=Paper=
{{Paper
|id=Vol-2387/20190127
|storemode=property
|title=Spatio-Temporal Representation of the Ecological State of the Surface Waters of the Lower Section of the Dnieper River using GIS Technologies
|pdfUrl=https://ceur-ws.org/Vol-2387/20190127.pdf
|volume=Vol-2387
|authors=Anastasiia Bystriantseva,Iryna Shakhman,Maksym Bystriantsev
|dblpUrl=https://dblp.org/rec/conf/icteri/BystriantsevaSB19
}}
==Spatio-Temporal Representation of the Ecological State of the Surface Waters of the Lower Section of the Dnieper River using GIS Technologies==
https://ceur-ws.org/Vol-2387/20190127.pdf
Spatio-Temporal Representation of the Ecological State
of the Surface Waters of the Lower Section of the
Dnieper River using GIS Technologies
Anastasiia Bystriantseva1[0000-0003-0611-1548], Iryna Shakhman2[0000-0001-6204-4410] and
Maksym Bystriantsev3
1Kherson State University, 27 Universitetska st., Kherson, 73000 Ukraine
abystryantseva@ksu.ks.ua
2Kherson State Agricultural University, 23 Stretenskaya st., Kherson, 73000 Ukraine
shakhman.i.a@gmail.com
3Teaching and Educational Complex “School of Liberal Arts” of Kherson Regional Council,
33 Molodizna st., Kherson, 73000 Ukraine
bismaxmail@gmail.com
Abstract. Research goal of the paper is to study the ecological state of the
surface waters using spatio-temporal representation of water quality using a
geographic information system (GIS), which will provide interdepartmental
information interaction and analytical support for environmental and socio-
economic decision making. Mathematical modeling of the ecological state of
surface waters according to hydrochemical ingredients was carried out in
accordance with the ecological classification. The visual interpretation of
multidimensional data, which was obtained using GIS technologies, makes it
possible to obtain information on the extent and areas of surface waters
pollution and to estimate the level of anthropogenic load on hydroecosystems.
Keywords: GIS technology, modeling process, ecological state, hydrochemical
ingredients
1 Introduction
Recently, human society has become increasingly aware of the need to have clean
rivers, lakes, underground and coastal waters. That is why one of the priorities of the
European Union’s activities is water protection.
European water policy is aimed at achieving good water quality and steady
ecological state of water bodies. In accordance with the Water Framework Directive
2000/60/EC (Directive 2000/60/EC) [1] it is planned to introduce an integrated
approach to the protection of all water bodies – rivers, lakes, coastal water and
groundwater; water resource management by basin principle; strengthening
transnational cooperation of coastal countries (one river basin – one management
plan); the effective use of water resources according to principle – the polluter pays;
large-scale involvement of citizens, interested parties, public organizations;
improvement of legislation.
The use of modern methods of the water objects monitoring contributes to new
opportunities for cooperation in improving the ecological status of hydroecosystems
and visual modeling (graphical representation of the model due to a certain standard
set of elements) using GIS technologies in the framework of the international process
“Environment for Europe”. This is vital for the realization of one of the advantages of
visual modeling – communication [2]. The development of visual interpretation of
multidimensional data and GIS technologies is connected, in particular, with the fact
that it is difficult for a person with his limited three-dimensional spatial imagination,
and in most cases it is impossible, to analyze and give generalized assessments of
multidimensional objects. Under conditions of the influence of economic activities of
enterprises (industrial, agricultural, energy, communal, transport) on aquatic
ecosystems particularly important role of communication between users, analysts,
managers, the public, etc.
Ecological indication of the state of hydroecosystems can provide information
about the extent and nature of water pollution, the distribution of pollution zones in
water bodies, and the possible state of the aquatic ecosystem on a seasonal scale.
When assessing the scale of anthropogenic pressure on hydroecosystems, it is
necessary to identify adverse processes in the aquatic environment, substantiate
chemical criteria for water quality and informative biological criteria, determine
critical levels of multifactor water pollution, and develop environmental-economic
optimization models for local and transboundary pollution of surface waters.
