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At least 235 records · Page 13

Model Data Archive for Manuscript Titled "Evaluation of a Coupled Surface–Subsurface Hydrologic Model Using Dense Water‑Level Sensors in a Mixed Urban–Rural Watershed"

This archive provides scripts, input files, and datasets used for the implementation and evaluation of a fully coupled surface–subsurface hydrologic model in the Neches River Basin, southeast Texas. The study uses the Advanced Terrestrial Simulator (ATS) to simulate coupled surface–subsurface hydrologic processes over a mixed urban–rural watershed and evaluates model performance using a dense network of 136 in situ water-level sensors, nine U.S. Geological Survey (USGS) stream gauges, and SSEBop-derived evapotranspiration estimates during the period October 2014–June 2024. The workflow is implemented primarily in Python 3 using the Watershed Workflow package. The Jupyter notebooks can be executed using open-source software such as Anaconda JupyterLab or Visual Studio Code. Other data files include TXT, CSV, XML, SHP, TIF, NetCDF, HDF5, and ExodusII files, which can be processed using the provided Python scripts. ATS input files are provided in XML format and can be edited using any commonly used text editor. This archive contains: *Scripts and input files used to generate the ATS model setup, including watershed discretization, mesh generation, parameter mapping, and model configuration. *Jupyter notebooks used for preprocessing observational data, evaluating streamflow, water levels, and evapotranspiration, computing performance metrics, and generating the figures presented in the manuscript. *ATS simulation outputs and processed observational datasets, including OneRain and DD6 water-level sensors, USGS streamflow observations, GIS data, and supporting spatial datasets used throughout the study.

Dense water-level sensor network↗

Theoretical model of dielectrophoretic water vapor condensation during multiphase flow of electrically charged water droplets in air

Water droplet growth in air, influenced by vapor diffusion and electrical charging, has significant implications for indoor air quality, cloud formation, and aerosol dynamics. Here, this study presents a comprehensive theoretical model that describes the growth dynamics of electrically charged water droplets under external electric fields, incorporating diffusion, electrostatic, and dielectrophoretic forces to enhance understanding and practical applications in air dehumidification and environmental control. A theoretical model was established to analyze the growth dynamics of the charged water droplets. The approach extended the thermodynamic framework of the Modified Kelvin-Thomson equation by integrating electrostatic and dielectrophoretic effects, enabling a comprehensive evaluation of vapor concentration near the surface of charged droplets. A sensitivity analysis was performed to assess the roles of droplet size, electric field intensity, surface charge, and vapor concentration on condensation rates. The study progressed beyond the classical diffusion-limited growth of neutral droplets, addressing the behavior of charged droplets in electrohydrodynamic environments. The model highlighted the significance of dielectrophoretic drift flux for dipolar vapor molecules, especially in micron-sized droplets ranging from 10 to 100 µm. Findings demonstrated that, for smaller droplets subjected to elevated electrical charge, average growth rates varied from 0.3 to 1.6 µm/s if the air relative humidity increased from 50 to 100 %. Analytical results are corroborated by numerical simulations, which exhibited strong concordance, thereby validating the proposed theoretical approach. This research introduced an innovative and scalable analytical methodology for electric field-enhanced droplet growth, offering valuable insights into the advancement of energy-efficient air dehumidification, water desalination, and atmospheric water harvesting technologies.

42 ENGINEERING↗

A study on the spectral models for waves in finite water depth

From an extension of the Wallops Spectrum (Huang et al., 1981) for the deep water waves, spectral models for waves in finite water depths are developed. Stokes wave expansions are found to offer a good approximation for intermediate water depth. The spectral function in this case is controlled by three parameters: the significant slope, the nondimensional depth, and the peak frequency. It is pointed out that solitary and cnoidal wave models must be used for the shallow water waves. The controlling parameters now reduce to the Urell number and the peak frequency. Even though the resulting spectral models place special emphasis on the energy-containing range of the spectrum, they are not limited to this range and they are not limited to any particular sea state. They are seen as offering a possible explanation of the variations in the special slope observed by previous investigators.

Huang, N. E.↗

Rough-Water Tests of Models of the Vosper and Plum Planing Boats

Models of two types of high-speed surface craft were tested in Langley tank no. 1 to obtain rough-water data for an evaluation by the David Taylor .Model Basin of the relative merits of the designs. Time-history records were obtained of trim, rise, and normal acceleration at two points in the hulls for various speeds and two sizes of waves.

