MyLake—A multi-year lake simulation model code suitable for uncertainty and sensitivity analysis simulations

Saloranta, Tuomo; Andersen, Tom

doi:10.1016/j.ecolmodel.2007.03.018

Cited by 133 publications

(141 citation statements)

References 17 publications

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“…Mean freeze-up for the north was shown to shift 7, 8 and 11 days later (3, 10 and 30 m depths respectively) with shifts ranging from 0-15 days later, a smaller change than seen in break-up. These ranges are comparable to those identified by Dibike et al (2011), using the MyLake model (Saloranta and Anderson, 2007) to examine future changes over a broader and more southern area of North America. Ice cover durations ranged from 10 to more than 40 days shorter, with the areas of greatest change in scenario 1 located near the Alaskan coast, the far northern Arctic islands, and northern Quebec; while scenario 2 had the greatest changes in the north eastern section of the study area (the CAA and southern Baffin Island/northern Quebec).…”

Section: Discussionmentioning

confidence: 53%

The fate of lake ice in the North American Arctic

Brown

Duguay

2011

The Cryosphere

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Abstract. Lakes comprise a large portion of the surface cover in northern North America, forming an important part of the cryosphere. The timing of lake ice phenological events (e.g. break-up/freeze-up) is a useful indicator of climate variability and change, which is of particular relevance in environmentally sensitive areas such as the North American Arctic. Further alterations to the present day ice regime could result in major ecosystem changes, such as species shifts and the disappearance of perennial ice cover. The Canadian Lake Ice Model (CLIMo) was used to simulate lake ice phenology across the North American Arctic from 1961-2100 using two climate scenarios produced by the Canadian Regional Climate Model (CRCM). Results from the 1961-1990 time period were validated using 15 locations across the Canadian Arctic, with both in situ ice cover observations from the Canadian Ice Database as well as additional ice cover simulations using nearby weather station data. Projected changes to the ice cover using the 30-year mean data between 1961-1990 and 2041-2070 suggest a shift in break-up and freeze-up dates for most areas ranging from 10-25 days earlier (break-up) and 0-15 days later (freeze-up). The resulting ice cover durations show mainly a 10-25 day reduction for the shallower lakes (3 and 10 m) and 10-30 day reduction for the deeper lakes (30 m). More extreme reductions of up to 60 days (excluding the loss of perennial ice cover) were shown in the coastal regions compared to the interior continental areas. The mean maximum ice thickness was shown to decrease by 10-60 cm with no snow cover and 5-50 cm with snow cover on the ice. Snow ice was also shown to increase through most of the study area with the exception of the Alaskan coastal areas.

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Section: Discussionmentioning

confidence: 53%

The fate of lake ice in the North American Arctic

Brown

Duguay

2011

The Cryosphere

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“…Models are often related to each other. The MyLake model (Saloranta and Andersen 2007), for example, has characteristics that are also found in other lake models such as DYRESM-CAEDYM (Hamilton and Schladow 1997), MINLAKE (Riley and Stefan 1988), PROBE (Blenckner et al 2002) and BELAMO (Omlin et al 2001;Mieleitner and Reichert 2006). We aim for a more objective and in-depth analysis of a list of AEMs using a similarity index (for details on the analysis, see Online Resource 4 and for the data Online Resource 1, Datasheet 4).…”

Section: Documenting Diversity In Aemsmentioning

confidence: 99%

Exploring, exploiting and evolving diversity of aquatic ecosystem models: a community perspective

et al. 2015

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Here, we present a community perspective on how to explore, exploit and evolve the diversity in aquatic ecosystem models. These models play an important role in understanding the functioning of aquatic ecosystems, filling in observation gaps and developing effective strategies for water quality management. In this spirit, numerous models have been developed since the 1970s. We set off to explore model diversity by making an inventory among 42 aquatic ecosystem modellers, by categorizing the resulting set of models and by analysing them for diversity. We then focus on how to exploit model diversity by comparing and combining different aspects of existing models. Finally, we discuss how model diversity came about in the past and could evolve in the future. Throughout our study, we use Handling Editor: Piet Spaak.Electronic supplementary material The online version of this article (doi:10.1007/s10452-015-9544-1) contains supplementary material, which is available to authorized users. 123Aquat ) 49:513-548 DOI 10.1007 analogies from biodiversity research to analyse and interpret model diversity. We recommend to make models publicly available through open-source policies, to standardize documentation and technical implementation of models, and to compare models through ensemble modelling and interdisciplinary approaches. We end with our perspective on how the field of aquatic ecosystem modelling might develop in the next 5-10 years. To strive for clarity and to improve readability for non-modellers, we include a glossary.

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“…MyLake (MultiYear Lake) is a 1-D lake model code that simulates daily changes in physical and chemical dynamics over the depth gradient, including surface radiation balance, vertical light attenuation, vertical temperature and density profiles, ice and snow cover, and phosphorus exchange between suspended particles and water, as well as between water and sediment (Saloranta and Andersen 2007). The modelling principle is mostly based on MINLAKE (Riley and Stefan 1988) with some adjustments and additions.…”

Section: Mylakementioning

confidence: 99%

Challenges and opportunities for integrating lake ecosystem modelling approaches

et al. 2010

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A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: superindividual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.

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MyLake—A multi-year lake simulation model code suitable for uncertainty and sensitivity analysis simulations

Cited by 133 publications

References 17 publications

The fate of lake ice in the North American Arctic

The fate of lake ice in the North American Arctic

Exploring, exploiting and evolving diversity of aquatic ecosystem models: a community perspective

Challenges and opportunities for integrating lake ecosystem modelling approaches

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