Dr-Noha Kamal - Academia.edu (original) (raw)
Papers by Dr-Noha Kamal
The Egyptian Journal of Remote Sensing and Space Science
This paper investigates the potential of using the Sentinel-2 images for deriving bathymetric map... more This paper investigates the potential of using the Sentinel-2 images for deriving bathymetric maps for the Nile River in Egypt. Regression analysis technique with the aid of in situ measurements were used. Exploring the effects of the size of calibration data, and water depth is another aim of this paper. Linear and machine learning regression techniques (Fine Decision Tree (FDT), and Random Forest (RF) Algorithms) are investigated. The study area is about 23 km between Assiut and Delta barrages. Around 82,000 depth points, are available. Regression models are developed using the depth data and the corresponding digital values of the 13 Sentinel-2 imagery bands. The linear regression model was not applicable (R 2 = 0.02). The FDT, and RF models, have (R 2 = 0.86) when half of the depth points were used for calibration, and the RMSE of the testing data (the other half of the depth points) equaled to 2.86 and 2.09 m, respectively. When fewer points were used for calibration, the R 2 = 0.83 and 0.84, and RMSE = 2.65 and 2.19 m, for FDT and RF, respectively. When only the shallow water areas were considered, the RMSE reached 1.51 and 1.30 m for the FDT and RF, respectively. The VNIR bans of Sentinel-2 images are not enough to estimate the water depth of the Nile river. Collecting in situ measurements for small areas, is adequate for estimating the water depth and produces bathymetry maps for the Nile River in Egypt, and larger in situ measurements are not required.
Ain Shams Engineering Journal
The world's population explosion and water scarcity has researchers looking for smart inn... more The world's population explosion and water scarcity has researchers looking for smart innovations to provide food for the world and save water. In recent years, smart technologies have received much attention in the areas of irrigation and agriculture research. The main objective of this paper is to design and implement of new smart hydroponic and aeroponic greenhouse system based on Internet of Things (IoT) technology for research studies in National Water Research Center. The greenhouse is connected to many various tools for controlling the weather conditions automatically inside the greenhouse consistent with the plant type and season. The indoor environment is equipped with a set of IoT sensors to measure various parameters such as temperature; Humidity, luminous intensity, and total dissolved solids. The pesticide spraying tank is also used to overcome pests within the greenhouse. The IoT platform was used to automate and store system parameters, as well as provide graphical interface remote access. With minimal user input, the constructed system can preserve healthy plant growing parameters. The current study evaluates the environmental and technical impacts of the developed smart system on the cultivation of Batavia lettuce with high economic value. It can conclude that improving water and energy use efficiency (saving them to about 80%), in addition to doubling productivity per area and reducing the time yield to reach 45 days comparing 75 days with the traditional agriculture whatever the fertility of the soil. Moreover, save labor in agriculture, and reducing fertilizer and pesticide use. The resulted of Total Dissolved Solids (TDS), Relative Humidity (RH), and Temperature (T) was analyzed and evaluated during the cultivation period with and without the developed smart system.
Potential of Using Machine Learning Regression Techniques to Utilize Sentinel Images for Bathymetry Mapping of Nile River, 2023
This paper investigates the potential of using the Sentinel-2 images for deriving bathymetric map... more This paper investigates the potential of using the Sentinel-2 images for deriving bathymetric maps for the Nile River in Egypt. Regression analysis technique with the aid of in situ measurements were used. Exploring the effects of the size of calibration data, and water depth is another aim of this paper. Linear and machine learning regression techniques (Fine Decision Tree (FDT), and Random Forest (RF) Algorithms) are investigated. The study area is about 23 km between Assiut and Delta barrages. Around 82,000 depth points, are available. Regression models are developed using the depth data and the corresponding digital values of the 13 Sentinel-2 imagery bands. The linear regression model was not applicable (R 2 = 0.02). The FDT, and RF models, have (R 2 = 0.86) when half of the depth points were used for calibration, and the RMSE of the testing data (the other half of the depth points) equaled to 2.86 and 2.09 m, respectively. When fewer points were used for calibration, the R 2 = 0.83 and 0.84, and RMSE = 2.65 and 2.19 m, for FDT and RF, respectively. When only the shallow water areas were considered, the RMSE reached 1.51 and 1.30 m for the FDT and RF, respectively. The VNIR bans of Sentinel-2 images are not enough to estimate the water depth of the Nile river. Collecting in situ measurements for small areas, is adequate for estimating the water depth and produces bathymetry maps for the Nile River in Egypt, and larger in situ measurements are not required.
