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Water color is an important representation reflecting the characteristics of its quality in inland lakes or ponds; however, sufficient water color image samples are often difficult to obtain due to the limitation of fishery production. For few color image samples, the existing data enhancement methods based on the depth generation model have the problems of low quality of generated data, difficulty of network training, and so on; moreover, for image classification, traditional methods based on convolutional neural network (CNN) cannot effectively extract the potential manifold structure features in the image and the full connection layer in CNN cannot simulate biological neurons well, resulting in high time cost and low efficiency. In this paper, a water quality classification method has been proposed to solve the above problems, the improved semisupervised triple-generation adversarial network (triple-GAN) algorithm is used to enhance the few water color image samples, and the feature data can then be extracted from enhanced data by manifold learning method t-distributed stochastic neighborhood embedding (t-SNE). Moreover, convolutional spiking neural network (CSNN), in which spiking neural network (SNN) has replaced the original full connection layer of CNN, is used for final water quality classification. The main contribution of this paper is to build a new algorithm framework, introduce triple-GAN and CSNN into the field of classification of few water color image samples for the first time, and make an exploration of integrating artificial intelligence (AI) and water quality analysis problems. By comparing with traditional methods, the proposed method is proved to have the advantages of less time-consuming, low operation cost, and high classification accuracy. [ABSTRACT FROM AUTHOR]

In a water treatment plant, the decision to carry out a jar test, for determining the required coagulant dosage, is made based on notable changes in treated water qualities such as treated water turbidity and color, which is essentially a reactive response to changes in water qualities. In addition, until a change that the operator deems as 'significant' occurs, the plant tends to use the same dosage determined previously using the jar test for an elongated period of time. In this study, artificial neural network (ANN) models were developed to proactively decide what coagulant dosages to use based on changes in raw water parameters. Use of ANNs also prevents the regular use of costly chemicals used for jar tests and enables responding to sudden changes in water qualities. The general regression neural network (GRNN) and extreme learning machine neural networks require minimal computational effort for model development as they involve minimal model parameters and their training algorithms are not iterative. The current study determines the more convenient and efficient model of the two for aiding the coagulation process. The GRNN and ELM-RBF models predicted test data with R values of 0.9737 and 0.9783, respectively. It was noted that the GRNN was prone to overfitting and the ELM-RBF model demonstrated higher generalization ability than the GRNN. Therefore, it was concluded that the ELM-RBF model was the more suitable model for the prediction of the coagulant dosage. [ABSTRACT FROM AUTHOR]

Water colour is the result of its constituents and their interactions with solar irradiance; this forms the basis for water quality monitoring using optical remote sensing data. The Forel-Ule Index (FUI) is a useful comprehensive indicator to show the water colour variability and water quality change in both inland waters and oceans. In recent decades, lakes around the world have experienced dramatic changes in water quality under pressure from both climate change and anthropogenic activities. However, acquiring consistent water colour products for global lakes has been a challenge. In this paper we present the first time series FUI dataset for large global lakes from 2000–2018 based on MODIS observations. This dataset provides significant information on spatial and temporal changes of water colour for global large lakes during the past 19 years. It will be valuable to studies in search of the drivers of global and regional lake colour change, and the interaction mechanisms between water colour, hydrological factors, climate change, and anthropogenic activities. Measurement(s) color Technology Type(s) satellite imaging Factor Type(s) temporal interval Sample Characteristic - Environment water body • lake Sample Characteristic - Location global Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13257218 [ABSTRACT FROM AUTHOR]

Rivers are among the most imperiled ecosystems globally, yet we do not have broad‐scale understanding of their changing ecology because most are rarely sampled. Water color, as perceived by the human eye, is an integrative measure of water quality directly observed by satellites. We examined patterns in river color between 1984 and 2018 by building a remote sensing database of surface reflectance, RiverSR, extracted from 234,727 Landsat images covering 108,000 kilometers of rivers > 60 m wide in the contiguous USA. We found 1) broad regional patterns in river color, with 56% of observations dominantly yellow and 38% dominantly green; 2) river color has three distinct seasonal patterns that were synchronous with flow regimes; 3) one third of rivers had significant color shifts over the last 35 years. RiverSR provides the first map of river color and new insights into macrosystems ecology of rivers. Plain Language Summary: Rivers can appear different colors such as blues, greens, browns, and yellows. Water color is linked to water quality and can be related to the amount of sediment, algae, and dissolved organic carbon in water. Humans can therefore discern waters' suitability for use with our eyes. While we know many rivers are impaired globally, often due to poor water quality, the color of rivers has not been widely measured to investigate changes through space and time. Satellites act as "eyes in the sky" and regularly observe earth's large rivers. Using satellite remote sensing records from 1984 to 2018, we measured the color of rivers across the USA. We found that large rivers have distinct seasonal patterns in color that change with river flow, and that the dominant color in one third of rivers has significantly changed. Observations of water color can pinpoint rivers undergoing rapid environmental change and work toward continental‐scale understanding of rivers. Key Points: ∼15.9 million satellite observations over 35 years show USA rivers (>60 m wide) are dominantly yellow and green in colorRiver color has three distinct seasonal patterns that are synchronous with flow regimesRiver color significantly changed over the last three decades in one third of large US rivers [ABSTRACT FROM AUTHOR]

