Journal of Ecological Engineering Journal of Ecological Engineering 2021, 22(3), 169–178 Received: 2020.12.16 https://doi.org/10.12911/22998993/132546 Accepted: 2021.01.14 ISSN 2299–8993, License CC-BY 4.0 Published: 2021.02.01

A Study of the Processes of Desertification at the Modern Delta of the River with the Application of Remote Sensing Data

Shakhislam Uzakbaevich Laiskhanov1*, Maksat Nurbaiuly Poshanov2, Zhassulan Maratuly Smanov2, Nursipa Nursanovna Karmenova3, Kenzhekey Akhmetvalievna Tleubergenova3, Tazhihan Ashimovish Ashimov3

1 Abai Kazakh National Pedagogical University, 050010 , 2 U.U. Uspanov Kazakh Research Institute of Soil Science and Agrochemistry, 050060 Almaty, Kazakhstan 3 Kazakh National Women’s Teacher Training University, 050000 Almaty, Kazakhstan * Corresponding author’s e-mail: [email protected]

ABSTRACT The water regime is the main factor contributing to the formation of landscapes in the river deltas of arid zones, any fluctuations in which lead to a change in the integral hydromorphic landscape. After the construction of the Kapshagai reservoir, the anthropogenic load on the ecosystem of the Ili River delta increased, as a result of which degradation processes, such as drying out and salinization, intensified. In the short term, this phenomenon may lead to the desertification of about 1 million ha of land in the modern river delta. In this regard, the main goal of this study is to look at the processes of desertification in the modern delta of the Ili River, using remote sensing data, which allows for quick identification of the long-term dynamics of degradation processes. For this, the authors used satellite data from Landsat 1–5 MSSS and Landsat 8OLI satellites for 1979 and 2019 and soil analysis data obtained through the ground (field) surveys. Using regression analysis of space and soil data, predictors for inter- preting space images were identified and maps of landscape drying and soil salinization were compiled, reflecting the changes that have occurred over the past 40 years. As a result, it was found that in 2019, compared to 1979, the area of landscapes covered with vegetation had decreased by 12% and there was a transformation of hydromorphic landscapes into salt marshes and solonetzes. Over the past 40 years, the volume of non-saline soils has decreased by 41.3% and the volume of saline soils has increased to varying degrees. That is, at present, on the territory of the modern delta, a difficult land improvement situation has developed associated with the cessation of spring and summer floods due to the intensive water use at the Chinese and Kazakh sides.

Keywords: water supply, satellite imagery data, soil salinity, vegetation indices

INTRODUCTION observed on an ever-larger scale. About 25% of arable land surface worldwide is considered de- Land desertification has long acquired a glob- graded; annually, about 12 million ha are added to al dimension and is one of the largest challenges the total area of degraded land [UNCSD, 2012]. for the sustainable development of humanity, In Central Asia, including Kazakhstan, the causing serious problems of both ecological and risk of desertification is one of the main envi- socio-economic nature. According to the UN, a ronmental and socio-economic problems. In the third of the Earth’s surface is subject to degrada- arid landscapes of Kazakhstan, where it is impos- tion. This is especially true of agricultural lands, sible to imagine the development of agriculture where the processes of erosional degradation, de- without irrigation of lands, the lands are very humidification, depletion of fertility, salinization, vulnerable to impacts, especially in modern con- waterlogging, acidification, over-consolidation of ditions of climate change, reduction of water re- soils, and an increase in the area of such lands are sources, and active anthropogenic development

