Abstract
During the last decade, a variety of agricultural drought indices have been developed using soil moisture (SM), or any of its surrogates, as the primary drought indicator. In this study, a comprehensive study of four innovative SM-based indices, the Soil Water Deficit Index (SWDI), the Soil Moisture Agricultural Drought Index (SMADI), the Soil Moisture Deficit Index (SMDI) and the Soil Wetness Deficit Index (SWetDI), is conducted over a large semi-arid crop region in northwest Spain. The indices were computed on a weekly basis from June 2010 to December 2016 using 1-km satellite SM estimations from Soil Moisture and Ocean Salinity (SMOS) and/or Moderate Resolution Imaging Spectroradiometer (MODIS) data. The temporal dynamics of the indices were compared to two well-known agricultural drought indices, the atmospheric water deficit (AWD) and the crop moisture index (CMI), to analyze the levels of similarity, correlation, seasonality and number of weeks with drought. In addition, the spatial distribution and intensities of the indices were assessed under dry and wet SM conditions at the beginning of the growing season. The results showed that the SWDI and SMADI were the appropriate indices for developing an efficient drought monitoring system, with higher significant correlation coefficients (R ≈ 0.5–0.8) when comparing with the AWD and CMI, whereas lower values (R ≤ 0.3) were obtained for the SMDI and SWetDI.
Highlights
Drought is a complex natural hazard that can affect all climates and produce devastating environmental, economic and social impacts, such as damage to wildlife habitat, diminishment of crop growth or mass migration
The results showed that the Soil Water Deficit Index (SWDI) and Soil Moisture Agricultural Drought Index (SMADI) were the appropriate indices for developing an efficient drought monitoring system, with higher significant correlation coefficients (R ≈ 0.5–0.8) when comparing with the Atmospheric Water Deficit (AWD) and crop moisture index (CMI), whereas lower values (R ≤ 0.3) were obtained for the Soil Moisture Deficit Index (SMDI) and Soil Wetness Deficit Index (SWetDI)
The SWetDI had a very low dynamic range, usually from −1 to +1 and did not reach its minimum or maximum limits (−4 to +4) in any week of the study period (Figures 5i,j and 6i,j). This variability of the SWetDI was similar to that obtained in a previous study, where the SWetDI was calculated over Iran, a region with an annual precipitation of 130 mm per year, and a variability ranging from −1.7 to +1.2 in a rainfed farmland location was displayed [50]
Summary
Drought is a complex natural hazard that can affect all climates and produce devastating environmental, economic and social impacts, such as damage to wildlife habitat, diminishment of crop growth or mass migration. The Soil Moisture Deficit Index (SMDI) was developed from SM anomalies In this case, the SM was obtained from the Soil Water Assessment Tool (SWAT) hydrological model [27]. All of the previous agricultural drought indices were estimated from hydrological modeling instead of direct root-zone SM measurements In this regard, the Water Deficit Index (WDI) was introduced as an appropriate way to express SM in terms relative to available water content [30]. The SMOS SM data have been employed to derive the Soil Moisture Agricultural Drought Index (SMADI) together with the land surface temperature (LST) and the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor [47,48]. This research could help enlighten the choice of the more appropriate drought index for developing an accurate agricultural drought monitoring system
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