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At least 1,297 records · Page 72Linked to original sources

Real-time validation of the Dst Predictor model

The Dst Predictor model, which has been running real-time in the Space Weather Analysis and Forecast System (SWAFS), provides 1-hour and 4-hour forecasts of the Dst index. This is useful for awareness of impending geomagnetic activity, as well as driving other real-time models that use Dst as an input. In this report, we examine the performance of this forecast model in detail. When validating indices it should be noted that performance is only with respect to a reference index as they are derived quantities assumed to reflect a state of the magnetosphere that cannot be directly measured. In this case U.S. Geological Survey (USGS) Definitive Dst is the reference index (Section 3). Whether or not the model better reflects the actual activity level is nearly impossible to discern and is outside the scope of this report. We evaluate the performance of the model by computing continuous predictant skill scores against USGS Definitive Dst values as “observations” (Section 4.2). The two sets of data are not well-correlated for both 1-hour and 4-hour forecasts. The Dst Predictor Prediction Efficiency for both the 1- and 4-hour forecasts suggests poor performance versus the climatological mean. However, the skill score against a nowcast persistence model is positive, suggesting value added by the Dst Predictor model. We further examine statistics for storm times (Section 4.3) with similar results: nowcast persistence performs worse than Dst Predictor. Dst Predictor is superior to the nowcast persistence model for the metric used in this study. We recommend continued use of the DstPredictor model for 1-and4-hour Dst predictions along with active study of other Dst forecast models that do not rely on nowcast inputs (Section 6). The lack of certified requirements makes further recommendations difficult. A study of how the error in Dst translates to error in models and a better understanding of operational needs for magnetic storm warning are needed to determine such requirements. Nowcast persistence is often hard to beat for short term forecasts and specification and Dst Predictor clearly performs well against that standard (with 1-hour and 4-hour skill-scores of 0.233 and 0.485 respectively), although poor in absolute terms (with1-hourand4-hour prediction efficiencies of-64.6and-43.1, respectively).

Air Force Research Laboratory Technical Report↗

Understanding the occurrence and transport of current-use pesticides in the San Francisco estuary watershed

The occurrence and potential effects of current-use pesticides are of concern in the San Francisco Estuary watershed but our understanding of the spatial and temporal distribution of contamination is limited. This paper summarizes almost two decades of historical data and uses it to describe our current knowledge of the processes controlling the occurrence of current-use pesticides in the watershed. Monitoring studies analyze fewer than half of the pesticides applied in the watershed and most of our knowledge is about inputs of dissolved pesticides in the upper watershed. The four major seasonal patterns of riverine inputs of pesticides to the estuary can be identified by usage and transport mechanism. Dormant spray insecticides applied to orchards and herbicides applied to a variety of crops are transported by rainfall during the winter. Alfalfa pesticides are detected following rainfall and irrigation return flow in the spring, and rice pesticides are detected following release of rice field water in the summer. Irrigation return flows transport a variety of herbicides during the summer. In addition, pesticides applied on Delta islands can cause elevated pesticide concentrations in localized areas. Although not as well characterized, urban creeks appear to have their own patterns of insecticide concentrations causing toxicity throughout most of the year. Current-use pesticides have also been detected on suspended and bed sediments throughout the watershed but limited data make it difficult to determine occurrence patterns. Data gaps include the lack of analysis of many pesticides (or degradates), changing pesticide use, limited information on pesticide transport within the Delta, and an incomplete understanding of the transport and persistence of sediment-associated pesticides. Future monitoring programs should be designed to address these data gaps.

California↗

The National Elevation Dataset

The National Elevation Dataset (NED) is a primary elevation data product that has been produced and distributed by the U.S. Geological Survey (USGS). Since its inception, the USGS has compiled and published topographic information in many forms, and the NED is a significant development in this long line of products that describe the land surface. The NED provides seamless raster elevation data of the conterminous United States (CONUS), Alaska, Hawaii, U.S. island territories, Mexico, and Canada. The NED is derived from diverse source datasets that are processed to a specification with consistent resolutions, coordinate system, elevation units, and horizontal and vertical datums. The NED was developed as the logical result of the maturation of the long-standing USGS elevation program, which for many years concentrated on production of quadrangle-based digital elevation models (DEM). The NED contributes to the elevation layer of The National Map, and it provides basic elevation information for earth science studies and mapping applications in the U.S. and most of North America. For over 15 years (1999–2014), the NED served as the flagship elevation product of the USGS. In 2015, the 3D Elevation Program (3DEP) was initiated. When the 3DEP initiative became operational, the name “National Elevation Dataset” (and the abbreviation “NED”) were retired as the USGS elevation activities and data were rebranded under the 3DEP banner. However, elevation data produced and distributed as part of the NED are still widely used (and distributed by other entities), so there is a continuing need for detailed documentation, including how it was produced, its accuracy, and how it is used. This chapter directly addresses that need for detailed information about the NED. The most recent detailed description of the NED appeared in the 2nd edition of the DEM Users Manual (2007), and because NED production continued through 2014, the details reported herein provide valuable information for data accessed by the user community from 2007 through 2014. The NED has been widely used in operational applications and research studies and is extensively cited in reports on those activities, so it is important for the user community to have access to information about the NED to better judge how its qualities and characteristics might affect results derived from its use as the elevation data source. Additionally, the NED seamless layers serve as one of the input data sources for the current 3DEP elevation production system, so, as with any input data source, an understanding of the data characteristics is critical.

