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A steady-state groundwater-flow model described in Scientific Investigations Report 2013-5160, ”Numerical Simulation of the Groundwater-Flow System in Chimacum Creek Basin and Vicinity, Jefferson County, Washington” was developed to evaluate potential future impacts of growth and of water-management strategies on water resources in the Chimacum Creek Basin. This supplement to that report describes the unsuccessful attempt to perform a calibration to transient conditions on the model. The modeled area is about 64 square miles on the Olympic Peninsula in northeastern Jefferson County, Washington. The geologic setting for the model area is that of unconsolidated deposits of glacial and interglacial origin typical of the Puget Sound Lowlands. The hydrogeologic units representing aquifers are Upper Aquifer (UA, roughly corresponding to recessional outwash) and Lower Aquifer (LA, roughly corresponding to advance outwash). Recharge from precipitation is the dominant source of water to the aquifer system; discharge is primarily to marine waters below sea level and to Chimacum Creek and its tributaries. The model is comprised of a grid of 245 columns and 313 rows; cells are a uniform 200 feet per side. There are six model layers, each representing one hydrogeologic unit: (1) Upper Confining unit (UC); (2) Upper Aquifer unit (UA); (3) Middle Confining unit (MC); (4) Lower Aquifer unit (LA); (5) Lower Confining unit (LC); and (6) Bedrock unit (OE). The transient simulation period (October 1994–September 2009) was divided into 180 monthly stress periods to represent temporal variations in recharge, discharge, and storage. An attempt to calibrate the model to transient conditions was unsuccessful due to instabilities stemming from oscillations in groundwater discharge to and recharge from streamflow in Chimacum Creek. The model as calibrated to transient conditions has mean residuals and standard errors of 0.06 ft ±0.45 feet for groundwater levels and 0.48 ± 0.06 cubic feet per second for flows. Although the expected seasonal trends were observed in model results, the typical observed annual variation of groundwater levels of about 2 feet was not. Streamflow at the most downstream observation point was about three times larger than simulated streamflow. Because the transient version of the model proved inherently unstable, it was not used to simulate forecast conditions for alternate hydrologic or anthropogenic changes. Adaptation of alternate stream simulation packages, such as RIV, or newer versions of MODFLOW, such as MODFLOW-NWT, could possibly assist with achieving calibration to transient conditions.
During 2005, the U.S. Geological Survey (USGS) developed, calibrated, and validated a multidimensional flow model for simulating streamflow in the white sturgeon spawning habitat of the Kootenai River in Idaho. The model was developed as a tool to aid understanding of the physical factors affecting quality and quantity of spawning and rearing habitat used by the endangered white sturgeon (Acipenser transmontanus) and for assessing the feasibility of various habitat-enhancement scenarios to re-establish recruitment of white sturgeon. At the request of the Kootenai Tribe of Idaho, the USGS extended the two-dimensional flow model developed in 2005 into a braided reach upstream of the current white sturgeon spawning reach. Many scientists consider the braided reach a suitable substrate with adequate streamflow velocities for re-establishing recruitment of white sturgeon. The 2005 model was extended upstream to help assess the feasibility of various strategies to encourage white sturgeon to spawn in the reach. At the request of the Idaho Department of Fish and Game, the USGS also extended the two-dimensional flow model several kilometers downstream of the white sturgeon spawning reach. This modified model can quantify the physical characteristics of a reach that white sturgeon pass through as they swim upstream from Kootenay Lake to the spawning reach. The USGS Multi-Dimensional Surface-Water Modeling System was used for the 2005 modeling effort and for this subsequent modeling effort. This report describes the model applications and limitations, presents the results of a few simple simulations, and demonstrates how the model can be used to link physical characteristics of streamflow to the location of white sturgeon spawning events during 1994-2001. Model simulations also were used to report on the length and percentage of longitudinal profiles that met the minimum criteria during May and June 2006 and 2007 as stipulated in the U.S. Fish and Wildlife Biological Opinion.
The U.S. Geological Survey (USGS), in cooperation with the Bureau of Land Management (BLM), estimated streamflow statistics for stream segments designated “Wild,” “Scenic,” or “Recreational” under the National Wild and Scenic Rivers System in the Owyhee Canyonlands Wilderness in southwestern Idaho. The streamflow statistics were used by the BLM to develop and file a draft, federal reserved water right claim to protect federally designated “outstanding remarkable values” in the Jarbidge River. The BLM determined that the daily mean streamflow equaled or exceeded 20, 50, and 80 percent of the time during bimonthly periods (two periods per month) and the bankfull (66.7-percent annual exceedance probability) streamflow are important thresholds for maintaining outstanding remarkable values. Although streamflow statistics for the Jarbidge River below Jarbidge, Nevada (USGS 13162225) were published previously in 2013 and used for the draft water right claim, the BLM and USGS have since recognized the need to refine streamflow statistics given the approximate 40 river mile distance and intervening tributaries between the original point of estimation (USGS 13162225) and at the mouth of the Jarbidge River, which is the downstream end of the Wild and Scenic River segment. A drainage-area-ratio method was used in 2013 to estimate bimonthly exceedance probability streamflow statistics at the mouth of the Jarbidge River based on available streamgage data on the Jarbidge and East Fork Jarbidge Rivers. The resulting bimonthly streamflow statistics were further adjusted using a scaling factor calculated from a water balance on streamflow statistics calculated for the Bruneau and East Fork Bruneau Rivers and Sheep Creek. The final, adjusted bimonthly exceedance probability and bankfull streamflow statistics compared well with available verification datasets (including discrete streamflow measurements made at the mouth of the Jarbidge River) and are considered the best available estimates for streamflow statistics in the Jarbidge Wild and Scenic River segment.
