The natural support capacity (NSC) of water resources is a key aspect of the regional carrying capacity of water resources, and it can reflect the quality and quantity of water resources in a region. This paper aims to evaluate the NSC of water resources using a model based on the principal component analysis (PCA) to benefit the development and utilization of regional water resources. A case study in the Fuyang district, Zhejiang Province, China, was carried out. First, water resources, as dependent variables, were assumed to be linearly influenced by the indicators affecting the NSC of water resources. These indicators were regarded as independent variables for multivariate analysis in this study. Then, the available water resources data for the Fuyang district between 1995 and 2003 were inputted to the model to analyze NSC levels of water resources. The results indicated that the most important parameters influencing the NSC of water resources could be shortlisted to water resources availability, surface water resources, groundwater resources, allowable withdrawal of water resources, and emission intensity of chemical oxygen demanding. Our findings revealed that the NSC of water resources in the Fuyang district fluctuated between 1995 and 1999 and generally declined after 2000, indicating that the issue of water pollution has worsened since 2000. These results are consistent with the field observations and thus shall provide new potential applications of a PCA-based model in evaluating the NSC of water resources and the relevant water resource carrying capacity for similar areas.
There are mainly three types of gross primary production (GPP), including light use efficiency (LUE) model, rectangular hyperbolic model (RHM), and process-based model (PBM). RHM is not widely used because its parameters, namely, quantum yield (α) and maximum photosynthetic rate (P m ), vary temporally with temperature and spatially with vegetation type under natural conditions. In the study, we present a temperature-and vegetation-type-adapted RHM by linking it to the Baldocchi's model to obtain the relationship between α-P m and V cmax,25 -temperature to overcome the shortcomings of traditional RHM. The modified RHM (MRHM) coupled with a two-leaf upscaling strategy makes it possible to accurate and fast estimation of GPP at large scale. Twenty-two CO 2 eddy-covariance sites with different vegetation types, including evergreen needleleaf forest, deciduous broadleaf forest, grassland, and evergreen broadleaf forest, are used to evaluate the performance of MRHM for GPP estimation. The comparisons of the simulated GPP using MRHM with measured and Boreal Ecosystem Productivity Simulator-simulated GPP demonstrate that the MRHM can simulate GPP as accurately as PBM and in the meantime with the advantage of simplicity as LUE model. These results show the promising potential of MRHM for accurately simulating GPP with relative high computational efficiency, providing an ideal alternative tool for large-scale and long time series GPP simulations.
SUMMARYA high-order difference method based multiphase model is proposed to simulate nonlinear interactions between water wave and submerged coastal structures. The model is based on the Navier-Stokes equations using a constrained interpolation profile (CIP) method for the flow solver, and employs an immersed boundary method (IBM) for the treatment of wave-structure interactions. A more accurate interface capturing scheme, the volume of fluid/weighed line interface calculation (VOF/WLIC) scheme, is adopted as the interface capturing method. A series of computations are performed to verify the application of the model for simulations of fluid interaction with various structures. These problems include flow over a fixed cylinder, water entry of a circular cylinder and solitary waves passing various submerged coastal structures. Computations are compared with the available analytical, experimental and other numerical results and good agreement is obtained. The results of this study demonstrate the accuracy and applications of the proposed model to simulate the nonlinear flow phenomena and capture the complex free surface flow.
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