Modeling of Coastal Processes in the Mediterranean Sea: A Pilot Study on the Entrance of Suez Canal in Egypt

*Mona Fouad Kaiser, Walaa Awaad Ali and Maysara Khairy El Tahan*

## **Abstract**

The main objective of this research is applying numerical modeling to simulate the impact of the Suez Canal jetties on the beach morphology and hydrodynamic regime along the Suez Canal coastal zone. In addition, coastal processes including waves and wave-induced currents will be evaluated using 2D modeling. This research will contribute to quantify the shoreline stability during the last three decades. Hydrodynamic and sediment transport (ST) models are utilized to predict sediment transport pathways and how sediment might move within the entrance of Suez Canal port. Remote sensing analyses of the Landsat Thematic Mapper images during 2000–2018 show siltation processes at the entrance of the Suez Canal. Vector analyses of the images' data indicated updrift accretion at a rate of +15 m/year and downdrift erosion at a rate of −13 m/year. Coastal processes including waves and currents contribute to shoaling problem along the navigation channel of the Suez Canal port. Applications of 2-3D models were used to simulate wave and current dissipation. In addition, beach slope profiles and hydrodynamic models are used to help in understanding the impact of coastal processes on beach morphology and hydrodynamic regime controlling siltation problem along the entrance of Port Said harbor.

**Keywords:** 2D modeling, Mediterranean Sea, coastal processes, Suez Canal port, hydrodynamic regime, beach morphology

## **1. Introduction**

The Suez Canal is located in Egypt west of the Sinai Peninsula. Its construction was preceded by cutting a small freshwater canal from the Nile Delta and connecting it with a southern branch to Suez and a northern branch to Port Said. The Suez Canal is considered to be the first artificial canal to be used in Travel and Trade. It is completed to create the first saltwater passage between Port Said on the Mediterranean and Port of Suez on the Red Sea, providing an essentially direct route for transport of goods and petroleum tankers between Europe and Asia. The construction of Suez Canal, nearly from 40 centuries, by the pharaohs, aims at to do linking between the Red Sea and Mediterranean Sea. In addition, Suez Canal Authority is responsible to

do periodical dredging for the navigation channel and its surroundings to keep this channel deep and safe. The canal supports approximately 8% of the world's shipping traffic with almost 50 vessels traveling through the canal daily. It has 195 km length; its width ranges from 60 to 300 m. It is able to accommodate ships as large as 150,000 tons fully loaded (Suez Canal Authority personal communication). This study aims to understand the main factors controlling siltation problem in the entrance of the Suez Canal port. Numerical modeling will be used to simulate coastal processes, beach profiles, and hydrodynamic regime. The results help in shoaling mitigation and facilitating passing of high loading ships along the canal.

As the important geographical location of Port Said Governorate, it has many activities in national and regional development. In addition, it is considered as the Gulf of Suez extension. Consequently, it has valuable resources such as the Mediterranean Sea, the Red Sea beaches, lakes, protected areas, and historical and archeological areas. These resources are suitable for tourism development. Therefore, Port Said has quickly become the third largest urban governorate in Egypt with respect to population.

## **2. Study site description**

The Suez Canal coastal zone lies between longitudes 32°13′ and 32°25′ E and between latitudes 31°10′ and 31°20′ N (**Figure 1**). The concerned site represents a part of the Egyptian Mediterranean coast lying to the north of the Nile Delta east of Port Said. The beach profile slope has 1 m/km, and the depth of seabed reaches 25 m at the northern boundary of the study site. The beach sediment, along the coastal zone, is mainly composed of sand; its limit reaches 5 m in depth [1]. Although going to the sea bed offshore, the sediment texture that is covering the seabed was changed from muddy sand in the area limit between 5 and 10 m to muddy in deeper zone. Abu Asi [2] concluded that the coastal zone of Sinai from Port Said to El Arish is under extensive development. Consequently, several integrated development projects are being implemented along the coastal zone of North Sinai including the El-Tina plain [3]. The area is identified as it is completely covered by quaternary sediments of littoral, alluvial, and eolian origin, which show variations in their texture and composition ranging from unconsolidated sands to salinized silt and clay of chemical and biochemical origins. They also described the area as it has a concave shoreline configuration that is about 39 km long and 818 km2 in area. The plain is subsiding at a rate of about

**93**

*Modeling of Coastal Processes in the Mediterranean Sea: A Pilot Study on the Entrance…*

0.5 cm/year. The only engineering structures built at the study area are the 7.7 and 2.0 km jetties constructed to protect the inlet at Port Said and the East Port Said harbors, respectively. Additionally, the thickness of Holocene strata beneath the modern delta plain is a direct function of subsidence, which ranges from 50 m at Port Said and tends to decrease or be nearly absent westward below the Alexandria coastal plain. The principal transporting agents in the concerned site are waves and waveinduced longshore current [4]. The wave rose was constructed based on records measured between 1997 and 1999 off the Damietta Harbor using a pressure wave gauge (InterOcean System S4DW) installed at ~12 m water depth [5]. The average significant wave height ranges from 1.04 to 4.45 m with long duration, its direction is mainly coming from NW in winter. These waves are responsible for generating the longshore currents and transporting sediment toward the east. However, the N-E waves having short duration are responsible for generating a reverse longshore

The eroded sediment of Damietta promontory was blocked west of Port Said causing accretion of +15 m/year along the western jetty of the El-Gamil inlet. Growth of tombolos occurred behind detached breakwaters at a rate of +6 m/year. The resulting break in longshore drift caused erosion of −6 m/year downdrift of the breakwaters. The eastern side of the Suez Canal, Bur Fouad, is suffering from erosion at a rate of −18 m/year. The coastline of El-Bardawil Lake is experiencing accretion of +6 m/year in some sections and erosion of −9 m/year in others [7]. The basins inside the Port Said harbor have a depth ranging from 8 to 24 m water; it is subjected to a severe sand drift. Suez Canal Authority usually keeps it clear by dredging. Maintenance dredging is simply the removal of sediments from a body of water that have accumulated due to erosion in order to maintain a desired depth, as in a navigation channel. Suez Canal navigation channel is authorized to be maintained to certain depths depending on its use, by periodic dredging of the silt, sand, and clay that are deposited in it [8]. In order to evaluate the impact of engineering protection on the coastal processes including waves and currents and beach profile configuration, numerical modeling techniques are utilized to predict the patterns of shoreline changes due to

Shoreline positions were obtained from the TM band-7 images using a regionbased segmentation process in which the sea area was extracted as a region [9]. Region growing techniques are generally better in noisy images, where borders are extremely difficult to delineate. Homogeneity is an important character of regions and is used as the main segmentation criterion in region growing. Thematic Mapper band 7 (short-wave infrared) was used for the image segmentation procedure to produce a vector map of the shoreline, so that the land-sea boundary could be delineated. Shorter wavelengths can pass through shallow water, making accurate delineation of the coastline difficult [10]. Using short-wave infrared data ameliorates the highreflectance problems caused by surf in the breaker zone [11]. A line representing shoreline position (the boundary between sea and land) was created along the Suez Canal coastal zone. The output data were saved as a vector file enabling analysis of coastline change using geographic information system (GIS) software [12]. Shoreline displacements during the 2000–2018 period were extracted from the images using the measurement tools in ERDAS IMAGINE VirtualGIS. Edge detection and segmentation seem to be the most suitable approach to produce vector map data for the

*DOI: http://dx.doi.org/10.5772/intechopen.88509*

current toward the west [6].

the changes in wave conditions.

**3.1 Change detection**

**3. Remote sensing techniques and results**

**Figure 1.** *Suez Canal entrance; protected by eastern and western jetties.*

*Modeling of Coastal Processes in the Mediterranean Sea: A Pilot Study on the Entrance… DOI: http://dx.doi.org/10.5772/intechopen.88509*

0.5 cm/year. The only engineering structures built at the study area are the 7.7 and 2.0 km jetties constructed to protect the inlet at Port Said and the East Port Said harbors, respectively. Additionally, the thickness of Holocene strata beneath the modern delta plain is a direct function of subsidence, which ranges from 50 m at Port Said and tends to decrease or be nearly absent westward below the Alexandria coastal plain.

The principal transporting agents in the concerned site are waves and waveinduced longshore current [4]. The wave rose was constructed based on records measured between 1997 and 1999 off the Damietta Harbor using a pressure wave gauge (InterOcean System S4DW) installed at ~12 m water depth [5]. The average significant wave height ranges from 1.04 to 4.45 m with long duration, its direction is mainly coming from NW in winter. These waves are responsible for generating the longshore currents and transporting sediment toward the east. However, the N-E waves having short duration are responsible for generating a reverse longshore current toward the west [6].

The eroded sediment of Damietta promontory was blocked west of Port Said causing accretion of +15 m/year along the western jetty of the El-Gamil inlet. Growth of tombolos occurred behind detached breakwaters at a rate of +6 m/year. The resulting break in longshore drift caused erosion of −6 m/year downdrift of the breakwaters. The eastern side of the Suez Canal, Bur Fouad, is suffering from erosion at a rate of −18 m/year. The coastline of El-Bardawil Lake is experiencing accretion of +6 m/year in some sections and erosion of −9 m/year in others [7]. The basins inside the Port Said harbor have a depth ranging from 8 to 24 m water; it is subjected to a severe sand drift. Suez Canal Authority usually keeps it clear by dredging. Maintenance dredging is simply the removal of sediments from a body of water that have accumulated due to erosion in order to maintain a desired depth, as in a navigation channel. Suez Canal navigation channel is authorized to be maintained to certain depths depending on its use, by periodic dredging of the silt, sand, and clay that are deposited in it [8].

In order to evaluate the impact of engineering protection on the coastal processes including waves and currents and beach profile configuration, numerical modeling techniques are utilized to predict the patterns of shoreline changes due to the changes in wave conditions.

### **3. Remote sensing techniques and results**

#### **3.1 Change detection**

*Coastal and Marine Environments - Physical Processes and Numerical Modelling*

mitigation and facilitating passing of high loading ships along the canal.

**2. Study site description**

that is about 39 km long and 818 km2

*Suez Canal entrance; protected by eastern and western jetties.*

do periodical dredging for the navigation channel and its surroundings to keep this channel deep and safe. The canal supports approximately 8% of the world's shipping traffic with almost 50 vessels traveling through the canal daily. It has 195 km length; its width ranges from 60 to 300 m. It is able to accommodate ships as large as 150,000 tons fully loaded (Suez Canal Authority personal communication). This study aims to understand the main factors controlling siltation problem in the entrance of the Suez Canal port. Numerical modeling will be used to simulate coastal processes, beach profiles, and hydrodynamic regime. The results help in shoaling

As the important geographical location of Port Said Governorate, it has many activities in national and regional development. In addition, it is considered as the Gulf of Suez extension. Consequently, it has valuable resources such as the Mediterranean Sea, the Red Sea beaches, lakes, protected areas, and historical and archeological areas. These resources are suitable for tourism development. Therefore, Port Said has quickly become the third largest urban governorate in Egypt with respect to population.

The Suez Canal coastal zone lies between longitudes 32°13′ and 32°25′ E and between latitudes 31°10′ and 31°20′ N (**Figure 1**). The concerned site represents a part of the Egyptian Mediterranean coast lying to the north of the Nile Delta east of Port Said. The beach profile slope has 1 m/km, and the depth of seabed reaches 25 m at the northern boundary of the study site. The beach sediment, along the coastal zone, is mainly composed of sand; its limit reaches 5 m in depth [1]. Although going to the sea bed offshore, the sediment texture that is covering the seabed was changed from muddy sand in the area limit between 5 and 10 m to muddy in deeper zone. Abu Asi [2] concluded that the coastal zone of Sinai from Port Said to El Arish is under extensive development. Consequently, several integrated development projects are being implemented along the coastal zone of North Sinai including the El-Tina plain [3]. The area is identified as it is completely covered by quaternary sediments of littoral, alluvial, and eolian origin, which show variations in their texture and composition ranging from unconsolidated sands to salinized silt and clay of chemical and biochemical origins. They also described the area as it has a concave shoreline configuration

in area. The plain is subsiding at a rate of about

**92**

**Figure 1.**

Shoreline positions were obtained from the TM band-7 images using a regionbased segmentation process in which the sea area was extracted as a region [9]. Region growing techniques are generally better in noisy images, where borders are extremely difficult to delineate. Homogeneity is an important character of regions and is used as the main segmentation criterion in region growing. Thematic Mapper band 7 (short-wave infrared) was used for the image segmentation procedure to produce a vector map of the shoreline, so that the land-sea boundary could be delineated. Shorter wavelengths can pass through shallow water, making accurate delineation of the coastline difficult [10]. Using short-wave infrared data ameliorates the highreflectance problems caused by surf in the breaker zone [11]. A line representing shoreline position (the boundary between sea and land) was created along the Suez Canal coastal zone. The output data were saved as a vector file enabling analysis of coastline change using geographic information system (GIS) software [12]. Shoreline displacements during the 2000–2018 period were extracted from the images using the measurement tools in ERDAS IMAGINE VirtualGIS. Edge detection and segmentation seem to be the most suitable approach to produce vector map data for the

study site. The results indicate updrift accretion at a rate of +15 m/year and downdrift erosion at a rate of −13 m/year along the entrance of the Suez Canal port (**Figure 2**).

### **3.2 Image classification**

Unsupervised classification was carried out on the three data sets of the images separately using a histogram peak cluster technique to identify dense areas or frequently occurring pixels [13–15]. Generally, multispectral classification consists of a compression of all information in a multispectral data set into a single image that depicts the major types of surfaces in different colors [16]. Maximum likelihood of supervised classification was applied to detect land cover classes. Once

**95**

**Figure 3.**

*Modeling of Coastal Processes in the Mediterranean Sea: A Pilot Study on the Entrance…*

a sufficient number of such spectral subclasses were acquired for all information classes, a maximum likelihood classification was performed with the full set of refined spectral classes [17]. Image classification of the Enhanced Landsat Thematic Mapper displays an increase in siltation problem along the entrance of the Suez

*Image classification during 2000–2018; green color showing siltation along the study site coastal zone.*

The data input for Mike 21-2D modeling, which is the key parameter to run spectral wave (SW) model, the flow model of hydrodynamics (HD), and flow model of sediment transport (ST), includes bathymetry, tide, wind, waves, sediment grain

Canal port during 2000–2018 (**Figure 3**).

