Rain gauge network design applied to millimeter radiocommunications performance analysis

Author(s):  
R. Marino ◽  
F.P. Fontan ◽  
F. Machado ◽  
C. Enjamio ◽  
S. Otero
2016 ◽  
Vol 11 (1) ◽  
pp. 166-175 ◽  
Author(s):  
Changfeng Jing ◽  
Jianjun Yu ◽  
Peipei Dai ◽  
Haiyang Wei ◽  
Mingyi Du

An algorithm of rule-based rain gauge network design in urban areas was proposed in this study. We summarized three general criteria to select the sites of rain gauges, including: (i) installment in open space; (ii) priority consideration of important regions and even distribution; and (iii) keep strong signal and avoid weak interference. Aided by spatial kernel density, the candidate locations were determined through clustering the residential buildings at first. Secondly, the overlay and buffer spatial analyses were carried out to optimize the candidate sites to avoid signal interference. Finally, the quality of site location was evaluated by cross-validation in using observed historical rainfall and ranked by mean square error for final consideration. A study case in Xicheng district, Beijing, China was selected to demonstrate the proposed method. The result showed that it could be well applied in urban areas with the capability of considering complex urban features through defining rules. It thus could provide scientific evidence for decision making in rain gauge site selection.


Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1357
Author(s):  
Yanyan Huang ◽  
Hongli Zhao ◽  
Yunzhong Jiang ◽  
Xin Lu ◽  
Zheng Hao ◽  
...  

A reasonable rain gauge network layout can provide accurate regional rainfall data and effectively support the monitoring, development and utilization of water resources. Currently, an increasing number of network design methods based on entropy targets are being applied to network design. The discretization of data is a common method of obtaining the probability in calculations of information entropy. To study the application of different discretization methods and different entropy-based methods in the design of rain gauge networks, this paper compares and analyzes 9 design results for rainy season rain gauge networks using three commonly used discretization methods (A1, SC and ST) and three entropy-based network design algorithms (MIMR, HT and HC) from three perspectives: the joint entropy, spatiality, and accuracy of the network, as evaluation indices. The results show that the variation in network information calculated by the A1 and ST methods for rainy season rain gauge data is too large or too small compared to that calculated by the SC method, and also that the MIMR method performs better in terms of spatiality and accuracy than the HC and HT methods. The comparative analysis results provide a reference for the selection of discrete methods and entropy-based objectives in rain gauge network design, and provides a way to explore a more suitable rain gauge network layout scheme.


2019 ◽  
Vol 178 ◽  
pp. 108686 ◽  
Author(s):  
Wenqi Wang ◽  
Dong Wang ◽  
Vijay P. Singh ◽  
Yuankun Wang ◽  
Jichun Wu ◽  
...  

2020 ◽  
Author(s):  
Claudia Bertini ◽  
Elena Ridolfi ◽  
Leonardo Alfonso ◽  
Francesco Napolitano

2017 ◽  
Vol 18 (2) ◽  
pp. 363-379 ◽  
Author(s):  
Qiang Dai ◽  
Michaela Bray ◽  
Lu Zhuo ◽  
Tanvir Islam ◽  
Dawei Han

Abstract A remarkable decline in the number of rain gauges is being faced in many areas of the world, as a compromise to the expensive cost of operating and maintaining rain gauges. The question of how to effectively deploy new or remove current rain gauges in order to create optimal rainfall information is becoming more and more important. On the other hand, larger-scaled, remotely sensed rainfall measurements, although poorer quality compared with traditional rain gauge rainfall measurements, provide an insight into the local storm characteristics, which are sought by traditional methods for designing a rain gauge network. Based on these facts, this study proposes a new methodology for rain gauge network design using remotely sensed rainfall datasets that aims to explore how many gauges are essential and where they should be placed. Principal component analysis (PCA) is used to analyze the redundancy of the radar grid network and to determine the number of rain gauges while the potential locations are determined by cluster analysis (CA) selection. The proposed methodology has been performed on 373 different storm events measured by a weather radar grid network and compared against an existing dense rain gauge network in southwestern England. Because of the simple structure, the proposed scheme could be easily implemented in other study areas. This study provides a new insight into rain gauge network design that is also a preliminary attempt to use remotely sensed data to solve the traditional rain gauge problems.


10.29007/1kc9 ◽  
2018 ◽  
Author(s):  
Wenqi Wang ◽  
Dong Wang ◽  
Vijay P. Singh ◽  
Yuankun Wang

Ground-based rain-gauge stations are the most direct sources of precipitation data. The evaluation of rain-gauge network is essential and important for water management. One of the most popular methods for design of hydrometric network including rain- gauge network is information theory. Entropy concepts from information theory has been widely adopted and applied in rain-gauge network design. In this paper, spatial- temporal evaluation of rain-gauge network located in Shanghai, China will be performed based on entropy theory. The transinformation-distance (T-D) spatial model is applied under three different sampling frequencies. Weekly precipitation data fits the T-D model best. In addition, the representative network is evaluated to be suitable according to the result.


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