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At least 235 records · Page 13Linked to original sources
USGS2022

Discovery and potential ramifications of reduced iron-bearing nanoparticles — Magnetite, wüstite, and zero-valent iron — In wildland–urban interface fire ashes

The increase in fires at the wildland–urban interface has raised concerns about the potential environmental impact of ash remaining after burning. Here, we examined the concentrations and speciation of iron-bearing nanoparticles in wildland–urban interface ash. Total iron concentrations in ash varied between 4 and 66 mg g −1 . Synchrotron X-ray absorption near-edge structure (XANES) spectroscopy of bulk ash samples was used to quantify the relative abundance of major Fe phases, which were corroborated by transmission electron microscopy measurements. Maghemite (γ-(Fe 3+ ) 2 O 3 ) and magnetite (γ-Fe 2+ (Fe 3+ ) 2 O 4 ) were detected in most ashes and accounted for 0–90 and 0–81% of the spectral weight, respectively. Ferrihydrite (amorphous Fe( III )–hydroxide, (Fe 3+ ) 5 HO 8 ·4H 2 O), goethite (α-Fe 3+ OOH), and hematite (α-Fe 3+ 2 O 3 ) were identified less frequently in ashes than maghemite and magnetite and accounted for 0–65, 0–54, and 0–50% of spectral weight, respectively. Other iron phases identified in ashes include wüstite (Fe 2+ O), zerovalent iron, FeS, FeCl 2 , FeCl 3 , FeSO 4 , Fe 2 (SO 4 ) 3 , and Fe(NO 3 ) 3 . Our findings demonstrate the impact of fires at the wildland–urban interface on iron speciation; that is, fires can convert iron oxides ( e.g. , maghemite, hematite, and goethite) to reduced iron phases such as magnetite, wüstite, and zerovalent iron. Magnetite concentrations ( e.g. , up to 25 mg g −1 ) decreased from black to gray to white ashes. Based on transmission electron microscopy (TEM) analyses, most of the magnetite nanoparticles were less than 500 nm in size, although larger particles were identified. Magnetite nanoparticles have been linked to neurodegenerative diseases as well as climate change. This study provides important information for understanding the potential environmental impacts of fires at the wildland–urban interface, which are currently poorly understood.

Environmental Science Nano↗
USGS2024

Next generation public supply water withdrawal estimation for the conterminous United States using machine learning and operational frameworks

Estimation of human water withdrawals is more important now than ever due to uncertain water supplies, population growth, and climate change. Fourteen percent of the total water withdrawal in the United States is used for public supply, typically including deliveries to domestic, commercial, and occasionally including industrial, irrigation, and thermoelectric water withdrawal. Stewards of water resources in the USA require estimates of water withdrawals to manage and plan for future demands and sustainable water supplies. This study compiled the most comprehensive conterminous United States water withdrawal data set to date and developed a machine learning framework for estimating public supply withdrawals and associated uncertainty for the period 2000–2020. The modeling approach provides service area resolution estimates to allow for annual and monthly water withdrawal estimation while incorporating a complex array of driving factors that include hydroclimatic, demographic, socioeconomic, geographic, and land use factors. Model results reveal highly variable and lognormally distributed per-capita water withdrawal, spanning from 30 to 650 gallons per capita per day (GPCD), across community, regional, and national scales, with pronounced seasonal variations. Analysis of estimated withdrawal trends indicates that the national annual average withdrawal experienced a decline at a rate of 0.58 GPCD/year during the period from 2000 to 2020. Model interpretation reveals a complex interplay between public supply withdrawal and key predictors, including population size, warm-season precipitation, counts of large buildings and houses, and areas of urban and commercial land use. The developed models can forecast future public supply driven by various climate, demographic, and socioeconomic scenarios.

conterminous United States↗
USGS2025

Regional analysis of the dependence of peak-flow quantiles on climate with application to adjustment to climate trends

