Remedial strategy of algal proliferation in a regulated river system by integrated hydrological control: an evolutionary modelling framework

Abstract

We simulated water-quality measures in a regulated river system (the lower Nakdong River) under simultaneous discharge control at upriver dams and an estuarine barrage with the goal of reducing phytoplankton biomass (chlorophyll a concentration). We used genetic programming (GP) to create a rule-set-based predictive model for the chlorophyll a concentration based on 16 years (1994–2009) of meteorological, hydrological, and limnological data. The rule-set model used eight variables, including water temperature, dam and estuarine barrage discharge, phosphate and silica concentrations, and accurately predicted the phytoplankton biomass (determination coefficients, r2, for training and test data were 0.52 and 0.45, respectively). According to sensitivity and scenario analyses, a larger water volume resulting from increased discharge from upriver dams and decreased discharge from an estuarine barrage would reduce chlorophyll a concentrations at the study site. This result provided ample evidence that simultaneous manipulation of dam and estuarine discharge rates could effectively increase river flow and flush aggregated algal populations downstream. Additionally, we considered that even small increases in river flow could play a role in diluting phytoplankton biomass during the dry winter season when estuarine discharge remains low. These two hydrological mechanisms could be used as selective strategies for water-resource management.