scholarly journals St Helena Marine Water Quality: Background Conditions and Development of Assessment Levels for Coastal Pollutants

2021 ◽  
Vol 8 ◽  
Author(s):  
Suzanne Jane Painting ◽  
Eleanor K. Haigh ◽  
Jennifer A. Graham ◽  
Simon A. Morley ◽  
Leeann Henry ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Relevant Literature ◽  
Remote Sensing Data ◽  
Euphotic Zone ◽  
Fecal Bacteria ◽  
Chemical Contaminants ◽  
Background Values ◽  
Suspended Particulate ◽  
St Helena

St Helena is an isolated oceanic island located in the tropical South Atlantic, and knowledge of broadscale oceanography and productivity in its surrounding waters is limited. This study used model outputs (2007-2017), remote sensing data (1998-2017) and survey measurements (April 2018 and 2019) to determine background conditions for nutrients, chlorophyll and suspended particulate matter (SPM) in offshore waters and propose standards (thresholds) for assessing inshore water quality based on 50% deviation from seasonal (usually June to November) or annual averages. Seasonal thresholds were proposed for surface nitrate (average 0.18 μM), phosphate (average 0.26 μM), silicate (average 2.60 μM), chlorophyll (average 0.45 μg chl l–1), and SPM (average 0.96 mg l–1). Associated background values for most surface parameters (phosphate 0.17 μM, silicate 1.57 μM, chlorophyll 0.30 μg chl l–1; from model outputs and remote sensing) were slightly higher than offshore observations (April 2019). For nitrate, the average background value (0.12 μM) was lower than the observed average (0.24 μM). At depth (150-500 m), annual background values from model outputs were high (nitrate 26.8 μM, phosphate 1.8 μM, silicate 17.3 μM). Observed water masses at depths >150 m, identified to be of Antarctic and Atlantic origin, were nutrient-rich (e.g., 16 μM for nitrate, April 2019) and oxygen deficient (<4-6 mg l–1). A thermocline layer (between ca. 10 and 230 m), characterized by a sub-surface chlorophyll maximum (average 0.3-0.5 μg chl l–1) near the bottom of the euphotic zone (ca. 100 m), is likely to sustain primary and secondary production at St Helena. For assessing inshore levels of chemical contaminants and fecal bacteria estimated from survey measurements, standards were derived from the literature. A preliminary assessment of inshore observations using proposed thresholds from surface offshore waters and relevant literature standards indicated concerns regarding levels of nutrients and fecal bacteria at some locations. More detailed modeling and/or field-based studies are required to investigate seasonal trends and nutrient availability to inshore primary producers and to establish accurate levels of any contaminants of interest or risk to the marine environment.

Monitoring land use change in the Lake Taupo catchment between 1975, 1990 and 2002 using satellite remote sensing data

2007 ◽  
pp. 17-22
Author(s):  
H. Lilienthal ◽  
A. Brauer ◽  
K. Betteridge ◽  
E. Schnug
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Land Use ◽  
Land Use Change ◽  
Satellite Remote Sensing ◽  
Remote Sensing Data ◽  
Native Vegetation ◽  
Lake Water Quality ◽  
Livestock Farming ◽  
Slow Decline

Conversion of native vegetation into farmed grassland in the Lake Taupo catchment commenced in the late 1950s. The lake's iconic value is being threatened by the slow decline in lake water quality that has become apparent since the 1970s. Keywords: satellite remote sensing, nitrate leaching, land use change, livestock farming, land management

scholarly journals Detecting spatiotemporal variability in the physicochemical properties of water in the Lower Mearim using remote sensing data

2020 ◽  
Vol 42 ◽  
pp. e32
Author(s):  
George Colares Silva Filho ◽  
Juliana Martins dos Santos ◽  
Paulo Cesar Mendes Villis ◽  
Ingrid Santos Gonçalves ◽  
Isael Coelho Correia ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Physicochemical Properties ◽  
Monitoring Program ◽  
Remote Sensing Data ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Spatiotemporal Variability ◽  
Landsat 8 ◽  
Solids Content

Natural or anthropogenic chemical compounds of different origins often accumulate in estuarine regions. These compounds may alter the water quality. Therefore, It is important to constantly monitor the quality of estuarine regions. A combination of remote sensing and traditional sampling can lead to a better monitoring program for water quality parameters. The objective of this work is to assess the spatiotemporal variability of the physicochemical properties of water in the lower region of the Mearim River and estimate water quality parameters via remote sensing. Samples were collected at 16 points, from Baixo Arari to the mouth of the watershed, using a multiparameter meter and Landsat 8 satellite images. The physicochemical parameters of the water had high salinity levels, between 2.30 and 20.10 parts per trillion; a high total dissolved solids content, between 2.77 and 19.70 g/L; and minimum dissolved oxygen values. Estimating the physicochemical properties of the water via remote sensing proved feasible, particularly in the dry season when there is less cloud cover.

