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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

V1G Frequency Regulation: Algorithm Development, Validation & Analysis at Scale

Researchers at Argonne National Laboratory developed and validated a high-fidelity digital twin of a smart charging (V1G) ecosystem to model the participation of up to 1,000 unique electric vehicles (EVs) in the PJM frequency regulation market. Utilizing a discrete-event framework, the simulation models complex interactions, from dynamic grid signals (updated every 2 seconds) to individual EV charging dynamics. The simulation incorporates multiple EV models created from real-world lab test data. Researchers tested multiple control algorithms to balance the dual objectives of maximizing aggregator’s revenue and driver charging needs. Results demonstrate that aggregated EVs function as a controllable, highly effective grid resource, achieving high PJM Performance Scores (80–90%). Additionally, an optimized, market-aware bidding strategy was identified as key to profitability. The platform was shown to provide drivers with an average charging discount of nearly 50%. The algorithm was further validated in the lab using production EVs and charging stations to compare simulation results with real-world performance.

Manne, Nithin↗
DOE OSTI2022

MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters

Abstract With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2018

An Initial Validation of Landsat 5 and 7 Derived Surface Water Temperature for U.S. Lakes, Reservoirs, and Estuaries

The United States Harmful Algal Bloom and Hypoxia Research Control Act of 2014 identified the need for forecasting and monitoring harmful algal blooms (HAB) in lakes, reservoirs, and estuaries across the nation. Temperature is a driver in HAB forecasting models that affects both HAB growth rates and toxin production. Therefore, temperature data derived from the U.S. Geological Survey Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper Plus thermal band products were validated across 35 lakes and reservoirs, and 24 estuaries. In situ data from the Water Quality Portal (WQP) were used for validation. The WQP serves data collected by state, federal, and tribal groups. Discrete in situ temperature data included measurements at 11,910 U.S. lakes and reservoirs from 1980 through 2015. Landsat temperature measurements could include 170,240 lakes and reservoirs once an operational product is achieved. The Landsat-derived temperature mean absolute error was 1.34 C in lake pixels (is) greater than180 m from land, 4.89 C at the land-water boundary, and 1.11 C in estuaries based on comparison against discrete surface in situ measurements. This is the first study to quantify Landsat resolvable U.S. lakes and reservoirs, and large-scale validation of an operational satellite provisional temperature climate data record algorithm. Due to the high performance of open water pixels, Landsat satellite data may supplement traditional in situ sampling by providing data for most U.S. lakes, reservoirs, and estuaries over consistent seasonal intervals (even with cloud cover) for an extended period of record of more than 35 years.

Schaeffer, Blake A.↗
DOE OSTI2021

Quantification of energy and cost reduction from decreasing dissolved oxygen levels in full‐scale water resource recovery facilities

Abstract Aeration systems often lack the efficiency to maintain a desired residual dissolved oxygen (DO) concentration in the tank in part because little consideration is given to the dynamic daily and seasonal loading conditions. Although advanced aeration controllers exist, the majority of plants have DO set points typically based on common practice and literature values rather than site‐specific conditions, which can result in DO set points higher than those necessary to meet treatment objectives. DO set point reduction strategies have primarily been proposed through either static or dynamic simulations. In this study, the substantial improvements associated with DO set point reduction are demonstrated at full scale. A yearlong characterization of full‐scale aeration dynamics captured the effect of diurnal and seasonal fluctuations on oxygen transfer and energy demand and so facilitated the estimation of the potential savings of DO reduction strategies. Full‐scale validation provided direct evidence of DO reduction strategies inducing an overall enhancement of oxygen transfer efficiency along the different bioreactors, while confirming that energy savings as high as 20% were feasible. This study quantifies the influence of oxygen transfer efficiency on operating choices and site‐specific conditions (control strategy, loading conditions, and influent flow variability). Practitioner points We quantified the energy reduction and cost savings associated with a DO reduction in an aeration tank. For each 0.2 mg/L of DO decreased, the average power demand reduction per unit water treated exceeded 17%. Field measurements of dynamic alpha values eliminate the uncertainty in estimating aeration energy and cost savings from DO variations.

