Delta shoreline structure has long been hypothesized to encode information on the relative influence of fluvial, wave, and tidal processes on delta formation and evolution. We introduce here a novel multiscale characterization of shorelines by defining three process-informed morphological metrics. We show that this characterization yields self-emerging classes of morphologically similar deltas, i.e., delta morphotypes, and also predicts the dominant forcing of each morphotype. Then we show that the dominant forcings inferred from shoreline structure generally align with those estimated via relative sediment fluxes, while positing that misalignments arise from spatiotemporal heterogeneity in deltaic sediment fluxes not captured in their estimates. The proposed framework for shoreline characterization advances our quantitative understanding of how shoreline features reflect delta forcings, and may aid in deciphering paleoclimate from images of ancient deposits and projecting delta morphologic response to changes in sediment fluxes.

Whether the presence of permafrost systematically alters the rate of riverbank erosion is a fundamental geomorphic question with significant importance to infrastructure, water quality, and biogeochemistry of high latitude watersheds. For over four decades this question has remained unanswered due to a lack of data. Using remotely sensed imagery, we addressed this knowledge gap by quantifying riverbank erosion rates across the Arctic and subarctic. To compare these rates to non-permafrost rivers we assembled a global dataset of published riverbank erosion rates. We found that erosion rates in rivers influenced by permafrost are on average six times lower than non-permafrost systems; erosion rate differences increase up to 40 times for the largest rivers. To test alternative hypotheses for the observed erosion rate difference, we examined differences in total water yield and erosional efficiency between these rivers and non-permafrost rivers. Neither of these factors nor differences in river sediment loads provided compelling alternative explanations, leading us to conclude that permafrost limits riverbank erosion rates. This conclusion was supported by field investigations of rates and patterns of erosion along three rivers flowing through discontinuous permafrost in Alaska. Our results show that permafrost limits maximum bank erosion rates on rivers with stream powers greater than 900 W/m-1. On smaller rivers, however, hydrology rather thaw rate may be dominant control on bank erosion. Our findings suggest that Arctic warming and hydrological changes should increase bank erosion rates on large rivers but may reduce rates on rivers with drainage areas less than a few thousand km2.

Permafrost active layer thickness (ALT) is a sensitive indicator of permafrost response to climate change. In recent decades, ALT has increased at sites across the Arctic, concurrent with observed increases in annual minimum streamflow (baseflow). The trends in ALT and baseflow are thought to be linked via: 1) increased soil water storage capacity due to an increased active layer, and 2) enhanced soil water mobility within a more continuous active layer, both of which support higher baseflow in Arctic rivers. One approach to analyzing these changes in ALT and baseflow is to use baseflow recession analysis, which is a classical method in hydrology that relates groundwater storage S to baseflow Q with a power law-like relationship Q = aSb. For the special case of a linear reservoir (b=1.0), the baseflow recession method has been extended to quantify changes in ALT from streamflow measurements alone. We test this approach at sites across the North American Arctic and find that catchments underlain by permafrost behave as nonlinear reservoirs, with scaling exponents b~1.5–3.0, undermining the key assumption of linearity that is commonly applied in this method. Despite this limitation, trends in a provide insight into the relationship between changing ALT and changing Arctic baseflow. Although care should be taken to ensure the theoretical assumptions are met, baseflow recession analysis shows promise as an empirical approach to constrain modeled permafrost change at the river basin scale.

The tandem rise in satellite-based observations and computing power has changed the way we (can) see rivers across the Earth’s surface. Global datasets of river and river network characteristics at unprecedented resolutions are becoming common enough that the sheer amount of available information presents problems itself. Fully exploiting this new knowledge requires linking these geospatial datasets to each other within the context of a river network. In order to cope with this wealth of information, we are developing Veins of the Earth (VotE), a flexible system designed to synthesize knowledge about rivers and their networks into an adaptable and readily-usable form. VotE is not itself a dataset, but rather a database of relationships linking existing datasets that allows for rapid comparison and exports of river networks at arbitrary resolutions. VotE’s underlying river network (and drainage basins) is extracted from MERIT-Hydro. We link within VotE a newly-compiled dam dataset, streamflow gages from the GRDC, and published global river network datasets characterizing river widths, slopes, and intermittency. We highlight VotE’s utility with a demonstration of how vector-based river networks can be exported at any requested resolution, a global comparison of river widths from three independent datasets, and an example of computing watershed characteristics by coupling VotE to Google Earth Engine. Future efforts will focus on including real-time datasets such as SWOT river discharges and ReaLSAT reservoir areas.