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[Yessenamanova, et al., 2020]. According to the to the , the largest lake in Central latest data, approximately 76.1% of Kazakhstan’s Asia after the drying up of the Aral Sea. The main lands are considered areas sensitive to desertifica- channel of the Ili River is divided into a fan of tion with medium and high sensitivity [Yunfeng, deltaic channels diverging to the west and north- Yueqi, & Yunzhi, 2020]. Therefore, it is very im- west about 105–130 km from the Lake Balkhash. portant to quickly determine the location of lands In the north-east, it borders on the ancient delta of prone to desertification and understand the main the Ili River, in the south Moiynkum and in the causes of desertification to take measures to stop north and north-west on the on the water area of degradation processes in arid zones [Liangliang, the Lake Balkhash (Fig. 1). et al., 2019]. The implementation of measures The formation of the soil and vegetation to combat desertification is based on land moni- cover of the ancient delta is closely related to the toring. Since the advent of aerial and especially history of the formation of the river delta. Some satellite imagery, the dynamics of changes in researchers [Dzhurkashev, 1972; Shtegman, ecosystems have been intensively studied. At the 1946] believe that initially, the entire Balkhash same time, much attention is paid to the develop- depression looked like a sandy desert which the ment of methods for remote monitoring of lands Ili River later invaded and, as a result of increased [Fathizad, et al., 2018; Munkhnasan, et al., 2016; moisture in the depression, wetland and meadow Pankova, & Rukhovich, 1999]. landscapes were formed. The combination of the We gained positive experience in using satel- desert regime and increased moisture has created lite data as a result of the implementation of sci- an exceptional contrast and diversity of the soil entific projects to develop methods for satellite and vegetation cover of the lower reaches. mapping of soil salinity using the example of the The location of the region in question in the and Shaulder irrigated areas (2012–2015). depths of the Eurasian continent and a significant This experience of many years served as the basis distance from the seas and oceans determine the for our research in the Ili River delta [Duisekov et pronounced continentality of the climate with al., 2015; Otarov, et al., 2016]. characteristic amplitudes of the temperature re- gime in a seasonal aspect. The hottest month is July, with an average monthly air temperature of Study object +25.40С, and the coldest month is January, with an average monthly temperature of -13.20С. The The object of our study is the delta of the Ili average annual precipitation does not exceed River, which occupies the southwestern part of 130–150 mm. The amount of precipitation in a the internal-drainage Balkhash depression. The long-term cycle is much less than air humidity. Ili River is a trans-border river between China A sharp increase in moisture deficit is noted in and Kazakhstan and the main supplier of water early spring. It decreases in autumn, which causes

Fig. 1. Map of the location of the object of our study

170 Journal of Ecological Engineering 2021, 22(3), 169–178 intense evaporation of moisture from the soil sur- purpose, we used topographic maps and satellite face and desiccation of the upper part of the pro- images from open sources. The currently avail- file to an air-dry state. This creates pronounced able topographic maps have not been updated for features of haloxeromorphism in the natural veg- a long time; therefore, in most cases, the situation etation cover and is reflected in the evolution and on the ground is outdated, especially the numer- transformation of delta soils [Borovskii, 1982; ous delta lakes and channels of the Ili River in Karazhanov, 1970; Kornienko, Voinova, & Ma- the conditions of the modern delta. Therefore, mutov, 1977]. to clarify the situation on the ground, we also The main and permanent sources of ground- downloaded from open sources and used (digi- water supply are seepage waters of the Ili River tized) high-resolution satellite images. In most and the Tasmurun and Akdala irrigation arrays cases, we used images from the Landsat satellite, and an underground inflow from the Tasmurun which has a fairly large archive of free images mountains and the sands of the Sary-Ishik-Otrau. and fairly correctly reflects the current situation The general outflow goes to the north-northwest. [Earth Resources Observation and Science Cen- The features of the location of the hydrographic ter (EROS), 2020]. network, its hydrological and hydrochemical re- Thus, using cartographic and remote sens- gimes are important factors affecting the halo- ing methods, we created thematic layers, such as chemical feature of the landscapes of the lower lakes, rivers, channels, irrigated lands, roads, and reaches. The main source of water in the region settlements, that are an integral part of any infor- is the Ili River with the main tributaries Kurty, mation system. Moreover, each layer has the cor- Kaskelen, , Chilik, , etc. It is formed responding attribute information, which is in the from the confluence of the Kunges and Tekes riv- database of the information system. ers, which originate in the Tien Shan mountains In the second stage, we performed a tradition- in China. Currently, the flow of the Ili River is al ground survey. These works were necessary regulated by the Kapchagai reservoir [Starodubt- to reveal the dependence of the brightness of the sev, & Truskavetskiy, 2011]. pixels of satellite images on the salinity of soils (the main salt-forming ions) of the sub-satellite area. In Figure 2, as an example, we provide a MATERIALS AND METHODS diagram of the location of the subsatellite terri- tory and the location of wells drilling (red circles) At the first stage of the study, we developed for sampling soil at this stage of work. its structure and created a geoinformation system The survey was carried out using the tradi- of the object of study with an appropriate spa- tional ground-based method with laying of sec- tially coordinated database using geographical tions, drilling wells, and taking soil samples from information system (GIS) technologies. For this three calculated 0–20, 20–50, and 50–100 cm