Book chapter↗

Groundwater flow model for Western Chippewa County–Including analysis of water resources related to industrial sand mining and irrigated agriculture

A groundwater flow model for western Chippewa County, Wisconsin, was developed by the Wisconsin Geological and Natural History Survey (WGNHS) and the U.S. Geological Survey (USGS) using the computer program MODFLOW. The model is the result of a five-year groundwater study commissioned by Chippewa County in 2012 to evaluate the effects of industrial sand mining and irrigated agriculture on the county’s water resources. The study incorporates existing data and newly acquired data from fieldwork conducted within the study area. The groundwater model may be useful for future investigations, such as evaluation of proposed high-capacity well sites, development of municipal wellhead protection plans, and studies that seek to further quantify surface water-groundwater relationships. The model conceptualizes the hydrostratigraphy of western Chippewa County as six stacked layers. Each layer is distinct, beginning with unlithified glacial material at the surface, and alternating between sandstones (that act as aquifers) and shale units (that serve as aquitards). The model is bounded below by Precambrian crystalline bedrock and its perimeter was derived from a regional-scale groundwater flow model. The MODFLOW model represented average conditions during 2011–2013 with “steady-state” assumptions, meaning that simulated water levels do not fluctuate seasonally or from year to year. Steady-state models simplify natural variability, making results of scenario simulations easier to interpret and compare while also maximizing effects of stressors because the simulated stress is always applied (not halted after a few months or years). Model calibration used the parameter estimation code (PEST), and calibration targets included heads (groundwater levels) and streamflows. Calibration focused on 2011–2013 because a large amount of head and streamflow data were available for that period. The MODFLOW model explicitly simulates all sources and sinks of water, including groundwater/surface-water interaction with streamflow routing. Model input included estimates of aquifer hydraulic conductivity and a spatial groundwater recharge distribution developed using a GIS-based soil-water-balance (SWB) model applied to the model area. Groundwater withdrawals were simulated for 269 high-capacity wells across the entire model domain, which includes western Chippewa County and adjacent portions of Dunn, Barron, and Rusk Counties. Collectively, these wells withdrew about 1.14 million gallons per year between 2011 and 2013. Once the model was calibrated, it was applied to two distinct scenarios of increased groundwater withdrawals: one evaluating hydrologic effects of more intensive industrial sand mining and the second evaluating the hydrologic effects of more intensive agricultural irrigation practices. Each scenario was developed with input from Chippewa County and a stakeholder group established expressly for this study. The scenarios were designed to represent reasonable future buildout conditions for both mining and irrigated agriculture. The mining scenario underscores the potential hydrologic effects related to changing land-use practices (i.e., hilltops and farmland becoming sand mines), while the irrigated agriculture scenario illustrates the potential hydrologic effects of intensifying existing land-use practices (i.e., installing new wells to irrigate farm fields). While each scenario evaluated distinctly different conditions, modeling results demonstrated the potential of both scenarios to lower the water table and reduce baseflows in headwater streams within the modeled area. In the case of irrigated agriculture, hydrologic effects were associated directly with groundwater withdrawals. By assuming that irrigation did not decrease, this steady-state simulation represented a sustained future effect. By contrast, hydrologic effects of industrial sand mining were the result of both groundwater withdrawals at mines and land-use changes that effectively reduced recharge to groundwater over distinct phases of active mining. This scenario included a post-mining phase, during which groundwater withdrawals stopped and mined areas were reclaimed to undeveloped prairie grass cover. If reclamation to undeveloped prairie indeed occurs as simulated, long-term increases in the water table and stream baseflows are possible. In this sense, the scenario representing build out of irrigated agriculture led to long-term baseflow declines while the future buildout of industrial sand mining led to declines that dissipated following mine reclamation to undisturbed prairie. Future investigations in similar hydrogeologic settings may find the following insights gleaned from this study useful: ❚❚ The characterization of hydrogeologic properties, delineation of hydrogeologic units, and calibration of groundwater flow models benefited from incorporation of accurate well construction reports, high-quality borehole geophysical logs, and streamflow gaging data. ❚❚ Infiltration testing performed in active mining areas provided evidence that reducing the degree and extent of compaction and enhancing areas designed to retain and infiltrate stormwater runoff could potentially reduce runoff and increase groundwater recharge. ❚❚ Similarly, reclaiming mined areas to prairie grasses would be expected to reduce runoff and increase groundwater recharge by reducing compaction and improving soil structure and vegetation that can slow runoff and enhance infiltration.

Wisconsin↗

Managed aquifer recharge in snow-fed river basins: What, why and how?