**4. Required data for modeling**

*DOI: http://dx.doi.org/10.5772/intechopen.88509*

*Modeling of Coastal Processes in the Mediterranean Sea: A Pilot Study on the Entrance… DOI: http://dx.doi.org/10.5772/intechopen.88509*

a sufficient number of such spectral subclasses were acquired for all information classes, a maximum likelihood classification was performed with the full set of refined spectral classes [17]. Image classification of the Enhanced Landsat Thematic Mapper displays an increase in siltation problem along the entrance of the Suez Canal port during 2000–2018 (**Figure 3**).

## **4. Required data for modeling**

The data input for Mike 21-2D modeling, which is the key parameter to run spectral wave (SW) model, the flow model of hydrodynamics (HD), and flow model of sediment transport (ST), includes bathymetry, tide, wind, waves, sediment grain

*Coastal and Marine Environments - Physical Processes and Numerical Modelling*

**3.2 Image classification**

study site. The results indicate updrift accretion at a rate of +15 m/year and downdrift erosion at a rate of −13 m/year along the entrance of the Suez Canal port (**Figure 2**).

Unsupervised classification was carried out on the three data sets of the images

separately using a histogram peak cluster technique to identify dense areas or frequently occurring pixels [13–15]. Generally, multispectral classification consists of a compression of all information in a multispectral data set into a single image that depicts the major types of surfaces in different colors [16]. Maximum likelihood of supervised classification was applied to detect land cover classes. Once

*(a) Patterns of shoreline changes during 2000–2018 and (b) areas of loss and gain along El-Tina plain.*

**94**

**Figure 2.**

size, and shoreline position. Simulation of shoreline changes, waves, sediment transport, and hydrodynamic regime, using the Mike 21 HD (Flow Model and Hydrodynamic Module), needs some data sets, which are not changed during all simulation analyses. The required data are (4.1) extracted shoreline positions, (4.2) offshore wave parameters, (4.3) bathymetric survey, and (4.4) sediment grain size.

## **4.1 Extracted shoreline positions**

The shoreline positions provided for modeling were extracted from remote sensing results using Thematic Mapper image technique. Wave characteristics required for modeling are wave height, period, and direction. Wave data were measured at Ras El-Bar station. Waves were recorded using a Cassette Acquisition System (CAS); the wave gauge was installed about 1200 m away from the western side of the navigation channel of the Damietta harbor, at water depth of 12 m. The recorder measured the wave characteristics for 20 min each 4 h during a day [18]. Data provided from the Coastal Research Institute in Alexandria have been analyzed in order to determine wave height, period, and direction. These data represent the wave parameters in year 1986 for eastern Nile Delta coast. Bathymetric data were supplied from the Suez Canal Authority. It shows parallel offshore contours to the shoreline trend from 0 to 20 m depth within the nearshore zone.

Satellite images are the main source of data for shoreline positions in this study. Data acquired include SPOT-4 images for year 2006, ETM+ Landsat 7 images during 2000–2012, EgyptSat images for year 2010, and Landsat 8 images for years 2013, 2014, and 2018.

#### **4.2 Offshore wave parameters**

Tidal data along the Egyptian Mediterranean coast do not exceed 44–50 cm range. Consequently, tide has insignificant role as input data for MIKE 21 modeling. One-year measurements (1990–2000) of wind and wave series data used in this study were measured in Port Said. The strongest wind series are coming from SSW to WSW direction and blowing from land; therefore, it did not create any waves approaching the shoreline. However, it transported beach sand toward offshore. The velocity of this series is 13.8 m/s. This speed is not strong enough to generate storm (wind speed 18 between 24.5 and 32.6 m/s). The main input wave parameters for the hydraulic computations in LITDRIFT and LITLINE are wave height, wave angle, and wave period. Longshore currents crossing beach profiles are generated using these programs due to shoaling and refraction of the incident waves. Wave data were supplied from many sources such as Suez Canal Authority and Delft Hydraulics. For year 2003, it was measured in Damietta promontory, while wave data for years 1986, 1987, and 1990 were measured in Rosetta promontory. Finally, during 2009–2013, it was measured in Alexandria.

#### **4.3 Bathymetric survey**

The bathymetric data used in this study were supplied from the Egyptian Military Survey as hard copy maps. Bathymetric data for year 2004 was used in Port Said and Suez Canal areas. This data was scanned by AutoCAD 2014 software to be digitized and processed using civil 3D software to get (x, y, z) format and work with Mike 21 Flow Model*.* Mesh file map was generated from the x, y, z digital file using MIKE 21 to understand hydrodynamics regime and sediment transport.

**97**

*Modeling of Coastal Processes in the Mediterranean Sea: A Pilot Study on the Entrance…*

The sediment properties should be defined for each grid point in the crossshore profile. The average grain size diameter at one of the concerned site, Port Said, is 0.14–1.21 mm (fine sand), and the closure depth is at a range of 2–4 m, and berm height varies from 0.5 to 1 m [18]. The changes in this range produce slight response in shoreline changes (which calculated by Genesis 1D modeling) [19]. When the median grain size decreased from 0.40 to 0.14 mm, there was no change in the shoreline position. The LITPACK module calculates the sediment transport capacity (i.e., it assumes that there is an unlimited source of sediment

Coastal zones are one of the most important areas for human activities and infrastructure growth. However, the systems in these areas are dynamic and need to be studied extensively before planning infrastructure to avoid damages. Numerical modeling is considered as important tool to evaluate coastal zone systems and predict its environmental characteristics. Quantitative prediction of coastal processes and coastal evolution via numerical modeling is now possible due to the major advances that have been made in understanding physical processes and mathematical modeling techniques. The problem of Nile Delta localities is the intensive erosion following construction of some engineering protection and transporting of these materials from beach face by waves and longshore currents. Consequently, the application of modeling is very important to understand hydrodynamic regime and coastal processes controlling coastal erosion and accretion at the concerned sites. In addition, the impact of construction of some engineering protections on the coastal morphodynamic during 2000–2015 will be evaluated. MIKE 21 by Danish Hydraulic Institute (DHI) software is such an integrated complete coastal modeling suite, commercially marketed by Danish Hydraulic Institute, which delivers superior technology, expert support, and outstanding value based on 40 years of experience. The DHI group helped us in this study by giving a permission to use the original package of MIKE 21 with a limited license. Certain modules were selected from MIKE 21 to achieve the objectives of this study; they are (1) MIKE 21 SW, (2) MIKE

Wave characteristics required for modeling are wave height, period, and direction. Wave data were measured at Ras El-Bar station for the eastern part of the Mediterranean coastal zone. The station was put nearly 1200 m away from the western side of the navigation channel of the Damietta harbor, at water depth of 12 m [7, 19]. The recorder measured the wave characteristics for 20 min each 4 h during a day. Data provided from the Coastal Research Institute in Alexandria have been analyzed in order to determine wave height, period, and direction. These data

In order to simulate the growth, transformation of wind-generated waves, and swell in offshore in coastal zones, MIKE 21 spectral analysis module (SW) has been used to get two-dimensional wave heights for the study area according to wave bottom interactions and wave structure interactions (shoaling, refraction, diffraction,

represent the wave parameters in year 1992 for eastern Nile Delta coast.

reflection, bottom friction, and wave breaking) [20] (**Figure 4**).

*DOI: http://dx.doi.org/10.5772/intechopen.88509*

**5. Results of modeling techniques**

21 HD, and (3) MIKE 21 sand transport (ST).

**5.1 MIKE 21 spectral wave**

**4.4 Sediment grain size**

supply) [20].

*Modeling of Coastal Processes in the Mediterranean Sea: A Pilot Study on the Entrance… DOI: http://dx.doi.org/10.5772/intechopen.88509*

### **4.4 Sediment grain size**

*Coastal and Marine Environments - Physical Processes and Numerical Modelling*

shoreline trend from 0 to 20 m depth within the nearshore zone.

**4.1 Extracted shoreline positions**

2014, and 2018.

sured in Alexandria.

**4.3 Bathymetric survey**

**4.2 Offshore wave parameters**

size, and shoreline position. Simulation of shoreline changes, waves, sediment transport, and hydrodynamic regime, using the Mike 21 HD (Flow Model and Hydrodynamic Module), needs some data sets, which are not changed during all simulation analyses. The required data are (4.1) extracted shoreline positions, (4.2) offshore wave parameters, (4.3) bathymetric survey, and (4.4) sediment grain size.

The shoreline positions provided for modeling were extracted from remote sensing results using Thematic Mapper image technique. Wave characteristics required for modeling are wave height, period, and direction. Wave data were measured at Ras El-Bar station. Waves were recorded using a Cassette Acquisition System (CAS); the wave gauge was installed about 1200 m away from the western side of the navigation channel of the Damietta harbor, at water depth of 12 m. The recorder measured the wave characteristics for 20 min each 4 h during a day [18]. Data provided from the Coastal Research Institute in Alexandria have been analyzed in order to determine wave height, period, and direction. These data represent the wave parameters in year 1986 for eastern Nile Delta coast. Bathymetric data were supplied from the Suez Canal Authority. It shows parallel offshore contours to the

Satellite images are the main source of data for shoreline positions in this study. Data acquired include SPOT-4 images for year 2006, ETM+ Landsat 7 images during 2000–2012, EgyptSat images for year 2010, and Landsat 8 images for years 2013,

Tidal data along the Egyptian Mediterranean coast do not exceed 44–50 cm

range. Consequently, tide has insignificant role as input data for MIKE 21 modeling. One-year measurements (1990–2000) of wind and wave series data used in this study were measured in Port Said. The strongest wind series are coming from SSW to WSW direction and blowing from land; therefore, it did not create any waves approaching the shoreline. However, it transported beach sand toward offshore. The velocity of this series is 13.8 m/s. This speed is not strong enough to generate storm (wind speed 18 between 24.5 and 32.6 m/s). The main input wave parameters for the hydraulic computations in LITDRIFT and LITLINE are wave height, wave angle, and wave period. Longshore currents crossing beach profiles are generated using these programs due to shoaling and refraction of the incident waves. Wave data were supplied from many sources such as Suez Canal Authority and Delft Hydraulics. For year 2003, it was measured in Damietta promontory, while wave data for years 1986, 1987, and 1990 were measured in Rosetta promontory. Finally, during 2009–2013, it was mea-

The bathymetric data used in this study were supplied from the Egyptian Military Survey as hard copy maps. Bathymetric data for year 2004 was used in Port Said and Suez Canal areas. This data was scanned by AutoCAD 2014 software to be digitized and processed using civil 3D software to get (x, y, z) format and work with Mike 21 Flow Model*.* Mesh file map was generated from the x, y, z digital file using MIKE 21 to understand hydrodynamics regime and sediment transport.

**96**

The sediment properties should be defined for each grid point in the crossshore profile. The average grain size diameter at one of the concerned site, Port Said, is 0.14–1.21 mm (fine sand), and the closure depth is at a range of 2–4 m, and berm height varies from 0.5 to 1 m [18]. The changes in this range produce slight response in shoreline changes (which calculated by Genesis 1D modeling) [19]. When the median grain size decreased from 0.40 to 0.14 mm, there was no change in the shoreline position. The LITPACK module calculates the sediment transport capacity (i.e., it assumes that there is an unlimited source of sediment supply) [20].

### **5. Results of modeling techniques**

Coastal zones are one of the most important areas for human activities and infrastructure growth. However, the systems in these areas are dynamic and need to be studied extensively before planning infrastructure to avoid damages. Numerical modeling is considered as important tool to evaluate coastal zone systems and predict its environmental characteristics. Quantitative prediction of coastal processes and coastal evolution via numerical modeling is now possible due to the major advances that have been made in understanding physical processes and mathematical modeling techniques. The problem of Nile Delta localities is the intensive erosion following construction of some engineering protection and transporting of these materials from beach face by waves and longshore currents. Consequently, the application of modeling is very important to understand hydrodynamic regime and coastal processes controlling coastal erosion and accretion at the concerned sites. In addition, the impact of construction of some engineering protections on the coastal morphodynamic during 2000–2015 will be evaluated. MIKE 21 by Danish Hydraulic Institute (DHI) software is such an integrated complete coastal modeling suite, commercially marketed by Danish Hydraulic Institute, which delivers superior technology, expert support, and outstanding value based on 40 years of experience. The DHI group helped us in this study by giving a permission to use the original package of MIKE 21 with a limited license. Certain modules were selected from MIKE 21 to achieve the objectives of this study; they are (1) MIKE 21 SW, (2) MIKE 21 HD, and (3) MIKE 21 sand transport (ST).

#### **5.1 MIKE 21 spectral wave**

Wave characteristics required for modeling are wave height, period, and direction. Wave data were measured at Ras El-Bar station for the eastern part of the Mediterranean coastal zone. The station was put nearly 1200 m away from the western side of the navigation channel of the Damietta harbor, at water depth of 12 m [7, 19]. The recorder measured the wave characteristics for 20 min each 4 h during a day. Data provided from the Coastal Research Institute in Alexandria have been analyzed in order to determine wave height, period, and direction. These data represent the wave parameters in year 1992 for eastern Nile Delta coast.

In order to simulate the growth, transformation of wind-generated waves, and swell in offshore in coastal zones, MIKE 21 spectral analysis module (SW) has been used to get two-dimensional wave heights for the study area according to wave bottom interactions and wave structure interactions (shoaling, refraction, diffraction, reflection, bottom friction, and wave breaking) [20] (**Figure 4**).

#### **Figure 4.**

*Simulated spectral wave (SW) model for Suez Canal entrance including (a) spectral waves in NNW direction, (b) spectral waves in NW direction, (c) spectral waves in N direction, and (d) spectral waves in NE direction.*

The model has coarsely triangle mesh at offshore zones and finely triangle mesh at surf zones and study area to get more accurate wave heights with acceptable model run period [21].

MIKE 21 SW includes two different formulations:

1.Directional decoupled parametric formulation

2.Fully spectral formulation [22].

#### **5.2 MIKE 21 hydrodynamics**

MIKE 21 hydrodynamic has modeled to solve currents due to interaction between wave radiation stresses and water level variations with bottom depths and structures at study area in addition to updrift and downdrift zones. The hydrodynamic forces due to wave breaking are the main effective parameters that lead sediments to move [23].

