Monitoring levels of cyanobacterial blooms using the visual cyanobacteria index (VCI) and floating algae index (FAI)

Cyanobacterial bloom is a growing environmental problem in inland waters. In this study, we propose a method for monitoring levels of cyanobacterial blooms from Landsat/ETM+ images. The visual cyanobacteria index (VCI) is a simple index for in-situ visual interpretation of cyanobacterial blooms levels, by classifying them into six categories based on aggregation (e.g., subsurface blooms, surface scum). The floating algae index (FAI) and remote sensing reflectance in the red wavelength domain, which can be obtained from Landsat/ETM+ images, were related to the VCI for estimating cyanobacteria bloom levels from the Landsat/ETM+ images. Nine field campaigns were carried out at Lakes Nishiura and Kitaura (Lake Kasumigaura group), Japan, from June to August 2012. We also collected reflectance spectra at 20 stations for different VCI levels on August 3, 2012. The reflectance spectra were recalculated in correspondence to each ETM+ band, and used to calculate the FAI. The FAI values were then used to determine thresholds for classifying cyanobacterial blooms into different VCI levels. These FAI thresholds were validated using three Landsat/ETM+ images. Results showed that FAI values differed significantly at the respective VCI levels except between levels 1 and 2 (subsurface blooms) and levels 5 and 6 (surface scum and hyperscum). This indicated that the FAI was able to detect the high level of cyanobacteria that forms surface scum. In contrast, the Landsat/ETM+ band 3 reflectance could be used as an alternative index for distinguishing surface scum and hyperscum. Application of the thresholds for VCI classifications to three Landsat/ETM+ images showed that the volume of cyanobacterial blooms can be effectively classified into the six VCI levels.     

Bathymetrical influences on spatial and temporal characteristics of chlorophyll-a concentrations in the Southern Ocean from 2002 to 2012 (October to March) using MODIS

Phytoplankton blooms, particularly in the Southern Ocean, can have significant impact on global biogeochemistry cycling. To investigate the accuracy of chlorophyll-a distribution, and to better understand the spatial and temporal dynamics of phytoplankton biomass, we examine chlorophyll-a estimates (October–March from 2002 to 2012) derived from Moderate Resolution Imaging Spectrometer (MODIS) data following the ocean chlorophyll-a 3 model (OC3M) algorithm. Noticeable seasonality occurs in the temporal distribution of chlorophyll-a concentrations, which shows the highest value in December and January and an increasing tendency during the 2002–2012 period. The spatial distribution of chlorophyll-a varies greatly with latitude, as higher latitudes experience more phytoplankton blooms (chlorophyll-a concentration larger than 1 mg/m³) and marginal seas (Ross Sea and Amundsen Sea) show different bloom anomalies caused by two dominant algae species. Areas at higher latitudes and shallow water (<500 m) experience the shorter ice-free periods with greater seasonality. A noticeable bathymetry gradient exists at 2500-m isobaths, while water at the 500–2500-m depth experiences quite long ice-free periods with a stable water environment. Blooms generally occur near topographic features where currents have strong interactions when the water depth is more than 2500 m. Based on these findings, we can classify the Southern Ocean into two bloom subregions, 0–500 m as an enhanced bloom zone (EBZ), and 500–2500 m as a moderate bloom zone (MBZ). The EBZ has a quite high-bloom probability of about 30%, while the MBZ has only 10%.     

基于激光测高数据的丹江口水库水位变化监测

针对多源星载激光测高数据监测湖泊水位变化问题,该文选取2003—2009年ICESat/GLAH14全球地表高程数据、2018年10月—2019年8月的ICESat-2/ATL13全球内陆水体高程数据,提取丹江口水库多期水位变化数据,最后利用水位站实测水位对其准确度进行了验证,并分析了丹江口水库年度水位变化规律。结果表明,丹江口水库水位呈现明显的季节性变化,每年11月达到较高水位,3月降至较低水位;由ICESat/GLAH14数据估算水库水位的精度为16 cm,ICESat-2/ATL13数据集估算水库水位的精度达到10 cm。因此,ICESat-2/ATL13数据用于内陆水体水位变化监测具有很高的可行性。     

Characterization of spatial and temporal variation of suspended sediments in the Yellow and East China Seas using satellite ocean color data