Standard flood-frequency analysis methods rely on an assumption of stationarity, but because of growing understanding of climatic persistence and concern regarding the effects of climate change, the need for methods to detect and model nonstationary flood frequency has become widely recognized. In this study, a regional statistical method for estimating the effects of climate variations on annual maximum (peak) flows that allows for the effect to vary by quantile is presented and applied. The method uses a panel–quantile regression framework based on a location-scale model with two fixed effects per basin. The model was fitted to 330 selected gauged basins in the midwestern United States, filtered to remove basins affected by reservoir regulation and urbanization. Precipitation and discharge simulated using a water-balance model at daily and annual time scales were tested as climate variables. Annual maximum daily discharge was found to be the best predictor of peak flows, and the quantile regression coefficients were found to depend monotonically on annual exceedance probability. Application of the models to gauged basins is demonstrated by estimating the peak-flow distributions at the end of the study period (2018) and, using the panel model, to the study basins as-if-ungauged by using leave-one-out cross validation, estimating the fixed effects using static basin characteristics, and parameterizing the water-balance model discharge using median parameters. The errors of the quantiles predicted as-if-ungauged approximately doubled compared to the errors of the fitted panel model.

Hydrology↗
USGS2025

A nationwide evaluation of crowd-sourced ambient temperature data

Growing concerns about heat in urban areas paired with the sparsity of weather stations have resulted in individuals drawing on data from citizen science sensor networks to fill in data gaps. The PurpleAir are the most widely-used low-cost air quality sensors in the contiguous United States with 14,777 deployed between 1 Jan 2017 and 20 July 2021. Although the air quality data from PurpleAir sensors have been widely studied, less attention has been paid to reported temperature. We compare temperature metrics reported by PurpleAir sensors with a gridded temperature product, the North American Land Data Assimilation System (NLDAS)-2, which although not a gold-standard measure of temperature, is widely used in epidemiologic research. We evaluate the lag between indoor and outdoor PurpleAir temperatures. We report associations of the difference between outdoor PurpleAir temperatures and NLDAS-2 temperatures, an indicator of degradation, and the duration of sensor operation. Finally, based on the temperature range recorded by the outdoor PurpleAir sensors vis.a.vis NLDAS-2 temperatures, we provide a list of 271 (2.5%) sensors potentially misclassified as outdoor and likely located indoors. We observed that outdoor PurpleAir sensors agreed well with NLDAS-2 (R2 > 0.82). This association broke down under warm conditions (daily average NLDAS ≥ 21.1oC). Landcover and climate zone were significant modifiers of the association between PurpleAir and NLDAS-2 temperature metrics with the poorest PurpleAir- NLDAS-2 agreement in urban areas. Indoor PurpleAir temperatures lagged hourly NLDAS temperatures by two hours across almost all climate zones. The mean difference in hourly PurpleAir and NLDAS-2 temperatures increased by 0.57oC for every operational year, suggesting that careful attention must be paid to degradation. Overall, we find for use in epidemiological studies, that the PurpleAir sensor data is a reliable metric of daytime mean air temperature, but researchers should be aware of its limitations when examining extreme heat, or when aggregating sensor data across multiple years.

Frontiers of Environmental Science and Engineering↗
USGS2016

Impacts of climate change and renewable energy development on habitat of an endemic squirrel, Xerospermophilus mohavensis , in the Mojave Desert, USA

