Intensification of the Agulhas Leakage (AL) during glacial terminations has long been proposed as a necessary mechanism for reverting the Atlantic Meridional Overturning Circulation (AMOC) to its interglacial mode. However, lack of records showing the downstream evolution of AL signal and substantial temporal differences between AL intensification and resumption of deep‐water convection have cast doubt on the importance of this mechanism to the AMOC. Here, we analyze a combination of new and previously published data relating to Mg/Ca‐derived temperatures and ice volume‐corrected seawater δ18O records (δ18OIVC‐SW, as a proxy for relative changes in ocean salinity), which demonstrate propagation of AL signal via surface and thermocline waters to the western South Atlantic (Santos Basin) during Termination II and the early Last Interglacial. The saline AL waters were temporally stored in the upper subtropical South Atlantic until they were abruptly released in two stages into the North Atlantic via surface and thermocline waters at ca. 129 and 123 ka BP, respectively. Accounting for age model uncertainties, these two stages are coeval with the resumption of convection in the Labrador and Nordic seas during the Last Interglacial. We propose a mechanism whereby both active AL and a favorable ocean‐atmosphere configuration in the tropical Atlantic were required to allow flux of AL waters into the North Atlantic, where they then contributed to enhancing the AMOC during the Last Interglacial period. Our results provide a framework that connects AL strengthening to the AMOC intensifications that followed glaciations.

One of the key measurements from the Clouds and the Earth’s Radiant Energy System (CERES) satellite is Earth emitted or longwave (LW) radiation. The CERES Ocean Validation Experiment (COVE), located at Chesapeake Light Station, approximately 25 kilometers east of Virginia Beach, Virginia (coordinates: 36.90N, 75.71W) had provided surface validation for the CERES satellite measurements for many years. Upwelling LW radiation was one of the measurements made at COVE but was complicated due to the Light Station tower being in the upwelling LW instruments field of view. According to our estimates, the Light Station tower alters 15% of the upwelling LW radiation. An unwanted consequence of the tower being in the field of view was the tower radiating effect, particularly noticeable on clear, sunny days. During these days, the tower would radiate extra heat energy by as much as 3% (15 W/m^2) that was measured by the upwelling LW instrument. COVE follows the Baseline Surface Radiation Network requirements and their target uncertainty is 2%. To resolve this issue, we obtain a different upwelling longwave value using data from an infrared radiation thermometer (IRT) and a pyrgeometer that retrieves sea surface temperature (SST) and downwelling longwave respectively. Using an IRT allows conversion from SST to a water emission value and the pyrgeometer provides the reflected flux of the downward longwave radiation. By determining the extent of the undesirable obstruction in the field of view of the upwelling longwave instrument and determining its emissivity could allow others with similar issues to obtain the proper values of upwelling longwave measurements.

A high-resolution model of exospheric temperatures has been developed, with the objective of predicting the global values of exospheric temperatures with greater accuracy. From these temperatures, the neutral densities in the thermosphere can be calculated. This model is derived from measurements of the neutral densities on the CHAMP, GRACE, and Swarm satellites. These data were sorted into 1620, triangular cells on a spherical, polyhedral grid, using coordinates of geographic latitude and local solar time (longitude). A least-error fit of the data is used to obtain a separate set of regression coefficients for each grid cell. Several versions of model functions have been tested, using parameters such as the day-of-year, Universal Time, solar indices, and emissions from nitric oxide in the thermosphere, as measured with the SABER instrument on the TIMED satellite. Accuracy is improved with the addition of parameters that use the total Poynting flux flowing into the Northern and Southern hemispheres. This energy flux is obtained from the solar wind velocity and interplanetary magnetic, using an empirical model. Given a specific date, time, and other inputs, a global map of the exospheric temperature is obtained. These maps show significant variability in the polar regions, that are strongly modulated by the time-of-day, due to the rotation of the magnetic poles around the geographic pole. Values at specific locations are obtained using a triangular interpolation of these results. Comparisons of the exospheric temperatures from the model with neutral density measurements are shown to produce very good results.

