Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
The Point-Source Load Estimation Tool (PSLoadEsT) provides a user-friendly interface for generating reproducible load calculations for point source dischargers while managing common data challenges including duplicates, incompatible input tables, and incomplete or missing nutrient concentration or effluent flow data. Maintaining a consistent method across an entire study area is important when estimating loads to be used as calibration data for regional water-quality models. PSLoadEsT is written using the open-source programming language R and has an easy-to-use interface written in Visual Basic for Applications® within a Microsoft Access® database file that guides the user through the necessary steps to estimate point source loads. The purpose of this report is to provide a detailed user guide for PSLoadEsT.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191025","collaboration":"National Water Quality Assessment Program","usgsCitation":"Gorman Sanisaca, L.E., Skinner, K.D., and Maupin, M.A., 2019, Annual wastewater nutrient data preparation and load estimation using the Point Source Load Estimation Tool (PSLoadEsT): U.S. Geological Survey Open-File Report 2019-1025, 48 p., https://doi.org/10.3133/ofr20191025.","productDescription":"Report: vi, 48 p.; Additional Report Piece","onlineOnly":"Y","ipdsId":"IP-099356","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":437510,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QWVZ4L","text":"USGS data release","linkHelpText":"Point-Source Load Estimation Tool (PSLoadEsT)"},{"id":362728,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1025/coverthb.jpg"},{"id":362733,"rank":4,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://doi.org/10.5066/P9QWVZ4L","text":"PSLoadEsT Software release","description":"PSLoadEsT Software release"},{"id":362729,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1025/ofr20191025.pdf","text":"Report","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1025"},{"id":362732,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ds1101","text":"Data Series 1101","description":"Data Series 1101","linkHelpText":"Point-Source Nutrient Loads to Streams of the Conterminous United States, 2012"}],"contact":"Director, MD-DE-DC Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Catonsville, MD 21228
Total nitrogen and phosphorous loads were estimated for 5,430 major point-source facilities (all types) and 11,537 minor wastewater treatment facilities discharging to streams in the conterminous United States during 2012. Facilities classified as a major discharger are typically a facility that discharges greater than one million gallons of water per day however some industrial facilities are classified as a major based on specific criteria developed by the U.S. Environmental Protection Agency (EPA) and the National Pollutant Discharge Elimination System state program. Data documenting discharge information from point sources were obtained from the EPA’s Integrated Compliance Information System (ICIS) and Permit Compliance System (PCS). When available, actual nutrient concentration measurements were used to calculate point-source loads. In the many cases in which concentration data were not available in either the ICIS or PCS databases, typical pollutant concentrations (TPCs) were developed using data from similar facilities. A new method for calculating TPCs was implemented that allows varying amounts of nutrient concentration data and (or) varying numbers of facilities to determine TPCs. This new method minimized the effect that any single facility discharging extremely large nutrient concentrations had on resultant TPC values. Because of the smaller TPC values from this new TPC method, the total nutrient load for many states was reduced compared to previous TPC methods.
Major wastewater treatment facilities are the largest contributor of nutrient loads to streams even though there are almost three times as many minor wastewater treatment facilities. Specifically, 4,218 major wastewater treatment facilities account for 94 percent of the total nitrogen load for the conterminous United States, whereas 11,397 minor wastewater treatment facilities contribute 6 percent of the total nitrogen load. Total phosphorous loads are similarly divided among major (93 percent) and minor (7 percent) wastewater treatment facilities. Total nitrogen loads, including all facility types, primarily are from wastewater treatment facilities and some petroleum refining facilities. Total phosphorous loads also are primarily from wastewater treatment facilities, but several manufacturing facilities such as corn milling, pulp and paper mills, and industrial chemical facilities also contribute to total phosphorous loads.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1101","usgsCitation":"Skinner, K.D., and Maupin, M.A., 2019, Point-source nutrient loads to streams of the conterminous United States, 2012: U.S. Geological Survey Data Series 1101, 13 p., https://doi.org/10.3133/ds1101.","productDescription":"Report: vi, 13 p.; Data Release","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-080332","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":362734,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20191025","text":"OFR 2019-1025","description":"OFR 2019-1025","linkHelpText":"Annual Wastewater Nutrient Data Preparation and Load Estimation Using the Point-Source Load Estimation Tool 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U.S. Geological Survey
230 Collins Rd
Boise, Idaho 83702-4520
Salmon populations spawning in the Lake Ozette watershed of northwestern Washington were once sufficiently abundant to support traditional Tribal fisheries, and were later harvested by settlers. However, in 1974 and 1975, the sockeye salmon (Oncorhynchus nerka) harvest decreased to 0 from a high of more than 17,500 in 1949, thus stimulating research into the causes of decrease, which resulted in eventual listing of the population as threatened under the Endangered Species Act in 1999. The listing status was upheld in 2005 and 2014 following 5-year reviews. Meanwhile, research results were compiled in a limiting factors analysis (LFA) and a recovery plan was developed. Although there has been some improvement in sockeye abundance since listing, the numbers remain too low to allow harvest and it is not yet clear which of the many potential limiting factors are most consequential.
