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At least 91 records · Page 5

NASA's Future Active Remote Sensing Missing for Earth Science

Since the beginning of space remote sensing of the earth, there has been a natural progression widening the range of electromagnetic radiation used to sense the earth, and slowly, steadily increasing the spatial, spectral, and radiometric resolution of the measurements. There has also been a somewhat slower trend toward active measurements across the electromagnetic spectrum, motivated in part by increased resolution, but also by the ability to make new measurements. Active microwave instruments have been used to measure ocean topography, to study the land surface. and to study rainfall from space. Future NASA active microwave missions may add detail to the topographical studies, sense soil moisture, and better characterize the cryosphere. Only recently have active optical instruments been flown in space by NASA; however, there are currently several missions in development which will sense the earth with lasers and many more conceptual active optical missions which address the priorities of NASA's earth science program. Missions are under development to investigate the structure of the terrestrial vegetation canopy, to characterize the earth's ice caps, and to study clouds and aerosols. Future NASA missions may measure tropospheric vector winds and make vastly improved measurements of the chemical components of the earth's atmosphere.

Hartley, Jonathan B.↗

Disentangling the Impacts of Microtopography and Shrub Distribution on Snow Depth in a Subarctic Watershed: Toward a Predictive Understanding of Snow Spatial Variability

Snow plays a critical role in carbon cycling, vegetation dynamics, and permafrost hydrology at high latitudes by influencing surface energy exchange. Predicting snow distribution patterns is essential for understanding the evolution of Arctic ecosystems, yet scaling process-level knowledge to landscape predictions remains challenging. Here, we analyze snow depth (2019 and 2022), terrain elevation, and vegetation height from a watershed on the Seward Peninsula, Alaska, to examine how topography and shrubs shape snow redistribution across spatial scales. We find that snow depth is strongly coupled to terrain at scales below ∼60 m but becomes increasingly decoupled at larger scales. The topographic model of snow depth variation, which transforms terrain data to align with these scale-dependent snow patterns, is well correlated with local snow depth variations (linear fit R 2 > 0.5 for 85% of 100-m patches). A machine learning reconstruction of shrub canopy snow trapping reveals a simple exponential relationship between canopy structure and snow accumulation ( R 2 = 0.59), highlighting the combined influence of topography and vegetation on snow distribution. Together, these empirical relationships capture much of the observed snow variability in the watershed ( R 2 = 0.49, root mean square error (RMSE) = 30 cm), though systematic limitations persist in areas of strong scour and at coarser scales where wind-terrain interactions are more complex. These findings provide a framework for more efficient snow depth prediction and offer insights to improve snow-vegetation feedback representation in Earth System Models.

54 ENVIRONMENTAL SCIENCES↗

The Energy Exascale Earth System Model Version 3: 2. Overview of the Coupled System

The Energy Exascale Earth System Model version 3 (E3SMv3) represents the latest advancement in Earth system modeling developed by the U.S. Department of Energy (DOE). Building upon previous versions, E3SMv3 introduces significant updates across its coupled components to enhance capability and improve fidelity. The atmosphere component incorporates advancements in chemistry, aerosol-cloud interactions, convection, and microphysics. The ocean features a new time-stepping scheme and a higher-resolution unstructured mesh with sub-ice-shelf cavities, while the sea ice model integrates advanced snow and ice physics for more realistic cryospheric simulations. The land model introduces prognostic vegetation dynamics and a new sub-grid topographic treatment of solar radiation. A new tri-grid configuration harmonizes the horizontal grids of the land and river components for improved process coupling. It is enabled by a new non-linear remapping between the atmosphere and land. E3SMv3 underwent extensive testing through a comprehensive simulation campaign, including pre-industrial control, idealized CO 2 experiments, and historical simulations spanning 1850–2024. The model demonstrates significant improvements in simulating the evolution of the historical surface temperature, particularly addressing the “pothole cooling” bias in earlier versions. Reduced aerosol-related forcing contributes to more realistic radiative forcing and better alignment with the observational record. Ocean heat content (OHC) and sea ice trends are also improved as a result.