Understanding the effects of water, energy, and food (WEF) consumption and production on socio-economic and environmental indicators has become a strategic issue for all countries, especially the developing ones, that depend on natural resources to promote economic growth. Our main objective with this study is to quantify and understand the interconnections (Nexus) of WEF production and consumption with regional economic growth and social development in Brazil. We use a multi input-output approach based on a Data Envelopment Analysis (DEA) model to calculate efficiency indicators over time for various municipalities in Brazil. We assume that a high input-output efficiency level indicates that a certain municipality can reach larger output benefits with less WEF consumption. The time-based approach using the Malmquist Index model enables us determining whether cities’ WEF input-output efficiencies have been rising or declining over time. The time-spatial analysis is appropriate to indicate the level of interdependence between WEF-Nexus and the demographic, economic, and environmental systems in Brazil. We expect that our results can help policymakers establishing regional and city-level policies that can benefit a more efficient use of WEF resources.

Water scarcity, population growth and climate change dilemmas imperatively require adaption strategies for a more efficient and sustainable use of water resources. Agricultural systems are part of a wider network, where all social, economic and, ecologic parameters must be taken into consideration to assess the performance and resilience of said network. The importance of accounting the complexity of human decisions and their impact on the water cycle has been increasingly studied, nevertheless the integration and analysis of different decision making theories into hydrological models still remains a major challenge and uncertainty source. Therefore, the ongoing project is aimed to improve the understanding of social dynamics in agrohydrological networks by assessing different irrigation practices including rainfed agriculture and deficit irrigation within a hydro-economic network. We developed an agent-based model (ABM) of farmer decision making on crop water productivity and groundwater levels using two existing optimization models: (i) the Assessment, Prognosis, Planning and Management Tool (APPM) (Schmitz, et al. 2010) that integrates the complex interactions of the strongly nonlinear meteorological, hydrological and agricultural phenomena, considering the socio-economic aspects and (ii) the Deficit Irrigation Toolbox (DIT) (Schütze and Mialyk 2019) to maximize crop-water productivity by analyzing the crop yield response to climate change, soil variability, water management practices. The developed ABM was assessed with the different theories on human decision-making based on the Modelling Human Behavior (MoHuB) framework (Schlüter, et al. 2017). As a result of this study, a sensitivity analysis of how different behavioral theories affect the dynamics of social-ecological systems which enables the evaluation of the robustness of policy implementation to different assumptions of human behavior where cooperation is a mechanism to improve resilience. This research was funded by the Technische Universität Dresden, by means of the Excellence Initiative by the German Federal and State Governments.

Formal international standards as well as promotion of community or recommended practices have their place in ensuring “FAIRness” of data. Data management in NASA’s Earth Observation System Data and Information System (EOSDIS) has benefited from both of these avenues to a significant extent. The purpose of this paper is to present one example of each of these, which promote (re)usability. The first is an ISO standard for specifying preservation content from Earth observation missions. The work on this started in 2011, informally within the Earth Science Information Partners (ESIP) in the US, while the European Space Agency (ESA) was leading an effort on Long-Term Data Preservation (LTDP). Resulting from the ESIP discussions was NASA’s Preservation Content Specification, which was applied in 2012 as a requirement for NASA’s new missions. ESA’s Preserved Data Set Content (PDSC) document was codified into a document adopted by the Committee on Earth Observation Satellites (CEOS). It was recognized that it would be useful to combine PCS and PDSC into an ISO standard to ensure consistency in data preservation on a broader international scale. This standard, numbered ISO 19165-2 has been under development since mid-2017. The second is an example of developing recommendations for “best practices” within more limited (still fairly broad) communities. A Data Product Developers’ Guide (DPDG) is currently being developed by one of NASA’s Earth Science Data System Working Groups (ESDSWGs). It is for use by developers of products to be derived from Earth observation data to improve product (re)usability. One of the challenges in developing the guide is the fact that there are already many applicable standards and guides. The relevant information needs to be selected and expressed in a succinct manner, with appropriate pointers to references. The DPDG aims to compile the most applicable parts of earlier guides into a single document outlining the typical development process for Earth Science data products. Standards and best practices formally endorsed by the Earth Science Data and Information System (ESDIS) Standards Office (ESO), outputs from ESDSWGs (e.g., Dataset Interoperability Working Group, and Data Quality Working Group), and recommendations from Distributed Active Archive Centers and data producers are emphasized.

