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USGS2015

Effects of land use on greenhouse gas fluxes and soil properties of wetland catchments in the Prairie Pothole Region of North America

Wetland restoration has been suggested as policy goal with multiple environmental benefits including enhancement of atmospheric carbon sequestration. However, there are concerns that increased methane (CH 4 ) emissions associated with restoration may outweigh potential benefits. A comprehensive, 4-year study of 119 wetland catchments was conducted in the Prairie Pothole Region of the north-central U.S. to assess the effects of land use on greenhouse gas (GHG) fluxes and soil properties. Results showed that the effects of land use on GHG fluxes and abiotic soil properties differed with respect to catchment zone (upland, wetland), wetland classification, geographic location, and year. Mean CH 4 fluxes from the uplands were predictably low (< 0.02 g CH 4 m − 2 day − 1 ), while wetland zone CH 4 fluxes were much greater (< 0.001–3.9 g CH 4 m − 2 day − 1 ). Mean cumulative seasonal CH 4 fluxes ranged from roughly 0–650 g CH 4 m − 2 , with an overall mean of approximately 160 g CH 4 m − 2 . These maximum cumulative CH 4 fluxes were nearly 3 times as high as previously reported in North America. The overall magnitude and variability of N 2 O fluxes from this study (< 0.0001–0.0023 g N 2 O m − 2 day − 1 ) were comparable to previously reported values. Results suggest that soil organic carbon is lost when relatively undisturbed catchments are converted for agriculture, and that when non-drained cropland catchments are restored, CH 4 fluxes generally are not different than the pre-restoration baseline. Conversely, when drained cropland catchments are restored, CH 4 fluxes are noticeably higher. Consequently, it is important to consider the type of wetland restoration (drained, non-drained) when assessing restoration benefits. Results also suggest that elevated N 2 O fluxes from cropland catchments likely would be reduced through restoration. The overall variability demonstrated by this study was consistent with findings of other wetland investigations and underscores the difficulty in quantifying the GHG balance of wetland systems.

Iowa, Minnesota, North Dakota, South Dakota↗

USGS2020

Spatiotemporal variation in occurrence and co-occurrence of pesticides, hormones, and other organic contaminants in rivers in the Chesapeake Bay Watershed, United States

Investigating the spatiotemporal dynamics of contaminants in surface water is crucial to better understand how introduced chemicals are interacting with and potentially influencing aquatic organisms and environments. Within the Chesapeake Bay Watershed, USA, there are concerns about the potential role of contaminant exposure on fish health. Evidence suggests that exposure to contaminants in surface water is causing immunosuppression and intersex in freshwater fish species. Despite these concerns, there is a paucity of information regarding the complex dynamics of contaminant occurrence and co-occurrence in surface water across both space and time. To address these concerns, we applied a Bayesian hierarchical joint-contaminant model to describe the occurrence and co-occurrence patterns of 28 contaminants and total estrogenicity across six river sites and over three years. We found that seasonal occurrence patterns varied by contaminant, with the highest occurrence probabilities during the spring and summer months. Additionally, we found that the proportion of agricultural landcover in the immediate catchment, as well as stream discharge, did not have a significant effect on the occurrence probabilities of most compounds. Four pesticides (atrazine, metolachlor, fipronil and simazine) co-occurred across sites after accounting for environmental covariates. These results provide baseline information on the contaminant occurrence patterns of several classes of compounds within the Chesapeake Bay Watershed. Understanding the spatiotemporal dynamics of contaminants in surface water is the first step in investigating the effects of contaminant exposure on fisheries and aquatic environments.

Delaware, Maryland, New York, Pennsylvania, Virgin↗

USGS2002

Organochlorine compounds and trace elements in fish tissue and streambed sediment in the Mobile River Basin, Alabama, Mississippi, and Georgia, 1998

