Showing papers on "Secchi disk published in 2021"

Comparing PlanetScope to Landsat-8 and Sentinel-2 for Sensing Water Quality in Reservoirs in Agricultural Watersheds

Abstract: 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.

Response of community composition and biomass of submerged macrophytes to variation in underwater light, wind and trophic status in a large eutrophic shallow lake

Abstract: Light climate is of key importance for the growth, community composition of submerged macrophytes in lakes and, they, in turn, are affected by lake depth and the degree of eutrophication. To test the relationships between submerged macrophyte presence and the ratio of Secchi disk depth (SDD) to water depth, i.e. SDD/depth, nutrients and wind, we conducted an extensive sampling campaign in a macrophyte-dominated area of the eastern region (n = 36) in 2016 in Lake Taihu, China, and combined the data gathered with results from extensive physico-chemical monitoring data from the entire lake. We confirmed that SDD/Depth is the primary factor controlling the community composition of macrophytes and showed that plant abundance increased with increasing SDD/Depth ratio (p 0.4 ensured growth of submerged macrophytes. Total phosphorus and total nitrogen also influenced the growth and community composition of macrophytes (p 0.05). The key to restore the macrophyte beds in the lake is to reduce the nutrient loading. A decrease of the water level may contribute as well in the shallow bays but will not bring plants back in the main part of the lake. As the tolerance of shade and nutrients varied among the species studied, this should be taken into account in the restoration of lakes by addition of plants.

Validation of Water Quality Monitoring Algorithms for Sentinel-2 and Sentinel-3 in Mediterranean Inland Waters with In Situ Reflectance Data

Abstract: Freshwater quality maintenance is essential for human use and ecological functions. To ensure this objective, governments establish programs for a continuous monitoring of the inland waters state. This could be possible with Sentinel-2 (S2) and Sentinel-3 (S3), two remote sensing satellites of the European Space Agency, equipped with spectral optical sensors. To determine optimal water quality algorithms applicable to their spectral bands, 36 algorithms were tested for different key variables (chlorophyll a (Chl_a), colored dissolved organic matter (CDOM), colored dissolved organic matter (TSS), phycocyanin (PC) and Secchi disk depth (SDD)). A database of 296 water-leaving reflectance spectra were used, as well as concomitant water quality measurements of Mediterranean reservoirs and lakes of Spain. Two equal data sets were used for calibration and validation. The best algorithms were recalculated using all database and used the following band relations: SDD, R560/R700; CDOM, R665/R490; PC, R705/R665 for S2 and R620, R665, R709 and R779 for S3, using a semi-analytical algorithm; R700 for TSS 20 mg/L; and for Chl_a, the maximum (R443; R492)/R560 for Chl_a 5 mg/m3. A preliminary test with a satellite image in a well-known reservoir showed results consistent with the expected ranges and spatial patterns of the variables.

Water quality assessment using Sentinel-2 imagery with estimates of chlorophyll a, Secchi disk depth, and Cyanobacteria cell number: the Cantareira System reservoirs (São Paulo, Brazil)

Abstract: Satellite images were used to assess surface water quality based on the concentration of chlorophyll a (chla), light penetration measured by the Secchi disk method (SD), and the Cyanobacteria cells number per mL (cyano). For this case study, six reservoirs interconnected were evaluated, comprising the Cantareira System (CS) in Sao Paulo State (Brazil). The work employed Sentinel-2 images from 2015 to 2018, SNAP image processing software, and the native products conc_chl and kd_z90max, treated using Case 2 Regional Coast Color (C2RCC) atmospheric correction. The database was obtained from CETESB, the agency legally responsible for operation of the Inland Water Quality Monitoring Network in Sao Paulo State. The results demonstrated robustness in the estimates of chla (RMSE = 3.73; NRMSE% = 19%) and SD (RMSE = 2,26; NRMSE% = 14%). Due to the strong relationship between cyano and chla (r2 = 0.84, p < 0.01, n = 90), both obtained from field measurements, there was also robustness in cyano estimates based on the estimates of chla from the satellite images. The data revealed a clear pattern, with the upstream reservoirs being more eutrophic, compared to those downstream. There were evident concerns, about water quality, particularly due to the high numbers of Cyanobacteria cells, especially in the upstream reservoirs.

