Introduction

The coastal areas are zones of primary importance from human and ecological perspectives. Nearly all of the maritime resource is on a narrow continental shelf which is affected by ecological pressures owing to a large-scale population increase in the coastal areas (half of the world’s population lives at least 60 km from a coast, and the proportion will be 70% in 2020) (FAO 2014).

In recent years, a number of remote-sensing sensors are available to resource managers for developing effective marine ecosystem management initiatives, including the use of information technology for analyzing and understanding an ecosystem as a whole and not simply the targeted resource or a specific zone (Gutierres et al. 2016).

Remote-sensing techniques are powerful tools to obtain specific information of Earth observation, including space and temporal characteristics, and aerial observation of the coastal zone. Substances in surface water can significantly change the characteristics and properties of coastal zone (Ritchie et al. 2003). Remote-sensing data provide not only photographic representation of the coastal and marine surfaces, but also physical observations of different properties of these ecosystems. These spectral characteristics can be used to access the major factors affecting water quality in coastal water bodies (e.g., total suspended matter and dissolved organic matter) (Vanhellemont and Ruddick 2014; Tang et al. 2013; Zhu et al. 2013); (1) to identify, characterize, and analyze river plumes (Mendes et al. 2014), (2) to extract estuarine/coastal sandy bodies (Teodoro and Gonçalves 2012), (3) to identify beach features/patterns (Teodoro 2015), and (4) to evaluate the changes and integrity (health) of the coastal lagoon habitats (Vahtmäe and Kutser 2013), at various scale. In fact, the remote sensing creates new opportunities for identifying which parameters function as regulators of marine/coastal ecosystems activity at local and regional levels and how these variables differ across spatial and temporal scales.

According to our knowledge, there is no research on the total suspended sediments along the Moroccan coast using remote-sensing tool. Therefore, more studies are needed to have a detailed picture of the total suspended sediments status of this area. In this study, satellite data are used to estimate the TSM concentrations in the studied area.

Materials and methods

Study area

Morocco country, as part of the Atlantic Ocean, is an important region in the local ecological system (DPDPM 2007). This region experiences strong currents in some coast and various tidal elevations. The area harbors several major and minor ports and is to subject to intensive industrial activities and urban growth (DPDPM 2008). Thus, as many other coastal region, environmental change, inland processes including sediment, nutrient fluxes (riverine flux), and anthropogenic activities in the area threaten its water quality (Bennasser et al. 1998; Bouasria et al. 2007; Alaoui et al. 2008; DPDPM 2011b). An increasing level of sand mining, for example, has stirred up heavy metals in the sediment load from some lake’s mouth like Sebou river in Kenitra city (DPDPM 2007; METL 2014; Jaaidi and Cirac 1987). The study area is situated in the North Atlantic Ocean (Fig. 1). It is part of Africa on the northwestern. It has bordered by Spain to the north and Western Sahara to the south. The Morocco coast extends approximatively over 3500 km. Along the coastline, a different landforms types (or geomorphology) have been recognized and described depend on topography, elevation, shape, and composition characteristics (e.g., depends on rock types, unconsolidated materials, etc.). Wherever, freshwater rivers, estuaries, lagoons, and deltas drain into this larger body of water. The longshore drifts associated with the waves are the principal agents responsible for the sedimentary transport and the sand distribution along the coat. Many researchers concluded that this area along the coast have a potential coastal erosion (Moussaid et al. 2015; Azidane et al. 2017). A variety of the present erosion could be associated with coastal response to river sediment sources, river sediment transport, and sea-level rise and dune destruction. Indeed, the higher dredging intensity that occurs along the Moroccan coast and illegal sand extraction can minimize sediment volumes. These marine activities are mostly distributed in the northern and western parts of a test area (Fig. 2).

Fig. 1
figure 1

Surface map of the North Atlantic Ocean, Morocco (right). A digital elevation model of the study area (left|)

Full size image
Fig. 2
figure 2

Volumes of commercial sand dredged from the Moroccan continental shelf in 2008 and planned production in 2015 (right). Synthetic map of sedimentological data of the continental shelf of the Moroccan Atlantic (Jaaidi and Cirac 1987, modified) (left)

Full size image

Datasets and image processing

The TSM measurements were made from 2007 to 2012 are based on Moderate Resolution Imaging Spectroradiometer (MODIS). MODIS is a big platform aboard the Aqua (EOS PM) satellites and Terra (EOS AM) orbit; and used in many research papers (e.g., Singh et al. 2021; Shen et al. 2021; Yang et al. 2021; Huang and Huang 2020). Three types of data were used; TSM images between 2007 and 2012; wind speed data between 2007 and 2009; and ocean current speed data between 2007 and 2009 covering the Atlantic coast (Table 1).