Changes in the magnitude and frequency of river flows have potential to alter sediment dynamics and morphology of rivers globally, but the direction of these changes remains uncertain. A lack of data across spatial and temporal scales limits understanding of river flow regimes and how changes in these regimes interact with river bank erosion and floodplain deposition. Linking characteristics of the flow regime to changes in bank erosion and floodplain deposition is necessary to understand how rivers will adjust to changes in hydrology from societal pressures and climatic change, particularly in snowmelt-dominated systems. We present a lidar dataset, intensive field surveys, aerial imagery and hydrologic analysis spanning 60 years, and spatial analysis to quantify bank erosion, lateral accretion, floodplain overbank deposition, and a floodplain fine sediment budget in an 11-km long study segment of the meandering gravel bed East River, Colorado, USA. Stepwise regression analysis of channel morphometry in nine study reaches and snowmelt-dominated annual hydrologic indices in this mountainous system suggest that sinuosity, channel width, recession slope, and flow duration are linked to lateral erosion and accretion. The duration of flow exceeding baseflow and the slope of the annual recession limb explain 59% and 91% of the variability in lateral accretion and erosion, respectively. This strong correlation between the rate of change in river flows, which occurs over days to weeks, and erosion suggests a high sensitivity of sedimentation along rivers in response to a shifting climate in snowmelt-dominated systems, which constitute the majority of rivers above 40° latitude.

This article provides a commentary about the state of integrated, coordinated, open, and networked (ICON) principles in Earth and Planetary Science Processes (EPSP) and discussion on the opportunities and challenges of adopting them. This commentary focuses on the challenges with current inclusive, equitable, and accessible science and highlights how research undertaken in the earth and planetary surface processes community currently benefit from and would be able to grow as a discipline with more directed implementation of ICON principles.

​​​​​​​​​Lakes in the Arctic are important reservoirs of heat with much lower albedo and larger absorption of solar radiation than surrounding tundra vegetation. Under climate warming scenarios, we expect Arctic lakes to further accelerate thawing underlying permafrost. Previous studies of Arctic lakes have focused on ice cover and thickness, the ice decay process, catchment hydrology, lake water balance, and eddy covariance measurements, but little work has been done in the Arctic to model lake heat balance. We applied the LAKE model to simulate water temperatures in three Arctic lakes in Northern Alaska over several years. The LAKE model is a one-dimensional that explicitly solves vertical profiles of water state variables on a grid. We used a combination of meteorological data from local and remote weather stations, as well as data derived from remote sensing, to drive the model. We validated simulated water temperatures with data of observed lake temperatures at several depths. Our validation of the LAKE model completes a necessary step toward modeling changes in Arctic lake ice regimes, lake heat balance, and thermal interactions with permafrost. Our results showed that winter precipitation and lake ice plays an important role in forming water temperatures over the winter period. Our findings suggest that reduction in the lake ice thickness and ice time period could lead to more heat storage by lakes and further warming of the Arctic.

Watersheds serve as natural spatial boundaries whose characteristics are often indicators of the hydrologic processes within them. Watershed characteristics are frequently used as predictors, parameters, or proxies in models of hydrologic and ecologic dynamics. Developments in DEMs over the past decade have resulted in elevation data spanning the globe that allows watershed delineation at arbitrary locations. In tandem, satellite-based observations and large-scale modeling efforts provide many sources of near-global watershed characteristics, e.g. topography, soil types, vegetation, climate, permafrost extent, and many more. However, with growing data availability comes a growing need for tools that can rapidly query and summarize them. We developed River and Basin Profiler (RaBPro), a Python module providing a pipeline to delineate drainage basins for any point on Earth and calculate watershed statistics for practically any geospatial raster dataset. RaBPro makes use of the MERIT-Hydro or HydroBASINS datasets to define watershed polygons, which can be exported in GeoJSON or ESRI shapefile format for further use in GIS software. RaBPro will also generate streamlines and river elevation profiles. Finally, RaBPro calculates statistics over delineated basins using Google Earth Engine (GEE). By taking advantage of GEE’s vast dataset archive and distributed computing system, RaBPro can quickly compute many statistics over even very large basins efficiently and without the need for storing large geo-rasters locally. Additionally, users may upload their own datasets to GEE and create custom statistic functions.

Understanding how thermokarst lakes on arctic river deltas will respond to rapid warming is critical for projecting how carbon storage and fluxes will change in those vulnerable environments. Yet, this understanding is currently limited partly due to the complexity of disentangling significant interannual variability from the longer-term surface water signatures on the landscape, using the summertime window of optical spaceborne observations. Here, we rigorously separate perennial lakes from ephemeral wetlands on 12 arctic deltas and report distinct size distributions and climate trends for the two waterbodies. Namely, we find a lognormal distribution for lakes and a power-law distribution for wetlands, consistent with a simple proportionate growth model and inundated fractal topography, respectively. Furthermore, while no trend with temperature is found for wetlands, a statistically significant decreasing trend of mean lake size with warmer temperatures is found, attributed to colder deltas having deeper and thicker permafrost preserving larger lakes.

