Abstract
Abstract. The increasing frequency of drought events has expanded the research interest in drought monitoring. In this regard, remote sensing is a useful tool to globally mapping the agricultural drought. While this type of drought is directly linked to the availability of root zone soil moisture (RZSM) for plants growth, current satellite soil moisture observations only characterize the water content of the surface soil layer (0–5 cm). In this study, two soil moisture-based agricultural drought indices were obtained at a weekly rate from June 2010 to December 2016, using RZSM estimations at 1 km from the Soil Moisture and Ocean Salinity (SMOS) satellite, instead of surface soil moisture (SSM). The RZSM was estimated by applying the Soil Water Index (SWI) model to the SMOS SSM. The Soil Moisture Agricultural Drought Index (SMADI) and the Soil Water Deficit Index (SWDI) were assessed over the Castilla y León region (Spain) at 1 km spatial resolution. They were compared with the Atmospheric Water Deficit (AWD) and the Crop Moisture Index (CMI), both computed at different weather stations distributed over the study area. The level of agreement was analyzed through statistical correlation. Results showed that the use of RZSM does not influence the characterization of drought, both for SMADI and SWDI.
Highlights
In the last years, drought has been one of the natural disasters with the worst impact in the agricultural regions worldwide (FAO, 2018)
The quicker response of Atmospheric Water Deficit (AWD) is consistent with the nature of this drought index, directly linked to processes that occur at the surfaceatmosphere layer
This delay was observed in a previous study, where Soil Moisture Agricultural Drought Index (SMADI) was estimated from the Soil Moisture and Ocean Salinity (SMOS) surface soil moisture (SSM) (Pablos et al, 2017)
Summary
Drought has been one of the natural disasters with the worst impact in the agricultural regions worldwide (FAO, 2018). Traditional drought indices, such as the Palmer Drought Severity Index, PDSI (Palmer, 1965), the Standardized Precipitation Index, SPI (McKee et al, 1993) or the Atmospheric Water Deficit, AWD (Purcell et al, 2003), utilize meteorological variables as drought indicators. The most used agricultural drought index is the Crop Moisture Index, CMI (Palmer, 1968) It is usually computed alongside the PDSI from evapotranspiration (ET0) deficit and moisture excess, using climate-based data. Several soil moisture-based agricultural drought indices are being developed, as the Soil Moisture Deficit Index, SMDI (Narasimhan and Srinivasan, 2005), the Soil Water Deficit Index, SWDI (Martínez-Fernández et al, 2015) and the Soil Moisture Agricultural Drought Index, SMADI (Sánchez et al, 2016), among others
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