Geology topics

Collin Cronkite-Ratcliff

Publications and source records attributed to Collin Cronkite-Ratcliff.

17 recordsLinked to original sources

USGS2026

Map depicting locations susceptible to landslide hazards triggered by prolonged intense rainfall, Utuado Municipio, Puerto Rico

Introduction Landslides commonly occur in Puerto Rico during or soon after rainstorms with prolonged intense rainfall. Rainfall-triggered landslides present significant hazards to the built environment and human safety (for example, Jibson, 1986; Larsen and Torres Sanchez, 1992; Bessette-Kirton and others, 2019a). These hazards were illustrated during September 2017 (Hughes and others, 2019) when Hurricane María triggered more than 70,000 landslides across Puerto Rico (fig. 1), causing loss of life and widespread destruction (figs. 2–4). In Utuado Municipio, about 18,000 landslides were observed after Hurricane María (Hughes and others, 2019). Most intense rainfall-triggered landslides in Puerto Rico occur in soil overlying bedrock and travel downslope from where they initiate (for example, Jibson, 1986; Bessette-Kirton and others, 2019a, 2020). Hazards to human life and infrastructure can differ substantially between where landslides initiate and where they travel. At landslide initiation locations, the ground breaks up (fails) as it moves downslope, removing support for buildings, roadways, and other structures located upon the landslides (fig. 3A, B). This ground failure often causes structures to collapse and suffer severe damage or complete destruction, rendering building occupants at extreme risk. Roadways and other vital infrastructure, such as water, power, and communication lines, are often severed. During intense rainfall events, landslide initiation and movement downslope can occur in seconds to hours. Downslope from where they initiate, landslides in Puerto Rico often move very rapidly (faster than a person can walk or run) and can impact and destroy or fill structures with mud and debris (fig. 4) as well as bury roadways (fig. 3A, C). Moving landslides present extreme hazards to human safety; some fatalities during Hurricane María resulted from mud and debris that flowed through windows and doors of a home and buried occupants. Many landslides in Puerto Rico become fast-moving liquefied masses (debris flows), which are especially common in channels where they can quickly travel kilometers downstream. Multiple debris flows may occur in a channel during a single rainstorm (some channels experienced more than 50 debris flows during Hurricane María; Bessette-Kirton and others [2020] ). This hazard map separately depicts locations and the relative likelihood of where landslides may initiate, where they may move downslope, and where channelized debris flows may travel during or soon after intense rainfall like that during Hurricane María. An estimated average of 399 millimeters of rainfall fell across Utuado during September 19–21, 2017 (Ramos-Scharrón and Arima, 2019). Lower rainfall amounts, durations, and intensities also trigger landsliding in Puerto Rico, although landslides and debris flows become more numerous as rainfall intensities, durations, and cumulative amounts increase. The map does not show potential landslide locations in the karst terrain of northern Utuado (Bawiec, 1999) because Hurricane María-induced landslides were very sparse in this region (Hughes and others, 2019; Baxstrom and others, 2021a), even though rainfall amounts were similar to those in other parts of Utuado. Based on data from Hughes and others (2019), landslides were about 10 times more likely to occur outside of the karst terrane than within it, and our preliminary analyses indicated relatively low susceptibility to rainfall-induced landslide hazards within the karst. Landslide-prone soils appear to be poorly developed on the very steep slopes present in the karst region, where weathering by dissolution appears to dominate.

Puerto Rico, Utuado Municipio↗

USGS2026

Map depicting locations susceptible to landslide hazards triggered by prolonged intense rainfall, Naranjito Municipio, Puerto Rico

