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Edman, Moa
Publications (10 of 12) Show all publications
Edman, M. & Sahlberg, J. (2020). The Swedish Coastal zone Model (SCM).
Open this publication in new window or tab >>The Swedish Coastal zone Model (SCM)
2020 (English)Report (Other academic)
Abstract [en]

SMHI develops and maintains a model system for water quality calculations in coastal zone waters around Sweden. It is called the Swedish Coastal zone Model (SCM) and has previously been presented in Sahlberg (2009). Since that report was published the model has been further developed and it is now also used in scientific research. This now calls for an updated report.The SCM is a coupled 1-dimensional physical and biogeochemical model. The model calculates the vertical profiles of all its variables and assumes that they are horizontally homogeneous in the studied area. In order to resolve horizontal variations, a region is divided into several smaller sub-regions, called basins, connected by sounds. Through these sound connections both water and mass of different constituents are exchanged. The basins in SCM are identical to the national water bodies defined in accordance with the Water Framework Directive (WFD). The vertical resolution is half a metre in the uppermost layers, one metre in the 4-70 m interval, and two metres between 70-100 m. Below 100 m the layer thickness increases to 5 m and to 10 m below 250 m.The physical part of SCM consists of the equation solver Program for Boundary Layers in the Environment (PROBE, Svensson (1998)), but also several subroutines which calculates, e.g., insolation, ice-cover, and the exchanges between basins. The exchanges that connect the modelled basins are assumed to be governed by baroclinic and barotropic pressure gradient between the coupled basins.The biogeochemical model is the Swedish Coastal Ocean BIogeochemical model (SCOBI, Marmefelt et al. (2000)). SCOBI is a process-oriented model that includes marine nitrogen, phosphorous and oxygen dynamics, as well as a simple representation of plankton dynamics typical for the Baltic Sea. It calculates 11 variables: zooplankton, three functional phytoplankton groups, detritus, nitrate, ammonium, phosphate, oxygen, benthic nitrogen and benthic phosphorus. SCOBI uses the O2 variable to also, indirectly, model H2S. H2S is represented as a negative oxygen concentration, i.e. the oxygen needed to oxidize a certain accumulated H2S concentration, which can also be considered as an oxygen debt.The mixing and advection of the nine pelagic biogeochemical variables are calculated by PROBE, while SCOBI calculates the process rates which decide how matter is exchanged between the 11 biogeochemical variables, and also the vertical transfers between the SCM’s grid cells due to the sinking of phytoplankton and detritus, i.e. sedimentation.SCM needs input data from the atmosphere (weather variables and deposition on nitrogen and phosphorus), from land (land run-off and point sources, e.g. sewage treatment plant and industries) and also from the open ocean.The model is part of the Swedish water management, but it is also used within research project which results in peer reviewed scientific publications.

Abstract [sv]

SMHI utvecklar och underhåller ett modellsystem för beräkningar av vattenkvalitet i Sveriges kustvatten. Modellen kallas Kustzonsmodellen (Swedish Coastal zone Model, SCM) och har tidigare presenterats i Sahlberg (2009). Sedan den rapporten publicerades 2009 har modellen utvecklats vidare och den används nu också inom forskning. Detta motiverar nu en uppdaterad rapport.Kustzonmodellen beräknar både det fysiska och biogeokemiska tillståndet i kustzonen runt Sverige. Modellen simulerar vertikalprofiler för både de fysiska, såväl som de biogeokemiska, variablerna, men bygger på antagandet att de är horisontellt homogena inom ett område. För att beräkna horisontella variationer delas en region upp i fleramindre underregioner, kallade bassänger, vilka sammankopplas av sund. Bassängerna i kustzonsmodellen är identiska med de nationella vattenförekomster som definieras i enlighet med ramdirektivet för vatten (WFD). Den vertikala upplösningen i modellen är en halv meter i de översta skikten, en meter i intervallet 4-70 m och två meter mellan 70-100 m. Under 100 m ökar skiktens tjocklek till 5 m och till 10 m under 250 m.Den fysiska delen av SCM består av ekvationslösaren Program for Boundary Layers in the environment (PROBE, Svensson (1998)), men också av beräkningsrutiner för till exempel solinstrålning, isbeläggning och utbytet mellan bassängerna. Utbytena som förbinder de modellerade bassängerna beräknas från de baroklina och barotropa tryckgradienterna över sunden.Den biogeokemiska modellen som används är Swedish Coastal Ocean BIogeochemical model (SCOBI, Marmefelt et al. (2000)). SCOBI är en processorienterad modell som inkluderar marin kväve-, fosfor- och syre-dynamik, samt en enkel representation av planktondynamik typisk för Östersjön. Den beräknar 11 variabler: zooplankton, tre fytoplanktongrupper, detritus, nitrat, ammonium, fosfat, syre, bentiskt kväve och bentiskt fosfor. SCOBI använder den modellerade syrekoncentrationen för att också indirekt modellera H2S. H2S representeras som en negativ syrekoncentration, d.v.s. det syre som skulle behövas för att oxidera en viss ackumulerad mängd H2S.Omlandningen och förflyttningen av de nio pelagiska biogeokemiska variablerna beräknas av PROBE, medan SCOBI beräknar processhastigheterna som bestämmer hur materia utbyts mellan variablerna. Även de vertikala överföringarna mellan SCM beräkningsceller som orsakas av sjunkande fytoplankton och detritus, d.v.s. sedimentation, beräknas av SCOBI.SCM behöver indata från atmosfären (väder och deposition av kväve och fosfor), från land (landavrinning och punktkällor, t.ex. avloppsreningsverk och industrier) och även från öppet hav.Modellen är en del av den svenska vattenförvaltningen, men den används också inom forskningsprojekt som resulterar i vetenskapliga publikationer.

