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.

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 Natural stochasticity vs. management effort: use of year-to-year variance for disentangling significance of two mutually confounding factors affecting water quality of a Norwegian cold dimictic lake

2014 ◽  
Vol 11 (11) ◽  
pp. 12489-12518
Author(s):  
A. T. Romarheim ◽  
K. Tominaga ◽  
G. Riise ◽  
T. Andersen
Keyword(s):  
Water Quality ◽  
Lake Water ◽  
Phytoplankton Biomass ◽  
Light Attenuation ◽  
System Structure ◽  
Confounding Factors ◽  
Lake Water Quality ◽  
Management Effort ◽  
Stochastic Event

Natural stochasticity can pose challenges in managing the quality of the environment, or hinder understanding of the system structure. It is problematic because unfavourable stochastic event cancels the costly management effort and because favourable stochastic event overestimates success of the management effort. This paper presents a variance-based modelling method that can be used to quantify the extent to which the natural stochasticity can affect the target environment. We use a case study of a lake water quality assessment in a Norwegian lake of Årungen, together with a lake model MyLake, in order to present the method, and how this method could assist in answering scientific and managerial questions. Specifically, the case study's goal was to disentangle the respective significance of nutrient loading (management) and weather (the confounding natural stochasticity). Many scientifically and managerially relevant understandings have been revealed. For example, variation in runoff volume was most prevalent during autumn and winter, while variation in phosphorus inflow was most extensive from late winter to early spring. Thermal related properties in the lake were mostly determined by weather conditions, whereas loading was the most important factor for phytoplankton biomass and water transparency. Mild winters and greater inputs of suspended matter and phosphorus were followed by increased phytoplankton biomass and light attenuation. These findings suggest also that future changes in the global climate may have important implications for local water management decision-making. The present method of disentangling mutually confounding factors is not limited to lake water quality studies and therefore should provide certain utility in other application field of modelling.

scholarly journals APPLICATION OF THE MODIFIED EBB TO IMPROVE LAKE WATER QUALITY IN HA NOI

2018 ◽  
Vol 55 (4C) ◽  
pp. 186
Author(s):  
Hoang Luong
Keyword(s):  
Water Quality ◽  
Lake Water ◽  
Bacterial Communities ◽  
Domestic Wastewater ◽  
Viet Nam ◽  
Residential Areas ◽  
Small Lakes ◽  
Lake Water Quality ◽  
Environmental Materials

The modified Eco-Bio-Block (EBB) has been studied and manufactured in Viet Nam, based on the process of blending friendly environmental materials as activated carbon, zeolite, kazemzite, sand and useful microorganisms. After culturing, bacterial communities in the modified EBB became significant abundant by DGGE analysis of 16S rDNA. The amount of microorganisms in the modified EBB was 107 CFU/g bacteria communities (Prokaryote). After 2 months treatment with the modified EBB, the quality of Khuong Thuong lake water has been significantly improved; the concentration of COD, NH4+, Coliform and Chlorophyll-a are reduced by 65.51 %, 64.28 %, 50 % and 68.42 %, respectively at the location A1. Sensuously, the lake water became brighter and cleaner. The application of the modified EBB to improve the lake water quality was conducted appropriately to the conditions at Vietnam in general and at Hanoi in particular. This research aims at localizing technology and improving efficiency on pond/lake water treatment. Further goal of the modified EBB application is to reduce pollutants in domestic wastewater form residential areas, in ditches, creeks and small lakes in Viet Nam.

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.

scholarly journals Spatiotemporal Variability of Lake Water Quality in the Context of Remote Sensing Models

2017 ◽  
Vol 9 (5) ◽  
pp. 409 ◽  
Author(s):  
Carly Hansen ◽  
Steven Burian ◽  
Philip Dennison ◽  
Gustavious Williams
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Lake Water ◽  
Spatiotemporal Variability ◽  
Lake Water Quality

Minlake: A dynamic lake water quality simulation model

1988 ◽  
Vol 43 (3-4) ◽  
pp. 155-182 ◽  
Author(s):  
Michael J. Riley ◽  
Heinz G. Stefan
Keyword(s):  
Water Quality ◽  
Simulation Model ◽  
Lake Water ◽  
Lake Water Quality ◽  
Water Quality Simulation

Effects of Sediment Dredging on Water Quality of Meiliang Lake

2011 ◽  
Vol 90-93 ◽  
pp. 2619-2623
Author(s):  
Fu Long Chen ◽  
Jing Wang
Keyword(s):  
Water Quality ◽  
Numerical Model ◽  
Bottom Sediment ◽  
Lake Water ◽  
Lake Water Quality ◽  
Sediment Dredging ◽  
Tai Lake ◽  
Before And After

Meiliang Lake is located at north of Tai lake, it is one of the most important part of Tai Lake. Water quality of Meiliang Lake is being worse because the TP, TN and COD is released from the bottom sediment. So th goverment is decided to dredg the bottom sediment to improve the water quality. This paper used WASP5 numerical model to simulate the water quality of Meiliang Lake before and after the sediment dredging. The results show that sediment dredging is useful for improving the water quality of Meiliang Lake.

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