| 1. |
- Dimberg, Peter H., 1985-, et al.
(författare)
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A Comparison Between Regression Models and Genetic Programming for Predictions of Chlorophyll-a Concentrations in Northern Lakes
- 2016
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Ingår i: Environmental Modelling and Assessment. - : Springer Science and Business Media LLC. - 1420-2026 .- 1573-2967. ; 21:2, s. 221-232
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Tidskriftsartikel (refereegranskat)abstract
- Chlorophyll-a (chl-a) concentrations are often used as a proxy for water quality problems as well as phytoplankton blooms. Available chl-a models range from simple phosphorus loading models to complex regression and dynamic models. A comparison of multiple regression models was made with genetic programming (GP) techniques to predict chl-a concentrations over a large range of 104 Swedish lakes. Independent variables used were lake area, mean depth, iron, latitude, ammonium, nitrogen + nitrate, pH, phosphate, secchi depth, silicon, temperature, total phosphorus, total nitrogen and total organic carbon. GP is a method based on the Darwinian evolution theory. This implies that a program will be able to test different mathematical equations, iterating and improving each equation using fundamental ideas from evolution theory to increase the predictive power. A good correspondence was found between the multiple regression and the GP modelling approach. No significant improvement of the predictive power was found using GP, and it is therefore recommended that multiple regression methods should be preferred when predicting chl-a concentrations as these models tend to be less complex and the modelling approach is easier to use. Results from GP were in some cases more accurate compared to multiple regressions; however, the best model was created by multiple regressions which used concentrations of total phosphorus, total nitrogen and latitude as independent variables. These findings will be an important note for limnologists and modelling managers when developing future models of chl-a concentrations in lakes.
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| 2. |
- Dimberg, Peter H., 1985-
(författare)
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Defining a new parameter for regression models with aggregated data in aquatic science
- 2014
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Ingår i: Environmetrics. - : Wiley. - 1180-4009 .- 1099-095X. ; 25:2, s. 97-106
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Tidskriftsartikel (refereegranskat)abstract
- In aquatic ecosystem analysis, it is common to create regression models of aggregated data. There are several published papers on regression models that produce high values for the coefficient of determination (r2) and low p-values but that have nevertheless failed to predict responses in individual lakes. There appears, therefore, to be a need for a descriptive parameter that can be used to determine the certainty in aggregated regression models. To explore the applicability of a new parameter, the aim of this study was to develop a new parameter to detect the reliability of aggregated data in regression analysis. This parameter was tested using three different examples of empirical data from Himmerfjärden bay (Sweden) and one example of 111 Swedish lakes. The results showed that even for a high r2 and a low p-value, it is possible that the aggregated data are too highly variable to make correct conclusions about causality. To investigate this, the new parameter should be used to indicate if r2 can demonstrate a causality relationship. However, if the parameter rejects r2 as valid, it does not mean that there is no causality; it indicates that the uncertainty in the aggregated data is too high to draw conclusions regarding causality. In such cases, more effort needs to be made to decrease uncertainty in the variables.
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| 3. |
- Dimberg, Peter H., 1985-, et al.
(författare)
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Predicted effects from abatement action against eutrophication in two small bays of the Baltic Sea
- 2014
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Ingår i: Environmental Earth Sciences. - : Springer Science and Business Media LLC. - 1866-6280 .- 1866-6299. ; 72:4, s. 1191-1199
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Tidskriftsartikel (refereegranskat)abstract
- The Baltic Sea has abnormal algal blooms during spring and summer which are effects of high concentrations of total phosphorus (TP) and other nutrients in the surface water. Björnöfjärden (BF), a coastal area connected to the Baltic Sea, is selected for investigating whether aluminium treatment of sediments may reduce TP concentrations in the water mass. The aim of this paper is to evaluate effects from different abatement actions in two bays, BF and Nyköpingsfjärden (NF). The four investigated scenarios are (1) no action, (2) reducing TP from local sources, (3) fixing TP in sediments with aluminium, and (4) decreasing TP concentrations in the outside sea. Magnitudes of different TP fluxes during the different scenarios were estimated using a dynamic mass balance model, CoastMab, which has previously been tested against data from Swedish coastal waters. Alternative actions such as aluminium treatment and reduction of TP from local sources would result in no or scant effect on the TP concentrations in the two bays according to model simulations. The only action which would result in a significant expected decrease in TP concentrations would be to decrease TP concentrations in the outside sea. It is concluded that BF and NF are not suitable for studying effects from local abatement action because of large TP fluxes from the outside sea.
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| 4. |
- Dimberg, Peter H., 1985-, et al.
(författare)
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Predicting median monthly chlorophyll-a concentrations
- 2013
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Ingår i: Limnologica. - : Elsevier. - 0075-9511 .- 1873-5851. ; 43:3, s. 169-176
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Tidskriftsartikel (refereegranskat)abstract
- Chlorophyll-a (Chl-a) is a plant pigment which is used in many environmental monitoring programs as a water quality indicator for lakes. However, monthly Chl-a data are often lacking in many monitored lakes as measurements are concentrated to certain periods of the year. This study investigates two methods of how monthly Chl-a medians can be predicted (i) new monthly regression models from median summer total phosphorus concentrations and latitude, (ii) and with monthly constants added to regression models from the literature. Data from 308 lakes were used and the trophic status of the lakes ranged from oligotrophic to hypertrophic, they were located from northern Sweden (Europe) to southern Florida (North America). These models may be useful for understanding the general Chl-a seasonality in lakes and for managing lakes in which Chl-a measurements are not made over the whole year.
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| 5. |
- Dimberg, Peter H., 1985-, et al.