Chambliss, Derrill B.↗

The influence of assimilating leaf area index in a land surface model on global water fluxes and storages

Vegetation plays a fundamental role not only in theenergy and carbon cycles but also in the global water balanceby controlling surface evapotranspiration (ET). Thus, accu-rately estimating vegetation-related variables has the poten-tial to improve our understanding and estimation of the dy-namic interactions between the water, energy, and carbon cy-cles. This study aims to assess the extent to which a land sur-face model (LSM) can be optimized through the assimilationof leaf area index (LAI) observations at the global scale. Twoobserving system simulation experiments (OSSEs) are per-formed to evaluate the efficiency of assimilating LAI into anLSM through an ensemble Kalman filter (EnKF) to estimateLAI, ET, canopy-interception evaporation (CIE), canopy wa-ter storage (CWS), surface soil moisture (SSM), and terres-trial water storage (TWS). Results show that the LAI dataassimilation framework not only effectively reduces errorsin LAI model simulations but also improves all the modeledwater flux and storage variables considered in this study (ET,CIE, CWS, SSM, and TWS), even when the forcing pre-cipitation is strongly positively biased (extremely wet con-ditions). However, it tends to worsen some of the modeledwater-related variables (SSM and TWS) when the forcingprecipitation is affected by a dry bias. This is attributed tothe fact that the amount of water in the LSM is conservative,and the LAI assimilation introduces more vegetation, whichrequires more water than what is available within the soil

Terrestrial Vegetation↗

Numerical modeling of water-vapor transport during pre-storm and COHMEX

Initial conditions are designed for numerical simulation of mesocale processes in the atmosphere using the Limited Area Mesoscale Prediction System (LAMPS) model. These initial conditions represent an idealized baroclinic wave in which the transport of water vapor can be simulated. The constructed atmosphere has two homogeneous air masses, polar front, polar jet stream and a stratosphere. All these simulate the basic structure of the earth's atmosphere. The hydrostatic and geostrophic balances make it possible to evaluate mutually consistent fields of wind and of the height of isobaric surfaces.

Djuric, Dusan↗

Steric Sea Level Rise and Relationships with Model Drift and Water Mass Representation in GFDL CM4 and ESM4

Abstract Density-driven steric seawater changes are a leading-order contributor to global mean sea level rise. However, intermodel differences in the magnitude and spatial patterns of steric sea level rise exist at regional scales and often emerge during the spinup and preindustrial control integrations of climate models. Steric sea level results from an eddy-permitting climate model, GFDL CM4, are compared with a lower-resolution counterpart, GFDL-ESM4. The results from both models are examined through basin-scale heat budgets and watermass analysis, and we compare the patterns of ocean heat uptake, redistribution, and sea level differ in ocean-only [i.e., Ocean Model Intercomparison Project (OMIP)] and coupled climate configurations. After correcting for model drift, both GFDL CM4 and GFDL-ESM4 simulate nearly equivalent ocean heat content change and global sea level rise during the historical period. However, the GFDL CM4 model exhibits as much as a 40% increase in surface ocean heat uptake in the Southern Ocean and subsequent increases in horizontal export to other ocean basins after bias correction. The results suggest regional differences in the processes governing Southern Ocean heat export, such as the formation of Antarctic Intermediate Water (AAIW), Subpolar Mode Water (SPMW), and gyre transport between the two models, and that sea level changes in these models cannot be fully bias-corrected. Since the process-level differences between the two models are evident in the preindustrial control simulations of both models, these results suggest that the control simulations are important for identifying and correcting sea level–related model biases.