Providing interdepartmental information interaction between stakeholders (water
users, scientists, analysts, ecologists, managers, the public, the media) at a local,
regional, state and international level and analytical decision support based on modern
methods of spatial analysis, modeling the development of emergency situations and
predicting their consequences using GIS tools will allow to calculate and visualize the
results of modeling the spread of pollution zones in the aquatic environment,
contribute to the improvement of environmental health of river basins, improving
water quality, sustainable development in Ukraine on the way to human values in a
common European home.
The purpose of the paper is demonstration of the use of spatial data analysis
technology by means of GIS technologies in ecology in assessing the impact of
human activities on the state of surface waters.
2 Related Works
Sustainable use of water resources entails the combined use of surface water
monitoring and assessment programs with decision making and management tools.
The use of GIS-based interpolation to create a continuous map of the whole area and
spatial analysis of water quality in areas where sampling does not exist is relevant.
Studies were conducted by Aminu M., Matori A.-N., Yusof K.W., Malakahmad A.,
Zainol R.B. [3] in a similar direction. They included an assessment of the water
quality of the Bertam River (Malaysia), which suffered due to the development of
tourism-related activities, and were based on data from seven sampling points. As a
result, a conclusion was made about the quality of the water surface using the
interpolation technique of geographic information system, and its suitability for
recreational activities was also assessed.
An equally important area involving the use of geospatial data is land use. For
example, Guo Y. and Liu Y. [4] outlined the problem of landscape degradation and
habitat fragmentation, which are caused by overuse of resources, including water
resources. ArcGIS overlay and least cost path algorithms were used, taking into
account relevant environmental and socioeconomic data in GIS projects. A regional
ecological network was built, which will serve as the basis for improving the
connectivity of the landscape.
In [5], Kussul N., Shelestov A., Basarab R., Skakun S., Kussul O., Lavreniuk M.
emphasize that geospatial data including satellite imagery play an important role,
since they can provide regular and objective information. The authors use special
techniques associated with the area of geospatial intelligence for the qualitative
assessment of changes occurring in space and time. The main idea of the proposed
geospatial intelligence approach is the use of supervised neural networks in order to
classify multi-temporal optical satellite images with the presence of missing data.
The author of Zhang Y. [6] studied coastline changes in the Modern Yellow River
delta in China based on remote sensing and GIS techniques. The impact assessment
was made using Landstat-5 satellite map images using distance measure tools
developed in ArcGIS. It was concluded that human activities had a strong influence
on the natural evolution of the Modern Yellow River delta coast.
The focus was also on identifying the critical prone areas for soil erosion, using the
Sarada River basin (India) as an example, in the work of scientists Sundra Kumar P.,
Vankata Praveen T., Anjanaya Prasad M., Santha Rao P. [7]. The basin has been
divided into micro basins for effective estimation and also for precise identification of
the areas that are prone to soil erosion. Remote Sensing and Geographic Information
Systems tools were used to generate and spatially organize the data that is required for
soil erosion modeling.
In recent years, the use of remotely sensed data and Geographic Information
System (GIS) applications has been found increasing in a wide range of resources
inventory, mapping, analysis, monitoring and environmental management. The
remote sensing data and GIS based detailed geomorphological and degraded lands
analysis ensure according to Reddy G.P.O., Maji A.K., Srinivas C.V.,
Velayutham M. [8] better understanding of landform-eroded lands relationship and
distribution to assess the status of land degradation, geo-environmental planning and
management. Similar study also helps in the areas of natural resource management,
environmental planning and management, watershed management and hazards
monitoring and mitigation.
As a case study area a group of scientists Trabucchi M., O’Farrell P.J., Notivol E.,
Comín F.A. [9] used a degraded semi-arid Mediterranean river basin in north east
Spain. The paper shows that the quantification and mapping of services are the first
step required for both optimizing and targeting of specific local areas for restoration.
A critical issue in mapping ecosystem services is data quality and availability.
Mapping involves GIS overlay analysis and geoprocessing to combine input layers
from diverse sources to derive the final ecosystem service map. Difficulties
encountered with deriving ecosystem service maps relate to the scale, age, and
accuracy of the input layers.
In the paper [10] by Chen Z., Pan D., Bai Y., a preliminary assessment of
ecosystem health in Zhejiang coastal water zone was made, mainly based on remote
sensing data and GIS technique. Its spatial and quantitative evaluation was facilitated
by the progress of remote sensing and GIS technique development. The results of this
research indicate that the coastal water ecosystem health value in winter is worse than
in summer, and the farther from shoreline, the better health condition. As compared
with the monitoring results of State Oceanic Administration, the results show the
credibility of this work. Therefore, the research proves the applicability of remote
sensing data and GIS analysis data as indicators for the coastal water ecosystem
health assessment.
