Spatial and Temporal Heterogeneity Analysis of Water Conservation in Beijing-Tianjin-Hebei Urban Agglomeration Based on the Geodetector and Spatial Elastic Coefficient Trajectory Models

Geohealth. 2020 Aug 1;4(8):e2020GH000248. doi: 10.1029/2020GH000248. eCollection 2020 Aug.

Abstract

To regulate regional water resources, it is essential to identify the relationships among the elements that influence water conservation. Taking the Beijing-Tianjin-Hebei urban agglomeration as the study area, the authors applied a new method in combination with a geodetector model and spatial elastic coefficient trajectory model to reveal factors controlling water conservation and to identify relationships among the elements driving water conservation, in which the water conservation capacity and its spatial distribution were achieved using an Integrated Valuation of Ecosystem Services and Tradeoffs model. The authors selected precipitation, potential evapotranspiration, temperature, land use, maximum burial depth of soil, plant-available water content, soil-saturated hydraulic conductivity, percentage slope, gross domestic product, and population as the spatial driving factors, which measured the influence on the distribution of water conservation capacity on the whole region, plateaus, mountains, and plains, respectively. On the basis of previous research results, the authors selected precipitation, potential evapotranspiration, and land use as time-driven factors. The results indicated that the strong water conservation capacity was reflected primarily in the Yanshan and Taihang Mountains and the eastern coastal areas. The water conservation capacity of the entire region, mountains, plateaus, and plains was affected mainly by the soil-saturated hydraulic conductivity, plant-available water content, precipitation, and precipitation, respectively. Each driving factor exhibited a clearly interactive influence on the spatial distribution of water conservation in terms of space and time.

Keywords: Beijing‐Tianjin‐Hebei urban agglomeration; InVEST model; driving factors; geodetector model; water conservation.