(författare)
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Predicting Total Nitrogen, Total Phosphorus, Total Organic Carbon, Dissolved Oxygen and Iron in Deep Waters of Swedish Lakes
- 2015
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Ingår i: Environmental Modelling and Assessment. - : Springer Science and Business Media LLC. - 1420-2026 .- 1573-2967. ; 20:5, s. 411-423
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Tidskriftsartikel (refereegranskat)abstract
- In many lakes, the physical and chemical characteristics are monitored for surface waters but not for deep waters. Yet, deep waters may be important for understanding the dynamics of lake water chemistry variables over the year. In this study, multiple regression models have been created for five different variables, total phosphorus, total nitrogen, total organic carbon, dissolved oxygen (DO) and iron, in the deep water for 61 Swedish temperate or subarctic lakes. The investigated season was February to October, depending on the data availability. Regressions used the corresponding variables from the surface water as well as different morphometric parameters as independent variables. It was possible to construct meaningful models (r2 > 0.65; p < 0.05) for most of the variables and months. However, it was not possible to attain this criterion for some months regarding the DO concentration. Surface water concentrations were in general most important for predicting corresponding deep water concentrations. An exception was that during summer, DO differed considerably between surface waters and deep waters and voluminous lakes had particularly high DO concentrations in deep waters. No cross-systems relationship could be found between deepwater hypoxia and total phosphorus in deep waters during summer when phosphorus diffusion from sediments is most likely. A mass-balance modelling example was applied to illustrate the use of the produced models. These findings may provide a better understanding of the dynamics of these five variables in temperate or subarctic lakes.
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| 6. |
- Dimberg, Peter H., 1985-
(författare)
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Predictions Within and Across Aquatic Systems using Statistical Methods and Models
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Aquatic ecosystems are an essential source for life and, in many regions, are exploited to a degree which deteriorates their ecological status. Today, more than 50 % of the European lakes suffer from an ecological status which is unsatisfactory. Many of these lakes require abatement actions to improve their status, and mathematical models have a great potential to predict and evaluate different abatement actions and their outcome. Several statistical methods and models exist which can be used for these purposes; however, many of the models are not constructed using a sufficient amount or quality of data, are too complex to be used by most managers, or are too site specific. Therefore, the main aim of this thesis was to present different statistical methods and models which are easy to use by managers, are general, and provide insights for the development of similar methods and models.To reach the main aim of the thesis several different statistical and modelling procedures were investigated and applied, such as genetic programming (GP), multiple regression, Markov Chains, and finally, well-used criteria for the r2 and p-value for the development of a method to determine temporal-trends. The statistical methods and models were mainly based on the variables chlorophyll-a (chl-a) and total phosphorus (TP) concentrations, but some methods and models can be directly transferred to other variables.The main findings in this thesis were that multiple regressions overcome the performance of GP to predict summer chl-a concentrations and that multiple regressions can be used to generally describe the chl-a seasonality with TP summer concentrations and the latitude as independent variables. Also, it is possible to calculate probabilities, using Markov Chains, of exceeding certain chl-a concentrations in future months. Results showed that deep water concentrations were in general closely related to the surface water concentrations along with morphometric parameters; these independent variables can therefore be used in mass-balance models to estimate the mass in deep waters. A new statistical method was derived and applied to confirm whether variables have changed over time or not for cases where other traditional methods have failed. Finally, it is concluded that the statistical methods and models developed in this thesis will increase the understanding for predictions within and across aquatic systems.
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| 7. |
- Dimberg, Peter H., 1985-, et al.
(författare)
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Probabilities of monthly median chlorophyll-a concentrations in subarctic, temperate and subtropical lakes
- 2013
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Ingår i: Environmental Modelling & Software. - : Elsevier. - 1364-8152 .- 1873-6726. ; 41, s. 199-209
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Tidskriftsartikel (refereegranskat)abstract
- High concentrations of chlorophyll-a (chl-a) during summer are by definition a common problem in eutrophicated lakes. Several models have been designed to predict chl-a concentrations but are unable to estimate the probability of predicted concentrations or concentration spans during subsequent months. Two different methods were developed to compute the probabilities of obtaining a certain chl-a concentration. One method is built on discrete Markov chains and the other method on a direct relationship between median chl-a concentrations from two months. Lake managers may use these methods to detect and counteract the risk of high chl-a concentrations and algal blooms during coming months. Both methods were evaluated and applied along different scenarios to detect the probability to exceed chl-a concentration in different coming months. The procedure of computing probabilities is strictly based on general statistics which means that neither method is constrained for chl-a but can also be used for other variables. A user-friendly software application was developed to facilitate and extend the use of these two methods.
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| 8. |
- Dimberg, Peter H., 1985-, et al.
(författare)
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Quantifying Water Retention Time in Non-tidal Coastal Waters Using Statistical and Mass Balance Models
- 2014
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Ingår i: Water, Air and Soil Pollution. - : Springer Science and Business Media LLC. - 0049-6979 .- 1573-2932. ; 225:2020
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Tidskriftsartikel (refereegranskat)abstract
- The water retention time (sometimes called residence time) in coastal areas is an indicator of coastal hydrodynamics which can be used to quantify the local transportation of dissolved and suspended pollutants. This study has used dynamic and statistical models to explore what governs the water retention time in non-tidal coastal waters of the Baltic Sea. If freshwater input divided by the cross-section area between the coastal water and the sea was below a certain threshold, freshwater had no notable impact on the retention time. Moreover, statistical models were developed for predicting surface water retention time and total water retention time from coastal water volume, cross-section area and freshwater discharge. This study can be useful for managers who need to determine where abatement measures should be focused in order to be as effective as possibly against coastal water pollution.
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