3 Modeling Process of Self-Purification of Surface Waters
The ecological state of natural waters largely depends on their ability to self-
purification. In the study of pollution and self-purification processes, the following
main areas are distinguished:
– establishment of dependence of changes in water quality on the hydrological regime
and the estimated characteristics of the flow;
– study of chemical, physicochemical transformations of pollutants in water bodies;
– study of biochemical processes of transformation of pollutants.
Along with hydrological factors, an important role in the process of self-
purification belongs to physicochemical and biochemical processes. Chemical
processes are closely related to biological ones in natural waters. It is often difficult to
tell where one process ends and another begins. The decisive role in this complex
belongs to biological processes. However, physicochemical processes will dominate
when highly toxic pollutants are present in the water, or unfavorable conditions are
created for the vital activity of animals and plant organisms, in which biological
processes are reduced to a minimum. So, the self-purification of watercourse or water
body depends on many factors: the volume of runoff, the velocity and turbulence of
the stream, the chemical composition and temperature of water, the level of water
pollution [11].
Aeration of water bodies is also important; it provides the saturation of water with
oxygen and increases the intensity of the self-purification process. The supply of
oxygen to water increases with increasing flow turbulence and lowering the
temperature of the water. Therefore, in water reservoirs, water self-purification occurs
slower than in rivers. On hot summer days with high temperatures, the process of self-
purification slows down due to lack of oxygen, which dissolves slower in warm
waters. The self-purification process also stops in winter, when ice does not allow
oxygen to pass into the water [11].
When sewage is discharged into the river, the oxygen content in the water first
decreases, and then, as water moves along the stream, the amount of oxygen increases
and gradually recovers. However, water must pass a certain segment of the river bed
for this. The effect of self-purification may stop if the amount of pollutants will
exceed the maximum permissible concentration (MPC). For fishery water bodies,
wastewater discharge standards are determined by the value of fish breeds, the
conditions of their breeding and feeding. In winter, when the oxygen (О 2) content
drops to 6 mg/dm3, it is prohibited to discharge wastewater into water bodies.
Assessment of the ecological state and the capability of self-purification of surface
water is a complex task. The coefficient of self-purification rate (degradation rate) K
(hour–1, day–1) characterizes the time required for the decomposition of substances to
a certain state, and can be approximately calculated by Streeter H.W. formula [12]:
2,3 С0 1 C0
K lg ln , (1)
С C
where – lag-time of water between the gauge stations, hour, day; С0 and С – the
concentration of the substance, respectively, in the initial and final (after the time )
gauge stations, mg/dm3.
If the self-purification coefficient (K) and the lag-time of water ( ) from the upper
to the lower gauge station are known, the concentration of the pollutant in the gauge
station can be determined in a time that is equal to :
KC
С С0 10 2,3 C0 e KC . (2)
The self-purification coefficient (K), the lag-time of water ( ) and the concentration
of the pollutant in the lower gauge station will depend on the water exchange
processes in the river, which are formed naturally and anthropogenically.
Recently, the determination of chemical oxygen consumption (COD) is used as a
general criterion for reducing the concentration of organic compounds in water. This
makes it possible to judge the pollution of water bodies with organic substances.
The German scientist B. Hawk used the differential equation to determine the
degree of decrease in the concentration of organic substances at various distances
from the places of wastewater discharge [13]:
dI
kI , (3)
d
where – lag-time of water between the gauge stations, hour, day; I – COD in the
water body over time , mg/dm3; k – COD destruction factor, 1/ day.
This equation can be written as:
T T0 e k , (4)
where Т0 – COD value in the water body at the point of complete mixing of water,
mg/dm3.
When the COD is determined in two gauge stations (A; B) at different distances
along the river by transforming equation (4), it is possible to determine the value of K,
which will characterize the total oxidation rate:
2,3 TA
K lg day1 , (5)
TB
where TA and TВ – the value of COD in gauge stations A and B.
