking into account non-linear sediment responses to changes in land use.