The Kootenai Tribe of Idaho, in cooperation with local, State, Federal, and Canadian agency co-managers and scientists, is assessing the feasibility of a Kootenai River habitat restoration project in Boundary County, Idaho. The restoration project is focused on recovery of the endangered Kootenai River white sturgeon (Acipenser transmontanus) population, and simultaneously targets habitat-based recovery of other native river biota. River restoration is a complex undertaking that requires a thorough understanding of the river and floodplain landscape prior to restoration efforts. To assist in evaluating the feasibility of this endeavor, the U.S. Geological Survey developed an updated one-dimensional hydraulic model of the Kootenai River in Idaho between river miles (RMs) 105.6 and 171.9 to characterize the current hydraulic conditions. A previously calibrated model of the study area, based on channel geometry data collected during 2002 and 2003, was the basis for this updated model. New high-resolution bathymetric surveys conducted in the study reach between RMs 138 and 161.4 provided additional detail of channel morphology. A light detection and ranging (LIDAR) survey was flown in the Kootenai River valley in 2005 between RMs 105.6 and 159.5 to characterize the floodplain topography. Six temporary gaging stations installed in 2006-08 between RMs 154.1 and 161.2, combined with five permanent gaging stations in the study reach, provided discharge and water-surface elevations for model calibration and verification. Measured discharges ranging from about 4,800 to 63,000 cubic feet per second (ft 3 /s) were simulated for calibration events, and calibrated water-surface elevations ranged from about 1,745 to 1,820 feet (ft) throughout the extent of the model. Calibration was considered acceptable when the simulated and measured water-surface elevations at gaging stations differed by less than (+/-)0.15 ft. Model verification consisted of simulating 10 additional events with measured discharges ranging from about 4,900 to 52,000 ft 3 /s, and comparing simulated and measured water-surface elevations at gaging stations. Average water-surface-elevation error in the verification simulations was 0.05 ft, with the error ranging from -1.17 to 0.94 ft over the range of events and gaging stations. Additional verification included a graphical comparison of measured average velocities that range from 1.0 to 6.2 feet per second to simulated velocities at four sites within the study reach for measured discharges ranging from about 7,400 to 46,600 ft 3 /s. The availability of high-resolution bathymetric and LIDAR data, along with the additional gaging stations in the study reach, allowed for more detail to be added to the model and a more thorough calibration, sensitivity, and verification analysis to be conducted. Model resolution and performance is most improved between RMs 140 and 160, which includes the 18.3-mile reach of the Kootenai River white sturgeon critical habitat.
A previous collaborative effort between the U.S. Geological Survey and the Bureau of Reclamation resulted in a watershed model for four watersheds that discharge into Potholes Reservoir, Washington. Since the model was constructed, two new meteorological sites have been established that provide more reliable real-time information. The Bureau of Reclamation was interested in incorporating this new information into the existing watershed model developed in 2009, and adding measured snowpack information to update simulated results and to improve forecasts of runoff. This report includes descriptions of procedures to aid a user in making model runs, including a description of the Object User Interface for the watershed model with details on specific keystrokes to generate model runs for the contributing basins. A new real-time, data-gathering computer program automates the creation of the model input files and includes the new meteorological sites. The 2009 watershed model was updated with the new sites and validated by comparing simulated results to measured data. As in the previous study, the updated model (2012 model) does a poor job of simulating individual storms, but a reasonably good job of simulating seasonal runoff volumes. At three streamflow-gaging stations, the January 1 to June 30 retrospective forecasts of runoff volume for years 2010 and 2011 were within 40 percent of the measured runoff volume for five of the six comparisons, ranging from -39.4 to 60.3 percent difference. A procedure for collecting measured snowpack data and using the data in the watershed model for forecast model runs, based on the Ensemble Streamflow Prediction method, is described, with an example that uses 2004 snow-survey data.
This scientific investigations report describes an effort by the U.S. Geological Survey (USGS) that used research, monitoring data, and modeling to develop a methodology to assess both the current and future population-level consequences of wind energy development on species of birds and bats that are present in the United States during any part of their life cycle. The methodology is currently applicable to birds and bats, focuses primarily on the effects of collisions with turbines, and can be applied to any species that breeds in, migrates through, or otherwise uses any part of the United States. The methodology assesses species at the national and regional scales and identifies those species potentially in need of more detailed study, as well as those species that are likely at low risk from wind energy development. This approach is fundamentally different from existing methods focusing on impacts at individual facilities. This report supersedes USGS Scientific Investigations Report 2015–5066 by the same authors, which described a preliminary version of the methodology. Following reviews of the preliminary methodology by a panel of external experts, public comments, and additional internal review, the methodology was revised and finalized. The three components of the refined methodology described in this new report rely on publicly available fatality information, population estimates, species range maps, turbine location data, biological characteristics of species, and population models. First, three metrics are combined to determine direct and indirect relative effects from wind energy facilities to generate a list of species scores. Second, a generic population model estimates the expected change in population trend caused by the additive mortality from collisions with wind turbines. Third, the methodology combines an estimate of observed fatalities and an estimate of potential biological removal to assess the possibility of a decrease in population size. The latter two components are quantitative. In a test case, the methodology was used to analyze data for six bird species and three bat species. Components of the methodology are based on simplifying assumptions and require information that, for many species, may be sparse or unreliable or may require further study. These assumptions should be carefully considered when using outputs from the methodology. Increases in the quality of data for fatalities from collisions with wind turbines, species distributions, abundance, and demography will likely improve results for uses of the methodology. The methodology’s design identifies and prioritizes a subset of the bird and bat species that may experience population-level impacts from collisions with wind turbines, both currently and from future wind energy development in the United States. Results of an assessment using this methodology could focus future research to improve our understanding of those impacts and to guide avoidance and minimization strategies. In addition, this methodology can be used to identify species for more intensive demographic modeling or to highlight those species that may not require any additional research because effects of wind energy development on their populations are projected to be small. The effects of wind energy facilities on nine unidentified species used in the test case described in this report have not been assessed. Their data were simply used to show the application of the methodology to real-world data and the types of outputs it would produce.