Arctic sea ice coverage has changed considerably over the last few decades. Sea ice extent record minimums have been observed in recent years, the distribution of sea ice age now heavily favors younger ice, and sea ice is thinning. To investigate the response of the ice pack to climate forcing during summertime melt, we have developed a technique to track individual Arctic sea ice parcels along with associated properties as these parcels advect through the Arctic Ocean. This sea ice parcel tracking method utilizes our sea ice motion dataset, archived at NASA’s National Snow and Ice Data Center. Tracked sea ice parcel locations coincide with other environmental products that influence sea ice growth/decay. We have recently tracked variables such as ice surface temperature, albedo, ice concentration, and ice thickness for hundreds of sea ice parcels, defined as occupying one EASE-grid cell location. These parcels can be tracked through a melt season, to determine the influence of these properties on sea ice melt, along with determining what fraction of the parcels survive or don’t survive summer melt. This analysis can be applied to determine the impact of these and other properties on ice melt, in terms of their relative importance. Here, we focus on tracking recent sea ice freeboard, produced from NASA’s ICESat-2 observations. We look at the evolution of ice thickness for individual parcels through the recent ICESat-2 record, to determine the rate of ice growth over part or all of the winter, depending on product availability (as of this writing, freeboard is available through Dec 27, 2018). We determine how sea ice growth varies for hundreds of parcels, and determine how growth is affected by location and time.

Students K-16 in the United States and Canada joined their GLOBE Program peers from across the world in collecting water quality measurements during a week-long data-collection period in September, led by the GLOBE Africa Regional Coordination Office. The project was built off of other GLOBE collaborations around spring phenology measurements (Europe) and expeditions to Mt. Kilimanjaro and Lake Victoria (Africa). The efforts and resulting analysis of Collaboration: Water were supported by an international team of scientists, faculty and education professionals. The GLOBE Program Country Coordinators from the U.S. and Canada share the project goals, discuss the results of the September data challenge and how these lead into the community-based collaboration projects being developed between schools. Some of the projects will be presented during the International Virtual Science Symposium and Student Research Symposia in spring 2020. This project works on several levels. It creates resiliency locally through community-based inquiry, supports the development of 21st Century critical thinking, collaboration and communication skills and places the community investigations into the global context of the United Nations Sustainable Development Goal 6 (Clean Water and Sanitation). Along with tools, templates and the benefits of participation, the presenters will share how other communities can be involved in the March data collection event.

It is now widely understood that seasonal snow cover in the Western United States is melting earlier than in past decades. This could have significant consequences for human populations and ecosystems dependent on regularity in timing and magnitude of downstream flows that originate as snow. However, while earlier melt is well established, less is known about intra-annual changes in the spatial and temporal distribution of accumulation and ablation (melt) cycles in the core winter months and spring months, i.e. the ‘persistence’ of seasonal snow cover. This is significant because changes to the persistence of seasonal snow in the winter and spring could have important implications for other snow cover characteristics such as albedo, as well as ancillary hydrologic factors such as soil moisture and runoff. To understand these changes in persistence, this project focuses on study basins in different climatic zones of the Columbia river basin, capturing the shift from maritime snowpack in the west to alpine snowpack in the east. The research relies on a combination of time series analysis of NRCS SNOTEL stations and snow courses and use of an optical remote sensing product which is based on the MODIS MOD10A1 dataset. To compensate for significant winter and spring cloud cover, particularly in the Pacific Northwest, a temporal and spatial gap filling approach utilizing higher spatial resolution products (e.g. Landsat and Sentinel 2) is implemented primarily in Google Earth Engine. The seasonal snow persistence from the MODIS-based product is evaluated using additional Landsat, Sentinel 2 and Planet Labs data, as well as data from the in situ monitoring stations. Finally, changes in intra-annual seasonal snow cover persistence are characterized for core winter, spring and early summer months along an elevational gradient and across study sub-basins.

The Space Physics Data Facility (SPDF https://spdf.gsfc.nasa.gov) and Solar Data Analysis Center (SDAC https://umbra.nascom.nasa.gov/), as the NASA Heliophysics active final archives, will be preserving and distributing the data from Parker Solar Probe. Working in cooperation with current operating missions and the heliophysics community, SPDF ingests, preserves and serves a wide range of past and current public science-quality data from the ionosphere into the furthest reach of deep-space exploration. SPDF has been working with the Parker Solar Probe mission in preparation for archiving and serving its in-situ data starting 2019 Nov 12, and also has arrangements to serve in-situ data from Solar Orbiter when those data become public. SPDF will facilitate scientific analysis of multi-instrument and multi-mission datasets to enhance the science return of Parker Solar Probe mission. SPDF develops and maintains the Common Data Format (CDF) and the associated ISTP/SPDF metadata guidelines. SPDF services include CDAWeb, which supports both survey and burst mode data with graphics, listings and data superset/subset functions. All public data held by SPDF are also available for direct file download by HTTPS or FTPS links from the SPDF home page (https://spdf.gsfc.nasa.gov). SPDF is currently receiving and serving from missions including Helios, MMS, Van Allen Probes, THEMIS/ARTEMIS, GOLD, ACE, Cluster, Geotail, Polar, Wind and many others, and >120 Ground-Based investigations. SPDF recently added support for ARASE/ERG and MAVEN as supplementary access at the requests of those missions. SPDF also operates the multi-mission orbit displays and query services of SSCWeb and the Java-based 4D Orbit Viewer, as well as the Heliophysics Data Portal (HDP) discipline-wide data inventory and access service, and the OMNIweb near-Earth solar wind plasma and magnetic field database.

