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Karen B. Gran

Publications and source records attributed to Karen B. Gran.

6 recordsLinked to original sources
USGS2025

Near-channel erosion as a driver of watershed-scale sediment and phosphorus loading in a forested sub-watershed of Lake of the Woods

The Little Fork River, a forested watershed in northern Minnesota, United States, is a disproportionate contributor of sediment and phosphorus to Rainy River and Lake of the Woods. Sources of sediment and sediment-bound phosphorus to the Little Fork were investigated using complementary lines of evidence in the form of geochemical sediment fingerprinting and a stream-corridor sediment budget that included harvested forest and ravines, in addition to upland forest and agriculture, roads, and streambanks. Near-channel ravine and streambank sources comprised 95–100 % of streambed sediment and 79–100 % of suspended sediment at the river mouth, while tributaries had up to 50% of suspended sediment from upland sources including harvested forest, agriculture, and roads. Repeat suspended-sediment sampling at eight sites showed more source variability among sites than across events. Ravine erosion was the watershed’s largest contributor to downstream sediment and sediment-bound phosphorus loading, while streambed sediment had a larger streambank source. Near-channel erosion also contributed phosphorus, though with less labile and redox-sensitive forms than forest and agricultural soils. In contrast to observations from agricultural settings, suspended-sediment phosphorus concentrations were elevated above some, but not all sources. The effects of watershed size, glacial history, land cover, and variable temperature and precipitation on runoff generation and peak streamflow are important considerations for mitigating near-channel loss of sediment and phosphorus in the Little Fork. These results suggest that management of sediment and phosphorus export from the Little Fork could incorporate context for location in the watershed, geomorphic setting, and runoff characteristics.

Minnesota↗
USGS2025

Factors influencing landslide occurrence in low-relief formerly glaciated landscapes: Landslide inventory and susceptibility analysis in Minnesota, USA

In landscapes recently impacted by continental glaciation, landslides may occur where topographic relief has been generated by the drainage of glacial lakes and ensuing post-glacial fluvial network development into unconsolidated glacially derived sediments and exhumed bedrock. To investigate linkages among environmental variables, post-glacial landscape development, and landslides, we created a landslide inventory of nearly 10,000 landslides in five regions of the formerly glaciated low-relief state of Minnesota, USA. Multivariate logistic regression indicates the importance of slope angle, lithology, and the development of stream valleys to landslide distribution. Areas underlain by fine-grained glaciolacustrine and nearshore deposits that are incised by streams are particularly prone to shallow (<1-2 m depth) landslides. Landslides also occur in a wide range of glacial and fluvial deposits, and as rockfall in layered Paleozoic sedimentary rocks in central and southern Minnesota and Precambrian igneous and sedimentary rocks in northeastern Minnesota. Although no more than 1-2% of the studied regions are susceptible to landslides, they can pose risk to life and safety, damage infrastructure, and impact water quality. The combination of recently generated low-relief steep slopes, extensive unconsolidated sediments, and layered sedimentary bedrock make this formerly glaciated landscape more susceptible to landslides than current national-scale models indicate.

Minnesota↗
USGS2022

Regional-scale mapping of landscape response to extreme precipitation using repeat lidar and object-based image analysis

Extreme precipitation events may cause flooding, slope failure, erosion, deposition, and damage to infrastructure over a regional scale, but the impacts of these events are often difficult to fully characterize. Regional-scale landscape change occurred during an extreme rain event in June 2012 in northeastern Minnesota. Landscape change was documented by 8,000 km 2 of airborne lidar data collected before and after the event. Following improved alignment of the lidar point data and reducing error using insight from analysis of extensive stable areas, elevation differences were classified into map objects representing geomorphic change in relation to process and landscape position using object-based image analysis. This remote mapping compares favorably to field and imagery-based mapping and provides the basis for volumetric sediment budgeting. Elevation differences in these objects indicate that 4.5 × 10 6 ± 1.0 × 10 6 m 3 of sediment was eroded in the study area. Of this, 2.5 × 10 6 ± 3.3 × 10 5 m 3 was deposited in deposits on hillslopes and valley floors, and 2.0 × 10 6 ± 4.6 × 10 5 m 3 were removed from watersheds and exported to the Saint Louis River Estuary and Lake Superior. Multivariate logistic regression analysis emphasized that topographic slope and presence of glaciolacustrine clay lithology are the primary control on landslide occurrence, and landslides occur most frequently on slopes within tens of meters of stream channels. These results provide the basis to anticipate the impacts of similar future storm events. Because precipitation events are forecast to continue to increase in frequency and intensity owing to climate change, characterizing and anticipating their effects may support hazard planning.

Minnesota↗
USGS2022

Landslides in Minnesota

Landslides in Minnesota have caused loss of life, damaged infrastructure, and negatively affected Minnesota’s natural resources. Landslides increase the amount of sediment contributed to lakes and rivers, with negative consequences for water quality and aquatic habitats. Recent mapping reveals that landslide susceptible areas within Minnesota primarily occur on steep slopes adjacent to rivers, lakes, and transportation corridors. Local variation in landslide susceptibility is related to the underlying geology and glacial history.

Minnesota↗
USGS2022

Implementing landscape connectivity with topographic filtering model: A simulation of suspended sediment delivery in an agricultural watershed

The widespread availability of high-fidelity topography combined with advances in geospatial analysis offer the opportunity to reimagine approaches to the difficult problem of predicting sediment delivery from watersheds. Here we present a model that uses high-resolution topography to filter sediment sources to quantify sediment delivery to the watershed outlet. It is a reduced-complexity, top-down model that defines transfer functions—topographic filters—between spatially distributed sediment sources and spatially integrated sediment delivery. The goal of the model is to forecast changes in watershed suspended sediment delivery in response to spatially distributed changes in sediment source magnitude or delivery, whether a result of watershed drivers or intentional management actions. Such an application requires the context of a watershed model that accounts for all sediment sources, enforces sediment mass balance throughout the spatial domain, and accommodates sediment storage and delivery over time. The model is developed for a HUC-8 watershed with a flat upland dominated by corn-soybean agriculture and deeply incised valleys near the watershed outlet with large sediment contributions from near-channel sources. Topofilter computes delivery and storage of field-derived sediment according to its spatial and structural connectivity to the stream channel network; subsequently, delivery of both field- and near-channel-derived sediment along with floodplain storage are computed in the stream channel network to the watershed outlet. The model outputs provide a spatially rich representation of sediment delivery and storage on field and along the stream that is consistent with available independent information on sediment accumulations and fluxes. Rather than a single best-calibrated solution, Topofilter uses the Generalized Likelihood Uncertainty Estimate (GLUE) approach to develop many possible solutions with sediment delivery rates expressed as probability distributions across the watershed. The ensemble of simulation outputs provides a useful basis for estimating uncertainty in sediment delivery and the effectiveness of different landscape management allocation across a watershed.

Minnesota↗