Copyright of Revista Ambiente e Água is the property of Revista Ambiente e Agua and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Dissolved organic carbon (DOC) and iron (Fe) have been observed to be the important contributors to surface water brownification. Additionally, the DOC quality influences water color by forming Fe-DOC complexes that provide additive effects and is influenced by dominant land use type within watersheds. However, the influence of quantity and quality of DOC on Fe and water color is poorly understood in headwater streams. The aim of this study was to investigate the effects of DOC and Fe on water color in forest (FC) and pasture (GFC) fine-scale watersheds to remove the confounding effects of climate and soil parent material. Significant differences of DOC, Fe, and water absorbance at 420 nm (a420) between FC and GFC were found (p < 0.05). A dominant contribution to water color was from DOC (95.5 − 63.7%) with a decreasing trend when Fe increased from 0.011 to 0.258 mg L−1. There were no significant interactions between FC and GFC and Fe on either a420/DOC (p = 0.06) or specific ultraviolet absorbance at 254 nm (SUVA254) (p = 0.30). Increasing values of a420/DOC and SUVA254 were significantly associated with increasing Fe concentration (p < 0.01). Significant interactions were found between FC and GFC and Fe on spectral slope ratio (S ratio) (p < 0.01). The response rate of S ratio with increasing Fe per unit was 0.235 for GFC while it was − 11.043 for FC. These differences indicate that land use may change the quality of DOC, influence Fe-DOC interactions, and thus affect water color. Linking the effects of soil Fe and DOC and headwater Fe and DOC may help identify optimal management practice to mitigate surface water brownification. [ABSTRACT FROM AUTHOR]

The visual capacity of aquatic organisms is, in general, related to light penetration in the water. Therefore, aquatic environments that differ in color can potentially contribute to species polymorphism, especially in fish. In this study, we explore the relationship between light quality and intensity in water bodies and the eye and mouth size in Galaxias maculatus, one of the most widespread fish. Fish morphology was studied photographically, and the vertical attenuation coefficient of light (Kd) was measured in five aquatic systems: two humic lakes, two estuaries, and one river. Water color was also estimated as absorbance at 440 nm. In those environments with less light penetration and darker water color, we observed bigger eyes and, additionally, larger mouths. The darkness of water bodies was mainly related to water color associated with humic substances. As G. maculatus is known to be a visual predator, our results suggest that bigger eyes increase visual capacity in darker environments, which would result in improved feeding rates, also supported by larger mouth length. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central China Normal University is the property of Huazhong Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Laguna Lake is significant to its surrounding cities and municipalities as it serves multiple purposes: flood basin, aquaculture, water source for irrigation and domestic use, among others. Monitoring the lake's water quality is an integral part ensuring that the lake would continue to serve its purposes. Bio-optical modelling is a type of empirical model that relates the inherent optical properties of water to different biological properties like chlorophyll-a. The BOMBER (Bio-Optical Model Based tool for Estimating water quality and bottom properties from Remote sensing images) tool makes use of the different IOPs apparent optical properties (AOPs) of satellite images to be able to produce water quality maps. To localize the parameters used by the BOMBER tool, the use of WASI (The Water Color Simulator) tool was introduced. Inverting in situ spectral measurements of the lake, WASI tool was able to produce parameters localized for the lake. This research used 2018 Landsat 8 Images to produce images and used a water profiler to validate results. Results show the bio-optical model provided a R-squared value of 0.6912 and an RMSE of 2.43 μg/l which shows good correlation between the in-situ and the bio-optical model results. [ABSTRACT FROM AUTHOR]

Introduction: The application of remote-sensing techniques for water quality assessment has become increasingly popular in China. However, existing reviews are often limited to qualitative description and are quite fragmented. Outcomes: We conducted a quantitative systematic review to display current research status and identify the existing challenges and future directions. Our review revealed that the application of remote-sensing techniques in water quality research has expanded dramatically in China, but the spatial distribution is quite uneven. Second, the ground object spectrometer is the most widely applied data source. Water color indicators such as chlorophyll a and suspended solid are the most widely investigated in China. Third, semiempirical method is the most commonly used inversion method. Existing studies rarely considered the anthropogenic factors, which limited the model robustness and its application in human-dominated aquatic ecosystems. Discussion and Conclusion: We concluded that, in the past several decades, China has made notable progresses in monitoring and evaluation of water quality using the remote-sensing techniques (especially in inland lakes). We proposed that further improvements would be needed in terms of temporal and spatial coverage, indicator list, the incorporation of human–nature interactions, inversion accuracy, and model generalization. [ABSTRACT FROM AUTHOR]