During the summer of 1998, as part of the National Water-Quality Assessment Program, a survey was conducted to determine which organochlorine compounds and trace elements occur in fish tissues and streambed sediments in the Mobile River Basin, which includes parts of Alabama, Mississippi, Georgia, and Tennessee. The data collected were compared to guidelines related to wildlife, land use, and to 1991 and 1994 National Water-Quality Assessment Program Study-Unit data.Twenty-one sites were sampled in subbasins of the Mobile River Basin. The subbasins ranged in size from about 9 to 22,000 square miles and were dominated by either a single land use or a combination of land uses. The major land-use categories were urban, agriculture, and forest.Organochlorine compounds were widespread spatially in the Mobile River Basin. At least one organochlorine compound was reported at the majority of sampling sites (84 percent) and in a majority of whole-fish (80 percent) and streambed-sediment (52 percent) samples. Multiple organochlorine compounds were reported at 75 percent of the sites where fish tissues were collected and were reported at many of the streambed-sediment sampling sites (45 percent). The majority of concentrations reported, however, were less than 5 micrograms per kilogram in fish-tissue samples and less than 1 microgram per kilogram in streambed-sediment samples.The majority of trace elements analyzed in fish-liver tissue (86 percent) and streambed-sediment (98 percent) samples were reported during this study. Multiple trace elements were reported in all samples and at all sites.Based on comparisons of concentrations of organochlorine compounds and trace elements in fish-tissue and streambed-sediment samples in relation to National Academy of Science and National Academy of Engineering and Canadian tissue guidelines, probable-effects concentrations, and mean probable-effects concentration quotients for streambed sediment, the potential exists for adverse effects to wildlife at 15 (72 percent) of the sites sampled. The potential for adverse effects at these sites is because of the presence of residues or breakdown products related to polychlorinated biphenyls (PCB?s), chlordane, dichlorodiphenyltrichloroethane (DDT), chromium, lead, and zinc.The majority of compounds reported (65 percent) were chlordane, DDT, and PCB?s, or their breakdown products. Concentrations of chlordane and heptachlor epoxide in whole-fish tissue were positively correlated to the amount of urban land use in a basin. Total DDT concentrations in whole-fish tissues were positively correlated to agriculture.The relation of trace elements to land use is not as clear as the relation of organochlorine compounds to land use. This lack of clarity may be due to the possibility of geologic sources of trace elements in the Mobile River Basin and to the ubiquitous nature of many of these trace elements. However, there may be a correlation between the amount of urban land use and concentrations of antimony, cadmium, lead, and zinc in streambed-sediment samples from the Mobile River Basin.Fewer organochlorine compounds and trace elements were reported in samples from the Mobile River Basin than in samples collected during the 1991 and 1994 National Water-Quality Assessment Program studies. Of the organochlorine compounds analyzed nationally, 57 percent were reported in whole-fish tissue samples collected locally and 41 percent were reported in streambed-sediment samples collected locally, whereas 96 percent and 86 percent, respectively, were reported nationally. Of trace elements analyzed nationally, 86 percent were reported in fish-liver tissue locally and 95 percent were reported in streambed-sediment samples locally, whereas 95 percent and 98 percent, respectively, were reported nationally.In general, concentrations of organochlorine compounds and trace elements and the frequency with which they were reported in the Mobile River Basin are similar to or less than t

Alabama, Georgia, Mississippi, Tennessee↗

USGS2018

Surrounding land cover types as predictors of palustrine wetland vegetation quality in conterminous USA

The loss of wetland habitats and their often-unique biological communities is a major environmental concern. We examined vegetation data obtained from 380 wetlands sampled in a statistical survey of wetlands in the USA. Our goal was to identify which surrounding land cover types best predict two indices of vegetation quality in wetlands at the regional scale. We considered palustrine wetlands in four regions (Coastal Plains, North Central East, Interior Plains, and West) in which the dominant vegetation was emergent, forested, or scrub-shrub. For each wetland, we calculated weighted proportions of eight land cover types surrounding the area in which vegetation was assessed, in four zones radiating from the edge of the assessment area to 2 km. Using Akaike's Information Criterion, we determined the best 1-, 2- and 3-predictor models of the two indices, using the weighted proportions of the land cover types as potential predictors. Mean values of the two indices were generally higher in the North Central East and Coastal Plains than the other regions for forested and emergent wetlands. In nearly all cases, the best predictors of the indices were not the dominant surrounding land cover types. Overall, proportions of forest (positive effect) and agriculture (negative effect) surrounding the assessment area were the best predictors of the two indices. One or both of these variables were included as predictors in 65 of the 72 models supported by the data. Wetlands surrounding the assessment area had a positive effect on the indices, and ranked third (33%) among the predictors included in supported models. Development had a negative effect on the indices and was included in only 28% of supported models. These results can be used to develop regional management plans for wetlands, such as creating forest buffers around wetlands, or to conserve zones between wetlands to increase habitat connectivity.

