Search

Remote sensing for water quality evaluation has advanced, with more satellites providing longer data series. Validations of remote sensing-derived data for water quality characteristics, such as chlorophyll-a, Secchi depth, and turbidity, have often remained restricted to small numbers of water bodies and have included local calibration. Here, we present an evaluation of > 100 water bodies in Germany covering different sizes, maximum depths, and trophic states. Data from Sentinel-2 MSI and Sentinel-3 OLCI were analyzed by two processing chains. Our work focuses on analysis of the accuracy of remote sensing products by comparing them to a large in situ data set from governmental monitoring from 13 federal states in Germany and, hence, achieves a national scale assessment. We quantified the fit between the remote sensing data and in situ data among processing chains, satellite instruments, and our three target water quality variables. In general, overall regressions between in situ data and remote sensing data followed the 1:1 regression. Remote sensing may, thus, be regarded as a valuable tool for complementing in situ monitoring by useful information on higher spatial and temporal scales in order to support water management, e.g., for the European Water Framework Directive (WFD) and the Bathing Water Directive (BWD). [ABSTRACT FROM AUTHOR]

Thayer J, Enloe S, Prince C, MacDonald G, Leary J. 2024. Spatial-temporal shifts in submersed aquatic vegetation community structure resulting from a selective herbicide treatment in Lake Sampson, Florida, USA. Lake Reserv Manage. 40:248–263. Submersed aquatic vegetation (SAV) is a major ecological component of Florida's shallow lake systems. Hydrilla (H; Hydrilla verticillata [L.F.] Royle) is a nonnative, invasive SAV dominating many of these lakes and a high management priority in conservation. Lake Sampson is a shallow 776-ha lake in north Florida dominated by hydrilla since the 1980s, with native Illinois pondweed (P; Potamogeton illinoensis Morong) and American eelgrass (V; Vallisneria americana Michx.) historically represented. In March 2021, an in-water treatment of the herbicide florpyrauxifen-benzyl was administered to the littoral zone covering 46% of the lake surface. Five months after treatment (MAT), H infestations were reduced by 99%, recruitment by 69%, and invasions to cohabitating native populations by 90%. Conversely, total combined P populations increased occupancy from 15% to 23%, while V populations exhibited only a slight decrease in occupancy, going from 19% to 18%. By 17 MAT, hydrilla infestations, recruits, and invasions had all increased, while native populations started to retract from earlier gains. Moreover, surveys revealed a significant shift in SAV communities to shallower depths that were immediate 1 month after treatment and sustained 17 months later with the posttreatment reduction of hydrilla exclusively occupying deeper water. Posttreatment changes in water quality were apparent and possibly influential to SAV community dynamics. Although this in-water herbicide treatment exhibited good selectivity and reduced hydrilla competition, unintended side effects in water quality may have impeded the long-term succession of resilient native SAV communities that could compete with the recovery of hydrilla. [ABSTRACT FROM AUTHOR]

Remote sensing for water quality evaluation has advanced, with more satellites providing longer data series. Validations of remote sensing-derived data for water quality characteristics, such as chlorophyll-a, Secchi depth, and turbidity, have often remained restricted to small numbers of water bodies and have included local calibration. Here, we present an evaluation of > 100 water bodies in Germany covering different sizes, maximum depths, and trophic states. Data from Sentinel-2 MSI and Sentinel-3 OLCI were analyzed by two processing chains. Our work focuses on analysis of the accuracy of remote sensing products by comparing them to a large in situ data set from governmental monitoring from 13 federal states in Germany and, hence, achieves a national scale assessment. We quantified the fit between the remote sensing data and in situ data among processing chains, satellite instruments, and our three target water quality variables. In general, overall regressions between in situ data and remote sensing data followed the 1:1 regression. Remote sensing may, thus, be regarded as a valuable tool for complementing in situ monitoring by useful information on higher spatial and temporal scales in order to support water management, e.g., for the European Water Framework Directive (WFD) and the Bathing Water Directive (BWD).

Water clarity has long been used as a visual indicator of the condition of water quality. The clarity of waters is generally valued for esthetic and recreational purposes. Water clarity is often assessed using a Secchi disk attached to a measured line and lowered to a depth where it can be no longer seen. We have applied an approach which uses atmospherically corrected Landsat 8 data to estimate the water clarity in freshwater bodies by using the quasi-analytical algorithm (QAA) and Contrast Theory to predict Secchi depths for more than 270 lakes and reservoirs across the continental US. We found that incorporating Landsat 8 spectral data into methodologies created to retrieve the inherent optical properties (IOP) of coastal waters was effective at predicting in situ measures of the clarity of inland water bodies. The predicted Secchi depths were used to evaluate the recreational suitability for swimming and recreation using an assessment framework developed from public perception of water clarity. Results showed approximately 54% of the water bodies in our dataset were classified as “marginally suitable to suitable” with approximately 31% classed as “eminently suitable” and approximately 15% classed as “totally unsuitable–unsuitable”. The implications are that satellites engineered for terrestrial applications can be successfully used with traditional ocean color algorithms and methods to measure the water quality of freshwater environments. Furthermore, operational land-based satellite sensors have the temporal repeat cycles, spectral resolution, wavebands, and signal-to-noise ratios to be repurposed to monitor water quality for public use and trophic status of complex inland waters. [ABSTRACT FROM AUTHOR]

