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  • 1.
    Abrahamsson, Otto
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences.
    Håkanson, Lars
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences.
    Modelling seasonal flow variability of European rivers1998In: Ecological Modelling, ISSN 0304-3800, E-ISSN 1872-7026, Vol. 114, no 1, p. 49-58Article in journal (Refereed)
    Abstract [en]

    River discharge influences many important processes in a lake ecosystem. For example, the tributary discharge is one of the major regulating factors for the lake water retention time and, hence, the retention of substances in lake water. However, river discharge depends on many more or less stochastic processes, which makes it difficult to give a reliable prediction of the discharge for a specific river at a given time. This paper presents an attempt to overcome many of those difficulties with a simple mathematical model. The model was designed to meet some specific demands for ecosystem modelling of contaminating substances. The most important of those requirements is that the model had to be based on readily available driving variables, preferably from standard maps. The presented results are based on extensive calibrations and validations using empirical data on monthly water discharge from more than 200 European rivers. It may be concluded that this model yields predictions that capture the essential components in mean monthly variations in river discharge in European rivers and that this model is driven by easily available driving variables like catchment area, mean annual precipitation, altitude, and latitude. The technique to obtain seasonal variability is based on calibrated ‘norms’ and smoothing functions defined from the driving variables.

  • 2.
    Abrahamsson, Otto
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences.
    Håkanson, Lars
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences.
    Presentation and analysis of a model simulating the response of potash treatment of lakes1997In: Journal of Environmental Radioactivity, ISSN 0265-931X, E-ISSN 1879-1700, Vol. 37, no 3, p. 287-306Article in journal (Refereed)
    Abstract [en]

    The potassium concentration in a lake may influence the caesium levels in lake biota. The biouptake and potential ecosystem effects of a caesium fall-out can be limited by addition of potassium, for example, by a potash treatment. This work presents for the first time a simple and practically useful model to facilitate the planning and to predict the outcome of potash treatments by simulating the processes that regulate the water chemical response of such a treatment. The model is a mixed model in the sense that it contains both statistical regressions and dynamic interactions within a lake ecosystem. This paper focuses on the dynamic processes and gives both calibrations and extensive validations of the model. A few examples on the practical use of the model are presented. The results indicate that the model, using only easily accessible input data, can, in fact, give good predictions on the increase and duration in potassium concentration following a potash treatment.

  • 3. Brittain, J
    et al.
    Håkanson, L
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences.
    Gallego, E
    Target ecosystems, key fish species, dose to biota and the impact and feasibility of countermeasures in aquatic systems2000In: ENEA, ISSN 1120-5555, p. 23-48Article in journal (Refereed)
  • 4.
    Bryhn, Andreas C.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Air and Water Science.
    Håkanson, Lars
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Air and Water Science.
    A comparison of predictive phosphorus load-concentration models for lakes2007In: Ecosystems (New York. Print), ISSN 1432-9840, E-ISSN 1435-0629, Vol. 10, no 7, p. 1084-1099Article in journal (Refereed)
    Abstract [en]

    Lake models that predict phosphorus (P) concentrations from P-loading have provided important knowledge enabling successful restoration of many eutrophic lakes during the last decades. However, the first-generation (static) models were rather imprecise and some nutrient abatement programs have therefore produced disappointingly modest results. This study compares 12 first-generation models with three newer ones. These newer models are dynamic (time-dependent), and general in the sense that they work without any further calibration for lakes from a wide limnological domain. However, static models are more accessible to non-specialists. Predictions of P concentrations were compared with empirical long-term data from a multi-lake survey, as well as to data from transient conditions in six lakes. Dynamic models were found to predict P concentrations with much higher certainty than static models. One general dynamic model, LakeMab, works for both deep and shallow lakes and can, in contrast to static models, predict P fluxes and particulate and dissolved P, both in surface waters and deep waters. PCLake, another general dynamic model, has advantages that resemble those of LakeMab, except that it needs three or four more input variables and is only valid for shallow lakes.