#### **5.3 MIKE 21 sand transport**

This model will be used to predict coastal sand transport and morphodynamics; MIKE 21 sediment transport is designed for the assessment of the sediment transport rates and related initial rates of bed level changes of non-cohesive sediment (sand) due to currents or combined wave-current flow [24]. It is only adapted for non-cohesive sediment (e.g., sand) for which it provides good results. Mathematical shoreline models are tools which are widely used to study the effect of hydrographic parameters on coastal processes and calculate the sediment transport rates and consequently the shoreline changes. The sediment transport process at onshore/ offshore and/or alongshore is very complicated problem because it results from

**99**

**Figure 5.**

*the eastern Jetty; and (c) siltation behind the western jetty.*

*Modeling of Coastal Processes in the Mediterranean Sea: A Pilot Study on the Entrance…*

*Modeling simulation of 10 years sediment transport during 2008–2018 along the Suez Canal coastal zone; (a) accretion along the updrift site and the entrance otherwise, erosion along the downdrift site; (b) erosion behind* 

*DOI: http://dx.doi.org/10.5772/intechopen.88509*

*Modeling of Coastal Processes in the Mediterranean Sea: A Pilot Study on the Entrance… DOI: http://dx.doi.org/10.5772/intechopen.88509*

#### **Figure 5.**

*Modeling simulation of 10 years sediment transport during 2008–2018 along the Suez Canal coastal zone; (a) accretion along the updrift site and the entrance otherwise, erosion along the downdrift site; (b) erosion behind the eastern Jetty; and (c) siltation behind the western jetty.*

*Coastal and Marine Environments - Physical Processes and Numerical Modelling*

The model has coarsely triangle mesh at offshore zones and finely triangle mesh

*Simulated spectral wave (SW) model for Suez Canal entrance including (a) spectral waves in NNW direction, (b) spectral waves in NW direction, (c) spectral waves in N direction, and (d) spectral waves in NE direction.*

at surf zones and study area to get more accurate wave heights with acceptable

MIKE 21 hydrodynamic has modeled to solve currents due to interaction between wave radiation stresses and water level variations with bottom depths and structures at study area in addition to updrift and downdrift zones. The hydrodynamic forces due to wave breaking are the main effective parameters that lead

This model will be used to predict coastal sand transport and morphodynamics; MIKE 21 sediment transport is designed for the assessment of the sediment transport rates and related initial rates of bed level changes of non-cohesive sediment (sand) due to currents or combined wave-current flow [24]. It is only adapted for non-cohesive sediment (e.g., sand) for which it provides good results. Mathematical shoreline models are tools which are widely used to study the effect of hydrographic parameters on coastal processes and calculate the sediment transport rates and consequently the shoreline changes. The sediment transport process at onshore/ offshore and/or alongshore is very complicated problem because it results from

MIKE 21 SW includes two different formulations:

1.Directional decoupled parametric formulation

2.Fully spectral formulation [22].

**5.2 MIKE 21 hydrodynamics**

sediments to move [23].

**5.3 MIKE 21 sand transport**

**98**

model run period [21].

**Figure 4.**

iteration from wind, waves, and currents with the bottom sediments and/or the shore face. The orbital velocity of the waves is the principal force to shake the sediments in its place and put them in suspended case, while the currents existing in this area are responsible for transport of sediment from one place to another.

Therefore, the sand movement in the longshore direction is the longshore sediment transport, while the actual volume of sand involved in the transport are termed the littoral drift Qs that counted in m3 /year or month. All morphological changes happen due to the littoral drift current, which was created as a result of waves that approach the coastline with an oblique angle. Based on that, the relationship between the incident wave and shoreline orientation is a major factor in evaluating the morphological changes for any studied area. All morphological changes happen due to the littoral drift current, which was created as a result of waves that approaches the coastline with an oblique angle. Based on that, the relationship between the incident wave and shoreline orientation is the goal of this study.

In conclusion, siltation inside Suez Canal entrance can be explained due to moving of waves and currents at west Port Said and inside the entrance of Suez Canal. Therefore, when current comes from shallow depths at west of Port Said in the direction of W-E to deep depths at the entrance of Suez Canal, while it is carrying sediment load, its speed gradually decreases near the long western Suez Canal jetty and starts making eddies up to the long jetty, and once it becomes quiet, it starts throwing its sediment load inside Suez Canal entrance (**Figure 5a–c**).

## **6. Discussion and conclusion**

Construction of ports such as in the Suez Canal entrance has a significant potential effect on natural sediment transport processes. This causes disruption to the adjacent beaches. When current transfers from low contour level at west of Suez Canal long jetty, it decreases gradually inside the entrance of Suez Canal then started to increase and decrease back and forth, by making eddies. This eddies around the eastern and western jetties start to throw their load, while the high current speed at the eastern side of Port Said causes erosion. Consequently, some recommendations are suggested as follows:


**101**

Egypt

**Author details**

Mona Fouad Kaiser1

provided the original work is properly cited.

Matrouh University, Marsa Matrouh, Egypt

\*, Walaa Awaad Ali2

\*Address all correspondence to: monakaiser2013@gmail.com

*Modeling of Coastal Processes in the Mediterranean Sea: A Pilot Study on the Entrance…*

erosion and consider it in any construction plans.

the annual rates before implementing any projects.

national projects on it, so it is mandatory to study and monitor the rates of

• Studying of sediment transport and bed level change and highlighting the risky and hot spot areas of erosions of east and west of Suez Canal to predict

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

1 Geology Department, Faculty of Science, Suez Canal University, Ismailia, Egypt

2 Petroloum Geology Department, Faculty of Petroleum and Mining Sciences,

3 Transportation Department, Faculty of Engineering, Alexandria University,

and Maysara Khairy El Tahan3

*DOI: http://dx.doi.org/10.5772/intechopen.88509*

*Modeling of Coastal Processes in the Mediterranean Sea: A Pilot Study on the Entrance… DOI: http://dx.doi.org/10.5772/intechopen.88509*

national projects on it, so it is mandatory to study and monitor the rates of erosion and consider it in any construction plans.

• Studying of sediment transport and bed level change and highlighting the risky and hot spot areas of erosions of east and west of Suez Canal to predict the annual rates before implementing any projects.

## **Author details**

*Coastal and Marine Environments - Physical Processes and Numerical Modelling*

termed the littoral drift Qs that counted in m3

**6. Discussion and conclusion**

coastal area hydrodynamic regime.

the existing shoreline.

and protection hard structures.

this study.

iteration from wind, waves, and currents with the bottom sediments and/or the shore face. The orbital velocity of the waves is the principal force to shake the sediments in its place and put them in suspended case, while the currents existing in

this area are responsible for transport of sediment from one place to another. Therefore, the sand movement in the longshore direction is the longshore sediment transport, while the actual volume of sand involved in the transport are

changes happen due to the littoral drift current, which was created as a result of waves that approach the coastline with an oblique angle. Based on that, the relationship between the incident wave and shoreline orientation is a major factor in evaluating the morphological changes for any studied area. All morphological changes happen due to the littoral drift current, which was created as a result of waves that approaches the coastline with an oblique angle. Based on that, the relationship between the incident wave and shoreline orientation is the goal of

In conclusion, siltation inside Suez Canal entrance can be explained due to moving of waves and currents at west Port Said and inside the entrance of Suez Canal. Therefore, when current comes from shallow depths at west of Port Said in the direction of W-E to deep depths at the entrance of Suez Canal, while it is carrying sediment load, its speed gradually decreases near the long western Suez Canal jetty and starts making eddies up to the long jetty, and once it becomes quiet, it starts

Construction of ports such as in the Suez Canal entrance has a significant potential effect on natural sediment transport processes. This causes disruption to the adjacent beaches. When current transfers from low contour level at west of Suez Canal long jetty, it decreases gradually inside the entrance of Suez Canal then started to increase and decrease back and forth, by making eddies. This eddies around the eastern and western jetties start to throw their load, while the high current speed at the eastern side of Port Said causes erosion. Consequently, some recommendations are suggested as follows:

• Increasing coastal development has led to a conflict between man desire and nature processes that modified the used land. Therefore, most countries that are located on coastal areas should study in details the coastal zone management problems and risk as a result of the protection work structure effect on

• Choice should be taken between allowing unlimited construction of highvalued property and implementing the regulations that prevent developments which would be exposed to major hazards. This choice requires the estimation and prediction of probable future shoreline position and risk assessment to balance between the possible losses of development against the reduction of

• Integration between remote sensing and 2D finite hydrodynamic flow models is mandatory to evaluate, interpret, and analyze the effect of costal processes

• Because of high current speed at Suez Canal east jetties, the downdrift area is exposed to sever erosion, and there is an investment plan to implement big

throwing its sediment load inside Suez Canal entrance (**Figure 5a–c**).

/year or month. All morphological

**100**

Mona Fouad Kaiser1 \*, Walaa Awaad Ali2 and Maysara Khairy El Tahan3

1 Geology Department, Faculty of Science, Suez Canal University, Ismailia, Egypt

2 Petroloum Geology Department, Faculty of Petroleum and Mining Sciences, Matrouh University, Marsa Matrouh, Egypt

3 Transportation Department, Faculty of Engineering, Alexandria University, Egypt

\*Address all correspondence to: monakaiser2013@gmail.com

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

## **References**

[1] El Tokhi M, Abdel Gawad E, Lotfy MM. Impact of heavy metals and petroleum hydrocarbons contamination of the East Port Said port area, Egypt. Journal of Applied Sciences Research. 2008;**4**(12):1788-1798

[2] Abu Asi IM. The Geographic Criteria for the East Port Said along the Mediterranean. Egyptian Geographical Association; 1998. 29 pp (in Arabic)

[3] Dewidar KM, Frihy OE. Thematic mapper analysis to identify geomorphologic and sediment texture of El-Tineh plain, north-western coast of Sinai, Egypt. International Journal of Remote Sensing. 2003;**24**:2377-2385

[4] Coleman JM, Robert HH, Murray SP, Salama M. Morphology and dynamic sedimentology of the eastern Nile delta shelf. Marine Geology. 1981;**42**:301-312

[5] Frihy OE, Debes EA, El Sayed WR. Processes reshaping the Nile delta promontories of Egypt: Pre- and post-protection. Geomorphology. 2003;**53**:263-279

[6] Kaiser MFM. Monitoring and modelling the impact of engineering structures on coastline change, Nile Delta, Egypt [Ph.D. thesis]. UK: University of Reading; 2004. 270 p

[7] Ali W, Kaiser MF, Kholief S, El-Tahan M. Assessment of shoreline stability and solidity for Please provide volume number and page range for Refs. [7, 12].future investment plans at Ras El-Bar Resort. Egyptian Journal of Aquatic Biology and Fisheries. 2017

[8] Wilson PA. Rule-based classification of water in Landsat MSS images using the variance filter. Photogrammetric Engineering and Remote Sensing. 1997;**63**:485-491

[9] Sonka M, Hlavac V, Boyle R. Image Processing, Analysis and Machine Vision. London: Chapman & Hall; 1993. 555 p

[10] Janssen LLF, Molenaar M. Terrain objects, their dynamics and their monitoring by the integration of GIS and remote sensing. IEEE Transaction on Geoscience and Remote Sensing. 1995;**33**:749-758

[11] Frouin R, Schwindling M, Deschamps PY. Spectral reflectance of sea foam in the visible and nearinfrared. In situ measurements and remote sensing implications. Journal of Geophysical Research. 1996;**101**:14361-14371

[12] Ali W, Kaiser MF, Kholief S, El-Tahan M. Assessment of coastal change along Baltim Resort from (2000- 2015) using remote sensing and DSAS method. Egyptian Journal of Aquatic Biology and Fisheries. 2017

[13] Eastman JR. Supervised Classification in IDRISI for Windows Version 2, Tutorial Exercises. Worcester, Massachusetts: Clark University; 1997. pp. 86-94

[14] Lillesand TM, Kiefer RW. Remote Sensing and Image Interpretation. 4th Edition. New York: John Wiley & Sons, Inc; 1994. 750 pp

[15] Mather PM. Computer Processing of Remotely-sensing Images. An Introduction. 2nd ed. Chichester: John Wiley and Sons; 1999. pp. 1-75

[16] Lillesand TM, Kiefer RW, Chipman JW. Remote Sensing and Image Interpretation. 5th Edition. New York: John Wiley & Sons, Inc; 2004. 763 pp

[17] Kaiser MF. Monitoring and Modelling the Impact of Engineering

**103**

*Modeling of Coastal Processes in the Mediterranean Sea: A Pilot Study on the Entrance…*

Institute of Coastal and Marine Management of the Netherlands. 2004

*DOI: http://dx.doi.org/10.5772/intechopen.88509*

Structures on Coastline Change, Nile Delta, Egypt. Reading, U.K.: University

[18] Holthuijsen LH. Waves in Oceanic and Coastal Waters. Cambridge

Univesity Press; ISBN 978-0521860284.

[20] Naef D, Rickenmann D, Rutschmann P, McArdell BW. Comaparison of flow resistance relations for debris flows using a one-dimensional finite element simulation model. Natural Hazards and Earth System Science.

[19] Ali W, Kaiser MF, El-Tahan M. Assessment of bottom erosion in front of Rosetta Eastern and Western Groins System. In: The Scientific Committee (SC) of the 1st Scientific Congress of Junior Geosciences in Egypt (SCJGE-1) held at Suhag University, February 3-4- 2019. Paper Work in Submission. 2019

of Reading, Ph.D; 2004

2007. pp. 387

2006;**6**(1):155-165

S0016756811000215

Influences. Delft. 2015

1990. pp. 1033-1067

[21] Julien PY. Erosion and Sedimentation. 2nd ed. xviii + 371 pp. Cambridge University Press;

2010;**148**(04):683-684. DOI: 10.1017/

[22] El-Tahan M, El Sharnouby B. Dramatic Erosion of Nile Delta Coast Caused by Anthropogenic and natural

[23] Wang JD. Numerical modelling of bay circulation. In: The Sea. Ocean Engineering Science. Australia: Elsevier Publisher; Vol. 9. Part B. Chapter 32.

