Evaluating irrigation status in the Mekong Delta through polarimetric L-band SAR data assimilation

For sustainable food production in the Mekong Delta, local information on irrigation status is essential for allocating water resources efficiently at the community level. ALOS-2 PALSAR-2 L-band SAR can be used to detect submerged and nonsubmerged soil covered by rice plants at a spatial resolution compatible with field observation but a low temporal resolution. In this study, a new multiscale data assimilation technique is developed to estimate the spatiotemporal dynamics of field water levels at a temporal resolution appropriate to inform decision-making on when to initiate irrigation. The method employs an irrigation model based on parameters representing farmers' irrigation practices. ALOS-2 PALSAR-2 data are used to derive the hydrological parameters of the model, including an irrigation parameter representing how deep the field water level dropped until the next round of irrigation was initiated. We developed observation operators for the soil submersion status under vegetation and spatial submersion percentages instead of assimilating soil moisture products. The study uses ALOS-2 PALSAR-2 data (25-100 m spatial resolution, approximately every 42 days) over the Mekong Delta and experimental data collected in situ for model initialization and validation. The estimated irrigation parameter controlling the maximum depth of field water level showed spatiotemporal consistency with the ground-observed value (RMSE = 4.24 cm). The values of the parameters also showed spatial consistency with respect to DEM data; he paddies with low irrigation model parameter values were prone to be located in low -elevation zones (< 2 m), whereas high model parameters values tended to be located in paddies in the high -elevation zones (> 3 m).The results show promising applications using L-band SAR observations for monitoring paddy field water level, for irrigation practices and for estimation of the water consumption and of methane emissions.

Automated summary

In this study, a new multiscale data assimilation technique is developed using ALOS-2 PALSAR-2 L-band SAR data to estimate the spatiotemporal dynamics of field water levels. The results show promising applications for monitoring paddy field water levels and informing irrigation practices.