Geology topics

Jonathan D. Stock

Publications and source records attributed to Jonathan D. Stock.

At least 19 recordsLinked to original sources

USGS2026

Post-fire soil hydrologic response and recovery in northern California (USA)

Background Wildfires abruptly change landscapes by altering soil properties and vegetation cover. These changes are thought to reduce soil infiltration capacity, making landscapes susceptible to runoff and erosion. However, post-fire soil response is complex and likely varies across locations and time. Aims Here, we aim to understand regional post-fire soil response and recovery by tracking changes across different northern California (USA) lithology and vegetation types. Methods We conducted repeat in situ soil infiltration tests for 3 years post-fire at 31 burned and 10 unburned sites spanning the 2021 Dixie, 2020 LNU Lightning Complex, 2020 Walbridge and 2020 Glass fires. Key results Our two main findings are: (1) burned chaparral soils have increased hydraulic conductivity compared with unburned sites, and (2) infiltration rates return to pre-fire conditions within 3 years across most lithologies and vegetations. Conclusions Recovery might be generalizable by vegetation and lithology but differ regionally, making it important to identify meaningful hydrologic response units (HRUs). Multi-year studies with paired burned and unburned measurements can constrain the recovery timeline and provide information missed by observations solely of burned soils. Implications Understanding where, and for how long, soil remains susceptible to runoff and erosion can help prioritize areas and time periods most in need of mitigation.

California↗

USGS2025

Mapping bedrock outcrops in the Sierra Nevada Mountains (California, USA) using machine learning

Accurate, high-resolution maps of bedrock outcrops can be valuable for applications such as models of land–atmosphere interactions, mineral assessments, ecosystem mapping, and hazard mapping. The increasing availability of high-resolution imagery can be coupled with machine learning techniques to improve regional bedrock outcrop maps. In the United States, the existing 30 m U.S. Geological Survey (USGS) National Land Cover Database (NLCD) tends to misestimate extents of barren land, which includes bedrock outcrops. This impacts many calculations beyond bedrock mapping, including soil carbon storage, hydrologic modeling, and erosion susceptibility. Here, we tested if a machine learning (ML) model could more accurately map exposed bedrock than NLCD across the entire Sierra Nevada Mountains (California, USA). The ML model was trained to identify pixels that are likely bedrock from 0.6 m imagery from the National Agriculture Imagery Program (NAIP). First, we labeled exposed bedrock at twenty sites covering more than 83 km 2 (0.13%) of the Sierra Nevada region. These labels were then used to train and test the model, which gave 83% precision and 78% recall, with a 90% overall accuracy of correctly predicting bedrock. We used the trained model to map bedrock outcrops across the entire Sierra Nevada region and compared the ML map with the NLCD map. At the twenty labeled sites, we found the NLCD barren land class, even though it includes more than just bedrock outcrops, accounted for only 41% and 40% of mapped bedrock from our labels and ML predictions, respectively. This substantial difference illustrates that ML bedrock models can have a role in improving land-cover maps, like NLCD, for a range of science applications.

California↗

USGS2022

Multi-stage soil-hydraulic recovery and limited ravel accumulations following the 2017 Nuns and Tubbs wildfires in Northern California

Wildfire can impact soil-hydraulic properties by reducing saturated hydraulic conductivity and sorptivity, making recently burned landscapes prone to debris flows and flash floods. The post-fire hazard window can range from years to decades. In Northern California, where wildfire frequency is steadily increasing, the impact and soil-hydraulic recovery from wildfires is unknown. Following the October 2017 Nuns and Tubbs fires in the Northern Bay Area of California, we established 41 monitoring sites for repeat tension-disc infiltrometer measurements of field-saturated hydraulic conductivity ( K fs ) over 3.5 years. Our site arrays, which encompass grasslands, chaparral, and oak and conifer forests across a range in lithology, show a marked decrease in K fs following the wildfires and a swift partial recovery following the initial post-fire rainy season. Our time series reveals a complex path to soil-hydraulic recovery marked by distinct seasonal stages. Analysis of changing K fs , sorptivity, and infiltration model residuals collectively suggests that these stages are related to transitions between soil-hydraulic processes like structural soil sealing from rainsplash, thermal cracking of bare soil, and vegetation regrowth. While soil infiltration rates were strongly impacted by the 2017 fires, dry ravel estimates are an order of magnitude less for similar slopes than the 2009 Station fire in the San Gabriel mountains of Southern California, suggesting that limited ravel flux may insufficiently load channels for debris flows that initiate from within-channel failure. Our analysis suggests that burned landscapes in the Northern Bay Area of California may experience rapid soil-hydraulic recovery and limited pathways toward post-fire debris flow initiation.

