InVEST Model-Based Spatiotemporal Analysis of Water Supply Services in the Zhangcheng District

Abstract

The Zhangcheng District is critically responsible for protecting water resources, preserving sand sources, and improving the ecological environment in Beijing. Quantitative evaluation and research on the ecosystem water supply services in this area are beneficial for developing conservation planning and establishing ecological compensation mechanisms in water conservation areas. In this paper, based on the land use, meteorological, soil, and field observation data of the research area, the InVEST water yield model is used to estimate the water supply of the ecosystem in the Zhangcheng District. The model quantitatively analyzes the spatiotemporal distribution characteristics of water supply services in the basin and the influence of different topographic factors. The results show that the average supply of ecosystem water in the Zhangcheng District is approximately 45 mm, and there is a degree of spatial heterogeneity. The total water supply in the Zhangcheng District is relatively small. The water resource supply in the southwest is relatively small, the rainfall in mountainous forest areas in the southeast is high, its water supply is higher, and the supply of forest land water is relatively high. The high-value areas are mainly distributed at 1500 to 3500 m and 15°~40°; the water supply on the sunny slope is greater than that on the shady slope. With the increase in altitude and slope, the water supply in the basin tends to increase first and then decrease.

Coupling PLUS–InVEST Model for Ecosystem Service Research in Yunnan Province, China

“…Therefore, the PLUS model is chosen to accurately simulate the spatial distribution by predicting land changes with future factor constraints. With the current in-depth research on ESs, numerous models can quantify them, such as InVEST [15], ARIES [16], ESM [17], and EcoMetrix [18], among which the InVEST model is more mature and can be used for largescale quantitative studies, the model has lower data requirements, lower computational workload, and higher accuracy of conclusions, and is widely used [19][20][21], while studies in the Chinese region have also shown strong applicability to evaluate and analyze a variety of indicators in time space and detect dynamic distribution changes [22][23][24][25].…”

Spatial and Temporal Distribution Characteristics of Water Yield in Guangdong Province and Spatial Management Strategies

“…Water yield refers to the runoff volume reaching the catchment area after precipitation flows over the ground. Its variation reflects the water retention capacity of vegetation or soil [3][4][5]. A high water yield per unit area indicates a lower retention capacity of vegetation or soil, whereas a lower water yield suggests a higher retention capacity.…”

Spatiotemporal Variation and Driving Factors of Water Supply Services in the Three Gorges Reservoir Area of China Based on Supply-Demand Balance

“…For example, Benra et al [22] used the InVEST seasonal water yield model to assess the water monitoring performance of 224 catchments in southern Chile, helping inform water supply policy decisions. Liu et al [23] utilized the InVEST annual water yield model to estimate the water supply of the Beijing Zhangcheng district ecosystem and quantitatively analyzed the characteristics of the spatiotemporal distribution of WSSs in the watershed and the influence of different topographic factors, which is conducive to formulating water conservation region protection and establishing ecological compensation mechanisms. Bejagam et al [24] used the InVEST annual water yield model to analyze the impacts of climate change on water supply and water-associated services such as hydropower generation in the densely populated Tungabhadra Basin.…”