Alireza Tabatabaeenejad

Shallow aquifers are the largest freshwater bodies in the North African Sahara and the Arabian Peninsula. Their groundwater dynamics and response to climatic variability and anthropogenic discharge remain largely unquantified due to the absence of large-scale monitoring methods. Currently, the assessment of groundwater dynamics in these aquifer systems is made primarily from sporadic well logs that barely cover a few percent of the geographical extent of these water bodies. To address this deficiency, we develop the use of an ultra-wideband (UWB) very high frequency (VHF) interferometric airborne sounding radar, under a collaboration between NASA and the Qatar Foundation, to characterize the depth and geometry of the shallowest water table in large hyperarid hydrological basins in North Africa and the Arabian Peninsula. Herein, we describe the science objectives, measurement requirements, instrument design, expected performance, flight implementation scenarios, primary targets for investigation, and the first technology demonstration of the concept. Our performance analyses suggest that an airborne, nadir-looking sounding radar system operating at a 70-MHz center frequency with a linearly polarized folded-dipole antenna array—enabling a bandwidth (BW) of 50 MHz—and a surface signal-to-noise ratio (SNR) of 85 dB flying at an altitude of 500–2,000 m can map the uppermost water table depths of aquifer systems spanning tens of kilometers at a vertical resolution of 3 m in desiccated terrains to an average penetration depth of 50 m, with a spatial resolution of 200 m. For the first time, this airborne concept will allow time-coherent high-resolution mapping of the uppermost water tables of major aquifer systems in hyperarid areas, providing unique insights into their dynamics and responses to increasing climatic and anthropogenic stressors, which remain largely uncharacterized. The aforementioned significantly surpasses the existing capabilities for mapping shallow aquifers in these harsh and remote environments, which relies today on data collected on different timescales from sparse well logs that do not cover their geographic extents. A list of key abbreviations for this article can be found in “The Key Abbreviations Used in This Article.”

A P-band SAR moisture estimation method is introduced for complex soil permittivity and penetration depth estimation using fully polarimetric P-band SAR signals. This method combines eigen- and model-based decomposition techniques for separation of the total backscattering signal into three scattering components (soil, dihedral, and volume). The incorporation of a soil scattering model allows for the first time the estimation of complex soil permittivity and permittivity-based penetration depth. The proposed method needs no prior assumptions on land cover characteristics and is applicable to a variety of vegetation types. The technique is demonstrated for airborne P-band SAR measurements acquired during the AirMOSS campaign (2012–2015). The estimated complex permittivity agrees well with climate and soil conditions at different monitoring sites. Based on frequency and permittivity, P-band penetration depths vary from 5 cm to 35 cm. This value range is in accordance with previous studies in the literature. Comparison of the results is challenging due to the sparsity of vertical soil in situ sampling. It was found that the disagreement between in situ measurements and SAR-based estimates originates from the discrepancy between the in situ measuring depth of the top-soil layer (0–5 cm) and the median penetration depth of the P-band waves (24.5–27 cm).

Objective: To develop a new class of emulsions using a protein-based emulsifier as the coupling fluid for microwave imaging systems. Methods: In this paper, we provide a theoretical basis for engineering shelf-stable dielectric fluids, a step-by-step formulation method, and measurements of complex dielectric properties in the frequency range of 0.5-3 GHz, which can be applicable for many of the recent microwave imaging systems. Results: This medium was primarily designed for long-term stability while providing a controllable range of complex dielectric permittivities given different fractions of its constituents. Consequently, this emulsion shows dielectric stability in open air throughout a 7-day experiment and temperature insensitivity over the range of 0 ${\,^\circ }$ C to 60 ${^\circ }$ . Conclusions: This control over dielectric permittivity enables formulations that tune the background-to-target contrast to the linearizable regime of iterative inverse scattering algorithms. Accordingly, the emulsion conductivity can also be controlled and reduced to maintain the required signal-to-noise ratio within the dynamic range of the imaging system. The new formulation overcomes the practical challenges of engineering coupling fluids for microwave imaging systems, e.g., temporal stability, non-toxic, low sensitivity to temperature variation, and easy formulation from readily available and inexpensive materials. Significance: The achieved properties associated with this new fluid are of particular benefit to microwave imaging systems used in thermal therapy monitoring.