Science of the Total Environment↗

USGS2021

Time marches on, but do the causal pathways driving instream habitat and biology remain consistent?

Stream ecosystems are complex networks of interacting terrestrial and aquatic drivers. To untangle these ecological networks, efforts evaluating the direct and indirect effects of landscape, climate, and instream predictors on biological condition through time are needed. We used structural equation modeling and leveraged a stream survey program to identify and compare important predictors driving condition of benthic macroinvertebrate and fish assemblages. We used data resampled 14 years apart at 252 locations across Maryland, USA. Sample locations covered a wide range of conditions that varied spatiotemporally. Overall, the relationship directions were consistent between sample periods, but their relative strength varied temporally. For benthic macroinvertebrates, we found that the total effect of natural landscape ( e.g ., elevation, longitude, latitude, geology) and land use ( i.e ., forest, development, agriculture) predictors was 1.4 and 1.5 times greater in the late 2010s compared to the 2000s. Moreover, the total effect of water quality ( e.g ., total nitrogen and conductivity) and habitat ( e.g ., embeddedness, riffle quality) was 1.2 and 4.8 times lower in the 2010s, respectively. For fish assemblage condition, the total effect of land use-land cover predictors was 2.3 times greater in the 2010s compared to the 2000s, while the total effect of local habitat was 1.4 times lower in the 2010s, respectively. As expected, we found biological assemblages in catchments with more agriculture and urban development were generally comprised of tolerant, generalist species, while assemblages in catchments with greater forest cover had more-specialized, less-tolerant species ( e.g., Ephemeroptera, Plecoptera, and Trichoptera taxa, clingers, benthic and lithophilic spawning fishes). Changes in the relative importance of landscape and land-use predictors suggest other correlated, yet unmeasured, proximal factors became more important over time. By untangling these ecological networks, stakeholders can gain a better understanding of the spatiotemporal relationships driving biological condition to implement management practices aimed at improving stream condition.

Maryland↗

USGS2023

Model-based assessment and mapping of total phosphorus enrichment in rivers with sparse reference data

Water nutrient management efforts are frequently coordinated across thousands of water bodies, leading to a need for spatially extensive information to facilitate decision making. Here we explore potential applications of a machine learning model of river low-flow total phosphorus (TP) concentrations to support landscape nutrient management. The model was trained, validated, and then applied for all rivers of Michigan, USA to identify potential drivers of nutrient variation, predict alteration in nutrient concentrations from minimally disturbed conditions, and explore reach specific sensitivity to riparian agricultural change. A boosted regression tree model of low-flow TP concentrations trained on natural and anthropogenic landscape predictors accounted for 53 % of variation in cross-validation data, had good accuracy, little bias, and plausible relationships between predictors and response. Percent riparian agricultural cover accounted for the greatest root mean square error reduction in the modeled response (33.2 %), followed by riparian soil permeability (12.9 %), watershed slope (9.6 %), and percent urban cover (9.6 %). An apparent non-linear relationship between TP concentrations and percent riparian agricultural cover suggested steep positive increases in stream TP concentrations between 10 and 30 % upstream riparian agricultural cover. Predicted minimally disturbed TP concentrations were spatially variable and ranged from 7.0 to 48.5 μg l −1 , with the highest concentrations in watersheds draining low-permeability lake plain soils. Comparison of minimally disturbed predictions to those from the early 2000s suggested that much of northern Michigan existed close to the reference condition, while lower Michigan streams were often substantially enriched. Our predicted values of minimally disturbed condition generally agree with previous studies but offer greater geographic specificity. Expanded application of machine learning modeling with landscape predictor data have great potential to inform large scale strategy development in landscapes with sparse reference data.