The availability of freshwater is a prerequisite for municipal development and agricultural production, especially in the arid and semiarid portions of the western United States (U.S.). Agriculture is the leading user of water in the U.S. Agricultural water use can be partitioned into green (derived from rainfall) and blue water (irrigation). Blue water can be further subdivided by source. In this research, we develop a hydrologic balance by 8-Digit Hydrologic Unit Code using a combination of Soil and Water Assessment Tool simulations and available human water use estimates. These data are used to partition agricultural groundwater usage by sustainability and surface water usage by local source or importation. These predictions coupled with reported agricultural yield data are used to predict the virtual water contained in each ton of corn, wheat, sorghum, and soybeans produced and its source. We estimate that these four crops consume 480 km³ of green water annually and 23 km³ of blue water, 12 km³ of which is from groundwater withdrawal. Regional trends in blue water use from groundwater depletion highlight heavy usage in the High Plains, and small pockets throughout the western U.S. This information is presented to inform water resources debate by estimating the cost of agricultural production in terms of water regionally. This research illustrates the variable water content of the crops we consume and export, and the source of that water. [ABSTRACT FROM AUTHOR]

• The response of aquatic biological indicators to Acid Sulphate soils were studied. • Low pH and content metals were related to amount of AS soils in the catchment. • The assemblage structure of biological groups was strongly spatially structured. • Bioassessment metrics responded to low pH and high acidity differently. • Status assessment of AS rivers should be based on multiple biological elements. Land use in the Acid Sulphate (AS) soils induces metal and acidity pollution of aquatic ecosystems in coastal areas worldwide. Increasing utilization of AS soils poses increasing risks for deterioration of water bodies. We studied the effects of the coverage of AS soils, together with other catchment land cover attributes, on aquatic assemblages of fish, diatoms and benthic invertebrates in 42 sites along 15 lowland rivers in Finland during three subsequent years. Low pH and increasing content of several metals in the river water were related to high amount of AS soils in the catchment. Especially increasing iron content and water color were correlated to amount of forested areas in the catchment, whereas lower water color values and higher arsenic, chromium and iron concentrations were associated with wetlands. The assemblage structure of all three biological groups was strongly spatially structured among rivers and varied less temporally. The spatial structure of fish and diatoms were strongly affected by the acidic water, whereas invertebrates were more affected by low alkalinity and increasing concentrations of organic matter and iron. Especially fish and benthic invertebrate bioassessment metrics demonstrated for AS soil induced degradation in acidity by responding to low pH and high acidity, while the response from the diatoms index was weaker. The high metal concentrations alone did not seem to add to the degradation in biometrics without further increase in acidification. Our results highlight the importance of recognizing AS soil areas in the catchment to target the mitigation effects. A holistic approach in the mitigation of the adverse effects from AS soils is needed, using several mitigation methods in the catchment, and directing main efforts and protection from human disturbance to catchment areas with the highest proportion of AS soils. Our results suggest that status assessment of AS rivers should be based on multiple biological quality elements and that their metrics could be improved for better detection of impacts from acidity and metal pressures. The effects of metals and their concentrations on aquatic assemblages should be further examined. [ABSTRACT FROM AUTHOR]

Copyright of Arab Gulf Journal of Scientific Research is the property of Arabian Gulf University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Browning of inland waters has been noted over large parts of the Northern hemisphere and is a phenomenon with both ecological and societal consequences. The increase in water color is generally ascribed to increasing concentrations of dissolved organic matter of terrestrial origin. However, oftentimes the increase in water color is larger than that of organic matter, implying that changes in the concentration of organic matter alone cannot explain the enhanced water color. Water color is known to be affected also by the quality of organic matter and the prevalence of iron. Here we investigated trends in water color, organic matter and iron between 1972 and 2010 in 30 rivers draining into the Swedish coast (data from the national Swedish monitoring program), and performed a laboratory iron addition experiment to natural waters, to evaluate the role of iron and organic matter in determining water color. By comparing the effect of iron additions on water color in the experiment, to variation in water color and iron concentration in the monitoring data, we show that iron can explain a significant share of the variation in water color (on average 25 %), especially in the rivers in the north of Sweden (up to 74 %). Furthermore, positive trends for iron are seen in 27 of 30 rivers (21-468 %) and the increase in iron is larger than that of organic matter, indicating that iron and organic matter concentrations are controlled by similar but not identical processes. We speculate that increasing iron concentrations can be caused by changes in redox conditions, that mean that more anoxic water with high concentrations of soluble FeII are feeding into the surface waters. More studies are needed about why iron is increasing so strongly, since both causes and consequences are partly different from those of increasing organic matter content. [ABSTRACT FROM AUTHOR]

Summary: Water discolouration is one of the key water quality problems faced by UK water companies taking raw water from peatland catchments. A water colour model has been developed using a combined Geographical Information System and Multicriteria Evaluation approach. The model was used to predict water colour production potential based on key land management practices controlling colour production in UK upland catchments. Calibration of the model with historic data collected at water treatment works treating water from upland areas showed that the model was potentially capable of accurately predicting water colour production potential at the catchment scale (c. 90%). Subsequent validation has shown this to be the case. Rotational heather burning and vegetation type (particularly heather) were identified as the two most statistically significant variables influencing water colour generation in the study catchments. It was predicted that colour is generated in particular hotspots and management to improve water quality should, therefore, focus on such areas. Blending of water is also an important process in controlling colour at the catchment scale and at water treatment works, with high colour often being diluted by runoff from land elsewhere in the catchment with lower potential to generate colour. [ABSTRACT FROM AUTHOR]