The self-purification capability of surface water (in percent) in a section of a water
body can be determined by the equation [14]:
С1 С2
С 100%, (6)
С1
where С – the percentage of purification; С1 – concentration of the substance in the
upper (initial) gauge station of the section, mg/dm3; С2 – concentration of the
substance in the lower (final) gauge station of the section after a certain time, mg/dm 3.
4 Mathematical Model of the Ecological State of the Surface
Waters of the Lower Section of the Dnieper River According
to the Hydrochemical Ingredients
Spatio-temporal information, which is used for modeling, covers the following
components rubricator for the territory of the Lower Section of the Dnieper River:
– geographical and geological description;
– hydrochemical ingredients and water quality assessment methods.
The data of the analytical monitoring of surface waters of the Kherson Water
Resources Board for the 2013–2018 was used to assess the ecological state of the
Lower Section of the Dnieper River on points of supervisions of water: 1 – the
Dnieper River – town Novovorontsovka-Ushkalka, Kakhovka Reservoir (195 km
from the mouth), 2 – the Dnieper River – low tail-water of Kakhovka HPS (92 km
from the mouth), 3 – the Dnieper River – city Kherson, 1 km upstream the city
(40 km from the mouth), 4 – the Dnieper River – village Kizomys, arm of a river
Rvach (0 km from the mouth) (fig. 1).
Fig. 1. Scheme of the Lower Section of the Dnieper River
As a result of the research, it was found that over the observation period of 2013–
2018 for the territory of the Lower Section of the Dnieper River, there is an excess of
COD concentrations according to fishery standards along the length of the river and in
time, which indicates water pollution, but does not provide information on the
components of pollution. The self-purification ability of surface waters (6), calculated
from the observed COD, for 2018 takes negative values (С [–12,7; –3,9]). This
confirms the results of previous research [15] and allows us to conclude that the level
of self-regulation and self-purification of the surface waters of the Lower Section of
the Dnieper River is low.
Data analysis of analytical control of surface waters by gauge stations of the Lower
Section of the Dnieper River for 2013–2018, allowed to identify the excess of the
measured values of hydrochemical ingredients relative to the MPC on fisheries
standards from 1.3 (COD) to 4.6 (Copper) (fig. 2).
Fig. 2. Excess annual average values (2013–2018) of hydrochemical ingredients relative to
MPC of the Lower Section of the Dnieper River
The method of environmental assessment of surface water quality according to the
relevant categories [16] allows analyzing observational data, determining the classes
and categories of water quality, the state of water bodies, and assessing the conditions
for the restoration of water resources using many tables. We propose to express the
dependence of the category of water quality on the concentration of hydrochemical
ingredients in the form of a regression equation. The following are examples of such a
representation of the dependencies of the water quality categories on the values of
COD, Suspended solids, Chlorides, Sulphates (fig. 3), Petroleum hydrocarbons, Iron,
Copper and Manganese (fig. 4).
Fig. 3. Dependence of the category of surface water quality on the concentration of
hydrochemical ingredients (COD, Suspended solids, Chlorides, Sulphates)
Fig. 4. Dependence of the category of surface water quality on the concentration of
hydrochemical ingredients (Cu, Petroleum hydrocarbons, Mn, Fe)
As a result of constructing approximating curves according to the values of the
concentrations of hydrochemical ingredients, regression equations are obtained. They
are logarithmic dependencies. (fig. 3, 4). The dependency equations are characterized
by the values of the correlation coefficients from 0.98 to 0.99, which indicates the
presence of close connections between the values of the provided sample. The
obtained dependences provide an opportunity to determine the category of surface
water quality (vertical axis) based on measured concentrations of the corresponding
hydrochemical ingredients (horizontal axis). They can serve as a basis for visualizing
the results of modeling the ecological state of surface waters using GIS technologies.
5 Visualization of the Ecological State of the Surface Waters of
the Lower Section of the Dnieper River using GIS
Technologies
An environmental assessment of the quality of the surface waters of the Lower
Section of the Dnieper River was carried out on the basis of the analysis of
hydrochemical ingredients for the observation period of 2013–2018 with subsequent
calculation and generalization. The results of spatial generalization are presented in
the form of maps of the ecological state of surface waters according to the content of
water quality indicators.
We presented in out study the possibilities of self-purification of a water body
(water quality) in space through a decrease the concentrations of harmful substances
through visual changes (color indication).