Introduction Landslides commonly occur in Puerto Rico during or soon after rainstorms with prolonged intense rainfall. Rainfall-triggered landslides present significant hazards to the built environment and human safety (for example, Jibson, 1986; Larsen and Torres Sanchez, 1992; Bessette-Kirton and others, 2019a). These hazards were illustrated during September 2017 (Hughes and others, 2019), when Hurricane María triggered more than 70,000 landslides across Puerto Rico (fig. 1), causing loss of life and widespread destruction (figs. 2–4). In Naranjito Municipio, about 2,000 landslides were observed after Hurricane María (Hughes and others, 2019). Most intense-rainfall-triggered landslides in Puerto Rico occur in soil overlying bedrock and travel downslope from where they initiated (for example, Jibson, 1986; Bessette-Kirton and others, 2019a; 2020). Hazards to human life and infrastructure can differ substantially between where landslides initiate and where they travel. At landslide initiation locations, the ground breaks up (fails) as it moves downslope, removing support for buildings, roadways, and other structures located upon the landslides (figs. 3B, 4A, B). This ground failure often causes structures to collapse and suffer severe damage or complete destruction, rendering building occupants at extreme risk. Roadways and other vital infrastructure, such as water, power, and communication lines are often severed. During intense rainfall events, landslide initiation and movement downslope can occur in seconds to hours. Downslope from where they initiate, landslides in Puerto Rico often move, or runout, very rapidly (faster than a person can walk or run) and can impact and destroy or fill structures with mud and debris (figs. 3A, 4A, C) as well as bury roadways (fig. 4A). Moving landslides present extreme hazards to human safety; some fatalities during Hurricane María resulted from mud and debris that flowed through windows and doors of a home and buried occupants. Many landslides in Puerto Rico become fast-moving debris flows, which are especially common in channels where they can quickly travel kilometers downstream. Multiple debris flows may occur in a channel during a single rainstorm (some channels experienced more than 50 debris flows during Hurricane María; Bessette-Kirton and others, 2020). This map separately depicts locations and the relative likelihood of where landslides may initiate, where they may move downslope, and where channelized debris flows may travel during or soon after intense rainfall like that during Hurricane María. An estimated average of 529 millimeters of rainfall fell across Naranjito during September 19–21, 2017 (Ramos-Scharrón and Arima, 2019). Lower rainfall amounts, durations, and intensities also trigger landsliding in Puerto Rico, although landslides and debris flows become more numerous as rainfall intensities, durations, and cumulative amounts increase.

Naranjito Municipio, Puerto Rico↗

USGS2026

Map depicting locations susceptible to landslide hazards triggered by prolonged intense rainfall, Lares Municipio, Puerto Rico

Introduction Landslides commonly occur in Puerto Rico during or soon after rainstorms with prolonged intense rainfall. Rainfall-triggered landslides present significant hazards to the built environment and human safety (for example, Jibson, 1986; Larsen and Torres Sanchez, 1992; Bessette-Kirton and others, 2019a). These hazards were illustrated during September 2017 (Hughes and others, 2019), when Hurricane María triggered more than 70,000 landslides across Puerto Rico (fig. 1), causing loss of life and widespread destruction (figs. 2 and 3). In Lares Municipio, about 3,500 landslides were observed after Hurricane María (Hughes and others, 2019). Most intense-rainfall-triggered landslides in Puerto Rico occur in soil overlying bedrock and travel downslope from where they initiated (for example, Jibson, 1986; Bessette-Kirton and others, 2019a; 2020). Hazards to human life and infrastructure can differ substantially between where landslides initiate and where they travel. At landslide initiation locations, the ground breaks up (fails) as it moves downslope, removing support for buildings, roadways, and other structures located upon the landslides (figs. 2, 3A, B). This ground failure often causes structures to collapse and suffer severe damage or complete destruction, rendering building occupants at extreme risk. Roadways and other vital infrastructure, such as water, power, and communication lines are often severed. During intense rainfall events, landslide initiation and movement downslope can occur in seconds to hours. Downslope from where they initiate, landslides in Puerto Rico often move, or runout, very rapidly (faster than a person can walk or run) and can impact and destroy or fill structures with mud and debris (figs. 3A, C) as well as bury roadways (fig. 3A). Moving landslides present extreme hazards to human safety; some fatalities during Hurricane María resulted from mud and debris that flowed through windows and doors of a home and buried occupants. Many landslides in Puerto Rico become fast-moving debris flows, which are especially common in channels where they can quickly travel kilometers downstream. Multiple debris flows may occur in a channel during a single rainstorm (some channels experienced more than 50 debris flows during Hurricane María; Bessette-Kirton and others, 2020). This map separately depicts locations and the relative likelihood of where landslides may initiate, where they may move downslope, and where channelized debris flows may travel during or soon after intense rainfall like that during Hurricane María. An estimated average of 256 millimeters of rainfall fell across Lares during September 19–21, 2017 (Ramos-Scharrón and Arima, 2019). Lower rainfall amounts, durations, and intensities also trigger landsliding in Puerto Rico, although landslides and debris flows become more numerous as rainfall intensities, durations, and cumulative amounts increase. The map does not show potential landslide locations in the karst terrain of northern Lares (Bawiec, 1999) because Hurricane María-induced landslides were very sparse in this region (Hughes and others, 2019; Baxstrom and others, 2021a), even though rainfall amounts were similar to those in other parts of Lares. Based on data from Hughes and others (2019), landslides were about ten times more likely to occur outside of the karst terrane than within it, and our preliminary analyses indicate relatively low susceptibility to rainfall-induced landslide hazards within the karst. Landslide-prone soils appear to be poorly developed on the very steep slopes present in the karst region, where weathering by dissolution appears to dominate.