Krasting, John P. [a NOAA/OAR/Geophysical Fluid Dy↗

Ice Growth Model for Polar Water Capture Systems

In-situ resource utilization (ISRU) is essential to NASA’s goal of sustainable and cost-effective missions to the Moon and beyond. Water has become a particular source of interest since its discovery in the permanently shadowed regions (PSRs) of the Moon. This water exists as ice bound within the regolith, so one mode of capture is heating to sublimation temperatures and capturing at very low pressure. It then can be stored in ice form and transported out of the PSR and to a sunlit ridge, where processes such as electrolysis can be performed[2]. An understanding of frost growth dynamics under rarefied conditions is necessary for successful water capture and storage due to transient thermal properties of frost. A Diffusion-Limited Aggregation (DLA) approach was taken to analytically model bulk thermal conductivity changes of the growing frost layer under varying wall temperatures and frost layer porosities. The model utilizes well-known correlations for effective thermal conductivity and records the values as the frost layer thickness increases. This thermal conductivity can be applied to a known temperature change and be used to evaluate heat flux through the combined frost layer and tank wall for either a flat plate or cylindrical geometry. An experiment is described that will evaluate this model using one-dimensional frost growth on a horizontal, flat plate under low-pressure. The ice growth will be measured using a millimeter-scale photogrammetry camera system and a load cell measured transient mass growth.

In situ Resource Utilization↗

Ice Growth Model for Polar Water Capture Systems

In-situ resource utilization (ISRU) is essential to NASA’s goal of sustainable and cost-effective missions to the Moon and beyond. Water has become a particular source of interest since its discovery in the permanently shadowed regions (PSRs) of the Moon. This water exists as ice bound within the regolith, so one mode of capture is heating to sublimation temperatures and capturing at very low pressure. It then can be stored in ice form and transported out of the PSR and to a sunlit ridge, where processes such as electrolysis can be performed[2]. An understanding of frost growth dynamics under rarefied conditions is necessary for successful water capture and storage due to transient thermal properties of frost. A Diffusion-Limited Aggregation (DLA) approach was taken to analytically model bulk thermal conductivity changes of the growing frost layer under varying wall temperatures and frost layer porosities. The model utilizes well-known correlations for effective thermal conductivity and records the values as the frost layer thickness increases. This thermal conductivity can be applied to a known temperature change and be used to evaluate heat flux through the combined frost layer and tank wall for either a flat plate or cylindrical geometry. An experiment is described that will evaluate this model using one-dimensional frost growth on a horizontal, flat plate under low-pressure. The ice growth will be measured using a millimeter-scale photogrammetry camera system and a load cell measured transient mass growth.

ice growth↗

Improved Dynamic Modeling of the Cascade Distillation Subsystem and Integration with Models of Other Water Recovery Subsystems

The Cascade Distillation Subsystem (CDS) is a rotary multistage distiller being developed to serve as the primary processor for wastewater recovery during long-duration space missions. The CDS could be integrated with a system similar to the International Space Station (ISS) Water Processor Assembly (WPA) to form a complete Water Recovery System (WRS) for future missions. Independent chemical process simulations with varying levels of detail have previously been developed using Aspen Custom Modeler (ACM) to aid in the analysis of the CDS and several WPA components. The existing CDS simulation could not model behavior during thermal startup and lacked detailed analysis of several key internal processes, including heat transfer between stages. The first part of this paper describes modifications to the ACM model of the CDS that improve its capabilities and the accuracy of its predictions. Notably, the modified version of the model can accurately predict behavior during thermal startup for both NaCl solution and pretreated urine feeds. The model is used to predict how changing operating parameters and design features of the CDS affects its performance, and conclusions from these predictions are discussed. The second part of this paper describes the integration of the modified CDS model and the existing WPA component models into a single WRS model. The integrated model is used to demonstrate the effects that changes to one component can have on the dynamic behavior of the system as a whole.

Perry, Bruce↗

Hydrologic and Agricultural Earth Observations and Modeling for the Water-Food Nexus

In a globalizing and rapidly-developing world, reliable, sustainable access to water and food are inextricably linked to each other and basic human rights. Achieving security and sustainability in both requires recognition of these linkages, as well as continued innovations in both science and policy. We present case studies of how Earth observations are being used in applications at the nexus of water and food security: crop monitoring in support of G20 global market assessments, water stress early warning for USAID, soil moisture monitoring for USDA's Foreign Agricultural Service, and identifying food security vulnerabilities for climate change assessments for the UN and the UK international development agency. These case studies demonstrate that Earth observations are essential for providing the data and scalability to monitor relevant indicators across space and time, as well as understanding agriculture, the hydrological cycle, and the water-food nexus. The described projects follow the guidelines for co-developing useable knowledge for sustainable development policy. We show how working closely with stakeholders is essential for transforming NASA Earth observations into accurate, timely, and relevant information for water-food nexus decision support. We conclude with recommendations for continued efforts in using Earth observations for addressing the water-food nexus and the need to incorporate the role of energy for improved food and water security assessments