Over the past third of a century the Incorporated Research Institutions for Seismology (IRIS) has facilitated observational seismology in many ways. At the beginning of IRIS in 1984, and with the support of the National Science Foundation and in partnership with the US Geological Survey, IRIS embarked on deploying the Global Seismographic Network (GSN). Key characteristics of the GSN are its use of high-performance digitizers, very broad band seismometers, strong motion accelerometers, and high frequency sensors to provide multi-decadal observations across a wide frequency band and dynamic range. The IRIS Portable Array Seismic Studies of the Continental Lithosphere (PASSCAL) program has also operated since 1984. PASSCAL’s extensive inventory of seismic equipment has been used by scientists to make observations on every part of the globe. The number and breadth of observations made with this equipment has fueled thousands of research papers and contributed to the education of hundreds, if not thousands, of students. More recently, the IRIS-operated EarthScope Transportable Array (TA) provided a breakthrough in the systematic collection of data using an array of unprecedented size. The success of the TA has ushered in a new era of “Large N” seismology, focused on dense spatial coverage of sensors to reduce aliasing and provide more complete recording of the full wavefield. The TA highlighted the power of survey mode data collection, where systematic, spatially-dense, and high-quality data fuel data-driven discovery, as opposed to deployments made to test a specific hypothesis. Key future directions in observational seismology include an increasing emphasis on wavefield measurements. Deploying instruments in large numbers requires reductions in the size, weight, and power of units, as well as a focus on dirt-to-desktop data management strategies that merge data and metadata while minimizing human intervention with the data flow from the sensor in the dirt to the scientist’s desktop. Other critical frontiers include pervasive seafloor observations to enable studies of key structures like subduction zones, more accessible satellite telemetry to enable ubiquitous sensing of the environment, and new sensing technologies such as MEMS and Distributed Acoustic Sensing.

Seismic site characterization of rock and soil properties has a large impact on earthquake ground motions and engineering seismology, especially for evaluation of local site amplification, calibration of strong-motion records and realistic shaking estimates at seismic stations, site-specific hazard assessment, estimation of ground motion models and soil classification for building code applications. However, there is not yet a common way to exchange site characterization information, whereas setting-up standard practices and quality assessment are becoming very important to reach high-level metadata. Within the framework of the SERA “Seismology and Earthquake Engineering Research Infrastructure Alliance for Europe” Horizon 2020 Project, a networking activity is leading to the definition of a European strategy and standards for site characterization of seismic stations in Europe. Based on the results of an online questionnaire, we first defined a list of indicators considered as mandatory for a reliable site characterization: fundamental resonance frequency, shear-wave velocity profile (Vs), time-averaged Vs over the first 30 m, depth of seismological and engineering bedrock, surface geology, soil class. We then proposed a summary report for each indicator, containing the most significant background information of data acquisition and processing details, and a quality metrics scheme. This requires the evaluation of both (i) reliability of the site characterization indicators provided by different methods, and (ii) consistency among the indicators according to the current knowledge and experience of the scientific community. The quality metrics application to some Italian accelerometric sites, characterized within the Italian Civil Protection Department-INGV agreement (2016 to 2021), highlights the capabilities of capturing the characterization quality. These guidelines have been shared within European and worldwide scientific community and validated through focus groups during a dedicated workshop (https://sites.google.com/view/site-characterization-workshop/). They represent a first attempt to reach high-level metadata for site characterization, being aware that they can be improved and modified after a few years of experience and feedback from users.