Internet of Things based smart automated indoor hydroponics and aeroponics greenhouse in Egypt, 2023
The world's population explosion and water scarcity has researchers looking for smart innovations... more The world's population explosion and water scarcity has researchers looking for smart innovations to provide food for the world and save water. In recent years, smart technologies have received much attention in the areas of irrigation and agriculture research. The main objective of this paper is to design and implement of new smart hydroponic and aeroponic greenhouse system based on Internet of Things (IoT) technology for research studies in National Water Research Center. The greenhouse is connected to many various tools for controlling the weather conditions automatically inside the greenhouse consistent with the plant type and season. The indoor environment is equipped with a set of IoT sensors to measure various parameters such as temperature; Humidity, luminous intensity, and total dissolved solids. The pesticide spraying tank is also used to overcome pests within the greenhouse. The IoT platform was used to automate and store system parameters, as well as provide graphical interface remote access. With minimal user input, the constructed system can preserve healthy plant growing parameters. The current study evaluates the environmental and technical impacts of the developed smart system on the cultivation of Batavia lettuce with high economic value. It can conclude that improving water and energy use efficiency (saving them to about 80%), in addition to doubling productivity per area and reducing the time yield to reach 45 days comparing 75 days with the traditional agriculture whatever the fertility of the soil. Moreover, save labor in agriculture, and reducing fertilizer and pesticide use. The resulted of Total Dissolved Solids (TDS), Relative Humidity (RH), and Temperature (T) was analyzed and evaluated during the cultivation period with and without the developed smart system.
The Nile River is an essential resource to maintain environmental balance in Egypt, it supplies d... more The Nile River is an essential resource to maintain environmental balance in Egypt, it supplies drinking water, low cost transportation, irrigation, hydropower, and provide livelihoods. The conjunction between river human interventions and morphological changes impacts show real challenges to the government and researchers. The design of information system to observe these impacts is necessary and required for Nile River sustainable development, management, and planning. This paper introduces the potential of GIS in developing a comprehensive Nile River information system (NRIS). This system is the key factor to facilitate and attain efficient decision making to the responsible of water management organizations. Scripts using python language is developed enabling the decision maker to access, edit, search, analyze and manipulate the available database. In addition, proposes that the designed GIS based information system can substitute the traditiona1 methods for extracting accurate information from database and can be updated in easily. Using the developed GIS-based information system in Nile river management is one of the most valuab1e tools that keep step with the development of Decision support systems.
Journal of Hydroinformatics, 2022
Wider adoption of machine learning methods in water resources has the potential to greatly accele... more Wider adoption of machine learning methods in water resources has the potential to greatly accelerate the efficiency and quality of analysis. The Nile River is one of the major fluvial hydro-systems in the world. Fluvial islands are present in nearly all natural and regulated rivers. The Nile River is characterized by numerous natural phenomena and human interventions represented in multiple islands characteristics. This paper investigates the formation and development of the Nile River islands in the fourth reach, which extends between Assuit and Delta barrages. A machine learning (ML) technique, with the Random Forest (RF) algorithm, has been introduced as a potential technique to replace the traditional ones, to extract and classify the land cover types and the geometrical characteristics of the Nile River islands. The assessment of the results of extracting the Nile River islands and the land cover types are included. The accuracy of the extracted boundaries of the islands is as...
