The terrestrial water cycle intensity (WCI) is a widely used tool to quantify the impact of climate change on the distribution of global water resources. In this study, a satellite-based WCI was tested by comparing the parameter-elevation regressions on independent slopes model (PRISM) precipitation estimates with those of the Global Precipitation Measurement (GPM) satellite mission across the contiguous United States (CONUS), based on an existing Köppen–Geiger climate classification for the CONUS. Both precipitation products were not statistically different across all climate classes. Consequently, satellite-based WCI changes between two multiannual periods (2001 to 2009 and 2010 to 2019) were calculated at a 0.1-degree spatial resolution using the GPM and a validated global evapotranspiration dataset. This study showed that: (1) The water cycle is speeding up in many parts of the CONUS, particularly the West, driven by recent increases in both precipitation and evapotranspiration through much of the region. (2) The El Niño-Southern Oscillation (ENSO) may be influencing the WCI of the CONUS by driving precipitation in the west, southeast, and parts of the north, and dryness in the northeast regions. The hydrological impacts of these results cannot be generalized. However, flood and drought risks, water availability and quality issues remain key primary concerns.

In the United States (US), salt marshes are especially vulnerable to the effects of projected sea level rise, increased storm frequency, and climatic changes. Sentinel-2 data offer the opportunity to observe the land surface at high spatial resolutions (10 m). The Sentinel-2 data, encompassing Cumberland Island National Seashore, Fort Pulaski National Monument, and Canaveral National Seashore, were analyzed to identify temporal changes in salt marsh presence from 2016 to 2020. ENVI-derived unsupervised and supervised classification algorithms were applied to determine the most appropriate procedure to measure distant areas of salt marsh increases and decreases. The Normalized Difference Vegetation Index (NDVI) was applied to describe the varied vegetation biomass spatially. The results from this approach indicate that the ENVI-derived maximum likelihood classification provides a statistical distribution and calculation of the probability (>90%) that the given pixels represented both water and salt marsh environments. The salt marshes captured by the maximum likelihood classification indicated an overall decrease in salt marsh area presence. The NDVI results displayed how the varied vegetation biomass was analogous to the occurrence of salt marsh changes. Areas representing the lowest NDVI values (−0.1 to 0.1) corresponded to bare soil areas where a salt marsh decrease was detected.

Changes in sea level along the coastal southeastern United States (U.S.) influence the dynamic coastal response. In particular, the Southeast Coastal Network (SECN) of the National Park Service (NPS) has exhibited evidence of fluctuations in sea level which caused coastal erosion. Airborne LiDAR acquired from NOAA for Fort Matanzas National Monument, Fort Pulaski National Monument, Charles Pinckney National Historic Site, and Cape Lookout National Seashore were analyzed to identify changes in both elevation and the spatial volume of unconsolidated sedimentary material in the coastal southeast over time. Areas that exhibited an increase (deposited material) or decrease (eroded material) in elevation were mapped across the study area from 2006 to 2018. Results indicate a quasi-cyclic process where unconsolidated sediment distribution and the morphodynamic equilibrium changes with time. The coastal zones are steadily oscillating between the process of erosion and deposition affecting the coastal geomorphological dynamic. The use of LiDAR for evaluating coastal sustainability and resiliency due to this environmental phenomenon is clear.

Thermal shifts have accelerated ice-wedge degradation and reorganized polygonal trough networks along the Utqiaġvik, Alaska coastline. Thus, quantifying their structural variability and hydrologic connectivity across spatial scales remains challenging. This study applies high-resolution remote sensing and terrain analysis to evaluate hydrologic controls on ice-wedge polygon morphology. Using a 0.5 m lidar-derived DEM, polygon boundaries were manually digitized and compared with Thiessen (Voronoi) tessellations to quantify structural divergence, boundary misalignment, and differences in area. Hydrologic influences on polygon development were assessed through compound terrain analysis, drainage network extraction, and surface flow modeling. Spatial intersection analyses reveal geometric discrepancies underscoring the limitations of automated polygon proxies in permafrost terrain. Modeled flow paths exhibit spatial congruence with mapped trough networks, indicating that surface hydrology plays a role in trough evolution. Hydrologic and morphometric parameters demonstrate high runoff potential associated with low-relief topography. Elevated Topographic Wetness Index (TWI > 12 ) and Stream Power Index (SPI > 60) values delineate zones of saturation and flow accumulation that frequently coincide with trough depressions. Despite high predicted runoff, minimal gradients produce ponded flow regimes that promote wetland formation. This integrative framework enhances detection and interpretation of permafrost terrain features, providing a scalable methodology for monitoring Arctic landscape dynamics.

Arctic coasts are among the most vulnerable landscape on Earth, where periglacial terrain undergoes thermal contraction and expansion through seasonal freeze–thaw cycles. Along the Utqiaġvik (formerly Barrow), Alaska coastline, shifting thermal regimes have accelerated ice wedge degradation, influenced by the evolution of polygonal trough networks. However, accurately mapping trough structure, variability, and hydrologic connectivity across spatial scales remains challenging. This study integrates high-resolution remote sensing and terrain modeling to investigate the relationship between surface hydrology and ice wedge polygon morphology. Using a 0.5 m resolution LiDAR-derived digital elevation model (DEM), ice wedge polygons were manually delineated and compared with Thiessen (Voronoi) polygons to evaluate differences in structure, spatial extent, and representation of natural variability. Intersection analyses revealed significant discrepancies in boundary alignment and area estimates between the two approaches. Hydrologic influences on polygon development were assessed through compound terrain analysis, drainage network extraction, and surface flow modeling. Results show strong spatial correspondence between modeled flow paths and mapped trough networks, indicating that surface hydrology plays a key role in ice wedge thaw and trough evolution. Calculated hydrologic and morphometric parameters suggest high runoff potential, driven by flat terrain, permafrost-limited infiltration, dense drainage networks, and short overland flow paths. High TWI (> 12) and SPI (> 60) values mark zones of concentrated surface saturation and flow accumulation, often coinciding with trough depressions. Despite high runoff potential, minimal gradients lead to slow-moving flow and persistent surface ponding, contributing to widespread wetland formation. This integrated approach demonstrates the value of combining high-resolution topographic data with hydrologic modeling to improve detection and interpretation of permafrost terrain features. The framework developed offers a scalable method for monitoring Arctic terrain dynamics and enhances remote sensing applications for assessing permafrost vulnerability.