CC BY
32EARTH SCIENCES
APPLICATION OF REMOTE SENSING METHODS TO DETERMINE THE EUTROPHICATION OF
SMALL LAKES IN NORTHERN KAZAKHSTAN
Akiyanova F.,
International Science Complex Astana, Nur-Sultan, Kazakhstan Chief Researcher, Doctor of Geographical Sciences
Mussagaliyeva Zh.,
International Science Complex Astana, Nur-Sultan, Kazakhstan
Research fellow Nazhbiyev A.,
International Science Complex Astana, Nur-Sultan, Kazakhstan
Research fellow
Zinabdin N.,
International Science Complex Astana, Nur-Sultan, Kazakhstan
Research fellow Zhamangara A.
Eurasian National University, Nur-Sultan, Kazakhstan
Associate Professor
Abstract
In Kazakhstan, in the last 50 years, small lakes have not been given due attention, inventory as well as monitoring of these resources and their water quality have not been carried out. Although it is the small lakes that provide the rural population with water, they are used for fisheries purposes, waterfowl breeding and public recreation. At the same time, small lakes and their catchments are exposed to active economic activity. Such activities include the plowing of catchments, the formation of numerous small reservoirs on the rivers which feed the lakes, the construction of roads and dams without adequate culverts. In many respects, these actions led to the loss of part of the runoff from the catchment areas, and as a result - to siltation, eutrophication, waterlogging or disappearance of many small lakes. The reduction in the number of small lakes is confirmed by Landsat satellite image interpretation data for 2021 for the Yesil river Basin. The results of the comparative analysis showed that the number of small lakes has decreased by 2.5 times over the past 48 years. The question arises - what is the current state of the remaining small lakes, what are the trends of their further development, especially if we take into account that the anthropogenic impact is increasing against the background of climate change. In accordance with the above, the purpose of the research was to test the capabilities of modern remote sensing methods for rapid assessment of the state of small lakes in Northern Kazakhstan, to determine the degree of their eutrophication. The research was carried out on the example of two groups of lakes in Northern Kazakhstan: the lakes of the Shchuchinsk-Borovskaya system and the lakes between the rivers Yesil and Nura. To validate the data obtained on the basis of remote sensing, sampling for phytoplankton was carried out on the lakes on the same dates. The Landsat and PlanetScope satellite images were processed using the Normalized Difference Chlorophyll Index (NDCl). A comparison of the results of the NDCI remote data processing showed that they generally correlate with the results of the phytoplankton samples. Thus, it is concluded that this method can be used to promptly update data on small lakes that have water, biological and recreational resources necessary for the social well-being of the local population. The applied remote sensing methods will allow us to see negative trends in advance and apply measures for the conservation and sustainable use of lakes. At the same time, it should be noted that selective validation of the results of remote sensing processing by field and laboratory studies is necessary.
Keywords: small lakes, eutrophication, phytoplankton, remote sensing, NDCI, BRG, BBGR indices.
Introduction. The results of remote sensing data processing on the territory of Kazakhstan in recent years show a significant reduction in the number and areas of small lakes [20]. For example, in 1973 the number of small lakes was 48262, of which 90% were lakes with an area of up to 1 km2 [22]. 3688 lakes from the total had an area of 1-5 km2, whereas 770 lakes had an area of 5-10 km2 [29]. The analysis of Landsat-8 images for 2021 showed that the number of lakes with an area of 1-5 km2 decreased to 1492, whereas the lakes with an area of 5-10 km2 decreased to 302. So, over the past 48 years, there has been a reduction in the number of lakes by 2.5 times. The reasons for the reduction of small lakes are associated with both climate change and
anthropogenic impact. Economic activities in the form of reservoir construction on rivers flowing into lakes, plowing of lake catchments and construction of roads have led to a reduction in runoff, decrease in water content, loss of biological diversity and eutrophication of lakes.
Field and laboratory studies have proved that information on the concentration of photosynthetically active phytoplankton pigment "Chl a" (hereinafter" Chl a"), which is a generally accepted indicator of phyto-plankton biomass in water bodies, serves as the main indicator of water bodies' eutrophication and water quality [29,1,11,31]. In recent years, specialized methods of satellite image processing have been used to
quantify "Chl a", which can quickly determine and monitor the state of water bodies [33].
In accordance with the above, the purpose of this research was to test the capabilities of modern remote sensing methods for rapid assessment of the state of small lakes in Kazakhstan, for the determination of their eutrophication degree. The research was carried out at two groups of lakes in Northern Kazakhstan: lakes of the Shchuchinsk-Borovskaya system located at latitude 53° 01.242' and the lakes between the Yesil and Nura rivers located at latitude 50° 59.434'N. In order to
confirm and correct the data obtained from remote sensing, samples for phytoplankton were taken during fieldworks, in addition, data from bathymetric surveys of lakes were used.