Global maps of Forel–Ule index, hue angle and Secchi disk depth derived from 21 years of monthly ESA Ocean Colour Climate Change Initiative data

Abstract: . We document the development and public release of a new dataset (1997–2018), consisting of global maps of the Forel–Ule index, hue angle and Secchi disk depth. Source data come from the European Space Agency (ESA) Ocean Colour (OC) Climate Change Initiative (CCI), which is providing merged multi-sensor data from the mid-resolution sensors in operation at a specific time from 1997 to the present day. Multi-sensor satellite datasets are advantageous tools for ecological studies because they increase the probabilities of cloud-free data over a given region as data from multiple satellites whose overpass times differ by a few hours are combined. Moreover, data-merging from heritage and present satellites can expand the duration of the time series indefinitely, which allows the calculation of significant trends. Additionally, data are remapped consistently and analysis-ready for scientists. Also, the products described in this article have the exclusive advantage of being linkable to in situ historic observations and thus enabling the construction of very long time series. Monthly data are presented at a spatial resolution of ∼4 km at the Equator and are available at PANGAEA ( https://doi.org/10.1594/PANGAEA.904266 ; Pitarch et al., 2019a). Two smaller and easier-to-handle test datasets have been produced from the former: a global dataset at 1 ∘ spatial resolution and another one for the North Atlantic at 0.25 ∘ resolution. The computer code for the generation of the Forel–Ule index, hue angle and Secchi disk depth from a given remote-sensing reflectance is also shared at https://doi.org/10.5281/zenodo.4439646 (Pitarch et al., 2021) and can be easily set in loop mode for batch calculations.

Variations of Water Transparency and Impact Factors in the Bohai and Yellow Seas from Satellite Observations

Abstract: Water transparency, measured with Secchi disk depth (SDD), is an important parameter for describing the optical properties of a water body. This study evaluates variations of SDD and related impact factors in the Bohai and Yellow Seas (BYS). Based on a new mechanistic model proposed by Lee et al. (2015) applied to MODIS remote sensing reflectance data, climatological SDD variation from 2003 to 2019 was estimated. The annual mean images showed an increasing trend from the coastal zone to the deep ocean. Lower values were found in the Bohai Sea (BHS), while higher values observed in the center of the southern Yellow Sea (SYS). Additionally, the entire sea has shown a decreasing temporal tend, with the variation rate lowest in the BHS at 0.003 m y−1, and highest in the SYS at 0.015 m y−1. However, the weak increasing trend that appeared since 2017 suggests that water quality seems to have improved. Further, it displayed seasonal patterns of low in winter and spring and high in summer and autumn. The empirical orthogonal function (EOF) analysis of SDD variations over the BYS, shows that the first SDD EOF mode is the highest, strongly correlated with total suspended matter. With the high correlation coefficients of chromophoric dissolved organic matter, it illustrates that the SDD variation is mainly dominated by the optical components in the seawater, although correlation with chlorophyll-a is the weakest. The second and third EOF modes show that photosynthetically available radiation, sea surface temperature, sea surface salinity, and wind speed are the main covariates that cause SDD changes. Water transparency evaluation on a long-term scale is essential for water quality monitoring and marine ecosystem protection.

Retrieving Water Turbidity in Araucanian Lakes (South-Central Chile) Based on Multispectral Landsat Imagery

Abstract: Remote sensing was used as an early alert tool for water clarity changes in five Araucanian Lakes in South-Central Chile. Turbidity records are scarce or unavailable over large and remote areas needed to fully understand the factors associated with turbidity, and their spatial-temporal representation remains a limitation. This work aimed to develop and validate empirical models to estimate values of turbidity from Landsat images and determine the spatial distribution of estimated turbidity in the selected Araucanian Lakes. Secchi disk depth measurements were linked with turbidity measurements to obtain a turbidity dataset. This in turn was used to develop and validate a set of empirical models to predict turbidity based on four single bands and 16 combination bands from 15 multispectral Landsat images. The best empirical models predicted turbidity over the range of 0.3–12.3 NTUs with RMSE values around 0.31–1.03 NTU, R2 (Index of Agreement IA) around 0.93–0.99 (0.85–0.97) and mean bias error (MBE) around (−0.36–0.44 NTU). Estimation maps to analyze the temporal-spatial turbidity variation in the lakes were constructed. Finally, it was found that the meteorological conditions may affect the variation of turbidity, mainly precipitation and wind speed. The data indicate that the turbidity has slightly increased in winter–spring. These models will be used in the future to reconstruct large datasets that allow analyzing transparency trends in those lakes.