  • 5.
    Bryhn, Andreas C.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences.
    Håkanson, Lars
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences.
    Coastal eutrophication: whether N and/or P should be abated depends on the dynamic mass balance2009In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 106, no 1, p. E3-E3Article in journal (Refereed)
  • 6.
    Bryhn, Andreas C.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Air and Water Science.
    Håkanson, Lars
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Air and Water Science.
    Eklund, Jenny
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences.
    Variabilities and uncertainties in key coastal water variables as a basis for understanding changes and obtaining predictice power in modelling2008In: Vatten, ISSN 0042-2886, Vol. 64, p. 259-272Article in journal (Refereed)
    Abstract [en]

    The focus of this work is on general patterns in uncertainty as well as temporal and spatial variability in keywater variables in coastal science and management. These patterns are essential since they regulate how manysamples must be taken to get reliable mean or median values characterising coastal water quality and whichvariables are most suitable for monitoring and predictive modelling. We present results concerning coefficientsof variation, correlations, regressions, variations in data from different time periods, and confidence intervalsfor empirical mean values. We use data from Ringkøbing Fjord (Denmark, N. Europe), Chesapeake Bay(Eastern U.S.) and other coastal marine sites to illustrate the basic principles related to patterns in variability.We have shown that total and particulate N and P generally have much lower coefficients of variability (CV)than dissolved inorganic nutrient fractions. The latter are, hence, of limited use in predictive models for coastalmanagement. Total nitrogen (N) and phosphorus (P) were, on the other hand, found to be useful predictors oftwo standard bioindicators, the Secchi depth (a measure of water clarity) and chlorophyll-a concentrations(a measure of phytoplankton biomass or production)