Materials and methods. The fresh lakes of the Shchuchinsk-Borovskaya system (Burabay, Katarkol), which are located in the national natural park "Bura-bay" within the island low-mountain massif, were studied. Lakes Maybalyk and Taldykol are located in the flat part of the interfluve of the Yesil-Nura rivers near the city of Nur-Sultan (Fig. 1).
Figure 1. The location of the studied lake groups: 1 - Shchuchinsk-Borovskaya lake system (a - Lake Burabay, b - Lake Katarkol); 2 - Lake Maybalyk (c) and Lake Taldykol (d). Source: adapted by the author based on [6]
The climate of the study area is continental, with hot summers and severe winters with little snow, which is softened within low mountain ranges with island forests. The soil-vegetation layer obeys latitudinal zonal-ity (steppe and dry steppe zones), which is modified within the low mountain islands. According to the natural zoning, the territory of the national park belongs to
the upland island steppe pine forests. Ordinary chernozems of low mountain massifs are replaced to the south on the plains by chestnut calcareous soils. The lakes are fresh and brackish. The area characteristics of the lakes were studied on the basis of field studies and remote sensing data (Table 1).
Table 1
Areal characteristics of lakes (2020)
Lakes Burabay Katarkol Maybalyk Taldykol
Area, thousand sq. m 9,9 4,3 25,94 11,51
Source: adapted by the author based on [3]
The river network in the northern part of the studied area is represented by small rivers and streams flowing into lakes. In the south - a section of the interfluve of the Yesil and Nura rivers the recharge of lakes and rivers is approximately similar, with a predominance (up to 80%) of snow.
To analyze the concentration of chlorophyll "a" and assess the turbidity of lakes, satellite images from Landsat-8 for 14.07.2019 and PlanetScope for
02.08.2019 were used [6, 26]. The images of both satellites are uploaded to the UTM projection with the WGS 84 coordinate system, cloud cover is up to 10%. In order to study the concentration of "Chl a", spectral channels of the visible, near-infrared and short-wave infrared bands were used (Table 2). The remote sensing image date was selected as close as possible to the date of lake field surveys with phytoplankton sampling.
Table 2
Characteristics of spectral bands
Satellite name Spectral bands, nm Resolution, meters
Blue Green Red NIR
Landsat-8 Band 2 - 0.4520.512 Band 3 - 0.5330.590 Band 4 - 0.6360.673 Band 5 - 0.8510.879 30 (Bands 1-10)
PlanetScope Band 1 - 0.4640.517 Band 2 - 0.5470.585 Band 3 - 0. 650 -0.682 Band 4 - 0.8460.888 3,7 (Bands 1-4)
Source: adapted by the author based on [6, 26]
Hydrobiological survey with sampling for phyto-plankton and water quality was carried out on lakes Bu-rabay and Katarkol from 29.07 till 2.08.2019. In total, 5-12 samples were taken from each of the lakes from the surface layers, which were fixed with a 40% formalin solution. For the processing of phytoplankton samples, a sedimentary method with a final volume of a concentrated sample of 5-10 ml was used. The number of plant cells was counted in the Goryaev chamber with subsequent recalculation per 1 m3, keys for the corresponding departments were used for species identification [4,7-10,13-15,18,19,23,27,35]. The biomass of phytoplankton was determined by summing up the biomasses of individual species, for which average values of the cell mass were preliminarily established. For the group of steppe plain lakes (Maybalyk and Taldykol), water samples were taken by the Apstein plankton net in the field period of 2010. To assess the saprobity of water, the method of indicator organisms was used, which was developed by R. Pantle and G. Bukka and modified by V. Sladechek [2,32]. To assess the water quality of the lakes, quarterly long-term data from the bulletins of the Republican State Enterprise "Kazhy-dromet" [12] and monitoring data (temperature, salinity, salinity, pH) from the State National Nature Park "Burabay" for 2019-2020 [26] were used. The morpho-metric data of the lakes have been updated based on hy-drological field observation methods and geoinfor-mation methods for processing PlanetScope satellite images and aerial photographs from a DJI Phantom 4 quadcopter. The bathymetry of the lakes was studied in the summer and autumn of 2019 using the Lowrance Elite 9 TI echo sounder and the compilation of bathy-metric maps.
