Documented trends in the timing and intensity of precipitation events have been met with associated hydrologic changes in water-balance partitioning. Changes in land use, initiation and length of the growing season and associated irrigation practices, timing of autumn leaf senescence, snow accumulation and melt, flooding, and drought all affect the hydrological processes of infiltration, evapotranspiration, and runoff. This study is an investigation of trends in groundwater recharge over space and time in the temperate climate of the Midwest USA. It tests the hypothesis that increasingly intense precipitation events resulting in extreme runoff events might be short-circuiting processes of infiltration and groundwater recharge by lowering the residence time of water in upland landscapes, while increasing infiltration in lowlands and riparian corridors. The climate-driven changes in precipitation events can be more easily linked to the documented increasing stream discharge trends than trends in groundwater levels. In this ongoing study, multiple methods were utilized to calculate annual and monthly, or seasonal, potential aquifer recharge amounts and trends in unconsolidated aquifers in Indiana and surrounding watersheds. Because observation wells in Indiana are sparsely distributed, estimates of groundwater recharge for selected wells were used for calibration and validation of a 40-year spatially continuous water balance (U.S. Geological Survey Soil Water Balance v 2.0, SWB2) model that solved for potential groundwater recharge (net infiltration) at a daily time step and was analyzed at annual and monthly intervals. Using estimates of annual net infiltration from the SWB2 model, 40-year temporal trends calculated on space-time cubes suggest that over 50% of the model domain is experiencing statistically significant increases (p < 0.006) in potential groundwater recharge. Trend analyses of unconfined water levels from 1980-2019 were conducted, finding that water levels in 8 (out of 9) climate divisions in the state are increasing (rising) in 6 of the 8 climate divisions. The distribution of increasing water tables reflects the same spatial distribution as the annual estimates of recharge generated by the SWB2 model.

The Glen Torridon stratigraphic sequence marks the transition from the low energy lacustrine-dominated Murray formation (Mf) (Jura member: Jm) to the more diverse Carolyn Shoemaker formation (CSf) (Knockfarril Hill member: KHm; Glasgow member: Gm), indicating a change in overall depositional setting. Alpha Particle X-ray Spectrometer (APXS) results and statistical analysis reveals that the bulk primary geochemistry of Mf targets are broadly in family with CSf targets, but with subtle compositional and diagenetic trends with increasing elevation. APXS results reveal significant compositional differences between Jm_GT and the stratigraphically equivalent Jura on Vera Rubin ridge (Jm_VRR). APXS data defines two geochemical facies (high-K or high-Mg) with a strong bimodal grain distribution in Jm_GT and KHm. The contact between KHm to Gm is marked by abrupt sedimentological changes but a similar composition for both. Away from the contact, the KHm and Gm plot discretely, suggesting a zone of common alteration at the transition and/or a gradual transition in provenance with increasing elevation in the Gm. APXS results point to a complex history of diagenesis within Glen Torridon, with increasing diagenesis close to the Basal Siccar Point unconformity on the Greenheugh pediment, and with proximity to the beginning of the clay sulfate transition. Elemental mobility is evident in localized enrichments or depletions of Ca, S, Mn, P, Zn, Ni. The highly altered Hutton interval, in contact with the unconformity on Tower butte, is also identified on Western Butte, indicating that the “interval” was once laterally extensive.

Most efforts to characterize the size and composition of the mantle that complements the continental crust have assumed that the mid-ocean ridge basalt (MORB) source is the incompatible-element depleted residue of continental crust extraction. The use of Nd isotopes to model this process led to the conclusion that the “depleted MORB reservoir” is confined to the upper ~30% of the mantle, leaving the lower mantle in a more “primitive” state. Here we use Nb/U and Ta/U to evaluate mass and composition of the mantle reservoir residual to continent extraction and find that it exceeds 67% of the total mantle. Thus the (Nb,Ta)/U-based mass balance conflicts with the ε(Nd)-based mass balance, and this invalidates the classical 3-reservoir silicate Earth model (continental crust, depleted mantle, primitive mantle). Including the combined MORB + ocean island basalt (OIB) sources in the ε(Nd)-based mass balance does not reconcile the conflict as it would require their average ε(Nd) to be ≤3.0, much lower than observed MORB+OIB ε(Nd) averages. We resolve this conflict by invoking an additional, “early-enriched reservoir” (EER), formed prior to extraction of significant continental crust, but now hidden or lost. This EER differs from EERs previously invoked by having no Nb-Ta anomaly. We suggest that it originated as an early mafic crust, which had unfractionated (Nb,Ta)/U but fractionated Sm/Nd ratios. The corresponding “early-depleted” reservoir (EDR) generated the present-day continental crust and the “residual mantle” MORB-OIB reservoir, which occupies at least 70% of the present-day mantle and is only moderately depleted in incompatible trace elements.