Predicting changes in species distributions under a changing climate is becoming widespread with the use of species distribution models (SDMs). The resulting predictions of future potential habitat can be cast in light of planned land use changes, such as urban expansion and energy development to identify areas with potential conflict. However, SDMs rarely incorporate an understanding of dispersal capacity, and therefore assume unlimited dispersal in potential range shifts under uncertain climate futures. We use SDMs to predict future distributions of the Mojave ground squirrel, Xerospermophilus mohavensis Merriam, and incorporate partial dispersal models informed by field data on juvenile dispersal to assess projected impact of climate change and energy development on future distributions of X. mohavensis . Our models predict loss of extant habitat, but also concurrent gains of new habitat under two scenarios of future climate change. Under the B1 emissions scenario- a storyline describing a convergent world with emphasis on curbing greenhouse gas emissions- our models predicted losses of up to 64% of extant habitat by 2080, while under the increased greenhouse gas emissions of the A2 scenario, we suggest losses of 56%. New potential habitat may become available to X. mohavensis , thereby offsetting as much as 6330 km 2 (50%) of the current habitat lost. Habitat lost due to planned energy development was marginal compared to habitat lost from changing climates, but disproportionately affected current habitat. Future areas of overlap in potential habitat between the two climate change scenarios are identified and discussed in context of proposed energy development.

California↗
USGS1990

The California Valley grassland

Grasslands are distributed throughout California from Oregon to Baja California Norte and from the coast to the desert (Brown 1982) (Figure 1). This review will focus on the dominant formation in cismontane California, a community referred to as Valley Grassland (Munz 1959). Today, Valley Grassland is dominated by non-native annual grasses in genera such as Avena (wild oat), Bromus (brome grass), and Hordeum (barley), and is often referred to as the California annual grassland. On localized sites, native perennial bunchgrasses such as Stipa pultra (purple needle grass) may dominate and such sites are interpreted to be remnants of the pristine valley grassland. In northwestern California a floristically distinct formation of the Valley Grassland, known as Coast Prairie (Munz 1959) or Northern Coastal Grassland (Holland and Keil 1989) is recognized. The dominant grasses include many native perennial bunchgrasses in genera such as Agrostis , Calamagrostis , Danthonia , Deschampsia , Festuca , Koeleria and Poa (Heady et al. 1977). Non-native annuals do not dominate, but on some sites non-native perennials like Anthoxanthum odoratum may colonize the native grassland (Foin and Hektner 1986). Elevationally, California's grasslands extend from sea level to at leas 1500 m. The upper boundary is vague because montane grassland formations are commonly referred to as meadows; a community which Munz (1959) does not recognize. Holland and Keil (1989) describe the montane meadow as an azonal community; that is, a community restricted not so much to a particular climatic zone but rather controlled by substrate characteristics. They consider poor soil-drainage an over-riding factor in the development of montane meadows and, in contrast to grasslands, meadows often remain green through the summer drought. Floristically, meadows are composed of graminoids; Cyperaceae, Juncaceae, and rhizomatous grasses such as Agropyron (wheat grass). Some bunchgrasses, such as Muhlenbergia rigens , are found in both montane meadows and moister grasslands. Forbs when present, are typically perennials. East of the interior ranges, grasslands are uncommon although native perennial bunchgrasses in genera such as Stipa , Hilaria and Aristida are common in steppe and desert scrub. Today, Valley Grassland covers nearly 7 million ha or 17% or the state (Huenneke 1989), although other sources list less than half this amount (Jones and Stokes 1987). There is some evidence that extent of the grassland region has not changed since pre-European conditions, although the spatial distribution of grasslands has likely changed substantially (Huenneke 1989). That is, many current grasslands previously may have been dominated by other vegetation types and vice versa. Without question, many former grasslands have been converted to agricultural and urban use (Barry 1972). The Valley Grassland community occurs in regions characterized by a broad range of climatic conditions. Average January temperatures may range from 5°C to 15°C and July temperatures from 15°C to 30°C (NOAA 1988). Annual precipitation ranges from approximately 12 cm to over 200 cm, although all sites are characterized by a summer drought of 4-8 months (Heady 1977). Grasslands are well developed on deep, fine-textured soils although they are not restricted to such conditions (Wells 1962, Adams 1964, Heady 1977).

