Assessing the Effects of Land Cover Land Use Change on Precipitation Dynamics in Guangdong–Hong Kong–Macao Greater Bay Area from 2001 to 2019

Abstract

The change of spatial and temporal distribution of precipitation has an important impact on urban water security. The effect of land cover land use change (LCLUC) on the spatial and temporal distribution of precipitation needs to be further studied. In this study, transfer matrix, standard deviation ellipse and spatial autocorrelation analysis techniques were used. Based on the data of land cover land use and precipitation, this paper analyzed the land cover land use change and its influence on the spatial and temporal distribution pattern of precipitation in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). The results showed that from 2001 to 2019, the area of cropland, water, barren, forest/grassland in the GBA decreased by 44.03%, 8.05%, 50.22%, 0.43%, respectively, and the area of construction land increased by 20.05%. The precipitation in the GBA was mainly concentrated in spring and summer, and the precipitation in spring tended to increase gradually, while the precipitation in summer tended to decrease gradually, while the precipitation in autumn and winter has no obvious change. It was found that with the change of land cover land use, the spatial distribution of precipitation also changed. Especially in the areas where the change of construction land was concentrated, the spatial distribution of precipitation changed most obviously.

Impacts of Climate Change and Land Use/Cover Change on Regional Hydrological Processes: Case of the Guangdong-Hong Kong-Macao Greater Bay Area

“…Unprecedented urban expansion has occurred in the GBA during the past decades, which may surely increase the area of impervious surface in this region. Land use/cover types in the GBA have mainly changed from cropland, herbaceous, tree or shrub cover, bare areas, water bodies to urban areas, and such results are consistent with those in the previous studies (Yang et al, 2020;Wang et al, 2021).…”

“…The center of the GBA is the alluvial plain of the Pearl River Delta, surrounded by hills in the west, north, and east (Li and Wen, 2018;Lyu et al, 2018;Yang et al, 2020). The GBA is a highly integrated urbanized region with the economy aggregate almost equal to that of the New York Bay Area (Wang et al, 2021); however, the development levels among cities are still uneven. Among the 11 cities, HK, SZ, and GZ are far ahead of other cities in terms of annual gross domestic product (GDP).…”

“…For the above reasons, this study takes the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), which is one of the most developed regions in China, as the study area to investigate the impacts of climate change and LUCC on regional hydrological processes. The GBA has been undergoing rapid urbanization in the past decades , and there have been more frequent extreme events recently (Wang et al, 2021), leading to an increasing flood risk in the GBA (Zhang et al, 2019a). Therefore, to identify and understand the evolution of climate change and LUCC in the GBA and their impacts on regional hydrological processes is vital to better promote the sustainable development of the GBA (Liu F et al, 2020).…”

Intensity Characteristics and Multi-Scenario Projection of Land Use and Land Cover Change in Hengyang, China

“…China has experienced unprecedented economic growth and urbanization since the launch of economic reforms in the late 1970s, which also brings a drastic change in the spatiotemporal pattern of LULC [ 42 ]. In several study cases, many scientists have investigated the LULC of urban agglomerations and developed areas in China [ 43 ], such as Beijing–Tianjin–Hebei [ 44 ], the Yangtze River Delta [ 45 ], Guangdong–Hong Kong–Macao Greater Bay Area [ 46 , 47 ] and national central cities [ 48 ]. However, socioeconomic development of urban areas in different regions, different cultures, and different levels often experiences various LULC change processes.…”

Spatial–temporal characteristics and driving factors of flash floods in Shaanxi Province considering regional differentiation

“…Shi et al (2018) used the SDE and MK þ Sen to analyze the spatiotemporal characteristics of PM2.5 (particulate matter with a diameter of 2.5 μm) from 1999 to 2014. Wang et al (2021) used the transfer matrix in combination with the SDE and spatial autocorrelation analysis to analyze the influence of land use and land cover on the spatiotemporal pattern of precipitation.…”