Michigan↗

USGS2006

North American prairie wetlands are important nonforested land-based carbon storage sites

We evaluated the potential of prairie wetlands in North America as carbon sinks. Agricultural conversion has resulted in the average loss of 10.1 Mg ha- 1 of soil organic carbon on over 16 million ha of wetlands in this region. Wetland restoration has potential to sequester 378 Tg of organic carbon over a 10-year period. Wetlands can sequester over twice the organic carbon as no-till cropland on only about 17% of the total land area in the region. We estimate that wetland restoration has potential to offset 2.4% of the annual fossil CO2 emission reported for North America in 1990. ?? 2005 Elsevier B.V. All rights reserved.

Science of the Total Environment↗

USGS2020

Economic, land use, and ecosystem services impacts of Rwanda's Green Growth Strategy: An application of the IEEM+ESM platform

We develop and link the Integrated Economic-Environmental Modeling (IEEM) Platform to ecosystem services modeling (ESM). The IEEM+ESM Platform is an innovative decision-making framework for exploring complex public policy goals and elucidating synergies and trade-offs between alternative policy portfolios. The IEEM+ESM approach is powerful in its ability to shed light on (i) change in land use and ecosystem services driven by public policy and the supply and demand responses of businesses and households; and (ii) impacts on standard economic indicators of concern to Ministries of Finance such as gross domestic product and employment, as well as changes in wealth and ecosystem services. The IEEM+ESM approach is being adopted rapidly and by the end of 2020, IEEM+ESM Platforms will be implemented for about 25 countries. To demonstrate the insights generated by the IEEM+ESM approach, we apply it to the analysis of alternative green growth strategies in Rwanda, a country that has made strong progress in reducing poverty and enhancing economic growth in the last 15 years. The case of Rwanda is particularly compelling as it faces intense pressure on its natural capital base and ecosystem services, already with the highest population density in Africa, which is projected to double by 2050. In applying IEEM+ESM and comparing the outcomes of Rwanda’s green growth policies, increasing fertilization of agricultural crops shows the largest economic gains but also trade-offs in environmental quality reflected through higher nutrient export and reduced water quality. Combining crop fertilization with forest plantations better balances critical ecosystem services and their role in underpinning economic development as Rwanda progresses toward its target of middle-income status by 2035. This application to Rwanda’s green growth strategy demonstrates the value-added of the IEEM+ESM approach in generating results that speak to both economic outcomes and impacts on market and non-market ecosystem services.

Science of the Total Environment↗

USGS2025

Land application of biosolid, livestock, and drilling wastes to US farmland: A potential pathway for the redistribution of contaminants in the environment

In the United States (U.S.), waste byproducts generated from the treatment of municipal waste (biosolids), production of livestock (livestock waste), and drilling of oil and gas wells (drilling waste) are commonly applied to agricultural lands. Although this can be a cost-effective reuse/disposal practice, there is limited research on the potential for contaminant exposures and effects on ecosystems, wildlife, and human health from such land applications. In this study, we conducted extensive chemical, microbial, and toxicity analyses of biosolid, livestock, and drilling wastes just prior to land application on agricultural lands at 34 sites across the U.S. Twenty-two analytical methods were used to determine potential contaminant exposures profiles for 452 organic and 114 inorganic chemicals, nine microbial groups, estrogenicity, and cytotoxicity. Analytical results document unique and substantial chemical, microbial, and toxicity profiles for these land-applied wastes. Of the three waste byproducts, biosolids contained the greatest concentrations of household chemicals, pesticides, pharmaceuticals, per-/polyfluoroalkyl substances, calcium, and phosphorus. Livestock waste contained the greatest concentrations of total and leachable dissolved organic carbon, biogenic hormones, mycotoxins, plant estrogens, total inorganic nitrogen, and potassium. Drilling waste contained the greatest concentrations of BTEX compounds (benzene, toluene, ethylbenzene, and xylenes), polycyclic aromatic hydrocarbons, rare-earth elements, barium, strontium, and uranium–thorium series radioisotopes. Biosolid and livestock wastes had greater culturable heterotrophic bacteria, halophilic bacteria, Escherichia coli ( E. coli ), enterococci, and staphylococci concentrations, and greater microbial diversity than drilling waste. Bioassay analyses indicated that exposure to contaminants in livestock wastes and biosolids could result in estrogenic effects, whereas exposure to contaminants in drilling waste could result in cytotoxic effects. Our study documents that current reuse/disposal practices for biosolid, livestock, and drilling wastes on agricultural lands could provide a potential pathway for the redistribution of unique and complex contaminant mixtures into the environment that have bioactive, endocrine disrupting, and carcinogenic characteristics. Results of this study provide a snapshot of chemical compositions and concentrations that can be used to inform the development of best-management practices to help maximize beneficial reuse of these wastes and minimize risk to the environment and human health.