Lares Municipio, Puerto Rico↗

USGS2026

Impacts of transient critical zone evolution on landslide susceptibility and hazard Across the Utuado batholith, Puerto Rico

Landscapes in humid climates often experience rapid chemical and mechanical weathering that can change groundwater fluxes, drainage pathways, and frictional strength via alterations in subsurface mineral composition and matrix porosity. These changes to hillslope critical zone structure and strength should control landslide susceptibility, size, and failure style. Here we test the impact of differential weathering on landslide failure processes by exploiting a natural experiment along the dioritic Utuado batholith in Puerto Rico's Cordillera Central, where a sharp weathering gradient follows an upstream-propagating knickzone into an uplifted shoreline platform that was affected by Hurricane Maria in 2017. Through a combination of landslide mapping, field geophysical and geotechnical surveys, topographic analysis, calibrated stream profile inversion, 3D back-analysis of hillslope strength, and debris-flow inundation assessments, we show that differential weathering induces changes to critical zone structure and consequently landslide susceptibility and hazard. Our mapping reveals that the hurricane-induced landslides preferentially cluster along less weathered hillslopes despite a marked increase in frictional strength. Jointly inverted seismic refraction and electrical resistivity profiles show that the frictionally weak, heavily weathered hillslopes are highly porous and dry, which we posit acts to stabilize slopes through limiting deeper hydrologic connectivity that can produce shallow water tables with destabilizing lateral seepage forces during storms. Debris-flow inundation mapping and analysis reveals that major contributors to debris-flow growth, channel steepness and landslide coalescence, scale linearly with hillslope friction angle. This leads to higher-mobility debris flows along knickzone reaches, which disproportionately affects communities at the base of the plateau.

Puerto Rico↗

USGS2026

Quantitative mineral resource assessment of lithium pegmatite deposits in the northern Appalachian orogen, USA

Lithium demand is projected to increase more than 48 times by 2040 due to electric vehicle production and other energy storage needs. Most lithium production is outside of the USA, thereby increasing supply chain vulnerability. The combined end use importance and heightened supply risk of lithium make this lightest metallic element a critical commodity to the USA. To mitigate this supply risk, the US Geological Survey is actively assessing lithium deposits in the USA. Herein, we detail an assessment for lithium-mineralized pegmatites in the US northern Appalachian Mountains. Permissive tracts were generated by cross-referencing tectonic and geologic maps and mineral occurrence data with mappable criteria derived from generalized and region-specific lithium pegmatite ore deposit models; tracts were then ranked as having high, medium, or low permissibility. Available geophysical and geochemical data were found to be of minimal utility for this deposit type at the scale of the assessment. The number of undiscovered deposits were estimated and integrated into probabilistic simulations, which included an expanded and updated global grade and tonnage model of pegmatite-hosted lithium ore. The estimated total amount of undiscovered resources for the northern Appalachian Orogen has a median value of 1,410,000 metric tons of Li 2 O when considering moderate correlation across sub-regions. At a confidence level of 90%, a resource of at least 90,000 metric tons of Li 2 O remains undiscovered, and at a 10% confidence level, a resource of as much as 7,380,000 metric tons Li 2 O remains undiscovered. After applying an up-to-date economic filter to convert median contained lithium to recoverable material, a correlated total of 900,000 metric tons of Li 2 O may be economically extractable, equating to enough Li 2 O to provide the current annual US lithium supply deficit (presently obtained through net imports) for 127 years at 2025 rates of apparent consumption. This period of provision will inevitably shorten with projected increasing consumption rates, emphasizing that further research could be completed to better delineate regions of high lithium resource potential and support exploration and domestic production.

