A fuzzy quality index for the environmental assessment of a restored wetland
This paper describes the feasibility study for the restoration of agricultural land with a tendency to become waterlogged into a natural wetland, conceived to mitigate floods and to remove nutrients from the water drained from the cultivated plots. The wetland model, developed in aquatox, includes the nutrient dynamics both in the water and in the sediment, and the vegetation that is expected to develop as a consequence of flooding. The model inputs were synthesized from historical time series of rainfall and chemical data collected over the last decade. The model outputs are used to compute a synthetic fuzzy quality index (FQI) to assess the removal efficiency of the wetland. This FQI is based on three main variables describing the ecosystem quality: chlorophyll-a, dissolved oxygen and total suspended solids. This index has the merit of being simple enough to be immediately grasped by non-technical people, like managers and stakeholders, to whom the restoration project is proposed. The simulations, performed under five differing loading scenarios demonstrate the feasibility of this solution, which is robust enough to accommodate a 50% increase in either nitrogen, phosphorous or organic matter.
Keywords: natural wetlands, fuzzy sets, artificial intelligence, water quality modeling, wetland modeling, simulation, AQUATOX