Hydrological data are the basic ingredients for planning, constructing, and operating of hydraulic structures. A well-designed rainfall network can accurately provide and reflect the information of rainfall in a catchment. However, in past studies, the required number and optimal location of rain gauge stations have yet to produce a satisfactory result. A more accurate design is required. Hence, in this study, a proposed model composed of kriging and entropy with probability distribution function is introduced to relocate the rainfall network and to obtain the optimal design with the minimum number of rain gauges. The ordinary kriging is used to generate rainfall data of potential locations where rain gauge stations may be installed. The information entropy based on probability is used to measure the uncertainty of rainfall distribution. The probability distribution function will be introduced to fit the statistical characteristics of data of the rain gauges. By calculating the joint entropy and the transferable information, the relocated rain gauges are prioritized and the minimum number and location of the rain gauges in the catchment can be obtained to construct the optimal rainfall network to replace the existing rainfall network.
This study applies a novel concept to decompose water stages to understand the factors that affect an estuary. The estuary water stages vary due to different complex, often nonlinear and non-stationary factors. Therefore, it is very difficult for researchers to break down water stages into contributing factors with single integrated methods. The Hilbert Huang transform (HHT) is an easy to use, efficient and powerful method of processing non-stationary, non-linear signals to optimize a complicated data process. The HHT is composed of empirical mode decomposition (EMD) and Hilbert transform. EMD decomposes the water stages into several intrinsic mode functions (IMFs). Through the Hilbert transform, IMFs could obtain amplitude and instantaneous frequency with time. Those IMFs with amplitude and frequency can be used to represent those factors that affect the water stages in an estuary. However, the physical meanings represented by IMFs should be inferred in conjunction with the other hydrological data. This study uses Tanshui River estuary water stages to show HHT applied to determining the factors that affect the water stages. HHT application provides a methodology for others to follow to identify the water stage components in an estuary.
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