Microwave Remote Sensing of Soil Moisture

2020 ◽  
pp. 121-144
Author(s):  
Costas A. Varotsos ◽  
Vladimir F. Krapivin
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Microwave Remote Sensing

scholarly journals Estimating annual water storage variations in medium-scale (2000–10 000 km<sup>2</sup>) basins using microwave-based soil moisture retrievals

2017 ◽  
Vol 21 (3) ◽  
pp. 1849-1862 ◽  
Author(s):  
Wade T. Crow ◽  
Eunjin Han ◽  
Dongryeol Ryu ◽  
Christopher R. Hain ◽  
Martha C. Anderson
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Water Budget ◽  
Surface Soil ◽  
Water Storage ◽  
Microwave Remote Sensing ◽  
The United States ◽  
Surface Soil Moisture ◽  
Medium Scale ◽  
Annual Water

Abstract. Due to their shallow vertical support, remotely sensed surface soil moisture retrievals are commonly regarded as being of limited value for water budget applications requiring the characterization of temporal variations in total terrestrial water storage (dS ∕ dt). However, advances in our ability to estimate evapotranspiration remotely now allow for the direct evaluation of approaches for quantifying dS ∕ dt via water budget closure considerations. By applying an annual water budget analysis within a series of medium-scale (2000–10 000 km2) basins within the United States, we demonstrate that, despite their clear theoretical limitations, surface soil moisture retrievals derived from passive microwave remote sensing contain statistically significant information concerning dS ∕ dt. This suggests the possibility of using (relatively) higher-resolution microwave remote sensing products to enhance the spatial resolution of dS ∕ dt estimates acquired from gravity remote sensing.

scholarly journals Field Observations During the Fifth Microwave Water and Energy Balance Experiment (MicroWEX-5): from March 9 through May 26, 2006

EDIS ◽  
2007 ◽  
Vol 2007 (17) ◽  
Author(s):  
Joaquin Casanova ◽  
Fei Yan ◽  
Mi-young Jang ◽  
Juan Fernandez ◽  
Jasmeet Judge ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Energy Balance ◽  
Root Zone ◽  
Microwave Remote Sensing ◽  
Field Observations ◽  
Biological Engineering

Circular 1514, a 47-page illustrated report by Joaquin Casanova, Fei Yan, Mi-young Jang, Juan Fernandez, Jasmeet Judge, Clint Slatton, Kai-Jen Calvin Tien, Tzu-yun Lin, Orlando Lanni, and Larry Miller, presents the results of experiments using microwave remote sensing to determine root-zone soil moisture at UF/IFAS PSREU. Published by the UF Department of Agricultural and Biological Engineering, May 2007. CIR1514/AE407: Field Observations During the Fifth Microwave Water and Energy Balance Experiment: from March 9 through May 26, 2006 (ufl.edu)

scholarly journals Towards an integrated soil moisture drought monitor for East Africa

2012 ◽  
Vol 9 (4) ◽  
pp. 4587-4631 ◽  
Author(s):  
W. B. Anderson ◽  
B. F. Zaitchik ◽  
C. R. Hain ◽  
M. C. Anderson ◽  
M. T. Yilmaz ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
East Africa ◽  
Remote Monitoring ◽  
Vegetation Cover ◽  
Land Surface ◽  
Microwave Remote Sensing ◽  
Surface Model ◽  
Monitoring Methods ◽  
Data Scarcity

Abstract. Drought in East Africa is a recurring phenomenon with significant humanitarian impacts. Given the steep climatic gradients, topographic contrasts, general data scarcity, and, in places, political instability that characterize the region, there is a need for spatially distributed, remotely derived monitoring systems to inform national and international drought response. At the same time, the very diversity and data scarcity that necessitate remote monitoring also make it difficult to evaluate the reliability of these systems. Here we apply a suite of remote monitoring techniques to characterize the temporal and spatial evolution of the 2010–2011 Horn of Africa drought. Diverse satellite observations allow for evaluation of meteorological, agricultural, and hydrological aspects of drought, each of which is of interest to different stakeholders. Focusing on soil moisture, we apply triple collocation analysis (TCA) to three independent methods for estimating soil moisture anomalies to characterize relative error between products and to provide a basis for objective data merging. The three soil moisture methods evaluated include microwave remote sensing using the Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E) sensor, thermal remote sensing using the Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance algorithm, and physically-based land surface modeling using the Noah land surface model. It was found that the three soil moisture monitoring methods yield similar drought anomaly estimates in areas characterized by extremely low or by moderate vegetation cover, particularly during the below-average 2011 long rainy season. Systematic discrepancies were found, however, in regions of moderately low vegetation cover and high vegetation cover, especially during the failed 2010 short rains. The merged, TCA-weighted soil moisture composite product takes advantage of the relative strengths of each method, as judged by the consistency of anomaly estimates across independent methods. This approach holds potential as a remote soil moisture-based drought monitoring system that is robust across the diverse climatic and ecological zones of East Africa.

