Keywords

10.1 Introduction

Satellites are unique sources of information about the surface of the Earth and its atmosphere and they are used by many scientists to improve the knowledge of our planet. The science of satellite remote sensing started back in the 1950s and is mainly based on our understanding of the physics of the interaction of electromagnetic radiation with different Earth’s surface geophysical parameters or atmospheric gases and particles. Such understanding of the interaction of electromagnetic radiation including absorption, emission, scattering, and reflection is important for the interpretation of data and images collected by different satellite sensors.

Historically, the capability of the satellites to provide information about the Earth goes back to1957, when Sputnik 1 was launched by the former Soviet Union. It was the first satellite that orbits around the Earth. Then came the USA TIROS series of satellites which were mainly used for metrological applications. The first satellite to monitor the Earth’s surface has been recognized in 1972 when Landsat-1 was launched. Now we have more than 3000 satellites orbiting the Earth and serving many vital applications. By satellites images, the geologist can observe many geological features (i.e., faults, folds, stratigraphy, and landform), distribution of groundwater, and location of natural resources (i.e., oil, gas, and mineral deposits).

The majority of Earth’s observational satellites carry passive sensors that measure either the reflected solar radiation in the visible or near-infrared regions or measure the natural emitted radiation from the Earth in the infrared or the microwave regions. Some satellites carry active sensors such as Altimeters, Radars, and Lidars that send signals and then record the reflected or backscattered radiation from different targets on Earth.

Kuwait is potentially facing both natural and anthropogenic hazards. This can range from dust storms, floods, fires, oil spills, and other hazards. Remote sensing is an important tool to support the decision-makers in the government with vital technical information to manage these hazards through all disaster management cycles, i.e., disaster preparedness, mitigation, response, and recovery (Eguchi et al., 2008; Thomas & Kemec, 2007). Kuwait Institute for Scientific Research (KISR) established a Decision Support System for crises management in Kuwait using the necessary decision support tools including remote sensing.

A remote sensing facility was developed to provide near real-time remote sensing monitoring on a 24/7 basis. The sensing operational archive is integrated based on several satellite missions covering Kuwait including middle-resolution optical scanners MODIS, VIIRS; high-resolution constellations Planet, Pleiades, LANDSAT; and Sentinel family: Sentinel-2, Sentinel-3, and Sentinel-1 C-band SAR and TerraX X-band SAR. This allows appropriate timing for data collection during cloudy periods, day and night as well as space and spectral resolution for observed disaster phenomena. Operational remote sensing monitoring identifies the land and marine environmental high-risk and accident areas, which can be a threat to the Kuwaiti environment hazards (Misak and Al-Dousari, 2012).

Kuwait is currently facing a possible potentially extensive and harmful scope of both natural and anthropogenic hazards. Hazards in Kuwait vary in nature, magnitude, and consequences. They are differentiated into man-related hazards (anthropogenic/technologic) and natural hazards. Man-related hazards are reported including fires, nuclear accidents, oil spills, and notable industrial activities associated with environmental crises such as oil refineries, oil gathering centers (GCs), petrochemical industries as well as thermal power plants (Girin & Carpenter, 2017; Li et al., 2016). Natural hazards are classified into geophysical (earthquakes of low magnitude), meteorological (dust and sand storms and drought), and surface hydrological (flash floods) (Bou-Rabee, 1994; Misak et al., 2013; Hassan et al., 2021). Unfortunately, these natural and anthropogenic crises are expected to continue and maybe increased in frequency and severity with the advance of climate changes. Meteorological hazards including dust and sandstorms and flash floods and oil spills are major hazards afflicting Kuwait with a focus on Kuwait City in the last few years. In 2018, Kuwait experienced the most severe dust storms in the summer, as well as flash floods which resulted in economic losses and death. Remote Sensing was an important tool for the observation of these hazards and providing an early warning (Manche, 2014).

10.2 Field Measurements of Soil Moisture in Kuwait by Remote Sensing

Soil moisture is an important geophysical parameter for hydrological, climate, and weather model predictions. In arid regions around the world, soil moisture is the main environmental factor that restricts plant growth and vegetation restoration, and it is an important index reflecting soil characteristics (D’Odorico et al., 2007). Many factors such as climate, topography, elevation, slope, vegetation, and soil properties affect soil moisture.