International Journal of Engineering and Advanced Technology, 2022
Egypt is one of the countries that will face significant challenges in the coming years, especial... more Egypt is one of the countries that will face significant challenges in the coming years, especially with dam projects, climate changes, and sea-level rise. These challenges may lead to water shortage or lead to excess inflow water according to the operation rules for these dams. As a result, many considerations must be made in order to face these challenges. One of them, which is the focus of this research, is studying the impact of the extra discharge that can be released downstream of the High Aswan Dam to manage disaster considering the dam operation restrictions. Two-dimensional mathematical model (Delft3D) is used to predict the water surface profile associated with high discharge, which is about 350 m.m3/day under different scenarios of Barrage operation rules in the study area. The Great Cairo Region, where significant projects such as tourism, water, and power plants have been chosen to carry out this study, is the most critical and active area. For each scenario, the predic...
International Journal of Advanced Computer Science and Applications, 2021
Fiber optics cables present various benefits over regular cables when used as a data transportati... more Fiber optics cables present various benefits over regular cables when used as a data transportation medium in today's communication networks. It is noted that there are significant challenges in the connectivity of inner cities that are located far inland away from the coastal areas. Most of the networks developed in Africa, especially in Egypt, are connected via submarine cables flowing across coastal areas. Very few connections are constructed to connect inner cities by crossing the Nile. The Nile River is characterized by a wide area, offering a natural path for underwater cables' laying areas. In this study, the analysis and evaluation of the laying of these cables along the bed of the Nile River in Egypt, rather than crossing it, is investigated. There are many issues with laying fiber optic cables across the Nile River. Some of these are the requirement of using more than one node over fiber optic cable for each. When the number of nodes increases, the cost of installation and drilling effort increases with each node. The fiber optic cable path along the Nile River is simulated with a numerical model (Delft-3D). Two different scenarios for laying cables were applied and analyzed to evaluate the effect of the predicted water surface and sediment profiles on the fiber optic cable path. Based on the results obtained, the fiber-optic network infrastructure is proposed to solve connectivity problems by laying fiber optic cables along the Nile River.
(IJACSA) International Journal of Advanced Computer Science and Applications, 2021
Fiber optics cables present various benefits over regular cables when used as a data transportati... more Fiber optics cables present various benefits over regular cables when used as a data transportation medium in today's communication networks. It is noted that there are significant challenges in the connectivity of inner cities that are located far inland away from the coastal areas. Most of the networks developed in Africa, especially in Egypt, are connected via submarine cables flowing across coastal areas. Very few connections are constructed to connect inner cities by crossing the Nile. The Nile River is characterized by a wide area, offering a natural path for underwater cables' laying areas. In this study, the analysis and evaluation of the laying of these cables along the bed of the Nile River in Egypt, rather than crossing it, is investigated. There are many issues with laying fiber optic cables across the Nile River. Some of these are the requirement of using more than one node over fiber optic cable for each. When the number of nodes increases, the cost of installation and drilling effort increases with each node. The fiber optic cable path along the Nile River is simulated with a numerical model (Delft-3D). Two different scenarios for laying cables were applied and analyzed to evaluate the effect of the predicted water surface and sediment profiles on the fiber optic cable path. Based on the results obtained, the fiber-optic network infrastructure is proposed to solve connectivity problems by laying fiber optic cables along the Nile River.
International Journal of Engineering and Advanced Technology (IJEAT), 2022
Egypt is one of the countries that will face significant challenges in the coming years, especial... more Egypt is one of the countries that will face significant challenges in the coming years, especially with dam projects, climate changes, and sea-level rise. These challenges may lead to water shortage or lead to excess inflow water according to the operation rules for these dams. As a result, many considerations must be made in order to face these challenges. One of them, which is the focus of this research, is studying the impact of the extra discharge that can be released downstream of the High Aswan Dam to manage disaster considering the dam operation restrictions. Two-dimensional mathematical model (Delft3D) is used to predict the water surface profile associated with high discharge, which is about 350 m.m3/day under different scenarios of Barrage operation rules in the study area. The Great Cairo Region, where significant projects such as tourism, water, and power plants have been chosen to carry out this study, is the most critical and active area. For each scenario, the predicted water level and its impact on human properties and habitations is analyzed. In addition, many other side effects on the river behavior, such as aggradations, degradation, bank erosion and inundation are evaluated. An application was developed using the Python programming language and GIS to store predicted water levels and assess the database for the river's vulnerable facilities. Finally, the study will propose a strategy for managing and mitigating flood hazards.