Introduction Volcanic unrest can trigger appreciable change to surface waters such as streams, springs, and volcanic lakes. Magma degassing produces gases and soluble salts that are absorbed into groundwater that feeds streams and lakes. As magma ascends, the amount of heat and degassing will increase, and so will any related geochemical and thermal signal. Subsurface magma movement can cause pressurization that alters hydrostatic head and may induce groundwater discharge. Fluid-pressure changes have been linked to distal volcano-tectonic earthquakes (White and McCausland, 2016; Coulon and others, 2017) and phreatic eruptions (for example, Yamaoka and others, 2016). Clearly, changes in groundwater and surface waters are both indicators of unrest and clues to how and where magma is rising toward the surface. Where possible, it is prudent to incorporate real-time hydrologic data into multiparameter monitoring of restless volcanoes. Hydrologic dynamics can also be tracked by changes in groundwater levels that are commonly measured in shallow boreholes (see of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–K, 5 p., https://doi.org/10.3133/sir20245062k. ">chapter K , this volume, on boreholes; Hurwitz and Lowenstern, 2024). Although inferred to be common, relatively few volcano-hydrology anomalies are well documented, and many are essentially anecdotal (Newhall and others, 2001), reflecting the fact that high-resolution time series remain rare. Extreme examples include the 2008 eruption of Nevado del Huila, Colombia, where relatively minor phreatomagmatic eruptions were accompanied by expulsion of as much as 300 million cubic meters of groundwater from fissures high on the volcano (Worni and others, 2011), generating large lahars. Substantial decreases in flow rate from springs about 8 kilometers from the summit of Mayon Volcano, Philippines, have been noted before most eruptions in the 20th century (Newhall and others, 2001). Stream monitoring at Redoubt Volcano in 2009 allowed Werner and others (2012) to recognize that groundwater was unable to absorb (or scrub) the high flux of volcanic gas and that a high CO 2 /SO 2 precursor signal had been evident for 5 months prior to the eruption. A key to better interpreting hydrologic anomalies—or even identifying them—is therefore obtaining adequate baseline data. Most hydrologic monitoring at U.S. volcanoes has been accomplished by intermittent sampling surveys with annual or less frequent sampling (for example, https://hotspringchem.wr.usgs.gov/index.php ). More frequent sampling, however, generally is needed to establish reliable baselines. A recent hydrologic and hydrothermal monitoring experiment at 25 sites and 10 of the 12 level 4 (very high threat) volcanoes in the U.S. portion of the Cascade Range demonstrated that there is sufficient temporal variability in hydrothermal fluxes, even during quiescent periods, that one-time measurements will commonly have limited interpretive value (Crankshaw and others, 2018). Thus, surveys are best augmented with data from streamgages (for example, Evans and others, 2004; Bergfeld and others, 2008). Streamflow (water discharge) data allow measured temperature and specific conductance to be converted to heat and solute mass fluxes, which could be insightful parameters for detecting anomalous activity (McCleskey and others, 2012). At the Yellowstone Caldera, long-term monitoring of river solutes has allowed calculation of the chloride flux, a proxy for heat discharge (Hurwitz and others, 2007; McCleskey and others, 2016) from the subsurface magma. This is readily accomplished because data from streamgages are continuously recorded and archived by the U.S. Geological Survey (USGS) National Water Information System (NWIS) (USGS, 2024). Similar studies on stratovolcanoes or shield volcanoes would be scientifically useful, and yet are logistically challenging, requiring streamgages on numerous radial drainages complemented by either frequent manual sampling or numerous deployments of equipment to measure water temperature and specific conductance as a proxy for water chemistry. Another challenge is that some volcanic areas, especially shield volcanoes, are characterized by near-surface porous rocks and soils, such that surface streams are rare and replaced by distant, dilute large-volume springs with only a trace of any original volcanically sourced water (Manga, 2001; Hurwitz and others, 2021). Volcanic lakes are worthy of special attention for monitoring efforts, as their temperature and composition can provide evidence of increased flux of volatile-rich fluids from below. Quantifying changes in volatile and heat release from magma can be simpler in lakes than for volcanoes with radial drainages and no major lakes. Moreover, volcanic lakes pose a range of hazards themselves, including phreatomagmatic eruptions, debris flows, flank collapse, tsunamis, and toxic gas release (Mastin and Witter, 2000; Delmelle and others, 2015; Manville, 2015; Rouwet and others, 2015)—hazards that have historically been responsible for substantial loss of life at many volcanoes worldwide (Manville, 2015). Catastrophic CO 2 release at Lake Nyos, Cameroon, in 1986 suffocated about 1,750 people and about 3,500 livestock and was probably triggered by a large landslide into the gas-saturated lake (Kling and others, 1987; Evans and others, 1993). Gas-charged springs in Soda Bay within Clear Lake (California) have caused almost a dozen deaths to bathers in the past hundred years (ABC News, 2000). A 2005 example of lake overturn and abundant gas release was documented at Mount Chiginagak in Alaska (Schaefer and others, 2008) but did not result in any human casualties. Although thermally stratified lakes, which promote trapping of exsolved magmatic gas, tend to develop in tropical regions, the phenomenon can also arise where salinity creates meromixis (a condition in which a lake does not mix completely), as occurs in Mono Lake, California (Jellison and Melack, 1993; Jellison and others, 1998). If magma erupts or flows into a lake, the interaction between hot magma and cold water can be explosive (Mastin and others, 2004; Zimanowski and others, 2015) and substantially expand the area affected by the eruption. Another hazard is the breaching of crater rims by landslides triggered by volcanic and (or) seismic activity. Under some circumstances, substantial volumes of water can be displaced, leading to large floods and lahars. Late Holocene lake flooding from Aniakchak Crater in the Alaska Peninsula (Waythomas, 2022) and from Paulina Lake in Newberry Crater, Oregon (Chitwood and Jensen, 2000), caused by the failure of outlet sills, testify to the substantial hazards at lake-filled calderas. Several volcanic systems in the United States host lakes known to receive heat and gas from underlying magma. These lakes vary widely in area, depth, and chemical composition. Lakes are present at level 4 volcanoes, including Crater Lake and Newberry Volcano in Oregon; Yellowstone Caldera in Wyoming; Long Valley Caldera, Clear Lake volcanic field, Medicine Lake, and Salton Buttes in California; and Aniakchak Crater, Mount Katmai, Fisher Caldera, Mount Okmok, and Kaguyak Crater, among others, in Alaska. A water lake was present in Halemaʻumaʻu, the crater of Kīlauea, Hawai‘i (fig. F1), from October 2019 to December 2020. Level 3 volcanoes with lakes include Mono Lake volcanic field (Calif.), Mount Bachelor (Ore.), Ukinrek Maars and Mount Chiginagak (Alaska), and Soda Lake (Nevada). In addition, there are lakes at many levels 1 and 2 volcanoes. In the United States, there are no strongly acidic lakes that receive abundant input of magmatic gas, such as those found at Mount Ruapehu (New Zealand), Ijen and Kelud (Indonesia), and Poás (Costa Rica). Nevertheless, many contain fluids that provide clues to magmatic processes below. Since publication of a previous report on recommended instrumentation for volcano monitoring (Moran and others, 2008), continuous hydrologic monitoring has become increasingly feasible. However, changes in water pressure, temperature, and chemistry remain, in general, poorly studied phenomena at volcanoes (Sparks, 2003; National Academies of Sciences, Engineering, and Medicine, 2017). Recent efforts by the USGS have included the temporary study of Cascade Range volcanoes, which included frequent (15 minute to hourly) temporal sampling of temperature, depth, and conductivity (Crankshaw and others, 2018; Ingebritsen and Evans, 2019). At Yellowstone Caldera, many streamgages have now added thermistors and specific conductance sensors, allowing estimation of time-dependent chloride flux as a proxy for variations in subsurface heat flux (McCleskey and others, 2012, 2016). Efforts to better understand lakes have also accelerated, with bathymetric mapping and sampling carried out at several locations in the United States. Especially thorough work was done at Yellowstone Lake thanks to the Hydrothermal Dynamics of Yellowstone Lake (HD-YLAKE, https://hdylake.org ) project, funded primarily by the National Science Foundation. In addition to geophysical surveys and recovery of cores and other samples, HD-YLAKE investigations included remotely operated vehicle (ROV) investigations of hydrothermal vents on the lake floor (fig. F2). Data collected by the ROV provided a better understanding of the thermal and chemical influx from lake-bottom hydrothermal systems (Sohn and others, 2017). In this chapter, we focus on detecting changes in the chemistry, temperature, discharge, or water levels of streams, springs, and lakes that can be caused by seismicity, volumetric strains, or increases in gas flux associated with ascending magma. There is unavoidable overlap with other chapters of this report. Samples of water and gas can also be obtained in boreholes ( of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–K, 5 p., https://doi.org/10.3133/sir20245062k. ">chapter K , this volume; Hurwitz and Lowenstern, 2024), both shallow and deep. Gas monitoring ( of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–E, 11 p., https://doi.org/10.3133/sir20245062e.">chapter E , this volume; Lewicki and others, 2024) relies in part on samples from springs and wells, particularly where measurable gas plumes are absent. Water acts as a trigger and lubricant for landslides and sediment-rich floods, and so hydrology has obvious relevance for lahar monitoring, as discussed in of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–H, 6 p., https://doi.org/10.3133/sir20245062h. ">chapter H (this volume; Thelen and others, 2024). Shared situational awareness among scientists engaged in geophysical, gas, and hydrologic monitoring will improve overall understanding of the volcanic hazard.