[24] Eurosion. Living with coastal erosion in Europe: Sediment and space for sustainability. A guide to coastal erosion management practices in Europe: Lessons learned. Coastal erosion–evaluation of the need for action. Directorate general environment. In: European Commission. Prepared by the National *Modeling of Coastal Processes in the Mediterranean Sea: A Pilot Study on the Entrance… DOI: http://dx.doi.org/10.5772/intechopen.88509*

Structures on Coastline Change, Nile Delta, Egypt. Reading, U.K.: University of Reading, Ph.D; 2004

Institute of Coastal and Marine Management of the Netherlands. 2004

[18] Holthuijsen LH. Waves in Oceanic and Coastal Waters. Cambridge Univesity Press; ISBN 978-0521860284. 2007. pp. 387

[19] Ali W, Kaiser MF, El-Tahan M. Assessment of bottom erosion in front of Rosetta Eastern and Western Groins System. In: The Scientific Committee (SC) of the 1st Scientific Congress of Junior Geosciences in Egypt (SCJGE-1) held at Suhag University, February 3-4- 2019. Paper Work in Submission. 2019

[20] Naef D, Rickenmann D, Rutschmann P, McArdell BW. Comaparison of flow resistance relations for debris flows using a one-dimensional finite element simulation model. Natural Hazards and Earth System Science. 2006;**6**(1):155-165

[21] Julien PY. Erosion and Sedimentation. 2nd ed. xviii + 371 pp. Cambridge University Press; 2010;**148**(04):683-684. DOI: 10.1017/ S0016756811000215

[22] El-Tahan M, El Sharnouby B. Dramatic Erosion of Nile Delta Coast Caused by Anthropogenic and natural Influences. Delft. 2015

[23] Wang JD. Numerical modelling of bay circulation. In: The Sea. Ocean Engineering Science. Australia: Elsevier Publisher; Vol. 9. Part B. Chapter 32. 1990. pp. 1033-1067

[24] Eurosion. Living with coastal erosion in Europe: Sediment and space for sustainability. A guide to coastal erosion management practices in Europe: Lessons learned. Coastal erosion–evaluation of the need for action. Directorate general environment. In: European Commission. Prepared by the National

**102**

1997;**63**:485-491

*Coastal and Marine Environments - Physical Processes and Numerical Modelling*

555 p

1995;**33**:749-758

1996;**101**:14361-14371

[9] Sonka M, Hlavac V, Boyle R. Image Processing, Analysis and Machine Vision. London: Chapman & Hall; 1993.

[10] Janssen LLF, Molenaar M. Terrain objects, their dynamics and their monitoring by the integration of GIS and remote sensing. IEEE Transaction on Geoscience and Remote Sensing.

[11] Frouin R, Schwindling M, Deschamps PY. Spectral reflectance of sea foam in the visible and nearinfrared. In situ measurements and remote sensing implications. Journal of Geophysical Research.

[12] Ali W, Kaiser MF, Kholief S, El-Tahan M. Assessment of coastal change along Baltim Resort from (2000- 2015) using remote sensing and DSAS method. Egyptian Journal of Aquatic

Biology and Fisheries. 2017

[13] Eastman JR. Supervised

pp. 86-94

Inc; 1994. 750 pp

Classification in IDRISI for Windows Version 2, Tutorial Exercises. Worcester, Massachusetts: Clark University; 1997.

[14] Lillesand TM, Kiefer RW. Remote Sensing and Image Interpretation. 4th Edition. New York: John Wiley & Sons,

[15] Mather PM. Computer Processing of Remotely-sensing Images. An Introduction. 2nd ed. Chichester: John

Chipman JW. Remote Sensing and Image Interpretation. 5th Edition. New York: John Wiley & Sons, Inc; 2004. 763 pp

Wiley and Sons; 1999. pp. 1-75

[16] Lillesand TM, Kiefer RW,

[17] Kaiser MF. Monitoring and Modelling the Impact of Engineering

[1] El Tokhi M, Abdel Gawad E, Lotfy MM. Impact of heavy metals and petroleum hydrocarbons contamination of the East Port Said port area, Egypt. Journal of Applied Sciences Research.

[2] Abu Asi IM. The Geographic

Criteria for the East Port Said along the Mediterranean. Egyptian Geographical Association; 1998. 29 pp (in Arabic)

[3] Dewidar KM, Frihy OE. Thematic

geomorphologic and sediment texture of El-Tineh plain, north-western coast of Sinai, Egypt. International Journal of Remote Sensing. 2003;**24**:2377-2385

[4] Coleman JM, Robert HH, Murray SP, Salama M. Morphology and dynamic sedimentology of the eastern Nile delta shelf. Marine Geology. 1981;**42**:301-312

Sayed WR. Processes reshaping the Nile delta promontories of Egypt: Pre- and post-protection. Geomorphology.

[6] Kaiser MFM. Monitoring and modelling the impact of engineering structures on coastline change, Nile Delta, Egypt [Ph.D. thesis]. UK: University of Reading; 2004. 270 p

[7] Ali W, Kaiser MF, Kholief S, El-Tahan M. Assessment of shoreline stability and solidity for Please provide volume number and page range for Refs. [7, 12].future investment plans at Ras El-Bar Resort. Egyptian Journal of Aquatic Biology and Fisheries. 2017

[8] Wilson PA. Rule-based classification of water in Landsat MSS images using the variance filter. Photogrammetric Engineering and Remote Sensing.

mapper analysis to identify

[5] Frihy OE, Debes EA, El

2003;**53**:263-279

2008;**4**(12):1788-1798

**References**

Chapter 6

Abstract

with contemporary references.

1. Introduction

105

Ionospheric Monitoring and

and Marine Environments

Ljiljana R. Cander and Bruno Zolesi

Modeling Applicable to Coastal

Ionospheric monitoring and modeling in costal and marine environment is reviewed and characterized in terms of state of art, global, regional, and local issues across different domains of solar-terrestrial conditions for practical applications. Their effects on critical technological systems are either controlled by the Earth's ionosphere, as in telecommunications and information systems, or simply influenced by its variability, as in trans-ionospheric radio communication, and navigation systems. The evolution of long-distance high-frequency (HF) communications and then still the actuality of HF radio links especially for the coast environment, maritime services, and aeronautical applications, for control and emergency services, for communications equally important in case of great islands and remote areas, for economic reasoning and easy management, and for efficient backup in case of cyber threats are discussed. Some preferred methods for a proper assessment of HF networks have been identified, and examples of existing longterm prediction and near real-time nowcasting in ionospheric space weather modeling to be used, particularly in the Mediterranean area, are presented along

Keywords: ionosphere, space weather, model, HF and GNSS systems

Variability in the Earth's ionosphere reduces the reliability of radio-frequency

Ionospheric bottom- and topside observations and studies related to fundamental as well as radio communication and navigation purposes cover most of the planet but in an inhomogeneous way. Accordingly, the discovery and complete characterization phase for most ionospheric processes is still in progress. This is particularly

(RF) and global navigation satellite system (GNSS) communication systems because they depend on the attenuation, absorption, reflection, and refraction and accordingly changes in the propagation, phase, and amplitude characteristics of radio waves, in addition to the scintillation phenomenon induced by abrupt variations in electron density along the radio path. Significant scientific work over many decades, within national and international projects, is being conducted on monitoring, proper understanding, and predicting ionospheric variability in order to enhance reliability and robustness of both ground- and space-based communica-

tions networks and other applications for the benefit of society [1].

## Chapter 6

## Ionospheric Monitoring and Modeling Applicable to Coastal and Marine Environments

Ljiljana R. Cander and Bruno Zolesi

## Abstract

Ionospheric monitoring and modeling in costal and marine environment is reviewed and characterized in terms of state of art, global, regional, and local issues across different domains of solar-terrestrial conditions for practical applications. Their effects on critical technological systems are either controlled by the Earth's ionosphere, as in telecommunications and information systems, or simply influenced by its variability, as in trans-ionospheric radio communication, and navigation systems. The evolution of long-distance high-frequency (HF) communications and then still the actuality of HF radio links especially for the coast environment, maritime services, and aeronautical applications, for control and emergency services, for communications equally important in case of great islands and remote areas, for economic reasoning and easy management, and for efficient backup in case of cyber threats are discussed. Some preferred methods for a proper assessment of HF networks have been identified, and examples of existing longterm prediction and near real-time nowcasting in ionospheric space weather modeling to be used, particularly in the Mediterranean area, are presented along with contemporary references.

Keywords: ionosphere, space weather, model, HF and GNSS systems

### 1. Introduction

Variability in the Earth's ionosphere reduces the reliability of radio-frequency (RF) and global navigation satellite system (GNSS) communication systems because they depend on the attenuation, absorption, reflection, and refraction and accordingly changes in the propagation, phase, and amplitude characteristics of radio waves, in addition to the scintillation phenomenon induced by abrupt variations in electron density along the radio path. Significant scientific work over many decades, within national and international projects, is being conducted on monitoring, proper understanding, and predicting ionospheric variability in order to enhance reliability and robustness of both ground- and space-based communications networks and other applications for the benefit of society [1].

Ionospheric bottom- and topside observations and studies related to fundamental as well as radio communication and navigation purposes cover most of the planet but in an inhomogeneous way. Accordingly, the discovery and complete characterization phase for most ionospheric processes is still in progress. This is particularly

ionizes a part of the neutral atmosphere. Absorption of EUV radiation at other wavelengths also heats a small fraction of the neutral atmosphere so that the deposition of this energy drives a complex cycle of photochemical response that interacts strongly with atmospheric transport. Solar variation of its spectrum on timescales as long as the 11-year solar activity cycle can have a significant effect on ionospheric structure and dynamics, and hence on propagation parameters, in terms of solar

Ionospheric Monitoring and Modeling Applicable to Coastal and Marine Environments

The maximum expansion of the ground-based ionospheric measurements was achieved during the International Geophysical Year (IGY, July 1957 to December 1958) and has steadily continued to the present days. Since 1995 the US Global Positioning System (GPS) has made possible the electron content observations along a radio signal path between a satellite and a ground receiver station, with valuable total electron content (TEC) data coming from sustained growth of GNSS technologies. Measured quantities like critical frequencies f0E, f0F1, and f0F2 are related to ionospheric layers, the F2 layer (atomic oxygen ions) around 350 km altitude, the daytime F1 layer (molecular oxygen ions) around 190 km and E layer at 120 km, and the D layer near 70 km (Figure 2). Separate regions in the Earth's ionosphere including topside part above 1000 km are direct consequence of solar spectrum energy deposited at various heights depending on absorption of atmosphere, of recombination processes depending on density of atmosphere changeable with height, and of the upper atmosphere composition itself also variable with height. The various forms of temporal and spatial variability of each ionospheric layer include both systematic diurnal, seasonal, and solar cycle variations and large irregular variations. They are also a function of geomagnetic latitude as the role of the Earth's magnetic field is essential, and in solar-terrestrial physics, it is very often

cycle, annual, seasonal, daily, and hourly variations [1, 2].

DOI: http://dx.doi.org/10.5772/intechopen.90467

described by geomagnetic indices such as Dst, AE, Kp, and Ap [3].

Figure 2.

107

From Figure 2 it is clear that the F2 layer has the greatest plasma density, with maximum electron density NmF2 = 1.24 10<sup>10</sup> foF2<sup>2</sup> (see also Eq. 3), which carries the highest frequencies for less absorption, and radio waves can travel the furthest distance with a minimum of attenuating hops making this ionospheric region the most important for HF communications. Its rapid changes throughout the day are shown in Figure 3 by an example of the day-to-day foF2 variability at the Nicosia (35.1° N, 33.3° E) ionosonde station over temporal scales from 15 minutes to 1 month

Diurnal and nocturnal ionospheric N(h) profile representing electron density as a function of height.

Figure 1.

Map of Mediterranean and north African regions depicting the real-time operating ionosondes (red stars) and GNSS sites (blue points). (www.igs.org/network).

true for the transition area between mid-latitude and equatorial ionosphere where the Mediterranean and North African regions have a special importance for ionospheric studies and applications. Moreover, the sea and deserted areas in these regions make even more important ionospheric monitoring and modeling because of limited availability of sufficient and high-quality data for activities in a broad range of areas within geophysics. Figure 1 shows the positioning of the ionosondes and GNSS receivers, as principal sources of ionospheric information within Mediterranean and North African regions, respectively.

In order to illustrate ionospheric monitoring and modeling results applicable to coastal and marine environments, Section 2 discusses in brief the salient points of the well-established physical background of the Earth's upper atmosphere. Section 3 describes the basic principle of the main techniques systematically used for monitoring the ionized layers of the Earth's upper atmosphere based on propagation effects that influence radio waves traveling through the ionosphere. Section 4 contains an overview of the current state of the most important electron density models, while particular attention is given to ionospheric mapping techniques to spatially interpolate derived parameters between sites from the sparse network of measurements and/or observations with emphasis on local and/or restricted area. Some aspects of HF communications in coastal and maritime applications are described in Section 5. Finally, Section 6 briefly summarizes the work, notes limitations of the current methodology, and suggests areas for further study.

### 2. General description of the Earth's ionosphere

The ionosphere is embedded in the neutral Earth's atmosphere beginning at an altitude of about 50 km and extending outward up to 1000 km. It is dynamic plasma medium, highly variable in space on scales of meters to hundreds of kilometers and time on scales of seconds to hour, months, and solar cycles that exhibit climatology and weather features at all latitudes, longitudes, and altitudes. The Earth's ionosphere is created and maintained on a very regular basis by energetic solar irradiance in the extreme ultraviolet (EUV) and X-ray regions of the spectrum that

#### Ionospheric Monitoring and Modeling Applicable to Coastal and Marine Environments DOI: http://dx.doi.org/10.5772/intechopen.90467

ionizes a part of the neutral atmosphere. Absorption of EUV radiation at other wavelengths also heats a small fraction of the neutral atmosphere so that the deposition of this energy drives a complex cycle of photochemical response that interacts strongly with atmospheric transport. Solar variation of its spectrum on timescales as long as the 11-year solar activity cycle can have a significant effect on ionospheric structure and dynamics, and hence on propagation parameters, in terms of solar cycle, annual, seasonal, daily, and hourly variations [1, 2].

The maximum expansion of the ground-based ionospheric measurements was achieved during the International Geophysical Year (IGY, July 1957 to December 1958) and has steadily continued to the present days. Since 1995 the US Global Positioning System (GPS) has made possible the electron content observations along a radio signal path between a satellite and a ground receiver station, with valuable total electron content (TEC) data coming from sustained growth of GNSS technologies. Measured quantities like critical frequencies f0E, f0F1, and f0F2 are related to ionospheric layers, the F2 layer (atomic oxygen ions) around 350 km altitude, the daytime F1 layer (molecular oxygen ions) around 190 km and E layer at 120 km, and the D layer near 70 km (Figure 2). Separate regions in the Earth's ionosphere including topside part above 1000 km are direct consequence of solar spectrum energy deposited at various heights depending on absorption of atmosphere, of recombination processes depending on density of atmosphere changeable with height, and of the upper atmosphere composition itself also variable with height. The various forms of temporal and spatial variability of each ionospheric layer include both systematic diurnal, seasonal, and solar cycle variations and large irregular variations. They are also a function of geomagnetic latitude as the role of the Earth's magnetic field is essential, and in solar-terrestrial physics, it is very often described by geomagnetic indices such as Dst, AE, Kp, and Ap [3].

