Author(s): Kay Khaing Kyaw; Ticha Lalupiman; Watin Thanathanphon; Piyamarn Sisomphon
Linked Author(s):
Keywords: Satellite rainfall products; Drought related indexes; Myanmar
Abstract: Remote sensing data and information can strengthen the basis for informed flood and drought management actions. The reliability of satellite data needs to be validated and compared against ground measurements to a specific area and temporal scales before it can be used in any subsequent application. Rainfall is an important component in the water balance and hydrological modelling. As ground data may be scarce, remote sensing datasets can be used to give spatially distributed data and fill in data gaps. In this study, Climate Hazards Group InfraRed Precipitation with Station (CHIRPS), Global Precipitation Measurement (GPM) and Tropical Rainfall Measuring Mission (TRMM) rainfall data are compared with ground measurements from rainfall gauges and the remote sensing datasets are also compared with each other. Along with the floods, there are drought-stricken areas in Myanmar, which have devastating impacts on agriculture, quality of life of farmers and national economy. The drought related indicators such as Standardized Precipitation Index (SPI), Normalized Difference Vegetation Index (NDVI), Soil Water Index (SWI), NDVI deviation and SWI percentile are the most interesting indexes to attempt validation. The findings of this study indicate that satellite rainfall estimates have a consistently good agreement with ground rainfall at different spatiotemporal scales. In addition, rainfall estimates from remote sensing at a large catchment scale is more accurate than single stations. For the drought index validation, the results show that they can be used as indicators because they have good performance not only in rainy season but also in drought years.
Year: 2020