An Integrated Graphic Modeling System for Three-Dimensional Hydrodynamic and Water Quality Simulation in Lakes

Understanding the complex hydrodynamics and transport processes are of primary importance to alleviate and control the eutrophication problem in lakes. Numerical models are used to simulate these processes. However, it is often difficult to perform such a numerical modeling simulation for common users. This study presented an integrated graphic modeling system designed for three-dimensional hydrodynamic and water quality simulation in lakes. The system, called the Lake Modeling System (LMS), provides necessary functionalities streamlined for hydrodynamic modeling. The LMS provides a geographic information system (GIS)-based data processing framework to establish a model and provides capabilities for displaying model input and output information. The LMS also provides mapping and visualization tools to support the model development process. All of these features in a GIS-based framework makes the task of complex hydrodynamic and water quality modeling easier. The applicability of the LMS is demonstrated by a case study in Lake Donghu, which is a large urban lake in the middle reaches of the Yangtze River in China. The LMS was utilized to setup and calibrate a model for Lake Donghu. Then the model was used to study the effects of a water diversion project on the change in hydrodynamics and the water quality.

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Research on Water Environment Regulation of Artificial Playground Lake Interconnected Yangtze River

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph15102110 ◽

2018 ◽

Vol 15 (10) ◽

pp. 2110 ◽

Cited By ~ 1

Author(s):

Weiwei Song ◽

Xingqian Fu ◽

Yong Pang ◽

Dahao Song ◽

Qing Xu ◽

...

Keyword(s):

Water Quality ◽

Water Level ◽

Yangtze River ◽

Flood Control ◽

Numerical Models ◽

Rapid Development ◽

Control Level ◽

Water Environment ◽

Water Diversion ◽

Coupled Models

With the rapid development of China, water pollution is still a serious problem despite implementation of control measures. Reasonable water environment management measures are very important for improving water quality and controlling eutrophication. In this study, the coupled models of hydrodynamics, water quality, and eutrophication were used to predict artificial Playground Lake water quality in the Zhenjiang, China. Recommended “unilateral” and “bilateral” river numerical models were constructed to simulate the water quality in the Playground Lake without or with water diversion by pump, sluice and push pump. Under “unilateral” and “bilateral” river layouts, total nitrogen and total phosphorus meet the landscape water requirement through water diversion. Tourist season in spring and summer and its suitable temperature result in heavier eutrophication, while winter is lighter. Under pumping condition, water quality and eutrophication of “unilateral” river is better than “bilateral” rivers. Under sluice diversion, the central landscape lake of “unilateral river” is not smooth, and water quality and eutrophication is inferior to the “bilateral”. When the water level exceeds the flood control level (4.1 m), priority 1 is launched to discharge water from the Playground Lake. During operation of playground, when water level is less than the minimum level (3.3 m), priority 2 is turned on for pumping diversion or sluice diversion to Playground Lake. After opening the Yangtze river diversion channel sluice, priority 3 is launched for sluice diversion to the Playground Lake. When the temperature is less than 15 °C, from 15 °C to 25 °C and higher than 25 °C, the water quality can be maintained for 15 days, 10 days and 7 days, respectively. Corresponding to the conditions of different priority levels, reasonable choices of scheduling measures under different conditions to improve the water quality and control eutrophication of the Playground Lake. This article is relevant for the environmental management of the artificial Playground Lake, and similar lakes elsewhere.

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IberWQ: A GPU Accelerated Tool for 2D Water Quality Modeling in Rivers and Estuaries

Water ◽

10.3390/w12020413 ◽

2020 ◽

Vol 12 (2) ◽

pp. 413 ◽

Cited By ~ 3

Author(s):

Orlando García-Feal ◽

Luis Cea ◽

José González-Cao ◽

José Manuel Domínguez ◽

Moncho Gómez-Gesteira

Keyword(s):

Water Quality ◽

High Performance ◽

Numerical Models ◽

Water Quality Modeling ◽

Test Cases ◽

Processing Unit ◽

Environmental Status ◽

Quality Modeling ◽

Stratified Estuaries ◽

Averaged Model

Numerical models are useful tools to analyze water quality by computing the concentration of physical, chemical and biological parameters. The present work introduces a two-dimensional depth-averaged model that computes the most relevant and frequent parameters used to evaluate water quality. High performance computing (HPC) techniques based on graphic processing unit (GPU) parallelization have been applied to improve the efficiency of the package, providing speed-ups of two orders of magnitude in a standard PC. Several test cases were analyzed to show the capabilities and efficiency of the model to evaluate the environmental status of rivers and non-stratified estuaries. IberWQ will be freely available through the package Iber.

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Application of Data Fusion for Uncertainty and Sensitivity Analysis of Water Quality in the Shenandoah River

Geospatial Intelligence ◽

10.4018/978-1-5225-8054-6.ch061 ◽

2019 ◽

pp. 1383-1410

Author(s):

Mbongowo Joseph Mbuh

Keyword(s):

Water Quality ◽

Data Fusion ◽

Field Observation ◽

Water Quality Modeling ◽

Coefficient Of Determination ◽

Water Quality Simulation ◽

Quality Modeling ◽

Invaluable Tool ◽

Using Data ◽

Very High

This article is aimed at demonstrating the feasibility of combining water quality observations with modeling using data fusion techniques for efficient nutrients monitoring in the Shenandoah River (SR). It explores the hypothesis; “Sensitivity and uncertainty from water quality modeling and field observation can be improved through data fusion for a better prediction of water quality.” It models water quality using water quality simulation programs and combines the results with field observation, using a Kalman filter (KF). The results show that the analysis can be improved by using more observations in watersheds where minor variations to the analysis result in large differences in the subsequent forecast. Analyses also show that while data fusion was an invaluable tool to reduce uncertainty, an improvement in the temporal scales would also enhance results and reduce uncertainty. To examine how changes in the field observation affects the final KF analysis, the fusion and lab analysis cross-validation showed some improvement in the results with a very high coefficient of determination.

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