Publisher
p. 32
Series
Oceanography, ISSN 0283-7714 ; 128
National Category
Oceanography, Hydrology and Water Resources
Research subject
Oceanography
Identifiers
urn:nbn:se:smhi:diva-5625 (URN)
Available from: 2020-02-05 Created: 2020-02-05 Last updated: 2020-02-07Bibliographically approved
Meier, M., Edman, M., Eilola, K., Placke, M., Neumann, T., Andersson, H., . . . Savchuk, O. P. (2019). Assessment of Uncertainties in Scenario Simulations of Biogeochemical Cycles in the Baltic Sea. Frontiers in Marine Science, 6, Article ID UNSP 46.
Open this publication in new window or tab >>Assessment of Uncertainties in Scenario Simulations of Biogeochemical Cycles in the Baltic Sea
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2019 (English)In: Frontiers in Marine Science, E-ISSN 2296-7745, Vol. 6, article id UNSP 46Article in journal (Refereed) Published
National Category
Oceanography, Hydrology and Water Resources
Research subject
Oceanography
Identifiers
urn:nbn:se:smhi:diva-5181 (URN)10.3389/fmars.2019.00046 (DOI)000462709300001 ()
Available from: 2019-04-09 Created: 2019-04-09 Last updated: 2019-04-09Bibliographically approved
Algotsson, J. & Edman, M. (2019). Förslag till statusklassning av parameter 9.5 Sötvatteninflöde och vattenutbyte i kustvatten och vatten i övergångszon: En jämförelse mellan Kustzonsmodellens naturliga och normala uppsättning.
Open this publication in new window or tab >>Förslag till statusklassning av parameter 9.5 Sötvatteninflöde och vattenutbyte i kustvatten och vatten i övergångszon: En jämförelse mellan Kustzonsmodellens naturliga och normala uppsättning
2019 (Swedish)Report (Other academic)
Abstract [sv]

