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HJ 1098-2020 English PDF

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HJ 1098-2020: Technical specifications for monitoring and evaluating algal bloom based on remote sensing and field monitoring
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Basic data

Standard ID	HJ 1098-2020 (HJ1098-2020)
Description (Translated English)	Technical specifications for monitoring and evaluating algal bloom based on remote sensing and field monitoring
Sector / Industry	Environmental Protection Industry Standard
Word Count Estimation	16,112
Date of Issue	2020
Date of Implementation	2020-04-12
Issuing agency(ies)	Ministry of Ecology and Environment

HJ 1098-2020: Technical specifications for monitoring and evaluating algal bloom based on remote sensing and field monitoring

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Technical specifications for monitoring and evaluating algal bloom based on remote sensing and field monitoring National Environmental Protection Standards of the People's Republic of China Technical Specifications for Water Bloom Remote Sensing and Ground Monitoring and Evaluation (Trial) 2020-02-12 release 2020-04-12 Implementation Issued by the Ministry of Ecology and Environment

Foreword...ii 1 Scope of application...1 2 Normative references...1 3 Terms and definitions...1 4 Water bloom remote sensing monitoring...3 5 Water bloom ground monitoring...7 6 Evaluation of the degree of blooming...9

Foreword

To implement the Environmental Protection Law of the People’s Republic of China and the Water Pollution Prevention Law of the People’s Republic of China, and protect the ecology The environment, safeguard human health, regulate and guide the monitoring and evaluation of algae blooms in freshwater bodies in my country, and formulate this standard. This standard specifies remote sensing monitoring methods for algae blooms in freshwater bodies, ground monitoring methods, and evaluation methods for the degree of blooms, etc. content. This standard is issued for the first time. This standard was formulated by the Department of Ecological Environment Monitoring and the Department of Regulations and Standards of the Ministry of Ecology and Environment. Drafting organizations of this standard. China Environmental Monitoring Center, Satellite Environment Application Center of Ministry of Ecology and Environment. This standard was approved by the Ministry of Ecology and Environment on February 12, 2020. This standard will be implemented on April 12, 2020. This standard is interpreted by the Ministry of Ecology and Environment. Technical specifications for water bloom remote sensing and ground monitoring and evaluation

1 Scope of application

This standard specifies the remote sensing monitoring methods for cyanobacteria blooms in freshwater bodies, ground monitoring methods, and the evaluation methods for water bloom levels. Content. The monitoring and evaluation of dinoflagellate, diatom and other algae blooms can refer to this standard. This standard applies to the monitoring, evaluation and management of water blooms in freshwater lakes and reservoirs in my country. Water bloom monitoring and evaluation of other freshwater bodies can be Refer to this standard.

2 Normative references

The content of this standard refers to the following documents or their clauses. For undated references, the latest version is suitable Used in this standard. GB/T 14950 Terminology for Photogrammetry and Remote Sensing GB/T 30115 Satellite Remote Sensing Image Vegetation Index Product Specification