From Figure 2 it is clear that the F2 layer has the greatest plasma density, with maximum electron density NmF2 = 1.24 10<sup>10</sup> foF2<sup>2</sup> (see also Eq. 3), which carries the highest frequencies for less absorption, and radio waves can travel the furthest distance with a minimum of attenuating hops making this ionospheric region the most important for HF communications. Its rapid changes throughout the day are shown in Figure 3 by an example of the day-to-day foF2 variability at the Nicosia (35.1° N, 33.3° E) ionosonde station over temporal scales from 15 minutes to 1 month

Figure 2. Diurnal and nocturnal ionospheric N(h) profile representing electron density as a function of height.

true for the transition area between mid-latitude and equatorial ionosphere where the Mediterranean and North African regions have a special importance for ionospheric studies and applications. Moreover, the sea and deserted areas in these regions make even more important ionospheric monitoring and modeling because of limited availability of sufficient and high-quality data for activities in a broad range of areas within geophysics. Figure 1 shows the positioning of the ionosondes and GNSS receivers, as principal sources of ionospheric information within Medi-

Map of Mediterranean and north African regions depicting the real-time operating ionosondes (red stars) and

Coastal and Marine Environments - Physical Processes and Numerical Modelling

In order to illustrate ionospheric monitoring and modeling results applicable to coastal and marine environments, Section 2 discusses in brief the salient points of the well-established physical background of the Earth's upper atmosphere. Section 3 describes the basic principle of the main techniques systematically used for monitoring the ionized layers of the Earth's upper atmosphere based on propagation effects that influence radio waves traveling through the ionosphere. Section 4 contains an overview of the current state of the most important electron density models, while particular attention is given to ionospheric mapping techniques to spatially interpolate derived parameters between sites from the sparse network of measurements and/or observations with emphasis on local and/or restricted area. Some aspects of HF communications in coastal and maritime applications are described in Section 5. Finally, Section 6 briefly summarizes the work, notes limi-

tations of the current methodology, and suggests areas for further study.

The ionosphere is embedded in the neutral Earth's atmosphere beginning at an altitude of about 50 km and extending outward up to 1000 km. It is dynamic plasma medium, highly variable in space on scales of meters to hundreds of kilometers and time on scales of seconds to hour, months, and solar cycles that exhibit climatology and weather features at all latitudes, longitudes, and altitudes. The Earth's ionosphere is created and maintained on a very regular basis by energetic solar irradiance in the extreme ultraviolet (EUV) and X-ray regions of the spectrum that

2. General description of the Earth's ionosphere

terranean and North African regions, respectively.

GNSS sites (blue points). (www.igs.org/network).

Figure 1.

106

#### Figure 3.

Plot of the day-to-day critical frequency foF2 variability over temporal scales from 15 minutes to 1 month at the Nicosia ionosonde station during a period of very low solar activity in October 2009 with the monthly mean of the daily sunspot number Ri = 4.6. The foF2 monthly median is in black.

of October 2009, representing ionospheric equinox during very low solar activity conditions. During this particular month, overall foF2 departure from the monthly median values is about 30%, while during very high solar activity conditions, departure from median conditions is usually much greater following the ratio of the corresponding values of solar radio flux F10.7, an index derived from measurements of total emission originating from high in the solar chromosphere and lower corona thus frequently used as a very good indicator of solar activity [2].

Similar results of the high variability are obtained if the maximum ionization density is replaced by the column density or vertical total electron content, VTEC, of the ionosphere at the co-located GNSS station at the site nico (35.1 N, 33.4 E), in Cyprus (http://www.igs.org/). Figure 4 shows diurnal 10 minutes VTEC values during absolute solar minimum in December 2008 when the variability around the monthly median values is around 40% during the nighttime and a little lower during the daytime ≈ 30%. Again it has to be emphasized that solar cycle dependence is fundamental when values of VTEC around solar maximum largely exceed by a factor of approximately 2 for those around solar minimum.

Solar events such as flares and coronal mass ejections often produce large variations in the corpuscular and electromagnetic radiations leading to disturbances of the regular regions known as ionospheric storms. They have important terrestrial consequences generating large disturbances in ionospheric electron density distribution N(h), total electron content TEC, and the electric currents system. All these phenomena can continue for a few hours to several days and lead to significant changes in the ionospheric plasma parameters which can be particularly damaging to both satellite- and ground-based systems. The F region's response to ionospheric storms has been studied since the earliest days of solar-terrestrial physics more than 90 years ago. In general results show consistency in characteristic patterns of an ionospheric storm: (1) a short positive phase that occurs during the daytime hours on the first day of a storm with the tendency to significantly increase electron density during the first 24 hours of the storm above its quiet time reference level and (2) a prolonged negative phase on subsequent days leaning to significantly

decrease electron density below its quiet time reference level, with recovery in 1 or 2 days later [see solid and dashed blue curves for the high mid-latitude Chilton

Time variations in Dst and Kp geomagnetic indices and NmF2 at the Chilton (51.6° N, 358.7° E) (blue solid and dashed curves) and at Nicosia (35.1° N, 33.3° E) ionosonde stations (red solid and dashed curves) during

Plot of the day-to-day vertical total electron content VTEC variability at the nico GNSS station over temporal scales from 10 minutes to 1 month during absolute solar minimum in December 2008 with the monthly mean of

Ionospheric Monitoring and Modeling Applicable to Coastal and Marine Environments

DOI: http://dx.doi.org/10.5772/intechopen.90467

Remarkable differences occur in the magnitudes and longevities of the only positive storm pattern represented with solid and dashed red curves for the low mid-latitude Nicosia (35.1° N, 33.3° E) ionosonde station at the island of Cyprus in the Mediterranean Sea. The striking feature is the pronounced NmF2 increase above monthly median values, which has been taken to represent the quiet reference level at both stations. It is to be believed that short-timescale dynamical mechanisms

(51.6° N, 358.7° E) ionosonde station in Figure 5].

the ionospheric storm period of 8 –10 March 2012.

Figure 5.

109

Figure 4.

the daily sunspot number Ri = 0.8.

Ionospheric Monitoring and Modeling Applicable to Coastal and Marine Environments DOI: http://dx.doi.org/10.5772/intechopen.90467

#### Figure 4.

of October 2009, representing ionospheric equinox during very low solar activity conditions. During this particular month, overall foF2 departure from the monthly median values is about 30%, while during very high solar activity conditions, departure from median conditions is usually much greater following the ratio of the corresponding values of solar radio flux F10.7, an index derived from measurements of total emission originating from high in the solar chromosphere and lower corona

Plot of the day-to-day critical frequency foF2 variability over temporal scales from 15 minutes to 1 month at the Nicosia ionosonde station during a period of very low solar activity in October 2009 with the monthly mean

Coastal and Marine Environments - Physical Processes and Numerical Modelling

Similar results of the high variability are obtained if the maximum ionization density is replaced by the column density or vertical total electron content, VTEC, of the ionosphere at the co-located GNSS station at the site nico (35.1 N, 33.4 E), in Cyprus (http://www.igs.org/). Figure 4 shows diurnal 10 minutes VTEC values during absolute solar minimum in December 2008 when the variability around the monthly median values is around 40% during the nighttime and a little lower during the daytime ≈ 30%. Again it has to be emphasized that solar cycle dependence is fundamental when values of VTEC around solar maximum largely

Solar events such as flares and coronal mass ejections often produce large variations in the corpuscular and electromagnetic radiations leading to disturbances of the regular regions known as ionospheric storms. They have important terrestrial consequences generating large disturbances in ionospheric electron density distribution N(h), total electron content TEC, and the electric currents system. All these phenomena can continue for a few hours to several days and lead to significant changes in the ionospheric plasma parameters which can be particularly damaging to both satellite- and ground-based systems. The F region's response to ionospheric storms has been studied since the earliest days of solar-terrestrial physics more than 90 years ago. In general results show consistency in characteristic patterns of an ionospheric storm: (1) a short positive phase that occurs during the daytime hours on the first day of a storm with the tendency to significantly increase electron density during the first 24 hours of the storm above its quiet time reference level and (2) a prolonged negative phase on subsequent days leaning to significantly

thus frequently used as a very good indicator of solar activity [2].

of the daily sunspot number Ri = 4.6. The foF2 monthly median is in black.

Figure 3.

108

exceed by a factor of approximately 2 for those around solar minimum.

Plot of the day-to-day vertical total electron content VTEC variability at the nico GNSS station over temporal scales from 10 minutes to 1 month during absolute solar minimum in December 2008 with the monthly mean of the daily sunspot number Ri = 0.8.

#### Figure 5.

Time variations in Dst and Kp geomagnetic indices and NmF2 at the Chilton (51.6° N, 358.7° E) (blue solid and dashed curves) and at Nicosia (35.1° N, 33.3° E) ionosonde stations (red solid and dashed curves) during the ionospheric storm period of 8 –10 March 2012.

decrease electron density below its quiet time reference level, with recovery in 1 or 2 days later [see solid and dashed blue curves for the high mid-latitude Chilton (51.6° N, 358.7° E) ionosonde station in Figure 5].

Remarkable differences occur in the magnitudes and longevities of the only positive storm pattern represented with solid and dashed red curves for the low mid-latitude Nicosia (35.1° N, 33.3° E) ionosonde station at the island of Cyprus in the Mediterranean Sea. The striking feature is the pronounced NmF2 increase above monthly median values, which has been taken to represent the quiet reference level at both stations. It is to be believed that short-timescale dynamical mechanisms

#### Coastal and Marine Environments - Physical Processes and Numerical Modelling

driving the storms (electrodynamical and thermospheric) dominate the positive phase, while longer-timescale composition changes the negative phase [4, 5].

the function of the virtual height of reflection h' is virtual because the signal travels more slowly in the ionosphere than in the free space so that the observed

Ionospheric Monitoring and Modeling Applicable to Coastal and Marine Environments

The ionogram, the record produced by the ionosonde, is a plot of the virtual height of reflection vs. the transmitted frequency. In Figure 6 a typical ionogram is shown produced by a modern digital ionosonde [8], where several important characteristics (like the critical frequencies and the heights of the different ionospheric layers) are indicated as well as the automatic interpretation on the left side. They all have a significant role in the studies concerning ionospheric physics, space weather,

The routine observations of every ionospheric station need standard techniques and conventions applicable for the interpretation of ionospheric measurements in order to achieve a more phenomenological description of the ionogram as well as provide a simplified description of the ionosphere above the station. They were defined in the URSI handbook of ionogram interpretation and reduction edited by W.R. Piggot and K. Rawer [9]. During the past decades, the ionosondes have had an important technological evolution from the first ones analogical recorded on film, to the digital one, and more recently is the automatic scaling of the ionograms essential for real-time monitoring the ionospheric plasma of space weather purposes [1, 2]. The other principal method of ionospheric observation, the GNSS signals monitoring, is applied to evaluate the ionospheric total electron content,TEC, defined as the integral of electron density along the radio wave path s from a satellite trans-

TEC ¼

plasmasphere system is particularly important for trans-ionospheric

Daytime ionogram produced by a digisonde, a digital ionosonde, with routinely scaled ionospheric

ð

Ne sð Þ ds (5)

.

s

where Ne is the ionospheric electron density along the path s in electrons/m<sup>3</sup>

communications (propagation at VHF and above), navigation, and solar-terrestrial physics. Considering that the satellite is not at the zenith point of the receiver

This parameter providing information of overall ionization in the ionosphere-

heights h' exceed the true height reflections.

DOI: http://dx.doi.org/10.5772/intechopen.90467

and related phenomena.

mitter to a ground-based receiver:

Figure 6.

111

characteristics.

However a number of questions remain, e.g., solar-terrestrial circumstances and prior storm ionospheric condition necessary for these phases to occur. In particular: (1) duration and magnitude of the negative and/or positive phase versus latitude, local time, season, and phase of solar cycle as well as between different solar cycles and (2) temporal relationships between characteristics of the solar event and the consequent development of the geomagnetic and ionospheric storms in real time. Nowadays they are subjects of intense studies within the space weather domain [2].

### 3. Ionospheric monitoring

The exploration and the physical description of the ionosphere has been the result of a great activity of experimental observation and continuous systematic monitoring started at beginning of the last century when, G. Marconi realizing on 12 December 1901 a transoceanic radio link, provided the experimental proof of the existence of the Earth's ionosphere postulated during the nineteenth century by various scientists like B. Stewart and A. Schuster. Then the vertical structure of this part of the atmosphere has been described in detail thanks to the technological developments of G. Breit and M. A. Tuve and to the systematic experiments and theoretical studies of Appleton [6].

Two principal methods have been applied to observe and to investigate the terrestrial ionosphere: the first and traditional one is ground-based, the ionospheric vertical sounding by ionosondes to determine electron density of ionospheric plasma as a function of the height, and the second one, more recently, by using geostationary satellites to provide the total electron content.

The first one is a special radar technique based on the principle that when an electromagnetic wave of frequency f penetrates vertically in the ionospheric plasma, the reflection occurs, according to the magneto-ionic theory [7], at the level where the refractive n index becomes zero:

$$m^2 = \mathbb{1} - \left(f\_N / f\right)^2\tag{1}$$

Then considering that the plasma frequency fN is

$$f\_N = \left[ \left( Nq^2 \right) \left( 4m\pi^2 \varepsilon\_0 \right) \right] \tag{2}$$

where N is electron density and q and m are the charge and the mass of the electron, respectively; the reflection in the ionosphere occurs when the incident frequency f is equal to fN. Furthermore the maximum electron density Nm corresponds to the maximum reflected incidence frequency, called the critical frequency fo:

$$Nm = 1.24 \ 10^{10} \text{ fo}^2 \tag{3}$$

where Nm and fo are expressed in el/m<sup>3</sup> and in MHz, respectively.

A vertical ionospheric sounder emits radio impulses with increasing frequency from 1 to 20 MHz, measuring the time delay of radio signals received back from the different ionospheric layer:

$$
\Delta \mathbf{t} = \mathbf{2} \,\mathrm{h}^\prime / \mathrm{c} \tag{4}
$$

#### Ionospheric Monitoring and Modeling Applicable to Coastal and Marine Environments DOI: http://dx.doi.org/10.5772/intechopen.90467

the function of the virtual height of reflection h' is virtual because the signal travels more slowly in the ionosphere than in the free space so that the observed heights h' exceed the true height reflections.

The ionogram, the record produced by the ionosonde, is a plot of the virtual height of reflection vs. the transmitted frequency. In Figure 6 a typical ionogram is shown produced by a modern digital ionosonde [8], where several important characteristics (like the critical frequencies and the heights of the different ionospheric layers) are indicated as well as the automatic interpretation on the left side. They all have a significant role in the studies concerning ionospheric physics, space weather, and related phenomena.