Journal of Hydroinformatics, 2022
Wider adoption of machine learning methods in water resources has the potential to greatly accele... more Wider adoption of machine learning methods in water resources has the potential to greatly accelerate the efficiency and quality of analysis. The Nile River is one of the major fluvial hydro-systems in the world. Fluvial islands are present in nearly all natural and regulated rivers. The Nile River is characterized by numerous natural phenomena and human interventions represented in multiple islands characteristics. This paper investigates the formation and development of the Nile River islands in the fourth reach, which extends between Assuit and Delta barrages. A machine learning (ML) technique, with the Random Forest (RF) algorithm, has been introduced as a potential technique to replace the traditional ones, to extract and classify the land cover types and the geometrical characteristics of the Nile River islands. The assessment of the results of extracting the Nile River islands and the land cover types are included. The accuracy of the extracted boundaries of the islands is assessed using field surveying data. The classification of the islands based on the islands' geometric characteristics represented that 70% of the extracted islands are classified as Wide Island, 20% are classified as Equal Island, and 10% as Narrow Island. The islands' classification, based on the land cover, results show that there is only 5% of the islands that are urban areas, 5% of the islands are mixed class (both vegetation and urban), and the rest of the islands 90% have a vegetation land cover type. The accuracy assessment was performed using the error matrix, the results show that the overall accuracy of the land cover classification is greater than 84%. The proposed islands' classification scheme can become an important tool that provides the decision-makers with more detailed information to improve the planning of the Nile River islands development projects. Furthermore, this schema can be expanded to other climatic and topographic regions.
JES. Journal of Engineering Sciences, 2019
The Egyptian Journal of Remote Sensing and Space Science
This paper investigates the potential of using the Sentinel-2 images for deriving bathymetric map... more This paper investigates the potential of using the Sentinel-2 images for deriving bathymetric maps for the Nile River in Egypt. Regression analysis technique with the aid of in situ measurements were used. Exploring the effects of the size of calibration data, and water depth is another aim of this paper. Linear and machine learning regression techniques (Fine Decision Tree (FDT), and Random Forest (RF) Algorithms) are investigated. The study area is about 23 km between Assiut and Delta barrages. Around 82,000 depth points, are available. Regression models are developed using the depth data and the corresponding digital values of the 13 Sentinel-2 imagery bands. The linear regression model was not applicable (R 2 = 0.02). The FDT, and RF models, have (R 2 = 0.86) when half of the depth points were used for calibration, and the RMSE of the testing data (the other half of the depth points) equaled to 2.86 and 2.09 m, respectively. When fewer points were used for calibration, the R 2 = 0.83 and 0.84, and RMSE = 2.65 and 2.19 m, for FDT and RF, respectively. When only the shallow water areas were considered, the RMSE reached 1.51 and 1.30 m for the FDT and RF, respectively. The VNIR bans of Sentinel-2 images are not enough to estimate the water depth of the Nile river. Collecting in situ measurements for small areas, is adequate for estimating the water depth and produces bathymetry maps for the Nile River in Egypt, and larger in situ measurements are not required.