3 Terms and definitions

The following terms and definitions defined in GB/T 14950 and GB/T 30115 apply to this standard. 3.1 Algal bloom A natural ecological phenomenon in which algae bloom in large quantities in freshwater bodies. The apparent feature is that there are algae aggregation or algae on the surface of the water body. The particles are suspended in a body of water. 3.2 Algal density The number of algae cells per unit volume of water sample. Unit. Pieces/L. 3.3 Algal bloom area The area covered by algae when floating on the water. 3.4 Algal bloom area proportion The percentage (%) of water bloom area in the monitored water body area. 3.5 Algal bloom level Reflecting the strong and weak characteristics of water bloom, it is judged according to the density of algae in the water body or the proportion of water bloom area. 3.6 Standard false color composite image According to the principle of additive color synthesis, the near red, red, and green bands of remote sensing images are passed through the red, green, and blue filter systems respectively The color image produced by the system synthesis. 3.7 Spatial resolution Refers to the size of the ground area represented by the pixel. 3.8 Temporal resolution The shortest time interval during which the sensor can repeatedly obtain images of the same area. 3.9 Radiometric calibration According to the calibration equation and calibration coefficient of the remote sensor, the quantized digital gray value recorded by it is converted into the corresponding field appearance The process of radiance. 3.10 Geometric correction In order to eliminate the geometric distortion of the image, the correction work such as projection transformation and the matching of different band images. 3.11 Atmosphere correction Eliminate or weaken the radiation distortion caused by absorption or scattering in atmospheric transmission when satellite remote sensing images are acquired. 3.12 Digital gray value digital number (DN) The gray level quantified by the reflected or radiated energy obtained by the remote sensor in each band. 3.13 Apparent radiance The radiance at the top of the atmosphere is the radiance at the entrance pupil of the satellite remote sensor. 3.14 Apparent reflectance The ratio between the apparent radiance and the absolute white body assumption of the scene without atmospheric level should be obtained by the remote sensor. 3.15 Surface reflectance The ratio of the reflected energy from the surface of the feature to the incident energy that reaches the surface of the feature. 3.16 Normalized difference vegetation index (NDVI) The ratio of the difference between the values of the near-infrared band and the red band of visible light to the sum of the values of the two bands. 3.17 Normalized difference vegetation index of digital number (NDVIDN) The normalized vegetation index calculated based on the digital gray value (DN). 3.18 Normalized difference vegetation index of top of atmospheric reflectance (NDVITOA) The normalized vegetation index calculated using the apparent reflectivity of the top of the atmosphere. 3.19 Normalized difference vegetation index of bottom of atmosphere atmospheric reflectance (NDVIBOA) The normalized vegetation index calculated using atmospherically corrected surface reflectance. 3.20 Routine monitoring Routine monitoring behavior for the purpose of systematically mastering and monitoring the condition of algae in water bodies. 3.21 Warning monitoring During the sensitive period of water bloom, the purpose of monitoring the growth and development of algae in the water body in time, and judging the risk of water bloom occurrence Monitor behavior. 3.22 Emergency monitoring During the blooming period, the monitoring behavior for the purpose of tracking and monitoring the algae bloom in the water body. 4.6.1 Selection of remote sensing data Select satellite remote sensing images with red light (630 nm ~ 690 nm) and near infrared (760 nm ~ 900 nm) bands data. The spatial resolution should depend on the size of the monitored water body. The smaller the water body area, the higher the spatial resolution requirement. Remote sensing The image data covers at least 90% of the monitored water body; in the monitored water body, the cloud coverage is less than 50%. Amphibious mask, The coordinate system and projection of auxiliary data such as cloud mask, aquatic mask and observation geometric conditions should be consistent with the remote sensing image data. 4.6.2 Geometric correction Based on the reference image or spatial geometric information, carry out image geometric accuracy correction and spatial projection conversion, and the accuracy is controlled within 1 Within pixels. 4.6.3 Spatial clipping Based on the latitude and longitude of the upper left corner and lower right corner of the monitored water body area, the selected remote sensing image is spatially cropped, and the scope is Slightly larger than the water body area. 4.6.4 Radiation calibration Radiation calibration is performed according to the calibration formula of the remote sensor and the calibration coefficients of each band. The general form of the radiation calibration formula is. 4.6.6 Atmospheric correction Satellite remote sensing atmospheric correction in the visible and near-infrared bands is mainly aimed at atmospheric molecular scattering, aerosol scattering and water The effect of vapor absorption. Methods based on radiation transfer models (such as 6S model, Flaash atmospheric correction model, etc.) can be used Perform atmospheric correction to obtain the surface reflectivity of each band, also known as the bottom of the atmosphere reflectivity ρBOA. 4.6.8 Separation of water and land, cloud identification and water and grass identification In order to avoid misjudgment of cyanobacteria blooms, the monitored water area should be accurately identified based on the actual situation, and clouds, water plants, etc. should be eliminated The formation of auxiliary data such as water masks, cloud masks, and aquatic masks for monitoring water bodies to obtain water containing blue algae blooms The NDVI value of all pixels in the body area can be obtained by different processing methods to obtain NDVIDN, NDVITOA and NDVIBOA of the pixels. 4.6.9 Threshold segmentation and water bloom binary image For the NDVIDN and NDVITOA data of the water body area, the NDVI value of the cyanobacteria bloom is higher than that of the normal water body. Without atmospheric correction, the NDVI threshold for identifying cyanobacteria blooms will vary with different images, and remote sensing false color needs to be combined Color composite image visual recognition or NDVI gray histogram statistics to determine, the NDVI value is higher than the threshold value is cyanobacteria bloom. According to the NDVIBOA data of the water body area that has been accurately corrected by the atmosphere, the threshold for distinguishing the water bloom from the normal water body can be set Pixels with NDVI value higher than 0 are cyanobacteria blooms. The cyanobacteria bloom pixel is assigned a value of 1, and other features (including normal water bodies, clouds, land, etc.) are assigned a value of 0 to obtain Binary graph of blooms. 4.6.10 Calculation of water bloom area and water bloom area ratio Count the total number of water bloom pixels based on the water bloom binary graph, and multiply it by the actual area corresponding to each pixel to calculate the water bloom area; Divide the water bloom area by the water body area to obtain the water bloom area ratio (percentage).