California↗

USGS2022

Waters divided: A history of alluvial fan research and a view of its future

Flows exiting confined valleys tend to deposit sediment in fan-shaped landforms. Where deposition is wholly or largely by the tractive forces of flowing water, these landforms are called alluvial fans. They are the product of the progressive division of water and sediment downfan, from slopes that may exceed 0.10 to distal slopes that may be below 0.01. Channel depths also tend to decline, from values that approach one to several meters at steep fanheads, to a few decimeters at distal fan margins. The result is a radiating, depositional ramp where confined or unconfined flows transport sediment from source basins to bounding streams, subsiding basins, or stable platforms. Where streams or subsiding basins consume the sediment supply from the source basin, the fan may approach a steady form whose extent and distal slope are set by stream location or subsidence rate. Where boundary conditions do not remove sediment, the fan may prograde out to long distances and low slopes (<0.01). Theoretical and experimental work over the past several decades support the notion that alluvial fan long-profiles become steeper as sediment supply increases or transport capacity decreases, and increasingly concave upward as the rate of bed material deposition decreases downfan. Grainsize distributions of alluvial fans seem to span the range observed in alluvial rivers, with no processes that uniquely identify them, apart from the distributary pattern of deposition. Bed sand cover tends to increase downfan in arid-region fans, with an absence of systematic downfan fining of coarser grain sizes. Surficial mapping and geochronology have demonstrated that fan deposition varies greatly through time, arguably from climate variations that alter hillslope sediment supply. The combination of surficial mapping and hydraulic modeling with high-resolution topography can now produce detailed flood susceptibility maps. The effective use of these maps to protect lives and property, however, depends on answering many of the enduring questions about the mechanics of how water and sediment divide down alluvial fans.

Book chapter↗

USGS2021

Sediment budget for watersheds of West Maui, Hawaii

Episodic runoff brings suspended sediment to West Maui’s nearshore waters, turning them from blue to brown. This pollution degrades the ecological, cultural, and recreational value of these iconic nearshore waters. We used mapping, monitoring, and modeling to identify and quantify the watershed sources for fine sediment that pollutes the nearshore each year. These results focus strategies to reduce pollution on the outstanding sources for this sediment. Terrestrial runoff causing coastal plumes now occurs when two or more hours of rain falls at rates greater than 10–20 millimeter (mm) per hour in source watersheds. Analysis of recent and historical rainfall indicates that West Maui communities can expect rainfalls to bring coastal plumes at least 3–5 times per year. Former agricultural fields and some unimproved roads are possible sources for the fine sediment of these plumes. We found, however, that these obvious sources do not produce plumes during small annual storms, because they drain water at rates that far exceed most annual rainfalls and because there is no evidence for runoff from rains that caused recent plumes. Streambanks now eroding into historic fill terraces of sands, silts, and clays are a more plausible source. These terraces are found only downstream of historical agricultural fields and are composed of silt and fine sand. Surveys show that the fill terraces occupy ~40 percent of streambank length, making them extensive. During 2015–2016, these deposits eroded at median rates of 5–24 mm per year. Summed over West Maui’s watersheds, these rates imply sediment loads carried to the coast that can be ten times or more than modeled pre-human values. A sediment budget indicates that bank erosion of fill terraces from a few watersheds likely dominates the current annual fine-sediment load to the nearshore, with Kahana Stream watershed producing the largest annual input of 285 metric tons, the equivalent of 29 dump-truck loads every year. Although past large storms have contributed to sediment loading, annual plume generation is now caused by smaller rainfalls eroding these near-stream terrace deposits, a legacy of historic agriculture. Treatments of former agricultural fields, roads, and reserve forests are consequently not likely to measurably effect sediment pollution from smaller, more frequent storms. Increased runoff from residential and commercial development of West Maui has the potential to exacerbate sediment plumes from such storms.