Connecticut, Delaware, Maine, Massachusetts, New H↗

USGS2026

Open-source gravity reduction workflows for geothermal resource assessment

Potential-field geophysical data such as gravity can enhance understanding of geothermal resources at all stages of the resource life cycle, including assessment, exploration, development, and monitoring, and at multiple scales, from the reservoir scale to regional scale. However, to make gravity data useful for geothermal resource characterization, several processing steps are required to isolate the effects of density variations in the Earth’s crust to enable the identification of structural features associated with geothermal resources. Although this process is well-established, standard computational implementations for processing gravity data that are FAIR (Findable, Accessible, Interoperable, and Reproduceable) are still lacking. This paper details ongoing efforts at the U.S. Geological Survey (USGS) to develop a standard set of open-source Python tools for gravity data reduction that align with the FAIR principles. This workflow makes use of existing open-source tools for geophysical data processing with the goal of maximizing opportunities for rapid improvements, interoperability, and adaptability to other types of geophysical data.

Conference Paper↗

USGS2025

Topographic controls on landslide mobility: Modeling hurricane-induced landslide runout and debris-flow inundation in Puerto Rico

In 2017, Hurricane Maria triggered more than 70 000 landslides in Puerto Rico. After initiation, these predominantly shallow landslides were mobilized to varying extents – some landslides only traveled partway downslope, whereas others reached drainage channels and were mobilized into long-traveled debris flows that could severely impact roads and infrastructure. Thus, forecasting potential landslide runout and inundation zones is critical for estimating landslide and debris-flow hazards. Here we conduct an in-depth topographic analysis of landslide-affected areas from nine study areas and apply a linked modeling technique to estimate locations susceptible to varying degrees of landslide runout in the Lares, Utuado, and Naranjito municipalities. We find that the longest runout lengths are observed on high-relief escarpments, although highly mobile long-runout debris flows also occurred in lower-relief dissected uplands. These topographic differences indicate that landslides that are initiated under similar conditions and possess equal potential to be mobilized as debris flows may not travel the same distances or affect the same areal extent. Our modeling approach allows the local topography to automatically control the implementation of two runout methods: (1) H/L runout zones are assigned directly downslope of landslide source zones, and (2) debris-flow inundation zones are estimated in the presence of a channel network. Debris-flow volumes are calculated as a function of area-integrated growth factors, estimated as a function of the upstream areas susceptible to shallow landslides. Applying our empirical modeling scheme over an area of 560 km 2 , our results highlight the efficacy of our methods for the assessment of the potential for landslide runout and debris-flow inundation over diverse terrains with varied susceptibility.

Puerto Rico↗

USGS2025

Grfin Tools—User guide and methods for modeling landslide runout and debris-flow growth and inundation

The software package, Grfin Tools, can estimate potential runout from landslides or inundation from geophysical mass flows such as debris flows, lahars from volcanoes, and rock avalanches within a digital elevation model (DEM). Grfin is an acronym of gr owth + f low + in undation. The tools within this package apply simple, well-tested, empirical models of runout that are computationally efficient and require minimal parameters. These tools can be used individually (for example, to estimate debris-flow inundation) or in combination to represent a more complete series of linked processes, from landslide source areas, to unchannelized transport, to channelized flows. Grfin Tools can rapidly assess potential runout and inundation over large areas and the results are readily visualized in a geographic information system. Tools for assessing areas affected by runout and flow inundation include a height-to-length ( H / L ) ratio, angle-of-reach approach for estimating open-slope, unchannelized landslide runout, and volume-area scaling relations for assessing flow inundation in channels. Potential landslide areas that constitute the sources of runout or inundation can be delineated with topographic features, such as slope and (or) curvature, derived by the software package, or by employing potential sources derived from other landslide susceptibility models. Grfin Tools also has the capability to assess inundation from flows that grow volumetrically downstream. This is a vital feature, as larger flows commonly result in longer runout and larger inundation. The software uses empirically derived growth factors applied over upslope contributing source areas or upstream channel lengths to integrate the effects of various growth processes, such as channel entrainment, streambank failures, adjacent landslides, and hillslope erosion. Inundation follows a drainage network defined with a separate tool that uses topographic curvature to identify channel initiation locations. This document includes information on using Grfin Tools, the basis and methods underlying the tools and models, detailed descriptions of the software input and output files, and tips for handling special conditions such as roads and large water bodies. Multiple detailed examples illustrating different applications are also presented. Grfin Tools relies on the freely available TauDEM software package (Tarboton, 2005). The Grfin Tools software release is available from Cronkite-Ratcliff and others (2025).