Remote sensing and field measurement of soil moisture in the desert of Kuwait has a long history since the year 2000. About 100 soil samples were collected from several locations in the north area of Kuwait during the Shuttle Radar Topography Mission (SRTM) mission in February–March 2000 (Al Jassar et al., 2006). In the laboratory, the collected samples were immediately weighed and dried in an oven at a temperature of around 105 °C for 24 h. Then, the gravimetric soil moisture was estimated. The result of soil moisture contents for these samples was estimated from 1 to 11% with an average of 3.88%. In addition, the salinity, soil texture, specific density bulk density, and surface roughness were also measured. The analysis indicates that sand is the main content of all samples and the bulk density with an average of 1.2 g cm−3, while the specific density average about 2.65 g cm−3. In the same study, a simple statistical inversion model was developed to retrieve soil moisture from microwave satellite brightness temperatures, based on two frequencies (Al Jassar et al., 2006). The model was applied to retrieve soil moisture from Nimbus-7 SMMR brightness temperature (Tb) data at two bands (Tb(H) of 6.6 GHz and Tb(V) of 37 GHz) for six years (1979–1985). The volumetric soil moisture was found to range from 0.01 m3 m−3 (in dry summer) to 0.13 m3 m−3 (during the rainy season), with an average of 4%, Fig. 10.1. The simple inversion model is applicable to the desert of Kuwait, due to the scanty vegetation cover and moderate roughness.

Fig. 10.1
A graph of soil moisture versus years illustrates the time series of retrieved soil moisture. It plots 2 fluctuating lines: daytime at 11 A M and midnight at 12. The line for night has the highest peak.

Graph representing the time series of retrieved soil moisture during the day (11 am) and night (12 midnight) passes (Al Jassar et al., 2006)

The second major campaign was conducted from Dec-2005 to March-2006 nearby Al-Abdaly, North of Kuwait (Al-Jassar & Rao, 2010). During this campaign about Forty-five soil samples were collected in synchronous with the Advanced Microwave b Scanning Radiometer-Earth Observing System (AMSR-E) covering an area of one pixel of 25-km circular diameter Fig. 10.2a. A comparison was done between Field-estimated soil moisture values up to 5 cm depth, AMSR-E soil moisture values, and our model results. The result indicates that the field soil moisture values are consistently lower than AMSR-E and model values. This difference can be considered within the error value Also, the result indicates the similarity value of AMSR-E soil moisture and our model values. To study the temporal and spatial variation of soil moisture, monthly average soil moisture maps for the State of Kuwait were produced from AMSR-E data Fig. 10.2b (Al-Jassar & Rao, 2010).

Fig. 10.2
2 image. A has 2 grid graphs highlighting Kuwait and locating soil moisture using A M S R - E pixel. B is the color-contoured graph of monthly average soil moisture in Kuwait.

a Location of AMSR-E pixel with 25 km in diameter where 45 samples were collected (Al-Jassar & Rao, 2010). b Monthly Average Soil Moisture Map of Kuwait

The third campaign experiment to measure soil moisture was from April 2011 to September 2013 within KISR experimental research station in Kabd area (Al Jassar & Rao, 2015). The samples were collected from 16 sites within a 50 km2 area (Fig. 10.3). The field soil moisture measurements were compared in synchronous with soil moisture data from AMSR-E, which passes over the Kuwait desert, (Fig. 10.4) (Al Jassar & Rao, 2015). The lowest soil moisture was measured in September with a value of 0.01 m3 m−3, while the highest was in December during the wet season with a value of 0.11 m3 m−3. In a similar way, AMSR-E data from 2003 to 2011 shows a seasonal variation in Monthly average Volumetric Soil Moisture values (VSM) in Kuwait. The data shows the moisture is higher during the wet season and moisture is higher, in particular, during January with a value of 0.08 m3 m−3 and lowest in the dry season in August with a value of 0.06 m3 m−3.

Fig. 10.3
2 images. A: a grid map of soil moisture field in Kuwait using A M S R-E, within the diameter of 25 kilometers. B locates the 16 sites and labels S 1, S 2, and S 3.

Soil moisture field point at KISR Site. The AMSR-E 25-km grid is superimposed on the left image. The soil classification map is overlaid on the right image (Al Jassar & Rao, 2015)

Fig. 10.4
A line graph of soil moisture versus months from January to December plots 9 lines for the years 2003 to 2011. The highest value is marked by line 2008 in January.

Monthly average Soil moisture variations (2003–2011) (Al Jassar & Rao, 2015)

In the fourth field campaign, a total of 322 soil samples were collected in 2016 from Al-Salmi west of Kuwait within an area of 36 km by 36 km (Fig. 10.5) (AlJassar et al., 2019). The samples were collected from7:30 a.m. to 5:30 p.m. on 20 February 2016 and 19 March 2016. The in-situ field soil moisture measurements were then compared with data obtained from Special Sensor Microwave/Imager (SSM/I), European Space Agency Soil Moisture and Ocean Salinity (SMOS), NASA Soil Moisture Active Passive (SMAP), and Advanced Microwave Scanning Radiometer 2 (AMSR2). During this campaign, a large range of soil moisture values was observed due to precedent rain events and subsequent dry down. The statistical analysis of the VSM of collected samples shows a low variability of Mean Relative Difference (M) RD = −0.005 m3m−3. This indicates the stability of volumetric water content spatially and temporally over the selected site. This variability of the MRD values indicates the presence of differences in soil moisture values within the study site, which is possibly related to the soil heterogeneity (Fig. 10.6) (AlJassar et al., 2019). In relation to the topography, The study found that there is no clear correlation between soil moisture and elevation. This could be related to the nature of drainage patterns in the desert environment.