What does climate change mean for snow-fed river basins? Climate change poses unique challenges in snow-fed river basins across the western United States because the majority of water supply originates as snow (Dettinger, Udall, & Georgakakos, 2015). In the Sierra Nevada, recent observations include changes in snow accumulation and snowmelt, and shifts in peak streamflow timing (Barnhart et al., 2016; Hatchett et al., 2017; Kim & Jain, 2010; McCabe, Wolock, & Valentin, 2018; Mote, Li, Lettenmaier, Xiao, & Engel, 2018). Such changes upstream alter surface water deliveries downstream, as well as groundwater recharge utilized as both primary and supplemental water supply (Godsey et al., 2014; Harpold, 2016; Jasechko et al., 2014). basin where snowmelt runoff produces substantial water supply to meet diverse agricultural, environmental and urban water demand (Figure 1). The East and West Forks join at the confluence of the Carson River near the north end of the Carson Valley, a rich agricultural region (40,000 acres) that grows primarily alfalfa hay. The majority of irrigators rely on surface water delivered through a network of earthen ditches constructed in the mid-19th and early 20th centuries. Flow through these earthen networks and the practice of flood irrigation contribute significantly to groundwater recharge. Because no upstream surface water reservoirs exist, snowpack that accumulates through winter and melts slowly through spring has acted as a “natural” reservoir, providing ample supply through the summer irrigati agricultural, environmental and urban water demand (Figure 1). The East and West Forks join at the confluence of the Carson River near the north end of the season. Some irrigators have permitted access to supplemental groundwater that is useful during periods of drought for augmenting shortfalls in surface water delivery. Groundwater is the primary source of municipal and industrial water supply for surrounding communities (e.g., Carson City, Minden, Gardnerville, Dayton). Across the basin, water use is highly regulated through federal, tribal, state and local water-sharing agreements based on prior appropriation doctrine (Wilds, 2014). Carson River surface water allocations follow the Alpine Decree, initiated by the United States Department of Interior in 1925 and signed into law in 1980, following 55 years of litigation, to adjudicate surface water rights to individual parties (NDWP, 1999). The Alpine Decree acknowledges return flows to lower river segments, and thus each river segment is distributed autonomously. This means that the most junior water right on an upper segment can be fulfilled before considering the most senior water right on a lower segment. Ultimately, the ruling is at the discretion of the Federal Water Master to satisfy the needs of each water right Downstream of Carson Valley, surface water flows are stored in Lahontan Reservoir, the nation’s first desert reclamation project (est. 1906), where releases are managed to meet the Newland’s Project irrigation water demand and for environmental use on the Stillwater National Wildlife Refuge. Flows from the Carson River are supplemented through diversions from the Truckee River via the Truckee Canal, resulting in a trans-basin water supply system. How is the Water for the Seasons research program informing snow-fed river basin communities? In the Truckee-Carson River System, researchers and local water managers are working together to assess climate change impacts to water supply and explore how model simulations can produce useful information to support local climate adaptation. Twelve key water managers represent agricultural, environmental, urban and regulatory water-use communities, and bring to the table diverse input and perspectives on how to adapt to climate change. Hydrologists use this input to craft scenarios and simulations that meet the information needs of local water managers. Biannual workshops provide an opportunity for information exchange, where researchers and key water managers generate new knowledge of river system function. That is, researchers share results of models that examine the physical potential, and managers validate the on-the-ground potential, further informing the research process. Coincident to this research program, the region faced a prolonged drought period (2012-2016) with historically low snowpack, followed by a historic wet year (2017) that brought winter and spring flooding as a result of atmospheric river storm events (Sterle et al., 2019). For the Carson River, an important observation made by managers was that peak streamflow that had traditionally coincided with peak irrigation demands, had shifted to earlier in the spring, with summer baseflow also decreasing (Sterle & Singletary, 2017). Managers shared with researchers concerns over potential future impacts that changing snowpack will have on surface water deliveries and reliance on groundwater, as the region’s population and economy continue to grow. During workshops that occurred over this period, local water managers and researchers discussed ways to evaluate water distribution and use that honors the existing legal framework and accounts for changing snowpack regimes (amount, rain versus snow, timing). In response to managers growing interest, researchers introduced the concept of managed aquifer recharge as one potential strategy to adapt and enhance regional water sustainability. What is managed aquifer recharge? Simply stated, managed aquifer recharge is the intentional recharge of structures to spread water over agricultural lands, allowing water to naturally infiltrate into the groundwater system (Bouwer, 1999; Niswonger et al., 2017). The latter may occur during the irrigation season by applying excess water, or during the nonirrigation season when evapotranspiration losses are low. Figure 2 illustrates managed aquifer recharge in a snow-fed river basin, where streamflow generated from snowmelt runoff is diverted to agricultural lands to recharge the aquifer. Such flood irrigation practices, including water delivery through earthen ditch networks, provide incidental but significant aquifer recharge through seepage and deep drainage beneath fields (Niswonger, Allander, & Jeton, 2014). The effects of managed aquifer recharge can vary depending on the location and intensity of practice. For example, implementing managed aquifer recharge water into the groundwater system (Dillon, 2009). This differs from the incidental recharge that may occur as part of normal irrigation practices. Managed recharge may occur by injection into the aquifer through existingwells, or by using existing conveyance adjacent to/along the river’s floodplain has the potential to enhance late-season instream flows due to increased return flows, resulting in greater downstream deliveries as well as improving ecological conditions (Niswonger et al., 2017). Implementing managed aquifer recharge away from the river’s floodplain has the potential to enhance groundwater supply which is increasingly relied upon during surface water shortage (Green et al., 2011), by storing water in available aquifer space in the deep aquifer. At the basin scale, managed aquifer recharge may lead to regional groundwater sustainability. Is the Carson River Basin a candidate for managed aquifer recharge? The physical limitations to implementing managed aquifer recharge in the Carson River Basin hinges on three key factors. The first factor relates to the physical connectivity between rivers and streams, and the irrigation delivery network of canals and ditches that divert water to agricultural lands (Niswonger et al., 2017). In the Carson River Basin the mechanisms for getting water to fields is already in place. Thus, intentionally routing high flows that occur in wet years through this system during the nonirrigation season would mimic what occurs naturally during the irrigation season. The second factor relates to the occurrence of atmospheric river storm events that deliver large amounts of precipitation to the region, much greater than average (Dettinger et al., 2015). With increased frequency and intensity projected under a warmer climate, such events have the potential to produce excess water over short periods of time that could be stored through mechanisms such as managed aquifer recharge (Niswonger et al., 2017). The third factor relates to the change in snowpack accumulation and shifts in snowmelt timing observed elsewhere in the Sierra Nevada (e.g., Godsey et al., 2014; Mote et al., 2018). Having a mechanism in place to maximize use of earlier snowmelt and shifts in streamflow timing could be advantageous and enhance regional groundwater sustainability. As part of the Water for the Seasons study, a hypothetical scenario was developed to determine the feasibility of managed aquifer recharge in the Carson River Basin, assuming no legal constraints. During “wet” or above-average water years, irrigators in the Upper Carson Valley would divert high flows and spread water over agricultural lands during the nonirrigation season. Assuming flows are abundant and “early,” diversions would begin prior to the growing season, when water would otherwise flow downstream to the Lahontan Reservoir. During “dry” years or drought periods, when surface water availability is less, irrigators in the Upper Carson Valley could augment surface water shortages with groundwater, allowing available surface water flows to flow downstream. Researchers hypothesize the amount of water has the potential to boost baseflow to support environmental instream flows, for example. What concerns have local water managers expressed? The hypothetical managed aquifer recharge scenario was presented to water managers in a workshop setting. Presentations included an overview of the hydrologic and operations modeling tools used to evaluate managed aquifer recharge by simulating the timing and distribution of water in the upper watershed. Specifically, in the Upper Carson Valley, a hydrologic model (GSFLOW) simulates streamflow driven by snowmelt, and surface and groundwater interactions, while a river basin operations model (MODSIM) allocates water according to the prior appropriation doctrine in the basin (see Figure 1) (Morway, Niswonger, & Triana, 2016; Niswonger et al., 2017). Integrating these two modeling tools advances the evaluation of climate impacts on water availability in agricultural communities and the resulting impacts of alternative management strategies (Morway et al., 2016). When asked about the viability of managed aquifer recharge, the perspectives of 11 managers varied (Figure 3). Regardless of rating, all managers questioned, “How would thisreally work?” Several managers questioned whether models could simulate the connectivity between surface and groundwater to accurately quantify changes to instream flow. Others raised concerns that managed aquifer recharge violates the Alpine Decree and Nevada Water Law. Still others requested researchers consider alternatives that could work within the confines of current (2019) water law. Managers posed specific questions that should be considered when evaluating the potential for managed aquifer recharge. For example: What triggers implementation of managed aquifer recharge?How “high” or “low” must annual flows be to initiate managed aquifer recharge? When in the water year is this determined? Where exactly in the Carson Valley is managed aquiferre charge possible? For example, what areas away from the floodplain could ensure long-term storage? Can model simulations quantify potential benefits and consequences system-wide?Would this information support decision-making, such as permitting of additional supplemental groundwater rights? How are researchers going to address managers’ research questions? Managers’ perspectives help to validate the on-the-ground potential of particular strategies and further refine alternative management scenarios. For example, understanding that managers are concerned with oversaturated fields helps researchers to define conditions in the model, such as what defines a wet versus “too” wet type of year and where to focus irrigation for managed aquifer recharge. Incorporating these nuances provides more accurate quantification of the potential benefits and consequences for users across the basin. Modeling is underway to simulate managed aquifer recharge scenarios and explore basin-wide implications. Researchers and local water managers will convene to collaboratively review results and further assess whether this or other strategies could work under the confines of existing water law. Subsequent fact sheets will present these findings.