Citizen Science Tools Reveal Changes in Estuarine Water Quality Following Demolition of Buildings

Abstract: Turbidity and water colour are two easily measurable properties used to monitor pollution. Here, we highlight the utility of a low-cost device—3D printed, hand-held Mini Secchi disk (3DMSD) with Forel-Ule (FU) colour scale sticker on its outer casing—in combination with a mobile phone application (‘TurbAqua’) that was provided to laymen for assessing the water quality of a shallow lake region after demolition of four high-rise buildings on the shores of the lake. The demolition of the buildings in January 2020 on the banks of a tropical estuary—Vembanad Lake (a Ramsar site) in southern India—for violation of Indian Coastal Regulation Zone norms created public uproar, owing to the consequences of subsequent air and water pollution. Measurements of Secchi depth and water colour using the 3DMSD along with measurements of other important water quality variables such as temperature, salinity, pH, and dissolved oxygen (DO) using portable instruments were taken for a duration of five weeks after the demolition to assess the changes in water quality. Paired t-test analyses of variations in water quality variables between the second week of demolition and consecutive weeks up to the fifth week showed that there were significant increases in pH, dissolved oxygen, and Secchi depth over time, i.e., the impact of demolition waste on the Vembanad Lake water quality was found to be relatively short-lived, with water clarity, colour, and DO returning to levels typical of that period of year within 4–5 weeks. With increasing duration after demolition, there was a general decrease in the FU colour index to 17 at most stations, but it did not drop to 15 or below, i.e., towards green or blue colour indicating clearer waters, during the sampling period. There was no significant change in salinity from the second week to the fifth week after demolition, suggesting little influence of other factors (e.g., precipitation or changes in tidal currents) on the inferred impact of demolition waste. Comparison with pre-demolition conditions in the previous year (2019) showed that the relative changes in DO, Secchi depth, and pH were very high in 2020, clearly depicting the impact of demolition waste on the water quality of the lake. Match-ups of the turbidity of the water column immediately before and after the demolition using Sentinel 2 data were in good agreement with the in situ data collected. Our study highlights the power of citizen science tools in monitoring lakes and managing water resources and articulates how these activities provide support to Sustainable Development Goal (SDG) targets on Health (Goal 3), Water quality (Goal 6), and Life under the water (Goal 14).

Modelling of ecological status of Polish lakes using deep learning techniques

Abstract: Since 2000, after the Water Framework Directive came into force, aquatic ecosystems’ bioassessment has acquired immense practical importance for water management. Currently, due to extensive scientific research and monitoring, we have gathered comprehensive hydrobiological databases. The amount of available data increases with each subsequent year of monitoring, and the efficient analysis of these data requires the use of proper mathematical tools. Our study challenges the comparison of the modelling potential between four indices for the ecological status assessment of lakes based on three groups of aquatic organisms, i.e. phytoplankton, phytobenthos and macrophytes. One of the deep learning techniques, artificial neural networks, has been used to predict values of four biological indices based on the limited set of the physicochemical parameters of water. All analyses were conducted separately for lakes with various stratification regimes as they function differently. The best modelling quality in terms of high values of coefficients of determination and low values of the normalised root mean square error was obtained for chlorophyll a followed by phytoplankton multimetric. A lower degree of fit was obtained in the networks for macrophyte index, and the poorest model quality was obtained for phytobenthos index. For all indices, modelling quality for non-stratified lakes was higher than this for stratified lakes, giving a higher percentage of variance explained by the networks and lower values of errors. Sensitivity analysis showed that among physicochemical parameters, water transparency (Secchi disk reading) exhibits the strongest relationship with the ecological status of lakes derived by phytoplankton and macrophytes. At the same time, all input variables indicated a negligible impact on phytobenthos index. In this way, different explanations of the relationship between biological and trophic variables were revealed.