Fig. 10.5
2 maps. A: a color-contoured map highlights the 14 sites of soil tests. B: a map of Kuwait has markings of study area boundary, kuroad, location, and station.

The test site 36 × 36 km with 14 soil types showing six in-situ stations. The work in this paper focuses on the dominant landscape (Cp06, Cp07, GP03, Gp11, Gp 16, and Gp 19) (AlJassar et al., 2019)

Fig. 10.6
2 maps: the left has a cluster of small to big circles depicting soil moisture in February and the right has a cluster of small to big circles depicting soil moisture in March.

Spatial distribution of the measured VSM on February 20th, 2016 (left). Spatial distribution of the measured VSM on March 19th, 2016 (right) (AlJassar et al., 2019)

Kuwait University team was selected by the NASA SMAP science team as an international partner in the calibration and validation of soil moisture data from the Active and Passive Satellite (SMAP) mission which was launched on 31st January 2015. Kuwait’s site is located in the desert on the west side of Kuwait, and it is the only test site in the Middle East for the pre-launch and post-launch calibration and validation activities of NASA SMAP satellite data (Fig. 10.7) (Colliander et al., 2017). The test site has exceptionally homogeneity of land surface conditions and possesses six permanent stations to measure soil moisture at different depths. SMAP soil moisture data are compared with the automated station’s measurements of soil moisture in Fig. 10.8. The Kuwait University team conducted different gravimetric soil moisture measurements next to each station to validate the station’s measurement at 5 cm depth. The ground soil moisture measurements were compared with SMAP 36 km, 9 km, and 3 km resolution of soil moisture data from 2015 to 2020.

Fig. 10.7
A world map of the N A S A schedule management plan marks the test sites including Kuwait, as it is the only test site in the middle east.

NASA SMAP Core Validation Sites showing Kuwait test site which is the only test site in the middle east. [TJ (Colliander et al., 2017)

Fig. 10.8
2 photos. A is an automatic weather station in Kuwait and B is a photo of 3 people testing the ground during field validation sampling.

Automatic Weather Station and field validation sampling during the NASA/SMAP project

Fig. 10.9
A world map of S M A P soil moisture depicts north and southern parts of Africa, most of Asia and Australia, and other countries in low concentration.

SMAP Soil Moisture Over the Globe (JPL/NASA/Photojournal)

10.3 Land Subsidence in Burgan Oil Field in Kuwait

Land subsidence is a very common phenomenon wherever underground activities are in progress such as oil and water extraction, coal mining, and underground rail network. Land subsidence is a major problem in many countries and comes under disaster management. Though land subsidence is a problem in Kuwait oil fields due to oil extraction and other geological factors, no reliable data is available on this subject. Differential Synthetic Aperture Radar Interferometry technique is applied over Burgan oil field of Kuwait to assess the land subsidence. Thirty-five subsidence maps are generated with the temporal resolution varying from 35 to 630 days (Fig. 10.10) shows the subsidence map of the Burgan oil field which is the net result of processing 35 subsidence maps. It can be seen from Fig. 10.24 that as high as 4.1 mm/100 days subsidence is noticed in the southern portion of the Greater Burgan Oil Field. The subsidence slowly decreases as we move north of the oil field (Rao et al., 2011).

Fig. 10.10
A color-contoured map of the Great Burgan oil field depicts the subsidence in the area. The bottom ends and the sides of the field have concentrations with negative values. Values of legends are mentioned on the right.

Subsidence image of Greater Burgan Oil Field generated through least square technique. Most parts of the study area are free from subsidence. The southern portion shows subsidence of 4 mm/100 days and the northern portion shows upliftment of 1 mm/100 days (Rao et al., 2011)

Another study addresses the spatial variability of land subsidence over the Minagish and Umm Gudair oil fields of Kuwait. Synthetic Aperture Radar Interferometry technique coupled with Interferometric Point Target Analysis (IPTA) approach is used in this study. 29 scenes of ENVISAT ASAR data (for the period January 2005–August 2009) (Rao & Al-Jassar, 2010) were used to make 20 pairs of interferograms (with high coherence and low noise) for IPTA analysis (Fig. 10.11). The output of this study is the land subsidence map of Minagish and Umm Gudair oil fields with a spatial resolution of 40 m. The results indicate that there is land subsidence of 8 mm/100 days on the southern part of the oil field (Umm Gudair) (Fig. 10.12).

Fig. 10.11
An image by the environment satellite marks the oil fields in Kuwait: Burgan, Minagish, and Umm Gudair.