Introduction Explosive eruptions create plumes of volcanic ash and gas that can rise more than 30,000 feet (9.1 kilometers [km]) above sea level within minutes of eruption onset. The resulting clouds disperse under prevailing winds and may cause hazardous conditions hundreds to thousands of kilometers from the volcano, including in international airspace. Rapid detection and characterization of explosive activity is vital to mitigate the wide-ranging effects of volcanic ash. Ashfall thicknesses as small as a millimeter or so on the ground can affect infrastructure, agriculture, and air quality, requiring extensive clean-up procedures (Schuster, 1981; Warrick and others, 1981, U.S. Geological Survey, 2022). Volcanic clouds also pose substantial threats to aircraft. Since 1953, 88 encounters between airplanes and ash clouds have been documented worldwide (International Civil Aviation Organization, 2015, appendix F), resulting in aircraft damage and, in 9 cases, engine failure (Guffanti and others, 2010). In 1982, two large passenger planes suffered complete engine failure owing to eruptions in Indonesia (Global Volcanism Program, 1982) and a similar incident occurred over Alaska in 1989 (Casadevall, 1994). In all three cases, they were able to restart some engine capability and land safely once they emerged from the ash clouds, although with substantial damage (Guffanti and others, 2010). The clear threat to aviation has led to establishment of nine Volcanic Ash Advisory Centers (VAAC) around the world to monitor and rapidly disseminate information about volcanic eruptions to the aviation community. U.S. Geological Survey (USGS) volcano observatories issue the Volcano Observatory Notice for Aviation that informs of preeruptive unrest or eruptive activity. When ash-producing eruptions do occur, volcano observatories work closely with their regional VAAC to ensure consistency and accuracy in eruption onset time, cloud altitude, ash production, and duration as reported in Volcanic Ash Advisories. Explosive volcanism in the United States and Commonwealth of the Northern Mariana Islands prompts 50–100 such advisories in any given year (table J1). This collaborative effort is greatly aided by USGS detection and monitoring of eruption clouds to ensure a timely and coordinated response. To support these efforts to provide guidance on ash transport and fallout, the USGS developed the Ash3d volcanic ash dispersion model ( https://vsc-ash.wr.usgs.gov/ash3d-gui ) (Schwaiger and others, 2012). Automated simulations are run daily by the USGS for volcanoes that are in elevated states of unrest, and in response mode when eruptions occur. During eruptions, the model output is provided to local National Weather Service Weather Forecast Offices to guide them in the issuance of their information products (such as special weather statements, ashfall advisories, or ashfall warnings), as well as to State and local governments and the public. Characterization of the eruption source is needed to estimate the parameters used to initialize the Ash3d model, and by the Anchorage and Washington VAACs to initialize other dispersion models that inform forecasts for the airborne volcanic cloud. The source parameters that can be provided by observation during an eruption include eruption start time, eruption cloud height over time, and eruption duration. Other, nonobservable source parameters, such as mass eruption rate and grain-size distribution, are based on empirical correlations and study of historical deposits. The goal is to provide a time series of cloud heights, mass eruption rates, and particle-size distributions that accurately reflects current conditions. When feasible, the USGS also provides guidance on the nature of ongoing eruptions and forecasts future activity using petrologic monitoring of collected tephra samples. The aims of providing accurate observable parameters are achieved through analysis of (1) near-real-time meteorological satellite data, (2) ground-based cameras (see of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–G, 11 p., https://doi.org/10.3133/sir20245062g.">chapter G , this volume; Orr and others, 2024), (3) weather radar, (4) volcanic lightning detection, and (5) ground-based ash sensors and sampling. Explosive eruptions can be detected by a variety of geophysical monitoring, including infrasound (see of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–C, 11 p., https://doi.org/10.3133/sir20245062c.">chapter C , this volume; Lyons and others, 2024) and seismicity (see of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–B, 9 p., https://doi.org/10.3133/sir20245062b.">chapter B , this volume; Thelen and others, 2024). However, those methods cannot quantify the altitude, ash content, and dispersal dynamics of resulting volcanic clouds. Ideally, all available sources of monitoring data are synthesized to develop a coherent understanding of eruptive activity. The guidance summarized here provides a framework for characterizing volcanic clouds in the atmosphere and tracking the evolution of explosive eruption dynamics.