  • 7.
    Bryhn, Andreas C.
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVAL.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVAL.
    Eklund, Jenny M.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVAL.
    Variabilities and uncertainties in management-related coastal water variables.: Deliverable D2.3.3.2007Report (Other scientific)
  • 8.
    Bryhn, Andreas
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. LUVAL.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. LUVAL.
    Bekämpa Östersjöns övergödning med reningsverk i Polen.2008Other (Other (popular scientific, debate etc.))
  • 9. Carstensen, J.
    et al.
    Hernandez-Garcia, E.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVA.
    Terminology list for threshold modelling, identification and uncertainty evaluation.: Deliverable D2.4.1.2006Report (Other scientific)
  • 10. Dahl, Magnus
    et al.
    Wilson, David I.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVA.
    A combined suspended particle and phosphorus water quality model: Application to Lake Vänern.2006In: Ecological Modelling, Vol. 190, p. 55-71Article in journal (Refereed)
  • 11.
    Gyllenhammar, Andreas
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science.
    Environmental consequence analyses of fish farms emissions related to different scales and exemplified by data from the Baltic – a review.2005In: Marine Environmental Research, Vol. 60, p. 211-243Article in journal (Refereed)
  • 12.
    Gyllenhammar, Andreas
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVA.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVA.
    Integrated management of Lake Kyoga natural resources. Final report.2006Report (Other scientific)
  • 13. Hofman, D.
    et al.
    Monte, L.
    Brittain, J.
    Boyer, P.
    Donchys, G.
    Gallego, E.
    Gheorghiu, D.
    Heling, R.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVA.
    Kerekes, A.
    Kocsy, G.
    Lepicard, S.
    Mirzeabassov, O.
    Smith, J.
    van der Perk, M.
    Pecha, P.
    Mieczyslaw, B.
    Slavik, O.
    Yatsalo, B.
    Zheleznyak, M.
    EC computer systems in the field of hydrological dispersion modelling and aquatic radioecological research: state of the art, end-user experiences and recommendations for improvements2005In: Evaluation and nertwork of EC-decision support systems in the field of hydrological dispersion models and of aquatic radioecological research: Assessment of environmenal models and software., 2005, p. 203-323Chapter in book (Refereed)
  • 14. Holmer, Marianne
    et al.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVAL.
    Aquaculture and eutrophication.2008In: Assessment of climate change for the Baltic Sea basin by The BACC Author Team, Springer, Heidelberg , 2008, p. 420-423Chapter in book (Refereed)
  • 15.
    Håkanson, L
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences.
    The derivation and use of a dynamic model for mercury in lake fish based on a static (regression) model2000In: Water, Air, & Soil Pollution, ISSN 0049-6979, Vol. 124, p. 301-317Article in journal (Refereed)
  • 16.
    Håkanson, L
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences.
    The role of characteristic coefficients of variation in uncertainty and sensitivity analyses, with examples related to the structuring of lake eutrophication models2000In: Ecological Modelling, ISSN 0304-3800, Vol. 131, p. 1-20Article in journal (Refereed)
  • 17.
    Håkanson, L
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences.
    Andersson, M
    Rydén, L
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences.
    The Baltic Sea Basin: Nature, History and Economy2003In: Environmental Science, The Baltic University Press, Uppsala , 2003, p. 92-199Chapter in book (Refereed)
  • 18.
    Håkanson, L
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences.
    Boulion, V.V
    A general dynamic model to predict biomass and production of phytoplankton in lakes.2003In: Ecol. Modelling, Vol. 165, p. 285-301Article in journal (Refereed)
  • 19.
    Håkanson, L
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. AIR AND WATER SCIENCE.
    Boulion, V.V
    A model to predict how individual factors influence Secchi depth variations among and within lakes.2003In: Internat. Rev. Hydrobiol.,, Vol. 88, p. 212-232Article in journal (Refereed)
  • 20.
    Håkanson, L
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences.
    Boulion, V.V
    Empirical and dynamical models to predict the cover, biomass and production of macrophytes in lakes2002In: Ecol. Modelling, 151:213-243Article in journal (Refereed)
  • 21.
    Håkanson, L
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. AIR AND WATER SCIENCE.
    Boulion, V.V
    Modelling production and biomasses of herbivorous and predatory zooplankton in lakes.2003In: Ecol. Modelling, Vol. 161, p. 1-33Article in journal (Refereed)
  • 22.
    Håkanson, L
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. AIR AND WATER SCIENCES.
    Boulion, V.V
    Modelling production and biomasses of prey and predatory fish in lakes.2004In: Hydrobiologia, Vol. 511, p. 125-150Article in journal (Refereed)
  • 23.
    Håkanson, L
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. AIR AND WATER SCIENCE.
    Boulion, V.V
    Modelling production and biomasses of zoobenthos in lakes.2003In: Aqua. Ecol.,, Vol. 37, p. 277-306Article in journal (Refereed)
  • 24.
    Håkanson, L
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences.
    Boulion, V.V
    Regularities in primary production, Secchi depth and fish yield and a new system to define trophic and humic state indices for aquatic ecosystems.2000In: Proc. ASLO Meeting, 5-8 June 2000, Copenhagen., 2000Conference paper (Refereed)
  • 25.
    Håkanson, L
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences.
    Boulion, V.V
    The Lake Foodweb - modelling predation and abiotic/biotic interactions.2002Book (Refereed)
  • 26.
    Håkanson, L
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences.
    Fernandez, J.A
    A mechanistic sub-model for potassium influences on radiocesium uptake in aquatic biota.2001In: J. Env. Radioactivity, no 54, p. 345-360Article in journal (Refereed)
  • 27.
    Håkanson, L
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences.
    Gallego, E
    Rios-Insua, S
    The application of the lake ecosystem index in multi-attribute decision analysis in radioecology2000In: J. Env. Radioactivity, ISSN 0265-931X, Vol. 49, p. 319-344Article in journal (Refereed)
  • 28.
    Håkanson, L
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences.
    Jansson, M
    Principles of Lake Sedimentology, 2nd ed.2002Book (Refereed)
  • 29.
    Håkanson, L
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences.
    Parparov, A
    Hambright, K D
    Modelling the impact of water level fluctuations on water quality (suspended particulate matter) in Lake Kinneret, Israel2000In: Ecological Modelling, ISSN 0304-3800, Vol. 128, p. 101-125Article in journal (Refereed)
  • 30.
    Håkanson, L
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences.
    Sazykina, T
    A test of the MOIRA lake model for radiocesium for Lake Uruskul, Russia, contaminated by fallout from the Kyshtym accident in 19572000Report (Other scientific)
  • 31.
    Håkanson, L
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences.
    Sazykina, T G
    Kryshev, I I
    Modelling radionuclides in lakes2002In: ENEA, ISSN 1120-5555, Vol. 28, p. 13-49Article in journal (Refereed)
  • 32.
    Håkanson, Lars
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Air and Water Science.
    A data reduction exercise to detect threshold samples for regression models to predict key water variables2007In: International review of hydrobiology, ISSN 1434-2944, E-ISSN 1522-2632, Vol. 92, no 1, p. 84-97Article in journal (Refereed)
    Abstract [en]