Nevada↗

An examination of organic/carbonate-bound metals in bottom sediments of Bayou Trepagnier, Louisiana

To assess potential impact of metals on the biosphere in bottom sediments, forms were determined for selected metals in a southeastern Louisiana bayou, Bayou (B.) Trepagnier, which has been impacted by industrial activity at its head by a manufacturing complex (MC). Ten pairs of cores along the length of the bayou allowed variation with distance to be studied. Sequential extractions provided data on five chemical partitioning phases for subsamples from each of the cores. Results show that, beyond the mineral residue phase (phase 6 of the extractions) the organic/carbonate phase (phase 4 of the extractions) generally contains the highest concentrations of metals. This paper focuses on phase 4. In addition, metals in phase 4 show significant downstream gradients, though concentrations towards the mouth do not generally appear to differ significantly from those at a control site outside of the bayou. Data were also examined for interrelationships, and high correlation coefficients were the impetus for moving to a multivariate statistical method, polytopic vector analysis (PVA). Six end-members (EMs) were produced. EMs 2, 5, and 6 have high relative proportions of anthropogenic metals and are observed in highest proportions upstream, near the MC. These EMs may reflect industrial input from the MC. EM 3 contains significant calcium, magnesium, and manganese, with minor amounts of lead and barium, and is related to input from nearby Lake Ponchartrain since it increases in weight downstream. EMs 1 and 4 are composed of components commonly found in detrital minerals (e.g., iron, aluminum, magnesium, manganese, and silicon) and are probably not the product of anthropogenic influence. For anthropogenically-weighted end-members (EMs 2, 5, and 6) there appears to be little difference between weights at the mouth of the bayou and weights at the control site outside the bayou.

