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Special Issue "Water Quality Monitoring and Modeling in Lakes"

A special issue of Water (ISSN 2073-4441).

Deadline for manuscript submissions: 31 July 2017

Special Issue Editors

Guest Editor
Prof. Dr. Xing Fang

Department of Civil Engineering, Auburn University, Auburn, AL 36849, USA
Website | E-Mail
Interests: water quality modeling; climate change; lakes; rivers; hydrological modeling; water resources engineering; watershed hydrology; water quality monitoring; water quality analysis; eutrophication; surface hydrology; rainfall runoff modelling; aquatic ecosystems; fish habitat; regional climate modeling; stormwater managment
Guest Editor
Prof. Dr. Alan W. Groeger

Department of Biology, Texas State University, San Marcos, TX 78666, USA
Website | E-Mail
Interests: reservoir limnology; biogeochemistry; phytoplankton ecology; climate change; watershed processes
Guest Editor
Prof. Dr. Qin Qian

Department of Civil & Environmental Engineering, Lamar University, Beaumont, TX 77710, USA
Website | E-Mail
Interests: hydrology, hydraulics and water resources with a research goal to advance process-based knowledge to allow better informed land use planning, ecological restoration design, and preservation of aquatic ecosystems; specific area includes environmental hydrodynamics, water quality modeling and solute (contaminate) transport processes in lakes, streams and groundwater; water resource monitoring and management using ubiqutious wireless sensor network; restoration design application for preservation of aquatic ecosystem in streams, lakes and estuaries

Special Issue Information

Dear Colleagues,

Water quality in lakes is a critical issue due to its direct influence on public health, biological integrity of natural resources, and the economy. The earth has a tremendous variety of lakes, from small ponds to Lake Baikal in Siberia, and from manmade reservoirs to natural lakes. Even though lakes and reservoirs are only a small part of water on our planet, they play a critical and important role in the Earth’s biosphere. Climate changes, including climate variability, land-use/land-cover changes, and anthropogenic changes due to various urban and industrial development, can lead to hydrological, chemical, and biological changes in watersheds and freshwater ecosystems resulting in altered water quality. To understand impacts of changes from upstream or surrounding watersheds and within a lake on water quality is important to people who live nearby or visit the lake and is also fundamental in providing better ecological and environmental strategies and mitigation methods to protect freshwater ecosystems. Dissolved oxygen and other water quality constituents have implications for the growth, reproduction, and survival of freshwater organisms such as phytoplankton, zooplankton, benthic organisms, and fish. In particular, the bottom waters of thermally stratified lakes and reservoirs can become totally devoid of oxygen due to biochemical oxygen demand and sedimentary oxygen demand. Climate variations (seasonal or inter-annual) and global climate warming directly affect the heat budget of an aquatic system through the surface heat exchange between the water and the atmosphere, and then influence water quality characteristics. An increase of atmospheric carbon dioxide (CO2) and/or other greenhouse gases is projected to cause climate warming, which would alter water temperature, ice/snow cover, and water quality characteristics in aquatic systems. Land-use/land-cover changes and anthropogenic changes affect nutrients and chemical inputs to aquatic systems. These changes are, in turn, expected to have an effect on freshwater organism populations and biodiversity. Monitoring and modeling approaches have been used by citizen volunteers, biologists, water resources managers, engineers, and scientists to understand and study water quality issues in lakes. Different monitoring techniques and modern monitoring device/sensors allow us to get more in-depth information that we could not obtain before. Advanced models or modeling methods also allow us to better understand water quality dynamics and spatial distributions in lakes that discrete data collections or monitoring cannot reveal. Monitoring data are necessary for model calibration and validation before the model can be used for scenario study, sensitivity analysis, and future projection under certain changes in watersheds and lakes.