California↗
USGS1986

Techniques for estimating flood-peak discharges from urban basins in Missouri

Techniques are defined for estimating the magnitude and frequency of future flood peak discharges of rainfall-induced runoff from small urban basins in Missouri. These techniques were developed from an initial analysis of flood records of 96 gaged sites in Missouri and adjacent states. Final regression equations are based on a balanced, representative sampling of 37 gaged sites in Missouri. This sample included 9 statewide urban study sites, 18 urban sites in St. Louis County, and 10 predominantly rural sites statewide. Short-term records were extended on the basis of long-term climatic records and use of a rainfall-runoff model. Linear least-squares regression analyses were used with log-transformed variables to relate flood magnitudes of selected recurrence intervals (dependent variables) to selected drainage basin indexes (independent variables). For gaged urban study sites within the State, the flood peak estimates are from the frequency curves defined from the synthesized long-term discharge records. Flood frequency estimates are made for ungaged sites by using regression equations that require determination of the drainage basin size and either the percentage of impervious area or a basin development factor. Alternative sets of equations are given for the 2-, 5-, 10-, 25-, 50-, and 100-yr recurrence interval floods. The average standard errors of estimate range from about 33% for the 2-yr flood to 26% for the 100-yr flood. The techniques for estimation are applicable to flood flows that are not significantly affected by storage caused by manmade activities. Flood peak discharge estimating equations are considered applicable for sites on basins draining approximately 0.25 to 40 sq mi. (Author 's abstract)

Water-Resources Investigations Report↗
USGS2018

Coastal wetland adaptation to sea level rise: Quantifying potential for landward migration and coastal squeeze

Coastal wetland ecosystems are expected to migrate landwards in response to rising seas. However, due to differences in topography and coastal urbanization, estuaries vary in their ability to accommodate migration. Low‐lying urban areas can constrain migration and lead to wetland loss (i.e. coastal squeeze), especially where existing wetlands cannot keep pace with rising seas via vertical adjustments. In many estuaries, there is a pressing need to identify landward migration corridors and better quantify the potential for landward migration and coastal squeeze. We quantified and compared the area available for landward migration of tidal saline wetlands and the area where urban development is expected to prevent migration for 39 estuaries along the wetland‐rich USA Gulf of Mexico coast. We did so under three sea level rise scenarios (0.5, 1.0, and 1.5 m by 2100). Within the region, the potential for wetland migration is highest within certain estuaries in Louisiana and southern Florida (e.g. Atchafalaya/Vermilion Bays, Mermentau River, Barataria Bay, and the North and South Ten Thousand Islands estuaries). The potential for coastal squeeze is highest in estuaries containing major metropolitan areas that extend into low‐lying lands. The Charlotte Harbor, Tampa Bay, and Crystal‐Pithlachascotee estuaries (Florida) have the highest amounts of urban land expected to constrain wetland migration. Urban barriers to migration are also high in the Galveston Bay (Texas) and Atchafalaya/Vermilion Bays (Louisiana) estuaries. Synthesis and applications . Coastal wetlands provide many ecosystem services that benefit human health and well‐being, including shoreline protection and fish and wildlife habitat. As the rate of sea level rise accelerates in response to climate change, coastal wetland resources could be lost in areas that lack space for landward migration. Migration corridors are particularly important in highly urbanized estuaries where, due to low‐lying coastal development, there is not space for wetlands to move and adapt to sea level rise. Future‐focused landscape conservation plans that incorporate the protection of wetland migration corridors can increase the adaptive capacity of these valuable ecosystems and simultaneously decrease the vulnerability of coastal human communities to the harmful effects of rising seas.