54 ENVIRONMENTAL SCIENCES↗

Laser Altimetry Sampling Strategies over Sea Ice

With the conclusion of the science phase of the Ice, Cloud and land Elevation Satellite (ICESat) mission in late 2009, and the planned launch of ICESat-2 in late 2015, NASA has recently established the IceBridge program to provide continuity between missions. A major goal of IceBridge is to obtain a sea-ice thickness time series via airborne surveys over the Arctic and Southern Oceans. Typically two laser altimeters, the Airborne Topographic Mapper (ATM) and the Land, Vegetation and Ice Sensor (LVIS), are utilized during IceBridge flights. Using laser altimetry simulations of conventional analogue systems such as ICESat, LVIS and ATM, with the multi-beam system proposed for ICESat-2, we investigate differences in measurements gathered at varying spatial resolutions and the impact on sea-ice freeboard. We assess the ability of each system to reproduce the elevation distributions of two seaice models and discuss potential biases in lead detection and sea-surface elevation, arising from variable footprint size and spacing. The conventional systems accurately reproduce mean freeboard over 25km length scales, while ICESat-2 offers considerable improvements over its predecessor ICESat. In particular, its dense along-track sampling of the surface will allow flexibility in the algorithmic approaches taken to optimize the signal-to-noise ratio for accurate and precise freeboard retrieval.

Farrell, Sinead L.↗

ICESat Observations of Topographic Change in the Northern Segment of the 2004 Sumatra-Andaman Islands Earthquake Rupture Zone

The Andaman Islands are located 120 km east of the Sunda trench in the northern quarter of the 1300 km long rupture zone of the 2004 Sumatra-Andaman Islands earthquake inferred from the distribution of aftershocks. Initial field reports indicate that several meters of uplift and up to a meter of submergence occurred on the western and eastern shorelines of the Andaman Islands, respectively, associated with the earthquake (Bilham, 2005). Satellite images also document uplift of western shoreline coral reef platforms above sea level. Body-wave (Ji, 2005; Yamamaka, 2005) and tide-gauge (Ortiz, 2005) slip inversions only resolve coseismic slip in the southern one-third to one-half of the rupture zone. The amount of coseismic slip in the Andaman Islands region is poorly constrained by these inversions. The Ice, Cloud, and land Elevation Satellite (ICESat), a part of the NASA Earth Observing System, is being used to document the spatial pattern of Andaman Islands vertical displacements in order to constrain models of slip distribution in the northern part of the rupture zone. ICESat carries the Geoscience Laser Altimeter System (GLAS) that obtains elevation measurements from 80 m diameter footprints spaced 175 m apart along profiles. For surfaces of low slope, single-footprint absolute elevation and horizontal accuracies of 10 cm and 6 m (1 sigma), respectively, referenced to the ITRF 2002 TOPEX/Poseidon ellipsoid are being obtained. Laser pulse backscatter waveforms enable separation of ground topography and overlying vegetation cover. During each 33-day observing period ICESat acquires three profiles crossing the Andaman Islands. A NNE-SSW oriented track consists of 1600 laser footprints along the western side of North, Middle, and South Andaman Islands and 240 laser footprints across the center of Great Andaman Island. Two NNW-SSE tracks consist of 440 footprints across Middle Andaman Island and 25 footprints across the west side of Sentinel Island. Cloud-free profiles were acquired in the fall of 2003 and 2004. During February-March, 2005 ICESat's precise pointing capability will be used to exactly repeat these three profiles, with a cross-track accuracy of better than 100 m, providing trench- parallel and -perpendicular observations of topographic change of the Andaman Islands that will compliment geodetic field surveys. The observed elevation changes will be compared to models of coseismic deformation associated with the mainshock and large aftershocks in the Andaman Islands region.

Harding, David↗

Faults on Skylab imagery of the Salton Trough area, Southern California

The author has identified the following significant results. Large segments of the major high angle faults in the Salton Trough area are readily identifiable in Skylab images. Along active faults, distinctive topographic features such as scarps and offset drainage, and vegetation differences due to ground water blockage in alluvium are visible. Other fault-controlled features along inactive as well as active faults visible in Skylab photography include straight mountain fronts, linear valleys, and lithologic differences producing contrasting tone, color or texture. A northwestern extension of a fault in the San Andreas set, is postulated by the regional alignment of possible fault-controlled features. The suspected fault is covered by Holocene deposits, principally windblown sand. A northwest trending tonal change in cultivated fields across Mexicali Valley is visible on Skylab photos. Surface evidence for faulting was not observed; however, the linear may be caused by differences in soil conditions along an extension of a segment of the San Jacinto fault zone. No evidence of faulting could be found along linears which appear as possible extensions of the Substation and Victory Pass faults, demonstrating that the interpretation of linears as faults in small scale photography must be corroborated by field investigations.

