A multi-variate methodology for analyzing pre-existing lake water quality data

2011 ◽  
Vol 13 (9) ◽  
pp. 2477 ◽  
Author(s):  
Keah-Ying Lim ◽  
Cristiane Q. Surbeck
Keyword(s):  
Water Quality ◽  
Lake Water ◽  
Quality Data ◽  
Lake Water Quality ◽  
Water Quality Data

scholarly journals Watershed-Based Evaluation of Automatic Sensor Data: Water Quality and Hydroclimatic Relationships

2020 ◽  
Vol 12 (1) ◽  
pp. 396 ◽  
Author(s):  
Jacopo Cantoni ◽  
Zahra Kalantari ◽  
Georgia Destouni
Keyword(s):  
Water Quality ◽  
Lake Water ◽  
Water Discharge ◽  
Sensor Data ◽  
Quality Data ◽  
High Temporal Resolution ◽  
Lake Water Quality ◽  
Water Quality Data ◽  
Blue Green Algae ◽  
Water Quality Variables

Water is a fundamental resource and, as such, the object of multiple environmental policies requiring systematic monitoring of its quality as a main management component. Automatic sensors, allowing for continuous monitoring of various water quality variables at high temporal resolution, offer new opportunities for enhancement of essential water quality data. This study investigates the potential of sensor-measured data to improve understanding and management of water quality at watershed level. Self-organizing data maps, non-linear canonical correlation analysis, and linear regressions are used to assess the relationships between multiple water quality and hydroclimatic variables for the case study of Lake Mälaren in Sweden, and its total catchment and various watersheds. The results indicate water discharge from dominant watersheds into a lake, and lake water temperature as possible proxies for some key water quality variables in the lake, such as blue-green algae; the latter is, in turn, identified as a potential good proxy for lake concentration of total nitrogen. The relationships between water discharges into the lake and lake water quality dynamics identify the dominant contributing watersheds for different water quality variables. Seasonality also plays an important role in determining some possible proxy relationships and their usefulness for different parts of the year.

Delaqua – A Prototype Expert System for Operational Control and Management of Lake Water Quality

1991 ◽  
Vol 24 (6) ◽  
pp. 283-290 ◽  
Author(s):  
Frieder Recknagel ◽  
Erhard Beuschold ◽  
Uwe Petersohn
Keyword(s):  
Water Quality ◽  
Expert System ◽  
Lake Water ◽  
Quality Data ◽  
Raw Water ◽  
Operational Control ◽  
Lake Water Quality ◽  
Water Quality Data ◽  
Lakes And Reservoirs ◽  
Raw Water Quality

The expert system DELAQUA (Deep Expert system LAke water QUAlity) combines AI and simulation methods to support decision making in water quality control of lakes and reservoirs. It contains a knowledge base (PROLOG 2), a data base (dBASE III+) and a simulation system (FORTRAN 77) by which the following decision aids can be made available:derivation of recommendations for operational control of undesired impacts on raw water quality by algal blooms or pathogen germsclassification of raw water quality by means of legal standardsdrawing of analogy conclusions by the use of measured and simulated water quality data of reference waterspredictions of raw water quality under changing control strategies and environmental conditions of lakes and reservoirs. The expert system was implemented on an IBM-PC with MS.DOS operating system.

A modeling approach to simulate impact of climate change in lake water quality: phytoplankton growth rate assessment

1998 ◽  
Vol 37 (2) ◽  
pp. 177-185 ◽  
Author(s):  
Hany Hassan ◽  
Keisuke Hanaki ◽  
Tomonori Matsuo
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
Growth Rate ◽  
Dissolved Oxygen ◽  
Lake Water ◽  
Phytoplankton Growth ◽  
Quality Data ◽  
Model Parameters ◽  
Lake Water Quality ◽  
Phytoplankton Growth Rate

Global climate change induced by increased concentrations of greenhouse gases (especially CO2) is expected to include changes in precipitation, wind speed, incoming solar radiation, and air temperature. These major climate variables directly influence water quality in lakes by altering changes in flow and water temperature balance. High concentration of nutrient enrichment and expected variability of climate can lead to periodic phytoplankton blooms and an alteration of the neutral trophic balance. As a result, dissolved oxygen levels, with low concentrations, can fluctuate widely and algal productivity may reach critical levels. In this work, we will present: 1) recent results of GCMs climate scenarios downscaling project that was held at the University of Derby, UK.; 2) current/future comparative results of a new mathematical lake eutrophication model (LEM) in which output of phytoplankton growth rate and dissolved oxygen will be presented for Suwa lake in Japan as a case study. The model parameters were calibrated for the period of 1973–1983 and validated for the period of 1983–1993. Meterologic, hydrologic, and lake water quality data of 1990 were selected for the assessment analysis. Statistical relationships between seven daily meteorological time series and three airflow indices were used as a means for downscaling daily outputs of Hadley Centre Climate Model (HadCM2SUL) to the station sub-grid scale.

