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Capacity assessment for Earth Monitoring, Analysis, and Prediction (EarthMAP) and future integrated monitoring and predictive science at the U.S. Geological Survey

Executive Summary Managers of our Nation’s resources face unprecedented challenges driven by the convergence of increasing, competing societal demands and a changing climate that affects the stability, vulnerability, and predictability of those resources. To help meet these challenges, the scientific community must take advantage of all available technologies, data, and integrative Earth systems modeling capacity to better inform resource and risk management decisions. This is the overarching goal of the U.S. Geological Survey (USGS) Earth Monitoring, Analysis, and Prediction (EarthMAP) vision: “By 2030, the USGS will deliver well integrated observations and predictions of the future state of natural systems—water, ecosystems, energy, minerals, hazards—at regional and national scales, working primarily with federal, state, and academic partners to develop and operate the capability” (U.S. Geological Survey, 2021). Providing more integrated Earth systems science and actionable information to decision makers, stakeholders, and the public requires a better understanding of the depth and distribution of existing capacity (capabilities, tools, and techniques) across the Bureau. Identifying existing capacity is also a critical first step toward gap analysis and targeted investments to increase capacity over time. The USGS formed a Capacity Assessment Team (CAT) and charged it with (1) conducting a Request for Information (RFI) to identify existing USGS expertise and activities supportive of integrated and predictive science to inform decision making, (2) developing a strategy and proof-of-concept for a continuously updated capacity assessment capability, and (3) identifying lessons learned to inform development of best practices for future capacity assessment efforts. The RFI took the form of a survey, with content guided by the science and technology needs identified in a USGS report titled “Grand Challenges for Integrated U.S. Geological Survey Science—A Workshop Report” (Jenni and others, 2017). The 44-question survey provided respondents the ability to rate their level of experience with a suite of priority disciplines, analysis and modeling approaches, technologies, and stakeholder engagement strategies and to enter optional narrative text for supporting context. An introductory portion focused on general science capacity assessment, followed by three sections targeting capabilities related to the foundational components of EarthMAP: (1) data and information integration, (2) integrated predictive science, and (3) actionable information. The survey results provided a high-level snapshot of USGS capacity in the targeted areas. Respondents (1,035 individuals) represented approximately 13 percent of the USGS across all mission areas and regions. Seventy-four percent of the respondents held a science-focused position title and the remainder had position titles in information technology, computer science, management, administrative, or other (contractors, volunteers, emeritus, and unknown). To provide greater insight into respondent capabilities and activities, information from the U.S. Department of the Interior and USGS enterprise information systems were used to further characterize topical expertise and organizational associations of survey respondents. To address the ongoing need to assess the Bureau’s capacity to address integrated predictive science priorities, the CAT developed a software-based proof-of-concept called the Integrated Science Assessment Information Database (iSAID) for assembling various information sources together toward making the full extent of USGS capabilities and scientific assets available for routine capacity assessment. This proof-of-concept is intended to serve as a catalyst for further development. The process of implementing the EarthMAP capacity assessment survey, analyzing survey responses, and developing the proof-of-concept resulted in lessons learned, findings, and recommendations. Example scenarios throughout the report demonstrate how capacity assessment data can inform science planning. Three overarching findings and recommendations are: (1) Finding: Capacity is limited in some critical disciplines, skills, and technology applications, but “sufficient” depends on the question and the need relative to availability at a given point in time. Recommendation: Develop an on-demand capacity assessment framework that enables rapid identification and evaluation of existing and available expertise to support decision needs as they arise. (2) Finding: Institutional barriers and lack of awareness constrain the ability of USGS staff to adopt new technologies, collaborate across administrative boundaries, and deliver actionable information to stakeholders in a timely manner. However, these barriers are not universally experienced. Recommendation: Pursue more targeted inquiries to clarify which