Pub Date : 2024-04-05DOI: 10.1134/s0097807823600717
Mohammad Reza Khalilabadi
Abstract
In this investigation, the General Ocean Turbulent Model (GOTM) was used for the investigation of turbulent processes of a water column over a study site in the Oman Sea. The used method appropriately reproduces the main features of the study area, allows for a realistic view of the turbulence, and thus makes it possible to compare the Mixed Layer Depth (MLD) in all seasons. The MLD varies from 150 m in spring to 200 m in autumn. This simulation presented that the production of Turbulent Kinetic Energy (TKE) in the seawater column in the Oman Sea has seasonal changes. In the surface layer, TKE is small which is produced by low quantities of shear production, then it is conserved by the wind stress on the mixed layer and buoyancy production. In the deep layer, TKE is produced only by buoyancy. Calculated Prandtl number in all seasons presented that the turbulent diffusivity of temperature is dominant in most parts of water column, except in a thin layer which forms approximately between the depths of 150–200 m.
AbstractIn this investigation, the General Ocean Turbulent Model (GOTM) was used for the investigation of turbulent processes of a water column over a study site in the Oman Sea.所使用的方法恰当地再现了研究区域的主要特征，可以真实地观察湍流，从而可以比较各个季节的混合层深度（MLD）。混合层深度从春季的 150 米到秋季的 200 米不等。模拟结果表明，阿曼海海水柱中产生的湍流动能（TKE）具有季节性变化。在表层，TKE 较小，由少量剪切力产生，然后由混合层上的风应力和浮力产生来保持。在深层，TKE 仅由浮力产生。所有季节的普朗特尔数计算结果都表明，在水柱的大部分区域，温度的湍流扩散性占主导地位，只有大约在 150-200 米水深之间形成的薄层除外。
{"title":"Turbulent Processes in the Oman Sea: A Numerical Study","authors":"Mohammad Reza Khalilabadi","doi":"10.1134/s0097807823600717","DOIUrl":"https://doi.org/10.1134/s0097807823600717","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>In this investigation, the General Ocean Turbulent Model (GOTM) was used for the investigation of turbulent processes of a water column over a study site in the Oman Sea. The used method appropriately reproduces the main features of the study area, allows for a realistic view of the turbulence, and thus makes it possible to compare the Mixed Layer Depth (MLD) in all seasons. The MLD varies from 150 m in spring to 200 m in autumn. This simulation presented that the production of Turbulent Kinetic Energy (TKE) in the seawater column in the Oman Sea has seasonal changes. In the surface layer, TKE is small which is produced by low quantities of shear production, then it is conserved by the wind stress on the mixed layer and buoyancy production. In the deep layer, TKE is produced only by buoyancy. Calculated Prandtl number in all seasons presented that the turbulent diffusivity of temperature is dominant in most parts of water column, except in a thin layer which forms approximately between the depths of 150–200 m.</p>","PeriodicalId":49368,"journal":{"name":"Water Resources","volume":"25 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140574895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-05DOI: 10.1134/s0097807823700641
K. V. Titova, N. M. Kokryatskaya, S. S. Popov, O. Yu. Moreva, A. A. Sloboda, S. I. Klimov, V. M. Bykov, N. S. Prilutskaya
Abstract
Comprehensive hydrochemical studies of nine lakes of different types on the Bolshoi Solovetskii Island (Arkhangelsk region) were carried out (July 2022). The choice of the objects was determined by the morphometric features of the water bodies, their remoteness from the sea, and the possible anthropogenic load on them. The main hydrochemical characteristics were determined, including the temperature, electric conductivity/TDS, pH, color, alkalinity, ionic composition, hardness, and the concentrations of oxygen, hydrogen sulfide, organic carbon, nutrients, heavy metals, and methane. Water hardness was found to be low with chloride and sodium ions dominating in its TDS. The hydrochemical conditions are shown to be generally favorable for biogeochemical processes. At a low and medium concentration of organic mater (from 8 to 30 mg/L), humic acids dominated in its composition, determining a higher color index of water (except for the Nizhnii Pert Lake). By their trophic level, the examined lakes were classified as oligotrophic (one of them is dystrophic), mesotrophic, and eutrophic. The anthropogenic load determined the status of a mesotrophic water body, and the high trophicity was determined by natural factors (the swampiness of catchment areas and their relatively recent separation from the sea).
