Optimization of industry structure based on water environmental carrying capacity under uncertainty of the Huai River Basin within Shandong Province, China

Abstract

Optimization of the industry structure is important for the sustainable development for developing countries, e.g. China. The inexact stochastic multiple objective programming (ISMOP) which integrates stochastic programming, interval linear programming, and multiple objective programming was applied to analyze the optimization of industrial structure based on water environmental carrying capacity in Huai River Basin within Shandong Province (HRBSP). ISMOP can effectively solve the uncertainty existing in the multiple-objective optimization model and provide the information of development patterns of different industrial sectors. Results showed that the growth rates of output values from secondary industries under different qi values in the planning stage (2010–2020) will be almost 8%, and the total amounts of COD and NH3–N discharge will reduce by at least 65% from 2010 to 2020 in HRBSP. In term of the secondary industrial structure, the coal, paper-making and food processing industries, as the traditional backbone industries but with high risk of water pollution, should be reduced gradually; the beverage and textile industries should be strictly limited; and conversely, the new industries, such as metallurgy and construction material industries, should be allowed to maintain the rapid development. In the context of the aquatic environment protection in the basin level, the results based on ISMOP are useful for making policies to balance the economic development and water pollutant prevention within the Huai River Basin and other river basins.