Investigation of Highway Stormwater Management Pond Capacity for Flood Detention and Water Quality Treatment Retention via Remote Sensing Data and Conventional Topographic Survey

2020 ◽  
Vol 2674 (7) ◽  
pp. 514-527
Author(s):  
Houng Li
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Stormwater Management ◽  
Retention Volume ◽  
Remote Sensing Data ◽  
Stormwater Ponds ◽  
Topographic Survey ◽  
Storage Volume ◽  
Lidar Dem ◽  
Over Time

Stormwater management ponds are common best management practice (BMP) and green infrastructure (GI) for flood attenuation and water quality treatment in highway projects. Originally designed to provide storage volume for flood detention, stormwater ponds today often employ additional retention volume at pond bottom in a hope to improve water quality via sedimentation and other pollutant-removal mechanisms. It is commonly assumed that sediment accumulation and topographic variations (such as erosion, channelization, and in-pond plant growth and decay) over time often decrease the capacity of stormwater ponds. However, differences between design capacities and field capacities over time have never been verified and quantitatively analyzed before. This study presents such analysis using conventional topographic survey techniques and remote sensing data (topographic light detection and ranging digital elevation model [LIDAR DEM]) for 10 highway stormwater ponds along Interstate Highway-95 (I-95) systems in Baltimore City, Cecil County, and Harford County, Maryland, United States, with facility service life ranging from 14 to 26 years (1990–2015). Data derived from LIDAR DEM were compared with those from topographic survey; the LIDAR DEM data appear to be effective in measuring flood detention capacities and identifying silted ponds, but not in estimating the remaining retention volume for water quality treatment. Data from topographic survey indicate that the total volume in the ponds was relatively unchanged compared with the design, with increases in some instances. The increase typically occurred at the pond’s upper stages. Nonetheless, the water quality treatment capacity at pond bottom (wet pool volume) was drastically less (up to 100% of the design). As current maintenance practice of stormwater ponds relies heavily on visual inspection, the storage volume variations are often overlooked. As such, the findings prompt uncertainty on the long-term effectiveness of watershed implementation plan and models in the Chesapeake Bay watersheds, as many of them depend on wet pool volume design in BMP and GI.

scholarly journals Automatic calibration of a large-scale sediment model using suspended sediment concentration, water quality, and remote sensing data

RBRH ◽  
2019 ◽  
Vol 24 ◽  
Author(s):  
Hugo de Oliveira Fagundes ◽  
Fernando Mainardi Fan ◽  
Rodrigo Cauduro Dias de Paiva
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Suspended Sediment ◽  
Large Scale ◽  
Suspended Sediment Concentration ◽  
Remote Sensing Data ◽  
Sediment Concentration ◽  
Spatial Discretization ◽  
Calibration And Validation ◽  
Sediment Model

ABSTRACT Calibration and validation are two important steps in the application of sediment models requiring observed data. This study aims to investigate the potential use of suspended sediment concentration (SSC), water quality and remote sensing data to calibrate and validate a large-scale sediment model. Observed data from across 108 stations located in the Doce River basin was used for the period between 1997-2010. Ten calibration and validation experiments using the MOCOM-UA optimization algorithm coupled with the MGB-SED model were carried out, which, over the same period of time, resulted in 37 calibration and 111 validation tests. The experiments were performed by modifying metrics, spatial discretization, observed data and parameters of the MOCOM-UA algorithm. Results generally demonstrated that the values of correlation presented slight variations and were superior in the calibration step. Additionally, increasing spatial discretization or establishing a background concentration for the model allowed for improved results. In a station with high quantity of SSC data, calibration improved the ENS coefficient from -0.44 to 0.44. The experiments showed that the spectral surface reflectance, total suspended solids and turbidity data have the potential to enhance the performance of sediment models.

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