Organic matter (OM) content and a shallow water table are two key variables that govern the physical properties of the subsurface within the active layer of arctic soils underlain by permafrost, where the majority of biogeochemical activities take place. A detailed understanding of the soil moisture and OM profile behavior over short vertical distances through the active layer is needed to adequately model the subsurface physical processes. To observe and characterize the profiles of soil properties in the active layer, we conducted detailed soil sampling at five sites along Dalton Highway on Alaska’s North Slope. These data were used to derive a generalized logistics function to characterize the total OM and water saturation fraction behavior through the profile. Furthermore, a new pedotransfer function was developed to estimate the soil bulk density and porosity—information that is largely missing from existing soil datasets—within each layer, solely from the soil texture (organic and mineral properties). Given the currently sparse soil database of the Alaskan Arctic, these profile models can be highly beneficial for radar remote sensing models to study active layer dynamics.

Active layer thickness (ALT) is a critical metric for monitoring permafrost. How soil moisture influences ALT depends on two competing hypotheses: (a) increased soil moisture increases the latent heat of fusion for thaw, resulting in shallower active layers, and (b) increased soil moisture increases soil thermal conductivity, resulting in deeper active layers. To investigate their relative influence on thaw depth, we analyzed the Field Measurements of Soil Moisture and Active Layer Thickness (SMALT) in Alaska and Canada dataset, consisting of thousands of measurements of thaw depth and soil moisture collected at dozens of sites across Alaska and Canada as part of NASA’s Arctic Boreal Vulnerability Experiment (ABoVE). As bulk volumetric water content (VWC) integrated over the entire active layer increases, ALT decreases, supporting the latent heat hypothesis. However, as VWC in the top 12 cm of soil increases, ALT increases, supporting the thermal conductivity hypothesis. Regional temperature variations determine the baseline thaw depth while precipitation may influence the sensitivity of ALT to changes in VWC. Soil latent heat dominates over thermal conductivity in determining ALT, and the effect of bulk VWC on ALT appears consistent across sites.

The Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) P-band synthetic aperture radar (SAR) was flown more than 1200 h from August 2012 to September 2015, covering regions of 2500 km² spread over nine major biomes in North America. The flights, as a part of the NASA AirMOSS Earth Venture Suborbital 1 (EVS-1) mission, collected radar data used to map root-zone soil moisture (RZSM) at 3-arcsec resolution. We previously reported the baseline retrieval algorithm and demonstrated its performance for a semiarid shrubland (Walnut Gulch, AZ, USA); we represented the RZSM profile as a continuous quadratic function and solved a radar scattering nonlinear optimization problem to obtain the unknown polynomial coefficients. In this article, we expand the retrievals to other AirMOSS sites that, in addition to the semiarid shrubland, include grassland and crops (MOISST, OK, USA), woody savanna (Tonzi Ranch, CA, USA), temperate conifer forest (Metolius, OR, USA), and boreal forest (Saskatchewan, Canada). Due to a wide range of land covers, soil types, and soil moisture regimes, we parameterize the forward model and constrain the inverse algorithm for each site separately. We present the full set of retrievals for these sites, validating the results against in situ observations. Error sources and strategies to minimize their effects are discussed. The concept of sensing depth is introduced. We find that the retrieval errors are smallest for the top 25 cm of soil with a root-mean-square error (RMSE) of less than 0.05 m³/m³. The RMSE remains around 0.06 m³/m³ even for depths reaching 45 cm, which is the typical sensing depth for the sites considered. These AirMOSS RZSM products (known as Level-2/3 RZSM, or L2/3-RZSM, products) are the first of their kind in that it is the first time RZSM has been retrieved directly from remote sensing observation.

