4.7 Article

Integrating Remotely Sensed Leaf Area Index with Biome-BGC to Quantify the Impact of Land Use/Land Cover Change on Water Retention in Beijing

期刊

REMOTE SENSING
卷 14, 期 3, 页码 -

出版社

MDPI
DOI: 10.3390/rs14030743

关键词

water retention; ecosystem service; land use; land cover change; remote sensing; Biome-BGC; leaf area index; vegetation structure

资金

  1. National Key Research and Development Program of China [2018YFC0507303]

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This study analysed the impact of land use/land cover change on water retention in Beijing between 2000 and 2015. The results showed an overall increase in water retention, with forests contributing the most to the increase. However, urbanization, cropland expansion, and deforestation led to a decline in water retention.
Maintaining or increasing water retention in ecosystems (WRE) can reduce floods and increase water resource provision. However, few studies have taken the effect of the spatial information of vegetation structure into consideration when assessing the effects of land use/land cover (LULC) change on WRE. In this study, we integrated the remotely sensed leaf area index (LAI) into the ecosystem process-based Biome-BGC model to analyse the impact of LULC change on the WRE of Beijing between 2000 and 2015. Our results show that the volume of WRE increased by approximately 8.58 million m(3) in 2015 as compared with 2000. The volume of WRE in forests increased by approximately 26.74 million m(3), while urbanization, cropland expansion and deforestation caused the volume of WRE to decline by 11.96 million m(3), 5.86 million m(3) and 3.20 million m(3), respectively. The increased WRE contributed by unchanged forests (14.46 million m(3)) was much greater than that of new-planted forests (12.28 million m(3)), but the increase in WRE capacity per unit area in new-planted forests (124.69 +/- 14.30 m(3)/ha) was almost tenfold greater than that of unchanged forests (15.60 +/- 7.85 m(3)/ha). The greater increase in WRE capacity in increased forests than that of unchanged forests was mostly due to the fact that the higher LAI in unchanged forests induced more evapotranspiration to exhaust more water. Meanwhile, the inverted U-shape relationship that existed between the forest LAI and WRE implied that continued increased LAI in forests probably caused the WRE decline. This study demonstrates that integrating remotely sensed LAI with the Biome-BGC model is feasible for capturing the impact of LULC change with the spatial information of vegetation structure on WRE and reduces uncertainty.

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