Pasini, Federico↗
DOE OSTI2025

Large-Scale Compatibilization of Postconsumer Polyolefins in the Presence of Paraffin Wax as a Rheology Modifier

Postconsumer polyolefins (r-POs) are leading plastic waste contributors today. This study reports, for the first time, the compatibilization of r-POs at a 50 kilogram (kg) scale with a styrene block copolymer compatibilizer in the presence of paraffin waxes as rheology modifiers (RMs). The addition of the rheological modifier (RM) and compatibilizer enhances the melt flow indices (MFIs) and mechanical properties, respectively. One aspect of this study is to compare the effectiveness of low-cost paraffin wax to that of specialized and expensive RMs in r-POs. The mechanical and rheological properties such as the melt flow index (MFI) of r-POs were compared in the presence of two types of RMs. Next, the study explores the challenges encountered when scaling the compatibilization of r-POs in the presence of paraffin wax from a 10-g to a 50-kg scale. The mechanical properties were determined and compared for samples at different scales. The study further investigated the effect of the method used for blending paraffin wax with r-PO and its impact on the value of their MFI and mechanical properties. This at-scale validation could pave the way for the commercialization of r-POs.

crystallinity↗
DOE OSTI2023

Reaching a burning plasma and ignition using smaller capsules/ Hohlraums , higher radiation temperatures, and thicker ablator/ice on the national ignition facility

In indirect-drive implosions, the final core hot spot energy and pressure and, hence, neutron yield attainable in 1D increase with increasing laser peak power and, hence, radiation drive temperature at the fixed capsule and Hohlraum size. Here we present simple analytic scalings validated by 1D simulations that quantify the improvement in performance and use this to explain existing data and simulation trends. Extrapolating to the 500 TW National Ignition Facility peak power limit in a low gas-fill 5.4 mm diameter Hohlraum based on existing high adiabat implosion data at 400 TW, 1.3 MJ and 1 × 10 16 yield, we find that a 2–3 × 10 17 yield (0.5–0.7 MJ) is plausible using only 1.8 MJ of laser energy. Based on existing data varying deuterium–tritium (DT) fuel thickness and dopant areal density, further improvements should be possible by increasing DT fuel areal density, and hence confinement time and yield amplification.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Galaxy clustering in harmonic space from the dark energy survey year 1 data: compatibility with real-space results

ABSTRACT We perform an analysis in harmonic space of the Dark Energy Survey Year 1 Data (DES-Y1) galaxy clustering photometric data using products obtained for the real-space analysis. We test our pipeline with a suite of lognormal simulations, which are used to validate scale cuts in harmonic space as well as to provide a covariance matrix that takes into account the DES-Y1 mask. We then apply this pipeline to DES-Y1 data taking into account survey property maps derived for the real-space analysis. We compare with real-space DES-Y1 results obtained from a similar pipeline. We show that the harmonic space analysis we develop yields results that are compatible with the real-space analysis for the bias parameters. This verification paves the way to performing a harmonic space analysis for the upcoming DES-Y3 data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

The Switchgrass Microbiome: A Review of Structure, Function, and Taxonomic Distribution

Switchgrass (Panicum virgatum L.) has been championed as a promising bioenergy crop due to its high productivity across a wide environmental range. The switchgrass microbiome—including bacteria, archaea, fungi, and other microbiota inhabiting soil and plant tissues—can influence plant function substantially. We conducted a review of the literature investigating switchgrass microbiome structure, key functional roles, and taxa isolated from field-grown plants. Although site conditions and plant compartment (i.e., location within shoots, roots, or root-influenced soil) appear to be the strongest drivers of switchgrass microbiome structure, the microbiome is also shaped by climate, season, and host genotype. Studies comparing across plant species show that the switchgrass microbiome is more similar to the microbiomes of other perennial plants than to the microbiomes of annual plants. Members of the switchgrass microbiome confer several benefits to their host. Most notably, mycorrhizal fungi can increase plant biomass many-fold, associative nitrogen-fixing bacteria can provide a substantial portion of the plant’s nitrogen demand, and fungal endophytes can improve plant tolerance to drought. Although the fungi and bacteria cultured from switchgrass represent only a portion of the microbiome, these serve as a valuable resource for researchers interested in investigating functional outcomes of the switchgrass microbiome. We highlight areas where additional research is necessary for a more comprehensive understanding of switchgrass microbiome structure, function, and potential to enhance sustainable bioenergy production. Key gaps include the role of understudied organisms (e.g., viruses, microeukaryotes, and nonmycorrhizal fungi), multitrophic relationships, mechanisms underpinning switchgrass–microbiome interactions, and field-scale validation of experimental findings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Source Authentication of Distribution Synchrophasors for Cybersecurity of Microgrids