Prof. Dr. Xing Fang
Prof. Dr. Alan W. Groeger
Prof. Dr. Qin Qian
Guest Editors

Manuscript Submission Information

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Keywords

  • ponds, lakes and reservoirs
  • water quality
  • freshwater ecosystem
  • climate change
  • monitoring
  • data analysis
  • models or modeling
  • anthropogenic changes

Published Papers (8 papers)

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Research

Open AccessArticle Long Term Trends and Dynamics of Dissolved Organic Carbon (DOC) in a Subtropical Reservoir Basin
Water 2017, 9(7), 545; doi:10.3390/w9070545
Received: 24 April 2017 / Revised: 30 June 2017 / Accepted: 11 July 2017 / Published: 20 July 2017
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Abstract
This study evaluates the long term trends and seasonal patterns of dissolved organic carbon (DOC) concentration in the Fei-Tsui Reservoir basin in Northern Taiwan during the period of 2000 to 2015. The non-parametric seasonal Mann-Kendall test was conducted to identify the trends of
[...] Read more.
This study evaluates the long term trends and seasonal patterns of dissolved organic carbon (DOC) concentration in the Fei-Tsui Reservoir basin in Northern Taiwan during the period of 2000 to 2015. The non-parametric seasonal Mann-Kendall test was conducted to identify the trends of DOC and its potential drivers (e.g., temperature, runoff, atmospheric acid deposition and stream water chemistry). The monthly tributaries and water surface DOC concentrations in Fei-Tsui Reservoir had showed strong temporal and seasonal variability. The sulfate (SO4) concentration had exhibited statistically significant decreasing trend over a period of 16 years. The decreasing trends of anions (SO4 and NO3) and base cations (Ca and Mg) as well as increasing trends of pH and acidification index (ACI) in Fei-Tsui Reservoir and streams indicated recovery from acidification. However, there was no significant annual trend in DOC concentration of Fei-Tsui Reservoir and streams. Significant positive correlation was obtained between DOC and trophic state index of Fei-Tsui Reservoir. The results suggested that DOC concentration at the water surface of Fei-Tsui Reservoir was mainly driven by the re-oligotrophication and temperature effects rather than a decrease in atmospheric sulfur deposition. Stream DOC concentration was largely determined by the temporal variability in temperature and rainfall. We concluded that climatic and hydrological factors are the dominant drivers for stream DOC dynamics in the study. Full article
(This article belongs to the Special Issue Water Quality Monitoring and Modeling in Lakes)
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Open AccessArticle Chlorophyll-A Prediction of Lakes with Different Water Quality Patterns in China Based on Hybrid Neural Networks
Water 2017, 9(7), 524; doi:10.3390/w9070524
Received: 25 May 2017 / Revised: 12 July 2017 / Accepted: 13 July 2017 / Published: 14 July 2017
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Abstract
One of the most important water quality problems affecting lakes and reservoirs is eutrophication, which is caused by multiple physical and chemical factors. As a representative index of eutrophication, the concentration of chlorophyll-a has always been a key indicator monitored by environmental managers.
[...] Read more.
One of the most important water quality problems affecting lakes and reservoirs is eutrophication, which is caused by multiple physical and chemical factors. As a representative index of eutrophication, the concentration of chlorophyll-a has always been a key indicator monitored by environmental managers. The most influential factors on chlorophyll-a may be dependent on the different water quality patterns in lakes. In this study, data collected from 27 lakes in different provinces of China during 2009–2011 were analyzed. The self-organizing map (SOM) was first applied on the datasets and the lakes were classified into four clusters according to 24 water quality parameters. Comparison amongst the clusters revealed that Cluster I was the least polluted and at the lowest trophic level, while Cluster IV was the most polluted and at the highest trophic level. The genetic algorithm optimized back-propagation neural network (GA-BPNN) was applied to each lake cluster to select the most influential input variables for chlorophyll-a. The results of the four clusters showed that the performance of GA-BPNN was satisfied with nearly half of the input variables selected from the predictor pool. The selected factors varied for the lakes in different clusters, which indicates that the control for eutrophication should be separate for lakes in different provinces of one country. Full article