The rate of attenuation of sun rays in water is much faster than in the atmosphere. This rate of attenuation also varies in different water bodies due to n number of factors. Therefore, transparency is a significant environmental factor for a given water body. The thickness of illuminated layer of water is called euphotic layer or Zeuph. It represents the layer of water that has 1% of surface irradiance. Zeuph determines the rate of photosynthesis, occurrence of phytoplankton, and zooplankton. The conversion of sus's energy into biomass takes place in this layer. This energy then gets transferred to the lower aphotic zone of the water body. Therefore, modelling of this layer holds great environmental significance. Various methods of remote sensing have come into usage as practical ones for the inaccessible or extensively large areas. Still the first-hand field surveys have been proven most accurate methods. Thus, in the present study, an attempt was made to use first-hand Secchi depth data for modelling Zeuph using Secchi disk of four major lakes of Kumaun region naming Nainital, Bhimtal, Sattal, and Naukuchiyatal. Volume of Zeuph of each of the candidate lakes in relation to the lake's total volume is also estimated in order to estimate which lake has most photosynthetically active layer and it was found that Sattal is most active lake in terms of photosynthesis with roughly 10% volume as Zeuph while Bhimtal is found least active in this regard. The present study is considered as a novel study because first time this methodology has been applied to identified photosynthetically active euphotic layer in aforementioned lakes. An attempt is also made to examine the relationship between secchi depth and distance from the lake bank. [ABSTRACT FROM AUTHOR]

Using a dataset of more than 51,000 US lakes, we estimated the relationship between summertime lake visits, lake water clarity, landscape features, and other amenities, where visits were estimated with counts of geo‐located photographs. Given the size and complexity of our dataset, we used a combination of machine learning techniques, imputation techniques, and a Poisson count model to estimate these relationships. We found that every additional meter of average summertime Secchi depth was associated with at least 7% more summertime lake visits, all else equal. Second, we found that lake amenities, such as beaches, boat launches, and public toilets, were more powerful predictors of visits than water clarity. Third, we found that visits to a lake were strongly influenced by the lake's accessibility and its distance to nearby lakes and the amenities the nearby lakes offered. Our research highlights the need for (1) a better understanding of how representative social media data are of actual recreational behavior, (2) the development of best practices to account for nonrandom patterns in missing natural feature data, and (3) a better understanding of the potential endogeneity in the lake visit–water quality relationships. [ABSTRACT FROM AUTHOR]

Secchi depth (SD) is a valuable and feasible water quality indicator of lake eutrophication. The establishment of an automated system with efficient image processing and an algorithm suitable for the inversion of transparency in lake-rich regions could provide sufficient temporal and spatial information for lake management. These are especially critical for lake-rich regions where in situ monitoring data are scarce. This study demonstrated the implementation of an atmospheric correction algorithm (ACOLITE algorithm) in conjunction with the Google Earth Engine platform to generate remote-sensing reflectance products of specific points efficiently. The study also evaluated the performance of an algorithm for inverting lake SDs in Yunnan Plateau lakes, which is one of the five lake districts in China, since there is a lack of in situ data for most of the lakes in the region. The in situ data from four lakes with large SD ranges and imagery from Landsat Operational Land Imager were used to train and evaluate the performance of two algorithms: an empirical algorithm (stepwise regression) and machine learning (support vector machines and multi-layer perception). The results revealed that the retrieval accuracy of models with bands and band ratio combinations could be substantially improved compared with models with a single band or band combinations. A negative correlation was also observed between the temporal match between observations and the model accuracy. This study found that the MLP model with sufficient training data was more suitable for transparency estimation of lakes belonging to the dataset; the SVM model was more suitable for transparency prediction outside the training set, regardless of the adequacy of the training data. This study provides a reference for monitoring lakes within the Yunnan region using remote sensing. [ABSTRACT FROM AUTHOR]

The Trophic State Index (TSI), based on chlorophylla [TSI(Chla)], Secchi depth [TSI(SD)], total nitrogen [TSI(TN)], and total phosphorus [TSI(TP)], is a popular tool for lake eutrophication assessment worldwide, higher TSI scores implicitly indicate increased intensity of algal blooms. However, the application of TSI across diverse lakes may be questionable since the precondition of SD, TN, and TP as indicators of algal blooms lies in the fact that SD is dominated by algal turbidity; Chla in all lakes respond the same (or very similarly) to changes in TN (or TP) concentrations. Herein, 120 natural lakes and artificial reservoirs with a wide range of morphological, physicochemical, and Chla variables in the Chinese Eastern Plains ecoregion were collected via data mining to elaborate the utility of TSI on a regional scale. Moreover, we analyzed the source of uncertainties of TSI(SD), TSI(TN), and TSI(TP) in indicating algal biomass. Our results demonstrated that the TSI(SD), TSI(TN), and TSI(TP) scores were different with those of the TSI(Chla) (approximately 10 scores deviations). Considering 10 scores represent a doubling in algal biomass, the direct use of TSI may cause the misestimation of algal blooms intensity and under- or over-protection of the lakes and reservoirs. Furthermore, our results revealed water depth (WD, m) is the key inner-regional factor affecting the accuracy of TSI(SD), TSI(TN), and TSI(TP) in indicating algal biomass. For one, WD was closely related to mass ratio of nitrogen to phosphorus (N:P) and non-algal light attenuation (NALA, m−1) in our study lakes and reservoirs (lnNALA = -0.70*lnWD + 1.02, P 5 m in our study area. On a broader scale, empirical TN (or TP), Chla, and SD relationships of lakes in other ecoregions may also be affected by WD and other unmeasured factors (e.g., zooplankton grazing), the direct use of TSI may be problematical. Thus, this study provides essential information for developing accurate lake eutrophication assessments in both ours and other ecoregions.