Gulf of Mexico coast↗
USGS2012

Ecosystem services from converted land: the importance of tree cover in Amazonian pastures

Deforestation is responsible for a substantial fraction of global carbon emissions and changes in surface energy budgets that affect climate. Deforestation losses include wildlife and human habitat, and myriad forest products on which rural and urban societies depend for food, fiber, fuel, fresh water, medicine, and recreation. Ecosystem services gained in the transition from forests to pasture and croplands, however, are often ignored in assessments of the impact of land cover change. The role of converted lands in tropical areas in terms of carbon uptake and storage is largely unknown. Pastures represent the fastest-growing form of converted land use in the tropics, even in some areas of rapid urban expansion. Tree biomass stored in these areas spans a broad range, depending on tree cover. Trees in pasture increase carbon storage, provide shade for cattle, and increase productivity of forage material. As a result, increasing fractional tree cover can provide benefits land managers as well as important ecosystem services such as reducing conversion pressure on forests adjacent to pastures. This study presents an estimation of fractional tree cover in pasture in a dynamic region on the verge of large-scale land use change. An appropriate sampling interval is established for similar studies, one that balances the need for independent samples of sufficient number to characterize a pasture in terms of fractional tree cover. This information represents a useful policy tool for government organizations and NGOs interested in encouraging ecosystem services on converted lands. Using high spatial resolution remotely sensed imagery, fractional tree cover in pasture is quantified for the municipality of Rio Branco, Brazil. A semivariogram and devolving spatial resolution are employed to determine the coarsest sampling interval that may be used, minimizing effects of spatial autocorrelation. The coarsest sampling interval that minimizes spatial dependence was about 22 m. The area-weighted fractional tree cover for the study area was 1.85 %, corrected for a slight bias associated with the coarser sampling resolution. The pastures sampled for fractional tree cover were divided between ‘high’ and ‘low’ tree cover, which may be the result of intentional incorporation of arboreal species in pasture. Further research involving those ranchers that have a higher fractional tree cover may indicate ways to promote the practice on a broader scale in the region.

Urban Ecosystems↗
USGS2015

An integrated approach to modeling changes in land use, land cover, and disturbance and their impact on ecosystem carbon dynamics: a case study in the Sierra Nevada Mountains of California

Increased land-use intensity (e.g. clearing of forests for cultivation, urbanization), often results in the loss of ecosystem carbon storage, while changes in productivity resulting from climate change may either help offset or exacerbate losses. However, there are large uncertainties in how land and climate systems will evolve and interact to shape future ecosystem carbon dynamics. To address this we developed the Land Use and Carbon Scenario Simulator (LUCAS) to track changes in land use, land cover, land management, and disturbance, and their impact on ecosystem carbon storage and flux within a scenario-based framework. We have combined a state-and-transition simulation model (STSM) of land change with a stock and flow model of carbon dynamics. Land-change projections downscaled from the Intergovernmental Panel on Climate Change’s (IPCC) Special Report on Emission Scenarios (SRES) were used to drive changes within the STSM, while the Integrated Biosphere Simulator (IBIS) ecosystem model was used to derive input parameters for the carbon stock and flow model. The model was applied to the Sierra Nevada Mountains ecoregion in California, USA, a region prone to large wildfires and a forestry sector projected to intensify over the next century. Three scenario simulations were conducted, including a calibration scenario, a climate-change scenario, and an integrated climate- and land-change scenario. Based on results from the calibration scenario, the LUCAS age-structured carbon accounting model was able to accurately reproduce results obtained from the process-based biogeochemical model. Under the climate-only scenario, the ecoregion was projected to be a reliable net sink of carbon, however, when land use and disturbance were introduced, the ecoregion switched to become a net source. This research demonstrates how an integrated approach to carbon accounting can be used to evaluate various drivers of ecosystem carbon change in a robust, yet transparent modeling environment.