The routine observations of every ionospheric station need standard techniques and conventions applicable for the interpretation of ionospheric measurements in order to achieve a more phenomenological description of the ionogram as well as provide a simplified description of the ionosphere above the station. They were defined in the URSI handbook of ionogram interpretation and reduction edited by W.R. Piggot and K. Rawer [9]. During the past decades, the ionosondes have had an important technological evolution from the first ones analogical recorded on film, to the digital one, and more recently is the automatic scaling of the ionograms essential for real-time monitoring the ionospheric plasma of space weather purposes [1, 2].

The other principal method of ionospheric observation, the GNSS signals monitoring, is applied to evaluate the ionospheric total electron content,TEC, defined as the integral of electron density along the radio wave path s from a satellite transmitter to a ground-based receiver:

$$TEC = \int\_{\mathfrak{s}} \mathrm{Ne}(s) \, ds \tag{5}$$

where Ne is the ionospheric electron density along the path s in electrons/m<sup>3</sup> .

This parameter providing information of overall ionization in the ionosphereplasmasphere system is particularly important for trans-ionospheric communications (propagation at VHF and above), navigation, and solar-terrestrial physics. Considering that the satellite is not at the zenith point of the receiver

#### Figure 6.

Daytime ionogram produced by a digisonde, a digital ionosonde, with routinely scaled ionospheric characteristics.

driving the storms (electrodynamical and thermospheric) dominate the positive phase, while longer-timescale composition changes the negative phase [4, 5]. However a number of questions remain, e.g., solar-terrestrial circumstances and prior storm ionospheric condition necessary for these phases to occur. In particular: (1) duration and magnitude of the negative and/or positive phase versus latitude, local time, season, and phase of solar cycle as well as between different solar cycles and (2) temporal relationships between characteristics of the solar event and the consequent development of the geomagnetic and ionospheric storms

Coastal and Marine Environments - Physical Processes and Numerical Modelling

in real time. Nowadays they are subjects of intense studies within the space

The exploration and the physical description of the ionosphere has been the result of a great activity of experimental observation and continuous systematic monitoring started at beginning of the last century when, G. Marconi realizing on 12 December 1901 a transoceanic radio link, provided the experimental proof of the existence of the Earth's ionosphere postulated during the nineteenth century by various scientists like B. Stewart and A. Schuster. Then the vertical structure of this part of the atmosphere has been described in detail thanks to the technological developments of G. Breit and M. A. Tuve and to the systematic experiments and

Two principal methods have been applied to observe and to investigate the terrestrial ionosphere: the first and traditional one is ground-based, the ionospheric vertical sounding by ionosondes to determine electron density of ionospheric plasma as a function of the height, and the second one, more recently, by using

The first one is a special radar technique based on the principle that when an electromagnetic wave of frequency f penetrates vertically in the ionospheric plasma, the reflection occurs, according to the magneto-ionic theory [7], at the level

> = 4mπ<sup>2</sup>ԑ<sup>0</sup> � � h� i

n2 <sup>¼</sup> <sup>1</sup> � <sup>f</sup> <sup>N</sup>=<sup>f</sup> � �<sup>2</sup> (1)

Nm <sup>¼</sup> <sup>1</sup>:24 1010 fo<sup>2</sup> (3)

Δt ¼ 2 h'=c (4)

(2)

geostationary satellites to provide the total electron content.

Then considering that the plasma frequency fN is

<sup>f</sup> <sup>N</sup> <sup>¼</sup> Nq<sup>2</sup><sup>Þ</sup>

where Nm and fo are expressed in el/m<sup>3</sup> and in MHz, respectively.

A vertical ionospheric sounder emits radio impulses with increasing frequency from 1 to 20 MHz, measuring the time delay of radio signals received back from

where N is electron density and q and m are the charge and the mass of the electron, respectively; the reflection in the ionosphere occurs when the incident frequency f is equal to fN. Furthermore the maximum electron density Nm corresponds to the maximum reflected incidence frequency, called the critical frequency fo:

weather domain [2].

3. Ionospheric monitoring

theoretical studies of Appleton [6].

where the refractive n index becomes zero:

the different ionospheric layer:

110

and the real path s is not vertical, it is possible to calculate the vertical TEC (VTEC) by using different geophysical models to convert the values of the so-called slant TEC.

Gallet [13] to produce global maps of the two key ionospheric characteristics related to the maximum electron density of the ionospheric F region. They are the median monthly hourly values of foF2 and M(3000)F2, obtained from ionograms of the worldwide ionosonde network. These maps are extremely important for longdistance HF communications representing a significant tool for applied science and for radio users, especially frequency planners at radio broadcasting agencies as well as for geophysicists of the upper atmosphere. Here M(3000)F2 is the transmission M factor (also known as the propagation, obliquity, or maximum usable frequency (MUF) factor), an ionospheric characteristic derived from an empirical estimate of the relationship between reflecting layer height, frequency, and oblique radio wave propagation path length [9]. The other important propagation and prediction quantity is the maximum usable frequency, a function of a critical frequency fo and

Ionospheric Monitoring and Modeling Applicable to Coastal and Marine Environments

To produce regional models of the ionosphere for long-term prediction, nowcasting or even short-term forecasting with accuracy much better of the global mode was the target of European projects promoted by the European scientific framework, European Cooperation in Science and Technology (COST) [14]. In Figure 7 an example of the hourly foF2 nowcast map is given generated by using simplified ionospheric regional model real-time updated (SIRMUP) model for the digital upper atmosphere server (DIAS) [15], an application also embodied in the project ESPAS, the near-Earth space data infrastructure for e-Science (https://

An example of the foF2 nowcast map predicted by SIRMUP model in 16 January 2019 at 11:00 UT for DIAS

MUF dð Þ¼ fo M dð Þ (8)

an appropriate M factor for a given distance d:

DOI: http://dx.doi.org/10.5772/intechopen.90467

www.espas-fp7.eu/).

Figure 7.

113

(http://www.iono.noa.gr/Dias/).

The technique to evaluate the TEC is based on the physical fact that the signal propagation time between the satellite- and the ground-based receiver, due to the anisotropic nature of the ionosphere-plasmasphere system, is directly proportional to the total number of free electrons along the signal path. The great increase and technological development on the satellite navigation and positioning system provided a new source of ionospheric data available at several global and regional centers of the International GNSS Service formerly the International GPS Service for Geodynamics (IGS) (http://igscb.jpl.nasa.gov/) in the receiver independent exchange (RINEX) format [10]. These observations are particularly important in the evaluation of the error due to the ionospheric propagation delay for the single GNSS frequency that is inversely proportional to the square of its carrier frequency but proportional to TEC along the ray path. The Center for Orbit Determination in Europe (CODE) from Universität Bern (http://aiuws.unibe/ch/ionosphere) regularly provides global VTEC maps, while the International GNSS Service makes available an extensive variety of GNSS open data and ionospheric open products (http://www.igs.org/).

### 4. Ionospheric modeling and mapping

The ground-based and satellite routine measurements constituted, in the second half of last the century, the basis for the global, regional, and local modeling of the terrestrial ionospheric plasma. This activity was supported by international organizations, like the International Union of Radio Science (URSI), the Committee on Space Research (COSPAR), and in particular the International Radio Consultative Committee (CCIR) establishing internationally agreed global propagation models.

Simple models of the lower layers E and F1 are defined as Chapman layers, because referred to an ideal ionosphere as function of the solar zenith angle χ, then the geographical position, and of a solar activity index R [11]:

$$f\text{oE}\left(\chi,\mathbb{R}\right) = \text{\(3.3\)}\left[\left(\mathbb{1} + \text{0.0088R}\right)\cos\chi\right]^{1/4} \tag{6}$$

$$\left[\text{foF1}\left(\chi, R\right) = \text{4.25}\left[\left(\mathbf{1} + \mathbf{0.015R}\right)\cos\chi\right]^{1/4} \tag{7}$$

where foE and foF1 are the critical frequencies in MHz.

However, essential for theoretical studies and practical application are 3D pictures of the terrestrial ionosphere generated by combining the models of the electron density profile, the concentration of the electrons vs. the altitude (see Figure 2), and the global and regional mapping of the principal ionospheric characteristics. After the well-known and widely used model introduced by P.A. Bradley and J. Dudney [1], important results were obtained by more general empirical International Reference Ionosphere (IRI) model [12]. Following the beginning of IRI project in 1968, this global model has been systematically improved and updated over time, so that it is currently accepted as the standard for ionospheric parameters in the altitude range from 60 to 2000 km.

Thanks to the first use of computing devices, able to manage the enormous amount of observations collected during the years around the IGY, a numerical method was developed in the Institute of Telecommunication Sciences (ITS) at the Boulder Laboratories of the U.S. Department of Commerce by W.B. Jones and R.M. Ionospheric Monitoring and Modeling Applicable to Coastal and Marine Environments DOI: http://dx.doi.org/10.5772/intechopen.90467

Gallet [13] to produce global maps of the two key ionospheric characteristics related to the maximum electron density of the ionospheric F region. They are the median monthly hourly values of foF2 and M(3000)F2, obtained from ionograms of the worldwide ionosonde network. These maps are extremely important for longdistance HF communications representing a significant tool for applied science and for radio users, especially frequency planners at radio broadcasting agencies as well as for geophysicists of the upper atmosphere. Here M(3000)F2 is the transmission M factor (also known as the propagation, obliquity, or maximum usable frequency (MUF) factor), an ionospheric characteristic derived from an empirical estimate of the relationship between reflecting layer height, frequency, and oblique radio wave propagation path length [9]. The other important propagation and prediction quantity is the maximum usable frequency, a function of a critical frequency fo and an appropriate M factor for a given distance d:

$$\text{MUF } (d) = \text{fo } \mathcal{M} \; (d) \tag{8}$$

To produce regional models of the ionosphere for long-term prediction, nowcasting or even short-term forecasting with accuracy much better of the global mode was the target of European projects promoted by the European scientific framework, European Cooperation in Science and Technology (COST) [14]. In Figure 7 an example of the hourly foF2 nowcast map is given generated by using simplified ionospheric regional model real-time updated (SIRMUP) model for the digital upper atmosphere server (DIAS) [15], an application also embodied in the project ESPAS, the near-Earth space data infrastructure for e-Science (https:// www.espas-fp7.eu/).

#### Figure 7.

An example of the foF2 nowcast map predicted by SIRMUP model in 16 January 2019 at 11:00 UT for DIAS (http://www.iono.noa.gr/Dias/).

and the real path s is not vertical, it is possible to calculate the vertical TEC (VTEC) by using different geophysical models to convert the values of the

Coastal and Marine Environments - Physical Processes and Numerical Modelling

The technique to evaluate the TEC is based on the physical fact that the signal propagation time between the satellite- and the ground-based receiver, due to the anisotropic nature of the ionosphere-plasmasphere system, is directly proportional to the total number of free electrons along the signal path. The great increase and technological development on the satellite navigation and positioning system provided a new source of ionospheric data available at several global and regional centers of the International GNSS Service formerly the International GPS Service for Geodynamics (IGS) (http://igscb.jpl.nasa.gov/) in the receiver independent exchange (RINEX) format [10]. These observations are particularly important in the evaluation of the error due to the ionospheric propagation delay for the single GNSS frequency that is inversely proportional to the square of its carrier frequency but proportional to TEC along the ray path. The Center for Orbit Determination in Europe (CODE) from Universität Bern (http://aiuws.unibe/ch/ionosphere) regularly provides global VTEC maps, while the International GNSS Service makes available an extensive variety of GNSS open data and ionospheric open products

The ground-based and satellite routine measurements constituted, in the second half of last the century, the basis for the global, regional, and local modeling of the terrestrial ionospheric plasma. This activity was supported by international organizations, like the International Union of Radio Science (URSI), the Committee on Space Research (COSPAR), and in particular the International Radio Consultative Committee (CCIR) establishing internationally agreed global

Simple models of the lower layers E and F1 are defined as Chapman layers, because referred to an ideal ionosphere as function of the solar zenith angle χ, then

foE ð Þ¼ χ, R 3:3 1 ½ � ð Þ þ 0:0088R cos χ

foF1 ð Þ¼ χ, R 4:25 1 ½ � ð Þ þ 0:015R cos χ

However, essential for theoretical studies and practical application are 3D pictures of the terrestrial ionosphere generated by combining the models of the electron density profile, the concentration of the electrons vs. the altitude (see Figure 2), and the global and regional mapping of the principal ionospheric characteristics. After the well-known and widely used model introduced by P.A. Bradley and J. Dudney [1], important results were obtained by more general empirical International Reference Ionosphere (IRI) model [12]. Following the beginning of IRI project in 1968, this global model has been systematically improved and updated over time, so that it is currently accepted as the standard for ionospheric parameters

Thanks to the first use of computing devices, able to manage the enormous amount of observations collected during the years around the IGY, a numerical method was developed in the Institute of Telecommunication Sciences (ITS) at the Boulder Laboratories of the U.S. Department of Commerce by W.B. Jones and R.M.

<sup>1</sup>=<sup>4</sup> (6)

<sup>1</sup>=<sup>4</sup> (7)

the geographical position, and of a solar activity index R [11]:

where foE and foF1 are the critical frequencies in MHz.

in the altitude range from 60 to 2000 km.

so-called slant TEC.

(http://www.igs.org/).

propagation models.

112

4. Ionospheric modeling and mapping

## 5. HF communications in coastal and maritime applications

HF radio links via ionospere in the 3–30 MHz band represented in most part of the twentieth century the only way for long-distance radio communications, largely used by military and civilian users. Consequently the scientific research in ionospheric radio propagation and monitoring was mainly supported by those countries having global interests and among them the air and maritime communications [16]. The new and great increase of satellite use for long-distance communications gave, between the end of the 1970s and the beginning of the 1980s, the impression that the HF radio communication via ionosphere should be rapidly obsolete. Instead, the use of HF still plays a very important role during emergency situation as the natural catastrophes, for naval or coast to island communications, for people sparse in large extension of country, and for military and civilian radio links located in valleys of a mountain region. So the prediction, forecasting, or even the nowcasting of the future status of the reflectivity of the ionospheric layers is crucial for radio planners to choose the best radio frequency to use or, more recently to know, the evolution of the overall space weather conditions [2].

and geometry, principally on the radio technical characteristics of the equipment like power of the transmitter, sensitivity of the receiver, radio noise, gain of the

Ionospheric Monitoring and Modeling Applicable to Coastal and Marine Environments

Skip distance maps or MUF isolines in two typical examples provided by national services: (a) applied to the Mediterranean area and (b) applied to the Australian region provided by the Australian radio and space

Different national and international institutions provide long-term prediction of the hourly behavior of MUF and LUF for a given radio link. See as an important example the many radio and space weather information provided by the Australian SWS-Radio and Space Services at https://www.sws.bom.gov.au/, the American NOAA with the IONCAP procedure at ftp.ngdc.noaa.gov/STP/IONOSPHERE/ MODELS/IONCAP/, the France Telecom at www.iono.enst-bretagne.fr, and the already mentioned DIAS/ESPAS services. Other national institutions also provide ionospheric prediction, for example, the Italian INGV (Istituto Nazionale di Geofisica e Vulcanologia), inside European organizations or by special request of

antenna system, etc. [1, 11].