5 Water bloom ground monitoring

5.3.1 Layout principles Combining the natural geographic and climatic conditions of the monitoring area, select representative ones according to the monitoring purpose (routine, early warning, emergency) Algae bloom monitoring points are set up in the waters of China. The point layout should be as consistent as possible with the conventional physical and chemical indicator monitoring point layout. Sufficient to obtain continuous data needs. 5.3.2 Layout method Lake (reservoir) algae bloom monitoring points are generally located in the lake inlet area, lake outlet area, central area and other areas prone to storms. Waters with blooms. Wider rivers need to have points on the left and right sides of the nearshore at the same time, which is affected by the tide (backwater) The river should consider setting up points in the retrospective (backwater) area and the control area, and the drinking water source area must be located near the water intake point. Deploy routine monitoring points at locations where algae blooms are frequent and environmental conditions are representative for routine monitoring and early warning Monitoring is convenient for long-term and continuous monitoring. For sudden blooms, emergency monitoring points should be set up according to the on-site situation, that is, temporary The point is used to judge the occurrence, development and change of this algae bloom. 5.4.1 Routine monitoring The regular monitoring frequency is at least once a month, and the sampling period is in principle from 9.00 to 16.00.In actual monitoring, Increase or decrease the frequency appropriately, and stop monitoring during the freezing period. 5.4.2 Early warning monitoring The frequency of early warning monitoring is at least once a week and not less than 4 times a month. The monitoring time is the 1st to 3rd day of the week. The sampling period The principle is from 9.00 to 16.00. 5.4.3 Emergency monitoring Emergency monitoring shall be conducted at least once every two days. The monitoring index is the density of algae. The monitoring period is in principle from 9.00 to 16.00. 5.5.2 On-site records Ensure that the basic sampling information is complete. In addition to regular items, the record should also include water color, water color, Algae population shape (stripes, flakes), group size, and algae state (granular, muddy) and other blooms on the water surface Characterization description. 5.5.3 Sample storage and transportation For the samples collected on site, add 15 ml of Lugol's solution to each 1 L of sample to fix and store. If the sample is stored for a long time Value, need to add 1 ml of formalin and 2 ml of glycerol for sample storage. The storage temperature does not exceed the sample during transportation The temperature at the time of oversampling, if necessary, use refrigerated equipment, and the samples should be carefully stored to ensure that the samples are not damaged or contaminated. Analysis method 5.6 5.6.1 Algae density analysis method a) Microscope counting method (microscopic examination method) The following operating steps and methods can be used to carry out routine monitoring. After the relevant environmental monitoring and analysis method standards are released, press Implementation of relevant standards. The method mainly includes the following steps. Sample concentration. Take a quantitative 1000 ml water sample and let it settle for 24 hours, then carefully remove the supernatant with a siphon, leaving 20 ml~ Transfer 25 ml of the precipitate to a 100 ml quantitative flask, and then use the supernatant to rinse and dilute to the desired concentration. Wakasui The density of algae in the sample is relatively high, and the original water sample can be directly determined by microscope according to the actual situation. Instrument calibration. put the eyepiece micrometer (eyepiece) into the 10x eyepiece, and the scale should be clearly imaged (generally on the scale surface). Should face down), use the stage micrometer (stage ruler) as a microscope slide specimen, observe with a 20x objective lens, and make the scale of the stage ruler clear Clear imaging. The scale of the table ruler represents the actual length on the specimen, generally 0.01 mm per cell. Turn the eyepiece and move the stage, Make the mesh ruler parallel to the table ruler, and the edge scale of the mesh ruler coincides with the 0-point scale of the table ruler, and then count the 10 grids corresponding to the mesh ruler Multiply the number of grids by 0.01 mm, and the product indicates that 10 grids represent the length of the specimen. Make a note Record, that is, a microscope with a 20x objective lens and a 10x eyepiece, and the 10 grids of the eye scale represent the length of the specimen. Use a ruler to measure the field of view Calculate the field of view area according to πr2.The same should be done for every combination of other lenses used for measurement and counting Calibration and recording. Counting of algae. Before counting, the sample should be shaken well, and 0.1 ml of the sample should be sucked into 0.1 ml of the sample with the quantitative sample pipe. frame. Before moving in, place the cover glass obliquely on the counting frame, inject the sample on one side, and vent the air on the other side to avoid air bubbles. After filling Move the cover glass to the right. After the counting film is made, wait a few minutes, and wait for the algae to sink to the bottom of the frame. Count 100 fields under a magnification microscope. Take the average of the two counts above. If the count results of the two pieces differ by more than 15%, Then count the third slice, and take the average of two slices with similar numbers. Counting can also adopt the long-strip counting method, select two adjacent scales to count from the left side of the counting box to the right side of the counting box. As a long strip. Individuals that cross the lower scale should be counted, and those that cross the upper scale should not be counted. For individuals that intersect with the upper and lower scales, the center position of the organism is used as the criterion for judging. You can also press The above principles are counted separately, and finally added to the total. Generally count three, namely the second, fifth and eighth. If the number of algae is too small, It should be counted in full. b) Rapid determination method. portable instrument method Equipment. Algae density monitor. Instrument calibration. The calibration method uses two-point calibration, calibrating with distilled water and calibration solution. The calibration solution is known Phytoplankton suspension with algae density content. Before calibration, clean the inside of the calibration cup carefully. Replace with a new calibration every time Solution, first wash the calibration cup and all sensors with clean water, and then rinse the calibration cup and all sensors with a small amount of calibration solution to be used. Pour it out after the sensor, and then add the calibration solution for calibration. After each measurement, clean the calibration with clean water Cup and all sensor surfaces. After cleaning, add a small amount of clean water (tap water is sufficient, 1 cm height) into the calibration cup, Tighten it to the host and place it upright for next use. Instrument parameters. The resolution is 0.01 relative fluorescence intensity. 5.6.2 Analysis method of algae community composition The operation method of algae analysis and identification is the same as the microscope counting method of 5.6.1 algae density analysis method. Algae community composition analysis methods have identified species in principle (genus can be identified if the species is difficult to distinguish), and calculated The proportion of algae species (Pi) to determine the dominant species.