Niche differentiation between a native and an invasive species of submersed macrophyte in a subtropical reservoir

Abstract: Submersed macrophytes have important ecological roles but non-native invasive species may affect biodiversity and water uses. We investigated the native macrophyte Egeria najas and the invasive Hydrilla verticillata and measured their maximum colonization depth and its relationship with Secchi disk depth, their biomass along the depth gradient and their preferred depths of occurrence. The Itaipu Reservoir was monitored for seven years, during which maximum colonization depth and Secchi disk depth were measured. During a separate sampling, plants were collected to determine biomass along the depth gradient. Ancova showed that the maximum colonization depth of both species increased with increasing Secchi disk depth, but the maximum colonization depth of H. verticillata increased faster with increasing water transparency than did that of E. najas. Quadratic regression revealed that the biomass of each species peaks at intermediate depths. Hydrilla verticillata colonizes deeper regions than does E. najas. The patterns found in the present study can be explained by underwater light and, probably, wave disturbances. The preference of H. verticillata for deeper sites indicates that the ecological niches of the two macrophytes differ, and that H. verticillata has great potential to spread and accumulate biomass in reservoirs.

Dynamics of Nutrients and Colored Dissolved Organic Matter Absorption in a Wetland-Influenced Subarctic Coastal Region of Northeastern Japan: Contributions From Mariculture and Eelgrass Meadows

Abstract: Coastal oceans interacting with terrestrial ecosystems play an important role in biogeochemical cycles. It is therefore essential to research land–ocean interactions for further understanding of the processes influencing nutrients dynamics in coastal areas. We investigated the seasonal and spatial distribution of nutrient concentrations and light absorption coefficients of colored dissolved organic matter (CDOM), non-algal particles (NAP), and phytoplankton in a wetland-influenced river–eelgrass meadows–coastal waters continuum in the protected and semi-enclosed coastal sea of Akkeshi-ko estuary (AKE) and Akkeshi Bay (AB), Japan from April 2014 to February 2015. The mixing dilution lines of the CDOM absorption coefficient at 355 nm (aCDOM(355)) relative to salinity predicted by two end-members between freshwater and coastal water showed conservative mixing in AB. Silicate concentrations were significantly correlated with salinity and aCDOM(355) in AB in each month except for December 2014. These results suggest that silicate and CDOM in AB primarily originates from wetland-influenced river discharge. However, samples collected from the eelgrass meadows of AKE, where mariculture is developed, showed non-conservative mixing of silicate concentrations and aCDOM(355) with salinity except for June 2014. Elevated phosphate concentrations, probably released from sediments, were also found in the eelgrass meadows of AKE, especially during summer. These results suggest that the metabolic activities of mariculture and seagrass ecosystem significantly contribute to the nutrient cycles and CDOM absorption in AKE and to the distinct water-mass systems inside and outside AKE. The relative absorption properties of NAP (aNAP(443)), phytoplankton (aph(443)), and aCDOM(443) showed that CDOM is the main factor affecting the light distribution in AKE. However, the relative absorption properties varied seasonally in AB because of spring and autumn phytoplankton blooms and ice cover during winter. Significant relationships were observed between the Secchi disk depth (ZSD), aNAP(443), and aCDOM(443). Chl a concentration and aph(443) were not good indicators for predicting ZSD in our study region. These results suggest that incorporating inherent optical properties and CDOM from mariculture and seagrass ecosystem into ecosystem models could improve predictions of light distribution along the freshwater–eelgrass–coastal waters continuum in optically complex coastal waters.