Total suspended sediment (TSS) data concentrations are retrieved from two sets of satellite ocean color data (the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua and the Korean Geostationary Ocean Color Imager (GOCI)) using an existing regional model to characterize spatial and temporal variation of TSS in the Yellow and East China Seas. MODIS-derived TSS maps show that TSS concentrations are, in general, high along the Korean and Chinese coasts including the Bohai Sea and the Yangtz River estuary, and lower in the middle of the Yellow Sea and the southeastern area of the East China Sea. The monthly average of 10-year MODIS data reveals that TSS values are highest during winter (January to February) and lowest in summer (July to August). Short-term TSS concentrations retrieved from GOCI data showed the dominant influence of semi-diurnal tidal changes on sediment dynamics through temporal (hourly) and spatial distribution in coastal zones of the Yellow sea. The results presented here demonstrate that the satellite-derived TSS products can be utilized as an application tool for future studies on long- and short-term sediment dynamics of turbid coastal waters. In particular, GOCI observations provide unique important capabilities to characterize and quantify the water properties at high temporal (hourly) and spatial (0.5 km) resolutions in the turbid coastal waters of the Yellow Sea and its vicinities.     

Effect of dust storm on ocean color and snow parameters

The present study clearly shows the influence of dust storms on chlorophyll bloom in the offshore region of the Arabian Sea, with a time lag of few days, during the pre-monsoon season. Various satellite derived parameters over the Arabian Sea, Himalayan and Tibet snow covered regions show large changes due to the influence of dust storms. The MODIS snow albedo gives unreliable values under the influence of dust storms due to increase in the aerosol loading over these regions and snow albedo product must be used in combination with snow pixel counts during the dust storm season. A detailed study is required for the quantitative evaluation of dust storms on the chlorophyll blooms in the Arabian Sea region and on the snow parameters in the Himalayan region.     

Plume and bloom: effect of the Mississippi River diversion on the water quality of Lake Pontchartrain

The opening of the Bonnet Carré spillway to prevent flood threat to New Orleans in April 2008 created a sediment plume in the Lake Pontchartrain. The nutrient rich plume triggered a massive algal bloom in the lake. In this article, we have quantified the spatio-temporal distribution of the plume (suspended solids) and the bloom (chlorophyll-a (chl-a)) in the lake using remotely-sensed data. We processed the Moderate-resolution Imaging Spectroradiometer satellite data for mapping the total suspended solids (TSS) and chl-a concentrations. An existing algorithm was used for estimating TSS whereas a novel slope model was developed to predict the per-pixel chl-a concentration. Both algorithms were successful in capturing the spatio-temporal trend of TSS and chl-a concentrations, respectively. Algal growth was found to be inversely related to TSS concentrations and a time lag of ～45 days existed between the spillway opening and the appearance of the first algal bloom at an observation location.     

Remote determination of chromophoric dissolved organic matter in lakes,China

Chromophoric dissolved organic matter (CDOM) strongly influences the water-leaving radiance from aquatic ecosystems. In most inland waters, the remote determination of CDOM absorption presents a central challenge due to their complex optical conditions. However, identifying the temporal and spatial variability of CDOM is fundamental to the understanding of aquatic biogeochemical dynamics. In the present study, semi-analytical and empirical modeling approaches were used to examine CDOM absorption in four, shallow, inland water bodies using the spectral bands and sensitivities of major satellite observational systems. Of the models examined, an empirical multiband model was found to provide the highest correlation with measured CDOM absorption. The spectral characteristics of the MERIS sensors yielded the best results with respect to the other available satellite sensors. High detrital load was observed to be a major impediment to estimating CDOM absorption, while lakes with elevated phytoplankton biomass did not present similar problems.     

Analyzing ice dynamics using Sentinel-1 data at the Solheimajoküll Glacier,Iceland

ABSTRACT

The climate in southern Iceland has warmed over the last 70 years, resulting in accelerated glacier dynamics at the Solheimajoküll glacier. In this study, we compare glacier terminus locations from 1973 to 2018, to changes in climate across the study area, and we derive ice-surface velocities (2015–2018) from satellite remote-sensing imagery (Sentinel-1) using the offset-tracking method. There have been two regional temperature trends in the study period: cooling (1973–1979) and warming (1980–2018). Our results indicate a time lag of about 20 years between the onset of glacier retreat (?53 m/year since 2000) and the inception of the warming period. Seasonally, the velocity time series suggest acceleration during the summer melt season since 2016, whereas glacier velocities during accumulation months were constant. The highest velocities were observed at high elevations where the ice-surface slope is the steepest. We tested several scenarios to assess the hydrological time response to glacier accelerations, with the highest correlations being found between one and 30 days after the velocity estimates. Monthly correlation analyses indicated inter-annual and intra-annual variability in the glacier dynamics. Additionally, we investigate the linkage between glacier velocities and meltwater outflow parameters as they provide useful information about internal processes in the glacier. Velocity estimates positively correlate with water level and negatively correlate with water conductivity between April and August. There is also a disruption in the correlation trend between water conductivity and ice velocity in June, potentially due to a seasonal release of geothermal water.     

