Estimating regional scale hydroclimatic risk conditions from the soil moisture active-passive (SMAP) satellite
Citation
Champagne, C., Zhang, Y., Cherneski, P., Hadwen, T. (2018). Estimating regional scale hydroclimatic risk conditions from the soil moisture active-passive (SMAP) satellite. Geosciences (Switzerland), [online] 8(4), http://dx.doi.org/10.3390/geosciences8040127
Plain language summary
The Soil Moisture Active-Passive (SMAP) mission is a satellite launched by NASA in 2015 to measure soil moisture globally. It measures soil moisture accurately, but only in the surface layer which is less useful for detecting the severity of drought events. This paper evaluated how to use satellite soil moisture from SMAP to identify drought and excess moisture events. An index using SMAP integrated with a longer term data set from another satellite, the Soil Moisture and Ocean Salinity (SMOS) mission was evaluated against historical climate related risk events, and showed a good agreement with these at the provincial level. At a higher spatial resolution, this index showed a good agreement with crop water stress but not long term drought. This Soil Moisture Difference from Average (SMDA) index was however more sensitive to long term drought when it was averaged out over the whole growing season, which shows that satellites measuring soil moisture at the surface can be applied for longer term drought. Overall, the index showed to be a good indicator of soil moisture imbalances that create risk to crop production.
Abstract
Satellite soil moisture is a critical variable for identifying susceptibility to hydroclimatic risks such as drought, dryness, and excess moisture. Satellite soil moisture data from the Soil Moisture Active/Passive (SMAP) mission was used to evaluate the sensitivity to hydroclimatic risk events in Canada. The SMAP soil moisture data sets in general capture relative moisture trends with the best estimates from the passive-only derived soil moisture and little difference between the data at different spatial resolutions. In general, SMAP data sets overestimated the magnitude of moisture at the wet extremes of wetting events. A soil moisture difference from average (SMDA) was calculated from SMAP and historical Soil Moisture and Ocean Salinity (SMOS) data showed a relatively good delineation of hydroclimatic risk events, although caution must be taken due to the large variability in the data within risk categories. Satellite soil moisture data sets are more sensitive to short term water shortages than longer term water deficits. This was not improved by adding “memory” to satellite soil moisture indices to improve the sensitivity of the data to drought, and there is a large variability in satellite soil moisture values with the same drought severity rating.