Ensemble warming projections in Germany's largest drinking water reservoir and potential adaptation strategies

Mi, Chenxi; Shatwell, Tom; Ma, Jun; Xu, Yaqian; Su, Fangli; Rinke, Karsten

doi:10.1016/j.scitotenv.2020.141366

Cited by 37 publications

(23 citation statements)

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Resulting errors are in the same order of magnitude as values reported in other model applications (e.g. Bruce et al, 2018;Weber et al, 2017;510 Kobler et al, 2018;Mi et al, 2020;Chanudet et al, 2012;Dissanayake et al, 2019).…”

Section: Temperaturesupporting

confidence: 82%

“…By taking these general and model-specific limitations into consideration, models are valuable tools not only for managing water resources, but also for scientific applications (e.g. Sabrekov et al, 2017;Mi et al, 2020;de Carvalho Bueno et al, 2021).…”

Section: Dmentioning

confidence: 99%

“…Alternatively, the models resolve the vertical and one horizontal (longitudinal) dimension -2DV, suitable for elongated deep-water bodies where vertical thermal stratification plays a major role, e.g. CE-QUAL-W2 (Gelda et al, 2015;Kobler et al, 2018;Mi et al, 2020). Finally, three-dimensional (3D) models provide highly detailed spatial 45 data, but require larger computational effort in terms of time and storage.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Effects of dimensionality on the performance of hydrodynamic models

Ishikawa

González

Golyjeswski

et al. 2021

Preprint

View full text Add to dashboard Cite

Abstract. Numerical models are an important tool for simulating temperature, hydrodynamics and water quality in lakes and reservoirs. Existing models differ in dimensionality by considering spatial variations of simulated parameters (e.g., flow velocity and water temperature) in one (1D), two (2D) or three (3D) spatial dimensions. The different approaches are based on different levels of simplification in the description of hydrodynamic processes and result in different demands in computational power. The aim of this study is to compare three models with different dimensionality and to analyze differences between model results in relation to model simplifications. We analyze simulations of thermal stratification, flow velocity, and substance transport by density currents in a medium-sized drinking water reservoir in the subtropical zone, using three widely used open-source models: GLM (1D), CE-QUAL-W2 (2D) and Delft3D (3D). The models were operated with identical initial and boundary conditions over a one-year period. Their performance was assessed by comparing model results with measurements of temperature, flow velocity and turbulence. Results show that all models were capable of simulating the seasonal changes in water temperature and stratification. Flow velocities, only available for the 2D and 3D approaches, were more challenging to reproduce, but 3D simulations showed closer agreement with observations. With increasing dimensionality, the quality of the simulations also increased in terms of error, correlation and variance. None of the models provided good agreement with observations in terms of mixed layer depth, which also affects the spreading of inflowing water as density currents, and the results of water quality models that build on outputs of the hydrodynamic models.

show abstract

Section: Temperaturesupporting

confidence: 82%

Section: Dmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Effects of dimensionality on the performance of hydrodynamic models

Ishikawa

González

Golyjeswski

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

Section: Temperaturesupporting

confidence: 81%

Reply on CEC2

Ishikawa

2021

View full text Add to dashboard Cite

“…Physical lake models, even in their simplest one-dimensional form have been shown to reproduce thermal dynamics with relatively high accuracy (Bruce et al, 2018;Mesman et al, 2020) and are hence well suited for studying future changes in lake stratification and mixing. Lake models are therefore an efficient tool to simulate the consequences of climate warming and have even been applied to develop adequate adaptation strategies (Mi et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Simulating thermal dynamics of the largest lake in the Caucasus region: The mountain Lake Sevan

Shikhani

Gevorgyan

et al. 2021

J Limnol

Self Cite

View full text Add to dashboard Cite

Lake Sevan is the largest freshwater body in the Caucasus region, situated at an altitude of 1,900 m asl. While it is a major water resource in the whole region, Lake Sevan has received little attention in international limnological literature. Although recent studies pointed to algal blooms and negative impacts of climate change and eutrophication, the physical controls on thermal dynamics have not been characterized and model-based assessments of climate change impacts are lacking. We compiled a decade of historical data for meteorological conditions and temperature dynamics in Lake Sevan and used a one-dimensional hydrodynamic model (GLM 3.1) in order to study thermal structure, the stratification phenology and their meteorological drivers in this large mountain lake. We then evaluated the representativeness of meteorological data products covering almost 4 decades (EWEMBI-dataset: 1979-2016) for driving the model and found that these data are well suited to restore long term thermal dynamics in Lake Sevan. This established model setting allowed us to identify major changes in Lake Sevan’s stratification in response to changing meteorological conditions as expected from ongoing climate change. Our results point to a changing mixing type from dimictic to monomictic as Lake Sevan will experience prolonged summer stratification periods and more stable stratification. These projected changes in stratification must be included in long-term management perspectives as they will intensify water quality deteriorations like surface algal blooms or deep water anoxia.

show abstract

Ensemble warming projections in Germany's largest drinking water reservoir and potential adaptation strategies

Cited by 37 publications

References 62 publications

Effects of dimensionality on the performance of hydrodynamic models

Effects of dimensionality on the performance of hydrodynamic models

Reply on CEC2

Simulating thermal dynamics of the largest lake in the Caucasus region: The mountain Lake Sevan

Contact Info

Product

Resources

About