institutional barriers are obstructing the adoption of new technologies and approaches or the sharing of expertise and equipment across organizational and regional boundaries. These inquiries should inform USGS leadership, mission areas, and regions whether policies can be revised or whether a lack of understanding is creating perceived obstacles. Highlight cases when staff have successfully adopted new technologies and approaches to advance EarthMAP priorities and provide actionable information in a timely manner to spread awareness of how perceived obstacles can be navigated and overcome when appropriate. (3) Finding: Examples of people and projects integrating across disciplines and scales and applying advanced approaches to meet complex stakeholder needs exist. Such examples provide transfer value across the spectrum from approach to decision making. Many projects, already underway, appear to meet elements of the EarthMAP vision, and the USGS has people who can provide leadership in multiple types of specific integrated science efforts. Recommendation: Use these findings as a starting point for near-term strategic planning for integrated science. Highlight, incentivize, and build on existing interdisciplinary predictive science and information delivery activities across the USGS to advance toward further realization of an EarthMAP capacity. The CAT efforts to develop and assess existing USGS capacity to advance the EarthMAP vision revealed a fundamental challenge for not only this effort but any effort to assess existing capacity: A considerable amount of thought, time, and effort is required to survey and assess capabilities and tools available to support a given need, yet best results are still likely to provide an incomplete assessment. To better meet the frequent need to assess capabilities, tools, products, and projects that address an expressed strategic priority, the CAT proposes the concept of an on-demand capacity assessment framework supported by a software package that dynamically pulls and integrates information from existing USGS information systems and public domain registries. Although existing USGS enterprise information systems currently lack the structure, cross-system consistency, interoperability, and stability to support a continuously updated capacity assessment capability, we identify reasonable near-term steps to improve the utility of information gathered on expertise and project capacity and to improve the consistency and completeness of information and the ability of USGS systems to share that information. The ability to search and characterize this information will make future assessments of capacity faster, more complete, more efficient, and more targeted. This approach would grow the Bureau’s capacity knowledge over time, iteratively improving the ability to access, leverage, and synthesize existing capabilities and assets as well as identify and fill critical gaps. The greatest promise for developing integrated science could lie in linking across existing projects and expertise to create a multi-project capacity for addressing large, complex environmental issues.

Open-File Report

Spatial and temporal variation of stream chemistry associated with contrasting geology and land-use patterns in the Chesapeake Bay watershed—Summary of results from Smith Creek, Virginia; Upper Chester River, Maryland; Conewago Creek, Pennsylvania; and Difficult Run, Virginia, 2010–2013

Despite widespread and ongoing implementation of conservation practices throughout the Chesapeake Bay watershed, water quality continues to be degraded by excess sediment and nutrient inputs. While the Chesapeake Bay Program has developed and maintains a large-scale and long-term monitoring network to detect improvements in water quality throughout the watershed, fewer resources have been allocated for monitoring smaller watersheds, even though water-quality improvements that may result from the implementation of conservation practices are likely to be first detected at smaller watershed scales. In 2010, the U.S. Geological Survey partnered with the U.S. Environmental Protection Agency and the U.S. Department of Agriculture to initiate water-quality monitoring in four selected small watersheds that were targeted for increased implementation of conservation practices. Smith Creek watershed is an agricultural watershed in the Shenandoah Valley of Virginia that is dominated by cattle and poultry production, and the Upper Chester River watershed is an agricultural watershed on the Eastern Shore of Maryland that is dominated by row-cropping activities. The Conewago Creek watershed is an agricultural watershed in southeastern Pennsylvania that is characterized by mixed agricultural activities. The fourth watershed, Difficult Run, is a suburban watershed in northern Virginia that is dominated by medium density residential development. The objective of this study was to investigate spatial and temporal variations in water chemistry and suspended sediment in these four relatively small watersheds that represent a range of land-use patterns and underlying