ENVISAT scene acquired on 20-JAN-2007 showing Burgan, Minagish, and Umm Gudair Oil fields (Rao & Al-Jassar, 2010)

Fig. 10.12
A color-contoured map of the Minagish and Umm Gudair oil fields' final average velocity has the labels of the regions. Values of legends are mentioned on the right.

The final average velocity map (Geo-coded) of Minagish and Umm Gudair oil fields. The subsidence was estimated with reference to 28.97 N, 47.59E. The color coding is given on the right side of figure. The boundary of the oil fields is superimposed (Rao & Al-Jassar, 2010)

10.4 Flash Flood

Kuwait like most parts of the Arabian Peninsula is a desert-type environment with scanty rainfall (Al-Awadhi et al., 2005). As a result, when heavy rains occur, they often cause flash floods that can be very destructive. In Kuwait, flash floods, which are generally associated with heavy rainfall events over short durations, have caused millions of dollars worth of damage in the country, wreaking havoc on roads, bridges, and homes (Misak and Al-Dousari, 2012). In 2018, Kuwait experienced a great flash flood during the period from 4 to 14 November, and many urban communities of the country were exposed to devastating floods, in particular, southern urban areas. It was an extreme event with an average rainfall value of 151 mm. This event considered the third-largest destructive flash floods occurred in Kuwait causing damages more than 900 million dollars, with roads and tunnels paralyzed by an accumulation of clay following heavy rains. The flooded areas have been evacuated and local municipalities have begun a huge cleanup operation to clear roads and highways. The rainfall was accompanied by thunderstorms and gusts reaching up to 115 km/h. In this study, we will present flash flooded urban areas as seen by satellite images with flood hazard analysis, extent, and depth of flood over the flood-prone area during this event.

10.4.1 Flood Event Analysis (November 2018)

In 2018, from the 4th to 14th of November, a rainfall event occurred; it was an extreme event with an average rainfall value of 150 mm. Among the 16 meteorological stations, the highest total rainfall during that period was at Kuwait Airport station which reached 190 mm, while the daily rainfall was the highest recorded at Al-Taweel station on the 14th of November which was about 101 mm. The daily rainfall recorded among the 16 stations is tabulated and illustrated in Table 10.1 and Fig. 10.13 (Misak & Raafat, 2015; KMD, 2020). Figure 10.13 clarifies the spatial variation of rainfall, total rainfall of the entire event, recorded in each station across Kuwait. The map shows that the southern sector of the state of Kuwait is highly subjected to intensive rainfall. The remote sensing was used to delineate the flooded area within the urban area, in addition, using to uphold the rainfall event, a MODIS satellite image of cloud cover over the Kuwait region was extracted from 4th November to 14th November 2018. The data was downloaded from the USGS website for the respective days and the enhanced image along with the wind direction in the region is illustrated from Figs. 10.15, 10.16 and 10.17. The images depict that the direction of the wind during rainy days is mostly from the south to north or south to north-east and the cloud cover is the highest on the 14th of November (Fig. 10.14).

Table 10.1 Daily Rainfall recorded at various stations in Kuwait. (KMD 2020)
Fig. 10.13
A grouped bar graph of rainfall versus days from 4th to 14th November in 2018 in 16 areas. The highest rainfall is on 14th November 2018. Among them, Al- Taweel has the highest rainfall.

Daily Rainfall plot for 2018 Flood event at all stations

Fig. 10.14
A contour map of Kuwait plots the rainfall distribution between 4th to 14th November 2018. It marks the rainfall stations. The southern regions of Kuwait receive the highest rainfall. The inlet map highlights Kuwait from neighboring nations.

Spatial variation of total rainfall from 4 to 14th November 2018

Fig. 10.15
2 images. A: a satellite image of Kuwait with a cloud cover and a sketch to indicate its boundary and a dot to locate places. B is the wind field map of the study area. Its direction is towards the north and northeast.

Cloud cover extent and wind movement on 04th November 2018

Fig. 10.16
2 images. A: a satellite image of Kuwait with a cloud cover and a sketch to indicate its boundary and a dot to locate places. B is the wind field map of the study area. Its direction is towards the northeast.

Cloud cover extent and wind movement on 10th November 2018

Fig. 10.17
2 images. A: a satellite image of Kuwait with a cloud cover and a sketch to indicate its boundary and a dot to locate places. B is the wind field map of the study area. Its direction is towards the northeast.