Bathymetric LiDAR technology is a technology used for simultaneous data acquisition regarding the morphology of the bottom of water reservoirs and the surrounding coastal zone, realized from the air, e.g., by plane or drone. Contrary to the air topographic LiDAR, which uses an infrared wavelength of 1064 nm, bathymetric LiDAR systems additionally use a green wavelength of 532 nm. The green laser can penetrate the water, which makes it possible to measure the depth of shallow water reservoirs, rivers, and coastal sea waters within three Secchi depths. This article presents the theoretical basis for the construction of a green laser. Against the background of other methods of measuring the bottom of water reservoirs, the technology using waves from the visible light range is presented in detail in the assessment of the bottom morphology of shallow water reservoirs. The possibilities of using green laser in lidar bathymetry implemented in particular in non-navigable regions are shown. The results of the researchers' work on river processes (erosion, sedimentation), design of stream restoration, determination of morphometric parameters of the riverbed, as well as assessment of the topography of the marine coastal bottom zones are summarized. The development direction of lidar bathymetry is discussed. [ABSTRACT FROM AUTHOR]

Copyright of Acta Geographica Universitatis Comenianae is the property of Comenius University in Bratislava, Faculty of Natural Sciences 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.)

We used a time series of Secchi disk values retrieved from Landsat 5 images to study temporal and spatial patterns of water quality across gravel pit ponds located in Madrid, Spain from 1984 to 2009. There is a seasonal behavior in the water quality, with higher values of Secchi disks in autumn and winter (December--February) and lower values in summer (July--August), which can be explained by the relationship between Secchi disk values and temperature and solar radiation. We found that the 1994 administrative declaration of the regional park has had a positive impact on the water quality. The trophic state of the studied pit ponds has slowly improved, though the ponds have not reached the oligotrophic state. [ABSTRACT FROM AUTHOR]

Water transparency, measured as the diffuse attenuation coefficient of photosynthetically-active (400–700 nm) radiation, KdPAR, was measured monthly from May–Oct 2020 at 73 locations along 250 km of the Hudson River estuary (HRE) between New York City, NY and Waterford, NY. Three primary optical drivers of KdPAR variability: chlorophyll concentration (CHL), turbidity, and light absorption by colored dissolved organic matter (a CDOM), were measured concurrently to assess their relative importance to spatial and temporal KdPAR patterns. KdPAR was higher and more variable in the brackish HRE relative to limnetic regions further north. KdPAR was also significantly higher nearshore and near sewage treatment plant outfalls relative to midchannel sites. Temporal variability at individual stations was generally lower than cross-channel or cross-region spatial variability. Turbidity was the most important factor in KdPAR variability in all regions of the HRE, followed by CHL, with a CDOM playing a lesser role. Although many water quality variables have changed in the HRE over recent decades, KdPAR measurements in the brackish regions overlapped with published observations from the 1970s–1990s. KdPAR in the limnetic regions was lower in 2020 than measurements made prior to the Zebra mussel invasion in the early 1990s, but similar to measurements in the limnetic regions made since the invasion. Results of this study can be used to optimize satellite-based remote sensing algorithms for synoptic water quality observations of the HRE. Proposed future alterations in the HRE, including dredging and the construction of storm-surge barriers, would likely change existing KdPAR patterns. This study therefore provides an updated baseline for optical parameters in the HRE and highlights the importance of understanding the impacts of any proposed alterations to upper-water-column turbidity in this system. Results also demonstrate that KdPAR, euphotic depths, and Secchi depth measurements were positively correlated throughout the HRE. Secchi depth measurements may therefore be useful for additional retrospective studies, and future monitoring (including by satellite-derived KdPAR) of water transparency in the HRE. • Turbidity dominated water transparency variability in the Hudson River Estuary. • Chlorophyll concentration, and then CDOM, had decreasing influences. • High spatial and temporal variability did not affect overall dominance of turbidity. • Water transparency likely consistent for 20–50 years despite many ecosystem changes. • Impacts of potential management actions on turbidity are key for water quality. [ABSTRACT FROM AUTHOR]

Macrophytes play an important role in shallow lakes if large standing crop can be achieved. Here we stress the role of submerged macrophytes for benthic-pelagic coupling in the shallow oxbow lake Alte Donau (Austria) during restoration triggered by sufficient light availability (12% surface ambient light, photic>12% depth, zoptimum) in both, the benthic and the pelagic habitat. Focusing on zoptimum, rather than on minimum light requirement (euphotic depth), seemed to be more meaningful to follow the macrophyte development. After phosphate precipitation treatment, the photic>12% pelagic habitat accounted for more than half of the total water volume in summer, while the achievement of the same photic>12% conditions for half of the total sediment surface area was delayed by 8 years. A delay of light exposure on the lake bottom area compared to the lake water volume is given by the basin morphometry, but the time span that is required for passing this delay depends on the efficiency of restoration measures. The 8-year delay for Alte Donau means that lake restoration focusing on macrophyte re-establishment was difficult to stimulate due to insufficient light exposure at the lake bottom. A further increase of photic>12% conditions to more than 3/4 size of both pelagic and benthic habitat, however, eventually stimulated sustained macrophyte growth. With the onset of this large macrophyte biomass yield, the phosphorus storage pool of submerged macrophytes exceeded the annual peak concentration of total phosphorus of the whole lake water by about one order of magnitude for the first time. Further, the submerged macrophyte bio-surface exceeded the size of lake bottom surface, also by about one order of magnitude. Our results support that macrophytes can act as a significant sink of phosphorus by retaining this nutrient at least during the growing season. We further see the immensely large macrophyte bio-surface as a vast spatial dimension for an additional habitat for freshwater biota. Therefore, we conclude that mature submerged macrophyte formations need to be considered not only as biomass yield, but create a unique macrophyte habitat architecture as a third main component in the network between benthic (lake bottom) and pelagic (lake water) habitat.