{"title":"Hydrochemical Characteristics of Lakes of Different Types on the Bolshoi Solovetskii Island","authors":"K. V. Titova, N. M. Kokryatskaya, S. S. Popov, O. Yu. Moreva, A. A. Sloboda, S. I. Klimov, V. M. Bykov, N. S. Prilutskaya","doi":"10.1134/s0097807823700641","DOIUrl":"https://doi.org/10.1134/s0097807823700641","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Comprehensive hydrochemical studies of nine lakes of different types on the Bolshoi Solovetskii Island (Arkhangelsk region) were carried out (July 2022). The choice of the objects was determined by the morphometric features of the water bodies, their remoteness from the sea, and the possible anthropogenic load on them. The main hydrochemical characteristics were determined, including the temperature, electric conductivity/TDS, pH, color, alkalinity, ionic composition, hardness, and the concentrations of oxygen, hydrogen sulfide, organic carbon, nutrients, heavy metals, and methane. Water hardness was found to be low with chloride and sodium ions dominating in its TDS. The hydrochemical conditions are shown to be generally favorable for biogeochemical processes. At a low and medium concentration of organic mater (from 8 to 30 mg/L), humic acids dominated in its composition, determining a higher color index of water (except for the Nizhnii Pert Lake). By their trophic level, the examined lakes were classified as oligotrophic (one of them is dystrophic), mesotrophic, and eutrophic. The anthropogenic load determined the status of a mesotrophic water body, and the high trophicity was determined by natural factors (the swampiness of catchment areas and their relatively recent separation from the sea).</p>","PeriodicalId":49368,"journal":{"name":"Water Resources","volume":"11 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140574935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-05DOI: 10.1134/s0097807823700665
D. S. Dudakova, V. M. Anokhin, M. O. Dudakov, M. I. Orlova
Abstract
The article presents the results of studies of bottom landscapes carried out with the use of an echo sounder with a side-scan location function and supplemented by video filming from an underwater vehicle in a bay of one of the islands in the northern skerry area of Lake Ladoga in June 2022. The results of the echo sounding were used to develop a three-dimensional bathymetric model of the examined Haukaisenlahti Bay on Kukhka Island and to identify significant differences in comparison with published navigation maps for Haukaisenlahti Bay. The formation of the bed topography and the state of the shores in both above-water and underwater zones are determined by the specific features of the geological structure of this part of the water area, resulting from the different resistance to weathering processes in different geological formations. Six main types of facies were identified in the underwater landscape of the bay. The outlook and the change of facies are associated with the presence of hard rocky surfaces and hard clastic material followed by loose soils at greater depths. The outlook of the facies is also determined by the specific features of the bathymetric structure of the bay and the predominance of various associations of living organisms, the development of which depends on the type of surface and soil. The study confirmed the prospects of the use of echo sounders with a side-scan location function to study and map underwater landscapes of Lake Ladoga in combination with a remote video recording from an uninhabited vehicle.
{"title":"Using Remote Sensing Methods of Underwater Studies to Identify Elements and Simulate the Structure of Bottom Landscapes in the Haukaisenlahti Bay (Kuhka Island, Lake Ladoga)","authors":"D. S. Dudakova, V. M. Anokhin, M. O. Dudakov, M. I. Orlova","doi":"10.1134/s0097807823700665","DOIUrl":"https://doi.org/10.1134/s0097807823700665","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The article presents the results of studies of bottom landscapes carried out with the use of an echo sounder with a side-scan location function and supplemented by video filming from an underwater vehicle in a bay of one of the islands in the northern skerry area of Lake Ladoga in June 2022. The results of the echo sounding were used to develop a three-dimensional bathymetric model of the examined Haukaisenlahti Bay on Kukhka Island and to identify significant differences in comparison with published navigation maps for Haukaisenlahti Bay. The formation of the bed topography and the state of the shores in both above-water and underwater zones are determined by the specific features of the geological structure of this part of the water area, resulting from the different resistance to weathering processes in different geological formations. Six main types of facies were identified in the underwater landscape of the bay. The outlook and the change of facies are associated with the presence of hard rocky surfaces and hard clastic material followed by loose soils at greater depths. The outlook of the facies is also determined by the specific features of the bathymetric structure of the bay and the predominance of various associations of living organisms, the development of which depends on the type of surface and soil. The study confirmed the prospects of the use of echo sounders with a side-scan location function to study and map underwater landscapes of Lake Ladoga in combination with a remote video recording from an uninhabited vehicle.</p>","PeriodicalId":49368,"journal":{"name":"Water Resources","volume":"75 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140574937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-05DOI: 10.1134/s0097807823700677
P. N. Terskii, S. L. Gorin, E. D. Panchenko, A. M. Alabyan, N. D. Akhmerova, A. N. Vasilenko, V. A. Ivanov, E. A. Krastyn, Zh. M. Kulikova, D. A. Migunov, A. A. Popryadukhin, M. O. Fatkhi, M. A. Kharlamov
Abstract
The paper shows that the lower reaches of the Varzuga River (Terskii coast of the White Sea) are subject to a strong effect of sea tides, which can be seen in level variations and the periodic occurrence of reverse (tidal) currents and saltwater intrusions. The data was obtained during the expedition carried out in winter 2020 at the estuary of the Varzuga River along with data collected by the authors at the estuaries of other rivers in the White Sea basin (the Mezen, Onega, Umba, Kyanda, Tamitsa, and Kuzreka rivers) in 2017−2019. In this context, characteristics of the processes mentioned above are given and the factors that affect them (channel relief, river flow, tides, and ice) are discussed.