Abstract: Water quality around the Island of Borneo is important for the coral reefs in Borneo''s proximity. Sediment input into freshwater and marine ecosystems is a result of natural processes. However, mining, deforestation, poor agricultural practices can greatly increase sediment input into aquatic systems. According to time series analysis of the coastal waters around Borneo, water quality has worsened in the last 8 years. This short study analyzes and illustrates the particular year-to-year changes in the relevant waters using MERIS data from 2003-2010, as well as for the entire 8-year period. Changes in the statistical characteristics of the water surface variables, yellow substance (colored dissolved organic matter) and total suspended matter, in Borneo''s coastal waters can be seen. The intra-annual variables derived include minimum, maximum, standard deviation and average. The interesting inter-annual variables investigated are slopes of the mentioned water quality characteristics over a period of 8 years around Borneo, which changed since 2003 and decreases for most of the Island of Bro. According to this study, further land development on the island of Borneo will further decrease water quality around Borneo and worsen conditions for coral reefs and other coastal ecosystems. This study also illustrates the utility and prowess of the open source programs BEAM, GRASS and R. [Copyright &y& Elsevier]

One feature of volcanic lakes influenced by subaqueous fumaroles existing at lake bottoms (called active crater lakes) is the remarkable color of their waters: turquoise or emerald green. The active crater lake named Yudamari at Mt. Nakadake of Aso volcano, Japan, takes on a milky pale blue-green. The particular blue component of the lake water color results from Rayleigh scattering of sunlight by very fine aqueous colloidal sulfur particles; the green component is attributable to absorption of sunlight by dissolved ferrous ions. An objective color observation conducted during 2000–2007 revealed that the lake water color changed from blue-green to solid green. The disappearance of the blue ingredient of the water color will result in diminution of aqueous colloidal sulfur from chemical analyses of lake waters sampled simultaneously. The aqueous sulfur is produced by the reaction of sulfur dioxide and hydrogen sulfide supplied from subaqueous fumaroles. However, its production efficiency decreases by domination of sulfur dioxide in the subaqueous fumarolic sulfur gas species with increasing subaqueous fumarolic temperature. The disappearance of blue ingredients from the blue-green color of the lake water may be attributed to activation of subaqueous fumarole activity. [ABSTRACT FROM AUTHOR]

Abstract: The transfer of carbon from terrestrial peat to the fluvial environment forms an important component of the peatland carbon cycle, and has major implications for water quality. Dissolved organic carbon (DOC) is generally considered the largest constituent of aquatic carbon and tends to be the most intensively monitored, particularly in peatland catchments. However, many long-term records for DOC are based on proxy studies that use water colour as a surrogate. This paper tests the robustness of using spectrophotometric techniques to monitor water colour, based on absorbance from a single wavelength at 400nm, as a surrogate for true DOC determination. The general ability of spectrophotometric analysis to measure low DOC concentrations depends on the calibration used; thus, the minimum mass of DOC detectable varies considerably and in this study was found to be as high as 10.32mg C L−1. While there is often a significant correlation between water colour and DOC, it was found that the use of single or even “pooled” regressions to predict DOC concentrations could result in miscalculations of more than 50%. Further, the water colour–DOC relationship in blanket peat pore waters was found to vary significantly between peat layers, land management treatments and through time. Thus, studies using long-term water colour records as a proxy for long-term DOC concentrations in peatlands must be treated with a certain degree of caution, especially in cases where changes may have taken place to DOC production, such as those caused by land management change, during the course of investigation. [ABSTRACT FROM AUTHOR]

Summary: Peatlands are important terrestrial carbon stores but their environmental degradation has led to concerns of increased carbon loss. Many peatlands have been drained using open ditches and this practice has been associated with enhanced dissolved organic carbon loss and water discolouration. Recent peatland restoration schemes have therefore included the blocking of peatland drains as a strategy for environmental improvement. However, it is not clear whether drain-blocking consistently reduces dissolved organic carbon loads and water discolouration because many peats undergo significant physical and chemical change when they are disturbed. Previous studies investigating the impact of drain-blocking on water colour and dissolved organic carbon have been restricted to a limited spatial and temporal research framework. This study combines an extensive UK-wide survey of blocked and unblocked drains across 32 study sites and intensive monitoring of a peat drain system that has been blocked for 7years. Dissolved organic carbon concentrations and water discolouration were significantly lower in blocked drains: the mean dissolved organic carbon concentration of water sampled from blocked drains was 28% less than that sampled from unblocked drains. However, this pattern was not consistent at all sites. At the intensive monitoring site no significant differences could be observed in total dissolved organic carbon flux from the fully instrumented blocked and unblocked drains: the blocked drain exported 31,592kgkm−2 yr−1 and the unblocked drain 30,123kgkm−2 yr−1. Results from bi-weekly grab samples from other drains at the intensively monitored site, however, did conform to the general national pattern of lower dissolved organic carbon and discolouration in blocked drains. The results demonstrate that drain-blocking can be an effective management strategy for reducing DOC loss and water discolouration in disturbed peat catchments. The caveat remains, however, that there will be a number of sites where no significant change will occur. [Copyright &y& Elsevier]

