A drought risk map has been developed at the national scale by using remote-sensing satellite data over Iran by combining output layers resulting from three main components of a risk-evaluation procedure including Hazard Quantification (HQ), Vulnerability Assessment (VA) and Identification of Elements at Risk (IER) in a GIS environment. In this respect, Drought Severity (DS) was calculated by using the monthly Normalized Difference Vegetation Index (NDVI) (over 31 years from 1986–2016). Iran landcover classification and a slope map, population density maps, and irrigated farm percentages at the provincial scale were utilized within the drought risk evaluation (DRE) process. The final risk map reveals that the northwest of the country, with a climate similar to the central European weather conditions, is exposed to the maximum drought risk. In contrast, the areas with an arid climate, mainly located in the middle of Iran, exhibits minimum risk against drought. Based on the risk map, the southern part of the Caspian Sea shows very low drought risk due to the moderate and subtropical climate in this region. The outputs of this research will provide advice and warnings to help decision makers reduce drought risk consequences after prioritizing risk areas at the administrative scale.

A multifractal technique has been used to downscale 1 km optical remote sensing MODIS derived soil moisture index (SMI) to the scale of interpolated soil moisture map produced by ground measurements at the Valencia Anchor Station (VAS) during the SMOS Validation Rehearsal Campaign (2008) with the spatial resolution of 32 meters. Scale invariance assessment shows a constant behavior of soil moisture variability at all scales of aggregation. This result proves the homogeneity of the VAS region from a mathematical point of view and exempts or allows us from using ancillary data such as topography, soil texture and vegetation characteristics in our downscaling model. Our predicted soil moisture values compared to the observed ground data show RMSE ranges from 0.026 to 0.039 for 2008/05/02, indicating accurate predictions for this date. However, there are high RMSE values in the range of 0.761 to 0.784 for 2008/04/24, due to rainfall events (30 mm accumulated) occurring in the region a few days prior to the measurements, which influenced the result of the downscaling model. At the same time, the strong correlation (77%) between the predicted and the observed data is promising and warrants further application of the model to other homogeneous areas with or without rainfall events.