{"title":"The Tidal Estuary of the Varzuga River (Russian Subarctic): First Information about the Winter Hydrological Regimе","authors":"P. N. Terskii, S. L. Gorin, E. D. Panchenko, A. M. Alabyan, N. D. Akhmerova, A. N. Vasilenko, V. A. Ivanov, E. A. Krastyn, Zh. M. Kulikova, D. A. Migunov, A. A. Popryadukhin, M. O. Fatkhi, M. A. Kharlamov","doi":"10.1134/s0097807823700677","DOIUrl":"https://doi.org/10.1134/s0097807823700677","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The paper shows that the lower reaches of the Varzuga River (Terskii coast of the White Sea) are subject to a strong effect of sea tides, which can be seen in level variations and the periodic occurrence of reverse (tidal) currents and saltwater intrusions. The data was obtained during the expedition carried out in winter 2020 at the estuary of the Varzuga River along with data collected by the authors at the estuaries of other rivers in the White Sea basin (the Mezen, Onega, Umba, Kyanda, Tamitsa, and Kuzreka rivers) in 2017−2019. In this context, characteristics of the processes mentioned above are given and the factors that affect them (channel relief, river flow, tides, and ice) are discussed.</p>","PeriodicalId":49368,"journal":{"name":"Water Resources","volume":"70 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140574897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-05DOI: 10.1134/s0097807823602194
A. V. Goncharov, D. M. Palatov, N. L. Frolova, V. O. Polyanin, V. A. Isaev, E. Kh. Kudyakov
Abstract
This article presents the results of a study of zoobenthos of the Ural River in an area from the town of Verkhneuralsk to the city of Orenburg (about 1000 km) with sampling upstream and downstream of sources of anthropogenic impact: large cities, metallurgical plants, treatment facilities (TFs), and reservoirs. The degree of pollution was estimated using the Shannon and EPT indices, as well as the Woodiwiss index, an indicator that partially takes into account the first two indices. It is shown that the selected parameters decrease downstream of the sources of anthropogenic impact, thereby reflecting a decrease in the species diversity of benthic biocenoses and a decrease in the number of indicator species sensitive to pollution. Small streams are particularly affected; pools are subject to greater transformations than riffles. An integrated indicator of water quality based on biological parameters is proposed. It was used to rank all studied areas by the degree of pollution. It is shown that ten of the 23 studied river areas are assigned to the 1st class of water quality (conventionally clean areas), seven areas to the 2nd class (weakly polluted areas), three areas to the 4th class (dirty areas), and three areas to the 5th class (extremely dirty areas). This indicates that, despite multiple sources of pollution, the Ural River has a high self-purification capacity and most of the studied areas are quite clean and favorable for the habitation of benthic invertebrates.