Merifield, P. M.↗

Applications of ArcticDEM for measuring volcanic dynamics, landslides, retrogressive thaw slumps, snowdrifts, and vegetation heights

Topographical changes are of fundamental interest to a wide range of Arctic science disciplines faced with the need to anticipate, monitor, and respond to the effects of climate change, including geohazard management, glaciology, hydrology, permafrost, and ecology. This study demonstrates several geomorphological, cryospheric, and biophysical applications of ArcticDEM – a large collection of publicly available, time-dependent digital elevation models (DEMs) of the Arctic. Our study illustrates ArcticDEM's applicability across different disciplines and five orders of magnitude of elevation derivatives, including measuring volcanic lava flows, ice cauldrons, post-failure landslides, retrogressive thaw slumps, snowdrifts, and tundra vegetation heights. We quantified surface elevation changes in different geological settings and conditions using the time series of ArcticDEM. Following the 2014–2015 Bárðarbunga eruption in Iceland, ArcticDEM analysis mapped the lava flow field, and revealed the post-eruptive ice flows and ice cauldron dynamics. The total dense-rock equivalent (DRE) volume of lava flows is estimated to be (1431 ± 2) million m 3 . Then, we present the aftermath of a landslide in Kinnikinnick, Alaska, yielding a total landslide volume of (400 ± 8) × 103 m 3 and a total area of 0.025 km 2 . ArcticDEM is further proven useful for studying retrogressive thaw slumps (RTS). The ArcticDEM-mapped RTS profile is validated by ICESat-2 and drone photogrammetry resulting in a standard deviation of 0.5 m. Volume estimates for lake-side and hillslope RTSs range between 40,000 ± 9000 m 3 and 1,160,000 ± 85,000 m 3 , highlighting applicability across a range of RTS magnitudes. A case study for mapping tundra snow demonstrates ArcticDEM's potential for identifying high-accumulation, late-lying snow areas. The approach proves effective in quantifying relative snow accumulation rather than absolute values (standard deviation of 0.25 m, bias of −0.41 m, and a correlation coefficient of 0.69 with snow depth estimated by unmanned aerial systems photogrammetry). Furthermore, ArcticDEM data show its feasibility for estimating tundra vegetation heights with a standard deviation of 0.3 m (no bias) and a correlation up to 0.8 compared to the light detection and ranging (LiDAR). The demonstrated capabilities of ArcticDEM will pave the way for the broad and pan-Arctic use of this new data source for many disciplines, especially when combined with other imagery products. The wide range of signals embedded in ArcticDEM underscores the potential challenges in deciphering signals in regions affected by various geological processes and environmental influences.

Chunli Dai↗

Remote Sensing and GIS data at 1km-grid over Chesapeake Bay used in “He et al. 2024, Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem”

The package contains the data layers used in “He et al. 2024, Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem”. The study aims to use multi-source remote sensing and GIS datasets to investigate the spatial heterogeneity and identify spatial zones with similar environmental characteristics and understand the primary driving factors affecting soil respiration within sub-ecosystems of the coastal ecosystem. We employed unsupervised hierarchical clustering analysis to identify spatial regions with distinct environmental characteristics, then determined the main driving factors using Random Forest regression and SHapley Additive exPlanations (SHAP). Spatial data layers include soil respiration, kernel Normalized Difference Vegetation Index (kNDVI) computed from Harmonized Landsat 8 and Sentinel-2 time series, climate variables from the Daymet dataset, land cover, biodiversity, topographical metrics, soil property, and tidal elevation.

54 ENVIRONMENTAL SCIENCES↗

Remote sensing requirements as suggested by watershed model sensitivity analyses

A continuous simulation watershed model has been used to perform sensitivity analyses that provide guidance in defining remote sensing requirements for the monitoring of watershed features and processes. The results show that out of 26 input parameters having meaningful effects on simulated runoff, 6 appear to be obtainable with existing remote sensing techniques. Of these six parameters, 3 require the measurement of the areal extent of surface features (impervious areas, water bodies, and the extent of forested area), two require the descrimination of land use that can be related to overland flow roughness coefficient or the density of vegetation so as to estimate the magnitude of precipitation interception, and one parameter requires the measurement of distance to get the length over which overland flow typically occurs. Observational goals are also suggested for monitoring such fundamental watershed processes as precipitation, soil moisture, and evapotranspiration. A case study on the Patuxent River in Maryland shows that runoff simulation is improved if recent satellite land use observations are used as model inputs as opposed to less timely topographic map information.