Environmental Science: Processes & Impacts↗

USGS2011

A tree-ring reconstruction of the salinity gradient in the northern estuary of San Francisco Bay

Blue oak tree-ring chronologies correlate highly with winter–spring precipitation totals over California, with Sacramento and San Joaquin river stream flow, and with seasonal variations in the salinity gradient in San Francisco Bay. The convergence of fresh and saline currents can influence turbidity, sediment accumulation, and biological productivity in the estuary. Three selected blue oak chronologies were used to develop a 625-year-long reconstruction of the seasonal salinity gradient, or low salinity zone (LSZ), which provides a unique perspective on the interannual-to-decadal variability of this important estuarine habitat indicator. The reconstruction was calibrated with instrumental LSZ data for the winter–spring season, and explains 73% of the variance in the February–June position of the LSZ from 1956 to 2003. Because this calibration period post-dates the sweeping changes that have occurred to land cover, channel morphology, and natural streamflow regimes in California, the reconstruction provides an idealized estimate for how the LSZ might have fluctuated under the seasonal precipitation variations of the past 625 years, given the modern geometry and bathymetry of the estuary and land cover across the drainage basin. The February–June season integrates precipitation and runoff variability during the cool season, and does not extend into the late-summer dry season when LSZ extremes can negatively affect Sacramento–San Joaquin Delta (Delta) agriculture and some aquatic organisms. However, there is such strong inter-seasonal persistence in the instrumental LSZ data that precipitation totals during the cool season can strongly pre-condition LSZ position in late summer. The 625-year-long reconstruction indicates strong interannual and decadal variability, the frequent recurrence of consecutive 2-year LSZ maxima and minima, large-scale ocean atmospheric forcing, and an interesting asymmetrical influence of warm El Niño–Southern Oscillation (ENSO) events.

California↗

USGS2019

A bibliometric profile of the Remote Sensing Open Access Journal published by MDPI between 2009 and 2018

Remote Sensing Open Access Journal (RS OAJ) is an international leading journal in the field of remote sensing science and technology. It was first published in the year 2009 and is currently celebrating tenth year of publications. In this research, a bibliometric analysis of RS OAJ was conducted based on 5588 articles published during the 10-year (2009–2018) time-period. The bibliometric analysis includes a comprehensive set of indicators such as dynamics and trends of publications, journal impact factor, total cites, eigenfactor score, normalized eigenfactor, CiteScore, h-index, h-classic publications, most productive countries (or territories) and institutions, co-authorship collaboration about countries (territories), research themes, citation impact of co-occurrences keywords, intellectual structure, and knowledge commutation. We found that publications of RS OAJ presented an exponential growth in the past ten years. From 2010 to 2017 (for which complete years data were available), the h-index of RS OAJ is 67. From 2009–2018, RS OAJ includes publications from 129 countries (or territories) and 3826 institutions. The leading nations contributing articles, based on 2009–2018 data, and listed based on ranking were: China, United States, Germany, Italy, France, Spain, Canada, England, Australia, Netherlands, Japan, Switzerland and Austria. The leading institutions, also for the same period and listed based on ranking were: Chinese Academy of Sciences, Wuhan University, University of Chinese Academy of Sciences, Beijing Normal University, The university of Maryland, National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, China University of Geosciences, United States Geological Survey, German Aerospace Centre, University of Twente, and California Institute of Technology. For the year 2017, RS OAJ had an impressive journal impact factor of 3.4060, a CiteScore of 4.03, eigenfactor score of 0.0342, and normalized eigenfactor score of 3.99. In addition, based on 2009–2018, data co-word analysis determined that “remote sensing”, “MODIS”, “Landsat”, “LiDAR” and “NDVI” are the high-frequency of author keywords co-occurrence in RS OAJ. The main themes of RS OAJ are multi-spectral and hyperspectral remote sensing, LiDAR scanning and forestry remote sensing monitoring, MODIS and LAI data applications, Remote sensing applications and Synthetic Aperture Radar (SAR). Through author keywords citation impact analysis, we find the most influential keyword is Unmanned Aerial Vehicle (UAV), followed, forestry, Normalized Difference Vegetation Index (NDVI), terrestrial laser scanning, airborne laser scanning, forestry inventory, urban heat island, monitoring, agriculture, and laser scanning. By analyzing the intellectual structure of RS OAJ, we identify the main reference publications and find that the themes are about Random Forests, MODIS vegetation indices and image analysis, etc. RS OAJ ranks first in cited journals and third in citing, this indicates that RS OAJ has the internal knowledge flow. Our results will bring more benefits to scholars, researchers and graduate students, who hopes to get a quick overview of the RS OAJ. And this article will also be the starting point for communication between scholars and practitioners. Finally, this paper proposed a nuanced h-index (nh-index) to measure productivity and intellectual contribution of authors by considering h-index based on whether the one is first, second, third, or nth author. This nuanced approach to determining h-index of authors is powerful indicator of an academician’s productivity and intellectual contribution.