This letter proposes a hybrid approach combining Self-Adaptive Mathematical Morphology (SAMM) and Time-Frequency (TF) techniques to authenticate the source information of Distribution Synchrophasors (DS) within near-range locations. The SAMM can adaptively regulate the synchrophasors variations which are representatives of local environmental characteristics. Subsequently, TF mapping is employed to extract informative signatures from the regulated synchrophasors variation. Finally, Random Forest Classification (RFC) is used to correlate the extracted signatures with the source information based on the derived TF mapping. Experiment results using DS collected at multiple small geographical scales validated the proposed methodology.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Frontiers in the Simulation of Dislocations

Dislocations play a vital role in the mechanical behavior of crystalline materials during deformation. To capture dislocation phenomena across all relevant scales, a multiscale modeling framework of plasticity has emerged, with the goal of reaching a quantitative understanding of microstructure–property relations, for instance, to predict the strength and toughness of metals and alloys for engineering applications. This review describes the state of the art of the major dislocation modeling techniques, and then discusses how recent progress can be leveraged to advance the frontiers in simulations of dislocations. Furthermore, the frontiers of dislocation modeling include opportunities to establish quantitative connections between the scales, validate models against experiments, and use data science methods (e.g., machine learning) to gain an understanding of and enhance the current predictive capabilities.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Development of Carbon Molecular Sieves Hollow Fiber Membranes based on Polybenzimidazole Doped with Polyprotic Acids with Superior H 2 /CO 2 Separation Properties (Final Report)

The goal of this project was to develop a highly efficient membrane-based process to capture CO 2 from coal-derived syngas with 95% CO 2 purity, achieving the cost of electricity (COE) 30% below the baseline capture approaches (i.e., Selexol process) when coupled with the advancement in other areas of the power generation facility. Our core approach is based on high-permeance hollow fiber membranes (HFMs) with superior H 2 /CO 2 separation properties at the syngas process conditions, which can then be further utilized to design membrane reactors for process intensification of H 2 production and purification and CO 2 capture. Three organizations with complementary skills collaborated to achieve the goal, including the University at Buffalo (UB), Los Alamos National Laboratory (LANL), and Trimeric Corporation (Trimeric). We formulated logical steps to bring the membrane technology from Technology Readiness Level (TRL) 3 (Experimental proof of concept) to TRL 4 (Laboratory scale validation in relevant environment). During the budget period (BP) 1, we screened various polymeric materials and identified polybenzimidazole doped with inorganic polyprotic acids as the desirable platform. The acid doping increases the H 2 /CO 2 selectivity, and the sequential carbonization increases H 2 permeability while retaining the high selectivity. By manipulating the acid type and doping level and the carbonization temperature, we demonstrated advanced carbon molecular sieving (CMS) materials with H 2 permeability of above 200 Barrer (1 Barrer = 10 -10 cm 3 (STP) cm cm -2 s -2 cmHg -1 ) and H 2 /CO 2 selectivity of above 40 at 200-300°C with simulated syngas containing CO and water vapor. For example, the PBI-(H 3 PO 4 ) 0.11 carbonized at 700 °C exhibits H 2 permeability of 200 Barrer and H 2 /CO 2 selectivity of 60 at 200 °C, and H 2 permeability of 240 Barrer and H 2 /CO 2 selectivity of 54 at 225 °C, which meets the targeted properties and surpasses Robeson’s upper bound. During the BP2, we focused on the conversion of the advanced CMS materials to stable HFMs. Membranes with H 2 permeance of 1,090 GPU (1 GPU = 10 -6 cm 3 (STP) cm -2 s -2 cmHg -1 ) and H 2 /CO 2 selectivity of 57 at 300 °C were successfully fabricated. The effects of temperature, gas compositions, pressure, and time on the separation properties were systematically investigated. Pencil modules were continuously evaluated for 219 h (dry pure gas) and 669 h (dry simulated syngas) and showed initial decline in permeance and increased H 2 /CO 2 selectivity over time, ultimately achieving a steady state stable value, indicating that the ageing phenomena in the nanoporous structures of the membranes during the test. Membrane reactors were fabricated based on the CMS membranes and evaluated for water-gas shift (WGS) reaction. The use of membranes slightly improves the conversion of the CO. However, parametric tests of the membrane reactors at various temperatures and flow rates need to be conducted, as well as the membranes with improved separation performance. We performed a sensitivity analysis on the impact of H 2 /CO 2 selectivity on the COE based on a hybrid process of a membrane unit and cryogenic unit developed by Membrane Technology and Research, Inc. (MTR). Three H 2 /CO 2 selectivity (40, 60, and 15) cases were developed and compared with the baseline capture process (Case B5B) provided by the DOE report. Increasing the membrane H 2 /CO 2 selectivity reduces COE, but the rate of the decrease of COE also diminishes. The COE values for H 2 /CO 2 selectivities of 40 and 60 were nearly the same. As the H 2 /CO 2 selectivity increases, the inert recycling decreases, leading to smaller equipment, less auxiliary power requirements, and less heating, cooling, and refrigeration duty. The refrigeration system used to liquefy the CO 2 is the most expensive piece of equipment and consumes the most electricity within the CO 2 capture process. Increasing the CO 2 concentration in the recycle stream would improve the economics of the process by reducing the refrigeration duty requirement of the unit and also allow for higher liquefaction temperatures. The high H 2 -selective membrane developed by our team may be applicable in other separation processes where lower pressure H 2 retains value. Typically, hydrogen retains its pressure when it is separated from syngas components. Residual components may be used as low-quality fuel and then vented to the atmosphere. Applications might include control of H 2 /CO ratios or mitigation of the water gas shift reaction by CO 2 recycling to the feed of a gasifier or steam methane reformer. To summarize, we have developed industrial HFMs with the best H 2 /CO 2 separation performance reported in the literature. The membranes demonstrate stability with simulated syngas and show great potential for membrane reactors for WGS reactions, lowering the cost of blue H 2 production.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Advanced Structured Adsorbent Architectures for Transformative Carbon Dioxide Capture Performance (Final Report)