6 Evaluation of the degree of blooming

6.3.1 Water bloom degree classification standard based on algae density evaluation The degree of water bloom is evaluated according to the density of algae. See Table 1 for its classification standards and corresponding characteristics. The dominant species of bloom should be indicated. 6.3.3 Comprehensive evaluation of water bloom degree When the water bloom degree evaluation results based on the algae density and the water bloom area ratio exist at the same time, the comparison method is used for the water bloom process Comprehensive evaluation of the degree of water bloom, with the heavier one as the final evaluation result of the degree of water bloom, and indicate the dominant species of water bloom. Bloom See Table 1 and Table 2 for the description of the overall characteristics. The comprehensive evaluation of the degree of water bloom is applicable to the evaluation of the degree of water bloom in all water areas of the monitoring water body. 6.4.1 Quantitative comparison of different time periods The quantitative comparison of different time periods is to compare the water bloom conditions of the same monitoring point or monitoring water area in a certain period with the previous period and the previous year. Quantitative comparison and change analysis of water bloom conditions during the same period or other periods. The content of comparison includes algae density, bloom area, water bloom The degree of blooming, the frequency ratio (percentage) of different levels of blooming, etc. 6.4.2 Evaluation of changes in the degree of water bloom Based on the same monitoring point or monitoring water area, evaluate the extent and direction of changes in the degree of water bloom in different periods. Change the degree of blooming The magnitude and direction of the transformation are divided into three categories, namely no obvious change, some change (increased or reduced), and obvious change (increased or reduced). Lighten). The specific evaluation methods are as follows. a) Evaluation according to the level of water bloom. 1) When the level of water bloom is unchanged, it is evaluated as no significant change; 2) When the level of water bloom level changes by one level, it is evaluated as a change (increased or reduced); 3) When the level of water bloom level changes more than 2 levels (including 2 levels), it is evaluated as a significant change (increased or reduced).

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