Remote Sensing↗

USGS2011

Structural and functional effects of herbicides on non-target organisms in aquatic ecosystems with an emphasis on atrazine

Herbicide use has increased dramatically around the world over the past 6 decades (Gianessi and Reigner, 2007). Few herbicides were in use in the 1950s. However, by 2001 approximately 1.14 billion kilograms of herbicides were applied globally for the control of undesireable vegetation in agricultural, silvicultural, lawncare, aquacultural, and irrigation/recreational water management activities (Kiely et al., 2004). Twenty-eight percent of the total mass of herbicides is applied in the United States, with the remaining 72 percent being applied elsewhere around the globe (Kiely et al., 2004). Herbicides represent 36% of global pesticide use, followed by insecticides (25%), fungicides (10%) and other chemical classes (Kiely et al., 2004). Agricultural production accounts for approximately 90% of herbicide use in the U.S. (Kiely et al., 2004). Gianessi and Reigner (2007) indicated that herbicides are routinely used on more than 90% of the area designated for large commercial crops including corn, soybeans, cotton, sugar beets, peanuts, and rice. Increased farm mechanization, technological advancements in production of inexpensive sources of inorganic nitrogen fertilizer (e.g., anhydrous ammonia), and conversion of forest, grassland, and wetland habitats to cropland has led to a tremendous increase in global food production over the past half-century. Herbicides have augmented advances in large-scale agricultural systems and have largely replaced mechanical and hand-weeding control mechanisms (Gianessi and Reigner, 2007). The wide-spread use of herbicides in agriculture has resulted in frequent chemical detections in surface and groundwaters (Gilliom, 2007). The majority of herbicides used are highly water soluble and are therefore prone to runoff from terrestrial environments. In additon, spray drift and atmospheric deposition can contribute to herbicide contamination of aquatic environments. Lastly, selected herbicides are deliberately applied to aquatic environments for controlling nuisance aquatic vegetation. Although aquatic herbicide exposure has been widely documented, these exposures are not necessarily related to adverse non-target ecological effects on natural communities in aquatic environments. This chapter evaluates the potential for effects of herbicides on the structure and function of aquatic envrionments at the population, community, and ecosystem levels of biological organization. In this manuscript I examine several critical aspects of the subject matter area: primary herbicides in use and chemical modes of action; the regulatory process used for registration and risk assessment of herbicides; data regarding non-target risks and the relative sensitivity of aquatic plants, inveretebrates, and fish to herbicides; and emerging areas of science regarding the potential for endocrine-disrupting effects of herbicides on aquatic vertebrates. Much of the focus of this paper is on atrazine due to the extensive database which exists regarding its fate and effects.