Salomonson, V. V.↗

Fusion of AIRSAR and TM Data for Parameter Classification and Estimation in Dense and Hilly Forests

The expanded remotely sensed data space consisting of coincident radar backscatter and optical reflectance data provides for a more complete description of the Earth surface. This is especially useful where many parameters are needed to describe a certain scene, such as in the presence of dense and complex-structured vegetation or where there is considerable underlying topography. The goal of this paper is to use a combination of radar and optical data to develop a methodology for parameter classification for dense and hilly forests, and further, class-specific parameter estimation. The area to be used in this study is the H. J. Andrews Forest in Oregon, one of the Long-Term Ecological Research (LTER) sites in the US. This area consists of various dense old-growth conifer stands, and contains significant topographic relief. The Andrews forest has been the subject of many ecological studies over several decades, resulting in an abundance of ground measurements. Recently, biomass and leaf-area index (LAI) values for approximately 30 reference stands have also become available which span a large range of those parameters. The remote sensing data types to be used are the C-, L-, and P-band polarimetric radar data from the JPL airborne SAR (AIRSAR), the C-band single-polarization data from the JPL topographic SAR (TOPSAR), and the Thematic Mapper (TM) data from Landsat, all acquired in late April 1998. The total number of useful independent data channels from the AIRSAR is 15 (three frequencies, each with three unique polarizations and amplitude and phase of the like-polarized correlation), from the TOPSAR is 2 (amplitude and phase of the interferometric correlation), and from the TM is 6 (the thermal band is not used). The range pixel spacing of the AIRSAR is 3.3m for C- and L-bands and 6.6m for P-band. The TOPSAR pixel spacing is 10m, and the TM pixel size is 30m. To achieve parameter classification, first a number of parameters are defined which are of interest to ecologists for forest process modeling. These parameters include total biomass, leaf biomass, LAI, and tree height. The remote sensing data from radar and TM are used to formulate a multivariate analysis problem given the ground measurements of the parameters. Each class of each parameter is defined by a probability density function (pdf), the spread of which defines the range of that class. High classification accuracy results from situations in which little overlap occurs between pdfs. Classification results provide the basis for the future work of class-specific parameter estimation using radar and optical data. This work was performed in part by the Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, and in part by the NASA Ames Research Center, Moffett Field, CA, both under contract from the National Aeronautics and Space Administration.

Moghaddam, Mahta↗

Topographical Controls on Hillslope-Scale Hydrology Drive Shrub Distributions on the Seward Peninsula, Alaska

Observations indicate shrubs are expanding across the Arctic tundra, mainly on hillslopes and primarily in response to climate warming. However, the impact topography exerts on hydrology, nutrient dynamics, and plant growth can make untangling the mechanisms behind shrub expansion difficult. We examined the role topography plays in determining shrub expansion by applying a coupled transect version of a mechanistic ecosystem model (ecosys) in a tundra hillslope site in the Seward Peninsula, Alaska. Modeled biomass of the dominant plant functional types agreed well with field measurements (R 2 = 0.89) and accurately represented shrub expansion over the past 30 years inferred from satellite observations. In the well-drained crest position, canopy water potential and plant nitrogen (N) uptake was modeled to be low from plant and microbial water stress. Intermediate soil water content in the mid-slope position enhanced mineralization and plant N uptake, increasing shrub biomass. The deciduous shrub growth in the mid-slope position was further enhanced by symbiotic N 2 fixation primed by increased root carbon allocation. The gentle slope in the poorly drained lower-slope position resulted in saturated soil conditions that reduced soil O 2 concentrations, leading to lower root O 2 uptake and lower nutrient uptake and plant biomass. Additionally, a simulation that removed topographical interconnectivity between grid cells resulted in (1) a 28% underestimate of mean shrub biomass and (2) over or underestimated shrub productivity at the various hillslope positions. Our results indicate that land models need to account for hillslope-scale coupled surface and subsurface hydrology to accurately predict current plant distributions and future trajectories in Arctic ecosystems.