Omkring hälften av Sveriges elproduktion utgörs idag av vattenkraft vilken produceras i omkring 2000 kraftverk. Den största avrinningen av vatten från land sker under våren och vattnet lagras i magasin för elproduktion under vintern. Denna förändring av den naturliga avrinningen har stora effekter på de akvatiska ekosystemen och vara ett av de största miljöproblemen för svenska vattendrag och sjöar.Det saknas idag en vägledning för statusklassificering av hydromorfologiska parametrar i kustvatten enligt Vattendirektivet. SMHI fick i uppdrag av Vattenmyndigheterna att ta fram ett förslag till klassgränser och klassning för parameter 9.5 Sötvatteninflöde och vattenutbyte i kustvatten och vatten i övergångszon enligt Havs- och vattenmyndighetens föreskrifter HVMFS 2013:19. Den hydrologiska modellen S-HYPE och den oceanografiska Kustzonsmodellen användes för att studera de skillnader i färskvattentillförsel samt färskvatteninnehåll, salinitet och vattenålder i ytan som orsakas av reglering av vattenflödet på land.Baserat på resultaten har regleringen av vattenflödet på land överlag lett till en ökning av färskvatteninnehållet med 2 % längs Norrlandskusten och en motsvarande minskning av färskvatteninnehållet på västkusten. Typiskt leder regleringen av vatten på land till en lägre färskvattentillförsel till kusten under våren och sommaren och en högre färskvattentillförsel till kusten på hösten och vintern jämfört med ett scenario med en naturlig landavrinning.Den naturliga bakgrundsvariationen, enligt definitionen ± 2 MAD (Median Absolute Deviation), och den Maximala Absoluta Avvikelsen, MAA, användes för att konstruera 5 statusklasser. Denna metod gav upphov till att 98 % av kustvattenförekomsterna fick en Hög eller God status för parametrarna färskvattentillförsel och salinitet, 87 % av kustvattenförekomsterna fick en Hög eller God status för färskvatteninnehåll och 83 % av kustvattenförekomsterna fick en Hög eller God status för vattenålder.

Abstract [en]

Around half of Sweden's electricity generation consists of hydropower, which is produced in about 2000 power plants. The largest drainage of water from land takes place during the spring and the water is stored in reservoirs for electricity production during the winter. This change in the natural runoff has major effects on the aquatic ecosystems and is considered to be one of the biggest environmental challenges for Swedish waterways and lakes.There is currently no guidance for status classification of hydromorphological parameters in coastal waters according to the Water Framework Directive. SMHI was commissioned by the water authorities to produce a proposal for class boundaries and classification for parameter 9.5 Freshwater inflow and water exchange in coastal water and water in transition zone in accordance with the regulations stated by the Swedish Agency for Marine and Water Management in the document HVMFS 2013:19. The hydrological model S-HYPE and the oceanographic Coastal Zone Model were used to study the changes in fresh water supply as well as fresh water content, salinity and water age of the surface water caused by regulation of water flow on land.In general, the regulation of water flow on land has led to an increase in the fresh water content by 2% along the Norrlands coast and a corresponding decrease in the fresh water content on the west coast. Typically, the regulation of water on land leads to a lower freshwater supply to the coast during spring and summer and a higher freshwater supply to the coast in the autumn and winter compared to a scenario with a natural land runoff.The natural background variation, as defined by ± 2 MAD (Median Absolute Deviation), and the Maximum Absolute Deviation, MAA, were used to construct 5 status classes.

Publisher
p. 76
Series
Oceanography, ISSN 0283-7714 ; 127
National Category
Oceanography, Hydrology and Water Resources
Research subject
Oceanography
Identifiers
urn:nbn:se:smhi:diva-5458 (URN)
Available from: 2019-11-05 Created: 2019-11-05 Last updated: 2019-11-05Bibliographically approved
Kratzer, S., Kyryliuk, D., Edman, M., Philipson, P. & Lyon, S. W. (2019). Synergy of Satellite, In Situ and Modelled Data for Addressing the Scarcity of Water Quality Information for Eutrophication Assessment and Monitoring of Swedish Coastal Waters. Remote Sensing, 11(17)
Open this publication in new window or tab >>Synergy of Satellite, In Situ and Modelled Data for Addressing the Scarcity of Water Quality Information for Eutrophication Assessment and Monitoring of Swedish Coastal Waters
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2019 (English)In: Remote Sensing, ISSN 2072-4292, E-ISSN 2072-4292, Vol. 11, no 17Article in journal (Refereed) Published
Abstract [en]

