Location: Southeast Watershed ResearchTitle: Vegetation-soil moisture coupling metrics from dual-polarization microwave radiometry using regularization
|ZWIEBACK, SIMON - University Of Guelph
|Bosch, David - Dave
|BERG, AARON - University Of Guelph
Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/7/2019
Publication Date: 7/1/2019
Citation: Zwieback, S., Bosch, D.D., Cosh, M.H., Starks, P.J., Berg, A. 2019. Vegetation-soil moisture coupling metrics from dual-polarization microwave radiometry using regularization. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2019.111257.
Interpretive Summary: The moisture of the soil across the globe has critical implications with regard to climate, water balance, and crop production. Great strides have been made estimating soil moisture utilizing satellite based passive microwave observations. Here, improved methods were developed utilizing field data collected across Georgia, Iowa, California, and Oklahoma. These new methods help to stabilize and increase the accuracy of soil moisture estimation methods from passive microwave observations. The developed methodology will provide improved opportunities to study ecohydrological interactions such as plant water uptake and hydraulics. It can provide unprecedented insight into plant-water uptake, transpiration, and phenology on a global scale.
Technical Abstract: Soil and vegetation water content are closely coupled via complex physiological and ecohydrological processes. Joint passive microwave retrievals of soil moisture (theta) and vegetation optical depth (tau) potentially provide unparalleled insight into these couplings on a global scale. However, this requires careful data analyses. Using a novel coupling distortion metric R^2s, we show that snapshot dual-polarization retrievals of tau and theta, similar to those that have been widely used to study tau, are spuriously correlated for SMAP L-band observations. Naive estimates of tau–theta coupling are thus grossly distorted across a range of time scales. To mitigate the spurious correlations, we introduce a regularization framework that exploits the assumed slowly changing nature of tau. The degree of regularization r must balance a trade-off, as over-regularization due to the over-smoothing of tau also distorts coupling estimates. When r is chosen to balance the trade-off according to R^2s, estimates of tau–theta correlation change most (by approx. 0.5) over high-biomass at time scales of up to two weeks, but sizable differences are also found on longer time scales. Our analyses show that estimating vegetation–soilmoisture coupling benefits from dedicated retrievals and data analysis approaches. Provided the uncertainties are carefully accounted for, satellite radiometry offers exciting opportunities to study ecohydrological interactions such as plant water uptake and hydraulics.