(This article belongs to the Special Issue Water Quality Monitoring and Modeling in Lakes)
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Open AccessArticle Mapping Submerged Aquatic Vegetation Using RapidEye Satellite Data: The Example of Lake Kummerow (Germany)
Water 2017, 9(7), 510; doi:10.3390/w9070510
Received: 20 March 2017 / Revised: 13 June 2017 / Accepted: 5 July 2017 / Published: 12 July 2017
Cited by 1 | PDF Full-text (7378 KB) | HTML Full-text | XML Full-text
Abstract
Submersed aquatic vegetation (SAV) is sensitive to changes in environmental conditions and plays an important role as a long-term indictor for the trophic state of freshwater lakes. Variations in water level height, nutrient condition, light availability and water temperature affect the growth and
[...] Read more.
Submersed aquatic vegetation (SAV) is sensitive to changes in environmental conditions and plays an important role as a long-term indictor for the trophic state of freshwater lakes. Variations in water level height, nutrient condition, light availability and water temperature affect the growth and species composition of SAV. Detailed information about seasonal variations in littoral bottom coverage are still unknown, although these effects are expected to mask climate change-related long-term changes, as derived by snapshots of standard monitoring methods included in the European Water Framework Directive. Remote sensing offers concepts to map SAV quickly, within large areas, and at short intervals. This study analyses the potential of a semi-empirical method to map littoral bottom coverage by a multi-seasonal approach. Depth-invariant indices were calculated for four Atmospheric & Topographic Correction (ATCOR2) atmospheric corrected RapidEye data sets acquired at Lake Kummerow, Germany, between June and August 2015. RapidEye data evaluation was supported by in situ measurements of the diffuse attenuation coefficient of the water column and bottom reflectance. The processing chain was able to differentiate between SAV and sandy sediment. The successive increase of SAV coverage from June to August was correctly monitored. Comparisons with in situ and Google Earth imagery revealed medium accuracies (kappa coefficient = 0.61, overall accuracy = 72.2%). The analysed time series further revealed how water constituents and temporary surface phenomena such as sun glint or algal blooms influence the identification success of lake bottom substrates. An abundant algal bloom biased the interpretability of shallow water substrate such that a differentiation of sediments and SAV patches failed completely. Despite the documented limitations, mapping of SAV using RapidEye seems possible, even in eutrophic lakes. Full article
(This article belongs to the Special Issue Water Quality Monitoring and Modeling in Lakes)
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Open AccessArticle Transport of Conservative and “Smart” Tracers in a First-Order Creek: Role of Transient Storage Type
Water 2017, 9(7), 485; doi:10.3390/w9070485
Received: 29 April 2017 / Revised: 26 June 2017 / Accepted: 28 June 2017 / Published: 2 July 2017
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Abstract
Using “smart” tracers such as Resazurin (Raz) allows assessment of sediment-water interactions and associated biological activity in streams. We compared two approaches to simulate the effects of transient storage (TS) on the transport of conservative and reactive tracers. The first approach considered TS
[...] Read more.
Using “smart” tracers such as Resazurin (Raz) allows assessment of sediment-water interactions and associated biological activity in streams. We compared two approaches to simulate the effects of transient storage (TS) on the transport of conservative and reactive tracers. The first approach considered TS as composed of metabolically active and metabolically inactive compartments, while the second model approach accounted for the surface transient storage (STS) and hyporheic transient storage (HTS). Experimental data were collected at a perennial first-order creek in Maryland, MD, USA, by injecting the conservative tracer bromide (Br) and the reactive (Raz) tracer and sampling water at two weir stations. The STS–HTS approach led to a more accurate simulation of Br transport and tails of the Raz and its product Rezorufin (Rru) breakthrough curves. Sediments support large microbial communities, and the STS–HTS model in creeks provides additional parameters to characterize the habitats of microbial water-quality indicator organisms. Full article
(This article belongs to the Special Issue Water Quality Monitoring and Modeling in Lakes)
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Open AccessArticle Nutrients and Phytoplankton in a Shallow, Hypereutrophic Urban Lake: Prospects for Restoration