Ain Shams Engineering Journal
The world's population explosion and water scarcity has researchers looking for smart inn... more The world's population explosion and water scarcity has researchers looking for smart innovations to provide food for the world and save water. In recent years, smart technologies have received much attention in the areas of irrigation and agriculture research. The main objective of this paper is to design and implement of new smart hydroponic and aeroponic greenhouse system based on Internet of Things (IoT) technology for research studies in National Water Research Center. The greenhouse is connected to many various tools for controlling the weather conditions automatically inside the greenhouse consistent with the plant type and season. The indoor environment is equipped with a set of IoT sensors to measure various parameters such as temperature; Humidity, luminous intensity, and total dissolved solids. The pesticide spraying tank is also used to overcome pests within the greenhouse. The IoT platform was used to automate and store system parameters, as well as provide graphical interface remote access. With minimal user input, the constructed system can preserve healthy plant growing parameters. The current study evaluates the environmental and technical impacts of the developed smart system on the cultivation of Batavia lettuce with high economic value. It can conclude that improving water and energy use efficiency (saving them to about 80%), in addition to doubling productivity per area and reducing the time yield to reach 45 days comparing 75 days with the traditional agriculture whatever the fertility of the soil. Moreover, save labor in agriculture, and reducing fertilizer and pesticide use. The resulted of Total Dissolved Solids (TDS), Relative Humidity (RH), and Temperature (T) was analyzed and evaluated during the cultivation period with and without the developed smart system.
Potential of Using Machine Learning Regression Techniques to Utilize Sentinel Images for Bathymetry Mapping of Nile River, 2023
This paper investigates the potential of using the Sentinel-2 images for deriving bathymetric map... more This paper investigates the potential of using the Sentinel-2 images for deriving bathymetric maps for the Nile River in Egypt. Regression analysis technique with the aid of in situ measurements were used. Exploring the effects of the size of calibration data, and water depth is another aim of this paper. Linear and machine learning regression techniques (Fine Decision Tree (FDT), and Random Forest (RF) Algorithms) are investigated. The study area is about 23 km between Assiut and Delta barrages. Around 82,000 depth points, are available. Regression models are developed using the depth data and the corresponding digital values of the 13 Sentinel-2 imagery bands. The linear regression model was not applicable (R 2 = 0.02). The FDT, and RF models, have (R 2 = 0.86) when half of the depth points were used for calibration, and the RMSE of the testing data (the other half of the depth points) equaled to 2.86 and 2.09 m, respectively. When fewer points were used for calibration, the R 2 = 0.83 and 0.84, and RMSE = 2.65 and 2.19 m, for FDT and RF, respectively. When only the shallow water areas were considered, the RMSE reached 1.51 and 1.30 m for the FDT and RF, respectively. The VNIR bans of Sentinel-2 images are not enough to estimate the water depth of the Nile river. Collecting in situ measurements for small areas, is adequate for estimating the water depth and produces bathymetry maps for the Nile River in Egypt, and larger in situ measurements are not required.
Internet of Things based smart automated indoor hydroponics and aeroponics greenhouse in Egypt, 2023
The world's population explosion and water scarcity has researchers looking for smart innovations... more The world's population explosion and water scarcity has researchers looking for smart innovations to provide food for the world and save water. In recent years, smart technologies have received much attention in the areas of irrigation and agriculture research. The main objective of this paper is to design and implement of new smart hydroponic and aeroponic greenhouse system based on Internet of Things (IoT) technology for research studies in National Water Research Center. The greenhouse is connected to many various tools for controlling the weather conditions automatically inside the greenhouse consistent with the plant type and season. The indoor environment is equipped with a set of IoT sensors to measure various parameters such as temperature; Humidity, luminous intensity, and total dissolved solids. The pesticide spraying tank is also used to overcome pests within the greenhouse. The IoT platform was used to automate and store system parameters, as well as provide graphical interface remote access. With minimal user input, the constructed system can preserve healthy plant growing parameters. The current study evaluates the environmental and technical impacts of the developed smart system on the cultivation of Batavia lettuce with high economic value. It can conclude that improving water and energy use efficiency (saving them to about 80%), in addition to doubling productivity per area and reducing the time yield to reach 45 days comparing 75 days with the traditional agriculture whatever the fertility of the soil. Moreover, save labor in agriculture, and reducing fertilizer and pesticide use. The resulted of Total Dissolved Solids (TDS), Relative Humidity (RH), and Temperature (T) was analyzed and evaluated during the cultivation period with and without the developed smart system.
