Item talk:Q235030
From geokb
{
"USGS Publications Warehouse": { "@context": "https://schema.org", "@type": "Article", "additionalType": "Journal Article", "name": "Patterns and predictability in the intra-annual organic carbon variability across the boreal and hemiboreal landscape", "identifier": [ { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "70192580", "url": "https://pubs.usgs.gov/publication/70192580" }, { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse Internal ID", "value": 70192580 }, { "@type": "PropertyValue", "propertyID": "DOI", "value": "10.1016/j.scitotenv.2015.03.041", "url": "https://doi.org/10.1016/j.scitotenv.2015.03.041" } ], "journal": { "@type": "Periodical", "name": "Science of the Total Environment", "volumeNumber": "520", "issueNumber": null }, "inLanguage": "en", "isPartOf": [ { "@type": "CreativeWorkSeries", "name": "Science of the Total Environment" } ], "datePublished": "2015", "dateModified": "2017-11-17", "abstract": "Factors affecting total organic carbon (TOC) concentrations in 215 watercourses across Sweden were investigated using parameter parsimonious regression approaches to explain spatial and temporal variabilities of the TOC water quality responses. We systematically quantified the effects of discharge, seasonality, and long-term trend as factors controlling intra-annual (among year) and inter-annual (within year) variabilities of TOC by evaluating the spatial variability in model coefficients and catchment characteristics (e.g. land cover, retention time, soil type).Catchment area (0.18\u201347,000\u00a0km2) and land cover types (forests, agriculture and alpine terrain) are typical for the boreal and hemiboreal zones across Fennoscandia. Watercourses had at least 6\u00a0years of monthly water quality observations between 1990 and 2010. Statistically significant models (p\u00a0<\u00a00.05) describing variation of TOC in streamflow were identified in 209 of 215 watercourses with a mean Nash-Sutcliffe efficiency index of 0.44. Increasing long-term trends were observed in 149 (70%) of the watercourses, and intra-annual variation in TOC far exceeded inter-annual variation. The average influences of the discharge and seasonality terms on intra-annual variations in daily TOC concentration were 1.4 and 1.3\u00a0mg\u00a0l\u2212\u00a01\u00a0(13 and 12% of the mean annual TOC), respectively. The average increase in TOC was 0.17\u00a0mg\u00a0l\u2212\u00a01\u00a0year\u2212\u00a01\u00a0(1.6% year\u2212\u00a01).Multivariate regression with over 90 different catchment characteristics explained 21% of the spatial variation in the linear trend coefficient, less than 20% of the variation in the discharge coefficient and 73% of the spatial variation in mean TOC. Specific discharge, water residence time, the variance of daily precipitation, and lake area, explained 45% of the spatial variation in the amplitude of the TOC seasonality.Because the main drivers of temporal variability in TOC are seasonality and discharge, first-order estimates of the influences of climatic variability and change on TOC concentration should be predictable if the studied catchments continue to respond similarly.", "description": "10 p.", "publisher": { "@type": "Organization", "name": "Elsevier" }, "author": [ { "@type": "Person", "name": "Alexander, Richard B. ralex@usgs.gov", "givenName": "Richard B.", "familyName": "Alexander", "email": "ralex@usgs.gov", "identifier": { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0001-9166-0626", "url": "https://orcid.org/0000-0001-9166-0626" }, "affiliation": [ { "@type": "Organization", "name": "National Water Quality Assessment Program", "url": "https://www.usgs.gov/programs/national-water-quality-program" }, { "@type": "Organization", "name": "Office of Water Quality", "url": "https://www.usgs.gov/mission-areas/water-resources" } ] }, { "@type": "Person", "name": "Hytteborn, Julia K.", "givenName": "Julia K.", "familyName": "Hytteborn" }, { "@type": "Person", "name": "Temnerud, Johan", "givenName": "Johan", "familyName": "Temnerud" }, { "@type": "Person", "name": "Boyer, Elizabeth W.", "givenName": "Elizabeth W.", "familyName": "Boyer", "affiliation": [ { "@type": "Organization", "name": "Pennsylvania State University" } ] }, { "@type": "Person", "name": "Futter, Martyn N.", "givenName": "Martyn N.", "familyName": "Futter" }, { "@type": "Person", "name": "Fr\u00f6berg, Mats", "givenName": "Mats", "familyName": "Fr\u00f6berg" }, { "@type": "Person", "name": "Dahn\u00e9, Joel", "givenName": "Joel", "familyName": "Dahn\u00e9" }, { "@type": "Person", "name": "Bishop, Kevin H.", "givenName": "Kevin H.", "familyName": "Bishop" } ], "funder": [ { "@type": "Organization", "name": "National Water Quality Assessment Program", "url": "https://www.usgs.gov/programs/national-water-quality-program" } ] }, "OpenAlex": { "abstract_inverted_index": { "Factors": [ 0 ], "affecting": [ 1 ], "total": [ 2 ], "organic": [ 3 ], "carbon": [ 4 ], "(TOC)": [ 5 ], "concentrations": [ 6 ], "in": [ 7, 60, 119, 123, 141, 150, 168, 190, 212, 223, 233, 255, 269 ], "215": [ 8, 126 ], "watercourses": [ 9, 127 ], "across": [ 10, 94 ], "Sweden": [ 11 ], "were": [ 12, 121, 139, 172 ], "investigated": [ 13 ], "using": [ 14 ], "parameter": [ 15 ], "parsimonious": [ 16 ], "regression": [ 17, 199 ], "approaches": [ 18 ], "to": [ 19, 296 ], "explain": [ 20 ], "spatial": [ 21, 58, 210, 231, 253 ], "and": [ 22, 39, 48, 63, 77, 83, 91, 109, 147, 162, 174, 179, 227, 246, 273, 283 ], "temporal": [ 23, 267 ], "variabilities": [ 24, 52 ], "of": [ 25, 36, 53, 102, 117, 125, 134, 144, 159, 181, 208, 220, 229, 243, 251, 258, 266, 277, 280 ], "the": [ 26, 34, 57, 89, 145, 160, 182, 209, 213, 221, 224, 230, 241, 252, 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