Table 1 TSM and meteorological data used in this study
Full size table

Times series of good-quality MODIS 250 resolution products were downloaded from Glob Colour Merged (MODIS/MERIS/SEAWIFS) with the resolution of 4 km and daily datasets. The TSM values corresponding to our points of interest were geo-corrected, and land and cloud areas were masked out to obtain very precise TSM measurements. Upon extracting dataset to a local system, the data were displayed to access image quality and then processed using ESA Sentinel Application Platform (SNAP), and are available from the official website: http://step.esa.int/main/download/snap-download/.

Additionally, we chose two types of data, which were used to represent the meteorological conditions for the entire region: (1) monthly wind speed data that matched the date of acquisition for each satellite image from 2007 to 2009 were accessed from the website (http://apdrc.soest.hawaii.edu/las/v6/constrain?var=13073); (2) monthly ocean current prior to the acquisition date of each satellite image from 2007 to 2009 were accessed from the website (http://apdrc.soest.hawaii.edu/las/v6/constrain?var=2776).

The autumn period is defined here to include three months, September, October, and November. The winter period contains December, January, and February data. The spring period include Mars, April, and May. The summer season contains June, July, and August.

Results and discussion

Seasonal variability of satellite TSM concentration

Different seasons (autumn, winter, spring, and summer) have been studied. Figure 3 shows the seasonal distribution of TSM concentration in North Atlantic Ocean from MODIS images.

Fig. 3
figure 3

Derived-TSM pattern distribution snapshot map from 1978 to 2013 in North Atlantic Ocean

Full size image

From Fig. 3, the TSM in 2007 to 2012 distributed in wide area. High concentration of TSM accumulated around the coast represented by red color. December, January, and February represent winter which is wet season in Morocco. Wet season characterized by high rainfall, in which will increase the debit of rivers. TSM of coastal area is varying in range of 9 until max 10 g m−3. June, July, and September represent summer which is dry season in Morocco. Pattern of TSM distribution is spread compared with pattern of TSM in winter season, but the concentration of TSM in this period is lower than winter season. The rate of flow of rivers during dry season is lower and the TSM is about 3 g m−3. The dataset from 2012 has very high turbidity condition. This high turbidity is mainly concentrated near the river mouths.

On the other hand, Fig. 3 is a snapshot of the TSM pattern, and so, it cannot represent the mean TSM for each year in the season; in addition, it clearly shows the spatial patterns in each derived TSM snapshot and the main differences and changes in TSM patterns.

To view the changes of TSM patterns in coastal area, an alternative method for examining the annual variability in TSM concentration is used to examine the maps of the mean in each pixel box. For that, the pixel information values (Pins) were used. The Pins locations in coastal area are displayed in Fig. 4.

Fig. 4
figure 4

Distribution of TSM measurement stations using 111 pins in coastal area

Full size image

Furthermore, Fig. 5 shows TSM time series at the pixels. The TSM had significant spatial variability between 2007 and 2012. Overall, the mean TSM of each season varied widely, from 2 g m−3 in summer to 18 g m−3in winter. A higher mean of TSM observations in these years is evident in the autumn and winter seasons, with both models given very comparable results.

Fig. 5
figure 5

Total suspended matter time series extracted from 111 pins for the period 2007–2012

Full size image

However, it is clear from Fig. 6 that the maximum TSM concentrations appear in winter, and the minimum in summer, with lower concentration peaks arising in spring and autumn.

Fig. 6
figure 6

Derived mean TSM for four season, from 2007 to 2012

Full size image

The seasonal difference in satellite TSM concentrations was estimated by subtracted winter and summer TSM concentrations, winter and spring TSM concentrations, and winter and autumn TSM concentrations for each pixel box over the entire area (Fig. 7).

Fig. 7
figure 7

TSM concentration seasonal differences between summer and winter, winter and autumn, and winter and spring

Full size image

Interannual variability

The inter-annual variability is calculated separately for coastal stations from satellite data, which demonstrates the fact of annual mean TSM values tend to fluctuate more smoothly from 5 to 80 g m−3. Considerable inter-annual variations of TSM are typical for the northern Sahara, western Morocco on the Atlantic Ocean and northern Morocco.