Svante is a world leader at using solid sorbents for low-cost Carbon Dioxide (CO 2 ) capture, a technology which is recognized as critical in meeting the dual mandates of energy security/reliability and the mitigation of man-made CO 2 emissions. Svante has been developing proprietary adsorbent material compositions, forming them into structured laminates, developing and optimizing process cycles, and system design for efficient capture of CO 2 from post-combustion flue gases of thermal power plants and industrial facilities. The deployment of first-generation CO 2 capture technology has been significantly hampered by high costs and energy penalties, among other barriers. Second generation CO 2 capture technologies (including the Mark I variant of Svante’s Veloxotherm™ adsorption-based technology), utilizing single adsorbent architecture, show promise for reducing the barriers to deploying CO 2 capture plants in commercially meaningful numbers. The objective of this project was to evaluate the Recipient’s transformational (Mark-II) VeloxoTherm™ Technology via the development and bench-scale testing of an advanced structured adsorbent, including novel Bi-layer, laminated adsorbent structures and segmented beds. Svante selected, synthesized, and characterized tailored solid adsorbents for computational modeling, advanced structured adsorbent development, process simulations, and dynamic bench scale (~1-10 kg/day CO 2 captured) testing using an existing single-bed VeloxoTherm™ Station (VTS) coupled with a natural gas-fired boiler. Segmented beds used the in-house, multi-bed Process Demonstration Unit (PDU) to demonstrate key performance indicators (KPIs), such as recovery, product purity, regeneration energy, and the integrated system's productivity in lifetime analysis. Segmented beds were used at a 1 tonne per day (TPD) unit at an industrial site to provide bench-scale validation of performance in an industrial setting. Svante was developing and optimizing the post-combustion CO 2 adsorption technology architectures, including the Bi-layer and segmented laminated adsorbent structure design, integrated rapid cycle temperature swing adsorption (RC-TSA) cycle, flow path architecture, and adsorbent bed construction and packaging (including gas porting) to progress towards achievement of DOE’s Transformational CO 2 Capture goals of 95% CO 2 purity and a cost of electricity at least 30% lower than a supercritical Pulverized Coal (PC) power plant with CO 2 capture, or approximately $30 per tonne of CO 2 captured ready for demonstration by 2030. The main requirements to reach the DOE target cost of carbon capture below $30/MT using Rapid-Cycling Temperature Swing Adsorption (RC-TSA) are as follows: (1) Increased capacity at different CO 2 concentrations, (2) Increased sorbents cycle life, (3) Increased O 2 resistance, and (4) Decreased steam requirement to extract 1 kg of CO 2 .