Fig. 2. Sub-satellite sites for the land survey of soils

171 Journal of Ecological Engineering 2021, 22(3), 169–178 depths. Fieldwork was carried out using the lat- (traditional water extract) and space survey data est equipment for studying soil salinity and global [Otarov, et al., 2016]. Regression analysis was positioning systems. To refine the soil contours performed in the STATISTICA 7.0 software en- according to satellite images, we used the Gar- vironment. Three groups of predictors were used min 18 global positioning system (GPS) together as independent variables, namely the spectral with an ASUS netbook and to determine the co- channels of the Landsat satellite image, vegeta- ordinates of the points of sections, we used the tion indices describing the state of vegetation, and Garmin 62s GPS. Ground surveys were carried the ratio of spectral channels. Regression analysis out following the All-Union Instruction [USSR was carried out separately for each studied soil Ministry of Agriculture, 1973] and the Guidelines layer (0–20 cm, 20–50 cm, 50–100 cm). These for Conducting a large-scale soil survey [USSR data were used as a basis for identifying deserti- Ministry of Agriculture, 1979]. When using space fication processes using the ILWIS v.3.3 applica- methods, we used the methodology of Pankova tion package based on previously specially devel- and Mazikov [1985] as a basis, supplemented by oped algorithms. the works of Pankova’s students, D. Rukhovich [2009] and M. Konyushkova [2010]. To analyze the material composition of soils, we used analyt- RESULTS AND DISCUSSION ical methods, which are detailed in the guidelines for general soil analysis [Arinushkina, 1977]. The processes of desertification of hydro- As a result of the carried-out salt survey of the morphic landscapes in the Ili River delta, which territory of 7 sites with a total area of more than began after the construction of the Kapchagai res- 21 thousand ha, a total of 566 sections were laid ervoir in 1970 and the development of irrigation and wells were drilled and 966 soil samples were in its basin, have continued for 50 years, weaken- taken. After the chemical analysis of the selected ing only during flood years. The degree of land soil samples, the obtained analytical data were degradation is differentiated in space depending entered into the project database. on changes in the water regimes of delta land- The third stage consisted of laboratory re- scapes under the influence of anthropogenic pres- search, namely the analysis and interpretation of sure. Previous studies showed that in the modern space images. A large archive of satellite informa- delta of the Ili River, two types of desertifica- tion is needed to monitor soil drying and salin- tion dominate: drying and salinization of soils ity. We downloaded and applied Landsat images [Starodubtsev, & Truskavetskiy, 2011]. It was es- [Earth Resources Observation and Science Cen- tablished that these processes are closely related ter (EROS), 2020]. to each other and negatively affect not only the As shown in Table 1, to interpret the process bio productivity of landscapes [Starodubtsev, & of drying and salinization of soils, we selected Truskavetskiy, 2011; Yunfeng, Yueqi, & Yunzhi, satellite images taken with atmospheric cloudi- 2020] but also their microbiological activity ness of less than 1%. This is explained by the fact [Laiskhanov, et al., 2018]. that cloudiness is the main factor preventing the deciphering of the study object and the processes The dynamics of drying of the territory occurring in it [Konyushkova, 2010]. of the modern delta of the Ili River We deciphered satellite images to compile a drying map using the “maximum similar- To determine the impact of the intensive use ity” method, and for the soil salinity map of the of water in agriculture and the regulation of the study object, we used the “maximum similarity” flow of the Ili River as a result of the construction method and regression analysis of the relation- of the Kapchagai hydroelectric power station on ship between the ion-salt composition of soils the drying up of the delta and to identify the most susceptible to desertification areas of the delta, work was carried out to create thematic layers of Table 1. Satellite images used the water surface, such as lake systems and river No. Satellite images Shooting time Cloudiness network, surface covered with vegetation and Landsat 1–5 1 13.08.1979 0% open surface (without vegetation), i.e. sands, salt MSS marshes, takyrs, and other objects at the modern 2 Landsat 8OLI 05.08.2019 0% delta of the Ili River.