Methods for processing and analyzing remote sensing data are based on the registration of the brightness of the scattered and reflected radiation from the water surface by satellite radiometers, which is associated with the presence of an optically active component of phytoplankton - "Chl a" in the water [5,30]. All phytoplankton species contain the green pigment "Chl a", which is an important indicator for assessing phyto-plankton biomass and water body productivity. The bio-optical models estimate "Chl a" in three directions: phytoplankton absorption, fluorescence, and backscat-tering [25]. To estimate the concentration of chloro-
phyll "a", the Normalized Difference Chlorophyll Index (NDCl) was applied. Calculated by the formula: (NIR-RED)/(NIR+RED) [17]. According to Ogasha-wara et al. [21] high probability of a strong cyanobac-terial bloom occurs when the index scores exceed a factor of 0.15 and when the "Chl a" concentration exceeds 50 pg/l. Moderate flowering is characterized in the range from - 0.05 to 0.15 and "Chl a" concentration from 5 to 10 ^g/l. In addition, the strong bloom is characterized by a positive slope between the red (665 nm) and NIR bands (865 nm) due to the high absorption of "Chl a" in the red region of the spectrum and the high scattering of algal cells in the NIR region. The equation is almost neutral for moderate flowering conditions due to the average uptake of "Chl a" and average dispersion of algal cells [21].
The turbidity index BBGR (suspension in water) is calculated based on the analysis of remote sensing data using the following equation: BLUE/(BLUE + GREEN + RED). To check the turbidity index values for 26.07-03.08.2019, water samples were taken from the lakes for the presence of suspended solids [16].
The processing of satellite images by indices was carried out in the ENVI program using the Band Math tool. The average index scores were calculated using the Spatial Analyst (zonal statistics) toolkit of ArcGIS 10.6. The Spatial Analyst toolkit was used to obtain the contours.
Results. When processing Landsat-8 and PlanetScope images according to the NDCl index for the lakes of the Shchuchinsk-Borovskaya group with adjacent territories, the concentration of "Chl a" had negative values, the difference in average values did not exceed 0.14 units. According to the NDCI index, Lake Katarkol was characterized by average, and Lake Bura-bay by high values of "Chl a"concentration index.
In addition, the images were processed using the NDCl and BRG indices for the surface area of each lake. Figure 3 shows the processing results for lakes Burabay and Katarkol. Analysis of the maximum values of "Chl a" by the NDCl index from the PlanetScope image shows that a strong bloom of cyanobacteria occurs in some parts of Lake Katarkol (0.656), where the index values exceed 0.15 (Table 2). It should also be noted that the maximum values of the NDCl index from Landsat-8 images are 40-50% lower than the values calculated from the PlanetScope images.
Landsat-8, 07/14/2019
PlanetScope 02/08/2019
PlanetScope 02/08/2019
Lake Katharkol, BRG index Lake Katharkol, NDCI index Lake Katharkol, BBGR index
Figure 3. Concentration of "Chl a" in lakes Burabay and Katarkol according to the NDCI and BRG indices, the
level of turbidity according to the BBGR index
The values of the NDCl index for lakes Burabay (0.04) and Katarkol (-0.041), calculated from the Land-sat-8 image, are closest to the lower limit of the bloom class of temperate cyanobacteria from -0.05 to 0.15
Table 3
"Chl a" concentration values according to NDCl and BRG indices based on Landsat-8 and PlanetScope images.
[21]. Quantitative indicators for Landsat and PlanetScope images for "Chl a" concentration by NDCl and BRG indices are presented in Table 3.
Lakes PlanetScope Landsat
by NDCl index min. avg. max. min. avg. max.
Burabay -0.135 -0.107 -0.047 0.078 -0,039 0.240
Katarkol -0.265 -0.101 0.656 -0.063 -0,041 0.390
by BRG index min. avg. max. min. avg. max.
Burabay -0.031 0.471 0.548 -0.035 0.246 0.277
Katarkol 0.147 0.870 1.033 -1.003 0.241 0.278
Maps of the integral amount of suspended substances not only reveal blooming sites, but can also be used to accurately determine algal biomass. The highest value of the turbidity index (0.478) is typical for Lake Katarkol, which may be caused by the presence of finely dispersed inorganic compounds, organic impurities or living organisms. The water turbidity index increases in the zones of biogenic impact (recreation areas, settlements, livestock watering).
The analysis of PlanetScope images for lowland lakes Maybalyk and Taldykol was carried out with the calculation of the NDCl, BRG and BBGR indices (Fig.