Food Security↗

Data and scripts associated with “Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics within Water-Tagging Enabled Hydrologic Models” (v3)

This data package is associated with the publication “Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics within Water-Tagging Enabled Hydrologic Models” submitted to Journal of Advances in Modeling Earth Systems (Butler et al. 2025). This study developed the Sequential Precipitation Input Tagging (SPIT) framework to tag input precipitation and estimate water transit times and hydrologic tracers. SPIT tags all precipitation events at regular intervals over an extended period (monthly tags over seven years) in a hydrologic model from 2016-2022. SPIT is applied at six National Ecological Observatory Network (NEON) sites across the continental United States to calculate transit time distributions (TTD) and derive from these mean transit times (MTT), fractions of young water (Fyw), and hydrologic tracer concentrations in stream water (δ18O) within a water-tagging enabled version of the Weather Research and Forecast (WT-WRF-Hydro) model with national water model (NWM) configurations. We go on to validate WT-WRF-Hydro estimates against Butler et al. (2023), who analyzed the same NEON sites using stable water isotope data to estimate water transit times. This new tracking method provides a detailed picture of water movement and helps improve predictions about water availability in the future. This data package was originally published in January 2025. It was updated May 2025 (v2; new and modified files) and October 2025 (v3; new and modified files). File and folder names were not revised to indicate changes. See the change history section in the readme for more details. This data package contains the data and scripts used to develop the SPIT framework WT-WRF-Hydro (Water Tagging Weather Research and Forecasting Hydrologic) model and is associated with the following GitHub repository: https://github.com/zbutler33/SPIT-Framework. This data package contains five parent folders: (1) “Manipulated_outputs”, (2) “Metadata”, (3) “Observed”, (4) “Outputs”, and (5) “Scripts”. Each of these parent folders contains additional subfolders and files. Please see the FLMD (“v*_Butler_2024_WT_WRF_Hydro_flmd.csv”) for a list of all the files contained in this data package and descriptions for each. See the data dictionary (“v*_Butler_2024_WT_WRF_Hydro_dd.csv”) for definitions and units of all of the tabular (files ending in “.csv” and ".tsv") column headers.

54 ENVIRONMENTAL SCIENCES↗

Evaluating Lunar Water Processing System Model Configurations for Small Scale Oxygen and Hydrogen Production Within JAXA’s ISRU Technology Demonstration Plant

In-Situ Resource Utilization (ISRU) refers to novel methods of extracting and processing local resources for use in life support and propulsion systems, reducing or eliminating the required consumables to be transferred from Earth. Current estimates of water-ice availability embedded in regolith within the Moon’s permanently shadowed regions (PSR’s)range between 1-5% by weight. However, the composition and characteristics of the “wet” regolith is unknown. Alternate ISRU excavation techniques and Concept of Operations (ConOps) must be explored to optimize surface system operations based on these factors. To assess the feasibility of different ISRU subsystem technologies and compare system architecture configurations, an interchangeable system model was generated to incorporate technologies spanning excavation of raw materials to storage of products and determine optimal arrangement of total system processing needs. Total Mass, Volume, and Power (M/V/P) requirements were computed for 168 design iterations of this water processing plant.

ISRU↗

Mars Atmospheric Conversion to Methane and Water: An Engineering Model of the Sabatier Reactor with Characterization of Ru/Al2O3 for Long Duration Use on Mars

The Atmospheric Processing Module (APM) is a Mars In-Situ Resource Utilization (ISRU) technology designed to demonstrate conversion of the Martian atmosphere into methane and water. The Martian atmosphere consists of approximately 95 carbon dioxide (CO2) and residual argon and nitrogen. APM utilizes cryocoolers for CO2 acquisition from a simulated Martian atmosphere and pressure. The captured CO2 is sublimated and pressurized as a feedstock into the Sabatier reactor, which converts CO2 and hydrogen to methane and water. The Sabatier reaction occurs over a packed bed reactor filled with Ru/Al2O3 pellets. The long duration use of the APM system and catalyst was investigated for future scaling and failure limits. Failure of the catalyst was detected by gas chromatography and temperature sensors on the system. Following this, characterization and experimentation with the catalyst was carried out with analysis including x-ray photoelectron spectroscopy and scanning electron microscopy with elemental dispersive spectroscopy. This paper will discuss results of the catalyst performance, the overall APM Sabatier approach, as well as intrinsic catalyst considerations of the Sabatier reactor performance incorporated into a chemical model.