This report updates groundwater-storage and groundwater-level trends presented in U.S. Geological Survey (USGS) Scientific Investigations Report 2019–5060, in the Big Chino Subbasin, Yavapai County, Arizona. This earlier geophysical investigation of groundwater-storage change in the Big Chino Subbasin was conducted by the U.S. Geological Survey, in cooperation with the City of Prescott, the Town of Prescott Valley, and the Salt River Project from 2010 to 2017 to understand groundwater-level and groundwater-storage changes. Conclusions were based on precipitation, streamflow, groundwater level, and repeat microgravity data; the latter is a direct measurement of groundwater-storage change. This report focuses on the southern part of the Big Chino Subbasin for water years 2018–2021. These more recent data show relatively small changes in groundwater storage, consistent with the earlier monitoring presented in U.S. Geological Survey Scientific Investigations Report 2019–5060. In the Big Chino Water Ranch area, water levels have increased gradually owing to discontinued pumping for irrigation during summer months, and an in-channel recharge event in summer 2021. In the Paulden, Arizona, area, gradual water level declines have continued a downward trend that started in the 1990s. Seasonal variation is present in the Paulden area, with higher water levels in the winter months when pumping for irrigation and agricultural use is reduced. Two wells showed groundwater-level increases consistent with in-channel recharge in 2018 and 2021, whereas groundwater levels in a well screened in the deeper, confined to semi-confined carbonate aquifer showed no such discrete recharge events. In the area west of Big Chino Wash and east of the Juniper Mountains and Santa Maria Mountains, groundwater levels continued long-term declines, but storage changes were minimal.
Pueblo Reservoir is one of southeastern Colorado's most valuable water resources. The reservoir provides irrigation, municipal, and industrial water to various entities throughout the region. The reservoir also provides flood control, recreational activities, sport fishing, and wildlife enhancement to the region. The Bureau of Reclamation is working to meet its goal to issue a Final Environmental Impact Statement (EIS) on the Southern Delivery System project (SDS). SDS is a regional water-delivery project that has been proposed to provide a safe, reliable, and sustainable water supply through the foreseeable future (2046) for Colorado Springs, Fountain, Security, and Pueblo West. Discussions with the Bureau of Reclamation and the U.S. Geological Survey led to a cooperative agreement to simulate the hydrodynamics and water quality of Pueblo Reservoir. This work has been completed and described in a previously published report, U.S. Geological Survey Scientific Investigations Report 2008-5056. Additionally, there was a need to make comparisons of simulated hydrodynamics and water quality for projected demands associated with the various EIS alternatives and plans by Pueblo West to discharge treated water into the reservoir. Plans by Pueblo West are fully independent of the SDS project. This report compares simulated hydrodynamics and water quality for projected demands in Pueblo Reservoir resulting from changes in inflow and water quality entering the reservoir, and from changes to withdrawals from the reservoir as projected for the year 2046. Four of the seven EIS alternatives were selected for scenario simulations. The four U.S. Geological Survey simulation scenarios were the No Action scenario (EIS Alternative 1), the Downstream Diversion scenario (EIS Alternative 2), the Upstream Return-Flow scenario (EIS Alternative 4), and the Upstream Diversion scenario (EIS Alternative 7). Additionally, the results of an Existing Conditions scenario (water years 2000 through 2002) were compared to the No Action scenario (projected demands in 2046) to assess changes in water quality over time. All scenario modeling used an external nutrient-decay model to simulate degradation and assimilation of nutrients along the riverine reach upstream from Pueblo Reservoir. Reservoir modeling was conducted using the U.S. Army Corps of Engineers CE-QUAL-W2 two-dimensional water-quality model. Lake hydrodynamics, water temperature, dissolved oxygen, dissolved solids, dissolved ammonia, dissolved nitrate, total phosphorus, algal biomass, and total iron were simulated. Two reservoir site locations were selected for comparison. Results of simulations at site 3B were characteristic of a riverine environment in the reservoir while results at site 7B (near the dam) were characteristic of the main body of the reservoir. Simulation results for the epilimnion and hypolimnion at these two sites also were evaluated and compared. The simulation results in the hypolimnion at site 7B were indicative of the water quality leaving the reservoir. Comparisons of the different scenario results were conducted to assess if substantial differences were observed between selected scenarios. Each of the scenarios was simulated for three contiguous years representing a wet, average, and dry annual hydrologic cycle (water years 2000 through 2002). Additionally, each selected simulation scenario was evaluated for differences in direct- and cumulative-effects on a particular scenario. Direct effects are intended to isolate the future effects of the scenarios. Cumulative effects are intended to evaluate the effects of the scenarios in conjunction with all reasonably foreseeable future activities in the study area. Comparisons between the direct- and cumulative-effects analyses indicated that there were not large differences in the results between most of the simulation scenarios and, as such, the focus of this report was on results for the direct-effects analysis. Addi
Pueblo Reservoir is one of southeastern Colorado's most valuable water resources. The reservoir provides irrigation, municipal, and industrial water to various entities throughout the region. The reservoir also provides flood control, recreational activities, sport fishing, and wildlife enhancement to the region. The Southern Delivery System (SDS) project is a regional water-delivery project that has been proposed to provide a safe, reliable, and sustainable water supply through the foreseeable future (2046) for Colorado Springs, Fountain, Security, and Pueblo West. Discussions with the Bureau of Reclamation and the U.S. Geological Survey led to a cooperative agreement to simulate the hydrodynamics and water quality of Pueblo Reservoir. This work has been completed and described in a previously published report, U.S. Geological Survey Scientific Investigations Report 2008-5056. Additionally, there was a need to make comparisons of simulated hydrodynamics and water quality for projected demands associated with the various Environmental Impact Statements (EIS) alternatives and plans by Pueblo West to discharge treated wastewater into the reservoir. Wastewater plans by Pueblo West are fully independent of the SDS project. This report compares simulated hydrodynamics and water quality for projected demands in Pueblo Reservoir resulting from changes in inflow and water quality entering the reservoir, and from changes to withdrawals from the reservoir as projected for the year 2046. Four of the seven EIS alternatives were selected for scenario simulations. The four U.S. Geological Survey simulation scenarios were the No Action scenario (EIS Alternative 1), the Downstream Diversion scenario (EIS Alternative 2), the Upstream Return-Flow scenario (EIS Alternative 4), and the Upstream Diversion scenario (EIS Alternative 7). Additionally, the results of an Existing Conditions scenario (year 2006 demand conditions) were compared to the No Action scenario (projected demands in 2046) to assess changes in water quality over time. All scenario modeling used an external nutrient-decay model to simulate degradation and assimilation of nutrients along the riverine reach upstream from Pueblo Reservoir. Reservoir modeling was conducted using the U.S. Army Corps of Engineers CE-QUAL-W2 two-dimensional water-quality model. Lake hydrodynamics, water temperature, dissolved oxygen, dissolved solids, dissolved ammonia, dissolved nitrate, total phosphorus, algal biomass, and total iron were simulated. Two reservoir site locations were selected for comparison. Results of simulations at site 3B were characteristic of a riverine environment in the reservoir, whereas results at site 7B (near the dam) were characteristic of the main body of the reservoir. Simulation results for the epilimnion and hypolimnion at these two sites also were evaluated and compared. The simulation results in the hypolimnion at site 7B were indicative of the water quality leaving the reservoir. Comparisons of the different scenario results were conducted to assess if substantial differences were observed between selected scenarios. Each of the scenarios was simulated for three contiguous years representing a wet, average, and dry annual hydrologic cycle (water years 2000 through 2002). Additionally, each selected simulation scenario was evaluated for differences in direct and cumulative effects on a particular scenario. Direct effects are intended to isolate the future effects of the scenarios. Cumulative effects are intended to evaluate the effects of the scenarios in conjunction with all reasonably foreseeable future activities in the study area. Comparisons between the direct- and cumulative-effects analyses indicated that there were not large differences in the results between most of the simulation scenarios, and, as such, the focus of this report was on results for the direct-effects analysis. Additionally, the differences between simulation results generally were
This report, chapter A of Scientific Investigations Report 2016–5089, provides an overview of the U.S. Geological Survey (USGS) Sagebrush Mineral-Resource Assessment (SaMiRA). The report also describes the methods, procedures, and voluminous fundamental reference information used throughout the assessment. Data from several major publicly available databases and other published sources were used to develop an understanding of the locatable, leaseable, and salable mineral resources of this vast area. This report describes the geologic, mineral-occurrence, geochemical, geophysical, remote-sensing, and Bureau of Land Management mineral-case-status data used for the assessment, along with the methods for evaluating locatable mineral-resource potential. The report also discusses energy-resource data (oil and gas, coal, and geothermal) used in the assessment. Appendixes include summary descriptive mineral-deposit models that provide the criteria necessary to assess for the pertinent locatable minerals and market-demand commodity profiles for locatable mineral commodities relevant to the project. Datasets used in the assessment are available as USGS data releases.