Cloud cover extent and wind movement on 14th November 2018

10.4.2 Flash Hazard Assessment

An estimation of probabilistic flood extent and corresponding flood water depths for the entire State of Kuwait during the rainfall of Nov 2018 (Hassan et al., 2021) was done using hydrological and hydraulic modeling. For that purpose, the State of Kuwait was divided into 70 basins with a catchment area from 1 km2 to 10,300 km2. Only 10 large basins were having a catchment area between 500 km2 to 10,300 km2 (Fig. 10.18). Others were small basins having an area under 500 km2 and mostly these small basins were located along the coast. The flood extent and the depth were also simulated for one of the very heavy rain events that occurred from 4th–14th November 2018 in Kuwait. Flood extent for the entire Kuwait is governed by rainfall, drainage profile, and topography of the study area. Flood modeling for Kuwait shows that the southern area of Kuwait was highly susceptible to higher floodwater depth during heavy rainfall events. The flood depths were computed at most up to and to less extent between 1 to 2 m (Fig. 10.19). In southern Kuwait near Al-Taweel station, where there is the highest rainfall, the flooding depth reached more than 3 m.

Fig. 10.18
A map of Kuwait marks the major ten basin areas. Legends for the national capital, outlet, basin, and country boundary are marked. The inlet map highlights Kuwait from neighboring nations.

Map showing the ten Major basin areas in Kuwait

Fig. 10.19
A map to study the flood inundation during November 2018 rainfall has legends for flood depth. Heavy flood is observed in Umm Gudayr, and Al Burgan. The inlet map highlights Kuwait from neighboring nations.

Flood inundation map for November 2018 rainfall event

10.4.3 Urban Areas Flash Floods in 2018

In Nov 2018 flash flood events, the urban area in Kuwait witnessed intensive flooding because the quantity of rainfall is more than sewage and drainage systems are capable to drain within the urban areas. The southern urban area is mostly affected by flash floods in particular Al-Ahmadi Governorate. Figure 10.19 shows many water bodies accumulated in low terrain areas and mostly in sabkha. This governorate is located about 33 km south of Kuwait City with a total area of about 5,000 km2 and a population of 679,527 inhabitants. Most of the communities are located in the eastern of the Ridge called AL-Ahmadi ridge. It is a ridge that runs parallels to the southern coastline and rises to heights of about 137 m above sea level and is dissected a 116 shallow wadi and tributaries of the length of approximately 69 km located on the eastern and the western side of Kuwait (Hassan et al., 2021) (Fig. 10.20). The eastern wadis are pouring into the Arabian Gulf crossing some urban areas. In case of heavy rains for a few hours, similar to the Nov 2018 flash flood, the floods start from the top of the ridge and the rainfall water continues to flow east through drainage channels directed to the urban areas (Fig. 10.21). The western wadis flow toward the Burgan oil field and nearby areas. Figure 10.22 shows satellite images of some oil facilities including pipelines and oil gathering centers that are damaged by flash flooding.

Fig. 10.20
A satellite image of southern Kuwait with the land areas, roads, buildings, and water bodies.

Satellite images in southern Kuwait showing water bodies in low land areas

Fig. 10.21
3 images. A: a map of the Wadi system in Kuwait near the coastal area with values of legends in it. B and C are magnified satellite views of the eastern and western sides of the Al-Ahmadi ridge.

Wadi System over Kuwait and in the eastern and western side of Al-Ahmadi Ridge south of Kuwait

Fig. 10.22
A set of two satellite images of the flooded areas of Al-Ahmadi on the left and the Burgan oil field on the right.

Flooded area within Al-Ahmadi and Burgan oil field

Sabah Al-Ahmad is a recently established residential area located in the State of Kuwait about 76 km away from Kuwait city. Satellite images with GIS maps show several drainages trending from the Northwest to Southeast direction crossing the city (Fig. 10.23). During the 2018 rainfall, the city was flooded and many houses were drawn due to the crossing of this drainage within the urban area (Fig. 10.24). Most of the drainage drain into the inland sabkha South of Sabah Al-Ahmad. These sabkhas caused a body of water that accumulated due to limited infiltration of rainfall and hence flooded back to the city.

Fig. 10.23
A satellite image of urban areas and wadis in the Sabah Al-Ahmad region. Also, it indicates the streams with lines.

Satellite image and wadis within Sabah Al-Ahmad Urban area on 12 November

Fig. 10.24
2 photographs. A: a water body with a shore on one end and buildings on the other end. B: the movement of cars on the flooded roads.

Flooding of Sabah Al-Ahmad Urban area in November 2018

10.5 Transboundary Dust Storm Jets from Southern Iraq to Kuwait

Kuwait is in the northwestern part of the Arabian Gulf and shares borders with Saudi Arabia and Iraq. (Al-Awadhi et al., 2014; Al-Dabbas et al., 2012; Al-Dousari et al., Ahmed, 2017) defined the major source areas of dust for Kuwait. They are from the western desert of Iraq, the Mesopotamian flood plain in Iraq, the northern desert of Saudi Arabia, drained marshes in southern Iraq, and the dry marshes and abandoned farms in Iran. Figure 10.25 depicts the regional dust sources around Kuwait and the seasonal wind patterns in and around Kuwait. Since the winds dominantly blow from north and northwesterly directions during the summer months (mostly dry conditions) starting from April to October, this leads to frequent dust storms over Kuwait during the summer months as compared to the rest of the years called Shamal winds (Yassin et al., 2018). This causes frequently transboundary dust storm events in the state of Kuwait.