Louisiana↗

Management opportunities and research priorities for Great Plains grasslands

The Great Plains Grassland Summit: Challenges and Opportunities from North to South was held April 10-11, 2018 in Denver, Colorado. The geographical focus for the summit was the entire Great Plains. The summit was designed to provide syntheses of information about key grassland topics of interest in the Great Plains; networking and learning channels for managers, researchers and stakeholders; and working sessions for sharing input and ideas about challenges and future research and management opportunities. The summit was convened to better understand Great Plains stressors and resource demands and how to manage them, and to discuss methods for improved collaboration among natural resource managers, scientists, and stakeholders. Over 200 stakeholders, who collectively were affiliated with all of the Great Plains states, attended the summit. Attendees included university researchers, government scientists, and individuals affiliated with federal and state agencies, tribes, the private sector, and non-governmental organizations (NGOs). Plenary speakers provided syntheses of current knowledge on key topics to help stage working sessions on working lands, native plants and pollinators, native wildlife and biological diversity, invasive species, wildland and prescribed fire, energy development, and weather, water, and climate. The summit steering committee designed one suite of questions that were asked of participants in each working session. This report is a digest of the input from those who attended the seven working sessions and responded to the structured questions.

Colorado, Illinois, Iowa, Kansas, Minnesota, Misso↗

Modeling mangrove canopy reflectance using a light interaction model and an optimization technique

At 20 sites, incorporating mixtures of black, red, and white mangroves, canopy reflectance spectra were derived from high resolution spectral data taken from a helicopter platform. Canopy characteristics were predicted from the canopy reflectance spectra by using measured and estimated data as inputs into a light-canopy interaction model within a optimization routine. Pertinent to average conditions typifying the area and time of the study, the light-canopy interaction model accomplished two goals. Using the model as a predictor, a sensitivity analysis suggested that little error in modelling the near nadir view canopy reflectance (R cv ) would result from assuming an average soil reflectance of about 0.1, at leaf area index (LAI) values above 2, at near infrared (NIR) leaf reflectances higher than about 0.45. and at sun elevation angles >40 o . Moderate errors could result from assuming a spherical leaf angel distribution (LAD), and relatively high errors could result from errors in estimating visible leaf reflectances (and NIR leaf reflectances <0.45) and percent skylight. Differences between canopy hemispherical reflectance (R c ) and R cv were dominated by percent skylight variation, while differences between R c and R cv were moderate to slight at a sun elevation above 20 o to 30 o , a near spherical LAD, a soil reflectance near 0.1, a LAI up to 4, and a NIR leaf reflectance less than 0.7. Simulated canopy reflectance spectra were close predictors of obtained spectra, with R 2 values >0.97. Mean predicted LAI values were 2.6±0.86 (mean ±1 standard deviation) and were highly related to LAI values derived from field measurements. Seventy-eight percent of the modelled LAI variance was predicted by a normalized difference vegetation index transform of the field canopy spectra data. Predicted LAD values had a near spherical mean value, while the mean difference between input (estimated from laboratory measurements) and predicted leaf reflectances was nearly zero.

Florida↗

Time scales and volumes of large ignimbrite-caldera eruptions in continental arc: Relation to assembly of subvolcanic batholiths

Volcanoes and upper-crustal plutons in diverse geologic settings tend to share common features of mineral and chemical compositions, emplacement age, and magmatic volume. Voluminous silicic ignimbrites associated with caldera sources, widespread components of Cordilleran arcs, have commonly been interpreted as broadly concurrent with assembly of upper-crustal batholiths. Tertiary ignimbrites in the westerns USA and elsewhere, with volumes to 1-5x10 3 km 3 , record multi-stage histories of magma accumulation, fractionation, and solidification in upper parts of large subvolcanic plutons that were sufficiently liquid to erupt. Indiviudal calderas, to 75 km across with 2-5 km subsidence, are direct evidence for shallow magma bodies comparable to the largest granitic plutons. Nested polycyclic calderas that erupted compositionally diverse tuffs, some with reposed intervals of 100 ka or less, document deep composite subsidence and rapid evolution in subvolcanic magmas. Most ignimbrite compositions are more evolved than associated plutons, requiring that subcaldera chambers retained voluminous residua from fractionation. Geophysical data that shows that low-density upper-crustal rocks, inferred to be plutons, are 10km or more thick beneath many calderas. Alternatively, some recent field and geochronologic studies have been interpreted as indicating that individual Mesozoic Cordilleran plutons grew and solidified incrementally in small batches during > 10 6- year intervals, without presence of voluminous eruptible magma ("large tank") at any stage during pluton growth and batholith assembly. Such growth in plutons in small increments would minimize close associations with large ignimbrite calderas and suggest that batholith growth is largely unrelated to surface volcanism. Linked to these interpretations are inferences that ignimbrite eruptions record ephemeral magma chambers that (1) grow rapidly due to exceptionally high magmatic power input to the upper crust, (2) evacuate nearly completely during ignimbrite eruption, and (3) leave little geologic record in the form of crystallized crustal plutons. How to reconcile these alternatives? Many large continental arcs record a broadly unified time-space-composition evolution of upper-crustal magmatic systems. Such volcanic fields especially those containing ignimbrite-caldera episodes, commonly contain compositionally diverse eruptive products erupted over multimillion-year intervals. A common pattern is initial eruptions of intermediate-composition lavas from central volcanoes, followed by eruption of one or more large-volume ignimbrites of more silicic composition; concurrent caldera subsidence is located centrally within the are of prior lava vents. Such progressions of surface volcanism can be interpreted as providing instantaneous sequential snapshots of changing magma-chamber process through time. In contrast, subvolcanic plutons exposed in eroded volcanic terranes represent time-integrated and partly homogenized end products, as successive magmatic pulses accumulated, fractionated, and consolidated in the upper crust. Such perspectives combine evidence for prolonged growth and incremental pluton assembly with presence of large-volume eruptible chambers during peak magmatic input.