54 ENVIRONMENTAL SCIENCES↗

The Relationship of Forest Fires Detected by MODIS and SRTM Derived Topographic Features in Central Siberia

Fires are a common occurrence in the Siberian boreal forest. The MOD14 Thermal anomalies product of the Terra MODIS Moderate Resolution Spectroradiometer) product set is designed to detect thermal anomalies (i.e. hotspots or fires) on the Earth's surface. Recent field studies showed a dependence of fire occurrence on topography. In this study MODIS thermal anomaly data and SRTM topography data were merged and analyzed to evaluate if forest fires are more likely to occur at certain combinations of elevation, slope and aspect. Using the satellite data over a large area can lead to better understanding how topography and forest fires are related. The study area covers a 2.5 Million krn(exp 2) portion of the Central Siberian southern taiga from 72 deg to 110 deg East and from 50 deg to 60 deg North. About 57% of the study area is forested and 80% of the forest grows between 200 and 1000 m. Forests with pine (Pinus sylvestris), larch (Larix sibirica, L. gmelinii), Siberian pine (Pinus sibirica), spruce (Picea obovata.) and fir (Abies sibirica) cover most of the landscape. Deciduous stands with birch (Betula pendula, B. pubescens) and aspen (Populus tremula) cover the areas of lower elevation in this region. The climate of this area is distinctly continental with long, cold winters and short hot summers. The tree line in this part of the world is around 1500 m in elevation with alpine tundra, snow and ice fields and rock outcrops extending up to over 3800 m. A 500 m resolution landcover map was developed using 2001 MODIS MOD13 Normalized Vegetation Index (NDVI) and Middle Infrared (MIR) products for seven 16-day periods. The classification accuracy was over 87%. The SRTM version 2 data, which is distributed in 1 degree by 1 degree tiles were mosaiced using the ENVI software. In this study, only those MODIS pixels were used that were flagged as "nominal or high confidence fire" by the MODIS fire product team. Using MODIS data from the years 2000 to 2005 along with the improved Shuttle Radar Topographic Mission (SRTM) version 2 data at 100 m resolution, the distribution of hot spots was examined by elevation, slope and aspect as well as by forest type. The results show that more forest area burns at lower elevations but a larger percentage of the available forest area burns at higher elevations. This is probably because steep slopes occur at higher elevations. Fires are only more common on slopes with a southern exposure if the slope is steeper than 15 degrees. The next step in this study will be to monitor areas where the risk of fire is high (steep slopes with a southern exposure) and to refine this method by incorporating anthropogenic features for more accurate fire disturbance monitoring.

Ranson, Jon K.↗

ATLAS Beam Steering Mechanism Lessons Learned

This paper describes the design, testing, and lessons learned during the development of the Advanced Topographic Laser Altimeter System (ATLAS) Beam Steering Mechanism (BSM). The BSM is a 2 degree-of-freedom tip-tilt mechanism for the purpose of pointing a flat mirror to tightly control the co-alignment of the transmitted laser and the receiver telescope of the ATLAS instrument. The high resolution needs of the mission resulted in sub-arcsecond pointing and knowledge requirements, which have been met. Development of the methodology to verify performance required significant effort. The BSM will fly as part of the Ice, Cloud, and Elevation Satellite II Mission (ICESat II), which is scheduled to be launched in 2017. The ICESat II primary mission is to map the earth's surface topography for the determination of seasonal changes of ice sheet thickness and vegetation canopy thickness to establish long-term trends.

controls↗

Beam Steering Mechanism (BSM) Lessons Learned

This paper describes the design, testing, and lessons learned during the development of the Advanced Topographic Laser Altimeter System (ATLAS) Beam Steering Mechanism (BSM). The BSM is a 2 degree-of-freedom tip-tilt mechanism for the purpose of pointing a flat mirror to tightly control the co-alignment of the transmitted laser and the receiver telescope of the ATLAS instrument. High resolution needs of the mission resulted in sub-arcsecond pointing and knowledge requirements, which have been met. Development of methodology to verify performance was a significant effortadvancement. The BSM will fly as part of the Ice, Cloud, and Elevation Satellite 2 Mission (ICESat 2), which is scheduled to be launched in 2017. The ICESat 2 primary mission is to map the earths surface topography for the determination of seasonal changes of ice sheet thickness as well as vegetation canopy thickness.

Mechanism↗

ATLAS Beam Steering Mechanism (BSM) Lessons Learned

This paper describes the design, testing, and lessons learned during the development of the Advanced Topographic Laser Altimeter System (ATLAS) Beam Steering Mechanism (BSM). The BSM is a 2 degree-of-freedom tip-tilt mechanism for the purpose of pointing a flat mirror to tightly control the co-alignment of the transmitted laser and the receiver telescope of the ATLAS instrument. The high resolution needs of the mission resulted in sub-arcsecond pointing and knowledge requirements, which have been met. Development of the methodology to verify performance required significant effort. The BSM will fly as part of the Ice, Cloud, and Elevation Satellite II Mission (ICESat II), which is scheduled to be launched in 2017. The ICESat II primary mission is to map the Earth's surface topography for the determination of seasonal changes of ice sheet thickness and vegetation canopy thickness to establish long-term trends.