Errata **September 28, 2018: The purpose of a USGS Open-file report (OFR) is dissemination of information that must be released immediately to fill a public need or information that is not sufficiently refined to warrant publication in one of the other USGS series. As part of that refinement process, an error was discovered in one of the input data sets of the Rio Grande Transboundary Integrated Hydrologic Model (RGTIHM) that this OFR was based upon. The error involved the assignment of storage properties to “phantom cells.” Phantom cells are required for most variants of MODFLOW that use a structured finite-difference grid when individual stratigraphic layers are represented as separate layers. Using phantom cells is a common practice that allows separate model layers to be maintained without having to combine stratigraphic layers into equivalent model layers or to use an unstructured grid. Typically, phantom cell horizontal hydraulic conductivities and storage properties are set to a small number and vertical hydraulic conductivities are set to a number large enough to allow vertical flow between the vertically adjacent layers. In the RGTIHM, the specific storage properties of the phantom cells for the upper (RGTIHM layers 3 and 4), middle (RGTIHM layers 5 and 6), and lower (RGTIHM layers 7 and 8) members of the Santa Fe Group were inadvertently assigned a value of 1 feet -1 . The revision of these specific storage values to a small number (1.0 x 10 -09 feet -1 ) required additional trial-and-error model calibration and a new sensitivity analysis. After calibration, the overall model fit remained similar to the fit described in the OFR, but the fit for many individual features such as project water available for diversions at the American Canal and Acequia Madre improved due to the reduction in flow coming from lower layers. Overall, there is still an average net depletion of groundwater flow, and the conclusions of the report are not changed. The revised average annual groundwater flow depletion simulated for the period 1953-2014 is -1,480 acre-feet/year for the entire model region, and -3,660 acre-feet/year for the portion of the model in the United States. The final version of the model will be the basis of the USGS Scientific Investigations Report that will supersede this OFR. An updated Model Archive of RGTIHM is available upon request to the USGS California Water Science Center. The corrected version of the model WAS the basis for the USGS Scientific Investigations Report that SUPERSEDED this Open-File Report.** Abstract Changes in population, agricultural development and practices (including shifts to more water-intensive crops), and climate variability are increasing demands on available water resources, particularly groundwater, in one of the most productive agricultural regions in the Southwest—the Rincon and Mesilla Valley parts of Rio Grande Valley, Doña Ana and Sierra Counties, New Mexico, and El Paso County, Texas. The goal of this study was to produce an integrated hydrological simulation model to help evaluate water-management strategies, including conjunctive use of surface water and groundwater for historical conditions, and to support long-term planning for the Rio Grande Project. This report describes model construction and applications by the U.S. Geological Survey, working in cooperation and collaboration with the Bureau of Reclamation. This model, the Rio Grande Transboundary Integrated Hydrologic Model, simulates the most important natural and human components of the hydrologic system, including selected components related to variations in climate, thereby providing a reliable assessment of surface-water and groundwater conditions and processes that can inform water users and help improve planning for future conditions and sustained operations of the Rio Grande Project (RGP) by the Bureau of Reclamation. Model development included a revision of the conceptual model of the flow system, construction of a Transboundary Rio Grande Watershed Model (TRGWM) water-balance model using the Basin Characterization Model (BCM), and construction of an integrated hydrologic flow model with MODFLOW-One-Water Hydrologic Flow Model (referred to as One Water). The hydrologic models were developed for and calibrated to historical conditions of water and land use, and parameters were adjusted so that simulated values closely matched available measurements (calibration). The calibrated model was then used to assess the use and movement of water in the Rincon Valley, Mesilla Basin, and northern part of the Conejos-Médanos Basin, with the entire region referred to as the “Transboundary Rio Grande” or TRG. These tools provide a means to understand hydrologic system response to the evolution of water use in the region, its availability, and potential operational constraints of the RGP. The conceptual model identified surface-water and groundwater inflows and outflows that included the movement and use of water both in natural and in anthropogenic systems. The groundwater-flow system is characterized by a layered geologic sedimentary sequence combined with the effects of groundwater pumping, operation of the RGP, natural runoff and recharge, and the application of irrigation water at the land surface that is captured and reused in an extensive network of canals and drains as part of the conjunctive use of water in the region. Historical groundwater-level fluctuations followed a cyclic pattern that were aligned with climate cycles, which collectively resulted in alternating periods of wet or dry years. Periods of drought that persisted for one or more years are associated with low surface-water availability that resulted in higher rates of groundwater-level decline. Rates of groundwater-level decline also increased during periods of agricultural intensification, which necessitated increasing use of groundwater as a source of irrigation water. Agriculture in the area was initially dominated by alfalfa and cotton, but since 1970 more water-intensive pecan orchards and vegetable production have become more common. Groundwater levels substantially declined in subregions where drier climate combined with increased demand, resulting in periods of reduced streamflows. Most of the groundwater was recharged in the Rio Grande Valley floor, and most of the pumpage and aquifer storage depletion was in Mesilla Basin agricultural subregions. A cyclic imbalance between inflows and outflows resulted in the modeled cyclic depletion (groundwater withdrawals in excess of natural recharge) of the groundwater basin during the 75-year simulation period of 1940–2014. Changes in groundwater storage can vary considerably from year to year, depending on land use, pumpage, and climate conditions. Climatic drivers of wet and dry years can greatly affect all inflows, outflows, and water use. Although streamflow and, to a minor extent, precipitation during inter-decadal wet-year periods replenished the groundwater historically, contemporary water use and storage depletion could have reduced the effects of these major recharge events. The average net groundwater flow-rate deficit for 1953–2014 was estimated to be about 8,990 acre-feet per year.