Water 2017, 9(6), 431; doi:10.3390/w9060431
Received: 11 May 2017 / Revised: 8 June 2017 / Accepted: 12 June 2017 / Published: 14 June 2017
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Abstract
University Lake, a shallow, artificial, urban lake adjacent to the campus of Louisiana State University, has a long history of water quality problems, including algal blooms, fish kills, and high concentrations of fecal indicator bacteria. Periodic dredging of the lake is necessary to
[...] Read more.
University Lake, a shallow, artificial, urban lake adjacent to the campus of Louisiana State University, has a long history of water quality problems, including algal blooms, fish kills, and high concentrations of fecal indicator bacteria. Periodic dredging of the lake is necessary to prevent its return to swampland. This study was undertaken to elucidate the roles of allochthonous versus autochthonous nutrients as causes of water quality problems in the lake, with the expectation that this information would help identify strategies for lake restoration. Photosynthetic rates and concentrations of inorganic nutrients and phytoplankton pigments were measured over a period of one year. More than 90% of the chlorophyll a (chl a) in the lake was accounted for by Chlorophyceae, Cyanophyceae, and Bacillariophyceae. Concentrations of chl a, which averaged 75 μg L−1, fluctuated weekly during dry weather by as much as a factor of four. Phytoplankton growth rates were about 30% higher 1–2 days after rain events than after periods of dry weather, the implication being that allochthonous nutrient loading has a significant effect on the dynamics of the phytoplankton community in the lake. Therefore, dredging of sediments will likely produce no long-term improvement in water quality. More than 100 storm drains currently discharge into the lake, and diversion of those drains may be the most cost-effective strategy for effecting a long-term improvement in water quality. Full article
(This article belongs to the Special Issue Water Quality Monitoring and Modeling in Lakes)
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Open AccessArticle Effects of Dredging and Lanthanum-Modified Clay on Water Quality Variables in an Enclosure Study in a Hypertrophic Pond
Water 2017, 9(6), 380; doi:10.3390/w9060380
Received: 21 March 2017 / Revised: 19 May 2017 / Accepted: 19 May 2017 / Published: 27 May 2017
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Abstract
An enclosure experiment was conducted between July and September 2009 to compare the effectiveness of a phosphate fixative, the lanthanum-modified bentonite clay Phoslock® (LMB), dredging, and their combination in controlling eutrophication in a hypertrophic urban pond in Heesch, The Netherlands. In total,
[...] Read more.
An enclosure experiment was conducted between July and September 2009 to compare the effectiveness of a phosphate fixative, the lanthanum-modified bentonite clay Phoslock® (LMB), dredging, and their combination in controlling eutrophication in a hypertrophic urban pond in Heesch, The Netherlands. In total, 25 water quality variables were monitored. Multivariate analysis revealed that the combination LMB-treated and dredged enclosures deviated most from the pond (reference) and the controls, and showed the strongest eutrophication reduction. Overall, dredging significantly increased transparency, lowered turbidity, and improved the oxygen conditions in the enclosures compared to non-dredged ones. Nonetheless, one dredged enclosure deviated dramatically from the others, which might reflect methodological issues with dredging. The LMB treatment appeared to be less effective at mitigating eutrophication than dredging, and phosphate concentrations even increased during the experiment in the LMB-treated enclosures. Chemical equilibrium modeling suggested that humic substances could have formed complexes with lanthanum (La) from the LMB, rendering it unavailable for intercepting P over the course of the enclosure experiment. Residual lanthanum concentrations in combination dredging and LMB treatments exceeded the Dutch standard 10-fold. Total zooplankton abundance, and particularly Cladocera, increased in all enclosures over the course of the experiment. The limited effect of LMB in the enclosure experiment and the violation of the Dutch La standard when combined with dredging disqualify LMB as an intervention agent in the restoration of the pond. Full article
(This article belongs to the Special Issue Water Quality Monitoring and Modeling in Lakes)
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Open AccessArticle Variations in Spectral Absorption Properties of Phytoplankton, Non-algal Particles and Chromophoric Dissolved Organic Matter in Lake Qiandaohu
