Contrasting seasonal pattern between ground-based PM2.5 and MODIS satellite-based aerosol optical depth (AOD) at an urban site in Hanoi, Vietnam

This study investigated the seasonal variations of the ground-based PM_2.5 concentration measured at an urban site and Terra MODIS satellite-based aerosol optical depth (AOD) in Hanoi, Vietnam, during the year 2016. The findings showed the large differences in terms of the seasonal variation of both PM_2.5 concentration and columnar AOD. Clearly, the ground-based PM_2.5 concentrations decreased during the summer period and highly increased during the late fall and winter periods. The Terra MODIS AOD values also decreased in summer, however, significantly increased in spring. Interestingly, the increasing trend of AOD which in contrast to the decreasing trend of PM_2.5 concentration was found during the spring period, and vice versa for the winter period. The seasonal analysis of meteorological factors including relative humidity (RH), precipitation, and boundary layer height (BLH) as well as regional fire activities expressed that the increased columnar AOD in spring was largely influenced by the hygroscopic growth of aerosol induced by the increased RH, the larger BLH causing the more effective transport and mixing of atmospheric particles to higher altitudes, and especially the intensive fire activities in the Southeast Asian region during the spring period, whereas the significantly increased surface PM_2.5 concentration in winter was partly attributed to the impact from the highly industrialized and polluted source region in the Pearl River Delta of China. Different from the spring and winter periods, the abundant precipitation amount and the dominance of maritime air masses arrived in Hanoi in summer were the main reasons for the low AOD and surface PM_2.5 concentration during this period.

Hydrological model using ground- and satellite-based data for river flow simulation towards supporting water resource management in the Red River Basin, Vietnam

The Red River basin (RRB) exhibits substantial variation of water resource seasonally and annually. Sustainable water resource management in the RRB has been challenging due to the lack of in situ hydrological measurement data over the basin-wide scale. To address this issue, this study aimed to perform the setting up, calibration, and validation of the variable infiltration capacity (VIC) hydrological model forced with ground- and satellite-based datasets at a high spatial resolution of 0.1° for simulating the daily river flow of the Red River system in the RRB during the period of 2005-2014. By using the finely resolved land cover characterization with 15 types of land cover and leaf area index - the most important feature of vegetation that significantly influences the simulation of hydrological variables provided by the spatially distributed satellite remote sensing data, this study would not only address the poor data availability over the RRB but also enhance the accuracy of model simulation. The simulation results generally indicated that the calibrated VIC model could satisfactorily capture the river flow dynamics of the Red River system in the RRB. The VIC model's underestimated river flow compared to the observed data during the dry season for the downstream stations was likely due to the operation of the large man-made reservoirs and dams in the upstream catchments of the RRB that not represented by the VIC model. The findings also suggested that for further improving the VIC model performance, the use of more spatially representative meteorological data provided by satellite remote sensing should be considered in future studies.