Monthly CHL-a and Secchi Depth (SD) data derived from the full mission data of the Medium Resolution Imaging Spectrometer (MERIS; 2002-2012) were analysed along a horizontal transect from the inner Braviken bay and out into the open sea. The CHL-a values were calibrated using an algorithm derived from Swedish lakes. Then, calibrated Chl-a and Secchi Depth (SD) estimates were extracted from MERIS data along the transect and compared to conventional monitoring data as well as to data from the Swedish Coastal zone Model (SCM), providing physico-biogeochemical parameters such as temperature, nutrients, Chlorophyll-a (CHL-a) and Secchi depth (SD). A high negative correlation was observed between satellite-derived CHL-a and SD (rho = -0.91), similar to the in situ relationship established for several coastal gradients in the Baltic proper. We also demonstrate that the validated MERIS-based estimates and data from the SCM showed strong correlations for the variables CHL-a, SD and total nitrogen (TOTN), which improved significantly when analysed on a monthly basis across basins. The relationship between satellite-derived CHL-a and modelled TOTN was also evaluated on a monthly basis using least-square linear regression models. The predictive power of the models was strong for the period May-November (R-2: 0.58-0.87), and the regression algorithm for summer was almost identical to the algorithm generated from in situ data in Himmerfjarden bay. The strong correlation between SD and modelled TOTN confirms that SD is a robust and reliable indicator to evaluate changes in eutrophication in the Baltic proper which can be assessed using remote sensing data. Amongst all three assessed methods, only MERIS CHL-a was able to correctly depict the pattern of phytoplankton phenology that is typical for the Baltic proper. The approach of combining satellite data and physio-biogeochemical models could serve as a powerful tool and value-adding complement to the scarcely available in situ data from national monitoring programs. In particular, satellite data will help to reduce uncertainties in long-term monitoring data due to its improved measurement frequency.

National Category
Oceanography, Hydrology and Water Resources
Research subject
Oceanography
Identifiers
urn:nbn:se:smhi:diva-5441 (URN)10.3390/rs11172051 (DOI)000486874300095 ()
Available from: 2019-10-14 Created: 2019-10-14 Last updated: 2019-10-14Bibliographically approved
Meier, M., Edman, M., Eilola, K., Placke, M., Neumann, T., Andersson, H., . . . Savchuk, O. P. (2018). Assessment of Eutrophication Abatement Scenarios for the Baltic Sea by Multi-Model Ensemble Simulations. Frontiers in Marine Science, 5, Article ID UNSP 440.
Open this publication in new window or tab >>Assessment of Eutrophication Abatement Scenarios for the Baltic Sea by Multi-Model Ensemble Simulations
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2018 (English)In: Frontiers in Marine Science, E-ISSN 2296-7745, Vol. 5, article id UNSP 440Article in journal (Refereed) Published
National Category
Oceanography, Hydrology and Water Resources
Research subject
Oceanography
Identifiers
urn:nbn:se:smhi:diva-5163 (URN)10.3389/fmars.2018.00440 (DOI)000457228300001 ()
Available from: 2019-02-12 Created: 2019-02-12 Last updated: 2019-02-12Bibliographically approved
Edman, M., Eilola, K., Almroth-Rosell, E., Meier, M., Wåhlstrom, I. & Arneborg, L. (2018). Nutrient Retention in the Swedish Coastal Zone. Frontiers in Marine Science, 5, Article ID UNSP 415.
Open this publication in new window or tab >>Nutrient Retention in the Swedish Coastal Zone
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2018 (English)In: Frontiers in Marine Science, E-ISSN 2296-7745, Vol. 5, article id UNSP 415Article in journal (Refereed) Published
National Category
Oceanography, Hydrology and Water Resources
Research subject
Oceanography
Identifiers
urn:nbn:se:smhi:diva-5164 (URN)10.3389/fmars.2018.00415 (DOI)000457228900002 ()
Available from: 2019-02-12 Created: 2019-02-12 Last updated: 2019-02-12Bibliographically approved
Turner, D. R., Edman, M., Gallego-Urrea, J. A., Claremar, B., Hassellov, I.-M., Omstedt, A. & Rutgersson, A. (2018). The potential future contribution of shipping to acidification of the Baltic Sea. Ambio, 47(3), 368-378
Open this publication in new window or tab >>The potential future contribution of shipping to acidification of the Baltic Sea
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2018 (English)In: Ambio, ISSN 0044-7447, E-ISSN 1654-7209, Vol. 47, no 3, p. 368-378Article in journal (Refereed) Published
National Category
Oceanography, Hydrology and Water Resources
Research subject
Oceanography
Identifiers
urn:nbn:se:smhi:diva-4564 (URN)10.1007/s13280-017-0950-6 (DOI)000427846800010 ()28983824 (PubMedID)
Available from: 2018-04-10 Created: 2018-04-10 Last updated: 2018-05-22Bibliographically approved
Wåhlström, I., Eilola, K., Edman, M. & Almroth-Rosell, E. (2017). Evaluation of open sea boundary conditions for the coastal zone. A model study in the northern part of the Baltic Proper..
Open this publication in new window or tab >>Evaluation of open sea boundary conditions for the coastal zone. A model study in the northern part of the Baltic Proper.
2017 (English)Report (Other academic)
Abstract [en]

The environmental conditions in the coastal zone are strongly connected with the conditions in the open sea as the transports across the boundaries are extensive. Therefore, it is of critical importance that coastal zone models have lateral boundary forcing of high quality and required parameters with good coverage in space and time.

