Agricultural droughts are extreme events which are often a result of interplays between multiple hydro-meteorological processes. Therefore, assessing drought occurrence, extent, duration and intensity is complex and requires the combined use of multiple variables, such as temperature, rainfall, soil moisture (SM) and vegetation state. The benefit of using information on SM and vegetation state is that they integrate information on precipitation, temperature and evapotranspiration, making them direct indicators of plant available water and vegetation productivity. Microwave remote sensing enables the retrieval of both SM and vegetation information, and satellite-based SM and vegetation products are available operationally and free of charge on a regional or global scale and daily basis. As a result, microwave remote sensing products play an increasingly important role in drought monitoring applications. Here, we provide an overview of recent developments in using microwave remote sensing for large-scale agricultural drought monitoring. We focus on the intricacy of monitoring the complex process of drought development using multiple variables. First, we give a brief introduction on fundamental concepts of microwave remote sensing together with an overview of recent research, development and applications of drought indicators derived from microwave-based satellite SM and vegetation observations. This is followed by a more detailed overview of the current research gaps and challenges in combining microwave-based SM and vegetation measurements with hydro-meteorological data sets. The potential of using microwave remote sensing for drought monitoring is demonstrated through a case study over Senegal using multiple satellite- and model-based data sets on rainfall, SM, vegetation and combinations thereof. The case study demonstrates the added-value of microwave-based SM and vegetation observations for drought monitoring applications. Finally, we provide an outlook on potential developments and opportunities.

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In this study, we examined the ASCAT backscatter data from Metop-A from 2007 to 2016 to characterize spatial and temporal variability in the vegetation parameters of the TU Wien Soil Moisture Retrieval approach (TUW SMR) across the North American Grasslands. The vegetation parameters are the slope and curvature of a second order Taylor polynomial used to describe the incidence angle dependence of backscatter σ°. A recent development allows the vegetation parameters to be determined dynamically using the local slope values within a prescribed temporal window. Seasonal, interannual and diurnal variations in the vegetation parameters were found to vary across grassland cover types, reflecting variations in soil moisture availability and growing season length. While the slope has always been considered a measure of vegetation density, our results show that curvature also contains information about vegetation. Drought events in 2011 and 2012 resulted in extensive negative σ 40 ∘ and soil moisture anomalies during the maximum biomass period. Contiguous anomalies in slope and curvature were observed where the severity and persistence of the drought were enough to impact vegetation. Observed diurnal differences in slope and curvature suggest that daily moisture transport within the vegetation influences the relative dominance of scattering from the vegetation and soil surface. @en

In this study, we investigate the vegetation parameters of the TU Wien Soil Moisture Retrieval (TUW SMR) approach as a potential source of information about vegetation. A recent development in the TUW SMR approach allows for the dynamic estimation of the slope and curvature of the 2nd order Taylor polynomial used to represent the incidence angle dependence of backscatter. This allows us to characterize the seasonal cycle of these parameters and their inter-annual variability. With some modifications, this approach can also be used to estimate these parameters separately for the descending ( 9:30 AM) and ascending ( 9:30 PM) overpasses, allowing us to examine diurnal variations in the slope and curvature. The goal of this study is to explore the potential value of the dynamic vegetation parameters to monitor vegetation phenology and canopy water dynamics. Results will be presented from an analysis of the first ten years of ASCAT observations from Metop-A over the grasslands of North America. Grasslands are of particular interest due to their hydrological and ecological value, but also because the vegetation parameters are highly dynamic in this cover type. Spatial patterns in the seasonal cycle, inter-annual variations and diurnal differences of the vegetation parameters, normalized backscatter and soil moisture were found to vary across the different grassland ecosystems. Spatially contiguous anomalies in the vegetation parameters were observed in areas where the duration and intensity of drought was severe enough to impact vegetation. Diurnal differences in the slope and curvature suggest changes in the relative dominance of different scattering mechanism as a result of the daily water dynamics within the vegetation. In short, the vegetation parameters provide promising new insights into canopy water dynamics at daily, seasonal and inter-annual scales. @en