This study investigates the application of unoccupied aerial vehicles (UAVs) equipped with a Micasense RedEdge-MX multispectral camera for the estimation of Secchi depth (SD) in inland water bodies. The research analyzed and compared five sun-glint correction methodologies—Hedley, Goodman, Lyzenga, Joyce, and threshold-removed glint—to model the SD values derived from UAV multispectral imagery, highlighting the role of reflectance accuracy and algorithmic precision in SD modeling. While Goodman’s method showed a higher correlation (0.92) with in situ SD measurements, Hedley’s method exhibited the smallest average deviation (0.65 m), suggesting its potential in water resource management, environmental monitoring, and ecological modeling. The study also underscored the quasi-analytical algorithm (QAA) potential in estimating SD due to its flexibility to process data from various sensors without requiring in situ measurements, offering scalability for large-scale water quality surveys. The accuracy of SD measures calculated using QAA was related to variability in water constituents of colored dissolved organic matter and the solar zenith angle. A practical workflow for SD acquisition using UAVs and multispectral data is proposed for monitoring inland water bodies.

Hoyer MA, Canfield DE, Jr. 2022. A Limnological Yardstick based on phosphorus limitation. Lake Reserv Manage. 38:109–125. A new tool called a Limnological Yardstick was developed using long-term (15 to 35 yr) lake chemistry data collected by volunteers of the Florida LAKEWATCH program. This yardstick can assist managers of aquatic systems with identifying where there is a great probability that phosphorus is not only the limiting nutrient, but the limiting environmental factor. When a lake's phosphorus–chlorophyll data lie below the yardstick's lower 95% confidence interval, phosphorus may be the limiting nutrient but not the limiting environmental factor, indicating where phosphorus control strategies will most likely fail. The Limnological Yardstick cannot directly identify the limiting environmental factor(s), as this requires a thorough limnological study of the lake because each lake has unique properties. Limiting environmental factors discussed are nitrogen, true color (Pt-Co units), nonalgal suspended solids, flushing rate, and aquatic macrophytes. The potential impacts of limiting environmental factors on the classification of lake trophic state and eutrophication are also discussed. [ABSTRACT FROM AUTHOR]

Abstract Lake Hawassa is one of the major Ethiopian Rift Valley Lakes having an endorheic basin system. The surrounding community makes use of the lake water for the multiple purposes of irrigation, domestic water supply, recreation and fish harvesting. The aim of the present study was to ascertain the water quality of the lake in terms of water quality indices (WQI) and its health over a period of three months covering both dry and wet seasons. Overall, the water quality of Lake was unfit and bad as per the weighted arithmetic method (120.06–228.29) and modified Bascarón water quality index (MBWQI) methods (26.81–33.89), respectively. However, the quality was indicated as marginal, as per the Canadian Council of Ministers of the Environment (CCME) water quality index method (44.2–51.1). On average, the lake was under the hypertrophic stage as per the standard based on the results of Secchi depth and nutrient concentration. The current study showed the lake being unfit for all-purposes as per WAWQI range (> 100). According to the physicochemical and biological parameters, of the lake, it requires mitigation measures to control Eutrophication and pollutants inflow.

Secchi depth (SD) is a valuable and feasible water quality indicator of lake eutrophication. The establishment of an automated system with efficient image processing and an algorithm suitable for the inversion of transparency in lake-rich regions could provide sufficient temporal and spatial information for lake management. These are especially critical for lake-rich regions where in situ monitoring data are scarce. This study demonstrated the implementation of an atmospheric correction algorithm (ACOLITE algorithm) in conjunction with the Google Earth Engine platform to generate remote-sensing reflectance products of specific points efficiently. The study also evaluated the performance of an algorithm for inverting lake SDs in Yunnan Plateau lakes, which is one of the five lake districts in China, since there is a lack of in situ data for most of the lakes in the region. The in situ data from four lakes with large SD ranges and imagery from Landsat Operational Land Imager were used to train and evaluate the performance of two algorithms: an empirical algorithm (stepwise regression) and machine learning (support vector machines and multi-layer perception). The results revealed that the retrieval accuracy of models with bands and band ratio combinations could be substantially improved compared with models with a single band or band combinations. A negative correlation was also observed between the temporal match between observations and the model accuracy. This study found that the MLP model with sufficient training data was more suitable for transparency estimation of lakes belonging to the dataset; the SVM model was more suitable for transparency prediction outside the training set, regardless of the adequacy of the training data. This study provides a reference for monitoring lakes within the Yunnan region using remote sensing.

Water transparency is an important factor affecting fish availability (underwater visibility) for diving birds. The diet of Great Cormorants Phalacrocorax carbo in relation to water transparency (range 1.4–4.0 m) was studied by pellet analyses at the submontane reservoir Dobczyce, Poland, from June to November. Although water transparency proved to be related to the birds' distribution, in the range of turbidities studied, no relationship was found with either fish species and fish size taken. Of 14 species in the diet, Roach Rutilus rutilus was dominant in all monthly samples (35–91% in 2002, 56–82% in 2004). Numbers of Great Cormorants and water transparency (range 0.4–1.4 m) were studied in the turbid lowland reservoir Goczałkowice during the migration period in autumn (August–November 2011 and 2012). Observations here suggest that the effect of water transparency on food uptake and habitat choice was only apparent below 0.6 m Secchi depth. The number of foraging Great Cormorants was not only affected by Secchi depth, but by a complex of factors (year, month, place, Secchi depth and water depth). We argue that, especially when the number of Great Cormorants is low, only highly detailed measurements of these factors (both spatially and as time series) can show the complex relationship between prey distribution, environmental conditions and the predator's behaviour. [ABSTRACT FROM AUTHOR]