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For decryption, we applied an approach based Drying and desertification of the territory of on automatic image classification with training the modern Ili River delta are also confirmed by by the “best likelihood” method. The image clas- digital data of long-term dynamics of areas, i.e. sification was carried out in the GIS ILWIS 3.3 open and vegetated surfaces of the delta. Dur- software. For this purpose, during the fieldwork, ing the studied period of river flow, the open reference areas were selected for each class ac- surface area (without vegetation, such as sands, cording to the values of brightness and location. salt marshes, takyrs, etc.) had increased by For this purpose, we used images of 1979 and 82.8 thousand ha. The areas of water and vege- 2019 from the generated satellite data archive, tated surfaces had decreased, respectively, by 3.3 obtained in early August, when the vegetation and 79.5 thousand ha. cover of the delta is still in an active phase of It should be noted that the drying process of growth and development, i.e. at this moment, the hydromorphic landscapes throughout the delta is open surface uncovered by vegetation is quite ac- uneven. It is highly developed on the territory of curately deciphered. Using the selected Landsat the left wing of the Topar system, the Topar-Ili interfluve, and along the main channel of the Ili satellite images in the ILWIS 3.3 software envi- River and especially in its entry part. Besides, ronment, maps of the main natural objects (sur- the right bank of the canal is quite suscep- faces) of the Ili River were built (Fig. 3). tible to drying (desertification) [Starodubtsev, & A visual analysis of the cartographic material Truskavetskiy, 2011]. shows that over 40 years after the regulation of the river flow, the area of the open (without veg- etation) surface has increased quite noticeably (in Analysis of satellite imagery data and the figure, they are marked with red circles), i.e. mapping of soil salinity after the regulation of the river flow, the processes The data on the coordinates of the pits laying of drying and desertification of the territory have site, the depth of soil sampling, the content of the begun to prevail in the modern delta. Since re- main salt-forming ions in the water extract from cent years, water use has increased rapidly. The the soil, the calculated amounts of the sum of total water consumption in the Ili River basin salts, the “total effect” (TE) of toxic ions, and oth- in 2000 was 14.3 km3/year, in 2005, it equaled er indicators of soil salinity were introduced into 17.2 km3/year, and in 2014, it amounted to the database. This information was reflected in an 15 km3/year. In 2000, China and Kazakhstan con- article previously published by us [Duisekov, et. sumed 38% and 62% of water, respectively. By al., 2015]. During the study, these data were used 2014, the relative share of water consumption in to develop an algorithm for decoding soil salinity China had increased to 43% [Thevs, et al., 2017]. from satellite images.

Fig. 3. Dynamics of the area of natural objects (surfaces) of the Ili River delta (1979 – left, 2019 – right)

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To compile algorithms for the dependence of SQRT= J(Band5/Band4); TND VII= the spectral characteristics of the images on the =J ((Band 5-Band4)/(Band5 + Band 4))+0,5; ion-salt composition of soils (regression mod- GNDVI=(Band5-Band3)/(Band5+Band3); els) and maps of soil salinity, we used Landsat 8 NDGR=(Band3-Band4)/(Band3+Band4); OLI multispectral images downloaded from open IPVI=Band5/(Band5-Band4); sources with a spatial resolution of 30 m. RVI=(Band5-Band4); The following approach was used to compile NDSI=(Band6-Band5)/(Band6+Band5). soil salinity maps. For points with data from field 3. Ratio of channels not related to vegetation studies of soil salinity in the GIS, the values of indices: pixel brightness were extracted for all spectral B/G=Band2/Band3; R/G=Band4/Band3; channels of Landsat 8 OLI satellite images, and B/IR=Band2/Band5; B/SWIR2=Band2/Band6; the values of the pixel brightness ratios in differ- IR/B=Band5/Band2; SWIR2/G=Band6/Band3; ent channels and vegetation indices were calcu- SWIR/SWIR3=Band9/Band7. lated. The vegetation index is an indicator calcu- lated as a result of operations with different spec- To establish the relationship between soil sa- tral ranges (channels) of the image and related to linity and satellite imagery data, we performed the parameters of vegetation in a given pixel of regression analysis in the STATISTICA 10.0 soft- the image [Cherepanov, 2011]. The effectiveness ware environment separately for each soil layer of these indices is determined by the features of under study (0–20 cm, 20–50 cm, 50–100 cm). the reflection; they are derived mainly empirical- As a result of the performed regression analy- ly. As a result, the following potential predictors sis, we constructed significant regression models of soil salinity were obtained: for all layers with the coefficients of determina- The predictors used for the regression analy- tion (R2) from 0.3 to 0.6. Here, the vegetation in- sis can be divided into three groups: dex IPVI for the top layer of the canopy turned 1. Spectral channels Band 1, Band 2, Band 3, out to be the best predictors (Table 2). Band 4, Band 5, Band 6, Band 7, Band 8, Band For the two lower layers 20–50 cm and 9, Band 10, Band 11. 50–100 cm the B/IR2 predictors were used. In 2. Vegetation indices describing the state of Figure 4, as an example, we provide a map of the vegetation: degree of salinity of the upper 0–20 cm soil layer. NDVI=NDVI=(Band5-Band4)/(Band5+Band4); The convergence of soil contours, compiled using IR_R=Band5/Band4; VEGI=Band4-Band3; the regression equation and based on the results