California↗
USGS2010

Assessing the response of the Pamlico Sound, North Carolina, USA to human and climatic disturbances: Management implications

The Pamlico Sound (PS) with its sub-estuaries is the largest lagoonal ecosystem in the United States. It exhibits periodically strong salinity stratification and an average freshwater residence time of 1 year for the sound proper. This relatively long residence time promotes effective use and cycling of nutrients, allowing the system to support high rates of primary and secondary production, and serve as a vitally important fisheries nursery. This hydrologic characteristic also makes the system highly sensitive to nutrient over-enrichment and eutrophication. The PS is experiencing ecological change in response to increasing human activity and climatic perturbations. Human impacts include a rise in nutrient, sediment, and other pollutant loads that accompany urbanization and agricultural and industrial growth in its watersheds and airsheds. Since the mid-1990s, the PS has witnessed a sudden rise in tropical storm and hurricane impacts, with eight hurricanes and four tropical storms having made landfall in the PS watershed during the 1996 to 2007 period. Each of these storms had unique hydrologic, nutrient, and other pollutant loading effects. In addition, since the early 2000s, the region has experienced record droughts, which are continuing. Variable freshwater discharges from storms and droughts have caused large oscillations in nutrient enrichment, reflected ultimately in differential phytoplankton production, biomass, and community compositional responses. Floodwaters from the two wettest hurricanes, Fran (1996) and Floyd (1999), and from Tropical Storm Ernesto (2006) exerted long-term (months) effects on hydrology, nutrient loads, and algal production. Windy but relatively dry hurricanes, like Irene (1999) and Isabel (2003), caused strong vertical mixing, storm surges, but relatively minor changes in river flow, flushing, and nutrient loads. These contrasting effects are accompanied by biogeochemical (hypoxia, nutrient cycling) and habitat alterations, and associated food web disturbances. Each storm type influenced algal growth and compositional dynamics; however, their respective ecological impacts differed substantially. Changes in hydrologic and wind forcing resulting from changes in frequency and intensity of storms and droughts strongly influence water and habitat quality. These changes must be integrated with nutrient loading/dilution effects when assessing and predicting ecological responses to nutrient and hydrologic variability on this and other large lagoonal ecosystems.

North Carolina↗
USGS2016

Chaparral

One of the most dynamic California ecosystems is chaparral. Dominated by evergreen, sclerophyllous shrubs and small trees, chaparral is the most extensive vegetation type in the state (Figure 1). The nearly impenetrable tangle of stiff branches of this unusual vegetation inhibits exploration, and as a consequence the public know little about its natural history and unique characteristics. This under-valued ecosystem is recognized instead by the threat of its extensive, high-intensity canopy-burning wildfires that characterize the dry summer and fall seasons of the state. Because urban areas frequently share borders or intermix with chaparral, societal interests often conflict with conservation of this ecosystem, and understanding its history and dynamics are a key to appreciating its importance. In this chapter we emphasize the principal structure and dynamics of this important ecosystem. The long summer rainless period has strong impacts on all organisms and, importantly, the droughts influence the fire regime that characterizes chaparral. An ecosystem currently characterized by a specific drought and wildfire regime can expect significant impacts from climate change. Because of its dominance at lower elevations, chaparral also is frequently found at or near the boundaries of urban developments and metropolitan centers. Attempts to suppress fire also affect chaparral dynamics in the long absence of fire. The conflicts between the impacts of chaparral wildfire and human life and structures has been an aspect of California’s history since the beginning, but as development encroaches ever more into chaparral regions, the conflicts have increased. Consequently, understanding this vegetation is important not only because of its significance in understanding ecological evolution and the ecological services provided by chaparral, but also because of its direct impacts on human settlements.

Book chapter↗
USGS2018

Drivers of variability in public‐supply water use across the contiguous United States

This study explores the relationship between municipal water use and an array of climate, economic, behavioral, and policy variables across the contiguous U.S. The relationship is explored using Bayesian‐hierarchical regression models for over 2,500 counties, 18 covariates, and three higher‐level grouping variables. Additionally, a second analysis is included for 83 cities where water price and water conservation policy information is available. A hierarchical model using the nine climate regions (product of National Oceanic and Atmospheric Administration) as the higher‐level groups results in the best out‐of‐sample performance, as estimated by the Widely Available Information Criterion, compared to counties grouped by urban continuum classification or primary economic activity. The regression coefficients indicate that the controls on water use are not uniform across the nation: e.g., counties in the Northeast and Northwest climate regions are more sensitive to social variables, whereas counties in the Southwest and East North Central climate regions are more sensitive to environmental variables. For the national city‐level model, it appears that arid cities with a high cost of living and relatively low water bills sell more water per customer, but as with the county‐level model, the effect of each variable depends heavily on where a city is located.