Hawaii↗

USGS2019

Where’s the rock: Using convolutional neural networks to improve land cover classification

While machine learning techniques have been increasingly applied to land cover classification problems, these techniques have not focused on separating exposed bare rock from soil covered areas. Therefore, we built a convolutional neural network (CNN) to differentiate exposed bare rock ( rock ) from soil cover ( other ). We made a training dataset by mapping exposed rock at eight test sites across the Sierra Nevada Mountains (California, USA) using USDA’s 0.6 m National Aerial Inventory Program (NAIP) orthoimagery. These areas were then used to train and test the CNN. The resulting machine learning approach classifies bare rock in NAIP orthoimagery with a 0.95 F 1 "> F 1 score. Comparatively, the classical OBIA approach gives only a 0.84 F 1 "> F 1 score. This is an improvement over existing land cover maps, which underestimate rock by almost 90%. The resulting CNN approach is likely scalable but dependent on high-quality imagery and high-performance algorithms using representative training sets informed by expert mapping. As image quality and quantity continue to increase globally, machine learning models that incorporate high-quality training data informed by geologic, topographic, or other topical maps may be applied to more effectively identify exposed rock in large image collections.

California↗

USGS2018

Dust on a Hawaiian volcano: A regional model using field measurements to estimate transport and deposition

The western slopes of Hawaii's Mauna Kea volcano are mantled by fine-grained soils, the record of volcanic airfall and eolian deposition. Where exposed, strong winds transport this sediment across West Hawaii, affecting tourism and local communities with decreased air and water quality. Operations on US Army's Ke'amuku Maneuver Area (KMA) have the potential to increase dust flux from these deposits. The USGS established 18 ground monitoring sites and sampling locations surrounding KMA. For over 3 years, each station measured vertical and horizontal dust flux, while co-located anemometers measured wind speed and direction. We used these datasets to develop a parsimonious regional model for dust supply and transport to assess whether KMA is a net dust sink or source. We found that dust transport is most highly correlated with threshold wind speeds of 8 m/s. We used this value as the regional average threshold wind speed for dust entrainment. Using a model that partitions measured horizontal dust flux into inward- and outward-directed components, we estimate that KMA is currently a net dust sink. Geochemical analysis of dust samples illustrates that local organics and carbonate make up 64% of dust mass, the remainder being volcanic silt and fine sand. Measured vertical dust deposition rates of 0.006 mm/yr are similar to 0.004 mm/yr of deposition predicted from taking the divergence of dust across KMA's boundary. These rates are low compared with pre-historic rates of ~0.2–0.3 mm/yr, from radiocarbon dating of buried soils. KMA's soils record persistent deposition over millennia, at rates that imply episodic dust storms. Such events created a soil-mantled landscape in the middle of a largely Pleistocene rocky landscape. A substantial portion of fine-grained soils in other leeward Hawaiian Island landscapes may have formed from similar eolian deposition, and not direct weathering of parent rock. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.

Hawaii↗

USGS2018

Vegetation influences on infiltration in Hawaiian soils

Changes in vegetation communities caused by removing trees, introducing grazing ungulates, and replacing native plants with invasive species have substantially altered soil infiltration processes and rates in Hawaii. These changes directly impact run-off, erosion, plant-available water, and aquifer recharge. We hypothesize that broad vegetation communities can be characterized by distributions of field-saturated hydraulic conductivity (Kfs). We used 290 measurements of Kfs calculated from infiltration tests from 5 of the Hawaiian Islands to show this effect. We classified the data using 3 broad ecosystem categories: grasses, trees and shrubs, and bare soil. The soils of each site have coevolved with past and present ecological communities without significant mechanical disturbance by agriculture or urban development. Geometric mean values Kfs are 203 mm/hr for soils hosting trees and shrubs, 50 mm/hr for grasses, and 13 mm/hr for bare soil. Differences are statistically significant at the 95% confidence level. These examples show that it is feasible to make maps of relative Kfs based on field and ecosystem data. These ecosystem trends can be used to estimate ongoing changes to run-off and recharge from climate and land use change. Greater Kfs for ecosystems with primarily trees and shrubs suggests that management decisions concerning reforestation or other changes of vegetation can have substantial hydrologic impacts.