Ocean worlds such as Europa and Enceladus are high priority targets in the search for past or extant life beyond Earth. Evidence of life may be preserved in samples of surface ice by processes such as deposition from active plumes or thermal convection. Terrestrial life produces unique distributions of organic molecules that translate into recognizable biosignatures. Identification and quantification of these organic compounds can be achieved by separation science such as capillary electrophoresis coupled to mass spectrometry (CE-MS). However, the data generated by such an instrument can be multiple orders of magnitude larger than what can be transmitted back to Earth during an ocean worlds mission. This requires onboard science data analysis capabilities that summarize and prioritize CE-MS observations with limited compute resources. In response, the Autonomous Capillary Electrophoresis Mass-spectra Examination (ACME) onboard science autonomy system was created for application to the Ocean Worlds Life Surveyor (OWLS) instrument suite. ACME is able to compress raw mass spectra by two to three orders of magnitude while preserving most of its scientifically relevant information content. This summarization is achieved by the extraction of raw data surrounding autonomously identified ion peaks and the detection and parameterization of unique background regions. Prioritization of the summarized observations is then enabled by providing estimates of scientific utility, the uniqueness of an observation relative to previous observations, and the presence of key target compound signatures.

Lava tubes on Mars hold exciting potential for the preservation of biosignatures, which may survive on geological timescales in these isolated, stable environments. To support the development of future astrobiological mission concepts, we turn to terrestrial lava tubes, host to a variety of microbial communities and secondary minerals. Following a multidisciplinary sampling protocol, we retrieved biological, molecular, and mineralogical data from several lava tubes in Iceland. We report on blue-colored copper-rich secondary minerals and their associated bacterial communities using a multi-method approach, and an amalgam of 16S rRNA gene sequencing, Raman spectroscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy data sets. We found numerous bacterial genera known for their high metal resistance and ability to survive in low-nutrient environments, both characteristics to be expected for any potential life in Martian lava tubes. Associated with them, we identified several types of copper-rich secondary minerals as well as carotenoid signals. If found in Martian lava tubes, blue copper-rich mineral precipitates would be deserving of astrobiological investigation, as they have potential to preserve biosignatures and harbor life.

We report observations of a Bursty Bulk Flow (BBF) penetrating to the outer edge of the radiation belt. The turbulent BBF braking region is characterized by ion velocity fluctuations, magnetic field (B) variations, and intense electric fields (E). In this event, energetic (>100 keV) electron and ion fluxes are appreciably enhanced. Importantly, fluctuations in energetic electrons and ions suggest that they are locally energized. Using correlation distances and other observed characteristics of turbulent E, test-particle simulations support that local energization by E favors higher-energy electrons and leads to an enhanced energetic shoulder and tail in the electron distributions. The energetic shoulder and tail can be amplified to MeV energies by adiabatic transport into the radiation belt where |B| is higher. This analysis suggests that turbulence generated by BBFs can, in part, supply energetic particles to the outer radiation belt and that turbulence can be a significant contributor to particle acceleration.

Time-lapse borehole nuclear magnetic resonance (bNMR) relaxation is a promising method for linking water content changes in the unsaturated region of the critical zone with pore-scale properties associated with bedrock weathering. The saturation-dependance of the NMR T2 distribution is strongly controlled by pore-scale material properties and can be linked to hydraulic properties (e.g. the water retention function and hydraulic conductivity). Here, we leverage NMR’s sensitivity to pore-scale properties to investigate material controls on plant-available water storage dynamics in weathered bedrock via time-lapse bNMR relaxation measurements. To overcome slow logging speed and poor signal-to-noise (SNR) ratio typically associated with bNMR measurements in the unsaturated zone, we focus on the sum of echos (SE). We show that the advantage of using SE to characterize NMR relaxation, rather than using the full T2 distribution or the logarithmic mean of the distribution, is that it is easy to calculate, does not require inversion, has enhanced SNR, and is sensitive to both volumetric water content (VWC) and mean T2. This leads to high contrast in SE between time-lapse measurements relative to other metrics of NMR relaxation. At our hillslope study site associated with the Eel River CZO, VWC changes in weathered bedrock driven by deeply-rooted trees allow us to create “NMR characteristic curves” for different regions of the weathering profile. Analogous to a water retention function, the NMR characteristic curves describe NMR relaxation times of a material at a given VWC, and can be used to identify differences in pore-scale properties. We show that mean T2 times are typically shorter in bedrock that is more weathered for the same VWC, which is consistent with smaller pore-sizes and higher surface relaxivities associated with weathering products such as secondary clays and oxides. Our well logging indicates that changes in pore structure associated with bedrock weathering control plant-available water supply within the bedrock weathering profile. While these results illustrate the utility of bNMR, further studies that quantitatively link NMR measurements to flow properties via pore or empirical models will benefit mechanistic understanding of plant available water in the critical zone.