The hydrological conditions in Lake Poyang are relatively complicated (e.g., large variations in water level) due to its connection with the Yangtze River, and the drivers of phytoplankton distribution differ greatly from those in other lakes. Based on the monthly monitoring data of Lake Poyang in 2011–2019 from 6 sampling sites, we analyzed the distribution pattern of phytoplankton density and the succession of dominant genera as well as the potential drivers, including water temperature (WT), Secchi depth (SD), nutrients, and water flow velocity (V). The phytoplankton density showed an increasing trend at the interannual scale, with a mean value of 1.97 × 106 ind/L in 2011 and 6.75 × 106 ind/L in 2019. The frequency of Microcystis as the dominant genus decreased (from 31.7% in 2011 to 13.8% in 2019), while the frequency of Pseudanabaena, Cyclotella and Synedra increased overall. According to all data analyzed by the generalized additive model, the crucial factors affecting phytoplankton density were WT, V and SD, which together explained 29.1% of the variance. At the interannual scale, the increase in phytoplankton density was probably due to the significant increase in SD. The interannual value of V remained stable overall and showed a negative correlation with phytoplankton density. Nutrients and V may greatly determine the variability in dominant genera in Lake Poyang. The nutrient (total nitrogen and total phosphorus) concentrations have generally declined in recent years, especially after 2017. When Aulacoseira was dominant, V differed greatly from that when Microcystis was the dominant genus, with values of 0.40 m/s and 0.28 m/s, respectively. In particular, V generally increased yearly (P

Bathymetric LiDAR technology is a technology used for simultaneous data acquisition regarding the morphology of the bottom of water reservoirs and the surrounding coastal zone, realized from the air, e.g., by plane or drone. Contrary to the air topographic LiDAR, which uses an infrared wavelength of 1064 nm, bathymetric LiDAR systems additionally use a green wavelength of 532 nm. The green laser can penetrate the water, which makes it possible to measure the depth of shallow water reservoirs, rivers, and coastal sea waters within three Secchi depths. This article presents the theoretical basis for the construction of a green laser. Against the background of other methods of measuring the bottom of water reservoirs, the technology using waves from the visible light range is presented in detail in the assessment of the bottom morphology of shallow water reservoirs. The possibilities of using green laser in lidar bathymetry implemented in particular in non-navigable regions are shown. The results of the researchers’ work on river processes (erosion, sedimentation), design of stream restoration, determination of morphometric parameters of the riverbed, as well as assessment of the topography of the marine coastal bottom zones are summarized. The development direction of lidar bathymetry is discussed.

Hoyer, MV, Canfield, DE Jr. 2021. Volunteer-collected water quality data can be used for science and management. Lake Reserv Manage. 37:235–245. This study addresses concerns that comparison studies between professional and volunteer-collected data have been of limited scope, conducted under experimental conditions, and that results may not be applicable to existing large-scale, long-term volunteer monitoring datasets. Historical (2008 to 2019) phosphorus, nitrogen, chlorophyll, and Secchi data collected by 5 Florida organizations charged with monitoring water quality were compared with Florida LAKEWATCH volunteer-collected data from 216 lakes. The state organizations had National Environmental Laboratory Accreditation Conference (NELAC)-certified laboratories and LAKEWATCH used modified procedures needed to accommodate a volunteer program. The lakes are located in central Florida, range in trophic status from oligotrophic to hypereutrophic, and provided approximately 650 independent overlapping annual geometric mean pairs for comparison. Paired t-tests comparing logarithmic transformed annual geometric mean data pooled from all professional organizations with similar overlapping volunteer-collected data showed significant (P < 0.05) differences for phosphorus, nitrogen, and Secchi depth but not for chlorophyll. The significant differences when reported arithmetically were only 1.1 µg/L, −1.1 µg/L, and 0.1 m, respectively. Regression analyses on the same data showed strong significant (P < 0.05) relations with coefficient of determinations (R2) of 0.91, 0.98, 0.79, and 0.78 for phosphorus, nitrogen, chlorophyll, and Secchi depth, respectively. Slopes for each paired regression were not significantly different from 1. These results demonstrate that volunteer-collected data were equivalent to data collected professionally, that the quality of volunteer data can be similar to that produced by NELAC-certified laboratories, and thus that data are adequate for both research and management. [ABSTRACT FROM AUTHOR]

Secchi depth (SD) can directly reflect the state of lake water quality, and it is the key to control and improve the lake environment at mastering long-term and large-scale. In this research, deep neural networks algorithm was used to derive SD of 9 major plateau lakes in Yunnan Province from January 2001 to December 2018 based on MODIS remote sensing images, and explored the spatial-temporal variation characteristics with SD by geospatial analysis. The results showed that: (1) The inversion model proposed in this paper had a good performance (RMSE = 0.1359, MAE = 0.1134), which can objectively reflect SD status in the lake. (2) The temporal variation characteristics showed that SD of all lakes has a downward trend with a mean comprehensive change rate of −0.25 m/decade. (3) The spatial variation characteristics showed that the region of higher SD has a larger decline rate, and the trend in the region with lower SD was relatively stable. SD near urban and residential areas was relatively low, and declined fast. (4) Human activities would become an important factor to affect SD changes in the plateau lakes of Yunnan Province, and it was also the main factor causing lake pollution in the Yunnan-Guizhou Plateau.