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Evaluation of cloud height, optical thickness, and phase retrievals from the CHROMA algorithm applied to Sentinel-3 OLCI data

We previously developed the Cloud Height Retrieval from O 2 Molecular Absorption (CHROMA) algorithm for the Ocean Color Instrument (OCI) on the new NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission. Here, we apply CHROMA to observations from the Ocean Land Colour Instrument (OLCI) to guide expectations for PACE, as it will take some time to obtain large-scale validation data for OCI. We use cloud top height (CTH), phase, and (for liquid clouds) cloud optical thickness (COT) data from the ground-based Atmospheric Radiation Measurement (ARM) network to evaluate the OLCI retrievals. We found that OLCI and Moderate Resolution Imaging Spectroradiometer (MODIS) CTH compare similarly well to the ARM reference. OLCI has a tendency to underestimate CTH as CTH increases, and algorithm assumptions about cloud geometric thickness may contribute to this. ARM COT from multifilter shadowband radiometers (MFRSR) and Sun photometers are well-correlated with one another, albeit with a roughly 30 % offset on average; OLCI and MODIS COT agree more closely with the MFRSR data. OLCI retrieval uncertainty estimates show skill at telling low-uncertainty cases from high-uncertainty ones, although CTH uncertainties are underestimated. Additionally, we compare the OLCI data to satellite retrievals based on thermal infrared measurements from MODIS and Sea and Land Surface Temperature Radiometer (SLSTR) data. Differences are broadly consistent with physical expectations based on the A-band vs. thermal techniques, although one key challenge in such aggregated comparisons is different cloud masking sensitivities and algorithm failure rates meaning additional sampling differences are introduced. We conclude by discussing the transition to and possible enhancements for PACE OCI.

Sayer, Andrew M. [Univ. of Maryland Baltimore Coun↗
NASA NTRS1986

Development of rotorcraft interior noise control concepts. Phase 3: Development of noise control concepts

The goal of this research is the understanding of helicopter internal noise mechanisms and the development, design, and testing of noise control concepts which will produce significant reductions in the acoustic environment to which passengers are exposed. The Phase 3 effort involved the identification and evaluation of current and advanced treatment concepts, including isolation of structure-borne paths. In addition, a plan was devised for the full-scale evaluation of an isolation concept. Specific objectives were as follows: (1) identification and characterization of various noise control concepts; (2) implementation of noise control concepts within the S-76 SEA (statistical energy analysis) model; (3) definition and evaluation of a preliminary acoustic isolation design to reduce structure-borne transmission of acoustic frequency main gearbox gear clash vibrations into the airframe; (4) formulation of a plan for the full-scale validation of the isolation concept; and (5) prediction of the cabin noise environment with various noise control concepts installed.

Yoerkie, Charles A.↗
NASA NTRS2005

Experimental Results from the Active Aeroelastic Wing Wind Tunnel Test Program

The Active Aeroelastic Wing (AAW) program is a cooperative effort among NASA, the Air Force Research Laboratory and the Boeing Company, encompassing flight testing, wind tunnel testing and analyses. The objective of the AAW program is to investigate the improvements that can be realized by exploiting aeroelastic characteristics, rather than viewing them as a detriment to vehicle performance and stability. To meet this objective, a wind tunnel model was crafted to duplicate the static aeroelastic behavior of the AAW flight vehicle. The model was tested in the NASA Langley Transonic Dynamics Tunnel in July and August 2004. The wind tunnel investigation served the program goal in three ways. First, the wind tunnel provided a benchmark for comparison with the flight vehicle and various levels of theoretical analyses. Second, it provided detailed insight highlighting the effects of individual parameters upon the aeroelastic response of the AAW vehicle. This parameter identification can then be used for future aeroelastic vehicle design guidance. Third, it provided data to validate scaling laws and their applicability with respect to statically scaled aeroelastic models.