Spatiotemporal variability of secchi depths of the North Arabian Gulf over the last two decades

Abstract: Secchi Disk Depth is an important water quality measurement linked to many aspects of coastal and marine ecosystems. Understanding the role of this important indicator at regional scale requires synoptic observations through ocean color sensors, such as Moderate-Resolution Imaging Spectroradiometer (MODIS). In this study, the spatial and temporal distributions of Secchi depths were mapped over the North Arabian Gulf (NAG) from 2003 to 2020 using a regional Secchi depth model. Spatiotemporal patterns and trends of Secchi depths within the NAG were also investigated using time series analysis. Generally, the MODIS SDD retrievals revealed that NAG Secchi depths increased toward south and offshore waters of the study area. The northern areas exhibited very low Secchi depths with monthly means less than 1.7 m, whereas the middle and southern areas had the highest Secchi depths in all seasons with monthly means higher than 9 m. The Secchi depths were lower during the fall and winter seasons while higher during the spring and summer seasons with a general peak in June. The time series analysis approach used in this study can be a systematic guideline for the future remote sensing studies of Secchi depths and other water quality indicators over different geographical locations.

Convergent Validity of Satellite and Secchi Disk Measures of Water Clarity in Hedonic Models

Abstract: Budget-constrained environmental agencies across the United States are limited in their ability to monitor water quality changes using traditional in situ sampling. Satellite-based monitoring systems represent a lower-cost alternative. It is unclear, however, how this transition will impact nonmarket valuation estimates of perceived water quality. To answer this question, we merge housing information with Secchi depth and satellite estimates of water clarity from over 100 lakes in Wisconsin. A comparison of hedonic price functions reveals satellite estimates of water clarity provide a stronger statistical fit of housing price and produce implicit prices up to 11% larger in magnitude.

Patterns, Trends and Drivers of Water Transparency in Sri Lanka Using Landsat 8 Observations and Google Earth Engine

Abstract: Addressing inland water transparency and driver effects to ensure the sustainability and provision of good quality water in Sri Lanka has been a timely prerequisite, especially under the Sustainable Development Goals 2030 agenda. Natural and anthropogenic changes lead to significant variations in water quality in the country. Therefore, an urgent need has emerged to understand the variability, spatiotemporal patterns, changing trends and impact of drivers on transparency, which are unclear to date. This study used all available Landsat 8 images from 2013 to 2020 and a quasi-analytical approach to assess the spatiotemporal Secchi disk depth (ZSD) variability of 550 reservoirs and its relationship with natural (precipitation, wind and temperature) and anthropogenic (human activity and population density) drivers. ZSD varied from 9.68 cm to 199.47 with an average of 64.71 cm and 93% of reservoirs had transparency below 100 cm. Overall, slightly increasing trends were shown in the annual mean ZSD. Notable intra-annual variations were also indicating the highest and lowest ZSD during the north-east monsoon and south-west monsoon, respectively. The highest ZSD was found in wet zone reservoirs, while dry zone showed the least. All of the drivers were significantly affecting the water transparency in the entire island. The combined impact of natural factors on ZSD changes was more significant (77.70%) than anthropogenic variables, whereas, specifically, human activity accounted for the highest variability across all climatic zones. The findings of this study provide the first comprehensive estimation of the ZSD of entire reservoirs and driver contribution and also provides essential information for future sustainable water management and conservation strategies.

Anthropogenic stress on a Ramsar site, India: Study towards rapid transformation of the health of aquatic environment

Abstract: The East Kolkata Wetlands (EKW) region is an important Ramsar Site (huge provisional, regulatory, cultural and spiritual ecosystem services) which is located at the eastern periphery of Kolkata Metropolitan City (India). But in the recent years, illegal land acquisition, wetlands conversion, aquatic species depletion as well as water pollution related diseases have been experienced in different pockets of EKW region. The main objective is to determine regulating factors and stages of eutrophication. The water samples of consecutive three years 2017, 2018 and 2019 (pre and post monsoon) have been obtained from selective 20 wetlands in EKW. The important physicochemical parameters (temperature, electrical conductivity (EC), turbidity, total alkalinity, pH, total hardness, total dissolved solids (TDS), dissolved oxygen (DO), inorganic nitrogen, total phosphorus, potassium, ammonium-nitrogen (NH4+-N), biological oxygen demand (BOD), Secchi disk depth, chlorophyll - a), trophic status index and statistical techniques (like principal component analysis, hierarchical cluster analysis) have been considered to analyze the water quality of these wetlands. The results portray that the magnification of inorganic nitrogen, total phosphorus, potassium and ammonium-nitrogen accelerates the mechanism of eutrophication in the selective wetlands. The DO level has been diminished during 2019 while the BOD level and chlorophyll concentration have been accelerated amidst 2019.The results reveal that about 40% of wetlands i.e. wetland no. 5, 7, 10, 16, 17 (TSI value – 50–70) and wetland no. 8 and 11 (TSI value – 70–100) come under eutrophic and hyper-eutrophic stages respectively due to higher accumulation of nitrogen and phosphorus contents in the wetlands from various non-point sources and these principal components stimulate the processes of eutrophication of the water bodies. Some relevant mitigation measures have been recommended to protect the “kidney of Kolkata Metropolitan City”.