Techniques and Methods↗

USGS2023

Using integrated growth to delineate debris-flow inundation

Debris-flow volume is fundamental to mobility, yet many debris flows change volume as they travel. Growth can occur through diverse processes such as channel-bed entrainment, bank failures, aggregation of landslides, and coalescence of multiple flows. Integrating growth, either over upslope area or stream length, combines the effects of these growth processes and requires specification of only the growth zone extent and a growth factor. To delineate potential debris-flow inundation, we implement integrated growth factors and simple volume-area relations in a new USGS software package, Grfin Tools. We present two examples of forecasting debris-flow inundation – one using an area growth factor in Puerto Rico and another using a channel-length growth factor in Oregon, USA. The use of growth zones and growth factors enables scenario-based hazard assessments for geomorphic settings with debris-flow growth.

Conference Paper↗

USGS2023

Near surface sediments introduce low frequency noise into gravity models

3D geologic modeling and mapping often relies on gravity modeling to identify key geologic structures, such as basin depth, fault offset, or fault dip. Such gravity models generally assume either homogeneous or spatially uncorrelated densities within modeled rock bodies and overlying sediments, with average densities typically derived from surface and drill-hole sampling. The noise contributed to the gravity anomaly by these density assumptions is zero in the homogeneous case and typically <200 μGal in the uncorrelated case. Rock bodies and sediments, however, show both a range of densities and spatial correlation of these densities, in both surface and drill-hole samples, and this correlation causes an increase in power in the low frequency content of the resulting gravity anomaly. Spatial correlation of densities can be modeled as a Gaussian random field (GRF), with the random field parameters derived from drill-hole and geologic map data. Data from alluvial fan sediments in southern Nevada indicate correlation lengths of up to 300 m in the vertical dimension and kilometers in the horizontal dimension. The resulting GRF density models show that the noise contributed to the measured gravity anomaly is of low frequency and can be several mGal in amplitude, contradicting the common attribution of lower frequencies to deeper sources. This low-frequency noise increases in power with an increase in sediment thickness. Its presence increases the ambiguity of interpretations of subsurface geologic body shape, such as basin analyses that attempt to quantify concealed basement fault depths, offsets, and dip angles. In the southwestern United States, where basin analyses are important for natural resource applications, such ambiguity increases the uncertainty of subsequent process modeling.

Applied Computing and Geosciences↗

USGS2022

Comparing root cohesion estimates from three models at a shallow landslide in the Oregon Coast Range

Although accurate root cohesion model estimates are essential to quantify the effect of vegetation roots on shallow slope stability, few means exist to independently validate such model outputs. One validation approach for cohesion estimates is back-calculation of apparent root cohesion at a landslide site with well-documented failure conditions. The catchment named CB1, near Coos Bay, Oregon, USA, which experienced a shallow landslide in 1996, is a prime locality for cohesion model validation, as an abundance of data and observations from the site generated broad insights related to hillslope hydrology and slope stability. However, previously published root cohesion values at CB1 used the Wu and Waldron model (WWM), which assumes simultaneous root failure and therefore likely overestimates root cohesion. Reassessing published cohesion estimates from this site is warranted, as more recently developed models include the fiber bundle model (FBM), which simulates progressive failure with load redistribution, and the root bundle model-Weibull (RBMw), which accounts for differential strain loading. We applied the WWM, FBM, and RBMw at CB1 using post-failure root data from five vegetation species. At CB1, the FBM and RBMw predict values that are less than 30% of the WWM-estimated values. All three models show that root cohesion has substantial spatial heterogeneity. Most parts of the landslide scarp have little root cohesion, with areas of high cohesion concentrated near plant roots. These findings underscore the importance of using physically realistic models and considering lateral and vertical spatial heterogeneity of root cohesion in shallow landslide initiation and provide a necessary step towards independently assessing root cohesion model validity.