4). The values of the "Chl a" concentration according to the NDCl index for both lakes are practically similar; for Taldykol the values range from -0.364 to a maximum value of 0.373, for Lake Maybalik in the range -0.348-0.297, respectively. According to the BRG index, the values for Lake Taldykol are higher (0-1.532) than values for Lake Maybalyk (0-1.283). According to the BBGR index, practically both lakes have similar values; the spread of the average and maximum values is only 0.098. For Lake Taldykol, turbidity values vary from 0.333 to 0.574, for Lake Maybalyk from 0.303 to 0.542.
Lake Taldykol
Lake Maybalyk
BRG Index NDCI Index BBGR Index BRG Index NDCI Index BBGR Index
Figure 4. Concentration of "Chl a" in Lake Taldykol and Lake Maybalyk according to the NDCI, BRG and
BBGR indices according to the PlanetScope image
The spatial distribution of "Chl a" concentration over Lake Taldykol is associated with the complete embankment and reclamation of its shores. In the case of Lake Maybalyk an increase in the concentration of "Chl a" in the shallow eastern part and the places of confluence of temporary streams is clearly seen.
Phytoplankton of Lake Burabay is characterized by the highest species diversity (73 species), 49 phyto-plankton species were found in Lake Katarkol. Quantitative indicators of phytoplankton communities of lakes differ significantly. The largest number of microalgae
Biomass of phytoplankton communities
was recorded in Lake Burabay (3082.3 mln.kl/m3). At the same time, blue-green algae form the basis of the abundance on lakes Burabay and Katarkol. Phytoplank-ton biomass is at a relatively low level, with maximum values in Lake Burabay. In Lake Burabay, the biomass of diatom algae predominates.
An analysis of the spatial distribution of the biomass of phytoplankton communities and cyanobacteria over lakes, based on the analysis of laboratory data, generally shows their relationship with the anthropogenic development of lakes (Fig. 6).
Cyanobacterial biomass
(a) (b) (a) (b)
Figure 6. Distribution of biomass of communities ofphytoplankton and cyanobacteria in lakes Burabay (a),
Katarkol (b), summer 2019
Source: adapted by the author based on [9]
In Lake Burabay, the maximum biomass accumulation of diatom, myozoa and green algae was recorded in the northwestern part, in the zone of increased recreational load and the influence of the Burabay village. In Lake Katarkol, accumulations of algal biomass are confined to the zone of influence of sanatoriums and the village Katarkol [3].
In the samples from the lakes of the lowland group, green and diatom algae predominate. The greatest species diversity is noted in Lake Maybalyk, where 83 species of algae have been identified, of which 35 are diatoms, 33 are green, 15 are cyanobacteria. The coastal part of the lake is the richest in species. There are fewer species in the central part of the lake, but green algae predominate. In Lake Taldykol, 65 species of algae and cyanobacteria have been identified, including: 17 species of diatoms, 31 species of green, 1 species of chara algae and 16 species of cyanobacteria.
Based on the study of the species composition, quantitative data of algae and cyanobacteria, a saprobi-ological analysis of water bodies was carried out. In Lake Maybalyk, 37 indicator species with saprobity classes from a-mesosaprobic to x-0 saprobic were found. The average value of the saprobity index in Lake Maybalik is 1.97. This means that the water of Lake Maybalyk within the surveyed water area belongs to the P-mesosaprobic zone. Accordingly, the water quality class is III, that is, moderately polluted. There are 31 indicator species of algae in Lake Taldykol, with a wide range of saprobic zones. In Lake Taldykol, species of
the P-mesosaprobic zone prevail. Species of the oli-gosaprobic zone are sporadically represented. The saprobity index in the lake is 1.98, corresponding to the characteristics of moderately polluted water body.
Discussion. The rationale for the use of multispec-tral RED and NIR channels is given in the article by Pirasteh et. al [25], which describes two methods for extracting the "Chl a" index, based on the fluorescence line height (FLH) and the maximum chlorophyll index (MCI), based on the use of Sentinel-3 and Sentinel-2. The "Chl a" content is proportional to the fluorescence emission induced by the sun. Many researchers have begun to explore the possibility of using it to determine the concentration of "Chl a" in coastal waters. In China, to study the level of eutrophication of Lake Donggu, the complex trophic level index (TLI) was used [34]. According to this indicator, the authors assessed the development of lake eutrophication over a long period (1987-2018) and predicted the further trend of this process. The results obtained can form the basis for measures to improve water quality and control the eu-trophication of lakes. The TLI is calculated based on the content of four components that affect water quality: total nitrogen, total phosphorus, water purity and "Chl a" [24].
