A modelling approach for estimating suspended sediment concentrations for multiple rivers influenced by agriculture

A data-driven model based on an adaptive neuro-fuzzy inference system (ANFIS) was tested for the estimation of suspended sediment concentrations within watersheds influenced by agriculture. ANFIS models were developed using different combinations of inputs such as precipitation, streamflow, surface runoff and the watershed vulnerability index. A multi-watershed ANFIS model was also developed combining the datasets from all studied watersheds. The best results were obtained from a combination of precipitation, streamflow and watershed vulnerability index as input variables. Nash-Sutcliffe coefficients were improved for the multi-watershed ANFIS compared to watershed-specific ANFIS models. The introduction of the erosion vulnerability index significantly improved the ability of the ANFIS model to estimate suspended sediment concentrations within the watersheds. Furthermore, the inclusion of this index opens the possibility of using the ANFIS model to investigate the impact of land-use changes on sediment delivery.     

Institutional dimensions of the developing REDD+ process in Cameroon

The reducing emissions from deforestation and forest degradation (REDD+) initiative has emerged in recent years as a mechanism to simultaneously address climate change, biodiversity, and poverty reduction challenges at the margins of tropical forests. Congo Basin countries, including Cameroon, have embraced the opportunities that REDD+ provides, with great expectations. Yet, it needs to be investigated whether the enabling institutional environment, which is required for implementing REDD+, is present. Understanding is still limited on how to build adequate and strong institutional relations that could shape the reforms towards the establishment of efficient emissions reductions schemes. Furthermore, uncertainty remains on the operational mechanisms of REDD+, suggesting that, to catalyse effectiveness, there is a need to come up with a governance model nested in relevant policy frameworks. This study builds on a modified ‘4Is’ framework – Institutions, Interests, Ideas and Information – to analyse REDD+ and explore stakeholders' perceptions on the local forest governance potential. A structural implementation model to optimize the effectiveness of REDD+ is developed. Findings suggest that governments need to review existing policies to take into account participation, local people rights, and information access as a way to stimulate actors' willingness to contribute to emissions reductions and carbon stock increases under REDD+ regimes.