{"title":"Biological Indication of Pollution of the Ural River Based on the Results of a Study of Its Zoobenthos in Summer 2022","authors":"A. V. Goncharov, D. M. Palatov, N. L. Frolova, V. O. Polyanin, V. A. Isaev, E. Kh. Kudyakov","doi":"10.1134/s0097807823602194","DOIUrl":"https://doi.org/10.1134/s0097807823602194","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>This article presents the results of a study of zoobenthos of the Ural River in an area from the town of Verkhneuralsk to the city of Orenburg (about 1000 km) with sampling upstream and downstream of sources of anthropogenic impact: large cities, metallurgical plants, treatment facilities (TFs), and reservoirs. The degree of pollution was estimated using the Shannon and EPT indices, as well as the Woodiwiss index, an indicator that partially takes into account the first two indices. It is shown that the selected parameters decrease downstream of the sources of anthropogenic impact, thereby reflecting a decrease in the species diversity of benthic biocenoses and a decrease in the number of indicator species sensitive to pollution. Small streams are particularly affected; pools are subject to greater transformations than riffles. An integrated indicator of water quality based on biological parameters is proposed. It was used to rank all studied areas by the degree of pollution. It is shown that ten of the 23 studied river areas are assigned to the 1st class of water quality (conventionally clean areas), seven areas to the 2nd class (weakly polluted areas), three areas to the 4th class (dirty areas), and three areas to the 5th class (extremely dirty areas). This indicates that, despite multiple sources of pollution, the Ural River has a high self-purification capacity and most of the studied areas are quite clean and favorable for the habitation of benthic invertebrates.</p>","PeriodicalId":49368,"journal":{"name":"Water Resources","volume":"123 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140574922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-05DOI: 10.1134/s009780782370063x
D. A. Tikhonova, S. G. Karetnikov, E. V. Ivanova, E. P. Shalunova
Abstract
The vertical distribution of microplastics in Lake Ladoga was studied under conditions of density stratification with the presence of a thermocline and under homothermal conditions. Using a pump filtration device, water samples were taken at different water layers (0–70 m) under different hydrological conditions and a comparative analysis of the concentrations of microplastic particles with a size of 60–5000 μm was carried out. Microplastic particles were analyzed using both optical microscopy and Raman spectroscopy methods. Based on the obtained data, it was concluded that under conditions of density stratification, the concentrations of microplastic particles in the thermocline and above it are increased in comparison with the underlying layers (50 ± 40.2 and 15.9 ± 13 particles/m3, respectively). Under homothermal conditions, the vertical distribution of microplastics in the surface layer and in water column is more uniform (17.3 ± 17.8 and 12.7 ± 15.6 particles/m3, respectively).
{"title":"The Vertical Distribution of Microplastics in the Water Column of Lake Ladoga","authors":"D. A. Tikhonova, S. G. Karetnikov, E. V. Ivanova, E. P. Shalunova","doi":"10.1134/s009780782370063x","DOIUrl":"https://doi.org/10.1134/s009780782370063x","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The vertical distribution of microplastics in Lake Ladoga was studied under conditions of density stratification with the presence of a thermocline and under homothermal conditions. Using a pump filtration device, water samples were taken at different water layers (0–70 m) under different hydrological conditions and a comparative analysis of the concentrations of microplastic particles with a size of 60–5000 μm was carried out. Microplastic particles were analyzed using both optical microscopy and Raman spectroscopy methods. Based on the obtained data, it was concluded that under conditions of density stratification, the concentrations of microplastic particles in the thermocline and above it are increased in comparison with the underlying layers (50 ± 40.2 and 15.9 ± 13 particles/m<sup>3</sup>, respectively). Under homothermal conditions, the vertical distribution of microplastics in the surface layer and in water column is more uniform (17.3 ± 17.8 and 12.7 ± 15.6 particles/m<sup>3</sup>, respectively).</p>","PeriodicalId":49368,"journal":{"name":"Water Resources","volume":"19 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140574926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-05DOI: 10.1134/s0097807823601188
Wang Qiushun, Pan Cunhong, Chen Fuyuan
Abstract
Tidal bores inject large amounts of energy to the estuaries, and the variation of tidal bore is related to its energy distribution. In this study, the temporal and spatial changes of the tidal bore energy are investigated to demonstrate the propagation characteristics of tidal bores in the Qiantang River Estuary. Based on high frequency field data, the characteristics of the potential energy and the kinetic energy per unit area during the passage of tidal bores at Yanguan station is demonstrated. Numerical model employing shallow water equations is established to investigate the tidal bore energy along the estuary. Tidal level, tidal current and tidal bore during spring tides in September, 2019 are verified, and the tidal bore energy and its distribution characteristics along the sections from Ganpu to Wenjiayan are illustrated. The tidal bore energy is significantly decreased in the Daquekou reach but decreased relatively small in the reach from Qige to Wenjiayan. There is the maximum energy loss in the Jianshan reach. The tidal bore energy declines to 15% at Wenjiayan during the passage of the energetic breaking tidal bores, indicating tidal bore disappearance in the upstream reach.