geology to (1) characterize current water-quality conditions in these watersheds, and (2) identify the dominant sources, sinks, and transport processes in each watershed. The general study design involved two components. The first included intensive routine water-quality monitoring at an existing streamgage within each study area (including continuous water-quality monitoring as well as discrete water-quality sampling) to develop a detailed understanding of the temporal and hydrologic variability in stream chemistry and sediment transport in each watershed. The second component involved extensive water-quality monitoring at various sites throughout each watershed to develop a detailed understanding of spatial patterns. Both components were used to improve understanding of sources and transport processes affecting stream chemistry, including nutrients and suspended sediments, and their implications for detecting long-term trends related to best management practices. This report summarizes the results of monitoring that was performed from April 2010 through September 2013. Individual Small Watershed Summaries Summaries for each of the four small watersheds are presented below. Each watershed has a more descriptive and detailed section in the report, but these summaries may be particularly useful for some watershed managers and stakeholders desiring slightly less technical detail. Smith Creek Smith Creek is a 105.39-mi 2 watershed within the Shenandoah Valley that drains to the North Fork Shenandoah River. The long-term Smith Creek base-flow index is 72.3 percent, indicating that on average, approximately 72 percent of Smith Creek flow was base flow, which suggests that Smith Creek streamflow is dominated by groundwater discharge rather than stormwater runoff. A series of cluster and principal components analyses demonstrated that the majority of the variability in Smith Creek water quality could be attributed to hydrologic and seasonal variability. Statistically significant positive correlations with flow were observed for turbidity, suspended sediments, total nitrogen, ammonium, orthophosphate, iron, total phosphorus, and the ratio of calcium to magnesium. Statistically significant inverse correlations with flow were observed for specific conductance, magnesium, δ 15 N of nitrate, pH, bicarbonate, calcium, and δ 18 O of nitrate. Of particular note, flow and nitrate were not statistically significantly correlated, likely because of the relatively complex concentration-discharge relationship observed in continuous and discrete datasets. Statistically significant seasonal patterns were observed for numerous water-quality constituents: water temperature, turbidity, orthophosphate, total phosphorus, suspended-sediment concentration, and silica were higher during the warm season, but pH, dissolved oxygen, and sulfate were higher during the cool season. Surrogate regression models were developed to compute sediment and nutrient loads in Smith Creek using the continuous water-quality monitors. The mean Smith Creek in-stream sediment load was approximately 6,900 tons per year, with nearly 90 percent of the sediment load over the 3-year study period contributed during the eight largest storm events during that period. The Smith Creek total phosphorus load was approximately 21,000 pounds of phosphorus per year, with the majority of the load contributed during stormflow periods, although a substantial phosphorus load still occurs during base-flow conditions. The Smith Creek total nitrogen load was approximately 400,000 pounds per year, with total nitrogen accumulation less dominated by stormflow contributions (as was the case for sediment and total phosphorus) and strongly affected by base-flow export of nitrogen from the basin. Extensive water-quality monitoring throughout the Smith Creek watershed revealed how the complex geology and hydrology interacted to result in variable water chemistry. During relatively dry and low base-flow periods, much of the discharge in Smith Creek was contributed by a single dominant spring—Lacey Spring. During wetter base-flow periods, the flows in Smith Creek were largely generated by a mixture of headwater springs and forested mountain tributaries with very different geochemical composition. The headwater springs generally issued from limestone bedrock and were characterized as having relatively high nitrate, specific conductance, calcium, and magnesium, as well as relatively low concentrations of phosphorus, ammonium, iron, and manganese. The undeveloped, high-gradient, forested mountain sites were generally characterized by low ionic strength waters with low nutrient concentrations. Nitrate isotope data from the limestone springs generally were consistent with manure-derived nitrogen sources (such as cattle and poultry), although the possibility of other mixed sources cannot be excluded. Nitrate isotope data from the undeveloped, high-gradient forested mountain sites were more consistent with nitrogen from undisturbed soils, atmospheric deposition, or nitrogen fixation. Regardless of the nitrogen source, oxygen isotope