The main sources of the ambient seismic wavefield in the microseismic frequency band (peaking in the ~0.04-0.5 Hz range) are the earth’s oceans, namely wind-driven surface gravity waves (SGW) coupling oscillations into the seafloor and the upper crust underneath. Cyclones (e.g. hurricanes, typhoons) and other atmospheric storms are efficient generators of high ocean waves with complex but distinct microseismic signatures. In this study, we perform a polarization (i.e. 3-component) beamforming analysis of microseismic (0.05-0.16 Hz) retrograde Rayleigh and Love waves during major Atlantic hurricanes using a virtual array of seismometers in North America. Oceanic hindcasts and meteorological data are used for comparison. No continuous generation of microseism along the hurricane track is observed but rather an intermittent signal generation at specific oceanic locations along the track. Both seismic surface wave types show clear cyclone-related microseismic signatures and are consistent with a colocated generation at near-coastal or shallow regions, however the Love wavefield is comparatively less coherent. We identify two different kind of signals: a) intermittent signals that originate with a constant spatial lag at the trail of the hurricanes and b) signals remaining highly stationary in direction of arrival even days after the hurricane passed the presumable source region. This high complexity highlights the need for further studies to unravel the interplay between site-dependent geophysical parameters and SGW forcing at depth, as well as the potential use of cyclone microseisms as passive natural sources.

Hadal trenches act as depocenters for organic material, although pathways for hadal material transport and deposition rates are poorly constrained. Here we assess, focusing, deposition and accumulation, of material and organic carbon in four hadal trench systems underlying provinces of different net primary productivity in the surface ocean – from the eutrophic Atacama and Kuril-Kamchatka trenches, and the mesotrophic Kermadec Trench, to the oligotrophic Mariana Trench. The study is based on the distributions of 210Pbex, 137Cs and total organic carbon from recovered sediment cores and by applying previously quantified benthic mineralization rates. Periods of steady deposition and discreet mass-wasting deposits were identified from the profiles and the latter were associated with historic recorded seismic events in the respective regions. During periods without mass wasting, the estimated focusing factors along trench axes were elevated, suggesting continuous downslope focusing of material towards the interior of the trenches. The estimated accumulation rates of organic carbon during these periods exhibited extensive site-specific variability but were generally similar to values encountered at much shallower settings such as continental slopes and margins. Organic carbon deposition and accumulation rates during periods of steady deposition was not mirrored by surface ocean productivity, but appeared confounded by local bathymetry. Seismic driven mass wasting events markedly enhanced the accumulation of sediment and organic carbon by factors from 20 to 400. Thus, hadal trenches are important sites for deposition and sequestration of organic carbon in the deep-sea partly due to intensified downslope focusing of material but mainly due to mass-wasting events.

The ultimate goal of a scientific investigation is usually to find answers to specific, often low-dimensional questions: what is the size of a subsurface body? Does a hypothesised subsurface feature exist? Existing information is reviewed, an experiment is designed and performed to acquire new data, and the most likely answer is estimated. Typically the answer is interpreted from geological and geophysical data or models, but is biased because only one particular forward function is considered, one inversion method is applied, and because human interpretation is a biased process. Interrogation theory provides a systematic way to answer specific questions by combining forward, design, inverse and decision theories. The optimal answer is made more robust since it balances multiple possible forward models, inverse algorithms and model parametrizations, probabilistically. In a synthetic test, we evaluate the area of a low-velocity anomaly by interrogating Bayesian tomographic results. By combining the effect of four inversion algorithms, the optimal answer is very close to the true answer, even on a coarsely gridded parametrisation. In a field data test, we evaluate the volume of the East Irish Sea basins using 3D shear wave speed depth inversion results. This example shows that interrogation theory provides a useful way to answer realistic questions about the Earth. A key revelation is that while the majority of computation may be spent solving inverse problem, much of the skill and effort involved in answering questions may be spent defining and calculating those target function values in a clear and unbiased manner.