A software product was developed that made it possible to implement a visual
model of the distribution of pollutants between observation places along the length of
the river. The program allows, on the basis of the input data, to obtain a gradient
coloring of the river bed in a color range that corresponds to a certain category of
water quality (table 1).
Table 1. Environmental water quality assessment by ecological classification
Water
The extent of
Color quality Water quality class Water condition
water purity
category
1 I excellent very clean
2 very good clean
II
3 good sufficient clean
poorly
4 acceptable
contaminated
III
moderately
5 mediocre
contaminated
6 IV poor contaminated
7 V very poor very contaminated
Examples of obtained images are shown for the values of COD, Suspended solids,
Chlorides, Sulphates (fig. 5), Petroleum hydrocarbons, Iron, Copper and Manganese
(fig. 6).
Fig. 5. Ecological state of the surface waters of the Lower Section of the Dnieper River by
hydrochemical ingredients, mg/dm3: a - Suspended solids, b - Chlorides, c - Sulphates, d - COD
The basis for the implementation of the graphical image of the ecological state model
was formed by such development tools as HTML, CSS and JavaScript, which allows
for close integration with Web 2.0 technology. This gives the possibility of placing
software on the Internet and provides free access to it for scientific and educational
purposes.
Correspondence of ranges of the category scale and hexadecimal values of the
additive RGB color model for visualization of numerical indicators was carried out.
The distribution of colors is performed by dividing the color spectrum into seven
equal segments in the area from dark blue to red, which corresponds to the minimum
and maximum values of the numerical values of the hydrochemical ingredients.
ArcGis cartographic materials were used to form an image of the river bed.
Fig. 6. Ecological state of the surface waters of the Lower Section of the Dnieper River by
hydrochemical ingredients, mcg/dm3: a - Petroleum hydrocarbons, b - Fe, c - Cu, d - Mn
The convenience of use of these technologies consists in the independence of the
choice of the operating system to ensure the operability of the software product
because any modern browser will allow to successfully use this software.
The obtained maps demonstrate the ecological state of the surface waters of the
Lower Section of the Dnieper River, which varies from “excellent” by Suspended
solids for the Kakhovka Reservoir (Class I, Category 1, very clean water) (fig. 5, a) to
“poor” by Petroleum hydrocarbons for all observation area (Class IV, Category 6,
contaminated water) (fig. 6, а).
The unstable ecological state and the change in the water quality of the Lower
Section of the Dnieper River are explained by the flow of polluted water from the
Ingulets River (between 2 and 3 gauge stations) [17, 18] and stream flow control by
the Kakhovka HPS-1 [19, 20].
Low self-purification ability of the surface waters of the Lower Section of the
Dnieper River, located on the technogenically loaded area [17-20], indicates that the
anthropogenic load on the water body has reached a critical level. It is necessary to
provide scientifically based calculations of any type of economic activity [21], carried
out in the river basin, to restore the ability of the hydroecosystem to self-regulation
and self-purification. Recovery of self-purification processes of the Lower Section of
the Dnieper River is possible due to the optimization of the regime of Kakhovka
HPS-1 [18, 20] releases and/or building Kakhovka HPS-2 [22]. The activation of the
external water exchange will unambiguously increase the intensity of the river ability
to cleanse water masses, will improve the water quality in the system of the Lower
Section of the Dnieper River and the ecological state of the hydroecosystem.
6 Conclusions and Outlook
The research results presented in this article can be the basis for establishing trends
changes in the ecological state of the surface waters of the Lower Section of the Dnieper
River in time and space, determining the impact of anthropogenic load on ecosystems of
water bodies, estimating changes of water quality, informing the public, solving economic
and social issues, related to the rational use of natural resources and ensuring
environmental protection.
Visual interpretation of changes in the state of natural systems (color indication of
water quality) allows governing bodies (including those without special environmental
education) to make quickly decisions on regulating the anthropogenic load on a water
body (for example, reduce the volume of wastewater discharges, stop the enterprise,
increase releases from Kakhovka reservoir, etc.). In addition, the digital indication of
water quality is presented not only in quantitative terms, but also in qualitative assessment.
Perspectives for further research can be represented by the use of GIS technologies for
the spatio-temporal representation of the ecological state of the Lower Section of the
Dnieper River on the integrated index and ecological reliability of the water body.
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