scholarly journals Modelling Water Quality Improvements in a South Korean Inter-Basin Water Transfer System

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3173
Author(s):  
Hye Won Lee ◽  
Bo-Min Yeom ◽  
Jung Hyun Choi
Keyword(s):  
Water Quality ◽  
Quality Management ◽  
Constructed Wetlands ◽  
Management Practices ◽  
Water Quality Management ◽  
Quality Data ◽  
Watershed Model ◽  
Selective Withdrawal ◽  
Lake Water Quality ◽  
Water Quality Data

In this study, we investigated the feasibility of using constructed wetlands for non-point source pollution reduction. The effect of constructed wetlands in reducing suspended solids (SS) was analyzed using an integrated modeling system of watershed model (HSPF), reservoir model (CE-QUAL-W2), and stream model (EFDC) to investigate the behavior and accumulation of the pollution sources based on 2017 water quality data. The constructed wetlands significantly reduced the SS concentration by approximately 30%, and the other in-lake management practices (e.g., artificial floating islands and sedimentation basins) contributed an additional decrease of approximately 7%. Selective withdrawal decreased in the average SS concentration in the influents by ~10%; however, the effluents passing through the constructed wetlands showed only a slight difference of 1.9% in the average SS concentration. In order to meet the water quality standards, it was necessary to combine the constructed wetlands, in-lake water quality management, and selective withdrawal practices. Hence, it was determined that the model proposed herein is useful for estimating the quantitative effects of water quality management practices such as constructed wetlands, which provided practical guidelines for the application of further water quality management policies.

scholarly journals Numerical Simulation of Donghu Lake Hydrodynamics and Water Quality Based on Remote Sensing and MIKE 21

2020 ◽  
Vol 9 (2) ◽  
pp. 94 ◽  
Author(s):  
Xiaojuan Li ◽  
Mutao Huang ◽  
Ronghui Wang
Keyword(s):  
Remote Sensing ◽  
Numerical Simulation ◽  
Water Quality ◽  
Lake Water ◽  
Quality Data ◽  
Lake Water Quality ◽  
Water Quality Simulation ◽  
Donghu Lake ◽  
Mean Square Errors

Numerical simulation is an important method used in studying the evolution mechanisms of lake water quality. At the same time, lake water quality inversion technology using the characteristics of spatial optical continuity data from remote sensing satellites is constantly improving. It is, however, a research hotspot to combine the spatial and temporal advantages of both methods, in order to develop accurate simulation and prediction technology for lake water quality. This paper takes Donghu Lake in Wuhan as its research area. The spatial data from remote sensing and water quality monitoring information was used to construct a multi-source nonlinear regression fitting model (genetic algorithm (GA)-back propagation (BP) model) to invert the water quality of the lake. Based on the meteorological and hydrological data, as well as basic water quality data, a hydrodynamic model was established by using the MIKE21 model to simulate the evolution rules of water quality in Donghu Lake. Combining the advantages of the two, the best inversion results were used to provide a data supplement for optimization of the water quality simulation process, improving the accuracy and quality of the simulation. The statistical results were compared with water quality simulation results based on the data measured. The results show that the water quality simulation of chlorophyll a and nitrate nitrogen mean square errors fell to 17% and 24%, from 19% and 31% respectively, after optimization using remote sensing spatial information. The model precision was thus improved, and this is consistent with the actual pollution situation of Donghu Lake.

Improvement of Lake Water Quality by using Moving Rapid Water Treatment System

2018 ◽  
Vol 18 (1) ◽  
pp. 107-115 ◽  
Author(s):  
Kwang-Hee Lee ◽  
◽  
Min-Ho Kim ◽  
Nam-Woo An ◽  
Chul-hwi Park
Keyword(s):  
Water Quality ◽  
Water Treatment ◽  
Lake Water ◽  
Treatment System ◽  
Lake Water Quality ◽  
Water Treatment System
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