Oregon↗

USGS2018

GSFLOW-GRASS v1.0.0: GIS-enabled hydrologic modeling of coupled groundwater–surface-water systems

The importance of water moving between the atmosphere and aquifers has led to efforts to develop and maintain coupled models of surface water and groundwater. However, developing inputs to these models is usually time-consuming and requires extensive knowledge of software engineering, often prohibiting their use by many researchers and water managers, thus reducing these models' potential to promote science-driven decision-making in an era of global change and increasing water resource stress. In response to this need, we have developed GSFLOW–GRASS, a bundled set of open-source tools that develops inputs for, executes, and graphically displays the results of GSFLOW, the U.S. Geological Survey's coupled groundwater and surface-water flow model. In order to create a robust tool that can be widely implemented over diverse hydro(geo)logic settings, we built a series of GRASS GIS extensions that automatically discretizes a topological surface-water flow network that is linked with an underlying gridded groundwater domain. As inputs, GSFLOW–GRASS requires at a minimum a digital elevation model, a precipitation and temperature record, and estimates of channel parameters and hydraulic conductivity. We demonstrate the broad applicability of the toolbox by successfully testing it in environments with varying degrees of drainage integration, landscape relief, and grid resolution, as well as the presence of irregular coastal boundaries. These examples also show how GSFLOW–GRASS can be implemented to examine the role of groundwater–surface-water interactions in a diverse range of water resource and land management applications.

Geoscientific Model Development↗

USGS2018

Responses of unimpaired flows, storage, and managed flows to scenarios of climate change in the San Francisco Bay-Delta watershed

Projections of meteorology downscaled from global climate model runs were used to drive a model of unimpaired hydrology of the Sacramento/San Joaquin watershed, which in turn drove models of operational responses and managed flows. Twenty daily climate change scenarios for water years 1980–2099 were evaluated with the goal of producing inflow boundary conditions for a watershed sediment model and for a hydrodynamical model of the San Francisco Bay-Delta estuary. The resulting time series of meteorology, snowpack, unimpaired flow, reservoir storage, and managed flow were analyzed for century-scale trends. In the Sacramento basin, which dominates Bay-Delta inflows, all 20 scenarios portrayed warming trends (with a mean of 4.1 °C) and most had precipitation increases (with a mean increase of 9%). Sacramento basin snowpack water equivalent declined sharply (by 89%), which was associated with a major shift toward earlier unimpaired runoff timing (33% more flow arriving prior to 1 April). Sacramento basin reservoirs showed large declines in end-of-September storage. Water-year averaged outflows increased for most scenarios for both unimpaired and impaired flows, and frequency of extremely high daily unimpaired and impaired flows increased (increases of 175% and 170%, respectively). Managed Delta inflows were projected to experience large increases in the wet season and declines in the dry season. Changes in management strategy and infrastructure can mitigate some of these changes, though to what degree is uncertain.

California↗

USGS2018

Modeling managed flows in the Sacramento/San Joaquin watershed, California, under scenarios of future change for CASCaDE2

Projections of managed flows from the Sacramento River/San Joaquin River watershed, California, into the San Francisco Bay and Sacramento-San Joaquin Delta under scenarios of future climate change are needed for evaluations of potential impacts on water supply and estuarine ecosystems. A new, multiple-model approach for achieving this is described. First, downscaled global climate model outputs are used to drive an existing Variable Infiltration Capacity/Variable Infiltration Capacity Routing (VIC/RVIC) model of Sacramento/San Joaquin hydrology, resulting in projections of daily, unimpaired flows throughout the watershed. A management model, Computational Assessments of Scenarios of Change for the Delta Ecosystem phase 2 (CASCaDE2) modified CalSim (C2-CalSim), uses these projections as inputs and produces monthly estimates of reservoir and other infrastructure operations and resulting downstream managed flows. A historical resampling algorithm, CASCaDE2 resampling algorithm (CRESPI), also uses the projected daily unimpaired flows, along with historical managed flows, to estimate the daily variability in managed flows throughout the watershed. The monthly and daily managed-flow estimates are combined in a way that preserves the multi-decadal variability and century-scale trends produced by the C2-CalSim model and the day-to-day variability produced by the CRESPI algorithm. The performance of the new modeling approach is evaluated at major inflows to the Bay-Delta estuary using multiple metrics and found to be satisfactory for the purposes of future scenario evaluation.