The Swedish Coastal zone Model (SCM) is developed at SMHI to calculate water quality in the coastal zone. This model is currently forced by the outcome from a one-dimensional model, assimilated to observations along the coast. However, these observations are scarce both in space, time and do usually not include all required parameters. In addition, the variability closer to the coast may be underestimated by the open sea monitoring stations used for the data assimilation. These problems are partly overcome by utilize the one-dimensional model that resolves all the variables used in the SCM. However, the method is not applicable for examine either the past period or future scenario where the latter analyze how climate change might affect the coastal zone. In the present study, we therefore evaluate the possibility to use results from a three-dimensional coupled physical and biogeochemical model of the Baltic Sea as open sea boundary conditions for the coastal zone, primarily to investigate the two periods mentioned above.

Seven sensitivity experiments have been carried out in a pilot area of the coastal zone, the northern part of the Baltic proper, including the Stockholm Archipelago. The sensitivity tests were performed in order to explore methods to extract the outcome from the three-dimensional model, RCO-SCOBI, and apply as lateral boundary forcing for the SCM. RCO-SCOBI is a model for the open Baltic Sea with high horizontal and vertical resolution of the required variables. The results from the different tests were examined and evaluated against observations in the coastal zone. This was executed for both the physical and the biogeochemical variables utilizing a statistical method.

The results from this study concluded that the outcome from the RCO-SCOBI is applicable as forcing files for the SCM. The best results in the tests was obtained with a method extracting depth profiles for the required variables from the RCO-SCOBI at a position 10 nautical miles to the east and 10 nautical miles to the south in the Baltic proper or north in the Gulf of Bothnia outside each of the outer basins.

Abstract [sv]

Miljötillståndet i Sveriges kustvatten är starkt kopplat till tillståndet i det öppna havet på grund av det stora vattenutbytet mellan dessa. Det är därför viktigt att modeller utvecklade för kustzonens vatten har drivning från utsjön av god kvalitet med bra täckning i tid och rum samt med information om de variabler som krävs.

För att beräkna vattenkvalitén i kustnära vatten har SMHI utvecklat en modell kallad kustzonsmodellen (SCM). Den drivs för närvarande från öppna havet av resultatfiler från en en-dimensionell modell som med hjälp av observationer har korrigerat och förbättrat modellresultaten. Tyvärr är dessa observationer undermåliga i tid och rum, och saknar nödvändiga variabler för att få bra drivning av SCM modellen. Dessa mätstationer ligger också längre ut i öppna havet och kan därför underskatta variabiliteten närmare kusten för de olika parametrarna. Dessa problem löses delvis med den en-dimensionella modellen som beräknar alla de variabler som är nödvändiga i SCM. Dock är dessa resultat inte användbara om man vill undersöka en historisk period eller framtida klimatförändringar i kustzonen. På grund av dessa tillkortakommanden undersöker vi i denna studie om det är möjligt att istället ersätta dagens drivning från öppna havet med resultat från en tre-dimensionell, kopplad fysisk och biogeokemisk modell för Östersjön som drivning för SCM, framförallt för att undersöka de två ovan nämnda perioder.

I denna studie har sju känslighetsexperiment utförts i en pilotstudie för Norra Östersjön, inklusive Stockholms skärgård. De sju känslighetsexperimenten utfördes för att utvärdera olika metoder att extrahera resultat-filer från den tre-dimensionella modellen RCO-SCOBI med avsikt att användas som drivning för SCM. RCO-SCOBI är en modell för Östersjön med hög horisontell och vertikal upplösning av de variabler som krävs. Resultaten för både de fysiska och biogeokemiska processerna från de olika testen undersöktes och utvärderades mot observationer i kustzonen med hjälp av en statistisk metod.

Slutsaten från dessa test är att resultatfiler från RCO-SCOBI är tillämpbara som utsjödrivning för SCM. Den bästa metoden är att extrahera en djupprofil per variabel för varje ytterbassäng i SCM i en punkt 10 nautiska mil österut och 10 nautiska mil söderut i egentliga Östersjön eller norrut i Bottenhavet för varje ytterbassäng i SCM.