Proper selection of appropriate treatment processes for surface water supplies is a function of raw water quality including particles and natural organic matter (NOM). This paper presents an updated foundation for process selection based on routinely measured parameters of particles (turbidity) and organic matter content (UV254, color and TOC). The distinction between mineral and non-mineral turbidity is addressed. Processes considered include direct filtration, conventional sedimentation, dissolved air flotation and contact clarification. The results of this paper are based on a survey of currently operating facilities, pilot studies, theory and North American experience. Recommended guidelines for process selection as a function of raw water TOC, color and turbidity are presented. Figures to aid process selection based on source water quality are provided. [ABSTRACT FROM AUTHOR]

Summary: This study considers long-term records of the nature of water colour and coincident water quality and quantity in order to test hypotheses about increases in release of dissolved organic carbon from peat soils across the northern hemisphere. The study focuses upon the treatment ratio, i.e. the ratio of the amount of coagulant dose required to the water colour of the incoming water, and compares this ratio to possible explanatory variables: pH, conductivity, water temperature, river flow and alkalinity. The study shows that: [(i)] The annual average increase in treatment ratio is just less than 6.5% over a six year period. [(ii)] There is a long-term increase in the treatment ratio that is independent of changes in riverflow, pH, conductivity, water temperature and alkalinity and so a real change in DOC composition is occurring. [(iii)] There is a seasonal cycle in treatment ratio that is also independent of the available water and climate variables. [(iv)] The upward trend in treatment ratio is declining with time over the study period. The observed trends in DOC composition are consistent with an explanation of increasing DOC concentration and flux based upon changes in flow and temperature but is not consistent with present explanations based upon changes in atmospheric deposition or upon drought unless the effect of the drought are short-lived (1–2 years). [Copyright &y& Elsevier]

• Artificial ditching of catchments accelerates lake brownification. • Effect of ditching is strongest in catchments with high peatland coverage. • Effect of ditching is stronger for water color than for DOC concentrations. • Ditching affects water color mainly through its impact on Fe concentrations. • Ditching tends to increase water color: DOC ratio of lake waters. We studied the connections between lake water quality and the density of artificial ditching in lake catchments. Water color and the concentrations of dissolved organic carbon (DOC) and iron (Fe) in lake water increased with increasing ditch density. Additionally, the water color:DOC ratio increased along a ditch density gradient because ditching had a stronger effect on color than on DOC. This was mainly due to the positive effect of ditching on the Fe concentration in lakes. Color:DOC ratio was strongly dependent on Fe up to Fe concentrations of 1–1.5 mg L−1. Thus, the water color of lakes with Fe concentrations < 1 mg L−1 will respond especially strongly to the effects of catchment ditching. The effects of ditching were strongest in catchments with high peatland coverage due to their high ditch density and high storage of organic carbon and Fe. The long-lasting effects of ditching should be taken into account when studying the factors governing lake brownification. [Display omitted] [ABSTRACT FROM AUTHOR]

Developments in digital image acquisition technologies and citizen science lead to more water color observations and broader public participation in environmental monitoring. However, the implications of the use of these simple water color indices for water quality assessment have not yet been fully evaluated. In this paper, we build a low-cost digital camera colorimetry setup to investigate quantitative relationships between water color indices and concentrations of optically active constituents (OACs). As proxies for colored dissolved organic matter (CDOM) and phytoplankton, humic acid and algae pigments were used to investigate the relationship between water chromaticity and concentration. We found that the concentration fits an ascending relationship with xy chromaticity values and a descending relationship with hue angle. Our investigations permitted us to increase the information content of simple water color observations, by relating them to chemical constituent concentrations in observed waters. [ABSTRACT FROM AUTHOR]

Rainbow River is the fourth largest spring-fed river in Florida and is known for its outstanding water clarity, high rate of spring discharge, and recreational use. However, nitrate concentrations in the spring headwaters have increased 15-fold between 1957 and 2006 - from 0.08 mg L-1 to 1.22 mg L-1. More recently, a significant increase in chlorophyll a and decline in water transparency have been noted downstream of the springs. In a year-long study of phytoplankton, we found that the 79 taxa were similar to those of other spring-fed rivers, with pennate and centric diatoms dominating. The annual mean phytoplankton biovolumes at the six sampling stations ranged from 0.101 μL L-1 (Jan. 2004) to 0.349 μL L-1 (Jan. 2005). Three minor blooms occurred at downstream stations with species of Navicula and Synedra in May (0.348 μL L-1), Fragilaria in September (0.272 μL L-1), and Cycloteila and Navicula in January (1.190 μL L-1). The decrease in water transparency and an increase in chlorophyll a downstream, shown by a parallel study, correlated significantly with an increase in phytoplankton that in turn was related to the volume of discharge during the year. During the dry season, lower discharge rates increased the water residence time in the main channel and increased phytoplankton biovolume. It appears that further increases in nutrients and the possibility of lower discharges from the headwater springs will probably result in increased chlorophyll a, more phytoplankton blooms, and additional decreases in water clarity downstream. [ABSTRACT FROM AUTHOR]