Marine sediments contain considerable amounts and different types of magnetic mineral particles. Magnetic minerals in sediments may be statistically aligned to the direction of the ambient geomagnetic field so that sediments potentially preserve geomagnetic intensity records in the past. However, different types of magnetic minerals should preserve the remanent magnetization in different manners. And the compositional variation of magnetic mineral assemblages in marine sediments may hinder us from extracting reliable geomagnetic paleointensity records. We studied a sediment core taken from the Ontong-Java plateau, from which relative paleointensity (RPI) variations were estimated. The magnetic mineral assemblages of the sediment core are principally a two-component mixture of terrigenous and biogenic magnetite. So it provides an opportunity to assess the influence that compositional variations in marine sediments could bring to RPI estimations and thus to distinguish different contributions of the biogenic and terrigenous components to RPI recording in marine sediments. RPI obtained by normalizing natural remanent magnetization (NRM) with anhysteretic remanent magnetization (ARM) shows downcore decreases, and it has an inverse correlation with the ratio of ARM susceptibility (kARM) to saturation isothermal remanent magnetization (SIRM) (kARM/SIRM). This indicates that the RPI signal becomes apparently weaker with increasing proportion of biogenic magnetite. Moreover, NRM-ARM demagnetization diagrams show concave-down curvature, which indicates that the coercivity distributions of NRM and ARM are different. If we assume that the magnetization of the higher coercivity interval is mainly carried by biogenic magnetite while that of the lower coercivity interval is mainly carried by the terrigenous component, RPI recording efficiency of the biogenic component may be lower than that of the terrigenous component. The validity of this assumption was investigated by first-order reversal curve (FORC) measurements, transmission electron microscope (TEM) observations, low-temperature measurements, and extraction of silicate-hosted magnetic inclusion from the sediments, and the results proved that NRM of the higher coercivity interval is carried mainly by biogenic magnetite. But our conclusion contradicts with some previous studies using a similar method, which suggested higher RPI recording efficiency of the biogenic magnetic component than the terrigenous component [Ouyang et al., 2014; Chen et al., 2017]. Different concentrations of silicate-hosted magnetic inclusions due to different sedimentary environments might be a possible reason for the contradiction. The contribution of silicate-hosted magnetic inclusions to the magnetization is minor in our sediments (less than ~7% of SIRM). This contradiction remains to be studied further. Keywords: geomagnetic paleointensity, silicate-hosted magnetic mineral inclusion, biogenic magnetite, Ontong-Java plateau

The predictability of stratospheric sudden warming (SSW) events are considered in 10 subseasonal to seasonal (S2S) forecast models for 10 SSWs over the period 1999-2009. The 10 SSWs are divided into those with above-average predictability (in one case exceeding 20 days), below-average predictability, and average predictability. The four factors that most succinctly distinguish the composite with above average predictability are an active Madden-Julian Oscillation with enhanced convection in the West Pacific, the Quasi-Biennial Oscillation phase with easterlies in the lower stratosphere, a strong SSW, and a strong pulse of wave activity in the week before the event. Other factors, such as El Nino, stratospheric preconditioning, and the morphology (split vs. displacement) are comparatively less important.

Since the first space-borne Doppler wind lidar, Aeolus, was launched, global wind field observations from space have been possible. Several ground- and air-based validations followed, although most of these comparisons remained below 10 km in the troposphere, with rare validation work for the stratosphere. The Rayleigh Doppler lidar developed by the University of Science and Technology of China (USTC) was deployed in Xinjiang, China in 2017. It can observe wind speed and temperature in the stratosphere and mesosphere. By setting two geographical ranges centered on the USTC lidar, the Aeolus Rayleigh winds within these ranges can be compared with ground-based lidar wind data. Furthermore, after eliminating the effect of particulate backscatter on the USTC lidar, the lower limit of the detection range was extended to 10 km to obtain more samples. The mean biases between the Aeolus winds and the USTC lidar winds were 1.05±5.98 (-0.35±4.78) m/s, 1.80±6.30 (-1.88±4.97) m/s, and 0.17±5.45 (0.51±4.44) m/s for all data, ascending orbits, and descending orbits, respectively, in a large (small) geographical range. The results for descending orbits have a higher degree of consistency with those for ascending orbits, and the farther the distance between Aeolus observation swaths and the USTC lidar, the greater the bias. Overall, the Aeolus winds are consistent with the USTC lidar winds in the stratosphere.

