Eutrophication modelling of reservoirs in Taiwan

Kuo, J.B.; Lung, Wu‐Seng; Yang, Chenming; Liu, Wen‐Cheng; Yang, Ming‐Der; Tai-shan, Tang

doi:10.1016/j.envsoft.2005.03.006

Cited by 85 publications

(30 citation statements)

References 18 publications

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“…The calibrated kinetic coefficients and constants for the water quality simulation for the Yongdam reservoir are listed in Table 7.1. The values are consistent with those given in the literature for similar studies (Bowie et al, 1985;Cole and Buchak, 1995;Kuo et al, 2006). The reason for using some of the validated values of coefficients is that the uncertainty induced by the schematization of the geometiy for the reservoir including data acquisition may be much larger than that due to the lack of knowledge of the parameters.…”

Section: Water Quality Modellingsupporting

confidence: 80%

Eco-hydraulic Modelling of Eutrophication for Reservoir Management

Jung¹

2010

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Section: Water Quality Modellingsupporting

confidence: 80%

Eco-hydraulic Modelling of Eutrophication for Reservoir Management

Jung¹

2010

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“…The model is an opensource code written in FORTRAN. It has been used extensively throughout the United States (e.g., Deliman and Gerald 2002;Bowen and Hieronymous 2003;Debele et al 2006) and elsewhere in the world (e.g., Chung and Oh 2006;Kuo et al 2006Kuo et al , 2007 as a management and research tool, particularly for studying the nutrient and sediment dynamics of reservoirs and river impoundments. The model has also been used to drive models of food web dynamics (Saito et al 2001) and to support the studies of fish habitat (Sullivan et al 2003).…”

Section: Ce-qual-w2mentioning

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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“…Based on traditional techniques, calibration parameters of complex water quality models has been identified through a trial-and-error calibration procedure, which is often subjective, inefficient, and time consuming process. In most previous studies on calibration of CE-QUAL-W2, the goodnessof-fit of the calibrated model is generally based on a visual judgment by comparing the simulated and the field data (Baker and Dycus 2004;Nielsen 2005;Sullivan and Round 2005;Kuo et al 2006;Chung and Oh 2006;Gelda and Effler 2007;Diogo et al 2008;Liu et al 2008;Afshar and Saadatpour 2009;Etemad-Shahidi et al 2009). …”

Section: Introductionmentioning

confidence: 99%

Particle Swarm Optimization for Automatic Calibration of Large Scale Water Quality Model (CE-QUAL-W2): Application to Karkheh Reservoir, Iran

Afshar

Kazemi

Saadatpour

2011

Water Resour Manage

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An automatic calibration of water quality model is developed in this research. Automatic calibration as the process to determine the parameters appearing in the equations of a 2-dimensional, hydrodynamic, and water quality models (CE-QUAL-W2) is carried out with Particle Swarm technique as an optimization tool. In the calibration of the CE-QUAl-W2 model, evaporation as a significant parameter influences the thermal profile and water surface elevation in reservoir, simultaneously. Therefore to consider the simultaneous effects of the water temperature variations on water surface elevation in the reservoir, a multi objective technique is used to minimize the weighted sum of total deviations of temperature from field data at check points on monitoring days and those of water surface elevation on daily monitoring period. The proposed approach overcomes the high computational efforts required if a conventional calibration search technique was used, while retaining the quality of the final calibration results. The automatic calibration approach is applied in temperature and water budget calibration of Karkheh reservoir in Iran. Applying the proposed automatic calibration approach, shows the produced results by the CE-QUAL-W2 model with the calibrated coefficients agree closely with a set of field data.

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Eutrophication modelling of reservoirs in Taiwan

Cited by 85 publications

References 18 publications

Eco-hydraulic Modelling of Eutrophication for Reservoir Management

Eco-hydraulic Modelling of Eutrophication for Reservoir Management

Challenges and opportunities for integrating lake ecosystem modelling approaches

Particle Swarm Optimization for Automatic Calibration of Large Scale Water Quality Model (CE-QUAL-W2): Application to Karkheh Reservoir, Iran

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