Table 2. Results of regression analysis of the relationship between the chemical composition of the soil (0–20 cm layer) and spectral properties of Landsat 8OLI images

Soil chemistry (dependent variables) Predictors (independent Connection The total Total TE of toxic 4 variables) amount of alkalinity in Cl SO Ca Mg Na K ions, milligram- salts НСО3 equivalent C Band1 absent ------Band2 absent ------Band3 present + - + - + + + + + Band4 absent ------Band5 absent ------Other channels absent ------(Bands) B/IR absent ------B/IR2 absent ------IR2/B absent ------NDSI present + + + + + - + - + NDVI absent ------IPVI present + - + + + + + - + Other absent ------

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Fig. 4. Map of soil salinity in the modern delta of the Ili River, 2019 of the ground survey, was also satisfactory at the In support of this, for comparison with the border and amounted to 67.3%. 2019 map, below, we present a map of soil sa- The main reason for such a distribution of salts linity in the delta, compiled from 1979 images over the delta is the practical absence of spring (Fig. 5). To map soil salinity in 1979, the same and summer river floods and the subordination of approach and predictors were used as were used the intra-annual distribution of river flow to the to map the situation in 2019. From the soil salin- regime of water release from the reservoir. This ity map of the delta, it can be seen that by 1979, is primarily due to the construction and commis- the contours of highly and moderately saline soils sioning of the Kapchagai reservoir on the Ili river. had already appeared on the head of the delta due As a result of regulation, the flow of the Ili River to the cessation of spring floods, which occurred decreased by 25%, which led to a sharp deteriora- due to jamming phenomena in the channels. tion in the water supply of the entire delta area of As we have already noted, the process of dry- the river. Previously, the central part of the delta ing and salinization of soils is most pronounced was flooded mainly during the period of power- in the Topar and Dzhidelinskaya systems of ca- ful summer floods, while the head part was well nals and on the head of the delta. Hydromorphic watered by early spring floods as a result of mash- landscapes with non-saline soils are concentrated and-jam phenomena in the channels. The regime along the Zhideli, Kugaly, Ir, and Arystanda ca- of releases from the Kapchagai reservoir does not nals. A similar distribution of desertified territo- provide for large water discharges in the spring- ries in the delta for 37 years after the regulation summer period. Therefore, the head and central of the river flow was obtained in [Starodubtsev, parts of the delta were the first to dry out. In the & Truskavetskiy, 2011] through space monitoring Dzhidelinsky system of canals, the reduction in using NASA/MODIS/Terra space images. lakes went in two directions. On the one hand, the Comparison of areas with different degrees flowing lakes, intensively silting up, turned into of soil salinity showed that catastrophic changes swamps and most of them dried up. On the other have taken place in the delta over the past 40 years. hand, as a result of the development of the main The areas of non-saline soils during this time de- channels, smaller lateral canals that fed the lakes creased by 386.2 thousand ha, or 41.3% (Fig. 6). of the marginal parts of the system were cut off During the same period, the areas of slightly and and dried up [Otarov, 2014; Thevs, et al., 2017]. moderately saline soils increased by 2.4% and

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Fig. 5. Maps of soil salinity of the modern delta of the Ili River, 1979

15.7%, respectively. The areas of highly saline at present, on the territory of the modern delta, a soils increased by 21.4%, or 199.9 thousand ha. difficult reclamation situation has developed, as- Thus, the analysis of the long-term dynamics sociated with the cessation of spring and summer of soil salinization in the delta and the causes of floods. Besides, in the last decade, the ecological salinization showed that the main reason for the situation in the modern delta has become notice- change in water supply conditions leading to the ably more complicated due to the expansion of drying and desertification of the modern delta and irrigated areas in the Ili River basin from both the soil salinization is the regulation of the Ili River Kazakhstan and China sides [Thevs, et al., 2017]. runoff. The areas of saline soils increased quite It should also be noted that the water resources sharply, which in turn led to a reduction in hydro- for the delta are exactly the nodal link of problem morphic landscapes with non-saline soils. That is, situations, the management of which will allow

Fig. 6. Long-term dynamics of soil salinity in the modern delta of the Ili River

176 Journal of Ecological Engineering 2021, 22(3), 169–178 purposefully changing the degree of soil salinity Under these conditions, to maintain and pre- and the overall ecological situation of the delta. serve the delta, it is necessary to periodically ar- range artificial floods in the delta to flush the soil from salts and replenish the soil moisture. CONCLUSIONS

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