Citizen Science for Monitoring Rainfall in Vietnam

EasyChair Preprint 15457

Abstract

Citizen Science (CS) has been arising as a promising approach to address hydro-meteorological data gaps spatially and temporally and providing information about catchment characteristics for water resource management for the last ten years. In Vietnam, many national efforts aimed to renovate and extend the operating water monitoring networks. However, the lack of reliable hydro-meteorological data remains an issue that may be better handled by using a CS approach. This study examines the CS approach to monitor rainfall in the Bui River Basin in Vietnam using low-cost rain gauges constructed from soda bottles, concrete, and rulers. The rainfall data of 19 citizen scientists from January 2022 to August 2023 were used for the analysis. The CS data were compared with data from one official reference station. The correlation coefficient (R) was applied to evaluate the significance of the agreement between the monthly CS data at the station with the longest measurement period and reference data. Results yield a significant correlation between CS and reference station with an R = 0,90. The results show that citizen science has the potential of being a complementary approach for existing Vietnamese monitoring systems, particularly for data-scarce areas.

Keyphrases: Vietnam, citizen science, data collection applications, low-cost rain gauge, rainfall monitoring

@booklet{EasyChair:15457,
  author    = {Huan N Tran and Sudeep Duwal and Rajaram Prajapati and Jeffrey C Davids and Dung T Nguyen and Konrad Miegel},
  title     = {Citizen Science for Monitoring Rainfall in Vietnam},
  howpublished = {EasyChair Preprint 15457},
  year      = {EasyChair, 2024}}