California↗

USGS2018

A time-lapse gravity survey of the Coso geothermal field, China Lake Naval Air Weapons Station, California

We have conducted a gravity survey of the Coso geothermal field to continue the time-lapse gravity study of the area initiated in 1991. In this report, we outline a method of processing the gravity data that minimizes the random errors and instrument bias introduced into the data by the Scintrex CG-5 relative gravimeters that were used. After processing, the standard deviation of the data was estimated to be ±13 microGals. These data reveal that the negative gravity anomaly over the Coso geothermal field, centered on gravity station CER1, is continuing to increase in magnitude over time. Preliminary modeling indicates that water-table drawdown at the location of CER1 is between 65 and 326 meters over the last two decades. We note, however, that several assumptions on which the model results depend, such as constant elevation and free-water level over the study period, still require verification.

California↗

USGS2016

Relations between rainfall–runoff-induced erosion and aeolian deposition at archaeological sites in a semi-arid dam-controlled river corridor

Process dynamics in fluvial-based dryland environments are highly complex with fluvial, aeolian, and alluvial processes all contributing to landscape change. When anthropogenic activities such as dam-building affect fluvial processes, the complexity in local response can be further increased by flood- and sediment-limiting flows. Understanding these complexities is key to predicting landscape behavior in drylands and has important scientific and management implications, including for studies related to paleoclimatology, landscape ecology evolution, and archaeological site context and preservation. Here we use multi-temporal LiDAR surveys, local weather data, and geomorphological observations to identify trends in site change throughout the 446-km-long semi-arid Colorado River corridor in Grand Canyon, Arizona, USA, where archaeological site degradation related to the effects of upstream dam operation is a concern. Using several site case studies, we show the range of landscape responses that might be expected from concomitant occurrence of dam-controlled fluvial sand bar deposition, aeolian sand transport, and rainfall-induced erosion. Empirical rainfall-erosion threshold analyses coupled with a numerical rainfall–runoff–soil erosion model indicate that infiltration-excess overland flow and gullying govern large-scale (centimeter- to decimeter-scale) landscape changes, but that aeolian deposition can in some cases mitigate gully erosion. Whereas threshold analyses identify the normalized rainfall intensity (defined as the ratio of rainfall intensity to hydraulic conductivity) as the primary factor governing hydrologic-driven erosion, assessment of false positives and false negatives in the dataset highlight topographic slope as the next most important parameter governing site response. Analysis of 4+ years of high resolution (four-minute) weather data and 75+ years of low resolution (daily) climate records indicates that dryland erosion is dependent on short-term, storm-driven rainfall intensity rather than cumulative rainfall, and that erosion can occur outside of wet seasons and even wet years. These results can apply to other similar semi-arid landscapes where process complexity may not be fully understood.

Arizona↗

USGS2014

Stochastic modeling of a lava-flow aquifer system

This report describes preliminary three-dimensional geostatistical modeling of a lava-flow aquifer system using a multiple-point geostatistical model. The purpose of this study is to provide a proof-of-concept for this modeling approach. An example of the method is demonstrated using a subset of borehole geologic data and aquifer test data from a portion of the Calico Hills Formation, a lava-flow aquifer system that partially underlies Pahute Mesa, Nevada. Groundwater movement in this aquifer system is assumed to be controlled by the spatial distribution of two geologic units—rhyolite lava flows and zeolitized tuffs. The configuration of subsurface lava flows and tuffs is largely unknown because of limited data. The spatial configuration of the lava flows and tuffs is modeled by using a multiple-point geostatistical simulation algorithm that generates a large number of alternative realizations, each honoring the available geologic data and drawn from a geologic conceptual model of the lava-flow aquifer system as represented by a training image. In order to demonstrate how results from the geostatistical model could be analyzed in terms of available hydrologic data, a numerical simulation of part of an aquifer test was applied to the realizations of the geostatistical model.

Nevada↗