Fig. 10.25
2 images of in and around Kuwait. A: a schema with seasonal wind patterns using arrows and other legends for dust sources. B: the map of Bubiyan labels the sources of dust emission.

Source Al-Dousari and Al-Awadhi (2012)

Schematic diagram of the (a) Seasonal wind patterns in and around Kuwait (b) Sources of dust emission in and around Kuwait.

Kuwait is heavily influenced by dust storms from southern Iraq, particularly from the area located 250 km from its northern border which is considered a “hot spot” (Fig. 10.26). The “hot spot” recorded the largest monthly fallen dust weights in Iraq (200-250 g/m2/month) (Al-Dabbas et al., 2012). Remote sensing satellites have identified that intensive dust jets originate from this “hot spot” area, and it is most active in the summer months between May and July. To a lesser extent, other arid sources in the vast desert area in western Iraq also contribute to dust events; however, these dust storms do not constitute a major concern to Kuwait (Al-Awadhi et al., 2014; Al-Dousari et al., 2017). The particular “hot spot” area is located within the Mesopotamian flood plain, Samawah and Abu Jir lineaments; located between three major southern Iraqi cities (Al-Samawah, Al-Diwaniya, and Al-Nasriya); and stretches along with two provinces (Al-Muthana and Thi-Qar).

Fig. 10.26
A satellite picture of a dust storm over Kuwait and a mark of the hot spot area.

Dust storm over Kuwait originated from the “hot spot” area, MODIS Aqua (500 m/pixel), June 05, 2008

Moderate Resolution Imaging Spectroradiometer (MODIS) images from NASA’s Terra and Aqua satellites have identified that the size of the “hot spot” area has been shrinking during the past 35 years (1986–2020) (Table 10.2 and Fig. 10.27). MODIS Terra and Aqua satellite images were collected from 2008 to 2021 (14 years). Remote sensing satellite images from NASA GSFC OBPG Ocean color Level 0 from Local Area Coverage were processed and generated. Image processing included the true color based on RGB composition of Bands 1, 4, 3 and false color based on RGB compositions of Bands 2, 1, 1 and Bands 6, 5, 4. The B211 composition was mainly used for best MODIS resolution (250 m/pxl) and shows water as black color due to the use of red and NIR bands, vegetation as red color, shallow water as cyan color, and bared desert as white color. The real color composition B143 was used to obtain dust jet delineation of moderate resolution (500 m/pxl) and shows water as dark blue, dust jets as light yellow/bluish, and local sand jets as dark brownish from dry farmlands or overgrazing areas.

Table 10.2 The size of the “hot spot” area in southern Iraq (1986–2020)
Fig. 10.27
A set of four satellite images of southern Iraq in the years 1986, 2006, 2016, and 2020 represents the hot spot area highlighted in oval markings.

The “hot spot” area in southern Iraq (1986–2020)

Local dust storm jets within Iraq and Kuwait were originally discovered by (Peter & Al-Awadi, 2010) and confirmed by (Al-Hemoud et al., 2020). Historical MODIS images showed that thick clouds of dust just originate from the “hot spot” area in southern Iraq and cross over Kuwait (Fig. 10.28). Intensive dust storm jets from the “hot spot” area can travel long distances crossing Kuwait into the northern part of the Arabian and eastern Saudi Arabia (Fig. 10.29). Oftentimes, dust jets are carried by the northwesterly winds directly into Kuwait urban areas (Fig. 10.30), and the increased frontogenesis between the hot and dry atmosphere over the desert and the moist intrusions from the Arabian can create a cyclone over the area (Francis et al., 2021).

Fig. 10.28
A satellite picture of Kuwait indicates the hot spot area of dust storm origin.

Dust storm over Kuwait originated from the “hot spot” area, MODIS Aqua (500 m/pixel), July 05, 2012

Fig. 10.29
A satellite picture of Kuwait indicates the hot spot area of dust storm origin marked by a circle.

Dust storm over Kuwait originated from the “hot spot” area, MODIS Aqua (250 m/pixel), July 28, 2018

Fig. 10.30
A satellite picture of Kuwait highlights the hot spot area of dust storm origin, the dry lands in the south of Basra in Iraq, and the borders between the southwest of Iran and southeast of Iraq in circles.