    Inherent uncertainties in empirical data limit our understanding of interrelationships among variables and constrain our possibilities to identify critical thresholds as well as our possibilities to develop practically useful predictive models for water management. This work concerns key water variables for water management and the first aim is to utilize a very comprehensive set of data set for Ringkobing Fjord, Denmark. The paper first presents the methods and data used, then a reference regression for chlorophyll, coefficients of variation (CV = SD/MV; MV = mean value; SD = standard deviation) for a variety of water variables and how these CV-values influence n, the number of data used to determine coastal area characteristic mean or median values (note that the interest here is not on the conditions in sampling bottle but on the conditions in entire coastal areas, the ecosystem perspective). The main part of the work presents a data reduction exercise including a definition of an error function where the focus is on "large N", i.e., the number of data in a regression. The results are summarized in a diagram relating the error in the regression to different water variables with different inherent CVs in rivers, lakes and coastal areas. Given the inherently high CV-values of many of these water variables, more samples than generally taken in most regular monitoring programs are needed if scientific unassailable conclusions are to be made concerning interrelationships among the variables and to produce scientifically meaningful information to detect critical ecosystem changes and threshold values.

  • 33.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVA.
    A dynamic model for suspended particulate matter (SPM) in rivers.2006In: Global Ecol. Biogeogr., no 15, p. 93-107Article in journal (Refereed)
  • 34.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVA.
    A new dynamic model for suspended particulate matter (SPM) in lakes2005In: Internat. Rev. Hydrobiol., Vol. 90, p. 603-636Article in journal (Refereed)
  • 35.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVAL.
    A review of uncertainties in empirical data for operational effect variables and abiotic variables including thresholds for predictive power and practical use.: Deliverable D2.3.2.2007Report (Other scientific)
  • 36.
    Håkanson, Lars
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Air and Water Science.
    A revised dynamic model for suspended particulate matter (SPM) in coastal areas2006In: Aquatic geochemistry, ISSN 1380-6165, E-ISSN 1573-1421, Vol. 12, no 4, p. 327-364Article in journal (Refereed)
    Abstract [en]

    This paper presents a general, process-based model for suspended particulate matter (SPM) in defined coastal areas (the ecosystem scale). The model is based on ordinary differential equations and the calculation time (dt) is 1 month to reflect seasonal variations. The model has been tested using data from 17 Baltic coastal areas of different character and shown to predict mean monthly SPM-concentrations in water and Secchi depth (a measure of water clarity) very well (generally within the uncertainty bands given by the empirical data). The model is based on processes regulating inflow, outflow and internal fluxes. The separation between the surface-water layer and the deep-water layer is not done in the traditional manner from water temperature data but from sedimentological criteria (from the wave base which regulates where wind/wave-induced resuspension occurs). The model calculates the primary production of SPM (within the coastal areas), resuspension, sedimentation, mixing, mineralization and retention of SPM. The SPM-model is simple to apply in practice since all driving variables may be readily accessed from maps or regular monitoring programs. The model has also been extensively tested by means of sensitivity and uncertainty tests and the most important factor regulating model predictions of SPM-concentrations in coastal water is generally the value used for the SPM-concentration in the sea outside the given coastal area. The obligatory driving variables include four morphometric parameters (coastal area, section area, mean and maximum depth), latitude (to predict surface water and deep water temperatures, stratification and mixing), salinity, chlorophyll and the Secchi depth or SPM-concentration in the sea outside the given coastal area. Many of the structures in the model are general and could potentially be used for coastal areas other than those included in this study, e.g., for open coasts, estuaries or areas influenced by tidal variations.

  • 37.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVA.
    Changes to lake ecosystem structure resulting from fish cage farm emissions.2005In: Lakes & Reservoirs: Research and Management, Vol. 10, p. 71-80Article in journal (Refereed)
  • 38.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science.
    Dagens fiskeripolitik leder till katastrof.2006Other (Other (popular scientific, debate etc.))
  • 39.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVAL.
    Djupt enfaldig plan för Östersjön. UNT-debatt, 2007-11-28.2007Other (Other (popular scientific, debate etc.))
  • 40.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVA.
    Extended worksheets for case-study areas and variables, including sampling frequency, number of sites and analyzed variables -– a general protocol including methodological aspects related to variations and uncertainties in empirical data needed to run and validate predictive models in coastal management.: Deliverable D2.3.1.2006Report (Other scientific)
  • 41.
    Håkanson, Lars
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.
    Factors and criteria to quantify coastal area sensitivity/vulnerability to eutrophication: Presentation of a sensitivity index based on morphometrical parameters2008In: International review of hydrobiology, ISSN 1434-2944, E-ISSN 1522-2632, Vol. 93, no 3, p. 372-388Article in journal (Refereed)
    Abstract [en]