Hawaii↗

USGS2017

Vegetation response of a dry shrubland community to feral goat management on the island of Moloka‘i, Hawai‘i

The Hawaiian Islands are well known for their unique ecosystem assemblages that have a high proportion of endemic flora and fauna. However, since human colonization of this archipelago—starting with the arrival of Polynesian sailors approximately 1,200 years ago, and particularly following western contact in 1778—thousands of non-native species have been introduced to the Islands and many of these alien species have had severe impacts on the native ecosystems. Particularly damaging to these ecosystems are large mammals, including goats ( Capra hircus ), pigs ( Sus scrofa ), cattle ( Bos taurus ), deer ( Axis axis and Odocoileus hemionus ), and sheep ( Ovis spp.), which are collectively referred to here as ungulates; they cause extensive damage to the native vegetation by their browsing, grazing, and trampling. Similar impacts have been documented elsewhere, including New Zealand and many other island ecosystems. Previous studies in Hawai‘i have utilized fenced exclosures to assess the impacts of feral or wild ungulates on vegetation and the recovery potential for the native plant communities by comparing plant community composition, structure, and cover inside the fenced area (without ungulates) over time to the vegetation condition outside of the protection of the fence. In some cases, the native vegetation recovered once the animals were removed. However, in other situations alien plants were more competitive and dominated the revegetation process after the impacts of ungulates had been reduced or eliminated. This report describes the response of a highly degraded lowland dry habitat plant community located on the south slope of east Moloka‘i, Hawai ‘ i, to reduction of browsing and grazing impacts caused by feral goats. For this study, vegetation response inside a fenced exclosure was compared to vegetation change in the area outside of the fence that was still accessible to goats. This study is part of the larger U.S. Geological Survey Ridge-to-Reef (USGS-R2R) research project conducted between 2008 and 2014 to better understand the magnitude of, and factors responsible for, increased erosion on Moloka‘i. The upslope erosion has resulted in heavy sedimentation of the near-shore coral reef ecosystem on the leeward side of the island. The project area and adjacent lands are managed by the East Moloka‘i Watershed Partnership (EMoWP) to restore the vegetation and reduce erosion on the leeward side of the island. Specific questions addressed in this vegetation change study include: How does the vegetation composition, structure, and cover respond to different population levels of feral goats in this area? Are there plant species that can be used as indicators of different population levels of goats? Can native plants recover and become dominant again with the reduction or elimination of goats from this area? Are there invasive plant species that respond favorably to reduction of goat populations and could result in additional management threats to this area over time? How does the succession of vegetation following goat control relate to the original composition and structure of the plant communities that were formerly found in this area?

Hawai'i↗

USGS2016

Reconnaissance sediment budget for selected watersheds of West Maui, Hawai‘i

Episodic runoff brings suspended sediment to the nearshore waters of West Maui, Hawaiʻi. Even small rainfalls create visible plumes over a few hours. We used mapping, field experiments, and analysis of recent (July 19–20, 2014) and historic rainfall to estimate sources of land-based pollution for two watersheds in West Maui: Honolua, and Honokōwai. Former agricultural fields and some unimproved roads are plausible sources for polluted runoff, but have saturated hydraulic conductivities greater than the 10–15 millimeters per hour (mm/hr) rainfalls of July 2014. These fields and roads showed minor evidence for storm runoff, and could not have contributed substantially to July 2014 plume generation. Since 1978, rain at intensities capable of causing runoff from former agricultural fields sustained for 1–2 hours is also rare; such intensities have 2–5 year recurrence rates in the north, and greater than 25 year recurrence rates to the south near Lahaina. Streambanks now eroding into historic terraces of sands, silts, and clays are a more plausible source. Although past large storms contributed to sediment loading, annual plume generation is now caused by smaller rainfalls eroding these near-stream legacy deposits. Treatments of former agricultural fields, roads, and reserve forests are consequently not likely to measurably affect sediment pollution from smaller, more frequent storms. Increased runoff from the development of West Maui has the potential to exacerbate sediment plumes from such storms unless there is an effective strategy to reduce bank erosion. Uncertainties in the extent and erosion rate of historic terraces, however, limit our ability to plan mitigation.