Dust storm over Kuwait originated from the “hot spot” area, MODIS Aqua (500 m/pixel June 11, 2021. a red circle: “hot spot” area in southern Iraq, b black circle: drylands south of Basra, Iraq (Al-Faw), c green circle: dry land at the borders between the southwest of Iran and southeast of Iraq

Recently, on June 11, 2021, an intense dust storm blew from the “hot spot” area in southern Iraq and had a detrimental impact on Kuwait (Figs. 10.31 and 10.32). MODIS Terra acquired a true-color image of long, thick plumes of dust jets stretching from southern Iraq into Kuwait and the Arabian Gulf. Dust jet emissions started to rise from the “hot spot” area as strong winds whipped over the region on June 10, 2021. By June 11, 2021, the original gray-colored plume traveled over 500 km and stretched over Kuwait and the western coast of the Arabian Gulf. Two other dust jets were originated from two arid areas; the first dust jet originated from the drylands south of Basra, Iraq, while the second dust jet originated at the borders between the southwest of Iran and southeast of Iraq (east of Al-Faw). The dust jet continued the following day on June 12, 2021 (Fig. 10.33). A zoomed resolution (80 m) showed the high-density dust jet as whitish and the agriculture as reddish (Fig. 10.33a). The “hot spot” area is properly delineated during a non-dust day on May 16, 2021 (Fig. 10.33b).

Fig. 10.31
A satellite picture of Kuwait highlights the hot spot area of dust storm origin in a circle.

Dust storm from the “hot spot” area, MODIS Terra (250 m/pixel), June 11, 2021

Fig. 10.32
A satellite picture of a dust storm over Kuwait highlights the hot spot area of its origin in a circle.

Dust storm over Kuwait originated from the “hot spot” area, MODIS Terra (500 m/pixel), June 12, 2021

Fig. 10.33
A satellite picture of the hot spot area of dust storm origin in a magnified resolution.

A zoomed resolution (80 m) of the “hot spot” area: a during a dust jet MODIS Aqua (80 m/pxl), June 12, 2021 (Fig. 10.9a); b during a clear day, MODIS Aqua (250 m/pxl), May 16, 2021

10.6 Oil Spill Mapping

Oil is considered the most important energy source in the world. The oil spill is described as a form of pollution caused by the release of liquid petroleum hydrocarbons into the environment, especially marine areas, due to human activities (Li et al., 2016). These may be instigated by various activities, such as the release of crude oil from oil tankers, pipelines, railcars, offshore platforms, drilling rigs, and wells, as well as spills of refined petroleum products and their byproducts.

The impacts of accidental oil spills can contaminate the coastal zones and impact the high ecological quality. Spills can cause severe damage to the flora and fauna, aquaculture, and fisheries along the coast and the marine environment. The impact of an oil spill may eventually continue for several years, or maybe decades. The human activities in the Arabian Gulf cause a combination of intentional and accidental oil spills and pollution in the marine environment. The oil spills in the Arabian Gulf can be related to war-related activities, incidents release from oil tankers, offshore platforms, offshore drilling, and spills and pipeline leakages. Due to the high volume of shipping traffic in the Arabian Gulf, oil pollution is considered the main environmental concern in the Regional Organization for Protection of the Marine Environment (ROPME) Sea Area.

Kuwait is a part of the Arabian Gulf, a geographic region formed by countries having extensive reserves of crude oil. Like other countries in the Gulf region, the Kuwaiti economy relies heavily on petroleum exports, making it more susceptible to frequent oil spills and consequent marine pollution. The impact seems to vary a great deal from spill to spill, depending on the kind of oil, physical conditions, and the ecosystem affected. Based on available data, attempts were made to identify the location in the Kuwait marine environment where maximum events occurred along with the areal extents of oil spills. These oil spills also affect the economy of Kuwait. The oil spills during the Gulf war are estimated to have depleted about 2% of Kuwait’s oil reserves. At $20 a barrel, Kuwait lost about $60 million a day in revenues, which translates to $22 billion a year. On August 10, 2017, a large oil spill spot near the Kuwaiti coast, south of the State of Kuwait, leaked into the water approximately 3 km from the coast, and it is considered the largest leak in Kuwait after the gulf war. In this part, we will present the role of the remote sensing monitoring of oil spill in Kuwait and in the particular oil spill in 2017.

This study focuses on remote sensing and GIS-based mapping of oil spill events to estimate the extent of oil spills and identify hotspots in the State of Kuwait where the frequency of oil spill events is higher. Based on available data, satellite imagery is processed for estimating the extent of an oil spill. A total of 34 images were available for offshore oil spill mapping—26 images from 2018 and 6 images from 2017. However, out of these, 29 images were analyzed, due to the limitation of images available for validation.

The details of offshore oil spill data are summarized in Tables 10.3 and 10.4. Spaceborne Synthetic Aperture Radar (SAR) has proven to be very useful in oil spill detection and monitoring. Wide coverage provided by SAR-equipped satellites such as European Envisat gives a good opportunity for the development of operational oil spill applications. SAR system relies on the detection variation of the sea surface roughness. Oil films can be detected as dark patches relative to the surrounding water. In this study, we have used Sentinel-1 imagery for the detection of deepwater horizon oil spills.