data indicate that the nitrate was largely a result of nitrification. Land-use data indicate that manure sources of nitrogen dominated watershed nitrogen inputs. Phosphorus sources were less well studied. The presence of a single point-source discharge near the town of New Market contributed the majority of the phosphorus to Smith Creek under base-flow conditions, but nonpoint sources of phosphorus dominated the loading to Smith Creek during stormflow periods. Implementation of conservation practices increased in the Smith Creek watershed during the study period, and even though a broad range of practice types was implemented, the most common practices included stream fencing (for cattle exclusion), the development of nutrient management plans, conservation crop rotation, and the planting of cover crops. While the implementation of these conservation practices is encouraging, results indicate small increases in nitrate concentrations at the streamgage over the last 29 years, concurrent with small decreases in nitrate fluxes. It will likely be years before the cumulative effect of these practices can be detected in the Smith Creek water quality, and the magnitude of the effect of these conservation practices detected in Smith Creek will depend largely on whether nutrient loading (of manure and commercial fertilizer) is reduced over time. Upper Chester River The Upper Chester River watershed includes the 36-square-mile (mi 2 ) watershed area around several nontidal tributaries that drain into the tidal Chester River. The streamgage is on Chesterville Branch, the largest nontidal tributary (approximately 6.12 mi 2 ) and is the site for continuous water-quality monitoring for this project. The base-flow index at Chesterville Branch is about 72 percent and indicates that, as in most of the Coastal Plain, groundwater is the greatest contributor to streamflow. As such, more than 90 percent of the nitrogen in the stream is in the form of nitrate from groundwater. Continuous and discrete data collected at Chesterville Branch show the effects of streamflow and season on water quality. Significantly positive correlations with flow were observed for ammonium, dissolved and total phosphorus, sediment, and turbidity as runoff carried these constituents from the land surface into Chesterville Branch. Other constituents that increased significantly with flow include potassium, sulfate, iron, and manganese, which are likely contributed from near-stream areas and ponds with high organic-matter content. Total nitrogen, pH, and specific conductance, along with chemical constituents associated with groundwater inputs including nitrate, calcium, ratio of calcium to magnesium, silica, bicarbonate, and sodium, were negatively correlated with flow because concentrations of these constituents were diluted by runoff. Seasonal differences in water chemistry, which are most likely related to increased biologic effects on the uptake and release of chemicals in the stream and near-stream areas, also were observed. Water temperature, orthophosphate, δ 15 N of nitrate, bicarbonate, sodium, and the ratio of sodium to chloride were higher during the warm season, and dissolved oxygen, total nitrogen, nitrate, magnesium, sulfate, and manganese were higher during the cool season. Surrogate-regression models developed by using continuous water-quality data showed that the annual sediment load for the 2013 water year was about 2,600 tons, with more than 90 percent of this sediment contributed during two storms. The total phosphorus load in 2013 was about 13,000 pounds with more than 90 percent contributed during the same two storms as sediment. The load of total nitrogen, 140,000 pounds, accumulated steadily throughout the 2013 water year as nitrate in groundwater continuously discharged into the stream. The same two large storms that contributed 90 percent of the suspended-sediment and total phosphorus load only contributed about 20 percent of the annual total nitrogen load. Extensive water-quality monitoring of stream base flow throughout the Upper Chester River watershed identified how differences in land use and hydrogeology affected water chemistry. In parts of the watershed with well-drained soil and thick sandy aquifer sediments, concentrations of nitrate and other chemicals associated with fertilizer and lime application increased in streams as agricultural land use increased. More than 90 percent of the nitrogen in streams from these areas was in the form of nitrate, and concentrations ranged from about 5 milligrams per liter (mg/L) to 8 mg/L as nitrogen in the two largest tributaries. Stream nitrate concentrations were about 1 mg/L as nitrogen where soils were more poorly drained, the surficial aquifer sediments were thinner, and forests and wetlands were more widespread than agriculture. Nitrate isotope data were consistent with inorganic fertilizers ± atmospheric deposition and N 2 fixation as sources of nitrogen, and with nitrification as the dominant nitrate-forming process. Nitrate reduction was indicated by elevated δ 15 N and δ 18 O values in some samples