{"title":"Study on the Tidal Bore Energy along the Qiantang River Estuary, China","authors":"Wang Qiushun, Pan Cunhong, Chen Fuyuan","doi":"10.1134/s0097807823601188","DOIUrl":"https://doi.org/10.1134/s0097807823601188","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Tidal bores inject large amounts of energy to the estuaries, and the variation of tidal bore is related to its energy distribution. In this study, the temporal and spatial changes of the tidal bore energy are investigated to demonstrate the propagation characteristics of tidal bores in the Qiantang River Estuary. Based on high frequency field data, the characteristics of the potential energy and the kinetic energy per unit area during the passage of tidal bores at Yanguan station is demonstrated. Numerical model employing shallow water equations is established to investigate the tidal bore energy along the estuary. Tidal level, tidal current and tidal bore during spring tides in September, 2019 are verified, and the tidal bore energy and its distribution characteristics along the sections from Ganpu to Wenjiayan are illustrated. The tidal bore energy is significantly decreased in the Daquekou reach but decreased relatively small in the reach from Qige to Wenjiayan. There is the maximum energy loss in the Jianshan reach. The tidal bore energy declines to 15% at Wenjiayan during the passage of the energetic breaking tidal bores, indicating tidal bore disappearance in the upstream reach.</p>","PeriodicalId":49368,"journal":{"name":"Water Resources","volume":"107 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140574936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-05DOI: 10.1134/s0097807823600973
Ali Alkan, Mustafa Tombul
Abstract
A drought is a prolonged natural disaster with numerous economic, social, and environmental consequences; it occurs when the natural water supply in a given region falls below normal levels. Precautions must be taken to mitigate the negative impacts that drought can cause. Drought probabilities can be estimated by carefully analyzing variables such as precipitation, river flow, and soil moisture with the help of various indices. In the literature, many studies have been conducted to estimate drought indices over time. In this study, drought forecasts were made for the Seyhan and Ceyhan Basins in 3-, 4-, 6-, and 12-month periods with the Standardized Precipitation Index (SPI) using precipitation data between January 1989 and July 2020. The success rates of the forecasts made in the models created with the Random Forest (RF) Algorithm, Support Vector Machine (SVM), and Artificial Neural Network (ANN) machine learning methods were statistically compared. The SVM drought forecasting model was performed in 3-month forecasts in the study. Among the machine learning methods, the ANN method was more successful than the other methods in terms of performance in 4, 6, and 12-month drought forecasts.
{"title":"Drought Forecasting of Seyhan and Ceyhan Basins Using Machine Learning Methods","authors":"Ali Alkan, Mustafa Tombul","doi":"10.1134/s0097807823600973","DOIUrl":"https://doi.org/10.1134/s0097807823600973","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>A drought is a prolonged natural disaster with numerous economic, social, and environmental consequences; it occurs when the natural water supply in a given region falls below normal levels. Precautions must be taken to mitigate the negative impacts that drought can cause. Drought probabilities can be estimated by carefully analyzing variables such as precipitation, river flow, and soil moisture with the help of various indices. In the literature, many studies have been conducted to estimate drought indices over time. In this study, drought forecasts were made for the Seyhan and Ceyhan Basins in 3-, 4-, 6-, and 12-month periods with the Standardized Precipitation Index (SPI) using precipitation data between January 1989 and July 2020. The success rates of the forecasts made in the models created with the Random Forest (RF) Algorithm, Support Vector Machine (SVM), and Artificial Neural Network (ANN) machine learning methods were statistically compared. The SVM drought forecasting model was performed in 3-month forecasts in the study. Among the machine learning methods, the ANN method was more successful than the other methods in terms of performance in 4, 6, and 12-month drought forecasts.</p>","PeriodicalId":49368,"journal":{"name":"Water Resources","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140574772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Based on multi-variable water quality data, spatio-temporal variations of water quality can be explored to provide a scientific basis for sustainable water quality management. Lixia River Watershed, a relatively closed low-lying polder area in the lower reaches of Huai River basin, China, is closely related to the Yangtze River system. The spatio-temporal variations of water quality of Taizhou, a subsection of the Lixia River Watershed, were assessed based on the monthly water quality data of 39 sampling sites in 2017, by combining methods of Water Quality Index of the Canadian Council of Ministers of the Environment (CCME WQI), cluster analysis (CA), discriminant analysis (DA) and principal component analysis (PCA). The results show that CCME WQI ranged from 70.17 to 95.35, and the water quality of sampling sites could be grouped into 3 categories, where the southwestern parts of both Hailing and Jiangyan were excellent, the south and northeast of Xinghua were good, the southeast of Jiangyan and the northwest of Xinghua were fair. The 12 months of 2017 were grouped into two clusters, water quality in time period 1 (January to March, July to October) was poor, while that in time period 2 (April to June, November to December) was good. Sampling sites were grouped into two clusters: spatial group A (southwest of both Jiangyan and Hailing, south of Xinghua) and spatial group B (southeast of Jiangyan, north of Xinghua), and spatial group B was seriously polluted. NH3-N, total phosphorus (TP) and five-day biochemical oxygen demand (BOD5) were the major variables responsible for water quality variation, while permanganate index (CODMn), chemical oxygen demand (CODcr) and dissolved oxygen (DO) were the secondary parameters.
