Applicability of a one-dimensional coupled ecological-hydrodynamic numerical model to future projections in a very deep large lake (Lake Maggiore, Northern Italy/Southern Switzerland)

Fenocchi, Andrea; Rogora, Michela; Morabito, Giuseppe; Marchetto, Aldo; Sibilla, Stefano; Dresti, Claudia

doi:10.1016/j.ecolmodel.2018.11.005

Cited by 34 publications

(20 citation statements)

References 55 publications

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“…The GUI allows for a high level of interoperability due to the option of combining with other operating systems. This includes the coupling of GLM with ecological lake models (e.g., Snortheim et al, 2017;Robertson et al, 2018;Weber et al, 2017;Fenocchi et al, 2019), as the toolbox is already applicable for this purpose and can be the basis for establishing a coupling interface. Furthermore, we designed the software with the aim of a high flexibility for the application of other scenarios, for various study areas, or with diverse time steps.…”

Section: Discussionmentioning

confidence: 99%

“…GLM is able to simulate the thermal dynamics of lakes in their temporal and spatial (vertical) characteristics. The model code is open source and applied in numerous studies to a broad variety of different lakes and research questions (e.g., Bueche et al, 2017;Bucak et al, 2018;Bruce et al, 2018;Fenocchi et al, 2017Fenocchi et al, , 2018Fenocchi et al, , 2019Robertson et al, 2018;Ladwig et al, 2018;Mi et al, 2018). Carey and Gougis (2017) present the usage of GLM beyond the research application by incorporating it into a teaching tool for students.…”

Section: Introductionmentioning

confidence: 99%

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glmGUI v1.0: an R-based graphical user interface and toolbox for GLM (General Lake Model) simulations

Bueche¹,

Wenk²,

Poschlod³

et al. 2020

Geosci. Model Dev.

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Abstract. Numerical modeling provides an opportunity to quantify the reaction of lakes to alterations in their environment, such as changes in climate or hydrological conditions. The one-dimensional hydrodynamic General Lake Model (GLM) is an open-source software and widely used within the limnological research community. Nevertheless, no interface to process the input data and run the model and no tools for an automatic parameter calibration yet exist. Hence, we developed glmGUI, a graphical user interface (GUI) including a toolbox for an autocalibration, parameter sensitivity analysis, and several plot options. The tool is provided as a package for the freely available scientific code language R. The model parameters can be analyzed and calibrated for the simulation output variables water temperature and lake level. The glmGUI package is tested for two sites (lake Ammersee, Germany, and lake Baratz, Italy), distinguishing size, mixing regime, hydrology of the catchment area (i.e., the number of inflows and their runoff seasonality), and climatic conditions. A robust simulation of water temperature for both lakes (Ammersee: RMSE =1.17 ∘C; Baratz: RMSE =1.30 ∘C) is achieved by a quick automatic calibration. The quality of a water temperature simulation can be assessed immediately by means of a difference plot provided by glmGUI, which displays the distribution of the spatial (vertical) and temporal deviations. The calibration of the lake-level simulations of lake Ammersee for multiple hydrological inputs including also unknown inflows yielded a satisfactory model fit (RMSE =0.20 m). This shows that GLM can also be used to estimate the water balance of lakes correctly. The tools provided by glmGUI enable a less time-consuming and simplified parameter optimization within the calibration process. Due to this, i.e., the free availability and the implementation in a GUI, the presented R package expands the application of GLM to a broader field of lake modeling research and even beyond limnological experts.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

glmGUI v1.0: an R-based graphical user interface and toolbox for GLM (General Lake Model) simulations

Bueche¹,

Wenk²,

Poschlod³

et al. 2020

Geosci. Model Dev.

View full text Add to dashboard Cite

show abstract

“…This includes the coupling of GLM with ecological lake models (e.g. Snortheim et al, 2017;Robertson et al, 2018;Weber et al, 2017;Fenocchi et al, 2019), as the toolbox already works for this purpose and can be the basis for a development of a coupling interface. An increasing number of lake modeling studies are investigating the impact of global change on lakes using as meteorological input data regional climate model output or future scenarios (Fenocchi et al, 2018;Weinberger and Vetter, 2014;Bueche and Vetter, 2015;Ladwig et al, 2018;Pietikäinen et al, 2018;Piccolroaz and Toffolon, 2018).…”