from streams draining watersheds with poorly drained soils. An analysis of land-use data and SPARROW modeling input data attributed almost 90 percent of the nitrogen sources in the Upper Chester River watershed to inorganic fertilizer and fixation of atmospheric nitrogen by legumes, which is in agreement with the isotopic characteristics of nitrate in this watershed. Local sources of manure are limited in this area. Total phosphorus concentrations during base flow ranged from below detection to about 0.2 mg/L. Stream phosphorus concentrations during base flow were generally lower than those measured during storms because most phosphorus transport likely occurs as phosphorus attached to sediment particles during runoff. Because manure is not widely used in this area, the major source of phosphorus is likely fertilizer. The implementation of conservation practices in the Upper Chester River watershed increased substantially during the study period, with a total implementation of 1,194 U.S. Department of Agriculture-compliant practices. The most frequently used practices were oriented towards nutrient and sediment control, including cover crops, nutrient management planning, conservation crop rotation, conservation tillage, and irrigation management. The current Chesapeake Bay model for this area predicts that implementation of best management practices should result in a 13-percent decrease in overall delivery of nitrogen to the Upper Chester River. Because most nitrogen travels through the groundwater system for years to decades before being discharged to streams, the time period of monitoring was not sufficient to see the effects of these practices on water quality. The magnitude of the effect that may eventually be detected will depend on the degree to which nitrate leaching into the groundwater system is reduced over time. Loadings of phosphorus and sediment are primarily transported during large runoff events and are difficult to control and analyze for trends because of their timing and episodic nature. Conewago Creek Conewago Creek has two primary monitoring locations—one near the middle of the 47-mi 2 watershed and the other near the outlet just upstream of the Susquehanna River. The base-flow index was 47.3 percent for 2012–2013, indicating that on average, approximately 53 percent of the streamflow in Conewago Creek exited the watershed as surface flow, which suggests that the stormwater runoff was somewhat greater than groundwater discharge (base flow). A series of cluster and principal components analyses demonstrated that the majority of the variability in the Conewago Creek water quality could be attributed to hydrologic and seasonal variability. Statistically significant positive correlations with flow were observed at both monitoring sites for ammonium, total phosphorus, orthophosphate, iron, and manganese; additionally, at the upstream monitoring station, total nitrogen demonstrated a statistically significant positive correlation with flow. Statistically significant inverse correlations with flow were observed at both sites for water temperature, specific conductance (at the downstream site only), sulfate, chloride, calcium, and magnesium. Statistically significant seasonal patterns were observed for several water-quality constituents. Water temperature, phosphorus (upstream site only), and orthophosphate were higher during the warm season, and nitrate and total nitrogen (upstream site only) were higher during the cool season. Surrogate regression models were developed to compute sediment and nutrient load in Conewago Creek by using the continuous water-quality monitors and water-quality samples. Conewago Creek sediment load was approximately 9,900 tons in 2012 and approximately 18,900 tons in 2013, with nearly 80 percent of the sediment load in 2013 contributed by the three largest storm events. Annual total nitrogen loads could not be estimated due to poor model performance. The addition of continued monitoring or a continuously recording nitrate sensor could improve estimates of total nitrogen loads. During 2012 and 2013, phosphorus loads in Conewago Creek were approximately 50,000 pounds in each year. Combining data from one high-flow synoptic sampling with the data from routine sampling revealed how the geology and hydrology interact to result in variable water chemistry throughout the Conewago Creek watershed. The areas above the upstream gage in the headwaters are generally underlain by forested non-carbonate bedrock and are characterized by relatively low nitrate, specific conductance, calcium, and magnesium, as well as relatively low concentrations of phosphorus, ammonium, iron, and manganese. The more developed, agricultural areas below the upstream site were generally characterized by higher ionic strength waters with higher nutrient and metal concentrations. An analysis of land-use data and SPAtially Referenced Regressions On Watershed (SPARROW) modeling data indicates that manure sources of nitrogen dominate the input of nitrogen to the watershed. Implementation of conservation practices increased in the Conewago