In our research, we used the "Chl a" index as a basis for determining the level of eutrophication. However, we were not able to assess the long-term dynamics of changes in the "Chl a" values due to the lack of long-term field data.
Development of the coastal zone
Phytoplankton biomass Cyanobacterial biomass
Lake bathymetry
Lake Katarkol
Figure 7. Analysis of the dependence ofphytoplankton development on the natural and anthropogenic conditions
of Burabay and Katarkol lakes Source: adapted by the author based on [3]
The lakes of the Shchuchinsk-Borovskaya group, located within the national park, experience a large residential and recreational load, due to settlements located on the coast, sanatoriums, as well as the year-round operation of a resort center of republican significance.
Lake Taldykol, which until 2018 was a storage lake for the treated wastewater from the city, and Lake Maybalyk, which is a water body for discharge of flood waters during emergency, are both located in the immediate vicinity of the city of Nur-Sultan and they are experiencing a great anthropogenic impact.
In the course of processing Landsat-8 and Plan-etScope images, it became clear that the PlanetScope images (3 m resolution) can be used to calculate indicators both for the lake water area and for the entire image with adjacent territories. The high resolution of PlanetScope images makes it possible to determine in
(a)
more detail the reflective properties of various objects, including the chlorophyll content in the phytoplankton biomass. When processing Landsat images (resolution 30 m), values were obtained that are more similar to the values of field studies, when processing only the water areas of the lakes. This is indicated in the publications of other researchers [16,30].
To confirm the data obtained by remote sensing methods, the results of field and laboratory studies were used and their correlation estimated. The phytoplank-ton biomass values from field data and data from Plan-etScope image processing were the closest (Fig. 8). According to the results of BRG index, and to a lesser extent by the NDCl index, PlanetScope images show similar values of phytoplankton biomass in lakes. Less accurate data were obtained when processing Landsat images, there was a minimal difference between the phytoplankton biomass of different lakes.
(b)
Figure 8. Graphs of the correlation of data on the content of "Chl a" in lakes SHBSL by NDCl (a), BRG (b)
indices and field studies in 2019 Source: adapted by the author based on [3]
According to the results of field studies, the biomass of phytoplankton communities did not exceed 50 ^g/l (50 million cells/m3 = 50 ^g/l). Also, the obtained values of "Chl a" by the NDCl index do not exceed the coefficient 0.15. It follows from this that at the time of the study, moderate flowering was observed on the lakes of Shchuchinsko-Borovskaya lake system. Analysis of the results of satellite images processing with the NDCl and BRG indices showed that the obtained values generally correlate with the results of field studies. According to Figure 8, there is a correlation between field data and remote sensing data in the relative difference in "Chl a" content in the lakes.
Conclusion. Widely available remote sensing data significantly expand the possibilities of their application both for quantitative assessment of morphometric indicators of small lakes, as well as for studying the processes of their eutrophication. Due to the fact that phytoplankton is one of the most sensitive elements that quickly respond to changes in the aquatic environment, including the processes of eutrophication, the study used remote sensing methods to determine the spatial and quantitative parameters of phytoplankton development. In the course of the research, the applicability of the NDCI and BRG indices to determine the "Chl a" concentration for assessing the eutrophication of lakes in Northern Kazakhstan was evaluated.
The processing of PlanetScope satellite images (resolution 3.0 m) showed that high resolution allows more detailed determination of the reflective properties of various objects, including the chlorophyll content in biomass. Processing of Landsat images (resolution 30 m) for the water area of the lakes showed more objective values close to field data, which is confirmed by the data of other researchers [16,30]. Comparison of the Chl a content in lakes by remote sensing methods, field and laboratory studies showed that the phytoplankton biomass values from field data and PlanetScope image processing data are the most correlated.
The results of the study show that satellite images can be used to assess the ecological state of the lakes of Northern Kazakhstan. At the same time, it should be noted that it is desirable to increase the number of field measurements, especially in those water bodies where increased bloom is observed on satellite images. It is also planned to study the possibilities of using radar images to determine the quantitative parameters of the phytoplankton biomass of water bodies. The research results can be used as one of the regional algorithms that can be applied to assess the qualitative state of small lakes in forest-steppe and steppe territories.
Financing. This study was carried out within the framework of the state order of the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan for the project "Assessment of surface water resources and their use at the Nura-Yesil in-terfluve using geoinformation technologies for agricultural territories' sustainable development" (IRN AP08856733) and the program "Complex ecosystem assessment of Shchuchinsk-Borovoye resort area through the environmental pressure evaluation for the purposes of sustainable use of recreational potential" (IRN BR05236529).
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