In order to acquire inherent optical properties to serve the lake water colour/quality remote sensing in Taihu Lake 67 samples were distributed almost all over the lake. Surface water samples were collected and returned to the laboratory for the subsequent processing and analysis. In the laboratory, the absorptions due to the total particulate matter, non‐algal particulate matter, phytoplankton pigment, and CDOM, together with their concentrations were measured and/or calculated, respectively. Then their absorption properties were analysed and compared with those of other lake waters and/or coastal/open waters. Some different and similar characteristics were uncovered. On the one hand, it provides not only a solid basement for the Taihu Lake water colour/quality remote sensing with semi‐analytical/analytical approach but also a typical case for inherent optical properties of case two water especially for inland freshwater lakes. On the other, it is very helpful to improve the practical and intensive application and development of remote sensing in monitoring lake water quality. [ABSTRACT FROM AUTHOR]

Discoloration of potable water supplied to customer taps is one of the biggest causes of water quality related customer complaints. At present, understanding of the fundamental processes that cause discoloration is limited and the modeling of events unfeasible. This paper describes the development, verification, and validation of a novel cohesive transport modeling approach to simulate discoloration within distribution systems. The model is based on the principal that strength characteristics of fine particulate material accumulated at the pipe walls are conditioned by the shear stress of the usual daily hydraulics. Discoloration occurs when the flow through the systems changes, exceeding the peak daily value. Fieldwork results from two sites are presented in detail: Site 1 demonstrates model application including sensitivity and parameter dependence, while data from Site 2 is used to investigate the hypothesis that daily hydraulic forces condition the material layers within the pipes. Model simulations are also presented for a selection of other field sites to demonstrate the wider applicability of the model. [ABSTRACT FROM AUTHOR]

The primary, most obvious parameter indicating water quality is the color of the water. Not only can it be aesthetically disturbing, but it can also be an indicator of contamination. Clean, high-quality water is a valuable, essential asset. Of the available technologies for removing dyes, adsorption is the most used method due to its ease of use, cost-effectiveness, and high efficiency. The adsorption process is influenced by several parameters, which are the basis of all laboratories researching the optimum conditions. The main objective of this review is to provide up-to-date information on the most studied influencing factors. The effects of initial dye concentration, pH, adsorbent dosage, particle size and temperature are illustrated through examples from the last five years (2017–2021) of research. Moreover, general trends are drawn based on these findings. The removal time ranged from 5 min to 36 h (E = 100% was achieved within 5–60 min). In addition, nearly 80% efficiency can be achieved with just 0.05 g of adsorbent. It is important to reduce adsorbent particle size (with Φ decrease E = 8–99%). Among the dyes analyzed in this paper, Methylene Blue, Congo Red, Malachite Green, Crystal Violet were the most frequently studied. Our conclusions are based on previously published literature. [ABSTRACT FROM AUTHOR]

Different methods are available for retrieving chlorophyll-a (Chl-a) in inland waters from optical imagery, but there is still a need for an inter-comparison among the products. Such analysis can provide insights into the method selection, integration of products, and algorithm development. This work aims at inter-comparison and consistency analyses among the Chl-a products derived from publicly available methods consisting of Case-2 Regional/Coast Colour (C2RCC), Water Color Simulator (WASI), and OC3 (3-band Ocean Color algorithm). C2RCC and WASI are physics-based processors enabling the retrieval of not only Chl-a but also total suspended matter (TSM) and colored dissolved organic matter (CDOM), whereas OC3 is a broadly used semi-empirical approach for Chl-a estimation. To pursue the inter-comparison analysis, we demonstrate the application of Sentinel-2 imagery in the context of multitemporal retrieval of constituents in some Italian lakes. The analysis is performed for different bio-optical conditions including subalpine lakes in Northern Italy (Garda, Idro, and Ledro) and a turbid lake in Central Italy (Lake Trasimeno). The Chl-a retrievals are assessed versus in situ matchups that indicate the better performance of WASI. Moreover, relative consistency analyses are performed among the products (Chl-a, TSM, and CDOM) derived from different methods. In the subalpine lakes, the results indicate a high consistency between C2RCC and WASI when a C D O M (440) < 0.5 m−1, whereas the retrieval of constituents, particularly Chl-a, is problematic based on C2RCC for high-CDOM cases. In the turbid Lake Trasimeno, the extreme neural network of C2RCC provided more consistent products with WASI than the normal network. OC3 overestimates the Chl-a concentration. The flexibility of WASI in the parametrization of inversion allows for the adaptation of the method for different optical conditions. The implementation of WASI requires more experience, and processing is time demanding for large lakes. This study elaborates on the pros and cons of each method, providing guidelines and criteria on their use. [ABSTRACT FROM AUTHOR]