Colorado↗

Lake Ontario deepwater sculpin recovery: An unexpected outcome of ecosystem change

Fish population recoveries can result from ecosystem change in the absence of targeted restoration actions. In Lake Ontario, native Deepwater Sculpin Myoxecephalus thompsonii, were common in the late-1800s, but by the mid-1900s the species was possibly extirpated. During this period mineral nutrient inputs increased and piscivore abundance declined, which increased the abundance of the nonnative planktivores Alewife Alosa pseudoharengus and Rainbow Smelt Osmerus mordax. Deepwater Sculpin larvae are pelagic and vulnerable to predation by planktivores. Annual bottom trawl surveys did not capture Deepwater Sculpin from 1978 – 1995 (n = 6,666 tows) despite sampling appropriate habitat (trawl depths: 7 – 170 m). The absence of observations during this time resulted in an elevated conservation status for the species, but no restoration actions were initiated. In 1996, three individuals were caught in bottom trawls, the first observed since 1972. Since then, their abundance has increased and in 2017 they were the second most abundant Lake Ontario prey fish. The food-web changes that occurred from 1970 through the 1990s contributed to this recovery. Alewife and Rainbow Smelt abundance declined during this period due to predation by stocked salmonids and legislation that reduced nutrient inputs and food web productivity. In the 1990s, the proliferation of nonnative, filter-feeding dreissenid mussels dramatically increased water clarity. As light penetration increased, the early-spring depth distribution of Alewife and Rainbow Smelt shifted deeper, away from larval Deepwater Sculpin habitat. The intentional and unintentional changes that occurred in Lake Ontario were not targeted at Deepwater Sculpin restoration but resulted in conditions that favored the species’ recovery. While standard surveys documented the recovery, more diverse information (e.g. observations in deep habitats and early-life stages) would have improved our understanding of why the species recovered when it did. Annual Lake Ontario trawl surveys have collaboratively expanded their spatial extent and diversified habitat sampled, based on lessons learned from the Deepwater Sculpin recovery.

Lake Ontario↗

Ongoing efforts to make ash-cloud model forecasts more accurate

The 2010 eruption of Eyjafjallajökull volcano in Iceland changed the rules for air travel in Europe and introduced the use of restricted fly zones based on ash-cloud concentrations calculated by dispersion models. This change prompted a sustained effort to improve the accuracy of ash-cloud model forecasts. In this paper we describe how this goal is being advanced on three fronts: (1) assessing current capabilities and establishing best practices; (2) improving the accuracy of model inputs; and (3) developing strategies to automatically compare model output with observations and adjust inputs to produce the best match. Progress has been made on all three fronts. A key lesson is that accuracy can only be quantified by comparison with reliable observations, which are often elusive. Model improvements will have to be made in tandem with new technologies to observe and measure.

Conference Paper↗

Identifying sources of contaminants in urban stormwater and evaluation of their removal efficacy across a continuum of urban best management practices