Study region: Lake Hawassa, Ethiopian Rift Valley, Southern Region, Ethiopia. Study focus: Lake Hawassa is one of the major Ethiopian Rift Valley Lakes with an endorheic basin system located near Hawassa town. The Lake water is vital to the surrounding communities for irrigation, domestic water supply, recreation, and fish harvesting. The morphological changes due to flood water from the surrounding agricultural areas were noticed and the water quality deteriorates which will be reflecting the agricultural productivity in the region and negatively impacted the socio-economic development. The lake morphometric changes were investigated by using cartographic ArcGIS mapping and bathymetric mapping and during the analysis, the thermal Infrared data of Landsat ™ was used in the digital elevation model (30 × 30 m) and Google Earth Engine (GEE) platform. The morphometric changes for a period of 46 years were considered in this study. The Secchi discs and echo-sounder were used to during the preparation of bathymetric maps and kriging interpolation was used for the water depth assessment of the lake. New hydrological insights for the Lake: The surface area of the Lake increased by 11.28 % from 1973 to 2019. The depth and volume decreased by 33.04 % and 25.32 %, respectively over the same period. The observed Secchi disc depth was 2.06 m. It was found that the increased surface area due to sedimentation and eutrophication in the Lake.

Through the mechanisms of particle immobilization and subsequent depletion of particles, mussel cultivation has a direct effect on chlorophyll-a concentrations and Secchi depth; both of which are primary indicators of marine ecological status and metrics for water quality management. As such, mussel cultivation has been proposed as a measure to mitigate the effects of coastal eutrophication. However, the extent to which this ecosystem service, and relatedly, biomass accumulation, are affected by ambient environmental conditions involves complex interactions. To explore the interacting mechanisms underpinning depletion dynamics under various biophysical conditions along the salinity gradient in the Baltic Sea, we used an updated Dynamic Energy Budget (DEB) model with field data from the western Baltic Sea, accommodating osmotic stress. We use the DEB model to drive a 3D farm-scale model within a novel precompiled hydrodynamic framework (FlexSem) to evaluate the effects of different environmental conditions and farm configuration on the intensity and extent of the chlorophyll-a depletion signal. We also report on extensive in situ monitoring of chlorophyll-a and Secchi depth within and around mussel farms, from several cultivation areas from around the western Baltic Sea to evaluate site-specific characteristics of depletion. Monitoring reflected the high degree of spatio-temporal variability in the quantification of this ecosystem service; with relative differences in chlorophyll-a from −14 to 69% and Secchi depth from 0 to 75%. We find that the extensive in situ measurements in different environmental conditions can be represented by the integrated farm model in terms of mussel biomass accumulation and depletion, providing insight on the interactions of current velocity, farm orientation to predominant current direction, ambient chlorophyll-a concentrations, and total biomass loads on the intensity and spatial extent of the depletion signal. Furthermore, the model has been calibrated to cover a variety of environmental contexts and permits fine-resolution simulation of multiple environmental interactions on mussel energetics, which can be used to evaluate potentials for optimizing mussel mitigation culture and the associated ecosystem services of phytoplankton depletion under local conditions without extensive recalibration from field growth data. The general interactions exhibited here and model will be useful for evaluating depletion and planning the establishment of mitigation farms in regions where national environmental monitoring programs can provide basic data. This can also reduce the need for extensive and costly in situ monitoring programs.

Lake Hawassa is one of the major Ethiopian Rift Valley Lakes having an endorheic basin system. The surrounding community makes use of the lake water for the multiple purposes of irrigation, domestic water supply, recreation and fish harvesting. The aim of the present study was to ascertain the water quality of the lake in terms of water quality indices (WQI) and its health over a period of three months covering both dry and wet seasons. Overall, the water quality of Lake was unfit and bad as per the weighted arithmetic method (120.06–228.29) and modified Bascarón water quality index (MBWQI) methods (26.81–33.89), respectively. However, the quality was indicated as marginal, as per the Canadian Council of Ministers of the Environment (CCME) water quality index method (44.2–51.1). On average, the lake was under the hypertrophic stage as per the standard based on the results of Secchi depth and nutrient concentration. The current study showed the lake being unfit for all-purposes as per WAWQI range (> 100). According to the physicochemical and biological parameters, of the lake, it requires mitigation measures to control Eutrophication and pollutants inflow. [ABSTRACT FROM AUTHOR]

Ambitious to fulfill the European Water Framework Directive obligations, the European governments support projects to rehabilitate lakes with poor water quality. However, most lake restorations having relied on biomanipulation by fish thinning have failed to improve or even maintain water quality. Previous attempts removed all target fish species simultaneously, thus making it impossible to assess the specific impact of each feeding group on water chemistry. Lake Bromme was selected for extensive, time-selective fish biomanipulation to improve water clarity and promote submerged macrophytes and piscivorous fish stocks over a three-year monitoring period. Thinning of adult benthivorous bream (Abramis brama) and tench (Tinca tinca) was conducted throughout year one while thinning in years two and three targeted planktivorous roach (Rutilus rutilus), juvenile bream, and small perch (Perca fluviatilis). Yearly fish surveys assessed changes in fish population structure and biomass. Water quality parameters were monitored continually, and the cover of submerged macrophytes was surveyed annually via sonar. We found no improvement in water clarity or reductions of nutrients, organic particles, chlorophyll concentrations, or watercolor, despite a 6-fold thinning of total estimated fish biomass, from 112 to 19 kg ha -1 . Over the period, the macrophyte cover increased from 0.8 to 13.5 %, but no recruitment of large piscivorous fish (perch and pike (Esox lucius) > 10 cm) was detected. We found higher correlations of particle concentration and water clarity to water temperature than to wind speed, which indicates sediment particle resuspension by the remaining fish community (mostly carp Cyprinus carpio) that forage on benthos in shallow lakes. Further system-ecological research in Lake Bromme should evaluate whether thinning the stock of carp and increasing plant cover may improve water quality and test which optical properties sustain high water turbidity and prevent shallow, eutrophic lakes like Lake Bromme from responding to intense fish thinning., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Knowledge of trophic status is fundamental to understanding the condition and function of lake ecosystems. We developed regression models to predict chlorophyll a concentrations (chl a) in New Zealand lakes for reference and current states, based on an existing dataset of total nitrogen (TN) and total phosphorus (TP) concentrations for 1031 lakes. Models were then developed to predict Secchi depth based on chl a and a sediment resuspension term applicable to shallow lakes. Estimates of all four Trophic Level Index (TLI) variables (chl a, TN, TP and Secchi depth) were analysed to estimate reference and current state TLI for the nationally representative sample of 1031 lakes. There was a trend of eutrophication between reference and current states, with systematic differences among lake geomorphic types. Mean chl a increased 3.5-fold (2.42 mg m−3 vs. 8.32 mg m−3) and mean Secchi depth decreased (indicating lower clarity) by approximately one-third (9.62 m vs. 6.48 m) between reference and current states. On average, TLI increased by 0.67, with the TLI increase >1 in approximately one-third (31%) of lakes. This study informs the status of lake ecosystems in NZ and provides benchmarks to guide management and assessment. [ABSTRACT FROM AUTHOR]

