Soil Moisture Mapping Based on Temperature-Soil Moisture Dryness Index - a case study for the tailing dam in Brumadinho, Brazil

Abstract

[EN] The tailing dam in Brumadinho of Brazil collapsed on 25th January 2019, it caused serious casualties and environmental pollution. The monitoring of the tailing dam stability has become an urgent problem. For monitoring, soil moisture is an important parameter, if the soil moisture is too high, it will cause soil liquefaction and then the stability of the tailing dam will decrease. In this study, Landsat 8 data is innovatively used to calculate the Temperature-Soil Moisture Dryness Index (TMDI) for the estimation of soil moisture of the collapsed tailing dam in Brumadinho. The data on 14th January 2019 and 30th January 2019 are used in order to better understand the soil moisture before and after the collapse of tailing dam. TMDI is calculated based on triangle space of Land Surface Temperature (LST) and Normalized Difference Latent Heat Index (NDLI). This new index TMDI is used for the assessment of the soil moisture and evapotranspiration (ET). The performance of TMDI and Temperature Vegetation Dryness Index (TVDI) are evaluated by the reference evapotranspiration (ET), which is calculated based on the Surface Energy Balance Algorithm for Land (SEBAL). Results of the correlation between TMDI, TVDI and SEBAL-derived ET indicate that TMDI is a better index for estimating soil moisture. The built-up region shows high negative correlation with SEBAL-derived ET. According to the spatial distribution of TMDI and TVDI, in the tailing dam, some parts of the dam body shows high soil moisture which may have the potential risk of soil liquefaction.