Precipitation events in urban areas often result in stormwater runoff containing a diverse array of chemical contaminants. Although many traditional contaminants, such as nutrients, heavy metals, and polycyclic aromatic hydrocarbons have been studied extensively, only recently has evidence emerged showing that trace organic compounds (TrOCs), including pharmaceuticals, personal care products and pesticides are frequently found in stormwater runoff. As there is little existing information about the sources of TrOCs in urban stormwater or their removal efficacy across a range of stormwater treatment options, we conducted a study to address these knowledge gaps and to characterize the potential contribution of TrOCs to groundwater resources from stormwater infiltration practices, based on several synoptic measurements. The current study allowed us to enhance an existing effort to assess TrOC presence and toxicity in stormwater runoff and treatment pond outflow by addressing questions related to TrOC sources to stormwater and TrOC transport to groundwaters. Analysis of eDNA confirms multiple sources of TrOCs to stormwater including human sewage, dog waste, and feces from waterfowl. It is likely that the presence of some TrOCs detected in stormwater are the result of direct, untreated sewage inputs to stormwater from either human (i.e., leaking sewer infrastructure) or pet waste (washed from sidewalks into storm drains). The seasonal detection of avian eDNA is noteworthy as it highlights seasonality and patterns of migration patterns as contributing factors to stormwater contamination. In contrast to human and pet waste, which likely enters stormwater ponds via the stormwater conveyance system, avian feces may enter ponds either through stormwater runoff or through direct inputs by waterfowl stopping-over temporarily at stormwater ponds. Stormwater ponds had little effect in reducing TrOCs as determined by comparative inflow and outflow analysis. Our results also indicate that overall few TrOCs were present in receiving groundwater adjacent to underground infiltration basins, compared to inflow. However, some contaminants were present at relatively high concentrations compared to stormwater flowing into the basins. This is particularly true for pesticides and their degradants. Fewer TrOCs were detected in interstitial water collected near stormwater ponds compared to inflow and outflow. The presence and concentrations of TrOCs in outflow from ponds was generally similar to or higher than what was observed in inflow. The data collected as part of this study can be used to guide future research or monitoring in an effort to better understand TrOC fate and transport in the environment via stormwater BMPs. Specifically, more work is needed to track parcels of water as they flow through BMPs to better quantify transport and degradation of TrOCs, monitor flow into and out of ponds for mass balance calculations, and conduct tracer tests to better quantify the amount of water that monitoring wells are intercepting from underground infiltration basins. These results have been shared in multiple presentations and in meetings with high school teachers to develop age-appropriate curriculum to highlight the role of individuals in reducing and preventing stormwater contamination. The ongoing pandemic hindered some of these efforts (cancelled conferences; suspended MN Water Roundtable meetings; pre-occupation with teachers moving materials online), however, as dissemination activities become more common in the near future, we will continue to educate stakeholders and educators about the root causes and effects of urban stormwater contamination.

Minnesota↗

Characterization of hydrology and sediment transport following drought and wildfire in Cache Creek, California

The worst drought in California in over 1,200 years occurred between 2012-2017 (Griffin, 2014), depleting surface water and groundwater supply and drying out the soils past wilting point. In the summer of 2015, the Jerusalem and Rocky fires burned roughly 40,000 acres within the Cache Creek watershed. To fully characterize the post-fire effects in the Cache Creek watershed, an hourly model of streamflow and sediment transport was developed using the Hydrological Simulation Program – FORTRAN (HSPF). This model requires air temperature, precipitation, and potential evapotranspiration as climate inputs. Hourly station data are sparse in the area and may not capture the variability of elevation and local climatology patterns within the watershed. A technique used previously to spatially-interpolate daily-climate station data has improved the characterization of local and regional climate patterns on a daily scale in areas with sparse data (Flint et al., 2014). This technique was extended to hourly observed data to produce spatially-varying climate inputs for the Cache Creek hydrologic model to run as a continuous multi-year simulation with hourly time steps. Monthly PRISM grids were used in a two-step scaling method with climate Gradient and Inverse Distance Squared (GIDS) maps (Nalder and Wein, 1998) to develop daily grids, then the daily grids were used to scale hourly climate GIDS maps. This method captures the temporal variability at each climate station yet preserves the regional monthly spatial structure of the PRISM data. Hydrologic calibration used data from water year 2015, and validation used the same parameters for water year 2016. The model was run through water year 2017 to characterize the effects of wildfire on hydrology and sediment transport. For final simulations, the model was run at an hourly time step from June 2014 through September 2017 to ensure a model initiation period of 4 months prior to the target simulation period used for analysis. Sediment parameters were initially set using the existing Sacramento River Basin model for this sub-watershed area and then iteratively adjusted in the calibration process. To simulate a fire across the landscape, sediment parameters for water years 2016-17 were further modified for burned sub-basins to represent post-fire vegetation and soils in 2016, then partial recovery in 2017. Results were inconclusive for drought and wildfire effects on runoff. Modeled peak flows generally underpredicted observed peak flows; however, the modeled storm volumes were only slightly under or over the observed storm volumes. Sediment transport was sensitive to the watershed disturbances and R^2 values for daily mean suspended concentrations (SSC) and sediment discharge were 0.70 and 0.75, respectively. Simulated hourly values correlated less strongly with observed instantaneous SSC and sediment discharge (R^2 values of 0.56 and 0.46, respectively).

California↗

Predicting geothermal favorability in the western United States by using machine learning: Addressing challenges and developing solutions

Previous moderate- and high-temperature geothermal resource assessments of the western United States utilized weight-of-evidence and logistic regression methods to estimate resource favorability, but these analyses relied upon some expert decisions. While expert decisions can add confidence to aspects of the modeling process by ensuring only reasonable models are employed, expert decisions also introduce human bias into assessments. This bias presents a source of error that may affect the performance of the models and resulting resource estimates. Our study aims to reduce expert input through robust data-driven analyses and better-suited data science techniques, with the goals of saving time, reducing bias, and improving predictive ability. We present six favorability maps for geothermal resources in the western United States created using two strategies applied to three modern machine learning algorithms (logistic regression, support-vector machines, and XGBoost). To provide a direct comparison to previous assessments, we use the same input data as the 2008 U.S. Geological Survey (USGS) conventional moderate- to high-temperature geothermal resource assessment. The six new favorability maps required far less expert decision-making, but broadly agree with the previous assessment. Despite the fact that the 2008 assessment results employed linear methods, the non-linear machine learning algorithms (i.e., support-vector machines and XGBoost) produced greater agreement with the previous assessment than the linear machine learning algorithm (i.e., logistic regression). It is not surprising that geothermal systems depend on non-linear combinations of features, and we postulate that the expert decisions during the 2008 assessment accounted for system non-linearities. Substantial challenges to applying machine learning algorithms to predict geothermal resource favorability include severe class imbalance (i.e., there are very few known geothermal systems compared to the large area considered), and while there are known geothermal systems (i.e., positive labels), all other sites have an unknown status (i.e., they are unlabeled), instead of receiving a negative label (i.e., the known/proven absence of a geothermal resource). We address both challenges through a custom undersampling strategy that can be used with any algorithm and then evaluated using F1 scores.