Citizens and scientists collect comparable oceanographic data: measurements of ocean transparency from the Secchi Disk study and science programmes.

Abstract: Marine phytoplankton accounts for approximately 50% of all photosynthesis on Earth, underpins the marine food chain and plays a central role in the Earth’s biogeochemical cycles and climate. In situ measurements of ocean transparency can be used to estimate phytoplankton biomass. The scale and challenging conditions of the ocean make it a difficult environment for in situ studies, however. Here, we show that citizen scientists (seafarers) using a simple white Secchi Disk can collect ocean transparency data to complement formal scientific efforts using similar equipment. Citizen scientist data can therefore help understand current climate-driven changes in phytoplankton biomass at a global scale.

Retrieval and Spatio-Temporal Variations Analysis of Yangtze River Water Clarity from 2017 to 2020 Based on Sentinel-2 Images

Abstract: The Yangtze River is the third longest river in the world. Monitoring and protecting its water quality are important for economic and social development. Water clarity (Secchi disk depth, SDD) is an important reference index for evaluating water quality. In this study, Sentinel-2 multispectral instrument (MSI) remote sensing images were utilized together with the Forel-Ule index (FUI) and hue angle α to construct an SDD retrieval model, which was applied to the Yangtze River from 2017 to 2020, which was used to describe color in the International Commission on Illumination (CIE) color space to construct an SDD retrieval model that was applied to the Yangtze River for the period 2017–2020. Further, the spatial distribution, seasonal variation, inter-annual variation, and driving factors of the observed SDD variations were analyzed. The spatial distribution pattern of the Yangtze River was high in the west and low in the east. The main driving factors affecting the Yangtze River SDD was sediment runoff, water level, and precipitation. The upstream and downstream Yangtze River SDD were negatively correlated with the change in water level and sediment runoff, whereas the midstream Yangtze River SDD was positively correlated with the change in water level and sediment runoff. The upper and lower reaches of the Yangtze River and overall SDD showed a weak downward trend, and the middle reaches of the Yangtze River remained almost unchanged.

The role of mechanical harvesting on the recession of aquatic vegetation under an extreme water level increase in a eutrophic shallow lake

Abstract: Mechanical harvesting is quick and effective way to remove nuisance macrophytes and improve recreational use and aesthetics in shallow lake. However, applying mechanical harvesting to macrophytes in eutrophic shallow lake with weak resilience and strong perturbation raises concerns of the public and scientific communities. A combination of field investigation and remote sensing was used to determine the potential driving factors of macrophyte degradation in a eutrophic shallow lake from 2014 to 2017, including a comparative analysis of preserved and harvested areas to determine the impacts of mechanical harvesting. Over 95% of macrophytes had disappeared by 2017 in both preserved and harvested areas, with no significant difference in macrophyte distribution area or decline rate between the two by that time. The decline rate in the harvested area (76.7%) was slightly higher than in the preserved area (61.7%) in 2016 after performing the mechanical harvesting in 2015. The results demonstrate that mechanical harvesting is not the definitive driving factor for macrophyte loss, but it could accelerate the decline process. Bottom light availability (Secchi disk depth to water level), which decreased from 0.70 to 0.29 in 2015 and from 0.70 to 0.21 in 2016, is more likely the driving factor, caused by extreme water level increase events in two consecutive years (2015 and 2016) and decreased water clarity. Maintaining water clarity and low water level is crucial for macrophyte restoration.