Arctic amplification is a near-universal feature of climate change in simulations. However, climate models disagree in its magnitude and in its spatial and seasonal expression. Lower tropospheric stability (LTS = T_{850hpa} - T_{2m}) has been linked to Arctic amplification through its influence on radiative cooling efficiency and vertical propagation of surface fluxes. Using monthly mean output from the Community Earth System Model Large Ensemble (CESM LE) we find that internal variability in CESM LE is insufficient to explain the differences in LTS distributions over the Arctic Ocean found in CMIP3 and CMIP5 multi-model ensembles.To facilitate comparison with prior work we compare the CESM LE output to the ECMWF interim reanalysis (ERA-I) for the period 1979-2005. Over the ocean surfaces north of 60°, LTS exhibits a bimodal distribution. Dividing model and reanalysis output into open water and sea ice domains based on a sea ice concentration (SIC) threshold of 15% confirms LTS bimodality is the result of summing distinct distributions. Over sea ice, median NDJF LTS is 3.6 K in ERA-I and ranges from 5.7 K to 6.9 K in the CESM LE. Interquartile range of NDJF LTS is 4.7 K in ERA-I and varies from 9.6 K and 10.5 K across the ensemble. Spatial and seasonal patterns of LTS are qualitatively similar in the model and reanalysis: over ice LTS is positive through most of the year and slightly negative in the summer, and interannual variability is highest near the ice edge. However, the seasonal cycle of stability is stronger in CESM LE. We find that stability during early spring is consistently higher in CESM LE than in ERA-I. The enhanced variability over the central Arctic in CESM LE appears to be the result of variation in sea ice thickness.

The Solver of Hydrological Unstructured Domain (SHUD) is an integrated multi-process, multi-scale, multi-timestep hydrologic model where the dominant hydrological processes are fully coupled using the semi-discrete Finite Volume Method. The hydrologic processes in land surface, aquifer and river are fully coupled and solved together. The high spatial and temporal resolution in SHUD provides detailed and reliable hydrologic metrics in a watershed. The SHUD System consists of SHUD (the hydrologic model) and SHUDtoolbox (a data processing tool kit). The new SHUD system provides capabilities for public data downloads, pre-processing, hydrologic modeling, automatic calibration, post-processing and spatial visualization, and is fully open-source and ready for hydrological modelers to use. Here we introduce the philosophy of SHUD, from perceptual to computational structures of watershed hydrology, and select two watersheds (one in Africa and the other in California) as examples to demonstrate the workflow and capabilities of SHUD System. In modeling these examples, we exploit national/global public datasets and exemplify the data management, hydrologic analysis, model calibration and visualization capabilities. This modeling system not only supports quick deployment of hydrologic modeling functionality, but also benefits community modeling in other hydrology-related research fields, such as limnology, agriculture, climate change and Coupled-Natural-Human systems.

Migration is a complex and interdisciplinary problem involving multiple factors such as social interactions, resource scarcity, and geographical features. These factors must be incorporated in migration models, but how? We feel that the issue how different factors should be incorporated is not carefully addressed in existing models. Configuring factors in ways that are theoretically unsound can lead to false migration patterns and undermine the usefulness of models; indeed, factor configurations may be more critical than the factors themselves or other inputs. Therefore, we ask: i) How important is factor configuration to output results comparing with other inputs?; ii) How do different factor configurations produce different migration patterns?; and iii) How can multimodality of certain output distributions be controlled in a management perspective? To address the questions, we develop a “toy” migration agent-based model (ABM) and explore three possible configurations between two factors: i) two factors are perfectly substitutable (ADD), ii) both factors are indispensable (AND), and iii) either is enough (OR). ABM results are analyzed by global sensitivity analysis (GSA) and Monte-Carlo Filtering (MCF). The relative importance of factor configurations quantified by GSA emphasizes why we need to consider how the factors are incorporated. Depending on factor configurations, we also observe unimodal or multimodal output distributions. MCF is then applied to the ABM-GSA results to address how policymakers should control certain inputs to sustain systems with desirable outputs. Altogether, we have integrated ABM, GSA, and MCF to disentangle complexity of migration models and better understand underlying mechanisms and patterns of migration.