western United States↗

GIS mapping of earthquake ground shaking in San Francisco, California

Severe earthquakes of the last decade in Mexico, Armenia, and the United States have reemphasized the importance of local geologic site conditions in estimating damage and consequent losses. Recent advances in geographic information system (GIS) technology have created new opportunities for maintaining and integrating extensive spatial databases for applications in seismic hazard analysis. Ground motion data and damage distributions from past earthquakes are combined with GIS databases of geologic information to prepare preliminary maps for inferring input ground motion levels for earthquake resistant design. Maps of bedrock elevation, surface topography, and surface geology are used to develop maps of soil thickness and predominant period. Ground motion attenuation relationships are used to create maps estimating ground shaking intensity for a uniform ground condition. Relationships between geologic characteristics, ground motion amplification, and earthquake intensity are used to produce amplification capability maps. Estimated ground shaking for the uniform ground condition is combined with amplification capability to develop maps predicting regional ground shaking intensity. The methods of predictive GIS mapping described here are useful for estimating characteristics of input ground motion in many urbanized seismic regions of the world.

California↗

A simulation model of land-use change in the Lake Tahoe Basin of California and Nevada, as used in a decision-support system

The Tahoe Land-Use Change model is a stochastic, spatially explicit simulation of future land-use change—in particular, development and retirement of individual parcels—in the Lake Tahoe Basin of California and Nevada. The Federal, State, and regional management agencies responsible for the basin are revising and integrating their 20-year plans to meet various goals, including maintaining or improving several environmental (e.g., lake clarity, forest health) and socioeconomic (e.g., affordable housing) characteristics. To assist this effort, the model projects the long-term outcomes of land-use-management decisions, including those relating to existing and potential government regulations, development activities, and conservation practices. The model results are probabilistic maps of parcel-specific changes in land use and the resulting changes in the amount and locations of developed parcels and land-use change. To capture the uncertainties and variation in the exact parcels of land selected for development or retirement by individuals acting in the basin, a single model run includes multiple iterations, from which cumulative statistics are taken to describe the results. The purpose of the model is to generate changes in the amounts and types of land use and land cover that form inputs to a basinwide model of pollutant loading to Lake Tahoe, which, in turn, generates inputs to a lake-clarity model. Together, these three models form a chain of tools that link land-use decisions to changes in a critical environmental quality—the clarity of Lake Tahoe—within a decision-support context. Eventually, these three models will become part of a larger, more complete decision-support system.

California, Nevada↗

Drought prediction and water availability: A report on the 2022 ​​USGS-NIDIS National Listening Session Series

The U.S. Geological Survey (USGS) and NOAA’s National Integrated Drought Information System (NIDIS) conducted a series of four Listening Sessions in 2022 – each with a different application or topical focus – to seek input on priorities and needs related to predicting water availability changes under drought conditions at national and regional scales. This input was gathered to help inform the USGS Drought Program, regional and national drought efforts at NIDIS, and other national drought efforts. The series started with a February 2022 kick-off that introduced the series of Listening Sessions being held from March through September 2022. This kickoff also provided an overview of the USGS Drought Program’s work to characterize hydrological (e.g., streamflow and groundwater) drought, drought variability, drivers, and trends over the past century. Participants in these Listening Sessions included diverse stakeholder representation and perspectives. The first of the four Listening Sessions focused on streamflow (March 3, 2022), and included a short introduction to the USGS national streamflow drought research, the properties of a national drought prediction system, as well as presentations by other agencies on different drought prediction and forecasting efforts. The second session focused on groundwater (May 5, 2022), and included presentations on groundwater drought, sustainable groundwater management, and improving our understanding of soil moisture, groundwater, and surface water drought. The third session focused on water use (July 14, 2022), and included a discussion of the different drought types, as well as an introduction to several key projects, including the USGS Upper Colorado River Basin Study, the Ogallala Data Directory project, and a multi-agency drought prediction partnership in Oklahoma. The fourth and final Listening Session focused on water availability prediction for ecosystems (September 8, 2022), and included presentations on the development of a national capacity for eco-hydrological and drought science, building climate resilience, and actionable ecodrought resources.

Report↗

Panel review of Ground Motion Characterization Model in 2023 NSHM

The 2023 National Seismic Hazard Model (NSHM; Petersen et al., 2023) has two major components – a seismic source characterization (SSC) model and a ground motion characterization (GMC) model. The US Geological Survey (USGS) established separate panels to review and provide input on these two models. Both panels are advisory, meaning that they provide input on technical issues for consideration by the USGS NSHM team, but they do not have decision making authority. Here, we report on the activities and recommendations of the Ground Motion Characterization Panel, made up of the authors of this review. Final modeling decisions are presented in separate USGS documents, including Petersen et al., (2023) and Moschetti et al., (2023). Where modeling decisions depart from our recommendations, the rationale is explained in those publications.

Report↗