As part of the LFA process, a population model was developed to determine values of life-history parameters that would enable the population to survive for 100 years. The model was based on the best available data, but data are limited for the Lake Ozette system. Results informed the qualitative assessment of the importance of limiting factors used to develop the recovery plan for Lake Ozette sockeye. The model was built in Microsoft Excel® and is difficult to use. The purpose of the model described herein is to synthesize the results of the LFA in a form that can be manipulated by resource managers and the public to create scenarios, test hypotheses, and observe sensitivities of results to changes in parameters. The goal is to provide a tool that enables research, monitoring and management to be focused on the most impactful elements and processes, including identifying the information gaps that are most critical to fill.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191031","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Woodward, A., Haggerty, M., and Crain, P., 2019, Life-history model for sockeye salmon (Oncorhynchus nerka) at Lake Ozette, northwestern Washington—Users' guide: U.S. Geological Survey Open-File Report 2019-1031, 79 p., https://doi.org/10.3133/ofr20191031.","productDescription":"viii, 79 p.","numberOfPages":"92","onlineOnly":"Y","ipdsId":"IP-101934","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":362633,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1031/coverthb.jpg"},{"id":362634,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1031/ofr20191031.pdf","text":"Report","size":"4.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1031"}],"country":"United States","state":"Washington","otherGeospatial":"Lake Ozette","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.68074798583986,\n 48.033560004128255\n ],\n [\n -124.59320068359374,\n 48.033560004128255\n ],\n [\n -124.59320068359374,\n 48.15509285476017\n ],\n [\n -124.68074798583986,\n 48.15509285476017\n ],\n [\n -124.68074798583986,\n 48.033560004128255\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
Much of the current understanding of pharmaceutical pollution in the aquatic environment is based on research conducted in Europe, North America and other select high-income nations. One reason for this geographic disparity of data globally is the high cost and analytical intensity of the research, limiting accessibility to necessary equipment. To reduce the impact of such disparities, we present a novel method to support large-scale monitoring campaigns of pharmaceuticals at different geographical scales. The approach employs the use of a miniaturised sampling and shipping approach with a high throughput and fully validated direct-injection High-Performance Liquid Chromatography-Tandem Mass Spectrometry method for the quantification of 61 active pharmaceutical ingredients (APIs) and their metabolites in tap, surface, wastewater treatment plant (WWTP) influent and WWTP effluent water collected globally. A 7-day simulated shipping and sample stability assessment was undertaken demonstrating no significant degradation over the 1–3 days which is typical for global express shipping. Linearity (r2) was consistently ≥0.93 (median = 0.99 ± 0.02), relative standard deviation of intra- and inter-day repeatability and precision was <20% for 75% and 68% of the determinations made at three concentrations, respectively, and recovery from Liquid Chromatography Mass Spectrometry grade water, tap water, surface water and WWTP effluent were within an acceptable range of 60–130% for 87%, 76%, 77% and 63% of determination made at three concentrations respectively. Limits of detection and quantification were determined in all validated matrices and were consistently in the ng/L level needed for environmentally relevant API research. Independent validation of method results was obtained via an interlaboratory comparison of three surface-water samples and one WWTP effluent sample collected in North Liberty, Iowa (USA). Samples used for the interlaboratory validation were analysed at the University of York Centre of Excellence in Mass Spectrometry (York, UK) and the U.S. Geological Survey National Water Quality Laboratory in Denver (Colorado, USA). These results document the robustness of using this method on a global scale. Such application of this method would essentially eliminate the interlaboratory analytical variability typical of such large-scale datasets where multiple methods were used.
","language":"English","publisher":"MDPI","doi":"10.3390/app9071368","usgsCitation":"Wilkinson, J.W., Boxall, A., and Kolpin, D., 2019, A novel method to characterise levels of pharmaceutical pollution in large scale aquatic monitoring campaigns: Applied Sciences, v. 9, no. 7, 1368, 14 p., https://doi.org/10.3390/app9071368.","productDescription":"1368, 14 p.","ipdsId":"IP-106171","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":467751,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/app9071368","text":"Publisher Index Page"},{"id":369080,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilkinson, John W.","contributorId":147014,"corporation":false,"usgs":false,"family":"Wilkinson","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":774939,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boxall, Alistair","contributorId":152697,"corporation":false,"usgs":false,"family":"Boxall","given":"Alistair","affiliations":[],"preferred":false,"id":774940,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kolpin, Dana 0000-0002-3529-6506","orcid":"https://orcid.org/0000-0002-3529-6506","contributorId":220448,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":774938,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204653,"text":"70204653 - 2019 - Assessing seasonal changes in microgravity at Yellowstone caldera","interactions":[],"lastModifiedDate":"2019-08-09T10:45:59","indexId":"70204653","displayToPublicDate":"2019-04-01T07:51:55","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Assessing seasonal changes in microgravity at Yellowstone caldera","docAbstract":"Microgravity time series at active volcanoes can provide an indication of mass change related to subsurface magmatic processes, but uncertainty is often introduced by hydrologic variations and other noise sources that cannot easily be isolated. We empirically assessed seasonality and noise by conducting four surveys over the course of May-October 2017 at Yellowstone caldera, Wyoming. Yellowstone experiences frequent changes in the rates and styles of seismicity and surface deformation, but the mechanisms of these changes are poorly understood because the characteristics of the driving fluids are not clear. Past gravity data from the caldera have yielded ambiguous results, possibly due to hydrologic noise. Given the strong visually observable changes in surface water and snow conditions over the course of our surveys, we expected to see significant variations in gravity. The net change in gravity, however, was less than 20 µGal at most sites, and there was no strong correlation with river and lake levels or snow conditions. Seasonal changes in gravity are therefore small compared to those that would be expected from magmatic activity, although they may be on the same order as those associated with Yellowstone’s hydrothermal system. We did find that noise levels in gravity data were highly dependent on site characteristics, with bedrock sites away from trees yielding the lowest levels of noise, and thin concrete pads in forested areas the highest. These results can be used to plan future surveys at Yellowstone and to reinterpret past data, and they provide guidance in terms of best practices for repeat gravity work on volcanoes worldwide.","language":"English","publisher":"Wiley","doi":"10.1029/2018JB017061","usgsCitation":"Poland, M.P., and de Zeeuw-van Dalfsen, E., 2019, Assessing seasonal changes in microgravity at Yellowstone caldera: Journal of Geophysical Research, v. 124, no. 4, p. 4174-4188, https://doi.org/10.1029/2018JB017061.","productDescription":"15 p.","startPage":"4174","endPage":"4188","ipdsId":"IP-103468","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467754,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jb017061","text":"Publisher Index Page"},{"id":366351,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.28051757812499,\n 43.79488907226601\n ],\n [\n -109.3304443359375,\n 43.79488907226601\n ],\n [\n -109.3304443359375,\n 45.14717913418674\n ],\n [\n -111.28051757812499,\n 45.14717913418674\n ],\n [\n -111.28051757812499,\n 43.79488907226601\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"124","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":767930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Zeeuw-van Dalfsen, Elske 0000-0003-2527-4932","orcid":"https://orcid.org/0000-0003-2527-4932","contributorId":217967,"corporation":false,"usgs":false,"family":"de Zeeuw-van Dalfsen","given":"Elske","email":"","affiliations":[{"id":39727,"text":"KNMI","active":true,"usgs":false}],"preferred":false,"id":767931,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70203230,"text":"70203230 - 2019 - Simulating the effects of climate variability on waterbodies and wetland-dependent birds in the Prairie Pothole Region","interactions":[],"lastModifiedDate":"2019-05-02T08:07:59","indexId":"70203230","displayToPublicDate":"2019-04-01T07:46:05","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Simulating the effects of climate variability on waterbodies and wetland-dependent birds in the Prairie Pothole Region","docAbstract":"Understanding how bird populations respond to changes in waterbody availability in the climatically variable Prairie Pothole Region (PPR) of North America hinges on being able to couple hydrological and climate modeling to represent potential future landscapes. Model experiments run with the Pothole Complex Hydrologic Model using downscaled climate data (variables relating to precipitation, temperature, and potential evapotranspiration at 1/8° spatial resolution under four general circulation climate models and two gas emissions scenarios) were used to forecast the abundances of six focal wetland‐dependent bird species in the Missouri Coteau portion of the PPR, providing ensemble scenarios at a spatial scale relevant to resource management. Although the projected number of May ponds (waterbodies present during bird breeding season) fluctuated through time with some decadal periodicity (and with the number present in a given year reflecting abundance over the previous three years), the ensemble model average indicated an increase in the average number of waterbodies present by the turn of the next century. Overall, the model experiments conservatively projected an 11.75% increase in the number of waterbodies present by 2090–2099 compared to a baseline period from 1967 to 2005 in the PPR. Wetland‐dependent bird occurrence and abundance were significantly associated with temporal patterns and decadal periodicity in waterbody dynamics. Because of the strong associations between wetland‐dependent bird occurrence and abundance and the number of prairie potholes, projected waterbody increases are forecasted to result in an 11.97% overall increase in occurrence and 8.63% increase in abundance of the six focal species by the end of the 21st century; these results contrast with forecasted drought‐associated declines in waterbodies and birds in the PPR. This integrated hydrological–climatological approach offers a means of assessing how wetland‐dependent bird populations may respond to changes in wetland habitat availability due to a changing climate. Our results provide information that can help managers decide how to mitigate the effects of climate shifts on the distribution of wetland habitat and biota.
Beginning in the late 1970s, 10- to 15-year cyclical oscillations in salinity were observed at lower Colorado River monitoring sites, moving upstream from the international border with Mexico, above Imperial Dam, below Hoover Dam, and at Lees Ferry. The cause of these cyclical trends in salinity was unknown. These salinity cycles complicate the U.S. Bureau of Reclamation's (Reclamation) responsibility for managing salinity in the river for delivery of water to Mexico to meet treaty obligations. This study develops a conceptual model of the salinity cycles from time-series water quality, streamflow, and precipitation data in both the lower and upper Colorado River Basins in order to provide Reclamation the ability to understand, anticipate, and manage future salinity cycles in the lower river. Compared with the Lees Ferry record, both maximum and minimum salinity levels increase downstream by about 25% at Hoover Dam, by about 49% at Imperial Dam, and by about 69% at the northern international boundary with Mexico. In the upper basin, cyclical salinity trends are evident at the outflow of three major tributaries, where salinity is also noted to be inversely related to streamflow. Time series trends in precipitation within the catchments of the three upper basin tributaries indicate cyclical periods with above normal precipitation and periods with below normal precipitation. Periods of greater than normal precipitation in the contributing areas correspond with declines in salinity at the catchment monitoring sites and periods of less than normal precipitation correspond with rising salinity at the sites. Based on the conceptual model developed in this investigation, a multiple linear regression model was developed using a stepwise variable selection procedure to simulate salinity in Lake Powell inflow. Important variables in the explanation of salinity entering Lake Powell include flow from the three upper basin tributaries, seasonality, and mean precipitation in the upper basin, among others. The root mean square error of prediction for the MLR model was 31.48 mg/L (5.7%).
This is the fifty-fifth in a series of annual reports that describe groundwater conditions in Utah. Reports in this series, published cooperatively by the U.S. Geological Survey and the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Environmental Quality, Division of Water Quality, provide data to enable interested parties to maintain awareness of changing groundwater conditions.
This report, like the others in the series, contains information on well construction, groundwater withdrawals from wells, water-level changes, precipitation, streamflow, and chemical quality of water. Information on well construction included in this report refers only to new wells constructed for withdrawal of groundwater. Supplementary data are included in reports of this series only for those years or areas that are important to a discussion of changing groundwater conditions and for which applicable data are available.
This report includes individual discussions of selected significant areas of groundwater development in the State for calendar year 2017. Most of the reported data were collected by the U.S. Geological Survey in cooperation with the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Environmental Quality, Division of Water Quality. This report is also available online at https://waterrights.utah.gov/techinfo/wwwpub/GW2018.pdf. Groundwater conditions in Utah for calendar year 2016 are reported in Burden and others (2017) and are available online at https://waterrights.utah.gov/techinfo/wwwpub/GW2017.pdf.
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Land use and land cover change (LULCC) can also be a dominant driver of changes in stream biogeochemistry yet responses are not fully understood and vary across different LULCC scenarios. We measured dissolved and total nitrogen (N) and phosphorus (P) concentrations in four tributary streams of the Temash River watershed in southern Belize, Central America. The dominant land use practice in each of the four study catchments was swidden agriculture. We documented a strong seasonal control on the export of nutrients from these study systems with daily N fluxes increasing approximately 10-fold during the onset of the rainy season. P fluxes increased almost 4-fold during the same time period. Comparisons with nutrient export coefficients from other tropical streams suggest that nutrient export in streams of the Temash River watershed is similar or slightly lower. Establishing improved understanding of the terrestrial and hydrologic controls of N and P transport across the terrestrial-aquatic boundary and developing a comprehensive nutrient budget that includes inputs and outputs associated with crop production is warranted in future work.
","language":"English","publisher":"MDPI","doi":"10.3390/w11040664","usgsCitation":"Buck, D.G., Esselman, P., Jiang, S., Wainwright, J.D., Brenner, M., and Cohen, M.J., 2019, Seasonal fluxes of dissolved nutrients in streams of catchments dominated by swidden agriculture in the Maya Forest of Belize, Central America: Water, v. 11, no. 4, 664, 24 p., https://doi.org/10.3390/w11040664.","productDescription":"664, 24 p.","ipdsId":"IP-106287","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":467757,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w11040664","text":"Publisher Index Page"},{"id":381004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Belize","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.21722412109374,\n 15.890017659698243\n ],\n [\n -88.90411376953125,\n 15.890017659698243\n ],\n [\n -88.90411376953125,\n 16.151368535968885\n ],\n [\n -89.21722412109374,\n 16.151368535968885\n ],\n [\n -89.21722412109374,\n 15.890017659698243\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-03-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Buck, David G.","contributorId":245403,"corporation":false,"usgs":false,"family":"Buck","given":"David","email":"","middleInitial":"G.","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":806134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esselman, Peter C. 0000-0002-0085-903X","orcid":"https://orcid.org/0000-0002-0085-903X","contributorId":204291,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":806135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jiang, Shiguo 0000-0001-9088-883X","orcid":"https://orcid.org/0000-0001-9088-883X","contributorId":244799,"corporation":false,"usgs":false,"family":"Jiang","given":"Shiguo","email":"","affiliations":[{"id":48981,"text":"State University of New York","active":true,"usgs":false}],"preferred":false,"id":806136,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wainwright, Joel D.","contributorId":245404,"corporation":false,"usgs":false,"family":"Wainwright","given":"Joel","email":"","middleInitial":"D.","affiliations":[{"id":49186,"text":"University of Ohio","active":true,"usgs":false}],"preferred":false,"id":806137,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brenner, Mark","contributorId":245405,"corporation":false,"usgs":false,"family":"Brenner","given":"Mark","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":806138,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cohen, Matthew J.","contributorId":138990,"corporation":false,"usgs":false,"family":"Cohen","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":806139,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70204415,"text":"70204415 - 2019 - A revised continuous surface elevation model for modeling","interactions":[],"lastModifiedDate":"2019-09-20T12:48:37","indexId":"70204415","displayToPublicDate":"2019-03-31T12:48:27","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"title":"A revised continuous surface elevation model for modeling","docAbstract":"A digital elevation model (DEM) is an essential component of any hydrodynamic model. The Delta Modeling Section (Section) has maintained a database of bathymetry soundings and levee surveys for decades and published a 10-meter (10m) DEM for the San Francisco Bay and Sacramento-San Joaquin Delta (Delta) (California Department of Water Resources 2012). In collaboration with the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center, the California Department of Water Resources (DWR) has continued to upgrade these DEMs based on newer survey data and improved interpolation methodologies. An updated San Francisco Bay-Delta bathymetric/topographic digital elevation model was published by the USGS (Fregoso, Wang, Ateljevich, and Jaffe 2017). \n\nBoth DWR and USGS continue to work on the elevation models for several reasons. First, high-resolution multibeam bathymetry data continues to become available. A good portion of the newer collections are performed at locations where bathymetry data is lacking, or of poor quality, or where model sensitivity to bathymetry is known to be high, so the effort has a high return on investment. Recent high-resolution multibeam datasets easily support the development of accurate 2-meter (2m) DEMs, although shallow water, turbidity, vegetation, and the gap between the multibeam data and terrestrial data from light detection and ranging (LiDAR) remain vexing issues that fuel development of enhanced techniques. \n\nIn some locations, migration toward 2m resolution models is motivated by geographical structure even where there has been little improvement in the underlying data. DEMs at 10m resolution are insufficient to adequately describe small-scale terrain features, such as levee crests or the main conveyance channel through a narrow reach, such as Middle River. As a result, elevation modelers have traditionally needed to perform feature enforcement for 10m DEMs, but not for the Section’s 2m DEMs which do resolve these features (California Department of Resources 2012). There are several other problems associated with a coarse target resolution, including reduced conveyance and rough contours where channels run oblique to the elevation model. In places where the topography demands a finer elevation model, the Section and others have adopted improved interpolation techniques for single-beam data to produce reasonable 2m DEMs that preserve features on appropriate scales.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Methodology for flow and salinity estimates in the Sacramento-San Joaquin Delta and Suisun Marsh, 39th Annual Progress Report to the State Water Resources Control Board","largerWorkSubtype":{"id":2,"text":"State or Local Government Series"},"language":"English","publisher":"California Department of Water Resources, Bay-Delta Office","usgsCitation":"Wang, R., Ateljevich, E., Fregoso, T.A., and Jaffe, B.E., 2019, A revised continuous surface elevation model for modeling, chap. of Methodology for flow and salinity estimates in the Sacramento-San Joaquin Delta and Suisun Marsh, 39th Annual Progress Report to the State Water Resources Control Board, v. 39, p. 5-1-5-40.","productDescription":"40 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range","interactions":[],"lastModifiedDate":"2019-09-25T09:44:38","indexId":"70204441","displayToPublicDate":"2019-03-31T12:18:33","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":718,"text":"American Fisheries Society Symposium","active":true,"publicationSubtype":{"id":10}},"title":"Changes in body condition and diet of lotic Smallmouth Bass across two flow regimes during summer months at the southern extent of their native range","docAbstract":"The Ozark Plateau is located at the southern extent of native Smallmouth Bass Micropterus dolomieu range and water temperature and drought conditions during summer months may potentially affect growth of Smallmouth Bass in this region. Groundwater streams in the region do not warm to the same extent as runoff streams during summer months and could provide a thermal refuge habitat for Smallmouth Bass from high summer temperatures and drought conditions. Our study objective was to examine differences in body condition and diet of Small-mouth Bass through summer months between groundwater and runoff streams. We sampled Smallmouth Bass from eight streams across two the flow regimes monthly from June-September from 2014 to 2016 in the Ozark Plateau of Arkansas and Missouri. Relative weights were calculated and diet contents were examined for each fish. Linear mixed model analyses indicated that relative weights declined in both stream types in 2014 and 2015, but not in 2016. Surprisingly, there was no significant difference in change in relative weights between runoff and groundwater streams in any year. No diet shifts over the course of the summer were noted in any year, and no differences were seen between stream types. Our results suggest that further work should investigate the refuge qualities of groundwater streams for Smallmouth Bass in this region as Smallmouth Bass from both stream types may currently respond similarly to summer conditions.. Middaugh, Chris & Magoulick, Daniel. (2019). Changes in Body Condition and Diet of Lotic Smallmouth Bass across Two Flow Regimes during Summer Months at the Southern Extent of Their Native Range. The Ozark Plateau is located at the southern extent of native Smallmouth Bass Micropterus dolomieu range and water temperature and drought conditions during summer months may potentially affect growth of Smallmouth Bass in this region. Groundwater streams in the region do not warm to the same extent as runoff streams during summer months and could provide a thermal refuge habitat for Smallmouth Bass from high summer temperatures and drought conditions. Our study objective was to examine differences in body condition and diet of Small-mouth Bass through summer months between groundwater and runoff streams. We sampled Smallmouth Bass from eight streams across two the flow regimes monthly from June-September from 2014 to 2016 in the Ozark Plateau of Arkansas and Missouri. Relative weights were calculated and diet contents were examined for each fish. Linear mixed model analyses indicated that relative weights declined in both stream types in 2014 and 2015, but not in 2016. Surprisingly, there was no significant difference in change in relative weights between runoff and groundwater streams in any year. No diet shifts over the course of the summer were noted in any year, and no differences were seen between stream types. Our results suggest that further work should investigate the refuge qualities of groundwater streams for Smallmouth Bass in this region as Smallmouth Bass from both stream types may currently respond similarly to summer conditions.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Managing Centrarchid Fisheries in Rivers and Streams","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","isbn":"9781934874523","usgsCitation":"Middaugh, C.R., and Magoulick, D.D., 2019, Changes in body condition and diet of lotic Smallmouth Bass across two flow regimes during summer months at the southern extent of their native range: American Fisheries Society Symposium, v. 87, p. 93-110.","productDescription":"18 p.","startPage":"93","endPage":"110","ipdsId":"IP-083988","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":367606,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":367605,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://fisheries.org/bookstore/all-titles/afs-symposia/54087p/"}],"country":"United States","state":"Arkansas, Missouri","otherGeospatial":"Ozark Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.6142578125,\n 34.84085858477277\n ],\n [\n -91.669921875,\n 34.84085858477277\n ],\n [\n -91.669921875,\n 37.21283151445594\n ],\n [\n -94.6142578125,\n 37.21283151445594\n ],\n [\n -94.6142578125,\n 34.84085858477277\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"87","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Middaugh, Christopher R.","contributorId":177019,"corporation":false,"usgs":false,"family":"Middaugh","given":"Christopher","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":771488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":766920,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70202305,"text":"70202305 - 2019 - Estimating indirect impacts of wind-energy development for breeding grassland birds and waterfowl in the northern Great Plains","interactions":[],"lastModifiedDate":"2020-10-29T16:27:55.858367","indexId":"70202305","displayToPublicDate":"2019-03-31T11:19:14","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Estimating indirect impacts of wind-energy development for breeding grassland birds and waterfowl in the northern Great Plains","docAbstract":"No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the Wind Wildlife Research Meeting XII","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Wind Wildlife Research Meeting XII","conferenceDate":"Nov 27-30, 2018","conferenceLocation":"St.Paul, MN","language":"English","publisher":"National Wind Coordinating Collaborative","usgsCitation":"Shaffer, J.A., Loesch, C.R., and Buhl, D.A., 2019, Estimating indirect impacts of wind-energy development for breeding grassland birds and waterfowl in the northern Great Plains, in Proceedings of the Wind Wildlife Research Meeting XII, St.Paul, MN, Nov 27-30, 2018, p. 13-18.","productDescription":"6 p.","startPage":"13","endPage":"18","ipdsId":"IP-104914","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":379918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":361406,"type":{"id":15,"text":"Index Page"},"url":"https://www.nationalwind.org/meetings/wind-wildlife-research-meeting-xii/"}],"country":"United States","state":"North Dakota, South Dakota","county":"Dickey County, Hyde County, Oliver County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.1680908203125,\n 45.93969078234\n ],\n [\n -97.97607421875,\n 45.93969078234\n ],\n [\n -97.97607421875,\n 46.3886223381617\n ],\n [\n -99.1680908203125,\n 46.3886223381617\n ],\n [\n -99.1680908203125,\n 45.93969078234\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.7119140625,\n 44.213709909702054\n ],\n [\n -99.2449951171875,\n 44.213709909702054\n ],\n [\n -99.2449951171875,\n 44.85197466334984\n ],\n [\n -99.7119140625,\n 44.85197466334984\n ],\n [\n -99.7119140625,\n 44.213709909702054\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.744384765625,\n 46.96900803311957\n ],\n [\n -100.9808349609375,\n 46.96900803311957\n ],\n [\n -100.9808349609375,\n 47.26059219342468\n ],\n [\n -101.744384765625,\n 47.26059219342468\n ],\n [\n -101.744384765625,\n 46.96900803311957\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shaffer, Jill A. 0000-0003-3172-0708 jshaffer@usgs.gov","orcid":"https://orcid.org/0000-0003-3172-0708","contributorId":3184,"corporation":false,"usgs":true,"family":"Shaffer","given":"Jill","email":"jshaffer@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":757719,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loesch, Charles R. 0000-0003-3090-1566","orcid":"https://orcid.org/0000-0003-3090-1566","contributorId":213437,"corporation":false,"usgs":false,"family":"Loesch","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":757720,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buhl, Deborah A. 0000-0002-8563-5990 dbuhl@usgs.gov","orcid":"https://orcid.org/0000-0002-8563-5990","contributorId":146226,"corporation":false,"usgs":true,"family":"Buhl","given":"Deborah","email":"dbuhl@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":757721,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70203746,"text":"70203746 - 2019 - Effects of high flow experiments on warm-water native and nonnative fishes","interactions":[],"lastModifiedDate":"2020-05-28T18:25:36.820679","indexId":"70203746","displayToPublicDate":"2019-03-31T10:44:53","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Effects of high flow experiments on warm-water native and nonnative fishes","docAbstract":"The harsh environmental conditions and extreme flooding that created Grand Canyon also shaped the unique native fish that evolved in the Colorado River. Native fish have evolved their physiology, morphology and behavior to withstand high flood events. Flooding has been shown to benefit spawning, survival and recruitment of juvenile native fishes in many southwestern rivers. Annual pre-dam flooding on the Colorado River was sometimes more than double the flows released during a typical High-Flow Experiment (HFE). It is therefore unlikely that the 3-4 days of high flow created by HFEs will have negative impacts on native fish directly. However, HFEs can cause dispersal of flood adapted non-native species like green sunfish that utilize floods to invade and colonize new environments. Continued efforts to reduce known populations of green sunfish that inhabit backwater ponds before conducting HFEs may be necessary to reduce risks of spreading invasive green sunfish downstream.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"High-Flow Experiments Assessment Extended Abstracts","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Adaptive Management Work Group Meeting","conferenceDate":"March 6-7, 2019","conferenceLocation":"Tempe, AZ","language":"English","publisher":"US Bureau of Reclamation Glen Canyon Dam Adaptive Management Program","usgsCitation":"Ward, D., 2019, Effects of high flow experiments on warm-water native and nonnative fishes, in High-Flow Experiments Assessment Extended Abstracts, Tempe, AZ, March 6-7, 2019, p. 38-41.","productDescription":"4 p.","startPage":"38","endPage":"41","ipdsId":"IP-107993","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":375131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":364509,"type":{"id":15,"text":"Index Page"},"url":"https://www.usbr.gov/uc/progact/amp/amwg/2019-03-06-amwg-meeting/20190301-HFE_Extended_Abstracts-Combined_FINAL.pdf"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.58538818359374,\n 36.84006462037767\n ],\n [\n -111.6650390625,\n 36.848856608486905\n ],\n [\n -111.77215576171874,\n 36.72567681977065\n ],\n [\n -111.92047119140624,\n 36.51405119943165\n ],\n [\n -111.9451904296875,\n 36.35495110643483\n ],\n [\n -111.98089599609375,\n 36.250918288153876\n ],\n [\n -111.9287109375,\n 36.140092827322654\n ],\n [\n -112.0550537109375,\n 36.19774164407363\n ],\n [\n -112.20062255859374,\n 36.24427318493909\n ],\n [\n -112.26654052734375,\n 36.34389038251925\n ],\n [\n -112.50274658203125,\n 36.48093224547937\n ],\n [\n -113.21685791015625,\n 36.19109202182454\n ],\n [\n -113.345947265625,\n 36.12900165569652\n ],\n [\n -113.40087890624999,\n 36.053540128339755\n ],\n [\n -113.367919921875,\n 35.891275201659134\n ],\n [\n -113.411865234375,\n 35.84453450421662\n ],\n [\n -113.54095458984375,\n 35.88014896488361\n ],\n [\n -113.78265380859374,\n 36.09127994838079\n ],\n [\n -113.93096923828124,\n 36.140092827322654\n ],\n [\n -113.98040771484375,\n 36.089060460282006\n ],\n [\n -113.83209228515625,\n 35.94465937365276\n ],\n [\n -113.5986328125,\n 35.75097043944926\n ],\n [\n -113.35968017578125,\n 35.72421761691415\n ],\n [\n -113.27728271484374,\n 35.860117799832544\n ],\n [\n -113.27728271484374,\n 36.053540128339755\n ],\n [\n -113.21136474609375,\n 36.053540128339755\n ],\n [\n -112.94769287109375,\n 36.20217441183449\n ],\n [\n -112.60711669921875,\n 36.34610265300638\n ],\n [\n -112.56591796875,\n 36.33504067209607\n ],\n [\n -112.52471923828125,\n 36.21547120903648\n ],\n [\n -112.3736572265625,\n 36.13343831245866\n ],\n [\n -112.11547851562499,\n 35.980228800645676\n ],\n [\n -111.78039550781249,\n 36.02022525154813\n ],\n [\n -111.76391601562499,\n 36.25313319699069\n ],\n [\n -111.79412841796875,\n 36.47209813242351\n ],\n [\n -111.58538818359374,\n 36.84006462037767\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ward, David 0000-0002-3355-0673 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-3355-0673","contributorId":216124,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":763937,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70216659,"text":"70216659 - 2019 - Fire, forests and city water supply","interactions":[],"lastModifiedDate":"2020-11-27T16:38:23.593275","indexId":"70216659","displayToPublicDate":"2019-03-31T10:38:05","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3666,"text":"Unasylva","printIssn":"0041-6436","active":true,"publicationSubtype":{"id":10}},"title":"Fire, forests and city water supply","docAbstract":"Forest landscapes generate 57 percent of runoff worldwide and supply water to more than 4 billion people (Millennium Ecosystem Assessment, 2005). As the world population continues to increase, there is a strong need to understand how forest processes link together in a cascade to provide people with water services like hydropower, aquaculture, drinking water and flood protection (Carvalho-Santos, Honrado and Hein, 2014).