In recent decades, major growth is observed in wildfire incidents across the globe. These ecological disasters, triggered by natural and/or anthropogenic factors, can have long-lasting effects on the environment, ecosystems, and biodiversity. Advancements in remote sensing technology provided an impetus to forest fires research, enabling precise determination of the geographical locations susceptible to fire and assess fire risk. This study focuses on India, whose total forest cover (71.22 Mha) is about 21.67% of the country’s total geographical area. Around 90% of the forest fires in India are attributable to anthropogenic factors. Therefore, the generation of a forest fire risk map (FRM) is essential for devising strategies to mitigate/manage forest fires and avert their disastrous impacts. An attempt is made to develop FRM for the Budhabalanga river basin, which contains the Similipal national park, a part of the UNESCO World Network of Biosphere Reserves. For this purpose, covariates affecting forest fire are identified viz. fuel (vegetation), topographic features (elevation, aspect, and slope), and human activities. The covariates are assigned weights, depicting their relative importance in influencing the fire, byusing Analytical Hierarchical Process (AHP). The AHP is a widely used technique in multi-criteria decision-making models. The Similipal national park has experienced a prolonged dry spell and below-average monsoon in 2020. The consequent dry conditions led to a significant forest fire event in the last week of February 2021, which lasted nearly three weeks. Fine (30m) resolution satellite data (Landsat-8) are used to calculate the Normalized Difference Vegetation Index (NDVI) corresponding to the study area to assess vegetation conditions before the fire event. Furthermore, Cartosat-1 Digital Elevation Model (24m resolution) is used to extract topographic-related information. The FRM generated for the basin using the assigned weights was 80% accurate when validated with 375m resolution NASA’s VIIRS (Visible Infrared Imaging Radiometer Suite) fire point data for the analyzed fire event. Hence, the methodology considered for developing FRM appears promising. It can be extended to other river basins for identifying fire risk zones and devise timely strategies to mitigate fire risk.

In mountain rivers, long-term observations of water and sediment fluxes are crucial for understanding the dynamics of bedload fluctuations at multiple temporal scales. Here we analyze 7 years of data gathered at a bedload monitoring station in the glacier-fed Sulden/Solda River (South Tyrol, Italy). Continuous seismic data gathered from 8 geophone plates are analyzed to estimate the bedload flux at 1 minute scale. Sixty-five direct bedload sampling were carried out to derive the calibration equations adopted to quantify the transported bedload mass. The signal power is proposed as a more effective metric for calculating bedload mass than threshold-based impulses. Results show: (i) a remarkable variability of bedload rate for the same value of flow discharge; (ii) the joint effect of storm-driven flood events and seasonal changes in sediment supply on bedload rates; and (iii) the strong impact of climatic factors (i.e., temperature and snow cover) on bedload fluxes. Moderate bedload rates occurring in late spring/early summer are likely related to the mobilization of riverbed sediments, while higher bedload peak rates observed in July-August are associated with the activation of glacial and proglacial sediment sources. The dataset shows a complex climatic control on bedload transport at the basin scale, where precipitation, air temperature and snow cover determine flow and glacier melting dynamics. These findings suggest how the effects of the ongoing climatic change (e.g., higher frequency of intense rainfall events and prolonged heat waves) can result in a marked increase in bedload transport in glacier-fed rivers of the Alps.

The Surface Biology and Geology (SBG) mission is one of the core missions of NASA’s Earth System Observatory (ESO). SBG will acquire high resolution solar-reflected spectroscopy and thermal infrared observations at a data rate of ~10 TB/day and generate products at ~75 TB/day. As the per-day volume is greater than NASA’s total extant airborne hyperspectral data collection, collecting, processing/re- processing, disseminating, and exploiting the SBG data presents new challenges. To address these challenges, we are developing a prototype science pipeline and a full-volume global hyperspectral synthetic data set to help prepare for SBG’s flight. Our science pipeline is based on the science processing operations technology developed for the Kepler and TESS planet-hunting missions. The pipeline infrastructure, Ziggy, provides a scalable architecture for robust, repeatable, and replicable science and application products that can be run on a range of systems from a laptop to the cloud or an on-site supercomputer. Our effort began by ingesting data and applying workflows from the EO- 1/Hyperion 17-year mission archive that provides globally sampled visible through shortwave infrared spectra that are representative of SBG data types and volumes. We have fully implemented the first stage of processing, from the raw data (Level 0) to top-of-the-atmosphere radiance (Level 1R). We plan to begin reprocessing the entire 55 TB Hyperion data set by the end of 2021. Work to implement an atmospheric correction module to convert the L1R data to surface reflectance (Level 2) is also underway. Additionally, an effort to develop a hybrid High Performance Computing (HPC)/cloud processing framework has been started to help optimize the cost, processing throughput and overall system resiliency for SBG’s science data system (SDS). Separately, we have developed a method for generating full-volume synthetic data sets for SBG based on MODIS data and have made the first version of this data set available to the community on the data portal of NASA’s Advanced Supercomputing Division at NASA Ames Research Center. The synthetic data will make it possible to test parts of the pipeline infrastructure and other software to be applied for product generation.

