In this study, housing prices data for residential quarters from the period 2001-2012 were used and Global Differentiation Index （GDI） was established to measure the overall differentiation trend in housing prices i...In this study, housing prices data for residential quarters from the period 2001-2012 were used and Global Differentiation Index （GDI） was established to measure the overall differentiation trend in housing prices in Yangzhou City, eastern China. Then the influence of the natural landscape and environment on prices of global housing market and housing submarkets was evaluated by the hedonic price model. The results are shown as follows. （1） There have been increasing gaps among housing prices since 2001. In this period, the differentiation trend has shown an upward fluctuation, which has been coupled with the annual growth rate of housing prices. （2） The spatial distribution of residential quarters of homogenous prices has changed from clustered in 2001 into dispersed in 2012. （3） Natural landscape and environmental externalities clearly influence spatial differentiation of housing prices. （4） In different housing submarkets, the influence of natural landscape and environmental eternalities are varied. Natural landscape characteristics have significant impact on housing prices of ordinary commercial houses and indemnificatory houses, while the impact of environmental characteristics have obvious influence on housing prices of cottages and villas.展开更多
Numerous topography, land-cover, land-use, and soil-type parameterization methods are required to simulate the hydrologic cycle. In this paper, using the principles of hydrologic cycle simulation, 20 methods commonly ...Numerous topography, land-cover, land-use, and soil-type parameterization methods are required to simulate the hydrologic cycle. In this paper, using the principles of hydrologic cycle simulation, 20 methods commonly applied to runoff-yield simulation are analyzed. Additionally, parameterization methods used in 17 runoff-yield simulation methods and 15 confluence methods are discussed, including the degree of parameterization. Next, the parameterization methods are classified into four categories: not clearly expressed; calibrated; deterministic; and physical–conceptual. Furthermore, we clarify responses and contributions of different parameterization methods to hydrologic cycle simulation results. Finally, major weaknesses of simplified descriptions of complex rational and physical mechanisms in the parameterization methods of the underlying surfaces in hydrologic models are outlined, and two directions of future development are estimated, looking toward simple practicality and complex mechanization.展开更多
基金National Natural Science Foundation of China, No.41401164, No.41201128
文摘In this study, housing prices data for residential quarters from the period 2001-2012 were used and Global Differentiation Index （GDI） was established to measure the overall differentiation trend in housing prices in Yangzhou City, eastern China. Then the influence of the natural landscape and environment on prices of global housing market and housing submarkets was evaluated by the hedonic price model. The results are shown as follows. （1） There have been increasing gaps among housing prices since 2001. In this period, the differentiation trend has shown an upward fluctuation, which has been coupled with the annual growth rate of housing prices. （2） The spatial distribution of residential quarters of homogenous prices has changed from clustered in 2001 into dispersed in 2012. （3） Natural landscape and environmental externalities clearly influence spatial differentiation of housing prices. （4） In different housing submarkets, the influence of natural landscape and environmental eternalities are varied. Natural landscape characteristics have significant impact on housing prices of ordinary commercial houses and indemnificatory houses, while the impact of environmental characteristics have obvious influence on housing prices of cottages and villas.
基金National Natural Science Foundation of China,No.41771044,No.41501046Water Conservancy Science and Technology Innovation Project of Guangdong Provincial Water Resources Department,No.2014-14,No.2016-14+2 种基金Natural Science Foundation of Guangdong Province,No.2015A030310234GDAS’ Project of Science and Technology Development,No.2019GDASYL-0104003,No.2018GDASCX-0101,No.2017 GDASCX-0806Science and Technology Project of Guangdong Province,No.2018B030324002
文摘Numerous topography, land-cover, land-use, and soil-type parameterization methods are required to simulate the hydrologic cycle. In this paper, using the principles of hydrologic cycle simulation, 20 methods commonly applied to runoff-yield simulation are analyzed. Additionally, parameterization methods used in 17 runoff-yield simulation methods and 15 confluence methods are discussed, including the degree of parameterization. Next, the parameterization methods are classified into four categories: not clearly expressed; calibrated; deterministic; and physical–conceptual. Furthermore, we clarify responses and contributions of different parameterization methods to hydrologic cycle simulation results. Finally, major weaknesses of simplified descriptions of complex rational and physical mechanisms in the parameterization methods of the underlying surfaces in hydrologic models are outlined, and two directions of future development are estimated, looking toward simple practicality and complex mechanization.