Publisher
p. 23
Series
RO, Report Oceanography, ISSN 0283-1112 ; 55
National Category
Oceanography, Hydrology and Water Resources
Research subject
Oceanography
Identifiers
urn:nbn:se:smhi:diva-3914 (URN)
Available from: 2017-01-25 Created: 2017-01-25 Last updated: 2018-01-13Bibliographically approved
Eilola, K., Lindqvist, S., Almroth-Rosell, E., Edman, M., Wåhlstrom, I., Bartoli, M., . . . Zilius, M. (2017). Linking process rates with modellingdata and ecosystem characteristics.
Open this publication in new window or tab >>Linking process rates with modellingdata and ecosystem characteristics
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2017 (English)Report (Refereed)
Abstract [en]

This report is related to the BONUS project “Nutrient Cocktails in COAstal zones of the Baltic Sea” alias COCOA. The aim of BONUS COCOA is to investigate physical, biogeochemical and biological processes in a combined and coordinated fashion to improve the understanding of the interaction of these processes on the removal of nutrients along the land-sea interface. The report is especially related to BONUS COCOA WP 6 in which the main objective is extrapolation of results from the BONUS COCOA learning sites to coastal sites around the Baltic Sea in general. Specific objectives of this deliverable (D6.4) were to connect observed process rates with modelling data and ecosystem characteristics.

In the report we made statistical analyses of observations from BONUS COCOA study sites together with results from the Swedish Coastal zone Model (SCM). Eight structural variables (water depth, temperature, salinity, bottom water concentrations of oxygen, ammonium, nitrate and phosphate, as well as nitrogen content in sediment) were found common to both the experimentally determined and the model data sets. The observed process rate evaluated in this report was denitrification. In addition regressions were tested between observed denitrification rates and several structural variables (latitude, longitude, depth, light, temperature, salinity, grain class, porosity, loss of ignition, sediment organic carbon, total nitrogen content in the sediment,  sediment carbon/nitrogen-ratio, sediment chlorphyll-a as well as bottom water concentrations of oxygen, ammonium, nitrate, and dissolved inorganic  phosphorus and silicate) for pooled data from all learning sites.

The statistical results showed that experimentally determined multivariate data set from the shallow, illuminated stations was mainly found to be similar to the multivariate data set produced by the SCM model. Generally, no strong correlations of simple relations between observed denitrification and available structural variables were found for data collected from all the learning sites. We found some non-significant correlation between denitrification rates and bottom water dissolved inorganic phosphorous and dissolved silica but the reason behind the correlations is not clear.

We also developed and evaluated a theory to relate process rates to monitoring data and nutrient retention. The theoretical analysis included nutrient retention due to denitrification as well as burial of phosphorus and nitrogen. The theory of nutrient retention showed good correlations with model results. It was found that area-specific nitrogen and phosphorus retention capacity in a sub-basin depend much on mean water depth, water residence time, basin area and the mean nutrient concentrations in the active sediment layer and in the water column.

Publisher
p. 56
Series
RO, Report Oceanography, ISSN 0283-1112 ; 61
Keywords
Coastal zone, Eutrophication, Biogeochemistry, Nutrient retention
National Category
Oceanography, Hydrology and Water Resources
Research subject
Oceanography
Identifiers
urn:nbn:se:smhi:diva-4437 (URN)
Available from: 2017-12-04 Created: 2017-12-04 Last updated: 2018-01-13Bibliographically approved
Almroth-Rosell, E., Edman, M., Eilola, K., Meier, M. & Sahlberg, J. (2016). Modelling nutrient retention in the coastal zone of an eutrophic sea. Biogeosciences, 13(20), 5753-5769
Open this publication in new window or tab >>Modelling nutrient retention in the coastal zone of an eutrophic sea
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2016 (English)In: Biogeosciences, ISSN 1726-4170, E-ISSN 1726-4189, Vol. 13, no 20, p. 5753-5769Article in journal (Refereed) Published
National Category
Oceanography, Hydrology and Water Resources
Research subject
Oceanography
Identifiers
urn:nbn:se:smhi:diva-3491 (URN)10.5194/bg-13-5753-2016 (DOI)000385588600001 ()
Available from: 2016-11-15 Created: 2016-11-15 Last updated: 2018-01-13Bibliographically approved
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