A validation study of citizen science-based rainfall observation

Author:

Wang XingORCID,Zhao Jiuwei,He Yufeng

Abstract

Abstract Citizen science-based data collection approaches offer new opportunities to produce high-quality rainfall products. One of the most promising options, personal rain gauges (PRGs), allows for high spatial and temporal resolution rainfall observation and has received much attention in recent years. Doubts about the accuracy and stability of PRGs, however, have led many researchers to remain hesitant about using PRG-based rainfall datasets. It is, therefore, of great importance to investigate the effectiveness of the PRG rainfall observation network. In this paper, 294 daily (24 hr) rainfall data between June 2022 and June 2023 was collected in the Netherlands using the PRG network and compared with ground rain gauge and radar estimations. The experimental results indicate that: (1) during the large-scale rainfall events, PRG achieved a Pearson correlation performance of 0.498, 0.488, and 0.324 compared to the corrected/uncorrected rain gauge network and radar observations, respectively, which decreased to 0.11, 0.101, and 0.108 for small-scale rainfall. It can be concluded that the PRG network shows a certain degree of agreement with ground rainfall gauges and radar measurements and is more suitable for large-scale rainfall observation tasks; (2) the relative errors between the PRGs and compared rainfall products indicate that the accuracy of the PRG network still needs to be improved. This study could offer a useful complement to the existing rainfall observation system while providing a helpful supplement to the development of citizen science.

Funder

The Joint Open Project of KLME,NUIST

the National Natural Science Foundation of China

National Natural Science Foundation of China

the Talent Startup project of NJIT

Publisher

IOP Publishing

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