Creek watershed during the study period, and while a broad range of practice types were implemented, the most common practices included residue and tillage management, cover crops, nutrient management, terracing, and stream fencing (for animal exclusion or bank restoration). While the implementation of these conservation practices is encouraging, the cumulative effects of these practices probably will not be detected in Conewago Creek water quality for several years. The magnitude of the effects of these conservation practices on water quality in Conewago Creek will depend largely on the extent to which nutrient loading (septic, manure, and commercial fertilizer) and sediment-producing activities are reduced over time. Difficult Run The Difficult Run watershed is a 57.82-mi 2 watershed that drains to the Potomac River. The long-term Difficult Run base-flow index (from 1936 to 2010) was 57.9, indicating that approximately 58 percent of streamflow exited the watershed as base flow and 42 percent as stormflow; however, with continued development and urbanization of the watershed, the base-flow index has decreased to 50 percent during the last 20 years. This base-flow index was less than those of the other watersheds evaluated in this study, likely because the Difficult Run watershed largely is underlain by crystalline piedmont metamorphic rocks and has a greater proportion of impervious urban land cover. A series of cluster and principal components analyses indicated that most of the variability in Difficult Run water quality could be attributed to hydrologic variability and seasonality. Statistically significant positive correlations with flow were observed for turbidity, dissolved oxygen, suspended sediments, ammonium, orthophosphate, iron, and total phosphorus. Statistically significant inverse correlations with flow were observed for water temperature, pH, specific conductance, bicarbonate, calcium, magnesium, nitrate, δ 15 N of nitrate, and silica. Statistically significant seasonal patterns were observed for numerous water-quality constituents: water temperature, ammonium, orthophosphate, and δ 15 N of nitrate were higher during the warm season, and dissolved oxygen, nitrate, and manganese were higher during the cool season. Surrogate regression models were developed to compute sediment and nutrient loading rates. The Difficult Run sediment load was approximately 8,000 tons per year, with greater than 95 percent of the sediment load in the 2013 water year contributed by the seven largest storm events. The total phosphorus load in Difficult Run was approximately 14,000 pounds of phosphorus per year, with the majority of the load contributed during stormflow periods. The total nitrogen load in Difficult Run is estimated to have been approximately 140,000 pounds per year, with total nitrogen accumulation less dominated by stormflow contributions than that of phosphorus and strongly affected by base-flow export of nitrogen from the basin. Extensive water-quality monitoring throughout the Difficult Run watershed revealed relatively uniform generation of flow per unit of watershed area, as well as spatial variation in water quality that is strongly related to land-use activities. Elevated nitrate concentrations were observed in a subset of monitoring sites that are inversely correlated with population density and positively correlated to the septic system density within each subwatershed. The majority of the elevated nitrate concentrations for these sites are hypothesized to be caused by nitrate leaching from septic systems, more so than homeowner fertilizer usage among these subwatersheds that have lower population densities than other parts of the watershed. Nitrate isotope data, temporal patterns in the water-quality data, mass-balance computations, and a separate land-use analysis all generally indicate that leachate from septic systems was the likely source of the elevated nitrate. Another group of water-quality sites have relatively low nitrogen concentrations, are located in areas that are served by city sewer lines, and have experienced stream restoration activities. A final group of sites drained the areas with the highest imperviousness and had strongly elevated specific conductance, chloride, and sodium, which were likely caused by a combination of road salting and other anthropogenic sources draining these urbanized areas in the watershed. A fourth group of sites represents a mixture of water sources and had water quality similar to that at the Difficult Run streamgage. Analysis of the nitrate isotope data generally indicates a broad range of composition indicative of mixed natural and anthropogenic nitrogen sources. Implementation of conservation practices increased in the Difficult Run watershed during the study period, and while a broad range of practice types was implemented, the most common practices included stream restoration. While the implementation of these conservation practices is encouraging, the cumulative effect of these practices probably will not be detected in Difficult Run water quality for several years.