Water Resources Research↗
USGS1978

Interim report on streamflow, sediment discharge, and water quality in the Calabazas Creek Basin, Santa Clara County, California

Streamflow, sediment-discharge, and water-quality data are being collected in the Calabazas Creek basin, Santa Clara County, Calif., to determine annual water and sediment discharge at base-line conditions that are representative of a basin prior to urbanization. Results of the first 3 years of the study (1973-75) are given in this report. Climatic conditions during this period were representative of a very wet year (1973) and 2 years of above-average rainfall (1974 and 1975). Daily water and sediment discharge were monitored at three primary stations, and periodic measurements were made at five secondary stations during selected storms. Most of the total annual sediment discharge at each station was transported during a few days each year. Maximum daily sediment discharge in a given year ranged from 23 to 62 percent of the annual total. Daily water discharge at the gaging station Calabazas Creek at Rainbow Drive, near Cupertino, ranged from no flow to 3.31 cubic meters per second. Streamflow at this location was significantly augmented during low flow by diversion of water from the South Bay Aqueduct. Annual sediment discharge at Calabazas Creek at Rainbow Drive was 4,900 t in 1974 and 9,570 t in 1975. A large quantity of sediment was trapped in a debris basin at Comer Drive upstream from this station during both years. If this sediment had not been trapped, sediment discharge at the station would have been about 35 percent greater in 1974 and 30 percent greater in 1975. Most of the trapped sediment consists of sand and gravel that would probably have been deposited in the Calabazas Creek channel downstream from the station. (Woodard-USGS)

California↗
USGS1986

ESTIMATION OF URBAN STORM-RUNOFF LOADS.

The United States was divided into three regions, on the basis of mean annual rainfall, to decrease the variability in storm-runoff constituent loads and to improve regression relations with basin and climatic characteristics. Multiple-regression analyses, in progress, are being refined to determine the best regression models for each of the storm-runoff constituent loads in each of the three regions. These techniques, when finalized, can be used to estimate storm-runoff constituent loads for gaged and ungaged urban watersheds. The preliminary standard errors of estimate for five constituents examined to date ranged from 54 to 223 percent, and the coefficients of determination (r**2) ranged from 0. 39 to 0. 94. Total storm rainfall and total contributing drainage area appear to be the most significant independent variables in the regression models. This paper is a progress report on preliminary results of estimating storm-runoff constituent loads for ungaged watersheds.

Conference Paper↗
USGS2014

Contaminants from Cretaceous black shale: II. Effect of geology, weathering, climate, and land use on salinity and selenium cycling, Mancos Shale landscapes, southwestern United States

The Cretaceous Mancos Shale (MS) is a known nonpoint source for a significant portion of the salinity and selenium (Se) loads in the Colorado River in the southwestern United States and northwestern corner of Mexico. These two contaminants pose a serious threat to rivers in these arid regions where water supplies are especially critical. Tuttle et al. (companion paper) investigates the cycling of contaminants in a Colorado River tributary watershed (Uncompahgre River, southwestern Colorado) where the MS weathers under natural conditions. This paper builds on those results and uses regional soil data in the same watershed to investigate the impact of MS geology, weathering intensity, land use, and climate on salt and Se storage in and flux from soils on the natural landscape, irrigated agriculture fields, areas undergoing urban development, and wetlands. The size of salinity and Se reservoirs in the MS soils is quantified. Flux calculations show that during modern weathering, natural landscapes cycle salt and Se; however, little of it is released for transport to the Uncompahgre River (10% of the annual salinity and 6% of the annual Se river loads). When irrigated, salinity and Se loads from the MS soil increase (26% and 57% of the river load, respectively), causing the river to be out of compliance with Federal and State Se standards. During 100 years of irrigation, seven times more Se has been removed from agricultural soil than what was lost from natural landscapes during the entire period of pedogenesis. Under more arid conditions, even less salt and Se are expected to be transported from the natural landscape. However, if wetter climates prevail, transport could increase dramatically due to storage of soluble phases in the non-irrigated soil. These results are critical input for water-resource and land-use managers who must decide whether or not the salinity and Se in a watershed can be managed, what sustainable mitigation strategies are possible, and what landscapes should be targeted. The broader implications include providing a reliable approach for quantifying nonpoint-source contamination from MS and other rock units elsewhere that weather under similar conditions and, together with results from our companion paper, address the complex interplay of geology, weathering, climate, and land use on contaminant cycling in the arid Southwest.

