Soil Moisture Anomaly Standardized Index (SMASI): A multi-sensor drought index from soil moisture anomalies

Droughts have severe global impacts on the environment and economy. They affect crop yield and biodiversity, disrupt water transport, and cause shortages of drinking water. To mitigate these impacts, national weather and environmental agencies operate drought monitoring tools, which are primarily based on weather station data. However, these stations are not homogeneously distributed. Alternatively, satellite remote sensing allows for monitoring droughts contiguously over large areas. Precipitation, vegetation condition, evapotranspiration, and soil moisture estimates from space-borne sensors enable drought monitoring at a large scale. Among them, the soil moisture-based drought index is relevant for plant water availability as it helps to detect the moisture deficit even before the vegetation responds to droughts. Individual satellite sensors have a limited lifespan, and the data from each sensor is usually available for shorter periods of time. Such data are not sufficient to monitor drought conditions, which are long-term phenomena. However, the data can be merged into a long-term record to monitor the drought conditions. In this study, we developed a drought index, the soil moisture anomaly standardized index (SMASI), by merging the standardized soil moisture anomaly from various microwave satellite sensors. SMASI uses soil moisture from sensors that are used to develop the European Space Agency-Climate Change Initiative (ESA-CCI) soil moisture product. The SMASI dataset enables monitoring drought at a global scale with its record spanning more than 35 years. SMASI shows a good agreement with other well-known drought indices such as the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI).