Subsurface storage of sulfate salts allows closed-basin wetlands in the semiarid Prairie Pothole Region (PPR) of North America to maintain moderate surface water salinity (total dissolved solids [TDS] from 1 to 10 g L−1), which provides critical habitat for communities of aquatic biota. However, it is unclear how the salinity of wetland ponds will respond to a recent shift in mid-continental climate to wetter conditions. To understand better the mechanisms that control surface-subsurface salinity exchanges during regional dry-wet climate cycles, we made a detailed geoelectrical study of a closed-basin prairie wetland (P1 in the Cottonwood Lake Study Area, North Dakota) that is currently experiencing record wet conditions. We found saline lenses of sulfate-rich porewater (TDS > 10 g L−1) contained in fine-grained wetland sediments 2–4 m beneath the bathymetric low of the wetland and within the currently ponded area along the shoreline of a prior pond stand (c. 1983). During the most recent drought (1988–1993), the wetland switched from a groundwater discharge to recharge function, allowing salts dissolved in surface runoff to move into wetland sediments beneath the bathymetric low of the basin. However, groundwater levels during this time did not decline to the elevation of the saline lenses, suggesting these features formed during more extended paleo-droughts and are stable in the subsurface on at least centennial timescales. We hypothesize a “drought-induced recharge” mechanism that allows wetland ponds to maintain moderate salinity under semiarid climate. Discharge of drought-derived saline groundwater has the potential to increase the salinity of wetland ponds during wet climate.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2017.12.005","usgsCitation":"Levy, Z.F., Rosenberry, D.O., Moucha, R., Mushet, D.M., Goldhaber, M.B., LaBaugh, J.W., Fiorentino, A.J., and Siegel, D.I., 2018, Drought-induced recharge promotes long-term storage of porewater salinity beneath a prairie wetland: Journal of Hydrology, v. 557, p. 391-409, https://doi.org/10.1016/j.jhydrol.2017.12.005.","productDescription":"19 p.","startPage":"391","endPage":"409","ipdsId":"IP-086339","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":469147,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2017.12.005","text":"Publisher Index Page"},{"id":382739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","otherGeospatial":"Cottonwood Lake Study Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.69725036621094,\n 47.848187594394815\n ],\n [\n -100.64849853515625,\n 47.848187594394815\n ],\n [\n -100.64849853515625,\n 47.884348247770006\n ],\n [\n -100.69725036621094,\n 47.884348247770006\n ],\n [\n -100.69725036621094,\n 47.848187594394815\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"557","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Levy, Zeno F","contributorId":248464,"corporation":false,"usgs":false,"family":"Levy","given":"Zeno","email":"","middleInitial":"F","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":809207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":809208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moucha, Robert","contributorId":173102,"corporation":false,"usgs":false,"family":"Moucha","given":"Robert","email":"","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":809209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":809210,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goldhaber, Martin B. 0000-0002-1785-4243 mgold@usgs.gov","orcid":"https://orcid.org/0000-0002-1785-4243","contributorId":1339,"corporation":false,"usgs":true,"family":"Goldhaber","given":"Martin","email":"mgold@usgs.gov","middleInitial":"B.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":809211,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LaBaugh, James W. 0000-0002-4112-2536 jlabaugh@usgs.gov","orcid":"https://orcid.org/0000-0002-4112-2536","contributorId":1311,"corporation":false,"usgs":true,"family":"LaBaugh","given":"James","email":"jlabaugh@usgs.gov","middleInitial":"W.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":809212,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fiorentino, Anthony J","contributorId":248465,"corporation":false,"usgs":false,"family":"Fiorentino","given":"Anthony","email":"","middleInitial":"J","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":809213,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Siegel, Donald I.","contributorId":178130,"corporation":false,"usgs":false,"family":"Siegel","given":"Donald","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":809214,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70216340,"text":"70216340 - 2018 - Characterizing uncertainty in daily streamflow estimates at ungauged locations for the Massachusetts sustainable yield estimator","interactions":[],"lastModifiedDate":"2020-11-13T20:50:23.999745","indexId":"70216340","displayToPublicDate":"2017-11-17T10:40:42","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing uncertainty in daily streamflow estimates at ungauged locations for the Massachusetts sustainable yield estimator","docAbstract":"Hydrologic characterization at ungauged locations is one of the quintessential challenges of hydrology. Beyond simulation of historical streamflows, it is similarly important to characterize the level of uncertainty in hydrologic estimates. In tandem with updates to Massachusetts Sustainable Yield Estimator, this work explores the application of global uncertainty estimates to daily streamflow simulations. Expanding on a method developed for deterministic modeling, this approach produces confidence intervals on daily streamflow developed through nonlinear spatial interpolation of daily streamflow using flow duration curves; the 95% confidence is examined. Archived cross‐validations of daily streamflows from 66 watersheds in and around Massachusetts are used to evaluate an approach to uncertainty characterization. Neighboring sites are treated as ungauged, producing relative errors that can be resampled and applied to target sites. The method, with some modification, is found to provide appropriately narrow confidence intervals that contain 95% of the observed streamflows in cross‐validation. Further characterizing uncertainty, multiday means of daily streamflow are evaluated. Working through cross‐validation in Massachusetts, two‐ to three‐month averages of daily streamflow show the best performance. These two approaches to uncertainty characterization inform how streamflow simulation produced for prediction in ungauged basins can be used for water resources management.
The Everglades Depth Estimation Network (EDEN) provides scientists and resource managers with regional maps of daily water levels and depths in the freshwater part of the Greater Everglades landscape. The EDEN domain includes all or parts of five Water Conservation Areas, Big Cypress National Preserve, Pennsuco Wetlands, and Everglades National Park. Daily water-level maps are interpolated from water-level data at monitoring gages, and depth is estimated by using a digital elevation model of the land surface. Online datasets provide time series of daily water levels at gages and rainfall and evapotranspiration data (https://sofia.usgs.gov/eden/). These datasets are used by scientists and resource managers to guide large-scale field operations, describe hydrologic changes, and support biological and ecological assessments that measure ecosystem response to the implementation of the Comprehensive Everglades Restoration Plan. EDEN water-level data have been used in a variety of biological and ecological studies including (1) the health of American alligators as a function of water depth, (2) the variability of post-fire landscape dynamics in relation to water depth, (3) the habitat quality for wading birds with dynamic habitat selection, and (4) an evaluation of the habitat of the Cape Sable seaside sparrow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173069","collaboration":"Prepared as part of the U.S. Geological Survey Greater Everglades Priority Ecosystems Science and in collaboration with theDirector, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
The increased availability of global datasets and technologies such as global hydrologic models and the Gravity Recovery and Climate Experiment (GRACE) satellites have resulted in a growing number of global-scale assessments of water availability using simple indices of water stress. Developed initially for surface water, such indices are increasingly used to evaluate global groundwater resources. We compare indices of groundwater development stress for three major agricultural areas of the United States to information available from regional water budgets developed from detailed groundwater modeling. These comparisons illustrate the potential value of regional-scale analyses to supplement global hydrological models and GRACE analyses of groundwater depletion. Regional-scale analyses allow assessments of water stress that better account for scale effects, the dynamics of groundwater flow systems, the complexities of irrigated agricultural systems, and the laws, regulations, engineering, and socioeconomic factors that govern groundwater use. Strategic use of regional-scale models with global-scale analyses would greatly enhance knowledge of the global groundwater depletion problem.
","language":"English","publisher":"Wiley","doi":"10.1111/gwat.12578","usgsCitation":"Alley, W., Clark, B.R., Ely, M., and Faunt, C., 2018, Groundwater development stress: Global-scale indices compared to regional modeling: Groundwater, v. 56, no. 2, p. 266-275, https://doi.org/10.1111/gwat.12578.","productDescription":"10 p.","startPage":"266","endPage":"275","ipdsId":"IP-088279","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":347137,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-15","publicationStatus":"PW","scienceBaseUri":"59eeffa2e4b0220bbd988f5a","contributors":{"authors":[{"text":"Alley, William 0000-0001-7286-3938 walley@usgs.gov","orcid":"https://orcid.org/0000-0001-7286-3938","contributorId":140175,"corporation":false,"usgs":true,"family":"Alley","given":"William","email":"walley@usgs.gov","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":714370,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Brian R. 0000-0001-6611-3807 brclark@usgs.gov","orcid":"https://orcid.org/0000-0001-6611-3807","contributorId":1502,"corporation":false,"usgs":true,"family":"Clark","given":"Brian","email":"brclark@usgs.gov","middleInitial":"R.","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":714371,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ely, Matt 0000-0003-3190-2907 mely@usgs.gov","orcid":"https://orcid.org/0000-0003-3190-2907","contributorId":1641,"corporation":false,"usgs":true,"family":"Ely","given":"Matt","email":"mely@usgs.gov","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714373,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Faunt, Claudia C. 0000-0001-5659-7529 ccfaunt@usgs.gov","orcid":"https://orcid.org/0000-0001-5659-7529","contributorId":150147,"corporation":false,"usgs":true,"family":"Faunt","given":"Claudia C.","email":"ccfaunt@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714372,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190749,"text":"70190749 - 2018 - Maximizing establishment and survivorship of field-collected and greenhouse-cultivated biocrusts in a semi-cold desert","interactions":[],"lastModifiedDate":"2018-07-23T13:10:39","indexId":"70190749","displayToPublicDate":"2017-09-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3089,"text":"Plant and Soil","active":true,"publicationSubtype":{"id":10}},"title":"Maximizing establishment and survivorship of field-collected and greenhouse-cultivated biocrusts in a semi-cold desert","docAbstract":"Aims
Biological soil crusts (biocrusts) are soil-surface communities in drylands, dominated by cyanobacteria, mosses, and lichens. They provide key ecosystem functions by increasing soil stability and influencing soil hydrologic, nutrient, and carbon cycles. Because of this, methods to reestablish biocrusts in damaged drylands are needed. Here we test the reintroduction of field-collected vs. greenhouse-cultured biocrusts for rehabilitation.
Methods
We collected biocrusts for 1) direct reapplication, and 2) artificial cultivation under varying hydration regimes. We added field-collected and cultivated biocrusts (with and without hardening treatments) to bare field plots and monitored establishment.
Results
Both field-collected and cultivated cyanobacteria increased cover dramatically during the experimental period. Cultivated biocrusts established more rapidly than field-collected biocrusts, attaining ~82% cover in only one year, but addition of field-collected biocrusts led to higher species richness, biomass (as assessed by chlorophyll a) and level of development. Mosses and lichens did not establish well in either case, but late successional cover was affected by hardening and culture conditions.
Conclusions
This study provides further evidence that it is possible to culture biocrust components from later successional materials and reestablish cultured organisms in the field. However, more research is needed into effective reclamation techniques.
Increasing demand on groundwater resources motivates understanding of the controls on recharge dynamics so model predictions under current and future climate may improve. Here we address questions about the nonlinear behavior of flux variability in the vadose zone that may explain previously reported teleconnections between global-scale climate variability and fluctuations in groundwater levels. We use hundreds of HYDRUS-1D simulations in a sensitivity analysis approach to evaluate the damping depth of transient recharge over a range of periodic boundary conditions and vadose zone geometries and hydraulic parameters that are representative of aquifer systems of the conterminous United States (U.S). Although the models were parameterized based on U.S. aquifers, findings from this study are applicable elsewhere that have mean recharge rates between 3.65 and 730 mm yr–1. We find that mean infiltration flux, period of time varying infiltration, and hydraulic conductivity are statistically significant predictors of damping depth. The resulting framework explains why some periodic infiltration fluxes associated with climate variability dampen with depth in the vadose zone, resulting in steady-state recharge, while other periodic surface fluxes do not dampen with depth, resulting in transient recharge. We find that transient recharge in response to the climate variability patterns could be detected at the depths of water levels in most U.S. aquifers. Our findings indicate that the damping behavior of transient infiltration fluxes is linear across soil layers for a range of texture combinations. The implications are that relatively simple, homogeneous models of the vadose zone may provide reasonable estimates of the damping depth of climate-varying transient recharge in some complex, layered vadose zone profiles.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2017.08.028","usgsCitation":"Corona, C.R., Gurdak, J.J., Dickinson, J.E., Ferre, T., and Maurer, E.P., 2018, Climate variability and vadose zone controls on damping of transient recharge: Journal of Hydrology, v. 561, p. 1094-1104, https://doi.org/10.1016/j.jhydrol.2017.08.028.","productDescription":"11 p.","startPage":"1094","endPage":"1104","ipdsId":"IP-087076","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":469191,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2017.08.028","text":"Publisher Index Page"},{"id":345462,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"561","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59afb79ae4b0e9bde1351123","contributors":{"authors":[{"text":"Corona, Claudia R.","contributorId":196165,"corporation":false,"usgs":false,"family":"Corona","given":"Claudia","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":709517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gurdak, Jason J.","contributorId":196166,"corporation":false,"usgs":false,"family":"Gurdak","given":"Jason","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":709518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dickinson, Jesse E. 0000-0002-0048-0839 jdickins@usgs.gov","orcid":"https://orcid.org/0000-0002-0048-0839","contributorId":152545,"corporation":false,"usgs":true,"family":"Dickinson","given":"Jesse","email":"jdickins@usgs.gov","middleInitial":"E.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":709516,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ferre, T.P.A.","contributorId":196167,"corporation":false,"usgs":false,"family":"Ferre","given":"T.P.A.","email":"","affiliations":[],"preferred":false,"id":709519,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maurer, Edwin P.","contributorId":196168,"corporation":false,"usgs":false,"family":"Maurer","given":"Edwin","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":709520,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189567,"text":"70189567 - 2018 - An empirical perspective for understanding climate change impacts in Switzerland","interactions":[],"lastModifiedDate":"2018-01-05T14:35:56","indexId":"70189567","displayToPublicDate":"2017-07-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3242,"text":"Regional Environmental Change","active":true,"publicationSubtype":{"id":10}},"title":"An empirical perspective for understanding climate change impacts in Switzerland","docAbstract":"Planning for the future requires a detailed understanding of how climate change affects a wide range of systems at spatial scales that are relevant to humans. Understanding of climate change impacts can be gained from observational and reconstruction approaches and from numerical models that apply existing knowledge to climate change scenarios. Although modeling approaches are prominent in climate change assessments, observations and reconstructions provide insights that cannot be derived from simulations alone, especially at local to regional scales where climate adaptation policies are implemented. Here, we review the wealth of understanding that emerged from observations and reconstructions of ongoing and past climate change impacts in Switzerland, with wider applicability in Europe. We draw examples from hydrological, alpine, forest, and agricultural systems, which are of paramount societal importance, and are projected to undergo important changes by the end of this century. For each system, we review existing model-based projections, present what is known from observations, and discuss how empirical evidence may help improve future projections. A particular focus is given to better understanding thresholds, tipping points and feedbacks that may operate on different time scales. Observational approaches provide the grounding in evidence that is needed to develop local to regional climate adaptation strategies. Our review demonstrates that observational approaches should ideally have a synergistic relationship with modeling in identifying inconsistencies in projections as well as avenues for improvement. They are critical for uncovering unexpected relationships between climate and agricultural, natural, and hydrological systems that will be important to society in the future.
","language":"English","publisher":"Springer","doi":"10.1007/s10113-017-1182-9","usgsCitation":"Henne, P., Bigalke, M., Buntgen, U., Colombaroli, D., Conedera, M., Feller, U., Frank, D., Fuhrer, J., Grosjean, M., Heiri, O., Luterbacher, J., Mestrot, A., Rigling, A., Rossler, O., Rohr, C., Rutishauser, T., Schwikowski, M., Stampfli, A., Szidat, S., Theurillat, J., Weingartner, R., Wilcke, W., and Tinner, W., 2018, An empirical perspective for understanding climate change impacts in Switzerland: Regional Environmental Change, v. 18, no. 1, p. 205-221, https://doi.org/10.1007/s10113-017-1182-9.","productDescription":"17 p.","startPage":"205","endPage":"221","ipdsId":"IP-077272","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":469197,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1007/s10113-017-1182-9","text":"External Repository"},{"id":343951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Switzerland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 5.833740234375,\n 45.79816953017265\n ],\n [\n 10.5029296875,\n 45.79816953017265\n ],\n [\n 10.5029296875,\n 47.81315451752768\n ],\n [\n 5.833740234375,\n 47.81315451752768\n ],\n [\n 5.833740234375,\n 45.79816953017265\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"18","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-17","publicationStatus":"PW","scienceBaseUri":"596dcca0e4b0d1f9f0627547","contributors":{"authors":[{"text":"Henne, Paul D. 0000-0003-1211-5545 phenne@usgs.gov","orcid":"https://orcid.org/0000-0003-1211-5545","contributorId":169166,"corporation":false,"usgs":true,"family":"Henne","given":"Paul D.","email":"phenne@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":705211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bigalke, Moritz 0000-0002-6793-6159","orcid":"https://orcid.org/0000-0002-6793-6159","contributorId":194724,"corporation":false,"usgs":false,"family":"Bigalke","given":"Moritz","email":"","affiliations":[],"preferred":false,"id":705212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buntgen, Ulf 0000-0002-3821-0818","orcid":"https://orcid.org/0000-0002-3821-0818","contributorId":194725,"corporation":false,"usgs":false,"family":"Buntgen","given":"Ulf","email":"","affiliations":[],"preferred":false,"id":705213,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Colombaroli, Daniele 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0000-0003-2308-0907","orcid":"https://orcid.org/0000-0003-2308-0907","contributorId":194735,"corporation":false,"usgs":false,"family":"Rossler","given":"Ole","email":"","affiliations":[],"preferred":false,"id":705224,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Rohr, Christian 0000-0003-0283-6584","orcid":"https://orcid.org/0000-0003-0283-6584","contributorId":194736,"corporation":false,"usgs":false,"family":"Rohr","given":"Christian","email":"","affiliations":[],"preferred":false,"id":705225,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Rutishauser, This 0000-0003-0561-2164","orcid":"https://orcid.org/0000-0003-0561-2164","contributorId":194737,"corporation":false,"usgs":false,"family":"Rutishauser","given":"This","email":"","affiliations":[],"preferred":false,"id":705226,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Schwikowski, Margit 0000-0002-0856-5183","orcid":"https://orcid.org/0000-0002-0856-5183","contributorId":194738,"corporation":false,"usgs":false,"family":"Schwikowski","given":"Margit","email":"","affiliations":[],"preferred":false,"id":705227,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Stampfli, Andreas","contributorId":194739,"corporation":false,"usgs":false,"family":"Stampfli","given":"Andreas","email":"","affiliations":[],"preferred":false,"id":705228,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Szidat, Sonke","contributorId":194740,"corporation":false,"usgs":false,"family":"Szidat","given":"Sonke","email":"","affiliations":[],"preferred":false,"id":705229,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Theurillat, Jean-Paul","contributorId":194741,"corporation":false,"usgs":false,"family":"Theurillat","given":"Jean-Paul","email":"","affiliations":[],"preferred":false,"id":705230,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Weingartner, Rolf 0000-0001-9876-1104","orcid":"https://orcid.org/0000-0001-9876-1104","contributorId":194742,"corporation":false,"usgs":false,"family":"Weingartner","given":"Rolf","email":"","affiliations":[],"preferred":false,"id":705231,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Wilcke, Wolfgan 0000-0002-6031-4613","orcid":"https://orcid.org/0000-0002-6031-4613","contributorId":194743,"corporation":false,"usgs":false,"family":"Wilcke","given":"Wolfgan","email":"","affiliations":[],"preferred":false,"id":705232,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Tinner, Willy 0000-0001-7352-0144","orcid":"https://orcid.org/0000-0001-7352-0144","contributorId":169167,"corporation":false,"usgs":false,"family":"Tinner","given":"Willy","email":"","affiliations":[{"id":25430,"text":"University of Bern","active":true,"usgs":false}],"preferred":false,"id":705233,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}} ,{"id":70190589,"text":"70190589 - 2018 - The influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware","interactions":[],"lastModifiedDate":"2018-03-29T12:51:13","indexId":"70190589","displayToPublicDate":"2017-06-30T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3751,"text":"Wetlands Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"The influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware","docAbstract":"The dependence of downstream waters on upstream ecosystems necessitates an improved understanding of watershed-scale hydrological interactions including connections between wetlands and streams. An evaluation of such connections is challenging when, (1) accurate and complete datasets of wetland and stream locations are often not available and (2) natural variability in surface-water extent influences the frequency and duration of wetland/stream connectivity. The Upper Choptank River watershed on the Delmarva Peninsula in eastern Maryland and Delaware is dominated by a high density of small, forested wetlands. In this analysis, wetland/stream surface water connections were quantified using multiple wetland and stream datasets, including headwater streams and depressions mapped from a lidar-derived digital elevation model. Surface-water extent was mapped across the watershed for spring 2015 using Landsat-8, Radarsat-2 and Worldview-3 imagery. The frequency of wetland/stream connections increased as a more complete and accurate stream dataset was used and surface-water extent was included, in particular when the spatial resolution of the imagery was finer (i.e., <10 m). Depending on the datasets used, 12–60% of wetlands by count (21–93% of wetlands by area) experienced surface-water interactions with streams during spring 2015. This translated into a range of 50–94% of the watershed contributing direct surface water runoff to streamflow. This finding suggests that our interpretation of the frequency and duration of wetland/stream connections will be influenced not only by the spatial and temporal characteristics of wetlands, streams and potential flowpaths, but also by the completeness, accuracy and resolution of input datasets.
","language":"English","publisher":"Springer","doi":"10.1007/s11273-017-9554-y","usgsCitation":"Vanderhoof, M.K., Distler, H., Lang, M.W., and Alexander, L.C., 2018, The influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware: Wetlands Ecology and Management, v. 26, no. 1, p. 63-86, https://doi.org/10.1007/s11273-017-9554-y.","productDescription":"24 p.","startPage":"63","endPage":"86","ipdsId":"IP-084257","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":469198,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9534041","text":"External Repository"},{"id":438088,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70C4T8F","text":"USGS data release","linkHelpText":"Data Release for the influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware"},{"id":352120,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland","otherGeospatial":"Delmarva Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.1,\n 38.5\n ],\n [\n -76.1,\n 39.1\n ],\n [\n -75.5,\n 39.1\n ],\n [\n -75.5,\n 38.5\n ],\n [\n -76.1,\n 38.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-08","publicationStatus":"PW","scienceBaseUri":"5afee787e4b0da30c1bfc2b6","contributors":{"authors":[{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":709917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Distler, Hayley 0000-0001-5006-1360 hdistler@usgs.gov","orcid":"https://orcid.org/0000-0001-5006-1360","contributorId":179359,"corporation":false,"usgs":true,"family":"Distler","given":"Hayley","email":"hdistler@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":709918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lang, Megan W.","contributorId":196284,"corporation":false,"usgs":false,"family":"Lang","given":"Megan","email":"","middleInitial":"W.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":709919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alexander, Laurie C.","contributorId":196285,"corporation":false,"usgs":false,"family":"Alexander","given":"Laurie","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":709920,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70177030,"text":"70177030 - 2018 - The origin of shallow lakes in the Khorezm Province, Uzbekistan, and the history of pesticide use around these lakes","interactions":[],"lastModifiedDate":"2018-01-24T16:03:12","indexId":"70177030","displayToPublicDate":"2016-10-06T10:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2411,"text":"Journal of Paleolimnology","active":true,"publicationSubtype":{"id":10}},"title":"The origin of shallow lakes in the Khorezm Province, Uzbekistan, and the history of pesticide use around these lakes","docAbstract":"The economy of the Khorezm Province in Uzbekistan relies on the large-scale agricultural production of cotton. To sustain their staple crop, water from the Amu Darya is diverted for irrigation through canal systems constructed during the early to mid-twentieth century when this region was part of the Soviet Union. These diversions severely reduce river flow to the Aral Sea. The Province has >400 small shallow (<3 m deep) lakes that may have originated because of this intensive irrigation. Sediment cores were collected from 12 lakes to elucidate their origin because this knowledge is critical to understanding water use in Khorezm. Core chronological data indicate that the majority of the lakes investigated are less than 150 years old, which supports a recent origin of the lakes. The thickness of lacustrine sediments in the cores analyzed ranged from 20 to 60 cm in all but two of the lakes, indicating a relatively slow sedimentation rate and a relatively short-term history for the lakes. Hydrologic changes in the lakes are evident from loss on ignition and pollen analyses of a subset of the lake cores. The data indicate that the lakes have transitioned from a dry, saline, arid landscape during pre-lake conditions (low organic carbon content) and low pollen concentrations (in the basal sediments) to the current freshwater lakes (high organic content), with abundant freshwater pollen taxa over the last 50–70 years. Sediments at the base of the cores contain pollen taxa dominated by Chenopodiaceae and Tamarix, indicating that the vegetation growing nearby was tolerant to arid saline conditions. The near surface sediments of the cores are dominated by Typha/Sparganium, which indicate freshwater conditions. Increases in pollen of weeds and crop plants indicate an intensification of agricultural activities since the 1950s in the watersheds of the lakes analyzed. Pesticide profiles of DDT (dichlorodiphenyltrichloroethane) and its degradates and γ-HCH (gamma-hexachlorocyclohexane), which were used during the Soviet era, show peak concentrations in the top 10 cm of some of the cores, where estimated ages of the sediments (1950–1990) are associated with peak pesticide use during the Soviet era. These data indicate that the lakes are relatively young (mostly <150 years old) and that without irrigation and canal inputs from the Amu Darya, the lakes would not exist as freshwater lakes.
","language":"English","publisher":"Springer International Publishing","doi":"10.1007/s10933-016-9914-2","usgsCitation":"Rosen, M.R., Crootof, A., Reidy, L., Saito, L., Nishonov, B., and Scott, J.A., 2018, The origin of shallow lakes in the Khorezm Province, Uzbekistan, and the history of pesticide use around these lakes: Journal of Paleolimnology, v. 59, no. 2, p. 201-219, https://doi.org/10.1007/s10933-016-9914-2.","productDescription":"19 p.","startPage":"201","endPage":"219","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073927","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"links":[{"id":438095,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7319T07","text":"USGS data release","linkHelpText":"Datasets for determining the origin of shallow lakes in the Khorezm Province, Uzbekistan, and the history of pesticide use around these lakes"},{"id":335766,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7319T07","text":"Datasets for determining the origin of shallow lakes in the Khorezm Province, Uzbekistan, and the history of pesticide use around these lakes"},{"id":329762,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Uzbekistan","state":"Khorezm Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 60.172119140625,\n 41.582579601430346\n ],\n [\n 60.16387939453125,\n 41.629814503758624\n ],\n [\n 60.08148193359374,\n 41.70777900286713\n ],\n [\n 60.062255859375,\n 41.756971085614175\n ],\n [\n 60.09521484375,\n 41.812267143599804\n ],\n [\n 60.1336669921875,\n 41.80203073088394\n ],\n [\n 60.24078369140625,\n 41.77336007442076\n ],\n [\n 60.32867431640625,\n 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41.582579601430346\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"59","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-06","publicationStatus":"PW","scienceBaseUri":"58088688e4b0f497e78e24cb","contributors":{"authors":[{"text":"Rosen, Michael R. 0000-0003-3991-0522 mrosen@usgs.gov","orcid":"https://orcid.org/0000-0003-3991-0522","contributorId":495,"corporation":false,"usgs":true,"family":"Rosen","given":"Michael","email":"mrosen@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":651049,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crootof, Arica","contributorId":175416,"corporation":false,"usgs":false,"family":"Crootof","given":"Arica","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":651050,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reidy, Liam","contributorId":175417,"corporation":false,"usgs":false,"family":"Reidy","given":"Liam","affiliations":[],"preferred":false,"id":651051,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saito, Laurel","contributorId":139343,"corporation":false,"usgs":false,"family":"Saito","given":"Laurel","email":"","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":651052,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nishonov, Bakhriddin","contributorId":15860,"corporation":false,"usgs":false,"family":"Nishonov","given":"Bakhriddin","email":"","affiliations":[],"preferred":false,"id":651053,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scott, Julian A.","contributorId":145890,"corporation":false,"usgs":false,"family":"Scott","given":"Julian","email":"","middleInitial":"A.","affiliations":[{"id":16284,"text":"U.S.D.A. Forest Service, National Stream and Aquatic Ecology Center","active":true,"usgs":false}],"preferred":false,"id":651054,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70199137,"text":"70199137 - 2017 - Application of paleoflood surveys for the southern Black Hills of South Dakota","interactions":[],"lastModifiedDate":"2018-11-27T11:47:09","indexId":"70199137","displayToPublicDate":"2018-10-01T11:47:04","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5789,"text":"South Dakota Department of Transportation Office of Research Study","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"2010-04","title":"Application of paleoflood surveys for the southern Black Hills of South Dakota","docAbstract":"Flood-frequency analyses for the Black Hills area have especially large uncertainties and are especially important for planning purposes because of a history of extremely large and damaging floods, such as the extreme floods of June 9–10, 1972. Geology, topography, and climatology are additional complicating factors for flood-frequency characterization for the area. Two previous paleoflood studies for the Black Hills area indicated good potential for improving flood-frequency analyses through implementation of paleoflood investigations. The objectives of this study (SD2010-04) for the southern Black Hills were to (1) develop long-term flood chronologies and associated peak-flow frequency analyses for selected stream reaches by applying paleoflood hydrology approaches; and (2) develop flood-frequency information regarding “high-elevation” stream reaches to help address questions regarding differential potential for generation of exceptionally strong rain-producing thunderstorms across elevation gradients in the area. Neither objective was accomplished because the study was terminated before planned completion.\nSubstantial efforts could be applied for only 2 of the 12 research tasks prior to study termination. These were task 3 (preliminary reconnaissance) and task 4 (activities associated with Section 106 of the National Historic Preservation Act). Field reconnaissance conducted along 10 candidate streams indicated that conditions in the southern Black Hills appear quite favorable for conducting paleoflood investigations. All 10 candidate streams had moderate to good potential for favorable paleoflood evidence, and in general are well constrained in relatively narrow canyon reaches, which provides good sensitivity for changes in stage, relative to discharge.\nTask 4 (Section 106 activities) was needed because alcoves and rock shelters that are well suited for deposition and preservation of paleoflood evidence may have been used as shelters or cache locations by indigenous inhabitants and thus may be eligible for consideration as historic properties because of possible archaeological or cultural materials. The complexity of the Section 106 concerns and issues became progressively more apparent as the study evolved. The study eventually was terminated when it became apparent that the resources needed to address the Section 106 issues would overwhelm the resources available for study implementation. In the event of consideration of future re-implementation, approaches that might help expedite Section 106 issues could include (1) a partnership with another Federal agency that has substantial experience with the Section 106 process; (2) securing assistance from a consultant that could help with both the Section 106 process and the required archaeological component; and (3) partnering with a tribal college with archaeological or earth science/hydrology programs, which could help make this study become part of a learning exercise.","language":"English","publisher":"South Dakota Department of Transportation","usgsCitation":"Driscoll, D.G., 2017, Application of paleoflood surveys for the southern Black Hills of South Dakota: South Dakota Department of Transportation Office of Research Study 2010-04, 21 p.","productDescription":"21 p.","ipdsId":"IP-085944","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":359716,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":357090,"type":{"id":15,"text":"Index Page"},"url":"https://www.sddot.com/business/research/reports/Default.aspx"}],"country":"United States","state":"South Dakota","otherGeospatial":"Black Hills","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bfe65e3e4b0815414ca60fe","contributors":{"authors":[{"text":"Driscoll, Daniel G. 0000-0003-0016-8535 dgdrisco@usgs.gov","orcid":"https://orcid.org/0000-0003-0016-8535","contributorId":207583,"corporation":false,"usgs":true,"family":"Driscoll","given":"Daniel","email":"dgdrisco@usgs.gov","middleInitial":"G.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":744282,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70195159,"text":"70195159 - 2017 - Control of landslide volume and hazard by glacial stratigraphic architecture, Northwest Washington state, USA","interactions":[],"lastModifiedDate":"2018-02-08T09:31:33","indexId":"70195159","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Control of landslide volume and hazard by glacial stratigraphic architecture, Northwest Washington state, USA","docAbstract":"Landslide volumes span many orders of magnitude, but large-volume slides tend to travel\nfarther and consequently can pose a greater hazard. In northwest Washington State, USA, a\nlandscape abounding with landslides big and small, the recent occurrence of the large-volume\nand tragically deadly State Route 530 (Oso) landslide is a stark reminder of the hazards\nassociated with glacial terraces lining valleys of the western Cascade Range. What controls\nthe differences in location and size of these slope failures? Here, we examine the control on\nlandslide volume and failure style by terrace sedimentary architecture. We analyze lidar\ntopographic data in three nearby valleys and find significant variation in landslide deposit\nvolumes, morphology, and relative mobility in each valley. Geologic data show that each site\ndiffers in the thickness and position of outwash, tills, and glaciolacustrine clays. Combining\na three-dimensional limit-equilibrium slope-stability analysis (Scoops3D) with simulations\nof variably saturated groundwater flow (VS2Dt), we show that landslide volumes are highly\nsensitive both to the distribution of material strength as well as the location of perched water\ntables. Modeled landslides match observed failure sizes and depths in all valleys when the\neffects of variably saturated groundwater flow are included. The position and thickness of\nlow-strength strata act as first-order controls on landslide volume, with peak volumes for\nstratigraphic geometries similar to that of the valley containing the Oso landslide. Knowledge\nof feedbacks between lithology and hydrology is therefore critical to assess the landslide\nhazard and evolution of landscapes composed of stratigraphically layered units.","language":"English","publisher":"Geological Society of America","doi":"10.1130/G39691.1","usgsCitation":"Perkins, J., Reid, M.E., and Schmidt, K.M., 2017, Control of landslide volume and hazard by glacial stratigraphic architecture, Northwest Washington state, USA: Geology, v. 45, no. 12, p. 1139-1142, https://doi.org/10.1130/G39691.1.","productDescription":"4 p.","startPage":"1139","endPage":"1142","ipdsId":"IP-086196","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":351303,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -126.7822265625,\n 45.9511496866914\n ],\n [\n -119.0478515625,\n 45.9511496866914\n ],\n [\n -119.0478515625,\n 49.56797785892715\n ],\n [\n -126.7822265625,\n 49.56797785892715\n ],\n [\n -126.7822265625,\n 45.9511496866914\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-19","publicationStatus":"PW","scienceBaseUri":"5a7c1e6de4b00f54eb22929b","contributors":{"authors":[{"text":"Perkins, Jonathan","contributorId":201949,"corporation":false,"usgs":true,"family":"Perkins","given":"Jonathan","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":727247,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reid, Mark E. 0000-0002-5595-1503 mreid@usgs.gov","orcid":"https://orcid.org/0000-0002-5595-1503","contributorId":1167,"corporation":false,"usgs":true,"family":"Reid","given":"Mark","email":"mreid@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":727248,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmidt, Kevin M. 0000-0003-2365-8035 kschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-2365-8035","contributorId":1985,"corporation":false,"usgs":true,"family":"Schmidt","given":"Kevin","email":"kschmidt@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":727249,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70193663,"text":"sir20175133 - 2017 - Simulations of hydrologic response in the Apalachicola-Chattahoochee-Flint River Basin, Southeastern United States","interactions":[],"lastModifiedDate":"2018-01-02T13:23:03","indexId":"sir20175133","displayToPublicDate":"2017-12-29T15:45:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5133","title":"Simulations of hydrologic response in the Apalachicola-Chattahoochee-Flint River Basin, Southeastern United States","docAbstract":"A suite of hydrologic models has been developed for the Apalachicola-Chattahoochee-Flint River Basin (ACFB) as part of the National Water Census, a U.S. Geological Survey research program that focuses on developing new water accounting tools and assessing water availability and use at the regional and national scales. Seven hydrologic models were developed using the Precipitation-Runoff Modeling System (PRMS), a deterministic, distributed-parameter, process-based system that simulates the effects of precipitation, temperature, land cover, and water use on basin hydrology. A coarse-resolution PRMS model was developed for the entire ACFB, and six fine-resolution PRMS models were developed for six subbasins of the ACFB. The coarse-resolution model was loosely coupled with a groundwater model to better assess the effects of water use on streamflow in the lower ACFB, a complex geologic setting with karst features. The PRMS coarse-resolution model was used to provide inputs of recharge to the groundwater model, which in turn provide simulations of groundwater flow that were aggregated with PRMS-based simulations of surface runoff and shallow-subsurface flow. Simulations without the effects of water use were developed for each model for at least the calendar years 1982–2012 with longer periods for the Potato Creek subbasin (1942–2012) and the Spring Creek subbasin (1952–2012). Water-use-affected flows were simulated for 2008–12. Water budget simulations showed heterogeneous distributions of precipitation, actual evapotranspiration, recharge, runoff, and storage change across the ACFB. Streamflow volume differences between no-water-use and water-use simulations were largest along the main stem of the Apalachicola and Chattahoochee River Basins, with streamflow percentage differences largest in the upper Chattahoochee and Flint River Basins and Spring Creek in the lower Flint River Basin. Water-use information at a shorter time step and a fully coupled simulation in the lower ACFB may further improve water availability estimates and hydrologic simulations in the basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175133","collaboration":"U.S. Geological Survey National Water Census and Water Availability and Use Science Program","usgsCitation":"LaFontaine, J.H., Jones, L.E., and Painter, J.A., 2017, Simulations of hydrologic response in the Apalachicola-Chattahoochee-Flint River Basin, Southeastern United States: U.S. Geological Survey Scientific Investigations Report 2017–5133, 112 p., https://doi.org/10.3133/sir20175133.","productDescription":"Report: x, 112 p.; Data Release","numberOfPages":"126","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-075742","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":350203,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5133/sir20175133.pdf","text":"Report","size":"32.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5133"},{"id":350251,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/sir20175141","text":"Scientific Investigations Report 2017-5141","linkHelpText":"- Groundwater-Flow Budget for the Lower Apalachicola-Chattahoochee-Flint River Basin in Southwestern Georgia and Parts of Florida and Alabama, 2008–12"},{"id":350202,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5133/coverthb.jpg"},{"id":350244,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FJ2F1R","text":"USGS data release","description":"USGS data release","linkHelpText":"Model Input and Output for Hydrologic Simulations of the Apalachicola-Chattahoochee-Flint River Basin using the Precipitation Runoff Modeling System"}],"country":"United States","otherGeospatial":"Apalachicola-Chattahoochee-Flint River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.660400390625,\n 29.726222319395504\n ],\n [\n -83.397216796875,\n 29.726222319395504\n ],\n [\n -83.397216796875,\n 34.88593094075317\n ],\n [\n -85.660400390625,\n 34.88593094075317\n ],\n [\n -85.660400390625,\n 29.726222319395504\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
As part of the National Water Census program in the Apalachicola-Chattahoochee-Flint (ACF) River Basin, the U.S. Geological Survey evaluated the groundwater budget of the lower ACF, with particular emphasis on recharge, characterizing the spatial and temporal relation between surface water and groundwater, and groundwater pumping. To evaluate the hydrologic budget of the lower ACF River Basin, a groundwater-flow model, constructed using MODFLOW-2005, was developed for the Upper Floridan aquifer and overlying semiconfining unit for 2008–12. Model input included temporally and spatially variable specified recharge, estimated using a Precipitation-Runoff Modeling System (PRMS) model for the ACF River Basin, and pumping, partly estimated on the basis of measured agricultural pumping rates in Georgia. The model was calibrated to measured groundwater levels and base flows, which were estimated using hydrograph separation.
The simulated groundwater-flow budget resulted in a small net cumulative loss of groundwater in storage during the study period. The model simulated a net loss in groundwater storage for all the subbasins as conditions became substantially drier from the beginning to the end of the study period. The model is limited by its conceptualization, the data used to represent and calibrate the model, and the mathematical representation of the system; therefore, any interpretations should be considered in light of these limitations. In spite of these limitations, the model provides insight regarding water availability in the lower ACF River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175141","collaboration":"U.S. Geological Survey National Water Census and Water Availability and Use Science Program","usgsCitation":"Jones, L.E., Painter, Jaime, LaFontaine, Jacob, Sepulveda, Nicasio, and Sifuentes, D.F., 2017, Groundwater-flow budget for the lower Apalachicola-Chattahoochee-Flint River Basin in southwestern Georgia and parts of \nFlorida and Alabama, 2008–12: U.S. Geological Survey Scientific Investigations Report 2017–5141, 76 p., \nhttps://doi.org/10.3133/sir20175141.","productDescription":"Report: viii, 76 p.; Data Release","numberOfPages":"88","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":350246,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5141/coverthb.jpg"},{"id":350249,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/publication/sir20175133","text":"Scientific Investigations Report 2017-5133","linkHelpText":"- Simulations of Hydrologic Response in the Apalachicola-Chattahoochee-Flint River Basin, Southeastern United States"},{"id":350247,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5141/sir20175141.pdf","text":"Report","size":"10.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5141"},{"id":350248,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DV1HCG","text":"USGS data release","description":"USGS data release"}],"country":"United States","state":"Alabama, Florida, Georgia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.5,\n 30.5\n ],\n [\n -83.75,\n 30.5\n ],\n [\n -83.75,\n 32.25\n ],\n [\n -85.5,\n 32.25\n ],\n [\n -85.5,\n 30.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
Geochemical Modeling for Mine Site Characterization and Remediation is the fourth of six volumes in the Management Technologies for Metal Mining Infl uenced Water series about technologies for management of metal mine and metallurgical process drainage.
This handbook describes the important components of hydrogeochemical modeling for mine environments, primarily those mines where sulfi de minerals are present—metal mines and coal mines.
It provides general guidelines on the strengths and limitations of geochemical modeling and an overview of its application to the hydrogeochemistry of both unmined mineralized sites and those contaminated from mineral extraction and mineral processing.
The handbook includes an overview of the models behind the codes, explains vital geochemical computations, describes several modeling processes, provides a compilation of codes, and gives examples of their application, including both successes and failures.
Hydrologic modeling is also included because mining contaminants most often migrate by surface water and groundwater transport, and contaminant concentrations are a function of water residence time as well as pathways.
This is an indispensable resource for mine planners and engineers, environmental managers, land managers, consultants, researchers, government regulators, nongovernmental organizations, students, stakeholders, and anyone with an interest in mining influenced water.
The U.S. Geological Survey (USGS), in support of the Massachusetts Estuaries Project (MEP), delineated groundwater-contributing areas to various hydrologic receptors including ponds, streams, and coastal water bodies throughout southeastern Massachusetts, including portions of the Plymouth-Carver aquifer system and all of Cape Cod. These contributing areas were delineated over a 6-year period from 2003 through 2008 by using previously published regional USGS groundwater-flow models for the Plymouth-Carver region (Masterson and others, 2009), the Sagamore (western) and Monomoy (eastern) flow lenses of Cape Cod (Walter and Whealan, 2005), and lower Cape Cod (Masterson, 2004). The original USGS groundwater-contributing areas were subsequently revised in some locations by the MEP to remove modeling artifacts or to make the contributing areas more consistent with site-specific hydrologic conditions without further USGS review. This report describes the process used to create the USGS groundwater-contributing areas and provides these model results in their original format in a single, publicly accessible publication.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1074","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Carlson, C.S., Masterson, J.P., Walter, D.A., and Barbaro, J.R., 2017, Development of simulated groundwater-contributing areas to selected streams, ponds, coastal water bodies, and production wells in the Plymouth-Carver region and Cape Cod, Massachusetts: U.S. Geological Survey Data Series 1074, 17 p., https://doi.org/10.3133/ds1074.","productDescription":"Report: iv, 17 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087594","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":350104,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7V69H2Z","text":"USGS data release","description":"USGS data release","linkHelpText":"Simulated Groundwater-Contributing Areas to Selected Streams, Ponds, Coastal Water Bodies, and Production Wells, Plymouth-Carver Region and Cape Cod, Massachusetts"},{"id":350102,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1074/coverthb.jpg"},{"id":350103,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1074/ds1074.pdf","text":"Report","size":"5.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1074"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod, Plymouth-Carver Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.015625,\n 41.50857729743935\n ],\n [\n -69.88128662109375,\n 41.50857729743935\n ],\n [\n -69.88128662109375,\n 42.167475010395336\n ],\n [\n -71.015625,\n 42.167475010395336\n ],\n [\n -71.015625,\n 41.50857729743935\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
We worked with managers in two focal areas to plan for the uncertain future by integrating quantitative climate change scenarios and simulation modeling into scenario planning exercises.
In our central North Dakota focal area, centered on Knife River Indian Villages National Historic Site, managers are concerned about how changes in flood severity and growing conditions for native and invasive plants may affect archaeological resources and cultural landscapes associated with the Knife and Missouri Rivers. Climate projections and hydrological modeling based on those projections indicate plausible changes in spring and summer soil moisture ranging from a 7 percent decrease to a 13 percent increase and maximum winter snowpack (important for spring flooding) changes ranging from a 13 percent decrease to a 47 percent increase. Facilitated discussions among managers and scientists exploring the implications of these different climate scenarios for resource management revealed potential conflicts between protecting archeological sites and fostering riparian cottonwood forests. The discussions also indicated the need to prioritize archeological sites for excavation or protection and culturally important plant species for intensive management attention.
In our southwestern South Dakota focal area, centered on Badlands National Park, managers are concerned about how changing climate will affect vegetation production, wildlife populations, and erosion of fossils, archeological artifacts, and roads. Climate scenarios explored by managers and scientists in this focal area ranged from a 13 percent decrease to a 33 percent increase in spring precipitation, which is critical to plant growth in the northern Great Plains region, and a slight decrease to a near doubling of intense rain events. Facilitated discussions in this focal area concluded that greater effort should be put into preparing for emergency protection, excavation, and preservation of exposed fossils or artifacts and revealed substantial opportunities for different agencies to learn from each other and cooperate on common management goals. Follow up quantitative simulation modeling of grassland dynamics helped quantify the degree of change expected in vegetation production under the wide range of climate scenarios and suggested that (a) low grazing rates could be adversely affecting vegetation composition in the national park and (b) understanding of the management practices needed to maintain desired vegetation conditions is incomplete.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171129","usgsCitation":"Symstad, A.J., Miller, B.W., Friedman, J.M., Fisichelli, N.A., Ray, A.J., Rowland, Erika, and Schuurman, G.W., 2017, Model-based scenario planning to inform climate change adaptation in the Northern Great Plains—Final report: U.S. Geological Survey Open-File Report 2017–1129, 22 p., https://doi.org/10.3133/ofr20171129.","productDescription":"Report: vii, 22 p.; Data Release","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-089059","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":348794,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1129/coverthb.jpg"},{"id":348795,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1129/ofr20171129.pdf","text":"Report","size":"2.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1129"},{"id":348796,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7T1524X","text":"USGS data release","linkHelpText":"State-and-transition simulation model of rangeland vegetation in southwest South Dakota (1969–2050)"}],"country":"United States","state":"Montana, Nebraska, North Dakota, South Dakota, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114,\n 41\n ],\n [\n -97,\n 41\n ],\n [\n -97,\n 49\n ],\n [\n -114,\n 49\n ],\n [\n -114,\n 41\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, North Dakota 58401
The U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility evaluated three Hydrolab HL4 multiparameter water-quality sondes by OTT Hydromet. The sondes were equipped with temperature, conductivity, pH, dissolved oxygen (DO), and turbidity sensors. The sensors were evaluated for compliance with the USGS National Field Manual for the Collection of Water-Quality Data (NFM) criteria for continuous water-quality monitors and to verify the validity of the manufacturer’s technical specifications. The conductivity sensors were evaluated for the accuracy of the specific conductance (SC) values (conductance at 25 degrees Celsius [oC]), that were calculated by using the vendor default method, Hydrolab Fresh. The HL4’s communication protocols and operating temperature range along with accuracy of the water-quality sensors were tested in a controlled laboratory setting May 1–19, 2016. To evaluate the sonde’s performance in a surface-water field application, an HL4 equipped with temperature, conductivity, pH, DO, and turbidity sensors was deployed June 20–July 22, 2016, at USGS water-monitoring site 02492620, Pearl River at National Space Technology Laboratories (NSTL) Station, Mississippi, located near Bay Saint Louis, Mississippi, and compared to the adjacent well-maintained EXO2 site sonde.
The three HL4 sondes met the USGS temperature testing criteria and the manufacturer’s technical specifications for temperature based upon the median room temperature difference between the measured and standard temperatures, but two of the three sondes exceeded the allowable difference criteria at the temperature extremes of approximately 5 and 40 ºC. Two sondes met the USGS criteria for SC. One of the sondes failed the criteria for SC when evaluated in a 100,000-microsiemens-per-centimeter (μS/cm) standard at room temperature, and also failed in a 10,000-μS/cm standard at 5, 15, and 40 ºC. All three sondes met the USGS criteria for pH and DO at room temperature, but one sonde exceeded the allowable difference criteria when tested in pH 5.00 buffer and at 40 ºC. The USGS criteria and the technical specifications for turbidity were met by one sonde in standards ranging from 10 to 3,000 nephelometric turbidity units (NTU). A second sonde met the USGS criteria and the technical specifications except in the 3,000-NTU standard, and the third sonde exceeded the USGS calibration criteria in the 10- and 20-NTU standards and the technical specifications in the 20-NTU standard.
Results of the field test showed acceptable performance and revealed that differences in data sample processing between sonde manufacturers may result in variances between the reported measurements when comparing one sonde to another. These variances in data would be more pronounced in dynamic site conditions. The lack of a wiper or other sensor-cleaning device on the DO sensor could prove problematic, and could limit the use of the HL4 to profiling applications or at sites with limited biofouling.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171153","usgsCitation":"Snazelle, T.T., 2017, Evaluation of the Hydrolab HL4 water-quality sonde and sensors: U.S. Geological Survey Open-File Report 2017–1153, 20 p., https://doi.org/10.3133/ofr20171153.","productDescription":"Report: v, 20 p.; Data; Metadata","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072173","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":350018,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://www.sciencebase.gov/catalog/item/59b94eaae4b091459a54d8f9","text":"Data and Metadata ","linkHelpText":"Evaluation of Hydrolab HL4 Water-Quality Sondes and Sensors"},{"id":350016,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1153/coverthb.jpg"},{"id":350017,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1153/ofr20171153.pdf","text":"Report","size":"602 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1153"}],"contact":"Chief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
Sequoia Scientific’s LISST-ABS is an acoustic backscatter sensor designed to measure suspended-sediment concentration at a point source. Three LISST-ABS were evaluated at the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF). Serial numbers 6010, 6039, and 6058 were assessed for accuracy in solutions with varying particle-size distributions and for the effect of temperature on sensor accuracy. Certified sediment samples composed of different ranges of particle size were purchased from Powder Technology Inc. These sediment samples were 30–80-micron (µm) Arizona Test Dust; less than 22-µm ISO 12103-1, A1 Ultrafine Test Dust; and 149-µm MIL-STD 810E Silica Dust. The sensor was able to accurately measure suspended-sediment concentration when calibrated with sediment of the same particle-size distribution as the measured. Overall testing demonstrated that sensors calibrated with finer sized sediments overdetect sediment concentrations with coarser sized sediments, and sensors calibrated with coarser sized sediments do not detect increases in sediment concentrations from small and fine sediments. These test results are not unexpected for an acoustic-backscatter device and stress the need for using accurate site-specific particle-size distributions during sensor calibration. When calibrated for ultrafine dust with a less than 22-µm particle size (silt) and with the Arizona Test Dust with a 30–80-µm range, the data from sensor 6039 were biased high when fractions of the coarser (149-µm) Silica Dust were added. Data from sensor 6058 showed similar results with an elevated response to coarser material when calibrated with a finer particle-size distribution and a lack of detection when subjected to finer particle-size sediment. Sensor 6010 was also tested for the effect of dissimilar particle size during the calibration and showed little effect. Subsequent testing revealed problems with this sensor, including an inadequate temperature compensation, making this data questionable. The sensor was replaced by Sequoia Scientific with serial number 6039. Results from the extended temperature testing showed proper temperature compensation for sensor 6039, and results from the dissimilar calibration/testing particle-size distribution closely corroborated the results from sensor 6058.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171154","usgsCitation":"Snazelle, T.T., 2017, Laboratory evaluation of the Sequoia Scientific LISST-ABS acoustic backscatter sediment sensor: U.S. Geological Survey Open-File Report 2017–1154, 21 p., https://doi.org/10.3133/ofr20171154.","productDescription":"Report: vii, 21 p.; Data; Metadata","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-083385","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":350020,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1154/ofr20171154.pdf","text":"Report","size":"921 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1154"},{"id":350021,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://www.sciencebase.gov/catalog/item/59ba9376e4b091459a563ba7","text":"Data and Metadata","linkHelpText":"HIF evaluation of LISST-ABS"},{"id":350019,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1154/coverthb.jpg"}],"contact":"Chief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
Tsala Apopka Lake is a complex system of lakes and wetlands, with intervening uplands, located in Citrus County in west-central Florida. It is located within the 2,100 square mile watershed of the Withlacoochee River, which drains north and northwest towards the Gulf of Mexico. The lake system is managed by the Southwest Florida Water Management District as three distinct “pools,” which from upstream to downstream are referred to as the Floral City Pool, Inverness Pool, and Hernando Pool. Each pool contains a mixture of deep-water lakes that remain wet year round, ephemeral (seasonal) ponds and wetlands, and dry uplands. Many of the major deep-water lakes are interconnected by canals. Flow from the Withlacoochee River, when conditions allow, can be diverted into the lake system. Flow thorough the canals can be used to control the distribution of water between the three pools. Flow in the canals is controlled using structures, such as gates and weirs.
Hydrogeologic units in the study area include a surficial aquifer consisting of Quaternary-age sediments, a discontinuous intermediate confining unit consisting of Miocene- and Pliocene-age sediments, and the underlying Upper Floridan aquifer, which consists of Eocene- and Oligocene-age carbonates. The fine-grained quartz sands that constitute the surficial aquifer are generally thin, typically less than 25 feet thick, within the vicinity of Tsala Apopka Lake. A thin, discontinuous, sandy clay layer forms the intermediate confining unit. The Upper Floridan aquifer is generally unconfined in the vicinity of Tsala Apopka Lake because the intermediate confining unit is discontinuous and breached by numerous karst features. In the study area, the Upper Floridan aquifer includes the upper Avon Park Formation and Ocala Limestone. The Ocala Limestone is the primary source of drinking water and spring flow in the area.
The objectives of this study are to document the interaction of Tsala Apopka Lake, the surficial aquifer, and the Upper Floridan aquifer; and to estimate an annual water budget for each pool and for the entire lake system for 2004–12. The hydrologic interactions were evaluated using hydraulic head and geochemical data. Geochemical data, including major ion, isotope, and age-tracer data, were used to evaluate sources of water and to distinguish flow paths. Hydrologic connection of the surficial environment (lakes, ponds, wetlands, and the surficial aquifer) was quantified on the basis of a conceptualized annual water-budget model. The model included the change in surface water and groundwater storage, precipitation, evapotranspiration, surface-water inflow and outflow, and net groundwater exchange with the underlying Upper Floridan aquifer. The control volume for each pool extended to the base of the surficial aquifer and covered an area defined to exceed the maximum inundated area for each pool during 2004–12 by 0.5 foot. Net groundwater flow was computed as a lumped value and was either positive or negative, with a negative value indicating downward or lateral leakage from the control volume and a positive value indicating upward leakage to the control volume.
The annual water budget for Tsala Apopka Lake was calculated using a combination of field observations and remotely sensed data for each of three pools and for the composite three pool area. A digital elevation model at a 5-foot grid spacing and bathymetric survey data were used to define the land-surface elevation and volume of each pool and to calculate the changes in inundated area with change in lake stage. Continuous lake-stage and groundwater-level data were used to define the change in storage for each pool. The rainfall data used in the water-budget calculations were based on daily radar reflectance data and measured rainfall from weather stations. Evapotranspiration was computed as a function of reference evapotranspiration, adjusted to actual evapotranspiration using a monthly land-cover coefficient (based on evapotranspiration measurements at stations located in representative landscapes). Surface-water inflows and outflows were determined using stage data collected at a series of streamgages installed primarily at the water-control structures. Discharge was measured under varying flow regimes and ratings were developed for the water-control structures. The discharge data collected during the study period were used to calibrate a surface-water flow model for 2004–12. Flows predicted by the model were used in the water-budget analysis. Net groundwater flow was determined as the residual term in the water-budget equation.
The results of the water-budget analysis indicate that rainfall was the largest input of water to Tsala Apopka Lake, whereas evapotranspiration was the largest output. For the 2004–12 analysis period, surface-water inflow accounted for 11 percent of the inputs, net groundwater inflow accounted for 1 percent of inputs (annual periods with positive net groundwater flow were included as inputs, while annual periods with negative net groundwater flow were counted as outputs), and rainfall accounted for the remaining 88 percent. For the same period, the outputs consisted of 2 percent surface-water outflow, 12 percent net groundwater outflow, and 86 percent evapotranspiration. Net groundwater inflows and surface-water/groundwater storage were negligible during the water-budget period but could be important components of the budget in individual years.