Hawaii↗

USGS2013

Covariation of climate and long-term erosion rates acrossa steep rainfall gradient on the Hawaiian island of Kaua'i

Erosion of volcanic ocean islands creates dramatic landscapes, modulates Earth’s carbon cycle, and delivers sediment to coasts and reefs. Because many volcanic islands have large climate gradients and minimal variations in lithology and tectonic history, they are excellent natural laboratories for studying climatic effects on the evolution of topography. Despite concerns that modern sediment fluxes to island coasts may exceed long-term fluxes, little is known about how erosion rates and processes vary across island interiors, how erosion rates are influenced by the strong climate gradients on many islands, and how modern island erosion rates compare to long-term rates. Here, we present new measurements of erosion rates over 5 yr to 5 m.y. timescales on the Hawaiian island of Kaua‘i, across which mean annual precipitation ranges from 0.5 to 9.5 m/yr. Eroded rock volumes from basins across Kaua‘i indicate that million-year-scale erosion rates are correlated with modern mean annual precipitation and range from 8 to 335 t km –2 yr –1 . In Kaua‘i’s Hanalei River basin, 3 He concentrations in detrital olivines imply millennial-scale erosion rates of >126 to >390 t km –2 yr –1 from olivine-bearing hillslopes, while fluvial suspended sediment fluxes measured from 2004 to 2009 plus estimates of chemical and bed-load fluxes imply basin-averaged erosion rates of 545 ± 128 t km –2 yr –1 . Mapping of landslide scars in satellite imagery of the Hanalei basin from 2004 and 2010 implies landslide-driven erosion rates of 30–47 t km –2 yr –1 . These measurements imply that modern erosion rates in the Hanalei basin are no more than 2.3 ± 0.6 times faster than millennial-scale erosion rates, and, to the extent that modern precipitation patterns resemble long-term patterns, they are consistent with a link between precipitation rates and long-term erosion rates.

Hawai'i↗

USGS2012

Monitoring subsurface hydrologic response for precipitation-induced shallow landsliding in the San Francisco Bay area, California, USA

Intense winter storms in the San Francisco Bay area (SFBA) of California, USA often trigger shallow landslides. Some of these landslides mobilize into potentially hazardous debris flows. A growing body of research indicates that rainfall intensity-duration thresholds are insufficient for accurate prediction of landslide occurrence. In response, we have begun long-term monitoring of the hydrologic response of land-slide-prone hillslopes to rainfall in several areas of the SFBA. Each monitoring site is equipped with sensors for measuring soil moisture content and piezometric pressure at several soil depths along with a rain gauge connected to a cell phone or satellite telemetered data logger. The data are transmitted in near-real-time, providing the ability to monitor hydrologic conditions before, during, and after storms. Results are guiding the establishment of both antecedent and storm-specific rainfall and moisture content thresholds which must be achieved before landslide-causative positive pore water pressures are generated. Although widespread shallow landsliding has not yet occurred since the deployment of the monitoring sites, several isolated land-slides have been observed in the area of monitoring. The landslides occurred during a period when positive pore water pressures were measured as a result of intense rainfall that followed higher-than-average season precipitation totals. Continued monitoring and analysis will further guide the establishment of more general-ized thresholds for different regions of the SFBA and contribute to the development and calibration of physi-cally-based predictive models.

Conference Paper↗

USGS2011

From ridge to reef—linking erosion and changing watersheds to impacts on the coral reef ecosystems of Hawai‘i and the Pacific Ocean

Coral reef ecosystems are threatened by unprecedented watershed changes in the United States and worldwide. These ecosystems sustain fishing and tourism industries essential to the economic survival of many communities. Sediment, nutrients, and pollutants from watersheds are increasingly transported to coastal waters, where these contaminants damage corals. Although pollution from watersheds is one of many factors threatening coral survival, it is one that local people can have a profound influence on. U.S. Geological Survey scientists are using mapping, monitoring, and computer modeling to better forecast the effects of watershed changes on reef health. Working with communities in Hawai‘i and on other U.S. islands in the Pacific, they are helping to provide the science needed to make informed decisions on watershed and coral reef management.

