Recent socioeconomic development with associated rapid population growth, urbanization, and industrialization have significantly affected natural landscapes across the world, with various environmental impacts. Land use changes have direct impacts on water resources and ecosystems, both in terms of quantity and quality and the services provided. Such impacts are particularly evident in developing water-scarce areas, where any land use or infrastructure change can significantly stress water quality and ecosystem services (ES). Understanding the complex interactions between land use changes, infrastructure development, water quality, and ES is essential for strategic environmental planning.
We modelled the impacts of intensified urbanization on water quality and ES, in the context of developing regions facing water scarcity conditions. For that purpose, a large, arid, developing area was selected as the case study: the Yongding River Basin (YRB) in North China. The land use changes were modeled and projected through a Cellular Automata Markov model until 2035. The impacts were assessed by i) a comprehensive water quality model considering the discharge of major pollutants in the river network; ii) their spatiotemporal distribution at fine-resolution grid scale; and iii) the economic spatial valuation of the ES. We also account for the real-world environmental policies of the region by considering future infrastructure development, namely the actual planned expansion and efficiency improvement of wastewater treatment (WWT) plants by 2035.
The major pollutants were COD, NH4+, and Total Phosphorus, resulting primarily from urban sources. The efficiency of domestic WWT was found to be a dominant factor in the spatial distribution of future water pollution, but this cannot be the only solution. ES values decrease in the short-term but can increase in the long-term (2035) with the planned WWT expansion.
Our findings have multiple implications for integrated land--water--economic management toward more sustainable development, with targeted interventions to mitigate the environmental impacts.