Table 10.3 Data availability for offshore oil spill events from KISR
Table 10.4 Offshore oil spill extent area

Attempts were made to categorize these oil spill events considering the distance of events from Kuwait City. Oil spill events were classified into four categories, namely those between 0–50 km, 50–100 km, 100–150 km, and those more than 150 km. The extent of each oil spill event was determined by processing satellite data available from different sources and presented in Fig. 10.34. The areal extents for these events vary in range from 3 km2 to 750 km2. The majority of these events occurred between 100–150 km from Kuwait City and represent 44% of all selected offshore oil spill events (Fig. 10.35).

Fig. 10.34
A map of Kuwait with labels of its states and the offshore oil spills in the Arabian Gulf nearby.

Map showing offshore oil spills in the Arabian Gulf nearby the state of Kuwait

Fig. 10.35
A pie chart depicts the offshore oil spill with a distance in kilometers from Kuwait city. They are 0 to 50: 9%, 50 to 100: 23%, 100 to 150: 44%, and more than 150: 24%.

Distribution of Offshore Oil Spill Events in percentage with distance from Kuwait City

Figure 10.36 shows the oil spill rose diagram of the offshore oil spill events. Most of these events occurred in the southeastern direction with reference to Kuwait City. This is due to the influence of transport ships in this direction, southern ports such as Port of Mina Az Zawr, Mina Saud, Mina Al-Ahmadi, Mina Abdallah, and Ash Shuaybah. In the last few years, the number of supertankers increased in the number of these ports. Oil patches near these waiting areas are often seen in satellite images (Fig. 10.37).

Fig. 10.36
A rose diagram of the offshore oil spill in Kuwait in square kilometers with 5 legends. Most oil spill events took place in the southeast of Kuwait.

Oil spill rose diagram of offshore oil spills in Kuwait

Fig. 10.37
A set of two satellite images of the south of Kuwait with Ahmadi port on 21st November 2018 depicts the oil patches near the port.

Oil patches near Ahmadi port south of Kuwait, 21 November 2018. SAR—C, S1

On the 10th of August, a large oil spill was reported south of Kuwait near Az-zour port and about 30 km East of Qaru island (Fig. 10.38). It is estimated that about more than 35, 000 barrels of crude oil have leaked into the marine. This spill is considered the worst for the state of Kuwait in the last decades. The oil spill polluted the coastal and the marine environment south of Kuwait and causes an economic loss by shutting down some industrial ports (Fig. 10.39). Remote sensing, in this oil spill monitoring, utilizes satellites Sentinel-1, image data. These images indicated that the oil spill started in the south of Kuwait near Az-zour and then spread to the North nearby Funaits area and Nord of Ahmadi on 14th of August and finally by 16 Aug 2017 Kuwait crude oil spill patches reached Kuwait Bay and started to scatter (Fig. 10.40).

Fig. 10.38
A set of aerial images of the Az - zour port in south Kuwait on 21st November 2018 with the oil spill near the port in continuous patches.

Aerial view of the oil spill nearby Az-zour port south of Kuwait in August 2017

Fig. 10.39
3 photographs depict the effect of an oil spill. A: dark sediment on the coast. B: a floating greasy substance in a dam. C: the floating of dead fishes in the water body.

Impact of oil spill south of Kuwait causes pollution to the coastal and marine environment

Fig. 10.40
3 photographs depict the movement of the oil spill on the dates of 10th, 14th, and 16th of August 2017. The oil moves toward the land day by day.

SAR-C Sentinel-1 ESA images present the movement of the Oil spill, on 10th (a), 14th (b), and 16th (c) Aug 2017

Part of these oil spills is from natural causes. The southern marine region of the State of Kuwait is distinguished by its islands that contain coral reefs and are surrounded by sand sediments arising from the erosion of coral reefs, which are important ecosystems for the rest of the marine organisms that interact with them in terms of habitat and food resources (Al-Mohanna et al., 2014). They may be subject to potential pollution from the natural oil spill from the seabed in the marine area between the islands of Qaruh and Umm Al-Maradim, which was documented in the early nineties in that area (Literathy, 1993, 2001). Near Qaru Island, natural oil seepage is more frequent and appears at the surface as a sheen. The reason for this rise is due to the hydraulic transfer of petroleum hydrocarbons in the water column as soon as they leak from the bottom. This creates background contamination level, which affects marine life in the area. Figure 10.41 shows SAR satellite images (SENTINEL) of some large natural oil seepage around Qaru Island.

Fig. 10.41
A satellite image of Qaru Island in Kuwait on 17th August 2017 highlights a large natural seepage with dimensions of 60 kilometers in length, 24 kilometers in width, and an area of 330 square kilometers.

Kuwait Qaru Island, large natural seepage continue, 17 Aug 2017, length 60 km with 24 km, Area 330 km2

10.7 Summary

This chapter comprises the application of remote sensing in various fields such as soil moisture variation study, land subsidence across oil fields, flash floods, dust storms, and oil spills across the State of Kuwait using various satellite images.