Ru/Al2O3 Catlayst↗

Mars Atmospheric Conversion to Methane and Water: An Engineering Model of the Sabatier Reactor with Characterization of Ru/Al2O3 for Long Duration Use on Mars

The Atmospheric Processing Module (APM) is a Mars In-Situ Resource Utilization (ISRU) technology designed to demonstrate conversion of the Martian atmosphere into methane and water. The Martian atmosphere consists of approximately 95 carbon dioxide (CO2) and residual argon and nitrogen. APM utilizes cryocoolers for CO2 acquisition from a simulated Martian atmosphere and pressure. The captured CO2 is sublimated and pressurized as a feedstock into the Sabatier reactor, which converts CO2 and hydrogen to methane and water. The Sabatier reaction occurs over a packed bed reactor filled with Ru/Al2O3 pellets. The long duration use of the APM system and catalyst was investigated for future scaling and failure limits. Failure of the catalyst was detected by gas chromatography and temperature sensors on the system. Following this, characterization and experimentation with the catalyst was carried out with analysis including x-ray photoelectron spectroscopy and scanning electron microscopy with elemental dispersive spectroscopy. This paper will discuss results of the catalyst performance, the overall APM Sabatier approach, as well as intrinsic catalyst considerations of the Sabatier reactor performance incorporated into a chemical model.

Catlayst↗

Retrieval Assimilation and Modeling of Atmospheric Water Vapor from Ground- and Space-Based GPS Networks: Investigation of the Global and Regional Hydrological Cycles

Uncertainty over the response of the atmospheric hydrological cycle (particularly the distribution of water vapor and cloudiness) to anthropogenic forcing is a primary source of doubt in current estimates of global climate sensitivity, which raises severe difficulties in evaluating its likely societal impact. Fortunately, a variety of advanced techniques and sensors are beginning to shed new light on the atmospheric hydrological cycle. One of the most promising makes use of the sensitivity of the Global Positioning System (GPS) to the thermodynamic state, and in particular the water vapor content, of the atmosphere through which the radio signals propagate. Our strategy to derive the maximum benefit for hydrological studies from the rapidly increasing GPS data stream will proceed in three stages: (1) systematically analyze and archive quality-controlled retrievals using state-of-the-art techniques; (2) employ both currently available and innovative assimilation procedures to incorporate these determinations into advanced regional and global atmospheric models and assess their effects; and (3) apply the results to investigate selected scientific issues of relevance to regional and global hydrological studies. An archive of GPS-based estimation of total zenith delay (TZD) data and water vapor where applicable has been established with expanded automated quality control. The accuracy of the GPS estimates is being monitored; the investigation of systematic errors is ongoing using comparisons with water vapor radiometers. Meteorological packages have been implemented. The accuracy and utilization of the TZD estimates has been improved by implementing a troposphere gradient model. GPS-based gradients have been validated as real atmospheric moisture gradients, establishing a link between the estimated gradients and the passage of weather fronts. We have developed a generalized ray tracing inversion scheme that can be used to analyze occultation data acquired from space- or land-based receivers. The National Center for Atmospheric Research mesoscale model (version MM5) has been adapted for Southern California, and assimilation studies are underway. Additional information is contained in the original.

Dickey, Jean O.↗

Hydraulic model of the proposed Water Recovery and Management system for Space Station Freedom

A model of the Water Recovery and Management (WRM) system utilizing SINDA '85/FLUINT to determine its hydraulic operation characteristics, and to verify the design flow and pressure drop parameters is presented. The FLUINT analysis package is employed in the model to determine the flow and pressure characteristics when each of the different loop components is operational and contributing to the overall flow pattern. The water is driven in each loop by storage tanks pressurized with cabin air, and is routed through the system to the desired destination.

Martin, Charles E.↗