Conference Papers

The National Hydrography Dataset (NHD) managed by the U.S. Geological Survey (USGS) is being updated with higher-quality feature representations through efforts that derive hydrography from 3DEP HR elevation datasets. Deriving hydrography from elevation through traditional flow routing and interactive methods is a complex, time-consuming process that must be tailored for different hydrogeomorphic

Large geospatial datasets must often be generalized for analysis and display at reduced scales. Automated methods including artificial intelligence and deep learning are being applied to this problem, but the results are often analyzed on the basis of limited and subjective measures. To better support automation, a project is underway to develop a robust Python toolkit for computing objective metr

The origin of Au-bearing, low sulfide quartz veins in the Pogo and Tibbs Creek regions of interior Alaska remain enigmatic. Intrusion-related Au and mesozonal orogenic vein models have both been proposed (Thompson and Newberry, 2000; Rhys et al., 2003; Goldfarb et al., 2022; Dilworth et al., 2007). To date, studies of igneous geochronology and metamorphic timing have shown that gold veins formed b

Fish modeling in complex environments is critical for understanding drivers of population dynamics in aquatic systems. This paper proposes a Bayesian network method for modeling fish survival and growth over multiple connected rivers. Traditional fish survival models capture the effect of multiple environmental drivers (e.g., stream temperature, stream flow) by adding different variables, which in

A range of hydrologic responses can be observed in steep, recently burned terrain, which makes predicting the spatial distribution of large debris flows challenging. Studies from rainfall-induced landslides in unburned areas show evidence of hydroclimatic tuning of landslide triggering, such that the spatial distribution of events is best predicted by the observed rainfall anomaly relative to clim

Debris flow erosion into bedrock helps to set the pace of mountain denudation, but there are few empirical observations of this process. We studied the effects of debris flows on bedrock erosion using Structure-From-Motion photogrammetry and multiple real-time monitoring measurements. We found that the distribution of bedrock erosion across the channel cross-section could be generalized as an expo

We evaluated the ability of three debris-flow runout models (RAMMS, FLO2D and D-Claw) to predict the number of damaged buildings in simulations of the 9 January 2019 Montecito, California, debris-flow event. Observations of building damage after the event were combined with OpenStreetMap building footprints to construct a database of all potentially impacted buildings. At the estimated event volum

In the semi-arid regions of the western United States, postfire debris flows are typically runoff generated. The U.S. Geological Survey has been studying the mechanisms of postfire debris-flow initiation for multiple decades to generate operational models for forecasting the timing, location, and magnitude of postfire debris flows. Here we discuss challenges and progress for extending operational

No abstract available.

Accurate maps of built structures around stream channels, such as dams, culverts, and bridges, are vital in monitoring infrastructure, risk management, and hydrologic modeling. Hydrologic modeling is essential for research and decisionmaking related to infrastructure and development planning, emergency management, ecology, and developing hydrographic data. Technological advances in remote sensing

Sudden-onset hazards like earthquakes often induce cascading secondary hazards (e.g., landslides, liquefaction, debris flows, etc.) and subsequent impacts (e.g., building and infrastructure damage) that cause catastrophic human and economic losses. Rapid and accurate estimates of these hazards and impacts are critical for timely and effective post-disaster responses. Emerging remote sensing techni

This research aims to conduct a geosemantic comparison of landforms classified in the Summit and Ridge feature classes in the Geographic Names Information System (GNIS). The comparison is based on a 2D shape analysis of manually delineated polygons produced by USGS staff to correspond to 33,304 Summit and 8,006 Ridge features. Five shape measures were chosen for this specific geomorphometry-based