Hawai'i↗

USGS2011

Overview of the ARkStorm scenario

The U.S. Geological Survey, Multi Hazards Demonstration Project (MHDP) uses hazards science to improve resiliency of communities to natural disasters including earthquakes, tsunamis, wildfires, landslides, floods and coastal erosion. The project engages emergency planners, businesses, universities, government agencies, and others in preparing for major natural disasters. The project also helps to set research goals and provides decision-making information for loss reduction and improved resiliency. The first public product of the MHDP was the ShakeOut Earthquake Scenario published in May 2008. This detailed depiction of a hypothetical magnitude 7.8 earthquake on the San Andreas Fault in southern California served as the centerpiece of the largest earthquake drill in United States history, involving over 5,000 emergency responders and the participation of over 5.5 million citizens. This document summarizes the next major public project for MHDP, a winter storm scenario called ARkStorm (for Atmospheric River 1,000). Experts have designed a large, scientifically realistic meteorological event followed by an examination of the secondary hazards (for example, landslides and flooding), physical damages to the built environment, and social and economic consequences. The hypothetical storm depicted here would strike the U.S. West Coast and be similar to the intense California winter storms of 1861 and 1862 that left the central valley of California impassible. The storm is estimated to produce precipitation that in many places exceeds levels only experienced on average once every 500 to 1,000 years. Extensive flooding results. In many cases flooding overwhelms the state’s flood-protection system, which is typically designed to resist 100- to 200-year runoffs. The Central Valley experiences hypothetical flooding 300 miles long and 20 or more miles wide. Serious flooding also occurs in Orange County, Los Angeles County, San Diego, the San Francisco Bay area, and other coastal communities. Windspeeds in some places reach 125 miles per hour, hurricane-force winds. Across wider areas of the state, winds reach 60 miles per hour. Hundreds of landslides damage roads, highways, and homes. Property damage exceeds $ 300 billion, most from flooding. Demand surge (an increase in labor rates and other repair costs after major natural disasters) could increase property losses by 20 percent. Agricultural losses and other costs to repair lifelines, dewater (drain) flooded islands, and repair damage from landslides, brings the total direct property loss to nearly $ 400 billion, of which $ 20 to $ 30 billion would be recoverable through public and commercial insurance. Power, water, sewer, and other lifelines experience damage that takes weeks or months to restore. Flooding evacuation could involve 1.5 million residents in the inland region and delta counties. Business interruption costs reach $ 325 billion in addition to the $ 400 billion property repair costs, meaning that an ARkStorm could cost on the order of $ 725 billion, which is nearly 3 times the loss deemed to be realistic by the ShakeOut authors for a severe southern California earthquake, an event with roughly the same annual occurrence probability. The ARkStorm has several public policy implications: (1) An ARkStorm raises serious questions about the ability of existing federal, state, and local disaster planning to handle a disaster of this magnitude. (2) A core policy issue raised is whether to pay now to mitigate, or pay a lot more later for recovery. (3) Innovative financing solutions are likely to be needed to avoid fiscal crisis and adequately fund response and recovery costs from a similar, real, disaster. (4) Responders and government managers at all levels could be encouraged to conduct risk assessments, and devise the full spectrum of exercises, to exercise ability of their plans to address a similar event. (5) ARkStorm can be a reference point for application of Federal Emergency Management Agency (FEMA) and California Emergency Management Agency guidance connecting federal, state and local natural hazards mapping and mitigation planning under the National Flood Insurance Plan and Disaster Mitigation Act of 2000. (6) Common messages to educate the public about the risk of such an extreme disaster as the ARkStorm scenario could be developed and consistently communicated to facilitate policy formulation and transformation. These impacts were estimated by a team of 117 scientists, engineers, public-policy experts, insurance experts, and employees of the affected lifelines. In many aspects the ARkStorm produced new science, such as the model of coastal inundation. The products of the ARkStorm are intended for use by emergency planners, utility operators, policymakers, and others to inform preparedness plans and to enhance resiliency.

California↗

USGS2011

An empirical method to forecast the effect of storm intensity on shallow landslide abundance

We hypothesize that the number of shallow landslides a storm triggers in a landscape increases with rainfall intensity, duration and the number of unstable model cells for a given shallow landslide susceptibility model of that landscape. For selected areas in California, USA, we use digital maps of historic shallow landslides with adjacent rainfall records to construct a relation between rainfall intensity and the fraction of unstable model cells that actually failed in historic storms. We find that this fraction increases as a power law with the 6-hour rainfall intensity for sites in southern California. We use this relation to forecast shallow landslide abundance for a dynamic numerical simulation storm for California, representing the most extreme historic storms known to have impacted the state.

California↗

USGS2011

Hydrologic conditions and terrestrial laser scanning of post-fire debris flows in the San Gabriel Mountains, CA, U.S.A.