Book chapter↗

USGS2020

Trihalomethane precursors: Land use hot spots, persistence during transport, and management options

To meet drinking water regulations, rather than investing in costly treatment plant operations, managers can look for ways to improve source water quality; this requires understanding watershed sources and fates of constituents of concern. Trihalomethanes (THMs) are one of the major classes of regulated disinfection byproducts, formed when a specific fraction of the organic carbon pool—referred to as THM precursors—reacts with chorine and/or bromine during treatment. Understanding the source, fate, timing and duration of the organic compounds that react to form THMs will allow identification of targeted and effective management actions. In this study we evaluated THM precursor contributions from multiple land use categories and hydrologic contexts, including novel data for urban land uses that demonstrate strong potential to release water with high THM formation potential (THMFP; median 618 μg L −1 ): greater than storm runoff integrated across a mixed-use (1/3 natural, 2/3 agricultural) watershed (median 460 μg L −1 ), irrigation runoff from agricultural systems (357 μg L −1 ), or runoff from a natural forested (median 123 μg L −1 ) and shrubland/grassland (median 259 μg L −1 ) watersheds. While individual storm events released high THM precursor concentrations over short periods, dry season agricultural irrigation as well as urban landscapes have the potential to release water high in THM precursors for several months. Experimental bioassays and sampling along 333 miles of the California Aqueduct confirmed bioavailability and photooxidation potential of less than 10% for THM precursors, suggesting that rivers with residence times of days to weeks may act as THM precursor conduits, shuttling THM precursors from hundreds of miles away to drinking water intakes with minimal degradation. This finding has considerable implications for water managers, who may therefore consider THM precursor management strategies that target even sources located far upstream.

California↗

USGS2023

Contaminant exposure and transport from three potential reuse waters within a single watershed

Global demand for safe and sustainable water supplies necessitates a better understanding of contaminant exposures in potential reuse waters. In this study, we compared exposures and load contributions to surface water from the discharge of three reuse waters (wastewater effluent, urban stormwater, and agricultural runoff). Results document substantial and varying organic-chemical contribution to surface water from effluent discharges (e.g., disinfection byproducts [DBP], prescription pharmaceuticals, industrial/household chemicals), urban stormwater (e.g., polycyclic aromatic hydrocarbons, pesticides, nonprescription pharmaceuticals), and agricultural runoff (e.g., pesticides). Excluding DBPs, episodic storm-event organic concentrations and loads from urban stormwater were comparable to and often exceeded those of daily wastewater-effluent discharges. We also assessed if wastewater-effluent irrigation to corn resulted in measurable effects on organic-chemical concentrations in rain-induced agricultural runoff and harvested feedstock. Overall, the target-organic load of 491 g from wastewater-effluent irrigation to the study corn field during the 2019 growing season did not produce substantial dissolved organic-contaminant contributions in subsequent rain-induced runoff events. Out of the 140 detected organics in source wastewater-effluent irrigation, only imidacloprid and estrone had concentrations that resulted in observable differences between rain-induced agricultural runoff from the effluent-irrigated and nonirrigated corn fields. Analyses of pharmaceuticals and per-/polyfluoroalkyl substances in at-harvest corn-plant samples detected two prescription antibiotics, norfloxacin and ciprofloxacin, at concentrations of 36 and 70 ng/g, respectively, in effluent-irrigated corn-plant samples; no contaminants were detected in noneffluent irrigated corn-plant samples.

Oklahoma↗

USGS2008

Assessing the extent and diversity of riparian ecosystems in Sonora, Mexico

Conservation of forested riparian ecosystems is of international concern. Relatively little is known of the structure, composition, diversity, and extent of riparian ecosystems in Mexico. We used high- and low-resolution satellite imagery from 2000 to 2006, and ground-based sampling in 2006, to assess the spatial pattern, extent, and woody plant composition of riparian forests across a range of spatial scales for the state of Sonora, Mexico. For all 3rd and higher order streams, river bottomlands with riparian forests occupied a total area of 2,301 km2. Where forested bottomlands remained, on average, 34% of the area had been converted to agriculture while 39% remained forested. We estimated that the total area of riparian forest along the principal streams was 897 km2. Including fencerow trees, the total forested riparian area was 944 km2, or 0.5% of the total land area of Sonora. Ground-based sampling of woody riparian vegetation consisted of 92, 50 m radius circular plots. About 79 woody plant species were noted. The most important tree species, based on cover and frequency, were willow species Salix spp. (primarily S. goodingii and S. bonplandiana), mesquite species Prosopis spp. (primarily P. velutina), and Fremont cottonwood Populus fremontii. Woody riparian taxa at the reach scale showed a trend of increasing diversity from north to south within Sonora. Species richness was greatest in the willow-bald cypress Taxodium distichum var. mexicanum-Mexican cottonwood P. mexicana subsp. dimorphia ecosystem. The non-native tamarisk Tamarix spp. was rare, occurring at just three study reaches. Relatively natural stream flow patterns and fluvial disturbance regimes likely limit its establishment and spread. ?? 2008 Springer Science + Business Media BV.