A new era of spaceborne hyperspectral imaging has just begun with the recent availability of data from PRISMA (PRecursore IperSpettrale della Missione Applicativa) launched by the Italian space agency (ASI). There has been pre-launch optimism that the wealth of spectral information offered by PRISMA can contribute to a variety of aquatic science and management applications. Here, we examine the potential of PRISMA level 2D images in retrieving standard water quality parameters, including total suspended matter (TSM), chlorophyll-a (Chl-a), and colored dissolved organic matter (CDOM) in a turbid lake (Lake Trasimeno, Italy). We perform consistency analyses among the aquatic products (remote sensing reflectance (Rrs) and constituents) derived from PRISMA and those from Sentinel-2. The consistency analyses are expanded to synthesized Sentinel-2 data as well. By spectral downsampling of the PRISMA images, we better isolate the impact of spectral resolution in retrieving the constituents. The retrieval of constituents from both PRISMA and Sentinel-2 images is built upon inverting the radiative transfer model implemented in the Water Color Simulator (WASI) processor. The inversion involves a parameter (gdd) to compensate for atmospheric and sun-glint artifacts. A strong agreement is indicated for the cross-sensor comparison of Rrs products at different wavelengths (average R ≈ 0.87). However, the Rrs of PRISMA at shorter wavelengths (<500 nm) is slightly overestimated with respect to Sentinel-2. This is in line with the estimates of gdd through the inversion that suggests an underestimated atmospheric path radiance of PRISMA level 2D products compared to the atmospherically corrected Sentinel-2 data. The results indicate the high potential of PRISMA level 2D imagery in mapping water quality parameters in Lake Trasimeno. The PRISMA-based retrievals agree well with those of Sentinel-2, particularly for TSM. [ABSTRACT FROM AUTHOR]

True water color (TWC) is an important water quality indicator. However, despite many efforts for standardization of methods for TWC determination, there is still no consistency between visual and spectroscopic techniques. This study demonstrates that standard spectroscopic methods overestimate visual data from 21 to 47%, depending on methods involved. To retrieve relevant true water color values from spectral data, a new spectroscopic method is proposed. The method is based on the mathematical model of color perception by the standard observer implementing the dE2000 color difference in the L∗a∗b color space as calculated between blank and water samples. The method showed good agreement with the visual methods (comparator method and determination in Nessler cylinders) and the mean values between these methods. The mean relative difference between the proposed method and the mean of the two visual methods is only 2%. The method precision is independent from TWC in all measurement ranges and has S r 0.3 mgPt-Co L−1 (df = 98), which is at least three times lower than for the standard methods. As such, it shows higher accuracy and precision. As a result, the proposed method can be used for TWC determination in environmental samples from 3.3 to 500 mgPt-Co L−1 with SD 0.3 mgPt-Co L−1 in all measuring ranges, making sample dilution unnecessary. Image 1 • Existed spectroscopic methods overestimates visual water color determination (21–47%). • New spectroscopic method for true color determination in natural water is proposed. • Method is based on mathematical model of the standard observer color perception. • Proposed method show high agreement with visual methods (mean relative difference 2%). [ABSTRACT FROM AUTHOR]

The recent and continuous development of unmanned aerial vehicles (UAV) and small cameras with different spectral resolutions and imaging systems promotes new remote sensing platforms that can supply ultra-high spatial and temporal resolution, filling the gap between ground-based surveys and orbital sensors. This work aimed to monitor siltation in two large rural and urban reservoirs by recording water color variations within a savanna biome in the central region of Brazil using a low cost and very light unmanned platform. Airborne surveys were conducted using a Parrot Sequoia camera (~0.15 kg) onboard a DJI Phantom 4 UAV (~1.4 kg) during dry and rainy seasons over inlet areas of both reservoirs. Field measurements of total suspended solids (TSS) and water clarity were made jointly with the airborne survey campaigns. Field hyperspectral radiometry data were also collected during two field surveys. Bio-optical models for TSS were tested for all spectral bands of the Sequoia camera. The near-infrared single band was found to perform the best (R2: 0.94; RMSE: 7.8 mg L−1) for a 0–180 mg L−1 TSS range and was used to produce time series of TSS concentration maps of the study areas. This flexible platform enabled monitoring of the increase of TSS concentration at a ~13 cm spatial resolution in urban and rural drainages in the rainy season. Aerial surveys allowed us to map TSS load fluctuations in a 1 week period during which no satellite images were available due to continuous cloud coverage in the rainy season. This work demonstrates that a low-cost configuration allows dense TSS monitoring at the inlet areas of reservoirs and thus enables mapping of the sources of sediment inputs, supporting the definition of mitigation plans to limit the siltation process. [ABSTRACT FROM AUTHOR]