We propose an inversion model for retrieving the root-zone soil moisture profile using the P-band radar observations and validate it using data collected during the Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission. The forward model utilized in this article uses an existing small perturbation method (SPM) to calculate the electromagnetic wave scattered from multilayered rough surface dielectric structures. To solve the inverse problem, which is formulated as a least-squares problem, we utilize a novel global optimization technique that takes the advantage of the speed of a local optimization method while ensuring convergence to the global minimum. We present the numerical results to demonstrate significant improvements in the inversion results and computational speed compared to the previously used AirMOSS baseline inversion algorithm. The presented method is validated with in situ soil moisture measurements. Finally, by utilizing a closed-form analytical solution to Richards' equation, we demonstrate improvements in the accuracy of our soil moisture retrieval results.

This study examines the impact of variation in root‐zone soil moisture (RZSM), a key component of the Earth's hydrologic cycle and climate system, on regional carbon fluxes across seven North American ecosystems. P‐band synthetic aperture radar‐derived RZSM estimates were incorporated into the ecosystem demography (ED2) terrestrial biosphere model through a model‐data blending approach. Analysis shows that the model qualitatively captures inter‐daily and seasonal variability of observed RZSM at seven flux tower sites (r = 0.59 ± 0.26 andr = 0.70 ± 0.22 for 0–10 and 10–40 cm of soil layers, respectively;P < 0.001). Incorporating the remotely sensed RSZM estimates increases the accuracy (root‐mean‐square deviations decrease from 0.10 ± 0.07 and 0.09 ± 0.06 m³·m⁻³to 0.08 ± 0.05 and 0.07 ± 0.03 m³·m⁻³for 0–10 and 10–40 cm of soil layers, respectively) of the model's RZSM predictions. The regional carbon fluxes predicted by the native and RZSM‐constrained model were used to quantify sensitivities of gross primary productivity, autotrophic respiration (R_a), heterotrophic respiration (R_h), and net ecosystem exchange to variation in RZSM. Gross primary productivity exhibited the largest sensitivity (6.6 ± 10.7 kg·cm⁻²·year·θ⁻¹) followed by R_a(2.9 ± 7.3 kg·cm⁻²·year⁻¹·θ⁻¹), R_h(2.6 ± 3.1 kg·cm⁻²·year⁻¹·θ⁻¹), and net ecosystem exchange (−1.7 ± 7.8 kg·cm⁻²·year⁻¹·θ⁻¹). Analysis shows that these carbon flux sensitivities varied considerably across regions, reflecting influences of canopy structure, soil properties, and the ecophysiological properties of different plant functional types. This study highlights (1) the importance of improved terrestrial biosphere model predictions of RZSM to improve predictions of terrestrial carbon fluxes, (2) a need for improved pedotransfer functions, and (3) improved understanding of how soil characteristics, climate, and vegetation composition interact to govern the responses of different ecosystems to changing hydrological conditions.

We propose a method to estimate the active layer properties, including soil dielectric profiles and active layer thickness (ALT), in permafrost regions using time-series P-band polarimetric synthetic aperture radar (SAR) observations. The active layer and underlying permafrost are modeled as a three-layer dielectric structure with the layer dielectric constants representing the soil moisture and freeze-thaw state of the layer. To resolve the ambiguity of the retrieved layer thicknesses, an approach of finding the largest possible depths (LPDs) is combined with time-series observations, where the ALT is assumed time-invariant between the maximum thaw and before the upward freezing front rises significantly from the permafrost table. The LPD-assisted time-series retrieval algorithm is applied to the radar data acquired by the Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) P-band SAR in August and October 2014 and 2015 over the Alaska North Slope. The results show that the retrieved ALT values are generally underestimated for the sites where the in situ ALT is larger than the P-band sensing depth, with a retrieval bias ranging from -0.05 to -0.24 m as validated against the in situ ALT collected at Circumpolar Active Layer Monitoring (CALM) sites. For the sites where the in situ ALT is smaller than 0.55 m, the retrieval errors are generally less than 0.1 m. The retrieval results also show that the active layer properties are strongly influenced by the land cover types at the regional scale, and not as much by the North-South temperature gradient across a 180-km-long transect along the Deadhorse flight line.