Water 2017, 9(5), 352; doi:10.3390/w9050352
Received: 14 March 2017 / Revised: 5 May 2017 / Accepted: 12 May 2017 / Published: 18 May 2017
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Abstract
Light absorption by phytoplankton, non-algal particles (NAP) and chromophoric dissolved organic matter (CDOM) was investigated at 90 sites of a clear, deep artificial lake (Lake Qiandaohu) to study natural variability of absorption coefficients. Our study shows that CDOM absorption is a
[...] Read more.
Light absorption by phytoplankton, non-algal particles (NAP) and chromophoric dissolved organic matter (CDOM) was investigated at 90 sites of a clear, deep artificial lake (Lake Qiandaohu) to study natural variability of absorption coefficients. Our study shows that CDOM absorption is a major contributor to the total absorption signal in Lake Qiandaohu during all seasons, except autumn when it has an equivalent contribution as total particle absorption. The exponential slope of CDOM absorption varies within a narrow range around a mean value of 0.0164 nm−1 ( s d = 0.00176 nm−1). Our study finds some evidence for thIS autochthonous production of CDOM in winter and spring. Absorption by phytoplankton, and therefore its contribution to total absorption, is generally greatest in spring, suggesting that phytoplankton growth in Lake Qiandaohu occurs predominantly in the spring. Phytoplankton absorption in freshwater lakes generally has a direct relationship with chlorophyll-a concentration, similar to the one established for open ocean waters. The NAP absorption, whose relative contribution to total absorption is highest in summer, has a spectral shape that can be well fitted by an exponential function with an average slope of 0.0065 nm−1 ( s d = 0.00076 nm−1). There is significant spatial variability present in the summer of Lake Qiandaohu, especially in the northwestern and southwestern extremes where the optical properties of the water column are strongly affected by the presence of allochthonous matter. Variations in the properties of the particle absorption spectra with depths provides evidence that the water column was vertically inhomogeneous and can be monitored with an optical measurement program. Moreover, the optical inhomogeneity in winter is less obvious. Our study will support the parameterization of the Bio-optical model for Lake Qiandaohu from in situ or remotely sensing aquatic color signals. Full article
(This article belongs to the Special Issue Water Quality Monitoring and Modeling in Lakes)
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Open AccessArticle Measuring the Aesthetic Value of Multifunctional Lakes Using an Enhanced Visual Quality Method
Water 2017, 9(4), 233; doi:10.3390/w9040233
Received: 1 February 2017 / Revised: 19 March 2017 / Accepted: 21 March 2017 / Published: 23 March 2017
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Abstract
Aesthetic value is an important factor that should be considered in lake environments. However, there is a lack of research examining and undertaking investigation of the aesthetic value of multifunctional lake ecosystems. There are two major purposes for this study: (1) to define
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Aesthetic value is an important factor that should be considered in lake environments. However, there is a lack of research examining and undertaking investigation of the aesthetic value of multifunctional lake ecosystems. There are two major purposes for this study: (1) to define and investigate the important perceived attributes related to the aesthetic value of multifunctional lakes using a video-questionnaire method and (2) to provide some suggestions for the further development of a visual quality index facilitating decision making in management and policies. An enhanced visual quality method was used in this study to record the conditions of the multifunctional lakes in each location in the study area. The findings of the study defined water color and clarity, percentage of water hyacinth, types of debris, percentage of debris, and facilities and land values as the important attributes related to aesthetic value in multifunctional lakes. In summary, the perceived attributes in the visual ecology criteria indicated more significant relationships with the functional morphology criteria than the financial profitability criteria. The results showed that the video-questionnaire method used in this study is efficient, easy to use, and understandable in terms of identifying and measuring aesthetic value in relation to perceptions of perceived attributes. Full article
(This article belongs to the Special Issue Water Quality Monitoring and Modeling in Lakes)
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