Colorado↗
USGS2022

Human populations in the world’s mountains: Spatio-temporal patterns and potential controls

Changing climate and human demographics in the world's mountains will have increasingly profound environmental and societal consequences across all elevations. Quantifying current human populations in and near mountains is crucial to ensure that any interventions in these complex social-ecological systems are appropriately resourced, and that valuable ecosystems are effectively protected. However, comprehensive and reproducible analyses on this subject are lacking. Here, we develop and implement an open workflow to quantify the sensitivity of mountain population estimates over recent decades, both globally and for several sets of relevant reporting regions, to alternative input dataset combinations. Relationships between mean population density and several potential environmental covariates are also explored across elevational bands within individual mountain regions (i.e. sub-mountain range scale). Globally, mountain population estimates vary greatly from 0.344 billion (<5% of the corresponding global total) to 2.289 billion (>31%) in 2015. A more detailed analysis using one of the population datasets (GHS-POP) revealed that in 35% of mountain sub-regions, population increased at least twofold over the 40-year period 19752015. The urban proportion of the total mountain population in 2015 ranged from 6% to 39%, depending on the combination of population and urban extent datasets used. At sub-mountain range scale, population density was found to be more strongly associated with climatic than with topographic and protected-area variables, and these relationships appear to have strengthened slightly over time. Such insights may contribute to improved predictions of future mountain population distributions under scenarios of future climatic and demographic change. Overall, our work emphasizes that irrespective of data choices, substantial human populations are likely to be directly affected by and themselves affect mountainous environmental and ecological change. It thereby further underlines the urgency with which the multitudinous challenges concerning the interactions between mountain climate and human societies under change must be tackled.

PLoS ONE↗
USGS2010

Lake temperature and ice cover regimes in the Alaskan Subarctic and Arctic: Integrated monitoring, remote sensing, and modeling

Lake surface regimes are fundamental attributes of lake ecosystems and their interaction with the land and atmosphere. High latitudes may be particularly sensitive to climate change, however, adequate baselines for these lakes are often lacking. In this study, we couple monitoring, remote sensing, and modeling techniques to generate baseline datasets of lake surface temperature and ice cover in the Alaskan Subarctic and Arctic. No detectable trends were observed during this study period, but a number of interesting patterns were noted among lakes and between regions. The largest Arctic lake was relatively unresponsive to air temperature, while the largest Subarctic lake was very responsive likely because it is fed by glacial runoff. Mean late summer water temperatures were higher than air temperatures with differences ranging from 1.7 to 5.4°C in Subarctic lakes and from 2.4 to 3.2°C in Arctic lakes. The warmest mean summer water temperature in both regions was in 2004, with the exception of Subarctic glacially fed lake that was highest in 2005. Ice-out timing had high coherence within regions and years, typically occurring in late May in Subarctic and in early-July in Arctic lakes. Ice-on timing was more dependent on lake size and depth, often varying among lakes within a region. Such analyses provide an important baseline of lake surface regimes at a time when there is increasing interest in high-latitude water ecosystems and resources during an uncertain climate future.

Journal of the American Water Resources Associatio↗