The net groundwater flow was negative (downward) for 8 out of the 9 years modeled (2004–12), indicating that the Tsala Apopka Lake study area was primarily a recharge area for the underlying Upper Floridan aquifer during this time period. Groundwater-level elevation in paired wells (adjacent wells completed in the surficial aquifer and Upper Floridan aquifer) typically was higher in the surficial aquifer than the Upper Floridan aquifer. However, hydraulic head data indicate that the surficial aquifer often has discharge potential to the surface-water system, especially in the low lying areas near the major lakes. Surficial-aquifer water levels were often higher than lake stages, especially during wet periods, which is likely an indication of aquifer-to-lake seepage in these areas. East of the major lakes, hydraulic head data were nearly equal in the surficial aquifer and Upper Floridan aquifer, which is an indication that the Upper Floridan aquifer is unconfined. Based on deuterium and oxygen stable isotope data collected in December 2011 and December 2012, there was no evidence of recharge to the Upper Floridan aquifer from the wetlands east of the major lakes; aquifer isotopic ratios did not indicate an enriched source, which is typical of lake and wetland sources. West of the major lakes, there was evidence of enriched isotopic ratios in water samples from the Upper Floridan aquifer. Differences in hydraulic head at paired wells in the surficial aquifer and Upper Floridan aquifer indicated that the surficial aquifer has the potential to recharge the Upper Floridan aquifer in the western part of the pools and west of the major lakes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175132","collaboration":"Prepared in cooperation with the Southwest Florida Water Management District","usgsCitation":"McBride, W.S., Metz, P.A., Ryan, P.J., Fulkerson, Mark, and Downing, H.C., 2017, Groundwater levels, geochemistry, and water budget of the Tsala Apopka Lake system, west-central Florida, 2004–12: U.S. Geological Survey Scientific Investigations Report 2017–5132, 100 p., https://doi.org/10.3133/sir20175132.","productDescription":"xi, 100 p.","numberOfPages":"116","onlineOnly":"Y","ipdsId":"IP-059771","costCenters":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"links":[{"id":350056,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5132/sir20175132.pdf","text":"Report","size":"14.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5132"},{"id":350055,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5132/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Tsala Apopka Lake System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.452392578125,\n 28.66890107414433\n ],\n [\n -82.0520782470703,\n 28.66890107414433\n ],\n [\n -82.0520782470703,\n 29.00693934321682\n ],\n [\n -82.452392578125,\n 29.00693934321682\n ],\n [\n -82.452392578125,\n 28.66890107414433\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
The U.S. Geological Survey (USGS), in cooperation with the Colorado Department of Transportation, determined the peak discharge, annual exceedance probability (flood frequency), and peak stage of two floods that took place on Big Cottonwood Creek at U.S. Highway 50 near Coaldale, Colorado (hereafter referred to as “Big Cottonwood Creek site”), on August 23, 2016, and on Fountain Creek below U.S. Highway 24 in Colorado Springs, Colorado (hereafter referred to as “Fountain Creek site”), on August 29, 2016. A one-dimensional hydraulic model was used to estimate the peak discharge. To define the flood frequency of each flood, peak-streamflow regional-regression equations or statistical analyses of USGS streamgage records were used to estimate annual exceedance probability of the peak discharge. A survey of the high-water mark profile was used to determine the peak stage, and the limitations and accuracy of each component also are presented in this report. Collection and computation of flood data, such as peak discharge, annual exceedance probability, and peak stage at structures critical to Colorado’s infrastructure are an important addition to the flood data collected annually by the USGS.
The peak discharge of the August 23, 2016, flood at the Big Cottonwood Creek site was 917 cubic feet per second (ft3/s) with a measurement quality of poor (uncertainty plus or minus 25 percent or greater). The peak discharge of the August 29, 2016, flood at the Fountain Creek site was 5,970 ft3/s with a measurement quality of poor (uncertainty plus or minus 25 percent or greater).
The August 23, 2016, flood at the Big Cottonwood Creek site had an annual exceedance probability of less than 0.01 (return period greater than the 100-year flood) and had an annual exceedance probability of greater than 0.005 (return period less than the 200-year flood). The August 23, 2016, flood event was caused by a precipitation event having an annual exceedance probability of 1.0 (return period of 1 year, or the 1-year storm), which is a statistically common (high probability) storm. The Big Cottonwood Creek site is downstream from the Hayden Pass Fire burn area, which dramatically altered the hydrology of the watershed and caused this statistically rare (low probability) flood from a statistically common (high probability) storm. The peak flood stage at the cross section closest to the U.S. Highway 50 culvert was 6,438.32 feet (ft) above the North American Datum of 1988 (NAVD 88).
The August 29, 2016, flood at the Fountain Creek site had an estimated annual exceedance probability of 0.5505 (return period equal to the 1.8-year flood). The August 29, 2016, flood event was caused by a precipitation event having an annual exceedance probability of 1.0 (return period of 1 year, or the 1-year storm). The peak stage during this flood at the cross section closest to the U.S. Highway 24 bridge was 5,832.89 ft (NAVD 88).
Slope-area indirect discharge measurements were carried out at the Big Cottonwood Creek and Fountain Creek sites to estimate peak discharge of the August 23, 2016, flood and August 29, 2016, flood, respectively. The USGS computer program Slope-Area Computation Graphical User Interface was used to compute the peak discharge by adding the surveyed cross sections with Manning roughness coefficient assignments to the high-water marks. The Manning roughness coefficients for each cross section were estimated in the field using the Cowan method.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175107","collaboration":"Prepared in cooperation with the Colorado Department of Transportation","usgsCitation":"Kohn, M.S., Stevens, M.R., Mommandi, Amanullah, and Khan, A.R., 2017, Peak discharge, flood frequency, and peak stage of floods on Big Cottonwood Creek at U.S. Highway 50 near Coaldale, Colorado, and Fountain Creek below U.S. Highway 24 in Colorado Springs, Colorado, 2016: U.S. Geological Survey Scientific Investigations Report 2017–5107, 58 p., https://doi.org/10.3133/sir20175107.","productDescription":"Report: vii, 58 p.; Appendixes","numberOfPages":"70","onlineOnly":"Y","ipdsId":"IP-083372","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":349894,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5107/sir20175107_Appendix2_BigCottonwoodCr_LeftBank.zip","text":"Appendix 2, Big Cottonwood Creek, Left Bank—","size":"177 MB","linkFileType":{"id":6,"text":"zip"},"description":"Appendix 2 Left Bank","linkHelpText":"Photos of left bank high-water marks from Big Cottonwood Creek at U.S. Highway 50 near Coaldale, Colorado"},{"id":349892,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5107/coverthb.jpg"},{"id":349923,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5107/sir20175107_Appendix7_FountainCr_LeftBank.zip","text":"Appendix 7, Fountain Creek, Left Bank—","size":"303 MB","linkFileType":{"id":6,"text":"zip"},"description":"Appendix 7 Left Bank","linkHelpText":"Photos of left bank high-water marks from Fountain Creek below U.S. Highway 24 in Colorado Springs, Colorado"},{"id":349893,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5107/sir20175107.pdf","text":"Report","size":"19.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5107"},{"id":349921,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5107/sir20175107_Appendix3_BigCottonwoodCr.zip","text":"Appendix 3, Big Cottonwood Creek—","size":"154 MB","linkFileType":{"id":6,"text":"zip"},"description":"Appendix 3","linkHelpText":"Photos of cross Sections from Big Cottonwood Creek at U.S. Highway 50 near Coaldale, Colorado"},{"id":349925,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5107/sir20175107_Appendix7_FountainCr_RightBank.zip","text":"Appendix 7, Fountain Creek, Right Bank—","size":"305 MB","linkFileType":{"id":6,"text":"zip"},"description":"Appendix 7 Right Bank","linkHelpText":"Photos of right bank high-water marks from Fountain Creek below U.S. Highway 24 in Colorado Springs, Colorado"},{"id":349926,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5107/sir20175107_Appendix8_FountainCr.zip","text":"Appendix 8, Fountain Creek—","size":"220 MB","linkFileType":{"id":6,"text":"zip"},"description":"Appendix 8","linkHelpText":"Photos of cross sections from Fountain Creek below U.S. Highway 24 in Colorado Springs, Colorado"},{"id":349920,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5107/sir20175107_Appendix2_BigCottonwoodCr_RightBank.zip","text":"Appendix 2, Big Cottonwood Creek, Right Bank—","size":"142 MB","linkFileType":{"id":6,"text":"zip"},"description":"Appendix 2 Right Bank","linkHelpText":"Photos of right bank high-water marks from Big Cottonwood Creek at U.S. Highway 50 near Coaldale, Colorado"}],"country":"United States","state":"Colorado","city":"Coaldale, Colorado Springs","otherGeospatial":"Big Cottonwood Creek, Fountain Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.80493545532227,\n 38.79868097286392\n ],\n [\n -104.78673934936523,\n 38.79868097286392\n ],\n [\n -104.78673934936523,\n 38.80944982778107\n ],\n [\n -104.80493545532227,\n 38.80944982778107\n ],\n [\n -104.80493545532227,\n 38.79868097286392\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.76083183288574,\n 38.36297641178211\n ],\n [\n -105.7474637031555,\n 38.36297641178211\n ],\n [\n -105.7474637031555,\n 38.37083318856711\n ],\n [\n -105.76083183288574,\n 38.37083318856711\n ],\n [\n -105.76083183288574,\n 38.36297641178211\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225