    There are major differences in sensitivity or vulnerability to anthropogenic loading of nutrients (eutrophication) among different coastal areas. The aim of this work is to discuss criteria for coastal area sensitivity and to present a sensitivity index (SI). This index is based on two morphometric parameters, which can be determined from simple bathymetric maps. (1) The topographical openness (or exposure) and (2) the dynamic ratio of the coastal area. The exposure is defined by the ratio between the section area of the coast and the enclosed coastal area. The boundaries of the coastal area should not be defined in an arbitrary manner but according to the topographical bottleneck method so that the exposure attains a minimum value. The exposure regulates the theoretical water retention time, which, in turn, regulates the effects of a given nutrient loading. The dynamic ratio is defined by the ratio between the square root of the coastal area and the mean depth. The dynamic ratio influences many fundamental internal transport processes. Coastal management should focus remedial actions on critical coastal areas which are at hand if the nutrient loading is high and/or the sensitivity is high. Testing the sensitivity index using a comprehensive data set including 478 coastal areas from the Baltic Sea. There were 2 (0.4%) extremely sensitive coastal areas (SI > ; 50), 50 (10.5%) very sensitive coastal areas (10 < , SI < , 50), 121 (25.3%) sensitive coastal areas (5 < , SI < , 10), 301 (63.0%) low sensitive coastal areas (1 < , SI < , 5) and 4 (0.8%) not sensitive coastal areas (SI < , 1).

  • 42.
    Håkanson, Lars
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences.
    Factors and criteria to quantify the bioproduction potential of coastal areas and presentation of a simple operational Index of Biological Value (IBV) for coastal management2009In: The Open Marine Biology Journal, ISSN 1874-4508, Vol. 3, p. 6-15Article in journal (Refereed)
    Abstract [en]

    There are major differences in the bioproduction potential of different coastal areas. The aim of this work is to review and discuss simple, operational criteria related to the bioproduction potential of coastal areas and to present and motivate an Index of Biological Value (IBV) for coastal management. This index is based on two key variables, which can be determined easily from bathymetric maps and data from standard monitoring programs: (1) the bottom area of the coast above the Secchi depth and (2) the topographical openness (or exposure) of the coastal area. The exposure is defined by the ratio between the section area of the coast and the enclosed coastal area. The boundaries of the coastal area should not be defined in an arbitrary manner but according to the topographical bottleneck method so that the exposure attains a minimum value. IBV is meant to be used to identify coastal areas with a high production potential so that preservation plans and remedial actions can be directed to such areas in a cost-efficient manner. Applying the index using a dataset including 478 coastal areas from the Baltic Sea, there were 5 (1%) extremely productive coastal areas (IBV > 50), 43 (9%) very productive coastal areas (25 < IBV < 50), 209 (43.7%) productive coastal areas (10 < IBV < 25), 214 (63.0%) moderately productive coastal areas (1 < IBV < 10) and 7 (1.5%) low-productive coastal areas (IBV < 1).

  • 43.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science.
    Helhetssyn krävs för fisket.2006Other (Other (popular scientific, debate etc.))
  • 44.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVAL.
    Kvävereningen är ansvarslös.: UNT-Debatt, 2004-04-182008Other (Other (popular scientific, debate etc.))
  • 45.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVA.
    Lake environments.: Chapter 42007In: Environmental Sedimentology, Blackwell Publishing,Oxford, , 2007, p. 109-143Chapter in book (Refereed)
  • 46.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVA.
    Lakes – form and function.2004Book (Refereed)
  • 47.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVA.
    Protocols and motivations for selected operational effect variables to be generally used to address problems and realisitc remedial measures for coastal eutrophication.: Deliverable 2.5.1.2006Report (Other scientific)
  • 48.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVA.
    Radioaktiva ämnen i insjöfisk – förändringar i tiden.2006In: Strålskyddsnytt, no 1, p. 26-28Article in journal (Refereed)
  • 49.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVA.
    Report on classification of coastal zones.: Deliverable D6.2.1.2006Report (Other scientific)
  • 50.
    Håkanson, Lars
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Air and Water Science. LUVA.
    Suspended particulate matter in lakes, rivers and marine systems.2006Book (Refereed)
123 1 - 50 of 103
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