Blumenstock, Kenneth A.↗

The ICESat-2 Mission: Land, Ocean, and Inland Water Data Products for Middle and Low Latitude Science and Applications

NASA’s Ice, Cloud, and Land Elevation Satellite (ICESat-2) is a polar orbiting mission, launched on September 15, 2018, with over two years of nearly continuous observations. The sole instrument onboard is the Advanced Topographic Laser Altimeter System (ATLAS), a micropulse, high repetition rate, six-beam, 532 nm Lidar with photon-counting technology. Although designed primarily for detecting height changes in ice caps and sea ice in the high latitudes, it continuously observes all terrain in its track including middle and low latitude regions as well, during approximately 15 orbits per day. The official ICESat-2 products include not only cryosphere data but also global high resolution parameters associated with tree canopies, land surface, oceans, and over 1.5 million inland water bodies consisting of lakes, rivers and coastal waters. This presentation provides an overview and the status of the ICESat-2 mission including: i) a summary of the salient technological features and orbit design, ii) the official ICESat-2 science data products for ice, vegetation canopy, ocean sea level, and inland water including several examples in the middle and low latitudes, iii) a list of NASA sponsored software tools for globally browsing the two year archive and for processing both the raw data and the official ICESat-2 geophysical data products, and iv) avenues for interested users to connect with the ICESat-2 Applications Program for answering questions and assistance in possibly using ICESat-2 data in your particular science or application. The overall goal is to facilitate the use of ICESat-2 data not only for science investigations but also for improved decision support applications with societal benefit. Additional ICESat-2 information, documentation and data products are publicly available at https://nsidc.org/data/icesat-2

ICESat-2↗

Potential of Radar Imaging and Sounding Methods in Mapping Heavily Eroded Impact Craters: Mapping Some Structural Elements of the Hico Crater, TX

Shuttle Radar Topography Mission (SRTM) and Ground Penetrating Radar (GPR) data collected over an area north of the town of Hico, central Texas, have been used to map disturbances in the surface topography and subsurface stratigraphy. The Radar topography results confirm the presence of multiple rings suggestive of an impact crater. Correlation between the orbital SRTM and on-the-ground GPR field data are affected by different biases related to variations in terrain and vegetation cover. Nevertheless, the correspondence of the two data sets supports the earlier conclusions that a complex, multiple ring impact structure is reflected in the topography of this area. The SRTM data reveal three previously unrecognized rings; with the outermost ring some 5-6 km in diameter. The crater appears to be significantly larger than the size (2.5 km diameter) previously inferred on the basis of aerial images. In addition, the GPR data suggest the presence of subsurface faulting that spatially coincides with the two inner rings of the crater. This suggests that the topographic rings are structurally controlled by faulting.

Heggy, E.↗

Reducing impacts of artificial ponding in modeling salt marshes using a conductivity-formulated subgrid model

The landforms of salt marsh systems are rather complex, with meandering channel networks cutting through low-lying, extensive marsh platforms. Some small-scale topographic details are critical to flooding and draining processes but cannot be reflected in the Digital Elevation Model (DEM) due to limited measurement resolution and vegetation bias. Numerical models need a grid with high enough resolution to capture the small-scale connectivity to correctly model the small-scale flow processes, making the model computationally unaffordable. Here, in this study, we derived a subgrid model, which couples two flow components, one is the regular subgrid model for simulating the subgrid-resolved flows, and the other is a conductivity-formulated porous flow model for modeling small-scale gut flows unresolved at the subgrid level. The model validation was performed using an idealized case with a narrow slot that was unresolved in the coupled flow model. Model results were compared with a slot-resolved regular subgrid model where only surface flows are solved and suggested that, with a proper model parameterization, the coupled flow model is capable of reproducing flooding and draining processes similar to the slot-resolved subgrid model of surface flow. The model was applied to simulating flooding and draining processes in a meso-tidal salt marsh. The model results demonstrate that the coupled subgrid model can be used to reduce the impacts of artificial ponding that usually occur in numerical simulations of salt marshes with numerous narrow gullies and creeks.

54 ENVIRONMENTAL SCIENCES↗