\n\nWildfire is a major disturbance affecting forested watersheds and the water they provide (Box 1) (Paton et al., 2015). Several regions have experienced shifts in wildfires from natural ignition sources (primarily lightning) to ignitions dominated by human activities, especially in areas where populations are increasing (Moritz et al., 2014; Balch et al., 2017). Occasional wildfire is essential for the health and functioning of fire-adapted ecosystems through its effects on nutrient cycling, plant diversity and succession, and pest regulation (Pausas and Keeley, 2019). It also reduces the risk of subsequent wildfires until a forest has accumulated sufficient fuels and conditions are conducive for another fire.\n\nExtreme and hazardous wildfires, on the other hand, can cause erosion, gullying, soil loss and flooding – and, in severe cases, even debris flows and flash floods – by removing the protective functions of forests on hillsides (Ebel and Moody, 2017). Extreme wildfires have become more common after decades of fire suppression, allowing forests to become much denser with vegetation and causing more fuels to build up over time. Combined with increasing summer drought, this can have impacts on water yield and the ability of upstream forests to deliver high-quality water because forest vegetation uses less water immediately after fire and, in environments influenced by snow, more snow can accumulate in forest clearings (Kinoshita and Hogue, 2015; Hallema et al., 2019). Therefore, accounting for wildfire impacts on forests in water planning has become a priority for the nexus of fire, water and society or, in other words, the connection between fire risk and water security (Figure 1) (Martin, 2016). In this article, we discuss managed forest landscapes as nature-based solutions for water and explore how fire affects the provision of water-related services.","language":"English","publisher":"Food and Agriculture Organization of the United Nations","usgsCitation":"Hallema, D.W., Kinoshita, A.M., Martin, D.A., Robinne, F., Galleguillos, M., McNulty, S., Sun, G., Singh, K.K., Mordecai, R.S., and Moore, P.F., 2019, Fire, forests and city water supply: Unasylva, v. 70, no. 1, p. 58-66.","productDescription":"9 p.","startPage":"58","endPage":"66","ipdsId":"IP-110047","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":380838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":380826,"type":{"id":15,"text":"Index Page"},"url":"https://www.fao.org/documents/card/en/c/ca6842en/"}],"volume":"70","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hallema, Dennis W.","contributorId":245286,"corporation":false,"usgs":false,"family":"Hallema","given":"Dennis","email":"","middleInitial":"W.","affiliations":[{"id":49132,"text":"U.S. Department of Agriculture Forest Service Southern Research Station, North Carolina","active":true,"usgs":false}],"preferred":false,"id":805769,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kinoshita, Alicia M.","contributorId":245287,"corporation":false,"usgs":false,"family":"Kinoshita","given":"Alicia","email":"","middleInitial":"M.","affiliations":[{"id":49134,"text":"San Diego State University, California","active":true,"usgs":false}],"preferred":false,"id":805770,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Deborah A. 0000-0001-8237-0838 damartin@usgs.gov","orcid":"https://orcid.org/0000-0001-8237-0838","contributorId":168662,"corporation":false,"usgs":true,"family":"Martin","given":"Deborah","email":"damartin@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":805771,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robinne, Francois-Nicholas","contributorId":245288,"corporation":false,"usgs":false,"family":"Robinne","given":"Francois-Nicholas","email":"","affiliations":[{"id":12799,"text":"University of Alberta, Edmonton, Alberta, Canada","active":true,"usgs":false}],"preferred":false,"id":805772,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Galleguillos, Mauricio","contributorId":245289,"corporation":false,"usgs":false,"family":"Galleguillos","given":"Mauricio","email":"","affiliations":[{"id":49135,"text":"Universidad de Chile, Santiago, Chile","active":true,"usgs":false}],"preferred":false,"id":805773,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McNulty, Steven G.","contributorId":222251,"corporation":false,"usgs":false,"family":"McNulty","given":"Steven G.","affiliations":[{"id":39173,"text":"USDA Forest Service, Eastern Forest Environmental Threat Assessment Center, Raleigh, NC, USA","active":true,"usgs":false}],"preferred":false,"id":805774,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sun, Ge","contributorId":145893,"corporation":false,"usgs":false,"family":"Sun","given":"Ge","email":"","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":805775,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Singh, Kunwar K.","contributorId":245290,"corporation":false,"usgs":false,"family":"Singh","given":"Kunwar","email":"","middleInitial":"K.","affiliations":[{"id":49136,"text":"North Carolina State University, North Carolina","active":true,"usgs":false}],"preferred":false,"id":805776,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mordecai, Rua S.","contributorId":245291,"corporation":false,"usgs":false,"family":"Mordecai","given":"Rua","email":"","middleInitial":"S.","affiliations":[{"id":49137,"text":"U.S. Fish and Wildlife Service, North Carolina","active":true,"usgs":false}],"preferred":false,"id":805777,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Moore, Peter F.","contributorId":245292,"corporation":false,"usgs":false,"family":"Moore","given":"Peter","email":"","middleInitial":"F.","affiliations":[{"id":49138,"text":"Food and Agriculture Organization (FAO), Italy","active":true,"usgs":false}],"preferred":false,"id":805778,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ]}