Satellite and In Situ Observations of a Phytoplankton Bloom from Coastal Bay of Bengal: Role in pCO<Subscript>2</Subscript> Modulation

A phytoplankton bloom was monitored in coastal waters of Bay of Bengal and its influence in water column properties was investigated. Significant draw down of CO₂ was noted within the vicinity of the bloom associated with high chlorophyll biomass. Microscopic analysis revealed diatoms as the dominant population. Skeletonema costatum a diatom, reached cell density of 36,898 cells l^?1 within the bloom. The lowest surface pCO₂ observed was 287 µatm at the southern end of the transect covarying with surface chlorophyll of 1.090 µg l^?1. At the northern end the surface pCO₂ went as low as 313 µatm. The pCO₂ levels below the mixed layer increased twice of that of surface value (~600 µatm). The chlorophyll values observed by Ocean Colour Monitor-2 were modestly related with the in situ measurements. The primary productivity derived from growth rate, assimilation number and maximum surface chlorophyll was 160.6 mg C m^?2 day^?1 leading to a modest sequestration ~of 0.08 Gg of carbon per day by the surface waters. Our observations reflects the potential role of diatom blooms on coastal carbon dynamics therefore should be carefully monitored in realm of anthropogenic changes.     

联合卫星测高、GRACE、海洋和气象资料研究南海海水质量变化

首先利用重力恢复与气候实验（gravity recovery and climate experiment,GRACE）卫星重力、卫星测高和海洋温盐数据分析了2003-2012年间南海海水质量的变化特征,进而结合海洋和气象资料探讨了厄尔尼诺和南方涛动（El Ni?o-Southern Oscillation,ENSO）、净淡水通量、海水体积输送和陆地径流在此期间对南中国海海水质量变化的影响。研究结果表明,南海海水质量变化主要受海面净淡水通量和海水体积输送的联合调制影响,周边陆地径流对其影响有限。南海海水质量季节性变化显著,且具有明显的长期增加趋势;ENSO通过改变降水和黑潮自吕宋海峡流入南海的水量影响南海海水质量,使得南海海水质量存在着显著的具有ENSO特征的年际变化。     

基于MODIS 数据的悬浮泥沙定量遥感方法

以黄海及东海海域为对象,研究用MOD IS数据提取我国海域悬浮泥沙时空分布的定量遥感方法,建立了基于MOD IS数据的悬浮泥沙定量遥感实用模式。研究表明,用250 m和1 000 m分辨率的MOD IS数据进行悬浮泥沙浓度的定量遥感,可以达到实际应用的精度要求。这说明,MOD IS数据是研究近岸水体中悬浮物输运变化规律的一种经济实用数据源。     

基于卫星雷达测高技术的湖库动态监测理论、方法和研究进展

水位是反映水体变化的重要变量,利用卫星测高技术获取湖库的水位信息,很大程度上改变了传统地面观测数据匮乏的现状.本文综述了卫星雷达测高技术在湖泊和水库动态监测方面的理论、主要的数据处理方法和数据产品,以及当前的主要研究进展.从文献检索可以看出,当前的应用研究对象主要聚焦在个别湖泊或小范围内的湖泊群;在数据处理方面,数据以...     

Comparison of Inherent Optical Properties (IOPs) in Open and Coastal Waters of Arabian Sea Using In-Situ Bio-Optical Data

The two main inherent optical properties (IOPs) namely absorption and back scattering coefficients were estimated using a quasi analytical algorithm (QAA) for open and coastal ocean waters of Arabian Sea. Absorption due to gelbstoff and back scattering due to the particulate matter were calculated using the quasi analytical algorithm for all the in-situ measured reflectance spectra collected in the Arabian Sea. A comparative study was made to study the spectral variability of reflectance spectra in open as well as coastal waters of Arabian Sea. Spectral analysis was made for the absorption and back scattering coefficients calculated using the QAA for both open and coastal waters. The absorption coefficient in the open ocean waters vary from a minimum value of 0.029 to a maximum value of 0.445 and it varies from a minimum value of 0.081 to a maximum value of 4.000 for the coastal waters of Arabian Sea. Absorption due to gelbstoff or the CDOM a_g(λ), calculated for the Arabian Sea waters show a variation of 0.000202 to 0.112437 for open ocean waters and it varies from 0.002848 to 2.8936 for coastal waters of Arabian Sea. Particulate back scattering coefficient for open ocean waters vary from 0.0000307 to 0.006575 whereas b_bp(λ) vary from 0.000167 to 0.026014 for coastal ocean waters. The minimum slope for the open ocean waters is 0.989 and maximum value of 2.147 (average value of 1.7) was observed; whereas a minimum value of 0.046 and a maximum value of 1.201 (average value of 0.6) were observed from the in-situ spectra for coastal waters of Veraval. The slope ‘Y’ estimated from the model is 1.957 for open ocean waters and 0.515 for coastal waters collected in the Arabian Sea.     