Extreme flooding in the Missouri River in 2011, followed by a year of more typical streamflows in 2012, allowed the sediment-transport regime to be compared between the unprecedented conditions of 2011 and the year immediately following the flooding. As part of a cooperative effort between the U.S. Geological Survey and the U.S. Army Corps of Engineers, this report follows up U.S. Geological Survey Scientific Investigations Report 2013–5006 by comparing sediment transport between years and among sampling sites spanning the Garrison Segment in North Dakota, the Gavins Point Segment downstream from Lewis and Clark Lake, and a part of the Channelized Segment along the Nebraska-Iowa border. Suspended sediment, bed material, bedload, and streamflow data from June 2011 through November 2012 were designated as “measured” total loads, wash loads, and bed-material loads; and, alternatively, were applied to the Modified-Einstein Procedure to compute sediment loads that were designated as “estimated” total loads. Beyond the expected result that sediment loads were much lower during typical streamflows than those measured during the flooding, the measured data indicated some localized sediment-transport processes for further examination. Extreme and prolonged flooding can temporarily deplete sediment supplies locally, and evidence indicating such depletion was present at some sites. Unexpectedly high bed-material loads in the Gavins Point Segment may reflect episodic bar erosion just upstream from the sampling site. The relative contribution of bedload was typically 10 percent or less of the total load during the flooding. Following the flooding, this relative amount increased at some sites but not others, the reasons for which are possibly related to differences in stream velocity. Ultimately, the bedload decreased as it entered the Channelized Segment because of increased velocity and the turbulent mixing ability of the river as compared to the Gavins Point Segment. This turbulent mixing may also convert bed-material load into wash load, thereby rendering those sediments unavailable for creating sandbars and other bedforms. Though some of the sampling data support this premise, it was not consistently manifested by differences between the sediment load of the two segments during typical-streamflow conditions. The Modified-Einstein Procedure tended to predict greater total-sediment loads when compared to measured values. These differences may be the result of sediment deficits in the Missouri River that lead to an overprediction by the Modified-Einstein Procedure, the unsampled zone above the streambed that leads to an underprediction by the suspended sampler, or general uncertainty in the sampling approach. The differences between total-sediment load obtained through measurements and that estimated from applied theoretical procedures such as the Modified-Einstein Procedure pose a challenge for reliably characterizing total-sediment transport. Though it is not clear which of the two techniques is more accurate, the general tendency of the two to be within an order of magnitude of one another may be adequate for many sediment studies.
These datasets were compiled in support of U.S. Geological Survey Scientific-Investigations Report 2010-5082-Hydrogeology and Steady-State Numerical Simulation of Groundwater Flow in the Lost Creek Designated Ground Water Basin, Weld, Adams, and Arapahoe Counties, Colorado. The datasets were developed by the U.S. Geological Survey in cooperation with the Lost Creek Ground Water Management District and the Colorado Geological Survey. The four datasets are described as follows and methods used to develop the datasets are further described in Scientific-Investigations Report 2010-5082: (1) ds507_regolith_data: This point dataset contains geologic information concerning regolith (unconsolidated sediment) thickness and top-of-bedrock altitude at selected well and test-hole locations in and near the Lost Creek Designated Ground Water Basin, Weld, Adams, and Arapahoe Counties, Colorado. Data were compiled from published reports, consultant reports, and from lithologic logs of wells and test holes on file with the U.S. Geological Survey Colorado Water Science Center and the Colorado Division of Water Resources. (2) ds507_regthick_contours: This dataset consists of contours showing generalized lines of equal regolith thickness overlying bedrock in the Lost Creek Designated Ground Water Basin, Weld, Adams, and Arapahoe Counties, Colorado. Regolith thickness was contoured manually on the basis of information provided in the dataset ds507_regolith_data. (3) ds507_regthick_grid: This dataset consists of raster-based generalized thickness of regolith overlying bedrock in the Lost Creek Designated Ground Water Basin, Weld, Adams, and Arapahoe Counties, Colorado. Regolith thickness in this dataset was derived from contours presented in the dataset ds507_regthick_contours. (4) ds507_welltest_data: This point dataset contains estimates of aquifer transmissivity and hydraulic conductivity at selected well locations in the Lost Creek Designated Ground Water Basin, Weld, Adams, and Arapahoe Counties, Colorado. This dataset also contains hydrologic information used to estimate transmissivity from specific capacity at selected well locations. Data were compiled from published reports, consultant reports, and from well-test records on file with the U.S. Geological Survey Colorado Water Science Center and the Colorado Division of Water Resources.