Biodiversity and Conservation↗

USGS2021

A novel automatic phenology learning (APL) method of training sample selection using multiple datasets for time-series land cover mapping

The long record of Landsat imagery, which is the cornerstone of Earth observation, provides an opportunity to monitor land use and land cover (LULC) change and understand the interactions between the climate and earth system through time. A few change detection algorithms such as Continuous Change Detection and Classification (CCDC) have been developed to utilize all available Landsat images for change detection and characterization at local or global scales. However, the reliable, rapid, and reproducible collection of training samples have become a challenge for time series land cover classification at a large scale. To meet the challenge, we proposed an automatic phenology learning (APL) method with the assumption that the temporal profiles of samples within the same land cover type are the same or similar at a local scale to generate evenly distributed training samples automatically. We designed the method to build land cover patterns for each category based on consensus samples derived from multiple existing scientific datasets including LANDFIRE's (LF) Existing Vegetation Type (EVT), USGS National Land Cover Database (NLCD), National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL), and National Wetlands Inventory (NWI). Then we calculated the Time-Weighted Dynamic Time Warping (twDTW) distance between any undefined samples and land cover patterns in the same geographical region as prior knowledge. Finally, we selected the optimal land cover category for each undefined sample from the land cover products based on the designed criteria iteratively using the twDTW distance as an indicator. The method was applied in the footprint of 10 selected Landsat Analysis Ready Data (ARD) tiles in the eastern and western conterminous United States (CONUS) to produce annual land cover maps from 1985 to 2017. The accuracy assessment and visual comparison revealed that the APL method can generate reliable training samples without any manual interpretation, producing better land cover results especially for the grass/shrub and wetland land cover classes. Applying the APL method, the overall accuracy of the annual land cover maps was improved by 2% over the accuracy of Land Change Monitoring, Assessment, and Projection (LCMAP) Collection 1.0 Science Products in the research regions. Our results also indicate that the APL method provides an approach for best use of different land cover products and meets the requirement of intensive sampling for training data collection.

Remote Sensing of Environment↗

USGS2019

Inorganic nitrogen wet deposition gradients in the Denver-Boulder metropolitan area and Colorado Front Range – Preliminary implications for Rocky Mountain National Park and interpolated deposition maps

For the first time in the 40-year history of the National Atmospheric Deposition Program / National Trends Network (NADP/NTN), a unique urban-to-rural transect of wet deposition monitoring stations were operated as part of the NTN in 2017 to quantify reactive inorganic nitrogen wet deposition for adjacent urban and rural, montane regions. The transect of NADP stations (sites) was used to collect continuous precipitation depth and weekly wet-deposition samples in the Denver – Boulder, Colorado urban corridor. Gradients in reactive inorganic nitrogen (Nr) concentrations and wet deposition were identified along the transect, which included Rocky Mountain National Park. Back trajectory modeling and stable isotopes suggested contribution of agricultural ammonia (NH3) to urban Nr wet deposition in Denver, but apportionment of wet-deposited Nr to agricultural versus urban mobile sources was not possible for this study. The results demonstrate the importance of multiple monitoring sites across an urban area in defining fine-scale geographic patterns in atmospheric deposition and its sources. Data from new sites located within 50 km of the urban area demonstrate that the urban influence doesn't extend as far as the Inverse Distance Weighting would have suggested without such empirical monitoring data. It is important to determine the radius of influence of urban emissions and associated deposition on the interpolated deposition raster, which is constrained by a paucity of monitoring sites east of Denver.

Colorado↗

USGS2011

Overview of the ARkStorm scenario

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

California↗