Polynya Area in the Kara Sea, Arctic, Obtained With Microwave Radiometry for 1979–2003

The polynya signature simulation method is applied to satellite microwave radiometry data to get the mean (January-April) polynya distribution in the Kara Sea for 1995-2004. Temporal variability of polynya location and extent is confirmed with the variability of ERA40 surface wind speeds. The mean (January-April) fraction of ice area of 65%-85% ice concentration relative to the mean daily total Kara Sea ice area agrees well (correlation coefficient: 0.79) with the mean daily total Kara Sea polynya area for 1996-2003. The resulting linear fit is used to extend the polynya area time series until 1979. During 1979-2003, the polynya area increased by 2400 km²/dec. This is accompanied with slightly increasing southerly winds. Polynyas in the eastern Kara Sea seem to play a nonnegligible role for the winter-time Kara Sea ice export.     

Combining multisource satellite data to estimate storage variation of a lake in the Rift Valley Basin,Ethiopia

Integration of remote sensing data sets from multiple satellites is tested to simulate water storage variation of Lake Ziway, Ethiopia for the period 2009-2018. Sixty Landsat ETM+/OLI images served to trace temporal variation of lake surface area using a water extraction index. Time series of lake levels were acquired from two altimetry databases that were validated by in-situ lake level measurements. Coinciding pairs of optical satellite based lake surface area and radar altimetry based lake levels were related through regression and served for simulating lake storage variation. Indices for extracting lake surface area from images showed 91–99 % overall accuracy. Lake water levels from the altimetry products well agreed to in-situ lake level measurements with R² = 0.92 and root mean square error of 11.9 cm. Based on this study we conclude that integrating satellite imagery and radar altimetry is a viable approach for frequent and accurate monitoring of lake water volume variation and for long-term change detection. Findings indicate water level reduction (4 cm/annum), surface area shrinkage (0.08km²/annum) and water storage loss (20.4Mm³/annum) of Lake Ziway (2009–2018).     

Quantification of suspended solids in Dal lake,Srinagar using remote sensing technology

Indian Remote Sensing satellite (IRS)-1B, Linear Imaging Self Scanner (LISS)-II spectral digital data was analysed to determine the feasibility of quantifying the concentration of suspended solids in the surface water of inland water body, Dal lake, in Srinagar, India. The water samples collected in concurrent with IRS-1B overpass, were analysed to determine the concentration of suspended solids. The results indicate that a positive functional relationship exist between the concentration of suspended solids and the visible wave length bands 1 and 3 and near infrared band 4. It has been observed that as the concentration of suspended solids increase, the spectral response also increases. It is concluded that IRS LISS-H data can be effectively used to quantify suspended sediment concentration in the Dal lake surface water.     

An improved atmospheric correction algorithm for applying MERIS data to very turbid inland waters

Atmospheric correction (AC) is a necessary process when quantitatively monitoring water quality parameters from satellite data. However, it is still a major challenge to carry out AC for turbid coastal and inland waters. In this study, we propose an improved AC algorithm named N-GWI (new standard Gordon and Wang’s algorithms with an iterative process and a bio-optical model) for applying MERIS data to very turbid inland waters (i.e., waters with a water-leaving reflectance at 864.8 nm between 0.001 and 0.01). The N-GWI algorithm incorporates three improvements to avoid certain invalid assumptions that limit the applicability of the existing algorithms in very turbid inland waters. First, the N-GWI uses a fixed aerosol type (coastal aerosol) but permits aerosol concentration to vary at each pixel; this improvement omits a complicated requirement for aerosol model selection based only on satellite data. Second, it shifts the reference band from 670 nm to 754 nm to validate the assumption that the total absorption coefficient at the reference band can be replaced by that of pure water, and thus can avoid the uncorrected estimation of the total absorption coefficient at the reference band in very turbid waters. Third, the N-GWI generates a semi-analytical relationship instead of an empirical one for estimation of the spectral slope of particle backscattering. Our analysis showed that the N-GWI improved the accuracy of atmospheric correction in two very turbid Asian lakes (Lake Kasumigaura, Japan and Lake Dianchi, China), with a normalized mean absolute error (NMAE) of less than 22% for wavelengths longer than 620 nm. However, the N-GWI exhibited poor performance in moderately turbid waters (the NMAE values were larger than 83.6% in the four American coastal waters). The applicability of the N-GWI, which includes both advantages and limitations, was discussed.     