Maryland, Pennsylvania, Virginia

Sediment lithology and borehole erosion testing, American and Sacramento Rivers, California

Executive Summary A field investigation intended to measure the potential for erosion of sediments beside the American and Sacramento Rivers near Sacramento, California, is described. The study featured two primary components: (1) drilling and soil sampling to reveal lithology, down to depths matching the local river thalweg, where possible, and (2) borehole erosion tests (BETs) as described by Briaud and others (2017) at many of the same locations. The latter test involved drilling a vertical hole, measuring its diameter profile, inserting a hollow drilling rod to almost the bottom of the hole, and pumping fluid through the drilling rod at a known discharge for a chosen time interval. The hole was then resurveyed to establish an erosion rate (change in borehole radius divided by duration of flow event) as a function of depth, and the test was repeated. This test was performed with water as the erosive fluid at 12 locations, with 1 test repeated with drilling mud. Lithology holes were drilled at these same locations and an additional five locations. Drilling operations took place on river left and river right on the American River and river left (left bank, when looking downstream) on the Sacramento River. The drilling to acquire sediment samples and reveal lithology involved the use of a mobile drilling rig equipped with a 6-inch (in.) auger, a 140-pound pneumatic hammer to drive split spoon and Calmod samplers, and a piston to push Shelby tube samplers to obtain samples of clayey material. Blow count (hammer blows per 6-in. sampler advance) was recorded while sampling, and the process was logged using standard U.S. Army Corps of Engineers (USACE), Sacramento District procedures. Sediment samples were identified and described in the field per ASTM D2488 and then delivered to a USACE laboratory and to Texas A&M University for additional laboratory analysis. The BETs were performed with the same drilling rig that performed the drilling for definition of lithology. In most instances, tests were limited to regions above the water table, to avoid slumping of the borehole and heaving sands pushing into the hole. Most of the tests featured sediments that were primarily silty sand or sandy silt. The testing procedure involved comparing borehole profiles before and after passing an assumed constant discharge through a drilling rod to the bottom of the drilled hole. Discharge and water losses were logged during the testing procedure, and water losses into the walls of the drilled hole were typically less than 5 percent of the introduced volume. For the tests performed with water, the coefficient of variation of the discharge ranged from 4.5 to 28 percent, with a mean of 13 percent, but the mean discharge appeared to be reasonably steady over the typical test duration of 10–30 minutes. It was thus assumed that discharge was constant and water losses during the tests were neglected. Coefficients of variation of the discharge for the three tests performed with drilling mud were much higher (20–50 percent), but erosion rates were much smaller. Resolution of the borehole caliper-reported diameter was 0.1 in. and several of the tests lasted for 10 minutes. With boreholes measured twice, before and after each test, and averaged, these numbers correspond to an apparent erosion rate (radius change divided by test duration) of 0.3 inches per hour (in/hr), which is a theoretical lower bound on what could be measured with this approach and equipment. In practice, 0.5 in/hr appears to be a more realistic lower bound on the detectable erosion rate, based on inspection of computed changes and erosion rates. Three flow speeds (5, 8, and 12 feet per second; ft/s) were targeted for the tests. Because of equipment limitations, it was not possible in the field to reach an average of 12 ft/s throughout any given borehole, although much higher flow speeds were reached locally in some cases. Most tests featured at least two different flow rates, and the borehole was typically surveyed at least twice for each condition, to allow averaging to reduce the influence of random diameter measurement errors. Errors arising from out-of-round boreholes appeared to be uncommon. Briaud and others (2017) recommend stepped increases in the flow rate during a borehole test. This approach was taken during initial testing but proved to be problematic. The drilled hole would be enlarged by the first (smaller) discharge, and then it would be difficult to reach the desired higher flow speed because of the larger annulus between the drilled hole and the drilling rod that supplied the water for testing. This was largely solved by starting with a high discharge and, in many cases, maintaining it for subsequent tests with the average flow speed decreasing as the hole enlarged. Several different measures of erosion rate were computed and investigated by comparison to