An observing system simulation experiment for soil moisture measurements from the SMAP radiometer

Thesis (S.B. in Environmental Engineering Science)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 57-61).The Soil Moisture Active Passive (SMAP) satellite, to be launched in 2013, will use both radiometer and radar data to estimate soil moisture. Improved soil moisture knowledge has many applications in hydroclimatology, numerical weather prediction, flood forecasting, and human health. In this thesis, an observing system simulation experiment (OSSE) was used to study the error structure of radiometer measurements using two different retrieval algorithms. In an OSSE, geophysical fields are used to create a model of surface emission, which is coupled to an orbital sampling module and proposed retrieval algorithms. Comparing output from the retrieval algorithm to the starting soil moisture values demonstrates retrieval error. Significant uncertainty remains about the optimal representation of the effect of dielectric mixing, soil roughness, and vegetation opacity on radiometric emissions at a given soil moisture. The effect of this uncertainty on retrieval algorithms is studied by using different representations for each term in the forward and retrieval modules of the OSSE. Uncertainty due to roughness causes less error than errors in dielectric mixing and vegetation opacity treatment. In both algorithms, the retrieval shows a spatially variable bias, which is particularly large when using a single-polarization retrieval algorithm. The spatial and temporal variation of the bias, and the implications for characterization and removal of this bias as a possible error reduction strategy, are discussed.by Alexandra Georges Konings.S.B.in Environmental Engineering Scienc

Microwave remote sensing of water in the soil - plant system

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2015.Cataloged from PDF version of thesis.Includes bibliographical references (pages 171-191).Remotely sensed measurements made by radars or radiometers in the low microwave frequency range are sensitive to soil moisture, soil roughness, and vegetation water content. Measurements made at multiple polarizations can be used to determine additional ancillary parameters alongside the primary variable of interest. However, if an attempt is made to retrieve too many parameters from too few measurements, the resulting retrievals will contain high levels of noise. In this thesis, I introduce a framework to determine an upper bound on the number of geophysical parameters that can be retrieved from remotely sensed measurements such as those made by microwave instruments. The principles behind this framework, as well as the framework itself, are then applied to derive two new ecohydrological variables: a) soil moisture profiles across much of the root-zone and b) vegetation optical depth, which is proportional to vegetation water content. For P-band observations, it is shown that soil moisture variations with depth must be accounted for to prevent large forward modeling - and thus retrieval - errors. A Tikhonov regularization approach is then introduced to allow retrieval of soil moisture in several profile layers by using statistics on the expected co-variation between soil moisture at different depths. The algorithm is tested using observations from the NASA Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) Mission over the Harvard Forest in Western Massachusetts. Additionally, at L-band, a multi-temporal algorithm is introduced to determine vegetation optical depth (VOD) alongside soil moisture. The multi-temporal approach used reduces the chance of compensating errors between the two retrieved parameters (soil moisture and vegetation optical depth), caused by small amounts of measurement noise. In several dry tropical ecosystems, the resulting VOD dataset is shown to have opposite temporal behavior to coincident cross-polarized backscattering coefficients, an active microwave indicator of vegetation water content and scattering. This possibly shows dry season bud-break or enduring litter presence in these regions. Lastly, cross-polarized backscattering coefficients are used to test the hypothesis that vegetation water refilling slows down under drought even at the ecosystem scale. Evidence for this hypothesis is only found in the driest location tested.by Alexandra Georges Konings.Ph. D