The greater peak of TSM concentrations took place in northern Morocco in the 6-year period. This maximum appears in 2007, 2008, 2009, and from 2010 to 2012. Nevertheless, peak of TSM concentrations occurs twice in 2012 in the northern Morocco. As mentioned earlier, the discharge of TSM concentrations propagates in the whole northern part in 2012, as shown in Fig. 8.

Fig. 8
figure 8

Annual mean TSM concentration, calculated from satellite data

Full size image

Factors affecting the spatial and temporal changes in TSM

To test the TSM variation, the relationship between mean TSM and the local potential affecting factors was evaluated. Various factors influence the significant annual and seasonal variation generally observed in TSM, including seasonal wind, freshwater input, sediment load, tidal cycle, and flocculation (Wang et al. 2007).

In this study, the spatial–temporal variability of TSM concentration was demonstrated using the seasonal wind, ocean current, and freshwater input. Figure 9 shows the distributions of annual average wind speed. The increased wind speed in summer favored the resuspension of sediment in the northern Sahara, and therefore, TSM was higher in summer than in winter. Apparently, the maximum of TSM in the northern Sahara is provoked by increased wind storm activity resulting by air transfer in Sahara in 2007, 2008, 2009, 2010, 2011, and 2012. Strong winds and prevailing northern Sahara component affected coastal abrasion established resuspension of particulate matter along the coast where the major coastal stations are located.

Fig. 9
figure 9

Distributions of annual average wind speed in coastal waters in 2007, 2008, and 2009

Full size image

An increase in water turbidity in the northern Morocco and western Morocco on the Atlantic Ocean does necessarily imply dredging. Especially that the dredging concentrated in these regions. The annual mean TSM from 2007 to 2012 confirm the aforementioned increasing trend in water turbidity. One argument indicating the presence of dredging was the observation that the clear waters turned turbid in 2012 in northern Morocco. Furthermore, dredging further increased due to the rapidly rising demand for sand to support construction. In 2012, 30 million m3 of sand are dredged in the northern Morocco. The evidence extracted from MODIS images in 2012 in this area thus confirms this argument.

Many studies (e.g., Hakkou et al. 2015) have reported the impacts of dredging on littoral areas especially on the northern Morocco, including the effects of increased water turbidity, for instance, on aquatic plants and animals, and also noise, pollution. Hakkou et al. (2015) expressed that the noisy, oil pollution, turbidity, and decreased habitat caused by dredging coul seriously affect the propagation, growth, and subsistence of fish in the area. DPDPM (2011a) reported that the population of some fich species have rapidly decreased with the rapid growth of fisheries, boating, traffic, and dredging activites in Kenitra city. Sand dredging might in fact become the main factor of TSM variation in Kenitra coast after 2012.

The relationship between mean TSM and other potential affecting factors, such as ocean current data, is also illustrated in Fig. 10. During winter events of strong wind, together with currents, it is responsible for increase in the bottom friction producing very efficiently sediment resuspension. Strong currents are concentratred along the nothren coast of Morocco, and sediment concentrations are more pronounced.

Fig. 10
figure 10

Distributions of annual average ocean current in coastal waters in 2007, 2008, and 2009

Full size image

These results coincide very well with sediment thickness distributions in the cosatal and offshore area (Fig. 11). Sediment thickness increases dramatically toward the open sea in the Northern Morocco, westhern Morocco, and northern Sahara.

Fig. 11
figure 11

Sediment thickness map

Full size image

Conclusions

In this paper, we demonstrate how satellite images and time series analysis of TSM products may contribute to the understanding of process in marine environment, especially for shallow coastal areas. The spatial distribution and temporal variability of TSM concentration in the North Atlantic Ocean of Morocco coastal waters were investigated using satellite MODIS data for the period of 6 years (i.e.,2007–2012), leading to several key findings. It was first clearly established that higher TSM concentrations were observed in winter (December, January, and February), and lower TSM concentrations characterized summer (June, July, and August). The satellite data indicate similar patterns of TSM concentrations which may be divided accordingly into three different areas: at the north of Morocco, at the west of Morocco, and at the north of Sahara. The annual mean shows high turbidity in these regions.This distribution of maxima in the north and the west of Morocco affected by dredging operations, which could be a result of human activities such as an increased level of sand mining in response to the rapid economic growth occurring in Morocco that has resulted in increased sediment resuspension. On the other hand, the currents are strong in these areas, so the TSM distribution increase quickly.

The purpose of this paper is to demonstrate that capability of wind storm for monitoring the evolution of sediment resuspension processes in shallow coastal water environment in westhern Sahara. Our work offers new insight to understand the impacts of dredging. Futur improvements to the procedure include: conducting field sampling to better calibrate the image processing.