Ecological Indicators (Dec 2023)
Impact of greenspaces and water bodies on hydrological processes in an urbanizing area: A case study of the Liuxi River Basin in the Pearl River Delta, China
Abstract
The rapid shifts in landuse and the frequency of flooding events brought by urbanization significantly impact the urban basins, which means that optimizing landscape patterns is crucial for improving urban hydrology. Therefore, the Liuxi River Basin (LRB), an important river in the Pearl River Delta region, was utilized as an example in the study to examine how the landscape configuration of greenspaces and water bodies influences the hydrological components. However, there are few studies on landscape hydrology in the Pearl River Delta (PRD) and the spatial linkages between landscape metrics and hydrological components are not clear. Based on this, this paper aims to explore the mathematical and spatial associations between landscape configuration and hydrological variables in the PRD region. The SWAT model was constructed to simulate hydrological components based on landuse changes from 1980 to 2018, and regressions were established for landscape pattern indices, water morphology parameters, and hydrological components using stepwise multiple linear regression and geographically weighted regression (GWR). According to the results, the LRB continued to develop, although the greenspaces spread out and changed shape considerably. The influence of water bodies on the hydrological component is mainly in evapotranspiration, and some three-dimensional parameters such as relief ratio favor surface runoff. In the case of greenspace, the runoff is less in connected and wide farmland areas. Irregular forest land will promote water yield but suppress evapotranspiration, and the effect of forest’s shape on hydrological components is more obvious in upstream areas because the regression coefficients in this range are higher, such as 90.27. Methodologically, we found that for water yield, the accuracy of GWR was significantly higher (R2 = 0.814) than that of multiple linear regression (R2 = 0.243). In addition, understanding land use changes before conducting landscape hydrology studies can help make the results more interpretable. We supplemented the relevant research gaps in the PRD region and revealed the spatial correlation between landscape metrics and the hydrological cycle. These findings can aid urban planners in improving their comprehension of hydrological processes and landscape design, leading to more sustainable management of the urban basins.