Datums Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83). Abstract Longitudinal profiles of near-streambed temperature were collected for eight river reaches in the Stillaguamish River basin, Washington, during August 2011, to provide information about areas of groundwater discharge to streams. During summer, groundwater discharge can be a source of cold water to streams that regulates warm stream temperatures creating cold-water thermal refugia for native stream biota including salmon and trout. To assess areas of groundwater discharge to streams, temperature was measured using a probe with an internal datalogger towed behind a watercraft moving downstream at ambient stream velocity. The data were referenced to location, concurrently surveyed with a Global Positioning System, during collection of the water temperature data. Data are presented as Microsoft Excel® files consisting of date and time, near-streambed water temperature, and latitude and longitude. Introduction Longitudinal profiles of near-streambed temperatures surveyed at ambient river velocity in a Lagrangian framework provide information about potential areas of groundwater discharge as well as salmonid habitat and thermal refugia (Vaccaro and Maloy, 2006). Longitudinal thermal profiles have previously been surveyed in several rivers in Washington, including the Yakima River and tributaries (Vaccaro and others, 2008) and the Nooksack River (Cox and others, 2005). This report presents eight thermal profiles within the Stillaguamish River basin including parts of the North Fork Stillaguamish River, South Fork Stillaguamish River, Jim Creek, and Pilchuck Creek (fig. 1). This data augments previous investigations of longitudinal temperature variations within the Stillaguamish River and tributaries by thermal infrared radar by the Washington State Department of Ecology (Watershed Sciences, 2002), and may be used as a tool to develop a better understanding of groundwater/surface-water interactions within the Stillaguamish River basin. Purpose and Scope The purpose of this report is to present longitudinal thermal profiles of stream temperature of streams within the Stillaguamish River basin including the North Fork Stillaguamish River, the South Fork Stillaguamish River, Pilchuck Creek, and Jim Creek. This data may be used to determine zones of groundwater discharge and improve understanding of the relation between the groundwater and surface water systems of the Stillaguamish River basin. Description of Study Area The Stillaguamish River basin is in northwestern Washington and is bounded to the east by the Cascade Mountains, to the west by Puget Sound, to the north by the Skagit River basin, and to the south by the Snohomish River basin (fig. 1). The Stillaguamish River basin is characterized by cool, wet winters and warm, dry summers. Mean annual discharge of the North Fork Stillaguamish River (North Fork Stillaguamish River near Arlington, Washington, USGS gaging station 12167000) for water years 1929-2010 is 1,898 ft 3 /s and mean annual discharge of the South Fork Stillaguamish River (South Fork Stillaguamish River near Granite Falls, Washington gaging station 12161000) for water years 1929-1980 is 1,071 ft 3 /s. Jim Creek is a tributary of the South Fork Stillaguamish River and Pilchuck Creek is a tributary of the mainstem Stillaguamish River. Thermal Profile Survey Continuous water temperature and Global Positioning System (GPS) data were collected at 3-second intervals while drifting downstream at ambient stream velocity in a Lagrangian framework following the method of Vaccaro and Maloy (2006) for Pilchuck Creek between river mile (RM) 0.0 and 3.7 (table 1); the North Fork Stillaguamish River between RM 0.0 and 34.2 (tables 2-5); South Fork Stillaguamish River between RM 17.7 and 33.4 (tables 6-7); and Jim Creek between RM 0.0 and 7.0 (table 8). Profiling at ambient stream velocity in a Lagrangian framework tracks a parcel of water as it moves downstream during the day; departures from the diurnal heating cycle may be due to groundwater input, surface-water inflows, or riparian shading. Continuous temperature was measured using a Solinst® Levelogger LT temperature probe verified by a National Institute of Standards and Technology (NIST) certified thermistor and position data was measured using a Garmin® GPSmap® 60Csx for the eight surveys during August 15-26, 2011. The temperature probe was towed behind a watercraft following the stream thalweg and dragged along the streambed except when in-stream obstacles prevented probe movement downstream. The location of each temperature measurement was determined by relating the time stamp of the GPS data to the temperature data. If a GPS location was not recorded at the same time as a temperature measurement, the location of the temperature measurement was determined by linear interpolation of the two GPS known locations that bracket the time of the temperature measurement. A 0.5-mi gap exists between the beginning of the North Fork Stillaguamish datasets collected on August 18 (table 4) and August 22 (table 5) because of inadequate equilibration of the temperature probe to ambient stream temperature during the initial 0.5 mi of the August 22 survey. Distribution of Information An Excel file of tables 1-8 that include the thermal-profile data for each longitudinal thermal profile is available at http://pubs.usgs.gov/ds/654/ds654_tables.xls. Table 1. Temperature and Global Positioning System location data for the Pilchuck Creek (RM 0.0-3.7), August 15, 2011. Table 2. Temperature and Global Positioning System location data for the North Fork Stillaguamish River (RM 30.0-34.2), August 16, 2011. Table 3. Temperature and Global Positioning System location data for the North Fork Stillaguamish River (RM 17.6-30.0), August 17, 2011. Table 4. Temperature and Global Positioning System location data for the North Fork Stillaguamish River (RM 9.5-17.6), August 18, 2011. Table 5. Temperature and Global Positioning System location data for the North Fork Stillaguamish River (RM 0.0-9.0), August 22, 2011. Table 6. Temperature and Global Positioning System location data for the South Fork Stillaguamish River (RM 25.9-33.4), August 24, 2011. Table 7. Temperature and Global Positioning System location data for the South Fork Stillaguamish River (RM 17.7-25.9), August 26, 2011. Table 8. Temperature and Global Positioning System location data for Jim Creek (RM 0.0-7.0), August 25, 2011. References Cited Cox, S.E., Simonds, F.W., Doremus, L., Huffman, R.L., and Defawe, R.M., 2005, Ground water/surface water interactions and quality of discharging ground water in streams of the lower Nooksack River Basin, Whatcom County, Washington: U.S. Geological Survey Scientific Investigations Report 2005-5255, 46 p Vaccaro, J.J., Keys, M.E., Julich, R.J., and Welch, W.B., 2008, Thermal profiles for selected river reaches in the Yakima River basin, Washington: U.S. Geological Survey Data Series 342 (Available at http://pubs.usgs.gov/ds/342/). Vaccaro, J.J., and Maloy, K.J., 2006, A thermal profile method to identify potential ground-water discharge areas and preferred salmonid habitats for long river reaches: U.S. Geological Survey Scientific Investigations Report 2006-5136, 16 p. Watershed Sciences, LLC, 2002, Aerial surveys in the Stillaguamish and Skagit River Basins-Thermal infrared and color videography: Corvallis, Oreg., Water Sciences, for Washington Department of Ecology, 28 p.
Flood-frequency analysis provides the basis for flood risk estimates used by water-resource managers in land-use planning, and it informs the design of essential infrastructure such as bridges and culverts. Federal guidelines for flood-frequency analysis do not offer guidance on addressing changing climate and land-use conditions when estimating floods. However, failing to consider climatic and land-use changes that cause abrupt or gradual changes in flood regimes can result in a poor representation of the true flood risk. In response to concerns about changing flood regimes, the U.S. Geological Survey, in cooperation with nine State agencies (Illinois Department of Transportation, Iowa Department of Transportation, Michigan Department of Transportation, Minnesota Department of Transportation, Missouri Department of Transportation, Montana Department of Natural Resources and Conservation, North Dakota Department of Water Resources, South Dakota Department of Transportation, and Wisconsin Department of Transportation) began a study to examine variability and change in hydrology and climate and the effects of urbanization and tile drainage on flooding. The analyses of patterns and changes in hydrology and climate were reported in a multichapter Scientific Investigations Report, the findings of which are summarized in this U.S. Geological Survey Circular. Additional analyses documenting changes in seasonality of flooding and the effects of urbanization and tile drainage were completed and published as separate studies and are also summarized in this Circular. These studies provide extensive exploratory analysis of peak streamflow, daily streamflow, and climate data, setting the stage for advancements in flood-frequency analysis.