MODIS-Based Research on Secchi Disk Depth Using an Improved Semianalytical Algorithm in the Yellow Sea

Abstract: Secchi disk depth is a commonly measured parameter representing the optical properties of water bodies. Assessment of water transparency in seas is highly significant to marine-environment monitoring. In this study, an improved Secchi disk depth ( Z SD) inversion algorithm was proposed based on the Poole–Atkins model by determining the parameter A in the original model. The Forel–Ule index (FUI) is a water color parameter that can be obtained from remote sensing data. Through the analysis of the International Ocean Color Coordinating Group dataset, it was found that there are strong logarithmic and quadratic correlations between the FUI and parameter A , whose R 2 values are 0.929 and 0.925, respectively. Comparing the results derived from MODIS product data with the in situ measured data in the Yellow Sea showed that the RMSE and MRE of the quadratic formula are 1.83 m and 43.74%, respectively, which reflect better performance than the other empirical formulas. Thus, parameter A can be expressed in quadratic form with FUI as a variable. Finally, we mapped the ${Z_{{\rm{SD}}}}$ inversion results for the Yellow Sea and analyzed the spatial changes. This study provides new insight for inverting Z SD transparency algorithms and highlights the value of marine transparency monitoring.

The History and Future of the Secchi Disk

Abstract: A standardized method to determine water clarity (transparency) was adopted at the end of the nineteenth century. This method, lowering a 30 cm diameter white painted disk into the water until it disappeared out of sight, was extensively investigated by Alessandra Cialdi and Angelo Secchi and published 1865 in the journal Il Nuovo Cimento Giornale di Fisica, Chimica e Storia Naturale. It is now universally recognized as the Secchi disk method. The Secchi disk method and its corresponding parameter, the Secchi disk depth, today continues to be a subject of scientific investigation and theoretical considerations. It is even available in a smartphone app (www.secchidisk.org), and its data can be visualized in a global historic dataset (www.eyeonwater.org). Algorithms are available and operationally used to convert ocean color satellite data into Secchi disk depth. Combining historical and ongoing Secchi disk observations with satellite products, standardized water clarity products are at hand enabling researchers to assess long-term changes in water clarity in global seas and freshwater environments.

Relationship between algae diversity and water quality- a case study: Chah Niemeh reservoir Southeast of Iran.

Abstract: Algae are known with many detrimental impacts on drinking water quality. Discharge of municipal and agricultural wastewater into the receiving water resources make desirable conditions for algae growth and consequently cause eutrophication phenomena. Water samples were withdrawn monthly from 5 stations in Zabol City within spring and summer seasons. To identify algae species, micronutrients, and physical parameters such as temperature, depth of Secchi disk (SD) and pH on their growth were evaluated. The average phosphate in spring and summer were observed to be 0.034 and 0.028 mg/L, respectively. The results obtained from the present study indicated that the volume and depth of the water reservoirs were less critical on total phosphorus compared with the concentration of algal cells and total nitrogen. The mean pH for water samples taken from Chah Niemeh (CN) in spring and summer were observed to be 8.4 which is suitable for algae growth. Furthermore, the mean temperature (>20 °C) in both seasons were found to be desirable for the growth of algae, especially cyanobacteria in the CN. Moreover, the mean SD in spring and summer samples was 96.16 m and 119.83 m, respectively. As a result, the reservoir had low transparency in terms of algal growth. Totally, most of the identified algae were green algae (50%), algal flagella (19%), cyanobacteria (15.4%) and diatoms (15%). Therefore, cyanobacteria are most possible responsible for the taste and odor in the CN water reservoir. Future efforts should be directed toward preventive measurements for protecting water reservoirs from municipal and agricultural wastewaters and algae control.

Angelo Secchi, Instrument Innovator

Abstract: Angelo Secchi (1818–1878) is best remembered today as a pioneer of the New Astronomy that has become the science of astrophysics. Rather than being an astronomer, Secchi trained as a physicist with an interest and expertise in all of the physical sciences. This paper will examine his technical innovations and use of instruments in astronomy, physics, meteorology and oceanography, with a focus on his contributions both as inventor and improver of existing instrument design.