A growing number of coastal eco-geomorphologic modeling studies have been conducted to understand coastal marsh evolution under sea level rise (SLR). Although these models quantify marsh topographic change as a function of sedimentation and erosion, their representations of vegetation dynamics that control organic sedimentation differ. How vegetation dynamic schemes and parameter values contribute to simulation outcomes is still not quantified. Additionally, the sensitivity of modeling outcomes on parameter selection in the available formulations has not been rigorously tested to date, especially under the influence of an accelerating SLR. This knowledge gap severely limits modeling accuracy and the estimation of the vulnerability of coastal marshes under SLR. In this paper, we used coastal eco-geomorphologic models with different vegetation dynamic schemes to investigate the eco-geomorphologic feedbacks of coastal marshes and parametric sensitivity under SLR scenarios. We found that marsh accretion rate near the seaward boundary can keep pace with moderate and high rates of SLR, while interior marsh regions are vulnerable to a high rate of SLR. The simulations with different vegetation schemes exhibit diversity in elevation and biomass profiles and parametric sensitivity. We also found that the model parametric sensitivity varies with rates of future SLR. Vegetation-related parameters and sediment diffusivity, which are not well measured or discussed in previous studies, are identified as some of the most critical parameters. Our findings provide insights to appropriately choose modeling presentations of key processes and feedbacks for different coastal marsh landscapes under SLR, which has practical implications for coastal ecosystem management and protection.

Coastal saltwater intrusion (SWI) is one key factor affecting the hydrology, nutrient transport, and biogeochemistry of coastal marsh landscapes. Future climate change, especially intensified sea level rise (SLR), is expected to trigger SWI to encroach coastal freshwater aquifers more intensively. Numerous studies have investigated decadal/century scale SWI under SLR by assuming a static coastal landscape topography. However, coastal marshes are highly dynamic systems in response to SLR, and the impact of coastal marsh evolution on SWI has received very little attention. Thus, this study investigated how coastal marsh evolution affects future SWI with a physically-based coastal hydro-eco-geomorphologic model, ATS (Advanced Terrestrial Simulator). Our synthetic modeling experiments showed that it is very likely that the marsh elevation increases with future SLR, and a depression zone is formed due to the different marsh accretion rates between the ocean boundary and the inland. We found that, compared to the cases without marsh evolution, the marsh accretion may significantly reduce the surface saltwater inflow at the ocean boundary, and the evolved topographic depression zone may prolong the residence time of surface ponding saltwater, which causes distinct subsurface salinity distributions. We also found that the marshland may become more sensitive to the upland groundwater table that controls the freshwater flux to the marshes, compared with the cases without marsh evolution. This study demonstrates the importance of marsh evolution to the freshwater-saltwater interaction under sea level rise and can help improve our predictive understanding of the vulnerability of the coastal freshwater system to sea level rise.

Permafrost underlies approximately one fifth of the global land area and affects ground stability, freshwater runoff, soil chemistry, and surface‑atmosphere gas exchange. The depth of thawed ground overlying permafrost (active layer thickness, ALT) has broadly increased across the Arctic in recent decades, coincident with a period of increased streamflow, especially the lowest flows (baseflow). Mechanistic links between ALT and baseflow have recently been explored using linear reservoir theory, but most watersheds behave as nonlinear reservoirs. We derive theoretical nonlinear relationships between long‑term average saturated soil thickness η (proxy for ALT) and long-term average baseflow. The theory is applied to 38 years of daily streamflow data for the Kuparuk River basin on the North Slope of Alaska. Between 1983–2020, the theory predicts that η increased 0.11±0.17 [2σ] cm a-1, or 4.4±6.6 cm total. The rate of change nearly doubled to 0.20±0.24 cm a-1 between 1990–2020, during which time field measurements from CALM (Circumpolar Active Layer Monitoring) sites in the Kuparuk indicate η increased 0.31±0.22 cm a-1. The predicted rate of change more than doubled again between 2002–2020, mirroring a near doubling of observed ALT rate of change. The inferred increase in η is corroborated by GRACE (Gravity Recovery and Climate Experiment) satellite gravimetry, which indicates that terrestrial water storage increased ~0.80±3.40 cm a-1, ~56% higher than the predicted increase in η. Overall, hydrologic change is accelerating in the Kuparuk River basin, and we provide a theoretical framework for estimating changes in active layer water storage from streamflow measurements alone.