DOI: http://dx.doi.org/10.5772/intechopen.90467

Figure 10.

115

services at https://www.sws.born.gov.au › HF\_Systems.

In a typical HF radio link via ionosphere (Figure 8), radio users need to know in advance the range of the useful radio frequencies to be applicable for their service and the area covered by them. The spectrum of the radio frequencies between two points is included between the maximum usable frequency and the lower usable frequency (LUF). The MUF depends only on the geometry of the radio link and on the conditions of reflectivity of the ionosphere, practically the critical frequency fo of the ionospheric layer, while the LUF depends, besides geophysical parameters

Figure 8. Simple scheme of an ionospheric radio link.

Figure 9. Example of the HF ionospheric long-term prediction of MUF and LUF for a point-to-point radio link.

Ionospheric Monitoring and Modeling Applicable to Coastal and Marine Environments DOI: http://dx.doi.org/10.5772/intechopen.90467

and geometry, principally on the radio technical characteristics of the equipment like power of the transmitter, sensitivity of the receiver, radio noise, gain of the antenna system, etc. [1, 11].

Different national and international institutions provide long-term prediction of the hourly behavior of MUF and LUF for a given radio link. See as an important example the many radio and space weather information provided by the Australian SWS-Radio and Space Services at https://www.sws.bom.gov.au/, the American NOAA with the IONCAP procedure at ftp.ngdc.noaa.gov/STP/IONOSPHERE/ MODELS/IONCAP/, the France Telecom at www.iono.enst-bretagne.fr, and the already mentioned DIAS/ESPAS services. Other national institutions also provide ionospheric prediction, for example, the Italian INGV (Istituto Nazionale di Geofisica e Vulcanologia), inside European organizations or by special request of

#### Figure 10.

Skip distance maps or MUF isolines in two typical examples provided by national services: (a) applied to the Mediterranean area and (b) applied to the Australian region provided by the Australian radio and space services at https://www.sws.born.gov.au › HF\_Systems.

5. HF communications in coastal and maritime applications

Coastal and Marine Environments - Physical Processes and Numerical Modelling

the overall space weather conditions [2].

Figure 8.

Figure 9.

114

Simple scheme of an ionospheric radio link.

HF radio links via ionospere in the 3–30 MHz band represented in most part of the twentieth century the only way for long-distance radio communications, largely used by military and civilian users. Consequently the scientific research in ionospheric radio propagation and monitoring was mainly supported by those countries having global interests and among them the air and maritime communications [16]. The new and great increase of satellite use for long-distance communications gave, between the end of the 1970s and the beginning of the 1980s, the impression that the HF radio communication via ionosphere should be rapidly obsolete. Instead, the use of HF still plays a very important role during emergency situation as the natural catastrophes, for naval or coast to island communications, for people sparse in large extension of country, and for military and civilian radio links located in valleys of a mountain region. So the prediction, forecasting, or even the nowcasting of the future status of the reflectivity of the ionospheric layers is crucial for radio planners to choose the best radio frequency to use or, more recently to know, the evolution of

In a typical HF radio link via ionosphere (Figure 8), radio users need to know in advance the range of the useful radio frequencies to be applicable for their service and the area covered by them. The spectrum of the radio frequencies between two points is included between the maximum usable frequency and the lower usable frequency (LUF). The MUF depends only on the geometry of the radio link and on the conditions of reflectivity of the ionosphere, practically the critical frequency fo of the ionospheric layer, while the LUF depends, besides geophysical parameters

Example of the HF ionospheric long-term prediction of MUF and LUF for a point-to-point radio link.

their users. For example, in Figure 9 a schematic pattern of the MUF and LUF hourly monthly median predictions for a generic distance and month is shown. increasing the electron density from the South East. The second one, on the lower panel, provided by the Australian Radio and Space Services gives the nowcast optimum recommended frequency for the Australia region and the close-up oceans

Of course the first and most important application of the ionospheric radio propagation in the coastal and maritime communication is related to the point-topoint radio links between the country and the islands establishing a continued contact between the government critical infrastructures when they are not covered, due to the distance, by other options like VHF radio bridges or ground wave propagation. Secondly, HF radio communication is obviously still important for constant communication of civilian radio users, i.e., the small boats of fishermen and even for the national Coast Guard boats, especially in the Mediterranean area where there are recent operating rescue actions far from their country coast. The Mediterranean area is particularly interesting for the ionospheric physics and radio propagation, not only for historical, economical, and political reasons, but also because in that area, there are the southernmost systematic ionospheric soundings when no other ionospheric observations are available in all the northern part of the

In Figure 11 two nowcasting maps of foF2 and M(3000)F2 are shown produced

Example of long-term maps of MUF over the eastern part of the Mediterranean Sea predicted by SIRM for the

by the Geomagnetic Indices Forecasting and Ionospheric Nowcasting Tools

having a transmitter located at Sydney (http://www.sws.born.gov.au ›

Ionospheric Monitoring and Modeling Applicable to Coastal and Marine Environments

HF\_Systems).

DOI: http://dx.doi.org/10.5772/intechopen.90467

African region.

Figure 12.

117

Cyprus Ionospheric forecasting service.

Another parameter extremely relevant to the class of users like the broadcasting agencies and air and maritime application is the skip distance, defined as the minimum distance reflected from the ionosphere, drawn by isolines around the transmitting point. This parameter, typical for radio links from a fixed point to a mobile receiver, is derived by the MUF and gives information on the area covered by a given frequency; in fact within this distance, also known as the silent distance, only ground wave propagation is possible.

In Figure 10 there are two examples of this kind of service. The first one, on the upper panel, applied to the Mediterranean area, gives the hourly isolines of the MUF in MHz or the skip distance variable with time for a point of transmission located in South East. This sequence of maps clearly shows the effect of the Sun,

#### Figure 11.

Examples of foF2 and M(3000)F2 nowcast maps predicted by SIRMUP model for the Central Mediterranean area at two different hours and effective solar activity index R12eff.

Ionospheric Monitoring and Modeling Applicable to Coastal and Marine Environments DOI: http://dx.doi.org/10.5772/intechopen.90467

increasing the electron density from the South East. The second one, on the lower panel, provided by the Australian Radio and Space Services gives the nowcast optimum recommended frequency for the Australia region and the close-up oceans having a transmitter located at Sydney (http://www.sws.born.gov.au › HF\_Systems).

Of course the first and most important application of the ionospheric radio propagation in the coastal and maritime communication is related to the point-topoint radio links between the country and the islands establishing a continued contact between the government critical infrastructures when they are not covered, due to the distance, by other options like VHF radio bridges or ground wave propagation. Secondly, HF radio communication is obviously still important for constant communication of civilian radio users, i.e., the small boats of fishermen and even for the national Coast Guard boats, especially in the Mediterranean area where there are recent operating rescue actions far from their country coast. The Mediterranean area is particularly interesting for the ionospheric physics and radio propagation, not only for historical, economical, and political reasons, but also because in that area, there are the southernmost systematic ionospheric soundings when no other ionospheric observations are available in all the northern part of the African region.

In Figure 11 two nowcasting maps of foF2 and M(3000)F2 are shown produced by the Geomagnetic Indices Forecasting and Ionospheric Nowcasting Tools

#### Figure 12.

Example of long-term maps of MUF over the eastern part of the Mediterranean Sea predicted by SIRM for the Cyprus Ionospheric forecasting service.

their users. For example, in Figure 9 a schematic pattern of the MUF and LUF hourly monthly median predictions for a generic distance and month is shown.

Coastal and Marine Environments - Physical Processes and Numerical Modelling

agencies and air and maritime application is the skip distance, defined as the minimum distance reflected from the ionosphere, drawn by isolines around the transmitting point. This parameter, typical for radio links from a fixed point to a mobile receiver, is derived by the MUF and gives information on the area covered by a given frequency; in fact within this distance, also known as the silent distance,

only ground wave propagation is possible.

Figure 11.

116

Another parameter extremely relevant to the class of users like the broadcasting

In Figure 10 there are two examples of this kind of service. The first one, on the

Examples of foF2 and M(3000)F2 nowcast maps predicted by SIRMUP model for the Central Mediterranean

area at two different hours and effective solar activity index R12eff.

upper panel, applied to the Mediterranean area, gives the hourly isolines of the MUF in MHz or the skip distance variable with time for a point of transmission located in South East. This sequence of maps clearly shows the effect of the Sun, (GIFINT) [17], one of the space weather pilot projects promoted by the European Space Agency in the central area of the Mediterranean Sea.

wide scale of natural disasters or cyberattacks to render Internet links useless between the great islands of the Mediterranean region and their respective govern-

Ionospheric Monitoring and Modeling Applicable to Coastal and Marine Environments

The land and maritime mobile community for communication of voice and data, in coast stations, ship-ship, shore-ship, and ship-shore modes of operation, occupied about 15% of available HF radio spectrum. High-frequency transmissions and prediction support both maritime safety information (MSI) and distress related communications using digital selective calling (DSC). These communications take place across the maritime mobile service bands within 1.6–26.5 MHz as defined by the International Telecommunication Union (ITU) Radio Regulations [24]. More importantly there is currently considerable worldwide effort being applied to further expand the use of GNSSs by civilian users in general and the civil aviation community in particular. This effort is being directed toward switching from systems under military control to systems under civil control. Scientific studies and technical reports have supported a variety of work in these areas, but here focus is on the Earth's ionosphere's important role. One of the main reasons is related to the fact that this ionosphere is a medium of communication inexhaustible, not polluting and extremely economic especially for its role of possible backup in case of blackout

However, the highly complex nature of the Earth's ionosphere, and its potential

Problems of data shortage, within the Mediterranean and North African regions,

Data sources are acknowledged as follows: the Space World Data Centre for Solar-Terrestrial Physics (STP) at STFC Rutherford Appleton Laboratory for operation of the ionosonde at Chilton and data access via (http://www.ralspace.stfc.ac.uk/ RALSpace/); the Cyprus digital ionosonde station in Nicosia, the Helmholtz Centre Potsdam of GFZ, and the German Research Centre for Geosciences for the produc-

tion of Kp data (http://www.gfz-potsdam.de/en/kp-index/); the WDC for

and a potential lack in confidence in the performance of models based on such limited data sets have taken on greater importance in recent years. As real-time system operations and integrated management are becoming increasingly present in many domains within geophysics, which requires an increased amount of data with high spatiotemporal resolution, synthetic data is required to augment recorded data and to ensure that a wide variety of ionospheric conditions are tested and an

for huge spatial and temporal variability, is such that a very large number of modeling scenarios is required in general and coastal and marine environments in particular. It has been briefly shown that the algorithms used in this study can be tuned and optimized so as to meet the basic requirements, even under the worstcase space weather conditions [25]. The SIRM, and its real-time updating version SIRMUP, provides regional type of a self-consistent model initialization specifying most important ionospheric characteristics foF2 and M(3000)F2 at a given time, while the GIFINT approach could assess specifications and forecasts of ionospheric variables on a local level. This further enhances the necessity for a large number of

varied scenarios to be used for verification purposes.

ment organization.

DOI: http://dx.doi.org/10.5772/intechopen.90467

6. Conclusions

of other systems.

associated model is verified.

Acknowledgements

119

Long-term maps of the MUF in the Eastern part of the Mediterranean area are available within the Cyprus Ionospheric Forecasting Service (CIFS) [18] project promoted by the Frederick Research Center of Nicosia, Cyprus, in Figure 12.

The technique involved in the over-the-horizon (OTH) ionospheric radar (Figure 13) uses HF frequencies reflected by the ionosphere to detect objects at very long distances, not covered by the ordinary radars that cannot operate beyond the horizon [19, 20]. This technique needs a very high level of energy transmitted (from hundreds of MWatt to GWatt) and a large and complex structure of the antenna system (hundreds of square meters). A real-time control of the ionosphere by a network of ionospheric vertical soundings together with the 3D image and the ray tracing model of the ionosphere is also necessary. Figure 14 gives an example of 3D image of the ionosphere in the Mediterranean region applicable accordingly [21].

The OTH ionospheric radar, besides the obvious military use, has two important applications from the point of view of the coastal environment. The first one is the control of naval traffic in the space around the territorial waters in other words the border control. The second one is the remote control of the status of the sea level in order to detect tsunami waves for an early alert [22].

Finally, another important application of the HF ionospheric communication has been described within objectives of the European project Short Wave Critical Infrastructure Network based on New Generation (SWING) of high survival radio communications system [23]. The SWING project performed a study to maintain a high survival HF radio network (data/voice) in the real-time support of European critical infrastructure communications. This operating activity should establish a minimum flux of essential information for the management and control, in case, of

Figure 13. Simple scheme of the OTH operation for long-range detection of ships, aeroplanes and sea surface conditions.

#### Figure 14.

Map of the ionospheric electron density in el/m<sup>3</sup> at the fixed height of 201 km obtained by the IRI-SIRMUP-P procedure for a given epoch.

wide scale of natural disasters or cyberattacks to render Internet links useless between the great islands of the Mediterranean region and their respective government organization.

## 6. Conclusions

(GIFINT) [17], one of the space weather pilot projects promoted by the European

applications from the point of view of the coastal environment. The first one is the control of naval traffic in the space around the territorial waters in other words the border control. The second one is the remote control of the status of the sea level

been described within objectives of the European project Short Wave Critical Infrastructure Network based on New Generation (SWING) of high survival radio communications system [23]. The SWING project performed a study to maintain a high survival HF radio network (data/voice) in the real-time support of European critical infrastructure communications. This operating activity should establish a minimum flux of essential information for the management and control, in case, of

Simple scheme of the OTH operation for long-range detection of ships, aeroplanes and sea surface conditions.