Studies have long reported the existence of pronounced diurnal and semi-diurnal variations in near-surface winds and divergence over the tropical oceans. Diurnal cycles of convective precipitation and cloudiness in the tropics are also well recognized from in-situ and satellite observations. However, the linkages between diurnal variations in tropospheric circulation, cloudiness and precipitation over the tropical oceans remain to be fully documented and understood. Recently, global storm-resolving models, which do not require convective parameterizations, have created an unprecedented opportunity to investigate the full three-dimensional structure of the diurnal cycle over the tropical oceans. In this study, we used one such model – the Model for Prediction Across Scales (MPAS) – for two main purposes: first, to evaluate the model’s representation of semi-diurnal and diurnal variations in near-surface winds, precipitation, and cloudiness over the tropical oceans; and second, to extend the analyses to provide a full three-dimensional picture of the daily variations in tropospheric circulation and their linkage with the hydrological cycle. A 40-day MPAS simulation (the same as used for DYAMOND-1 global storm-resolving models inter-comparison project) was utilized in this study to examine the large-scale geographical patterns and vertical structures of mean daily variations of zonal and meridional wind components, wind divergence, vertical velocity, cloudiness, water vapor mixing ratio and precipitation. The model shows generally good agreement with the previously reported observational results for near-surface winds and divergence. In particular, MPAS exhibits a pronounced large-scale diurnal cycle in the local Hadley Circulation over the Tropical Pacific Ocean, with lower tropospheric divergence (convergence) relative to the daily mean, maximizing around 1000 (2200) LT. The amplitude of the diurnal variation in near-surface wind divergence at the equator is approximately 0.8×10-6 s-1, or approximately 44% of the daily mean. The vertical structure of this diurnal circulation, along with its signature in vertical velocity and its association with water vapor, cloudiness and precipitation, will be presented.

Soil moisture plays an essential role in the complex eco-hydrologic processes, such as infiltration, rainfall-evapotranspiration-runoff circulation, photosynthesis, and groundwater recharge. However, the accurate estimation of soil moisture (SM) at regional or larger scale is difficult because SM varies highly over space and time due to heterogeneous land cover and soil properties, and ground measurements are often time-consuming and expensive. Currently, Bangladesh Meteorological Department (BMD) measures SM only at twelve stations which is quite inadequate for assessing large-scale spatial and temporal variation of SM. Thus, satellite-derived soil moisture data products or Global Land Data Assimilation System simulated (GLDAS-2.2) soil moisture dataset with the Gravity Recovery and Climate Experiment Data Assimilation (GRACE-DA) can be promising alternatives to the in-situ measurement for this data-scarce region. In this study, the spatial and temporal variations of SM from GLDAS and Soil Moisture Active Passive (SMAP) satellite were compared against the in-situ measurements from seven agrometeorological stations of Bangladesh. The GLDAS and SMAP products overpredicted the in-situ SM for most of the stations and could capture the temporal dynamics of observed SM with correlation coefficient (R) of 0.36 and 0.17, respectively. Later an Artificial Neural Network model was developed based on soil moisture from both sources (SMAP and GLDAS) and terrestrial water storage from GLDAS to obtain more accurate estimation of SM for this data-scarce region. The ANN model shows an improvement in estimation and predicted SM with R = 0.63 (considering all stations). The results were more promising when separate model is developed for each study site. Incorporating additional climate data (such as precipitation with different lag times) as input improved the accuracy marginally. This study suggests that the release of daily GRACE gravity field solutions in near-real-time may provide a reasonable and continuous estimate of soil moisture in this data-scarce region.