The Nile River is an essential resource to maintain environmental balance in Egypt, it supplies d... more The Nile River is an essential resource to maintain environmental balance in Egypt, it supplies drinking water, low cost transportation, irrigation, hydropower, and provide livelihoods. The conjunction between river human interventions and morphological changes impacts show real challenges to the government and researchers. The design of information system to observe these impacts is necessary and required for Nile River sustainable development, management, and planning. This paper introduces the potential of GIS in developing a comprehensive Nile River information system (NRIS). This system is the key factor to facilitate and attain efficient decision making to the responsible of water management organizations. Scripts using python language is developed enabling the decision maker to access, edit, search, analyze and manipulate the available database. In addition, proposes that the designed GIS based information system can substitute the traditiona1 methods for extracting accurate information from database and can be updated in easily. Using the developed GIS-based information system in Nile river management is one of the most valuab1e tools that keep step with the development of Decision support systems.
Journal of Hydroinformatics, 2022
Wider adoption of machine learning methods in water resources has the potential to greatly accele... more Wider adoption of machine learning methods in water resources has the potential to greatly accelerate the efficiency and quality of analysis. The Nile River is one of the major fluvial hydro-systems in the world. Fluvial islands are present in nearly all natural and regulated rivers. The Nile River is characterized by numerous natural phenomena and human interventions represented in multiple islands characteristics. This paper investigates the formation and development of the Nile River islands in the fourth reach, which extends between Assuit and Delta barrages. A machine learning (ML) technique, with the Random Forest (RF) algorithm, has been introduced as a potential technique to replace the traditional ones, to extract and classify the land cover types and the geometrical characteristics of the Nile River islands. The assessment of the results of extracting the Nile River islands and the land cover types are included. The accuracy of the extracted boundaries of the islands is as...
International Journal of Engineering and Advanced Technology, 2022
Egypt is one of the countries that will face significant challenges in the coming years, especial... more Egypt is one of the countries that will face significant challenges in the coming years, especially with dam projects, climate changes, and sea-level rise. These challenges may lead to water shortage or lead to excess inflow water according to the operation rules for these dams. As a result, many considerations must be made in order to face these challenges. One of them, which is the focus of this research, is studying the impact of the extra discharge that can be released downstream of the High Aswan Dam to manage disaster considering the dam operation restrictions. Two-dimensional mathematical model (Delft3D) is used to predict the water surface profile associated with high discharge, which is about 350 m.m3/day under different scenarios of Barrage operation rules in the study area. The Great Cairo Region, where significant projects such as tourism, water, and power plants have been chosen to carry out this study, is the most critical and active area. For each scenario, the predic...
International Journal of Advanced Computer Science and Applications, 2021
Fiber optics cables present various benefits over regular cables when used as a data transportati... more Fiber optics cables present various benefits over regular cables when used as a data transportation medium in today's communication networks. It is noted that there are significant challenges in the connectivity of inner cities that are located far inland away from the coastal areas. Most of the networks developed in Africa, especially in Egypt, are connected via submarine cables flowing across coastal areas. Very few connections are constructed to connect inner cities by crossing the Nile. The Nile River is characterized by a wide area, offering a natural path for underwater cables' laying areas. In this study, the analysis and evaluation of the laying of these cables along the bed of the Nile River in Egypt, rather than crossing it, is investigated. There are many issues with laying fiber optic cables across the Nile River. Some of these are the requirement of using more than one node over fiber optic cable for each. When the number of nodes increases, the cost of installation and drilling effort increases with each node. The fiber optic cable path along the Nile River is simulated with a numerical model (Delft-3D). Two different scenarios for laying cables were applied and analyzed to evaluate the effect of the predicted water surface and sediment profiles on the fiber optic cable path. Based on the results obtained, the fiber-optic network infrastructure is proposed to solve connectivity problems by laying fiber optic cables along the Nile River.