Spatial variations of small phytoplankton contributions in the Northern Bering Sea and the Southern Chukchi Sea

Phytoplankton size classes (hereafter, PSCs) were derived from satellite ocean color data using a present phytoplankton abundance-based optical algorithm in the northern Bering and southern Chukchi Seas to characterize the spatial and seasonal variations of the different PSC and investigate the contributions of small phytoplankton to the total phytoplankton biomass. The comparison results showed that the phytoplankton abundance-based method approach could reasonably classify the three PSCs (pico-, nano-, and micro phytoplankton). The satellite maps of the dominant PSCs were derived using long-term satellite ocean color data. The general spatial distribution showed that the large (micro-) phytoplankton were dominant in the coastal waters and the west side of the Bering strait, while the small size (nano- or pico-) phytoplankton were dominant in the open ocean waters. Nano- and microphytoplankton were dominant in May and October in most of the study area, while pico-phytoplankton were dominant in the summer months in the open ocean waters. The annual variation in small phytoplankton dominance had a strong positive relationship with the annual mean sea surface temperature (SST), which is consistent with the increasing dominance of small phytoplankton biomass as water temperature increases. Microphytoplankton have an apparent increasing trend in the southeastern Chukchi Sea but slightly decreasing trends in Chirikov and St. Lawrence Island Polynya (SLIP). In contrast, there were increasing trends in picophytoplankton in Chirikov and SLIP, which seems to be related to increasing annual SST. It is crucial to monitor changes in dominant groups of phytoplankton community in the Bering and Chukchi Seas as important biological hotspots responding to the recent changes in environmental conditions.     

近岸/内陆典型水环境要素定量遥感空间尺度问题研究

近岸/内陆水环境遥感的空间尺度问题研究包括空间变异尺度及遥感监测空间尺度需求,以及多源多尺度遥感数据及定量产品的空间尺度误差两个方面。利用长时序高分一号16 m遥感数据集高时空分辨率的综合优势,采用空间半变异函数分析方法获取了中国近岸/内陆典型水环境要素（以悬浮颗粒物为例）的空间变异尺度。基于水环境要素空间变异的连续性和泰勒级数展开理论,定量化地描述了空间尺度误差解析函数。结果表明,近岸/内陆水体等高动态水体的空间变异尺度平均在150 m以下,而外海等相对稳定水体空间变异尺度在300 m以上。随着空间分辨率的降低,受到空间变异和水环境要素非线性定量反演模型的共同影响,悬浮颗粒物的空间尺度误差显著增大,亟需重点研究区域化的尺度误差校正方法。     

Application of Aqua MODIS sensor data for estimating chlorophyll a in the turbid Case 2 waters of Lake Erie using bio-optical models

There is considerable interest in accurately estimating water quality parameters in turbid (Case 2) and eutrophic waters such as the Western Basin of Lake Erie (WBLE). Lake Erie is a large, open freshwater body that supports diverse ecosystem, and over 12 million people in the mid-western part of the United States depend on it for drinking water, fisheries, navigational, and recreational purposes. The increasing utilization of the freshwater has deteriorated the water severely and currently the lake is experiencing recurring harmful algal blooms (HABs). Improving the water quality of Lake Erie requires the use of robust monitoring tools that help water quality managers understand sources and pathways of influxes that trigger HABs. Satellite-based remote sensing sensor such as the moderate resolution imaging spectroradiometer (MODIS) may provide frequent and synoptic view of the water quality indices. In this study, data set from field measurements was used to evaluate the performance of 14 existing ocean color algorithms. Results indicated that MODIS data consistently underestimated the chlorophyll a concentrations in the WBLE, with the largest source of errors from dissolved organic matter and xanthophyll accessory pigments in this data set. Most of the global algorithms, including OC4v4 and the Baltic model, generated near-identical statistical parameters with an average R² of ~0.57 and RMSE ~2.9 μg/l. MODIS performed poorly (R² ~0.18) when its NIR/red bands were used. A slightly improved model was developed using similar band ratio approach generating R² of ~0.62 and RMSE ~1.8 μg/l.