Uncertainty estimation of a complex water quality model: The influence of Box–Cox transformation on Bayesian approaches and comparison with a non-Bayesian method

2012 ◽  
Vol 42-44 ◽  
pp. 31-41 ◽  
Author(s):  
Gabriele Freni ◽  
Giorgio Mannina
Keyword(s):  
Water Quality ◽  
Bayesian Method ◽  
Uncertainty Estimation ◽  
Water Quality Model ◽  
Quality Model ◽  
Bayesian Approaches ◽  
Box Cox Transformation

Developing a Cloud-based Toolbox for Sensitivity Analysis of a Water Quality Model

2021 ◽  
pp. 105068
Author(s):  
Soobin Kim ◽  
Yong Sung Kwon ◽  
JongChel Pyo ◽  
Mayzonee Ligaray ◽  
Joong-Hyuk Min ◽  
...  
Keyword(s):  
Water Quality ◽  
Sensitivity Analysis ◽  
Water Quality Model ◽  
Quality Model

Choosing an appropriate water quality model—a review

2021 ◽  
Vol 193 (1) ◽  
Author(s):  
Cássia Monteiro da Silva Burigato Costa ◽  
Izabel Rodrigues Leite ◽  
Aleska Kaufmann Almeida ◽  
Isabel Kaufmann de Almeida
Keyword(s):  
Water Quality ◽  
Water Quality Model ◽  
Quality Model

scholarly journals Monitoring and simulating the distribution of phytoplankton in constructed wetlands based on SPOT 6 images

2021 ◽  
Vol 13 (1) ◽  
pp. 454-468
Author(s):  
Yumeng Song ◽  
Jing Zhang
Keyword(s):  
Water Quality ◽  
Water Quality Model ◽  
Quality Model ◽  
Band Ratio ◽  
Entire Study ◽  
Chl A ◽  
Analytical Tools ◽  
Best Fit ◽  
Entire Study Area ◽  
Range Of Values

Abstract We integrated hyperspectral and field-measured chlorophyll-a (Chl-a) data from the Kristalbad constructed wetland in the Netherlands. We developed a best-fit band ratio empirical algorithm to generate a distribution map of Chl-a concentration (C chla) from SPOT 6 imagery. The C chla retrieved from remote sensing was compared with a water quality model established for a wetland pond system. The retrieved satellite results were combined with a water quality model to simulate and predict the changes in phytoplankton levels. The regression model provides good retrievals for Chl-a. The imagery-derived C chla performed well in calibrating the simulation results. For each pond, the modeled C chla showed a range of values similar to the Chl-a data derived from SPOT 6 imagery (10–25 mg m−3). The imagery-derived and prediction model results could be used as the guiding analytical tools to provide information covering an entire study area and to inform policies.

scholarly journals Relative Performance of 1-D Versus 3-D Hydrodynamic, Water-Quality Models for Predicting Water Temperature and Oxygen in a Shallow, Eutrophic, Managed Reservoir

Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 88
Author(s):  
Xiamei Man ◽  
Chengwang Lei ◽  
Cayelan C. Carey ◽  
John C. Little
Keyword(s):  
Water Quality ◽  
Water Temperature ◽  
Water Quality Model ◽  
Relative Performance ◽  
Bubble Plume ◽  
Quality Model ◽  
Quality Models ◽  
Management Interventions ◽  
Water Quality Models ◽  
D Model

Many researchers use one-dimensional (1-D) and three-dimensional (3-D) coupled hydrodynamic and water-quality models to simulate water quality dynamics, but direct comparison of their relative performance is rare. Such comparisons may quantify their relative advantages, which can inform best practices. In this study, we compare two 1-year simulations in a shallow, eutrophic, managed reservoir using a community-developed 1-D model and a 3-D model coupled with the same water-quality model library based on multiple evaluation criteria. In addition, a verified bubble plume model is coupled with the 1-D and 3-D models to simulate the water temperature in four epilimnion mixing periods to further quantify the relative performance of the 1-D and 3-D models. Based on the present investigation, adopting a 1-D water-quality model to calibrate a 3-D model is time-efficient and can produce reasonable results; 3-D models are recommended for simulating thermal stratification and management interventions, whereas 1-D models may be more appropriate for simpler model setups, especially if field data needed for 3-D modeling are lacking.

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