Rapid and widespread monitoring of inland and coastal water quality occurs through the use of remote sensing and near-surface water quality sensors. A new addition is the development of smartphone applications (Apps) to measure and record surface reflectance, water color and water quality parameters. In this paper, we present a field study of the HydroColor (HC, measures RGB reflectance and suspended particulate matter (SPM)) and EyeOnWater (EoW, determines the Forel–Ule scale—an indication to the visual appearance of the water surface) smartphone Apps to evaluate water quality for inland waters in Eastern Australia. The Brisbane river, multiple lakes and reservoirs and lagoons in Queensland and New South Wales were visited; hyperspectral reflection spectra were collected and water samples were analysed in the laboratory as reference. Based on detailed measurements at 32 sites, covering inland waters with a large range in sediment and algal concentrations, we find that both water quality Apps are close, but not quite on par with scientific spectrometers. EoW is a robust application that manages to capture the color of water with accuracy and precision. HC has great potential, but is influenced by errors in the observational procedure and errors in the processing of images in the iPhone. The results show that repeated observations help to reduce the effects of outliers, while implementation of camera response functions and processing should help to reduce systematic errors. For both Apps, no universal conversion to water quality composition is established, and we conclude that: (1) replicated measurements are useful; (2) color is a reliable monitoring parameter in its own right but it should not be used for other water quality variables, and; (3) tailored algorithms to convert reflectance and color to composition could be developed for lakes individually. [ABSTRACT FROM AUTHOR]

The Secchi disk depth (ZSD, m) has been used globally for many decades to represent water clarity and an index of water quality and eutrophication. In recent studies, a new theory and model were developed for ZSD, which enabled its semi-analytical remote sensing from the measurement of water color. Although excellent performance was reported for measurements in both oceanic and coastal waters, its reliability for highly turbid inland waters is still unknown. In this study, we extend this model and its evaluation to such environments. In particular, because the accuracy of the inherent optical properties (IOPs) derived from remote sensing reflectance (Rrs, sr−1) plays a key role in determining the reliability of estimated ZSD, we first evaluated a few quasi-analytical algorithms (QAA) specifically tuned for turbid inland waters and determined the one (QAATI) that performed the best in such environments. For the absorption coefficient at 443 nm (a(443), m−1) ranging from ~0.2 to 12.5 m−1, it is found that the QAATI-derived absorption coefficients agree well with field measurements (r2 > 0.85, and mean absolute percentage difference (MAPD) smaller than ~39%). Furthermore, with QAATI-derived IOPs, the MAPD was less than 25% between the estimated and field-measured ZSD (r2 > 0.67, ZSD in a range of 0.1–1.7 m). Furthermore, using matchup data between Rrs from the Medium Resolution Imaging Spectrometer (MERIS) and in-situ ZSD, a similar performance in the estimation of ZSD from remote sensing was obtained (r2 = 0.73, MAPD = 37%, ZSD in a range of 0.1–0.9 m). Based on such performances, we are confident to apply the ZSD remote sensing scheme to MERIS measurements to characterize the spatial and temporal variations of ZSD in Lake Taihu during the period of 2003–2011. [ABSTRACT FROM AUTHOR]

Due to the growing significance of water quality degradation by non-point source (NPS) pollution, regions in which NPS management is required should be designated as the management areas. Relevant management measures should be established to control water quality items related to degradation. It is advantageous that the area where the water environment is negatively affected by NPS is provided with legal grounds for NPS management, namely the designation of an NPS management area. This is because if it is designated as an NPS management area, the government can support the budget necessary for the installation of non-point pollution reduction facilities. In order to effectively utilize the limited budget, it is necessary to select and concentrate the area that should be managed first in the NPS management area. For the efficiency of the NPS pollution management within a management region, priority locations or key management sub-regions should be determined to implement differential management plans. Also, in selecting priority management regions, evaluation factors that can reflect the effects of NPS, such as the water quality target excess ratio in the mid-level region (or the total maximum daily load (TMDL) management) which includes the target region (low-level region), the NPS load in land, and non-permeable area ratio, should be quantified and the management order should be defined. Since NPS has local characteristics, the management items should be determined based on turbidity, suspended solid (SS), or total phosphorus (TP) that affect the local water quality. When the water environment is polluted due to non-point pollutants, various materials such as turbidity, SS, TP, Escherichia coli, and heavy metals can be set as management items according to local characteristics. However, the most important items to be managed are turbidity, SS, and TP, because if the solid (SS) is present in the water, which is highly turbid and does not sink easily, people can feel unpleasant and feel that the water is not clean, even if they do not analyze the water quality. In addition, in the case of TP, nutrients accumulated in the land are introduced into the river by rainfall, causing eutrophication. People feel uncomfortable because it changes the water color. Other pollutants can only be found to be contaminated after water quality analysis is performed. The water quality target of the management items should be set realistically, based on the situation of the watershed by considering the watershed model, management flow, NPS pollutant reduction plan, the river flow in the management area, and load. All these reflect the characteristics of the region. To evaluate whether the water quality target is achieved after NPS management, a method similar to the one to set the water quality target should be used to review the performance of the management plan. This study introduces specific examples of key factors in establishing an NPS management plan, including consideration factors and methods for the designation of NPS management regions, consideration factors and the selection method for key management areas within a management region, the selection method of management items, the selection method of the water quality target, and an evaluation method of the water quality target. [ABSTRACT FROM AUTHOR]