The enhancement of agricultural lands through the use of artificial drainage systems is a common practice throughout the United States, and recently the use of this practice has expanded in the Prairie Pothole Region. Many wetlands are afforded protection from the direct effects of drainage through regulation or legal agreements, and drainage setback distances typically are used to provide a buffer between wetlands and drainage systems. A field study was initiated to assess the potential for subsurface drainage to affect wetland surface-water characteristics through a reduction in precipitation runoff, and to examine the efficacy of current U.S. Department of Agriculture drainage setback distances for limiting these effects. Surface-water levels, along with primary components of the catchment water balance, were monitored over 3 y at four seasonal wetland catchments situated in a high-relief terrain (7–11% slopes). During the second year of the study, subsurface drainage systems were installed in two of the catchments using drainage setbacks, and the drainage discharge volumes were monitored. A catchment water-balance model was used to assess the potential effect of subsurface drainage on wetland hydrology and to assess the efficacy of drainage setbacks for mitigating these effects. Results suggest that overland precipitation runoff can be an important component of the seasonal water balance of Prairie Pothole Region wetlands, accounting on average for 34% (19–49%) or 45% (39–49%) of the annual (includes snowmelt runoff) or seasonal (does not include snowmelt) input volumes, respectively. Seasonal (2014–2015) discharge volumes from the localized drainage systems averaged 81 m3 (31–199 m3), and were small when compared with average combined inputs of 3,745 m3 (1,214–6,993 m3) from snowmelt runoff, direct precipitation, and precipitation runoff. Model simulations of reduced precipitation runoff volumes as a result of subsurface drainage systems showed that ponded wetland surface areas were reduced by an average of 590 m2 (141–1,787 m2), or 24% (3–46%), when no setbacks were used (drainage systems located directly adjacent to wetland). Likewise, wetland surface areas were reduced by an average of 141 m2 (23–464 m2), or 7% (1–28%), when drainage setbacks (buffer) were used. In totality, the field data and model simulations suggest that the drainage setbacks should reduce, but not eliminate, impacts to the water balance of the four wetlands monitored in this study that were located in a high-relief terrain. However, further study is required to assess the validity of these conclusions outside of the limited parameters (e.g., terrain, weather, soils) of this study and to examine potential ecological effects of altered wetland hydrology.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/022017-JFWM-012","usgsCitation":"Tangen, B., and Finocchiaro, R., 2017, A case study examining the efficacy of drainage setbacks for limiting effects to wetlands in the Prairie Pothole Region, USA: Journal of Fish and Wildlife Management, v. 8, no. 2, p. 513-529, https://doi.org/10.3996/022017-JFWM-012.","productDescription":"17 p.","startPage":"513","endPage":"529","ipdsId":"IP-084102","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":461323,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/022017-jfwm-012","text":"Publisher Index Page"},{"id":350010,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","county":"Stutsman County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-99.2669,47.3268],[-98.8466,47.327],[-98.8392,47.327],[-98.8232,47.3272],[-98.8152,47.3271],[-98.4991,47.327],[-98.467,47.3266],[-98.4677,47.2402],[-98.4685,46.9788],[-98.4412,46.9789],[-98.4396,46.6296],[-98.7894,46.6294],[-99.0379,46.6309],[-99.1616,46.6317],[-99.4122,46.6316],[-99.4498,46.6319],[-99.4477,46.8044],[-99.4476,46.9788],[-99.4821,46.9795],[-99.4824,47.0089],[-99.4822,47.0162],[-99.4821,47.0249],[-99.4826,47.0396],[-99.4827,47.1558],[-99.4801,47.3267],[-99.2669,47.3268]]]},\"properties\":{\"name\":\"Stutsman\",\"state\":\"ND\"}}]}","volume":"8","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-01","publicationStatus":"PW","scienceBaseUri":"5a60fae7e4b06e28e9c2294a","contributors":{"authors":[{"text":"Tangen, Brian 0000-0001-5157-9882 btangen@usgs.gov","orcid":"https://orcid.org/0000-0001-5157-9882","contributorId":167277,"corporation":false,"usgs":true,"family":"Tangen","given":"Brian","email":"btangen@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":725082,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finocchiaro, Raymond 0000-0002-5514-8729 rfinocchiaro@usgs.gov","orcid":"https://orcid.org/0000-0002-5514-8729","contributorId":167278,"corporation":false,"usgs":true,"family":"Finocchiaro","given":"Raymond","email":"rfinocchiaro@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":725083,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70194784,"text":"70194784 - 2017 - First evidence of bighead carp wild recruitment in Western Europe, and its relation to hydrology and temperature","interactions":[],"lastModifiedDate":"2017-12-15T16:41:22","indexId":"70194784","displayToPublicDate":"2017-12-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"First evidence of bighead carp wild recruitment in Western Europe, and its relation to hydrology and temperature","docAbstract":"Bighead carp (Hypophthalmichthys nobilis) have been introduced throughout Europe, mostly unintentionally, and little attention has been given to their potential for natural reproduction. We investigated the presence of young-of-the-year bighead carp in an irrigation canal network of Northern Italy and the environmental conditions associated with spawning in 2011–2015. The adult bighead carp population of the canal network was composed by large, likely mature, individuals with an average density of 45.2 kg/ha (over 10 fold more than in the main river). The 29 juvenile bighead carp found were 7.4–13.1 cm long (TL) and weighed 9.5–12.7 g. Using otolith-derived spawning dates we estimated that these juveniles were 94–100 days old, placing their fertilization and hatch dates in mid-to-end-June. Using this information in combination with thermal and hydraulic data, we examined the validity of existing models predicting the onset of spawning conditions and the viability of egg pathways to elucidate spawning location of the species. While evidence of reproduction was not found every year, we determined that potentially viable spawning conditions (annual degree-days and temperature thresholds) and pathways of egg drift suitable for hatching are present in short, slow-flowing canals.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0189517","usgsCitation":"Milardi, M., Chapman, D., Long, J.M., and Castaldelli, G., 2017, First evidence of bighead carp wild recruitment in Western Europe, and its relation to hydrology and temperature: PLoS ONE, p. 1-13, https://doi.org/10.1371/journal.pone.0189517.","productDescription":"e0189517; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-083648","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":469238,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0189517","text":"Publisher Index Page"},{"id":350048,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-12","publicationStatus":"PW","scienceBaseUri":"5a60fae9e4b06e28e9c2296d","contributors":{"authors":[{"text":"Milardi, Marco","contributorId":201384,"corporation":false,"usgs":false,"family":"Milardi","given":"Marco","email":"","affiliations":[],"preferred":false,"id":725157,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":725156,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":725159,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Castaldelli, Giuseppe","contributorId":201385,"corporation":false,"usgs":false,"family":"Castaldelli","given":"Giuseppe","email":"","affiliations":[],"preferred":false,"id":725158,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194061,"text":"fs20173084 - 2017 - U.S. Geological Survey shrub/grass products provide new approach to shrubland monitoring","interactions":[],"lastModifiedDate":"2018-04-23T09:02:06","indexId":"fs20173084","displayToPublicDate":"2017-12-11T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-3084","title":"U.S. Geological Survey shrub/grass products provide new approach to shrubland monitoring","docAbstract":"In the Western United States, shrubland ecosystems provide vital ecological, hydrological, biological, agricultural, and recreational services. However, disturbances such as livestock grazing, exotic species invasion, conversion to agriculture, climate change, urban expansion, and energy development are altering these ecosystems.
Improving our understanding of how shrublands are distributed, where they are changing, the extent of the historical change, and likely future change directions is critical for successful management of these ecosystems. Remote-sensing technologies provide the most likely data source for large-area monitoring of ecosystem disturbance—both near-real time and historically. A monitoring framework supported by remote-sensing data can offer efficient and accurate analysis of change across a range of spatial and temporal scales.
The U.S. Geological Survey has been working to develop new remote-sensing data, tools, and products to characterize and monitor these changing shrubland landscapes. Nine individual map products (components) have been developed that quantify the percent of shrub, sagebrush, big sagebrush, herbaceous, annual herbaceous, litter, bare ground, shrub height, and sagebrush height at 1-percent intervals in each 30-meter grid cell. These component products are designed to be combined and customized to widely support different applications in rangeland monitoring, analysis of wildlife habitat, resource inventory, adaptive management, and environmental review.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173084","usgsCitation":"Young, S.M., 2017, U.S. Geological Survey shrub/grass products provide new approach to shrubland monitoring: U.S. Geological Fact Sheet 2017–3084, 4 p., https://doi.org/10.3133/fs20173084.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-091949","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":349910,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3084/coverthb.jpg"},{"id":349911,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3084/fs20173084.pdf","text":"Report","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017–3084"}],"contact":"Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
The natural flow regime is critical to the health of riverine ecosystems. Many hydrologic metrics (HMs) have been developed to describe natural flow regimes, quantify flow alteration, and provide the hydrologic foundation for the development of environmental flow standards. Many applications require the use of models to predict expected natural values of HMs from basin characteristics at sites with no observed records of unimpaired flows. However, the error associated with HM estimation has not been evaluated. The primary goal of our study was to provide guidance for river scientists and managers in the selection, use, and interpretation of HMs for stream classification and hydroecological investigations of river ecosystems. We evaluated the predictability of a broad suite of HMs for the conterminous USA based on random forest statistical models. We also examined how the predictability of metrics varied among unique components of the flow regime. Roughly 40% of 612 HMs we examined could be predicted reliably from basin characteristics. The predictable metrics were disproportionately represented in 5 flow components: asymmetry, seasonality, magnitude, variability, and average monthly flows. Most metrics that represent extreme hydrological events (i.e., high and low flows) could not be reliably predicted. Roughly ⅔ of the evaluated HMs were incalculable or highly biased at intermittent/ephemeral streams because of the need for logarithmic transformations or scaling by other HMs, such as mean flows or percentile flow thresholds. Scaling metrics by drainage area tended to improve predictability. We recommend that the predictability of HMs be given greater consideration in studies and applications in which they are used to characterize and assess alteration of streamflow regimes.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/694912","usgsCitation":"Eng, K., Grantham, T., Carlisle, D.M., and Wolock, D.M., 2017, Predictability and selection of hydrologic metrics in riverine ecohydrology: Freshwater Science, v. 36, no. 4, p. 915-926, https://doi.org/10.1086/694912.","productDescription":"12 p.","startPage":"915","endPage":"926","ipdsId":"IP-086242","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":358272,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc0309ae4b0fc368eb53a04","contributors":{"authors":[{"text":"Eng, Ken 0000-0001-6838-5849 keng@usgs.gov","orcid":"https://orcid.org/0000-0001-6838-5849","contributorId":3580,"corporation":false,"usgs":true,"family":"Eng","given":"Ken","email":"keng@usgs.gov","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":747728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grantham, Theodore E.","contributorId":198855,"corporation":false,"usgs":false,"family":"Grantham","given":"Theodore E.","affiliations":[{"id":6643,"text":"University of California - Berkeley","active":true,"usgs":false}],"preferred":false,"id":747729,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carlisle, Daren M. 0000-0002-7367-348X dcarlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":513,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"dcarlisle@usgs.gov","middleInitial":"M.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":747730,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":747731,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}