Map of the ionospheric electron density in el/m<sup>3</sup> at the fixed height of 201 km obtained by the IRI-SIRMUP-P

Finally, another important application of the HF ionospheric communication has

Long-term maps of the MUF in the Eastern part of the Mediterranean area are available within the Cyprus Ionospheric Forecasting Service (CIFS) [18] project promoted by the Frederick Research Center of Nicosia, Cyprus, in Figure 12. The technique involved in the over-the-horizon (OTH) ionospheric radar (Figure 13) uses HF frequencies reflected by the ionosphere to detect objects at very long distances, not covered by the ordinary radars that cannot operate beyond the horizon [19, 20]. This technique needs a very high level of energy transmitted (from hundreds of MWatt to GWatt) and a large and complex structure of the antenna system (hundreds of square meters). A real-time control of the ionosphere by a network of ionospheric vertical soundings together with the 3D image and the ray tracing model of the ionosphere is also necessary. Figure 14 gives an example of 3D image of the ionosphere in the Mediterranean region applicable accordingly [21]. The OTH ionospheric radar, besides the obvious military use, has two important

Space Agency in the central area of the Mediterranean Sea.

Coastal and Marine Environments - Physical Processes and Numerical Modelling

in order to detect tsunami waves for an early alert [22].

Figure 13.

Figure 14.

118

procedure for a given epoch.

The land and maritime mobile community for communication of voice and data, in coast stations, ship-ship, shore-ship, and ship-shore modes of operation, occupied about 15% of available HF radio spectrum. High-frequency transmissions and prediction support both maritime safety information (MSI) and distress related communications using digital selective calling (DSC). These communications take place across the maritime mobile service bands within 1.6–26.5 MHz as defined by the International Telecommunication Union (ITU) Radio Regulations [24]. More importantly there is currently considerable worldwide effort being applied to further expand the use of GNSSs by civilian users in general and the civil aviation community in particular. This effort is being directed toward switching from systems under military control to systems under civil control. Scientific studies and technical reports have supported a variety of work in these areas, but here focus is on the Earth's ionosphere's important role. One of the main reasons is related to the fact that this ionosphere is a medium of communication inexhaustible, not polluting and extremely economic especially for its role of possible backup in case of blackout of other systems.

However, the highly complex nature of the Earth's ionosphere, and its potential for huge spatial and temporal variability, is such that a very large number of modeling scenarios is required in general and coastal and marine environments in particular. It has been briefly shown that the algorithms used in this study can be tuned and optimized so as to meet the basic requirements, even under the worstcase space weather conditions [25]. The SIRM, and its real-time updating version SIRMUP, provides regional type of a self-consistent model initialization specifying most important ionospheric characteristics foF2 and M(3000)F2 at a given time, while the GIFINT approach could assess specifications and forecasts of ionospheric variables on a local level. This further enhances the necessity for a large number of varied scenarios to be used for verification purposes.

Problems of data shortage, within the Mediterranean and North African regions, and a potential lack in confidence in the performance of models based on such limited data sets have taken on greater importance in recent years. As real-time system operations and integrated management are becoming increasingly present in many domains within geophysics, which requires an increased amount of data with high spatiotemporal resolution, synthetic data is required to augment recorded data and to ensure that a wide variety of ionospheric conditions are tested and an associated model is verified.

## Acknowledgements

Data sources are acknowledged as follows: the Space World Data Centre for Solar-Terrestrial Physics (STP) at STFC Rutherford Appleton Laboratory for operation of the ionosonde at Chilton and data access via (http://www.ralspace.stfc.ac.uk/ RALSpace/); the Cyprus digital ionosonde station in Nicosia, the Helmholtz Centre Potsdam of GFZ, and the German Research Centre for Geosciences for the production of Kp data (http://www.gfz-potsdam.de/en/kp-index/); the WDC for

Geomagnetism, Kyoto, for the production of Ds index (http://wdc.kugi.kyoto-u.ac. jp/); and the International GNSS Service (IGS) for providing GNSS open data (http://www.igs.org/).

References

Springer; 2014

Verlaig; 2006

2005RG000193

1928;41:43-59

University Press; 1962

1983;18:477-492

Data Service; 1972

121

[1] Zolesi B, LjR C. Ionospheric

New York, Dordrecht, London:

Springer Geophysics. Cham, Switzerland: Springer Nature Switzerland AG; 2019

[3] Lanza R, Meloni A. The Earth's Magnetism, an Introduction for Geologists. Heidelberg: Springer-

[4] Prölss GW. Physics of the Earth's Space Environment: An Introduction. Berlin, Heidelberg: Springer; 2004

ionosphere: Patterns and processes for total electron content. Reviews of Geophysics. 2006;44. DOI: 10.1029/

[6] Appleton EV. Some notes on wireless methods of investigating the electrical structure of the upper atmosphere. I. Proceedings of the Physical Society.

[7] Ractliffe JA. The Magneto-Ionic Theory and its Applications to the Ionosphere. Cambridge: Cambridge

[8] Reinisch BW, Huang X. Automatic calculation of electron density profiles from digital ionograms 3, processing of bottomside ionograms. Radio Science.

[9] Piggot WR, Rawer K. U.R.S.I Handbook of Ionogram Interpretation and Reduction. World Data Center a for Solar Terrestrial Physics-Report UAG-23. Asheville: NOAA, Environmental

[10] Dow JM, Neilan RE, Rizos C. The international GNSS service in a

[5] Mendillo M. Storms in the

Prediction and Forecasting. Heidelberg,

DOI: http://dx.doi.org/10.5772/intechopen.90467

changing landscape of global navigation satellite systems. Journal of Geodesy. 2009;83:191-198. DOI: 10.1007/

[11] Davies K. Ionospheric Radio. IEE Electromagnetic Waves Series 31. London: Peter Peregrinus Ltd; 1990

[12] Bilitza D. International reference ionosphere 2000. Radio Science. 2001;

[13] Jones WB, Gallet RM. Ionospheric mapping by numerical methods. Telecommunication Journal. 1960;12:

[14] Zolesi B, LjR C. The role of COST actions in unifying the European

DOI: 10.5194/hgss-9-65-2018

Ionospheric regional model for

ionospheric community in the transition between the two millennia. History of Geo- and Space Sciences. 2018;9:65-77.

[15] Zolesi B, Belehaki A, Tsagouri I, LjR C. Real-time updating of the simplified

operational applications. Radio Science. 2004. DOI: 10.1029/2003RS002936

[16] Anduaga A. Wireless & Empire. Oxford: Oxford University Press; 2009

[17] Pallocchia G, Bertello I, Amata E, Consolini G, Pezzopane M, Zolesi B, et al. The GIFINT Space Weather products. Conference paper, First European Space Weather Week,

[18] Pezzopane M, Zolesi B, Pietrella M, Haralambous H, Oikonomou C, Cander

[19] Reinisch BW, Haines DM, Bibl K, Galkin I, Huang X, Kitrosser DF, et al.

LjR. Ionospheric Prediction and Forecasting Services in Mediterranean Area. Conference paper, General Assembly of the European Geophysical

Union, Wien, April 2014

Noordwijk; 2004

s00190-008-0300-3

36:261-275

Ionospheric Monitoring and Modeling Applicable to Coastal and Marine Environments

260-264

[2] LjR C. Ionospheric space weather. In:

## Conflict of interest

None.

## Author details

Ljiljana R. Cander<sup>1</sup> \* and Bruno Zolesi<sup>2</sup>


<sup>© 2019</sup> The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Ionospheric Monitoring and Modeling Applicable to Coastal and Marine Environments DOI: http://dx.doi.org/10.5772/intechopen.90467

## References

Geomagnetism, Kyoto, for the production of Ds index (http://wdc.kugi.kyoto-u.ac. jp/); and the International GNSS Service (IGS) for providing GNSS open data

Coastal and Marine Environments - Physical Processes and Numerical Modelling

(http://www.igs.org/).

Conflict of interest

None.

Author details

Ljiljana R. Cander<sup>1</sup>

120

\* and Bruno Zolesi<sup>2</sup>

1 Rutherford Appleton Laboratory, Harwell Oxford, UK

2 Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

\*Address all correspondence to: ljiljana.cander@stfc.ac.uk

provided the original work is properly cited.

[1] Zolesi B, LjR C. Ionospheric Prediction and Forecasting. Heidelberg, New York, Dordrecht, London: Springer; 2014

[2] LjR C. Ionospheric space weather. In: Springer Geophysics. Cham, Switzerland: Springer Nature Switzerland AG; 2019

[3] Lanza R, Meloni A. The Earth's Magnetism, an Introduction for Geologists. Heidelberg: Springer-Verlaig; 2006

[4] Prölss GW. Physics of the Earth's Space Environment: An Introduction. Berlin, Heidelberg: Springer; 2004

[5] Mendillo M. Storms in the ionosphere: Patterns and processes for total electron content. Reviews of Geophysics. 2006;44. DOI: 10.1029/ 2005RG000193

[6] Appleton EV. Some notes on wireless methods of investigating the electrical structure of the upper atmosphere. I. Proceedings of the Physical Society. 1928;41:43-59

[7] Ractliffe JA. The Magneto-Ionic Theory and its Applications to the Ionosphere. Cambridge: Cambridge University Press; 1962

[8] Reinisch BW, Huang X. Automatic calculation of electron density profiles from digital ionograms 3, processing of bottomside ionograms. Radio Science. 1983;18:477-492

[9] Piggot WR, Rawer K. U.R.S.I Handbook of Ionogram Interpretation and Reduction. World Data Center a for Solar Terrestrial Physics-Report UAG-23. Asheville: NOAA, Environmental Data Service; 1972

[10] Dow JM, Neilan RE, Rizos C. The international GNSS service in a changing landscape of global navigation satellite systems. Journal of Geodesy. 2009;83:191-198. DOI: 10.1007/ s00190-008-0300-3

[11] Davies K. Ionospheric Radio. IEE Electromagnetic Waves Series 31. London: Peter Peregrinus Ltd; 1990

[12] Bilitza D. International reference ionosphere 2000. Radio Science. 2001; 36:261-275

[13] Jones WB, Gallet RM. Ionospheric mapping by numerical methods. Telecommunication Journal. 1960;12: 260-264

[14] Zolesi B, LjR C. The role of COST actions in unifying the European ionospheric community in the transition between the two millennia. History of Geo- and Space Sciences. 2018;9:65-77. DOI: 10.5194/hgss-9-65-2018

[15] Zolesi B, Belehaki A, Tsagouri I, LjR C. Real-time updating of the simplified Ionospheric regional model for operational applications. Radio Science. 2004. DOI: 10.1029/2003RS002936

[16] Anduaga A. Wireless & Empire. Oxford: Oxford University Press; 2009

[17] Pallocchia G, Bertello I, Amata E, Consolini G, Pezzopane M, Zolesi B, et al. The GIFINT Space Weather products. Conference paper, First European Space Weather Week, Noordwijk; 2004

[18] Pezzopane M, Zolesi B, Pietrella M, Haralambous H, Oikonomou C, Cander LjR. Ionospheric Prediction and Forecasting Services in Mediterranean Area. Conference paper, General Assembly of the European Geophysical Union, Wien, April 2014

[19] Reinisch BW, Haines DM, Bibl K, Galkin I, Huang X, Kitrosser DF, et al. Ionospheric sounding in support of over-the-horizon radar. Radio Science. 1997;32(4):1681-1694

[20] Francis DB, Cervera MA, Frazer G. Performance prediction for design of a network of sky wave over-the-horizon radars. IEEE Aerospace and Electronic Systems Magazine; 2017;32(12):18-28. DOI: 10.1109/MAES.2017.170056

[21] Pezzopane M, Pietrella M, Pignatelli A, Zolesi B, Cander LR. Assimilation of autoscaled data and regional and local ionospheric models as input sources for real time 3D international reference ionosphere modeling. Radio Science. 2011;46. DOI: 10.1029/2011RS004697

[22] Artru J, Lognonné P, Occhipinti G, Crespon F, Garcia R, Jeason E, et al. Tsunamis detection in the ionosphere. Space Research Today. 2005;163:23-27

[23] Zolesi B, Bianchi C, Meloni A, Baskaradas JA, Belehaki A, Altadill D, et al. "SWING": A European project for a new application of an ionospheric network. Radio Science. 2016. DOI: 10.1002/2016RS006037

[24] The Radio Regulations as adopted by the World Radiocommunication Conference (WRC-15, Geneva), Edition of 2016

[25] Lanzerotti LJ. Space weather: Historical and contemporary perspectives. Space Science Reviews. 2017;212:1253-1270. DOI: 10.1007/ s11214-017-0408-y

Ionospheric sounding in support of over-the-horizon radar. Radio Science.

[21] Pezzopane M, Pietrella M, Pignatelli A, Zolesi B, Cander LR. Assimilation of autoscaled data and regional and local ionospheric models as

input sources for real time 3D international reference ionosphere modeling. Radio Science. 2011;46. DOI:

[22] Artru J, Lognonné P, Occhipinti G, Crespon F, Garcia R, Jeason E, et al. Tsunamis detection in the ionosphere. Space Research Today. 2005;163:23-27

[23] Zolesi B, Bianchi C, Meloni A, Baskaradas JA, Belehaki A, Altadill D, et al. "SWING": A European project for a new application of an ionospheric network. Radio Science. 2016. DOI:

[24] The Radio Regulations as adopted by the World Radiocommunication Conference (WRC-15, Geneva), Edition

[25] Lanzerotti LJ. Space weather: Historical and contemporary

perspectives. Space Science Reviews. 2017;212:1253-1270. DOI: 10.1007/

10.1029/2011RS004697

10.1002/2016RS006037

s11214-017-0408-y

of 2016

122

[20] Francis DB, Cervera MA, Frazer G. Performance prediction for design of a network of sky wave over-the-horizon radars. IEEE Aerospace and Electronic Systems Magazine; 2017;32(12):18-28. DOI: 10.1109/MAES.2017.170056

Coastal and Marine Environments - Physical Processes and Numerical Modelling

1997;32(4):1681-1694

## *Edited by José Simão Antunes Do Carmo*

This book systematizes the concepts of contemporary coastal zone management and suggests possible structural and non-structural management tools for decision-making processes. Some successful adaptation measures and case studies on oceanic processes and coastal protection are discussed. High-frequency communications in coastal and marine environments are also addressed.All chapters contribute relevant information and useful content to scientists and other readers interested or concerned about the lack of adequate management actions and the installation of appropriate protections or their ineffectiveness in containing coastal vulnerabilities and risks.

Published in London, UK © 2020 IntechOpen © Falco Negenman / unsplash

Coastal and Marine Environments - Physical Processes and Numerical Modelling

Coastal and Marine

Environments

Physical Processes and Numerical Modelling

*Edited by José Simão Antunes Do Carmo*