Characterising recent drought events using current reanalysis and remote-sensing soil moisture products within a common framework

2021 ◽  
Author(s):  
Martin Hirschi ◽  
Bas Crezee ◽  
Sonia I. Seneviratne
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Land Surface ◽  
Root Zone ◽  
Microwave Remote Sensing ◽  
Agricultural Drought ◽  
Climate Data ◽  
Data Store ◽  
Common Framework ◽  
Long Term Trends

&lt;p&gt;Drought events cause multiple impacts on the environment, the society and the economy. Here, we analyse recent major drought events with different metrics using a common framework. The analysis is based on current reanalysis (ERA5, ERA5-Land, MERRA-2) and merged remote-sensing products (ESA-CCI soil moisture, gridded satellite soil moisture from the Copernicus Climate Data Store), focusing on soil moisture (or agricultural) drought. The events are characterised by their severity, magnitude, duration and spatial extent, which are calculated from standardised daily anomalies of surface and root-zone soil moisture. We investigate the ability of the different products to represent the droughts and set the different events in context to each other. The considered products also offer opportunities for drought monitoring since they are available in near-real time.&lt;/p&gt;&lt;p&gt;All investigated products are able to represent the investigated drought events. Overall, ERA5 and ERA5-Land often show the strongest, and the remote-sensing products often weaker responses based on surface soil moisture. The weaker severities of the events in the remote-sensing products are both related to shorter event durations as well as less pronounced average negative standardised soil moisture anomalies, while the magnitudes (i.e., the minimum of the standardised anomalies over time) are comparable to the reanalysis products. Differing global distributions of long-term trends may explain some differences in the drought responses of the products. Also, the lower penetration depth of microwave remote sensing compared to the top layer of the involved land surface models could explain the partly weaker negative standardized soil moisture anomalies in the remote-sensing products during the investigated events. In the root zone (based on the reanalysis products), the drought events often show prolonged durations, but weaker magnitudes and smaller spatial extents.&lt;/p&gt;

scholarly journals Earth Observations-Based Evapotranspiration in Northeastern Thailand

2019 ◽  
Vol 11 (2) ◽  
pp. 138 ◽  
Author(s):  
Chaolei Zheng ◽  
Li Jia ◽  
Guangcheng Hu ◽  
Jing Lu
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Microwave Remote Sensing ◽  
Spatiotemporal Pattern ◽  
Monsoon Climate ◽  
Thermal Remote Sensing ◽  
Clear Sky

Thailand is characterized by typical tropical monsoon climate, and is suffering serious water related problems, including seasonal drought and flooding. These issues are highly related to the hydrological processes, e.g., precipitation and evapotranspiration (ET), which are helpful to understand and cope with these problems. It is critical to study the spatiotemporal pattern of ET in Thailand to support the local water resource management. In the current study, daily ET was estimated over Thailand by ETMonitor, a process-based model, with mainly satellite earth observation datasets as input. One major advantage of the ETMonitor algorithm is that it introduces the impact of soil moisture on ET by assimilating the surface soil moisture from microwave remote sensing, and it reduces the dependence on land surface temperature, as the thermal remote sensing is highly sensitive to cloud, which limits the ability to achieve spatial and temporal continuity of daily ET. The ETMonitor algorithm was further improved in current study to take advantage of thermal remote sensing. In the improved scheme, the evaporation fraction was first obtained by land surface temperature—vegetation index triangle method, which was used to estimate ET in the clear days. The soil moisture stress index (SMSI) was defined to express the constrain of soil moisture on ET, and clear sky SMSI was retrieved according to the estimated clear sky ET. Clear sky SMSI was then interpolated to cloudy days to obtain the SMSI for all sky conditions. Finally, time-series ET at daily resolution was achieved using the interpolated spatio-temporal continuous SMSI. Good agreements were found between the estimated daily ET and flux tower observations with root mean square error ranging between 1.08 and 1.58 mm d−1, which showed better accuracy than the ET product from MODerate resolution Imaging Spectroradiometer (MODIS), especially for the forest sites. Chi and Mun river basins, located in Northeast Thailand, were selected to analyze the spatial pattern of ET. The results indicate that the ET had large fluctuation in seasonal variation, which is predominantly impacted by the monsoon climate.

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