{"title":"Spatio-Temporal Variation of Water Quality in Lixia River Watershed Associated with the Operation of a Water Diversion Project","authors":"Chenjuan Jiang, Liang Luo, Jia’nan Zhou, Guosheng Fu, Xiaoli Chen","doi":"10.1134/s0097807823600572","DOIUrl":"https://doi.org/10.1134/s0097807823600572","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Based on multi-variable water quality data, spatio-temporal variations of water quality can be explored to provide a scientific basis for sustainable water quality management. Lixia River Watershed, a relatively closed low-lying polder area in the lower reaches of Huai River basin, China, is closely related to the Yangtze River system. The spatio-temporal variations of water quality of Taizhou, a subsection of the Lixia River Watershed, were assessed based on the monthly water quality data of 39 sampling sites in 2017, by combining methods of Water Quality Index of the Canadian Council of Ministers of the Environment (CCME WQI), cluster analysis (CA), discriminant analysis (DA) and principal component analysis (PCA). The results show that CCME WQI ranged from 70.17 to 95.35, and the water quality of sampling sites could be grouped into 3 categories, where the southwestern parts of both Hailing and Jiangyan were excellent, the south and northeast of Xinghua were good, the southeast of Jiangyan and the northwest of Xinghua were fair. The 12 months of 2017 were grouped into two clusters, water quality in time period 1 (January to March, July to October) was poor, while that in time period 2 (April to June, November to December) was good. Sampling sites were grouped into two clusters: spatial group A (southwest of both Jiangyan and Hailing, south of Xinghua) and spatial group B (southeast of Jiangyan, north of Xinghua), and spatial group B was seriously polluted. NH<sub>3</sub>-N, total phosphorus (TP) and five-day biochemical oxygen demand (BOD<sub>5</sub>) were the major variables responsible for water quality variation, while permanganate index (COD<sub>Mn</sub>), chemical oxygen demand (COD<sub>cr</sub>) and dissolved oxygen (DO) were the secondary parameters.</p>","PeriodicalId":49368,"journal":{"name":"Water Resources","volume":"10 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140574925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-05DOI: 10.1134/s0097807823700653
A. V. Savenko, V. S. Savenko
Abstract
Analyses of fluorine concentrations in the waters of the Dead Sea and Lake Urmia yielded the values of 5.3 ± 0.1 and 10.5 ± 0.1 mg/L, which in terms of the mass of the salt residue gives 15.9 and 26.0 mg F per 1 kg of anhydrous salts. Fluorine concentration in the salt residue of water in the examined hypersaline water bodies is far less than that for the normal seawater (37.1 mg F/kg). Experimental data show that the waters of the Dead Sea and Lake Urmia are strongly undersaturated in CaF2, because of which spontaneous chemogenic precipitation of fluorite in them is impossible.
{"title":"Fluorine in the Waters of Hypersaline Water Bodies: Dead Sea, Lake Urmia","authors":"A. V. Savenko, V. S. Savenko","doi":"10.1134/s0097807823700653","DOIUrl":"https://doi.org/10.1134/s0097807823700653","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Analyses of fluorine concentrations in the waters of the Dead Sea and Lake Urmia yielded the values of 5.3 ± 0.1 and 10.5 ± 0.1 mg/L, which in terms of the mass of the salt residue gives 15.9 and 26.0 mg F per 1 kg of anhydrous salts. Fluorine concentration in the salt residue of water in the examined hypersaline water bodies is far less than that for the normal seawater (37.1 mg F/kg). Experimental data show that the waters of the Dead Sea and Lake Urmia are strongly undersaturated in CaF<sub>2</sub>, because of which spontaneous chemogenic precipitation of fluorite in them is impossible.</p>","PeriodicalId":49368,"journal":{"name":"Water Resources","volume":"249 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140575029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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