In the Lower Mekong River Basin floodplains, rice cultivation is highly crucial for regional and global food security. However, prolonged flooding can pose damage to rice cultivation and other socio-economic aspects. Yet, there is no rapid operational inundation forecasting system that can help decision-makers proactively mitigate flood damages. Here, we integrated the so-called Forecasting Inundation Extents using Rotated empirical orthogonal function analysis (FIER) framework with an altimetry-based operational Mekong River level forecasting system and built an operational web application, FIER-Mekong, (https://fier-mekong.streamlit.app/) that generates daily skillful forecasted inundation extents (>70% of critical success index) and depths in about 3 and 30 s, respectively, with up to 18-day lead times. One of its applications, predicting flood-induced rice economic losses, is also presented. Had FIER-Mekong being adopted, we estimated that the rice damages, up to 87 and 53 million US dollars during the 2020 and 2021 harvest time, respectively, could have been avoided.
|Journal||Environmental Modelling and Software|
|Publication status||Published - 2023 Apr|
Bibliographical noteFunding Information:
This study was supported by NASA's Applied Sciences Program for SERVIR ( 80NSSC20K0152 , 80NSSC23K0184 ), University of Houston's GEAR Program, and Vietnam National Foundation for Science and Technology Development ( NE/S002847/1 ). This study was also partially supported by the Korea Ministry of Environment under the Demand Responsive Water Supply Service Program ( 2019002650004 ) and the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. 2021R1A2C100578011 ). We also acknowledge the publicly available FwDET-GEE tool developed by Peter et al. (2020) .
© 2023 Elsevier Ltd
All Science Journal Classification (ASJC) codes
- Environmental Engineering
- Ecological Modelling