lithological profiles. The vertically averaged erosion rate for each hole was computed, but this result does not reveal vertical variability of erodibility; and the mean flow speed within the hole is not a good representation of the speed when attempting to determine a relationship between erosion rate and flow speed. Instead, for each 6-inch layer within the hole, vertically averaged erosion rates and local flow speeds were computed and plotted. Where possible, the soil type for each layer was identified. For later laboratory analysis, project protocol dictated collection of Shelby tube samples whenever clay was encountered. Plots of erosion rate versus flow speed displayed scatter that indicate that several other factors influence the erosion potential of the soil. Blow count was not a good predictor variable; it is better correlated with soil type than erodibility. Soils were classified as sand, silt, or clay, depending on which soil type dominated within a sample. In general, those classified as sand and silt did not reveal clear patterns allowing erosion rate to be computed directly from flow speed, but the test results define the range and bounds on the erosion rate. Results for clay were slightly clearer with the erosion rate increasing with flow speed, once a threshold had been reached. In this case, the erosion rate appeared to change near a speed of 7 ft/s; above this threshold, erosion rates jumped from less than 2 in/hr to greater than 3 in/hr. Even for soils with similar classifications, large differences in erodibility were observed between sites and in different layers within an individual hole. One potential means of dealing with this problem would be to perform more tests at each site to allow establishment of relationships between flow speed and erodibility for individual layers within a borehole. The maximum number of tests performed at a site in this study was four, but in some cases, results are available for only one or two flow events. Comparison of data to a set of Erosion Function Apparatus tests that provide better resolution of the vertical variation in the erosion rate versus flow speed relationship would allow further investigation of this idea. It was hypothesized that drilling mud could expand the utility of the test in soft sands by reducing the likelihood of slumping that would be interpreted as erosion. The one test that was performed with drilling mud indicated that it greatly reduced the erosion rate of the soils encountered. It yielded very different results from the test performed at the same site with water. Erosion rate is often expressed as a function of shear stress applied to a soil. In order to compute shear stress on the walls of the drilled hole, one must assume a form for the relationship between flow speed and shear stress and select a friction factor that is often estimated empirically from head loss, observed water-surface profiles, surface roughness, or other data not available in this report. One methodology for computing shear stress from flow speed is discussed in this report, but the test results have been presented in terms of erosion rate versus flow speed to avoid assuming values that are not verifiable via the field data collected in this study. Erosion rate was computed from directly measured values (sequential borehole profiles) and flow speed was computed directly from measured quantities (discharge and borehole geometry). The BET has seen limited application, primarily in clayey soils, whereas most of the soils encountered in this study were primarily sand or silt. The objective of the BET is to determine the erodibility of in situ soil below the ground or riverbed surface. The BET is simple in principle and has the advantage of revealing erodibility of in situ sediments below the ground or riverbed surface; it appears to be very useful in clayey soils, based on previously published work, but is more difficult to apply in sandy soils where slumping and water losses within the hole during testing are more likely to occur. The BET did reveal a large variation in the results both laterally and vertically, even for the same soil-type classification. It is thus recommended that the results be applied considering these spatial variations rather than attempting to universally assign an erosion-rate relationship to a particular soil type. Results have been provided showing the results by site and by sediment classification (sand, silt, and clay), to allow either approach. Where possible, it is important to rely on site-specific results because the erosion-rate relationship for a given soil type varied by site. Data collected during this project have been made publicly available online via the U.S. Geological Survey (USGS) Sciencebase database. The measured borehole profiles, discharge, lithology log sheets, and photos are available in the data release that accompanies this report (see Work and Livsey (2019) in the “Selected References” section for the appropriate link).

California