The perspective on water transparency changed since the early days of limnology from being a physical parameter of optical water property to an ecological indicator tracking algal turbidity due to eutrophication or an overall success of sustained lake restoration in the late 60ies to 80ies. In modern cities, where ecosystems are commonly deteriorated by man-made modifications, water transparency offers a great opportunity to the public to raise socio-ecological consciousness concerning urban green-blue spaces. We thus re-emphasize water transparency as a key indicator of multi-functional value when assessing an oxbow lake of the riverine floodplain in Vienna, the Alte Donau. Our study covers the eutrophication from 1987 to 1994 due to the inclusion of the riverine landscape in the urban area, the following lake restoration with an ecosystem shift from a nutrient-rich, algal-turbid water body to a nutrient-poor, clear-water macrophyte controlled system and the impact of global warming in recent decades. We used light attenuation profiles to identify depth layers of specific ambient light requirements for photosynthetic domains (phytoplankton and submerged macrophytes), and to interpret Secchi measurements. Here, we calculated the depth at 1% (minimum light requirements for phytoplankton growth as euphotic depth), 3% (minimum light requirements for macrophytes as maximum macrophyte colonization depth), and 12% (preferred light requirements for phytoplankton development) of surface ambient light. A Secchi disk water transparency of 1.5 m (“lake bottom view”), judged as good water quality by human perception, refers to mesotrophic conditions with a maximum colonization depth for macrophytes exceeding the mean lake depth in Alte Donau. Water clarity required for sustained macrophyte growth, in particular for favoring bottom-dwelling Chara meadows instead of tall-growing Myriophyllum spicatum, is 3.5 m Secchi depth and thus exceeds by far water clarity requested due to bathing aesthetics. Global warming, mirrored by an advanced warming in spring seems to favor significantly a higher yield of macrophytes mainly built up by Myriophyllum at the expense of the yield of algae. The prolongation of the summer period above 21°C, however, coincides with lowered Secchi transparency. Water visibility during the hot season thus seems to be slightly hampered against lake restoration efforts by global warming.

Secchi depth (SD, m) is a direct and intuitive measure of water's transparency, which is also an indicator of water quality. In 2015, a semi-analytical model was developed to derive SD from remote sensing reflectance, thus able to provide maps of water's transparency in satellite images. Here an in-situ dataset (338 stations) is used to evaluate its potential ability to monitor water quality in the coastal and estuarine waters, with measurements covering the Zhujiang (Pearl) River Estuary, the Yellow Sea and the East China Sea where measured SD values span a range of 0.2–21.0 m. As a preliminary validation result, according to the whole dataset, the unbiased percent difference (UPD) between estimated and measured SD is 23.3% (N=338, R2=0.89), with about 60% of stations in the dataset having relative difference (RD) ⩽ 20%, over 80% of stations having RD ⩽ 40%. Furthermore, by excluding the field data which with relatively larger uncertainties, the semi-analytical model yielded the UPD of 17.7% (N=132, R2=0.92) with SD range of 0.2–11.0 m. In addition, the semi-analytical model was applied to Landsat-8 images in the Zhujiang River Estuary, and retrieved high-quality mapping and reliable spatial-temporal patterns of water clarity. Taking into account the uncertainties associated with both field measurements and satellite data processing, and that there were no tuning of the semi-analytical model for these regions, these findings indicate highly robust retrieval of SD from spectral techniques for such turbid coastal and estuarine waters. The results suggest it is now possible to routinely monitor coastal water transparency or visibility at high-spatial resolutions from measurements, like Landsat-8 and Sentinel-2 and newly launched Gaofen-5. [ABSTRACT FROM AUTHOR]

Cyanobacteria are an essential biological component of phytoplankton water quality assessment. However, there are some problems associated with the widely used everyday practices of sampling, estimation and use of cyanobacteria when calculating phytoplankton indices assessing water quality. Many indices were developed during the implementation of the Water Framework Directive, considered the most innovative European environmental legislation. Most indices include cyanobacteria as a composition or bloom metric. Problems with the indices concern the exclusion of most chroococcalean taxa from cyanobacterial biovolume estimations in lakes and reservoirs of the Mediterranean region, treatment of the mucilage of colonial chroococcalean taxa in biovolume estimations and overlooking of deep-water cyanobacterial blooms due to sampling depth. These problems may lead to a biased view of water quality. In this paper we argue in favour of including all cyanobacteria taxa and their mucilage in biovolume estimations and considering a sampling depth that covers deep-water maxima, such as those formed by Planktothrix rubescens or colonial chroococcalean taxa. Cyanobacteria are an influential and widely acknowledged biological component of lake water quality assessment. Nevertheless, there are gaps in the monitoring of cyanobacteria. In this article we review widespread problems in the use of cyanobacteria in Water Framework Directive-related water quality assessment (i.e. exclusion of taxa, mucilage carbon of the colonial species, sampling depth) and suggest solutions to optimise water quality assessment. [ABSTRACT FROM AUTHOR]