Heeg, Jennifer↗
NASA NTRS2019

Translating Phased Array Measurements of a Low-Noise Top-Mounted Propulsion Installation for a Supersonic Airliner

A novel translating-phased-array technique was applied during a model-scale validation test of low-noise propulsion concepts for supersonic transport aircraft. The test involved particle image velocimetry, far field and translating phased array acoustic measurements. This paper covers the translating phased array portion. Data were acquired for a series of nozzles with different chevron designs, both uninstalled and installed on a representative aircraft planform. The far field data confirmed the noise reduction potential of top-mounted installation, while the phased array results gave insights into how the reduction occurred and highlighted areas for improvement. This was the inaugural test for the new translating phased array, which measures source maps as seen by observers at different polar angles. Propagation effects through the free jet were documented for the different viewing angles. The source maps obtained were used to understand important aspects of the far field noise measurements.

Beamforming↗
NASA NTRS2022

Global Landslide Forecasting System for Hazard Assessment and Situational Awareness

Landslides triggered by extreme rainfall can be devastating, resulting in loss of life, property, and infrastructure. Landslide forecasting systems provide an opportunity to build awareness of potential hazards and ultimately take preemptive measures. There is currently a dearth of forecasting systems that provide regional or global coverage, but these systems can offer important situational awareness in data-sparse, ungauged, or large-scale catchments. A near global, primarily satellite-based system calledthe Landslide Hazard Assessment for Situational Awareness (LHASA) provides near real-time estimates of potential landslide hazard and exposure around the world. In this work, a precipitation forecast module is introduced into LHASA to complement the existing LHASA framework and provide an estimate of landslide hazard up to three days in advanceat 1km resolution. The model-based Goddard Earth Observing System-Forward Processing (GEOS-FP) precipitation forecast product is used as the forcing input for the model in place of the satellite-based Integrated Multi-satellitE Retrievals for Global Precipitation Mission product. Soil moisture and snow depth from the GEOS-FP assimilated product are also incorporated. The study period January 2020–January 2021 is usedto test the model performance against the LHASA near real-time estimates at multiple spatiotemporal scales. Validation of the model is carried out using a collection of rainfall-triggered landslide inventories from around the world as case studies to demonstrate the potential utility and limitations of this system.The rescaling of the GEOS-FP precipitation product is a critical step in incorporating the forecasted precipitation data within LHASA-Forecast (LHASA-F). Combining different streams of forecasted data within the LHASA-F framework shows promise, particularly for larger events at the 1-and 2-day lead time for events. Results indicate that for the case studies evaluated, the LHASA-F is generally able to resolve major landslide events triggered by extreme rainfall, such as from tropical cyclones. The analysis shows that landslide forecast outputs may be represented differently depending on the user’s needs. This framework serves as a first milestone in providing a global predictive view of landslide hazard.

Landslide forecasting system↗
NASA NTRS2024

Improved Soil Moisture Estimation and Detection of Irrigation Signal By Incorporating SMAP Soil Moisture Into the Indian Land Data Assimilation System (ILDAS)

Land surface models have facilitated the estimation of soil moisture over a range of spatiotemporal scales. However, limitations in model parameterization and under-representation of anthropogenic processes restrict their ability to estimate local-scale soil moisture variability, especially over irrigated areas. Assimilation of satellite-based soil moisture retrievals into land surface models can be a viable approach to overcome these constraints, specially over highly irrigated countries such as India, where such applications are rare. Additionally, large-scale validation of modeled soil moisture has been limited over India till now due to lack of a representative station network. By assimilating Soil Moisture Active Passive (SMAP)-based estimates into the state-of-the-art Indian Land Data Assimilation System (ILDAS) and combining with a new soil moisture station network of more than 200 stations, this study demonstrates improved soil moisture estimations and capture of irrigation signals over the region. The Noah-MP land surface model is forced by multiple local and global meteorological datasets and Ensemble Kalman Filter (EnKF) is used for assimilation of soil moisture. Comparison of open-loop and data assimilated soil moisture against station soil moisture data shows relative spatial mean improvement of 0.0178 in correlation and 0.0029 m3/m3 in RMSE. Further statistical comparison with in-situ data has also shown better results over most of the stations, as evident from improved correlations and reduced unbiased RMSE after assimilation. Finally, the climatology of soil moisture over the different irrigation fractions reveals that data assimilated outputs over irrigated grid cells tend to have higher soil moisture during dry winter season, demonstrating the ability to capture irrigation signals. These findings quantify the value of data assimilation in improving soil moisture estimates and the ability to capture unmodeled processes such as irrigation, which lays the science groundwork for upcoming space missions such as NASA ISRO Synthetic Aperture Radar (NISAR).

Soil Moisture↗