Section: The Development Of Glmgui For the Free And Open-source Progrmentioning

confidence: 99%

“…GLM is able to simulate the thermal dynamics of lakes in their temporal and spatial (vertical) characteristics. The model code is open-source and applied in numerous studies to a broad variety of different lakes 10 and irrogations (e.g., Bueche et al, 2017;Bucak et al, 2018;Bruce et al, 2018;Fenocchi et al, 2018;Robertson et al, 2018;Ladwig et al, 2018;Mi et al, 2018;Fenocchi et al, 2017;Fenocchi et al, 2019). Carey and Gougis (2017) present the usage of GLM beyond the research application incorporated in a teaching tool for students.…”

mentioning

confidence: 99%

glmGUI v1.0: an R-based Geographical User Interface and toolbox for GLM (General Lake Model) simulations

Bueche¹,

Wenk²,

Poschlod³

et al. 2019

Preprint

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Abstract. Numerical modeling provides the opportunity to quantify the reaction of lakes on alterations in their environment, such as changes in climate or hydrological conditions. The one-dimensional hydrodynamic General Lake Model (GLM) is an open-source software and widely used within the limnological research community. Nevertheless, neither an interface to process the input data and run the model, nor tools for an automatic parameter calibration exist. Hence, we developed glmGUI, a Geographical User Interface (GUI) including a toolbox for an autocalibration, parameter sensitivity analysis, and several plot options. The tool is provided as a package for the freely available scientific code language R. The model parameters can be analyzed and calibrated for the simulation output variables water temperature and lake level. The glmGUI package is tested for two sites (Lake Ammersee, Germany, and Lake Baratz, Italy) distinguishing in size, mixing regime, hydrology of the catchment area (i.e. the number of inflows and their runoff seasonality), and climatic conditions. A robust simulation of water temperature for both lakes (Ammersee: RMSE = 1.17 °C, Baratz: RMSE = 1.30 °C) is achieved by a quick automatic calibration. The quality of a water temperature simulation can be assessed immediately by a difference plot provided by glmGUI, which displays the distribution of the spatial (vertical) and temporal deviations. The calibration of the lake level simulations of Lake Ammersee for multiple hydrological inputs including also unknown inflows yielded a satisfactory model fit (RMSE = 0.20 m). This shows that GLM can be also used to estimate the water balance of lakes correctly. The tools provided by glmGUI enable a less time-consuming and simplified parameter optimization within the calibration process. Due to this, the free availability and the implementation in a GUI, the presented R package expands the application of GLM to a broader field of lake modeling research and even beyond limnological experts.

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“…Modeling river environment and ecology, such as flow speed, water surface elevation, water quality, sediment transport, and aquatic species population, is a complicated problem whose resolution requires multidimensional coupled models in general 14,15 . They are versatile but often inefficient.…”

Section: Introductionmentioning

confidence: 99%

A hybrid stochastic river environmental restoration modeling with discrete and costly observations

Yoshioka

Tsujimura

Hamagami

et al. 2020

Optim Control Appl Methods

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Summary A recent river environmental restoration problem is approached from a standpoint of stochastic control of hybrid regime‐switching diffusion processes with discrete and costly observations. This setting harmonizes with real problems because continuously obtaining environmental and ecological information is difficult, and is often costly. The main problem is to decide when and how much of the sediment should be supplied into a river environment to effectively suppress bloom of benthic algae. The interventions are allowed only at observation times. Finding the optimal river restoration policy ultimately reduces to solving an optimality equation in an unconventional form due to the observation cost and discrete observations. We show its unique solvability and present a connection with degenerate parabolic partial differential equations, with which we can construct an effective algorithm for its approximation. An uncertainty‐averse optimization problem is also considered as an advanced problem. Coefficients and parameter values are identified from experimental and observation results to numerically compute the optimal restoration policy of an existing river environment with and without uncertainty.

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Applicability of a one-dimensional coupled ecological-hydrodynamic numerical model to future projections in a very deep large lake (Lake Maggiore, Northern Italy/Southern Switzerland)

Cited by 34 publications

References 55 publications

glmGUI v1.0: an R-based graphical user interface and toolbox for GLM (General Lake Model) simulations

glmGUI v1.0: an R-based graphical user interface and toolbox for GLM (General Lake Model) simulations

glmGUI v1.0: an R-based Geographical User Interface and toolbox for GLM (General Lake Model) simulations

A hybrid stochastic river environmental restoration modeling with discrete and costly observations

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