A large-scale loss of the habitat-forming macroalgae Fucus vesiculosus was reported around the Baltic Sea in the 1980's, but only relatively local studies have reported its current status. We studied recent comprehensive mapping data in the Finnish marine area and compared reported Fucus occurrences in relation to its potential, to find out its current status on a larger scale. We also investigated the effects of water quality on Fucus occurrence and its depth penetration. Our results show that the status of Fucus is better in the Gulf of Bothnia than in the Gulf of Finland, both in terms of its occurrence rate and its depth distribution. Despite high potential in the outer Archipelago Sea, the status of Fucus is poor. The Fucus occurrence patterns are mainly related to salinity, exposure and Secchi depth, all positively affecting the Fucus occurrence rate and/or the lower limit of the Fucus zone. [ABSTRACT FROM AUTHOR]

Observations by satellite sensors provide data on inland water systems at spatial and temporal coverage superior to current monitoring programmes. We derived an empirical relationship for Secchi depth using in situ data from eight lakes and data from the Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus and Landsat 8 Operational Land Imager between 1999 and 2018 in the Rotorua Lakes Region in New Zealand. This relationship was then applied to all Landsat data of 23 lakes in that region. A trend analysis on annual and summertime averages of Secchi depth revealed several statistically significant and positive trends, indicating improving water clarity. Our trends were in agreement with those based on in situ observations illustrating the opportunities of remote sensing time series data for lake monitoring and management. [ABSTRACT FROM AUTHOR]

Successful management of coastal environments requires reliable monitoring methods and indicators. Besides Chlorophyll-a concentration (Chl-a), water transparency measured as Secchi Depth (ZSD) is widely used in Baltic Sea management for water quality assessment as eutrophication indicator. However, in many coastal waters not only phytoplankton but also colored dissolved organic matter (CDOM) and suspended particulate matter (SPM) influence the under-water light field, and therefore the ZSD. In this study all three main optical variables (CDOM, Chl-a, and SPM [organic and inorganic]) as well as ZSD were measured in three Swedish regions: the Bothnian Sea, the Baltic Proper, and the Skagerrak in 2010–2014. Regional multiple regressions with Chl-a, CDOM, and inorganic SPM as predictors explained the variations in ZSD well (Radj2 = 0.53–0.84). Commonality analyses of the regressions indicated considerable differences between regions regarding the contribution of each factor to the variance, Radj2, in ZSD. CDOM explained most of the variance in the Bothnian Sea and the Skagerrak; in general, Chl-a contributed only modestly to the ZSD variance. In the Baltic Proper the largest contribution was from the interaction of all three variables. As expected, the link between Chl-a and ZSD was much weaker in the Bothnian Sea with high CDOM absorption and SPM concentration. When applying the Swedish EU Water Framework Directive threshold for Good/Moderate Chl-a status in the models it was shown that ZSD is neither a sufficient indicator for eutrophication, nor for changes in Chl-a. Natural coastal gradients in CDOM and SPM influence the reference conditions for ZSD and other eutrophication indicators, such as the depth distribution of macro-algae. Hence, setting targets for these indicators based on reference Chl-a concentrations and simple Chl-a to ZSD relationships might in some cases be inappropriate and misleading due to overestimation of water transparency under natural conditions.

Agricultural runoff transports sediments and nutrients that deteriorate water quality erratically, posing a challenge to ground-based monitoring. Satellites provide data at spatial-temporal scales that can be used for water quality monitoring. PlanetScope nanosatellites have spatial (3 m) and temporal (daily) resolutions that may help improve water quality monitoring compared to coarser-resolution satellites. This work compared PlanetScope to Landsat-8 and Sentinel-2 in their ability to detect key water quality parameters. Spectral bands of each satellite were regressed against chlorophyll a, turbidity, and Secchi depth data from 13 reservoirs in Oklahoma over three years (2017–2020). We developed significant regression models for each satellite. Landsat-8 and Sentinel-2 explained more variation in chlorophyll a than PlanetScope, likely because they have more spectral bands. PlanetScope and Sentinel-2 explained relatively similar amounts of variations in turbidity and Secchi Disk data, while Landsat-8 explained less variation in these parameters. Since PlanetScope is a commercial satellite, its application may be limited to cases where the application of coarser-resolution satellites is not feasible. We identified scenarios where PS may be more beneficial than Landsat-8 and Sentinel-2. These include measuring water quality parameters that vary daily, in small ponds and narrow coves of reservoirs, and at reservoir edges.

There has been little rigorous investigation of the transferability of existing empirical water clarity models developed at one location or time to other lakes and dates of imagery with differing conditions. Machine learning methods have not been widely adopted for analysis of lake optical properties such as water clarity, despite their successful use in many other applications of environmental remote sensing. This study compares model performance for a random forest (RF) machine learning algorithm and a simple 4-band linear model with 13 previously published empirical non-machine learning algorithms. We use Landsat surface reflectance product data aligned with spatially and temporally co-located in situ Secchi depth observations from northeastern USA lakes over a 34-year period in this analysis. To evaluate the transferability of models across space and time, we compare model fit using the complete dataset (all images and samples) to a single-date approach, in which separate models are developed for each date of Landsat imagery with more than 75 field samples. On average, the single-date models for all algorithms had lower mean absolute errors (MAE) and root mean squared errors (RMSE) than the models fit to the complete dataset. The RF model had the highest pseudo-R2 for the single-date approach as well as the complete dataset, suggesting that an RF approach outperforms traditional linear regression-based algorithms when modeling lake water clarity using satellite imagery.