(IJACSA) International Journal of Advanced Computer Science and Applications, 2021
Fiber optics cables present various benefits over regular cables when used as a data transportati... more Fiber optics cables present various benefits over regular cables when used as a data transportation medium in today's communication networks. It is noted that there are significant challenges in the connectivity of inner cities that are located far inland away from the coastal areas. Most of the networks developed in Africa, especially in Egypt, are connected via submarine cables flowing across coastal areas. Very few connections are constructed to connect inner cities by crossing the Nile. The Nile River is characterized by a wide area, offering a natural path for underwater cables' laying areas. In this study, the analysis and evaluation of the laying of these cables along the bed of the Nile River in Egypt, rather than crossing it, is investigated. There are many issues with laying fiber optic cables across the Nile River. Some of these are the requirement of using more than one node over fiber optic cable for each. When the number of nodes increases, the cost of installation and drilling effort increases with each node. The fiber optic cable path along the Nile River is simulated with a numerical model (Delft-3D). Two different scenarios for laying cables were applied and analyzed to evaluate the effect of the predicted water surface and sediment profiles on the fiber optic cable path. Based on the results obtained, the fiber-optic network infrastructure is proposed to solve connectivity problems by laying fiber optic cables along the Nile River.
International Journal of Engineering and Advanced Technology (IJEAT), 2022
Egypt is one of the countries that will face significant challenges in the coming years, especial... more Egypt is one of the countries that will face significant challenges in the coming years, especially with dam projects, climate changes, and sea-level rise. These challenges may lead to water shortage or lead to excess inflow water according to the operation rules for these dams. As a result, many considerations must be made in order to face these challenges. One of them, which is the focus of this research, is studying the impact of the extra discharge that can be released downstream of the High Aswan Dam to manage disaster considering the dam operation restrictions. Two-dimensional mathematical model (Delft3D) is used to predict the water surface profile associated with high discharge, which is about 350 m.m3/day under different scenarios of Barrage operation rules in the study area. The Great Cairo Region, where significant projects such as tourism, water, and power plants have been chosen to carry out this study, is the most critical and active area. For each scenario, the predicted water level and its impact on human properties and habitations is analyzed. In addition, many other side effects on the river behavior, such as aggradations, degradation, bank erosion and inundation are evaluated. An application was developed using the Python programming language and GIS to store predicted water levels and assess the database for the river's vulnerable facilities. Finally, the study will propose a strategy for managing and mitigating flood hazards.
Journal of Hydroinformatics, 2022
Wider adoption of machine learning methods in water resources has the potential to greatly accele... more Wider adoption of machine learning methods in water resources has the potential to greatly accelerate the efficiency and quality of analysis. The Nile River is one of the major fluvial hydro-systems in the world. Fluvial islands are present in nearly all natural and regulated rivers. The Nile River is characterized by numerous natural phenomena and human interventions represented in multiple islands characteristics. This paper investigates the formation and development of the Nile River islands in the fourth reach, which extends between Assuit and Delta barrages. A machine learning (ML) technique, with the Random Forest (RF) algorithm, has been introduced as a potential technique to replace the traditional ones, to extract and classify the land cover types and the geometrical characteristics of the Nile River islands. The assessment of the results of extracting the Nile River islands and the land cover types are included. The accuracy of the extracted boundaries of the islands is assessed using field surveying data. The classification of the islands based on the islands' geometric characteristics represented that 70% of the extracted islands are classified as Wide Island, 20% are classified as Equal Island, and 10% as Narrow Island. The islands' classification, based on the land cover, results show that there is only 5% of the islands that are urban areas, 5% of the islands are mixed class (both vegetation and urban), and the rest of the islands 90% have a vegetation land cover type. The accuracy assessment was performed using the error matrix, the results show that the overall accuracy of the land cover classification is greater than 84%. The proposed islands' classification scheme can become an important tool that provides the decision-makers with more detailed information to improve the planning of the Nile River islands development projects. Furthermore, this schema can be expanded to other climatic and topographic regions.
JES. Journal of Engineering Sciences, 2019