Operation-based uncertainties in river waste load allocation and their impacts on controlling discharges

Abstract

ABSTRACTVariations in quality or quantity of reservoir discharges and of wastewater treatment plants (WWTP) are typical sources of uncertainty in controlling and management of river water quality downstream. This study evaluates and discusses the impacts of these operation-based uncertainties on waste load allocation (WLA) policies, like water quality trading (WQT), by Monte-Carlo simulation. For this purpose, we chose the Sefidrud River in northern Iran and developed an economic-based WLA in this area through a simulation-optimisation approach. The river with 1150 reaches is simulated by coding in MATLAB and linked to a multi-objective particle swarm optimization (MOPSO) algorithm in which the two objectives are minimisation of environmental violations and abatement costs. For uncertainty analysis through Monte-Carlo simulation, river flow and kinetic rates, dissolved oxygen (DO) at headwater, pollution loads of dischargers, and temperature are considered as primary variables. Results show that the success of WLA is mostly reliant on the DO concentration of headwater, occurrence of seasonal floods, and river aeration rate. The implications of the findings are also analysed for WQT. In particular, the above uncertainties are highlighted as possible threats for the success of discharge permit markets because polluters could be penalised or rewarded for uncertainties regardless of their pollution discharges. Consequently, effective WQT under uncertainty is likely to lead to a need for more monitoring to resolve potential disputes from uncertainties.