To investigate rainfall-runoff conditions that generate post-wildfire debris flows, we instrumented and surveyed steep, small watersheds along the tectonically active front of the San Gabriel Mountains, California. Fortuitously, we recorded runoff-generated debris-flows triggered by one spatially restricted convective event with 28 mm of rainfall falling over 62 minutes. Our rain gages, nested hillslope overland-flow sensors and soil-moisture probes, as well as a time series of terrestrial laser scanning (TLS) revealed the effects of the storm. Hillslope overland-flow response, along two ~10-m long flow lines perpendicular to and originating from a drainage divide, displayed only a 10 to 20 minute delay from the onset of rainfall with accumulated totals of merely 5-10 mm. Depth-stratified soil-moisture probes displayed a greater time delay, roughly 20- 30 minutes, indicating that initial overland flow was Hortonian. Furthermore, a downstream channel-monitoring array recorded a pronounced discharge peak generated by the passage of a debris flow after 18 minutes of rainfall. At this time, only four of the eleven hillslope overlandflow sensors confirmed the presence of surface-water flow. Repeat TLS and detailed field mapping using GPS document how patterns of rainsplash, overland-flow scour, and rilling contributed to the generation of meter-scale debris flows. In response to a single small storm, the debris flows deposited irregular levees and lobate terminal snouts on hillslopes and caused widespread erosion of the valley axis with ground surface lowering exceeding 1.5 m.

California↗

USGS2011

Spatially explicit shallow landslide susceptibility mapping over large areas

Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so it has generated downscaled precipitation maps for the storm. To predict the corresponding pattern of shallow landslide susceptibility across the state, we have used the model Shalstab (a coupled steady state runoff and infinite slope stability model) which susceptibility spatially explicit estimates of relative potential instability. Such slope stability models that include the effects of subsurface runoff on potentially destabilizing pore pressure evolution require water routing and hence the definition of upslope drainage area to each potential cell. To calculate drainage area efficiently over a large area we developed a parallel framework to scale-up Shalstab and specifically introduce a new efficient parallel drainage area algorithm which produces seamless results. The single seamless shallow landslide susceptibility map for all of California was accomplished in a short run time, and indicates that much larger areas can be efficiently modelled. As landslide maps generally over predict the extent of instability for any given storm. Local empirical data on the fraction of predicted unstable cells that failed for observed rainfall intensity can be used to specify the likely extent of hazard for a given storm. This suggests that campaigns to collect local precipitation data and detailed shallow landslide location maps after major storms could be used to calibrate models and improve their use in hazard assessment for individual storms.

California↗

USGS2009

Hydrologic characterization of desert soils with varying degrees of pedogenesis: 1. field experiments evaluating plant-relevant soil water behavior

To assess the eff ect of pedogenesis on the soil moisture dynamics infl uencing the character and quality of ecological habitat, we conducted infi ltration and redistribution experiments on three alluvial deposits in the Mojave National Preserve: (i) recently deposited active wash sediments, (ii) a soil of early Holocene age, and (iii) a highly developed soil of late Pleistocene age. At each, we ponded water in a 1-m-diameter infi ltration ring for 2.3 h and monitored soil water content and matric pressure during and atier infi ltration, using probes and electrical resistivity imaging (ERI). Infi ltration and downward fl ow rates were greater in younger material, favoring deep-rooted species. Deep-rooted species tend to colonize the margins of washes, where they are unaff ected by sediment transport that inhibits colonization. The ERI results support important generalizations, for example that shallower than 0.5 m, infi ltrated water persists longer in highly developed soil, favoring shallow-rooted species. Soil moisture data for the two youngest soils suggested that saturation overshoot, which may have signifi cant but unexplored hydroecologic and pedogenic eff ects, occurred at the horizontally advancing weting front. Spatial heterogeneity of soil properties generally increased with pedogenic development. Evidence suggested that some early-stage developmental processes may promote uniformity; the intermediate- age soil appeared to have the least heterogeneity in terms of textural variation with depth, and also the least anisotropy. Lateral heterogeneity was pronounced in older soil, having a multitude of eff ects on the distribution and retention of soil water, and may facilitate certain water-conserving strategies of plants over what would be possible in a laterally homogeneous soil. ?? Soil Science Society of America.

California↗