Low-current tributary-estuaries and embayments along the margin of the Hudson River are uniquely at risk for harmful algal blooms of cyanobacteria (cyanoHABs) due to rising temperatures as a result of climate change. An increased prevalence of cyanoHABs in near-shore, low-current sections of the Hudson River could be extremely harmful to nearby communities, aquatic organisms and wildlife. To address this increased risk, it is imperative to understand the current in-stream and upstream abiotic environmental controls (nutrients, water temperature, etc.) on the current background levels of cyanobacteria within the Hudson River. It is also important to understand how these controls and cyanobacterial populations vary spatially with relation to the higher risk, lower-flow sections along the margins of the Hudson River. Locations of tributary-estuaries of special concern within the Hudson Valley include Esopus Creek in Saugerties, Rondout Creek in Kingston, and Wappingers Creek in Wappingers, NY. Other locations of concern are embayments along the Hudson River such as Long Dock Park in Beacon, Port Ewen in Kingston and Norrie Point in Staatsburg, NY. Given the lower-flow nature of these sites, elevated surface water temperatures are likely a result of settled, striated layers from decreased current. These locations are also susceptible to growth of the invasive species Trapa natans or commonly known as the European water chestnut. High concentrations of nutrients like nitrogen and phosphorous within the water chestnut bloom and the captured sunlight from metabolic processes like photosynthesis can create an ideal microhabitat for harmful algae like cyanobacteria. The background levels of cyanobacteria in outflows of tributaries, and their lower-flow estuary extensions were observed alongside the water quality within the water chestnut blooms of these sites at varying depths. By studying the weekly changes in background abundance of cyanobacteria and their drivers occurring at contrasting locations along the Hudson River, it was found that the strongest controls included turbidity, temperature and levels of phosphorous. In locations of low turbidity and high surface water temperatures, the background levels of cyanobacteria were higher in these lower-flow areas than in areas with increased turbidity. Cyanobacteria was found in greater number within water chestnut blooms than in whole water samples outside the area of the bloom. High surface temperature and riverbed temperature also related to higher levels of cyanobacteria. Given the concluded information, it is apparent that invasive water chestnuts within lower-flow extensions of the Hudson River hold a greater threat than originally understood; creating an ideal habitat for potential cyanoHABs in the wake of climate change.

Anorthosites are attractive paleomagnetic recorders as silicate-hosted magnetite inclusions can be single-domain and be shielded from alteration. However, petrofabrics within anorthosites may result in magnetic remanence anisotropy that is potentially detrimental to recovering paleomagnetic direction and intensity. The Beaver River diabase of the North American Midcontinent Rift contains abundant nearly 100 percent plagioclase anorthosite xenoliths that are hypothesized to have been liberated from the lower crust by the magma enroute to becoming embedded in shallow crustal sills. In this study, we compare the remanent paleomagnetic directions recorded by anorthosite xenoliths to those of the Beaver River diabase host rocks. Given that both lithologies should record the same thermal remanent magnetization, this comparison provides a means to assess the effects of remanence anisotropy on the paleodirection recorded by the anorthosites. Thermal and anhysteretic remanence (TRM and ARM) anisotropy experiments, which are typically used to assess for anisotropy, can be compared to the natural remanence of the diabase and anorthosite in this geologic experiment that was conducted 1.1 billion years ago. Paleodirection data from the interior of the largest (>300 m) anorthosite xenoliths also have the potential to test their hypothetical lower crustal origin. An origin below the Curie depth would result in a full thermal remanence from the time of diabase emplacement, while a shallower origin from above the Curie depth could have resulted in a distinct remanence direction in the xenolith interior that predates the intrusion (with samples from the exterior having acquired a Beaver River diabase coeval thermal remanence in either scenario). Overall, this novel geological association between diabase and anorthosite provides a means to assess the effects of remanence anisotropy providing valuable context for efforts to use anorthosites to understand the ancient geomagnetic field.

Sediment settling velocities are commonly estimated from process-based or parametric data-driven approaches. The process-based approach has theoretical constraints due to the unclear settling physics; the parametric data-driven approach is limited by its mathematical assumptions. To overcome these limitations, this study compiles an aggregated sediment settling experimental database from literature and develops a non-parametric data-driven model to estimate the non-cohesive sediment settling velocity in water. A cross-comparison against five process-based equations and a parametric data-driven equation demonstrates the higher accuracy and better consistency of the new model in estimating sediment settling velocities under various physical regimes. The data-driven model also shows an easy-implemented self-update capability by assimilating theoretical data generated from the process-based equations. The updated model, leveraging experimental and theoretical data of sediment settling process, further improves the accuracy and reduces the uncertainty in estimating sediment settling velocities. This approach illustrates the value of integrating experimental and theoretical knowledge in estimating the complex process in sediment transport, and provides an alternative framework for future sediment transport exploration.