Effect of land-cover changes on heavy metals concentration and ecological risk in sediments of Tahaddart estuary, Morocco

Effect of land-cover changes on heavy metals concentration and ecological risk in sediments of Tahaddart estuary, Morocco | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effect of land-cover changes on heavy metals concentration and ecological risk in sediments of Tahaddart estuary, Morocco Meryem El Barjy, Mohamed Maanan, Hassna Boukaid, Najwa Hassou, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4460113/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Long-term trends of trace element contamination in coastal ecosystems are important for assessing the impact of land cover changes on the environment quality. In this study, the assessment of historical land cover changes and contamination status trends of Tahaddart estuary (N-W, Morocco) was investigated. Two sediment cores were selected, analyzed for trace elements (TEs), compared with sediment quality guidelines, and assessed by using environmental and ecological indices. Radiometric dating was performed on sediment core by using 210 Pb and 137 Cs isotope. Identification and description of the land cover patterns from 1984 to 2016 was analyzed using GIS methods. The geomatic results showed significant decline in agricultural land, forests, wetlands, and beaches/dunes between1984 and 2016, which are increasingly replaced by artificial land. The radio-dating of sediment core indicate that the mean sedimentation rates are 0.53 cm/years based on 210 Pb activities. The ecotoxicological risk and contamination indexes revealed a gradual deterioration in the environment quality of Tahaddart with moderate contamination level and 21% risk of toxicity. This research provides a reference database for costal area development. Coastal land cover change Spatial mapping Eco-toxicological risk Sediment quality guideline 210Pb/137Cs dating Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Recently, the Morocco’s Atlantic coast is already exposing to diverse human pressures, including urban sprawl, industrial development, and over-exploitation of coastal resources, which lead to rapid changes in land cover. The decrease in natural lands and the rise in built-up and agricultural areas are some of visual evidence of modifications in land cover patterns (Dadson, 2016 ; Kaliraj et al., 2017 ; Mas, 2004 ). Such dynamic can contribute to the input of trace elements (TEs) in coastal areas, thus resulting in serious environmental pollution (Sarı et al., 2013 ; Maanan et al, 2013 ; Lo and Gunasiri, 2016). Trace elements emission into the environment is harmful not only to the ecosystems, but also may have long-term consequences on human health because of refractory characteristics of bioaccumulation (Şimşek et al., 2022 ). The information of land cover is important to overcome problems of uncontrolled pollution and environmental risk for sustainable environment. To confirm this assumption, many studies have reported that built-up and agricultural land in coastal areas has been increased, while area under other natural land categories has decreased (Town et al., 2018 ; Lo and Gunasiri, 2016; Dadson, 2016 ). According to other studies, the improper use of land by human activities was a primary factor causing the degradation of coastal water quality (Romano et al. 2017 ; J. Wang et al. 2016 ). The rapid urbanization contributed to the input of significant amounts of TEs into the marine environment and directly affects the coastal systems in which they are often deposited and absorbed by sediments (Shi et al. 2022 ; Gulf et al. 2023 ; Vald et al. 2023 ). As a consequence of the land use practices, the metallic pollution has been dramatically increasing. But, the absence of long term records for TEs makes difficult to trace their behavior in coastal areas, which is the first step to prepare proactive adaptation strategies for proper marine management. The temporal distribution of the trace elements in coastal sediments cores adjacent to populated areas can provide the evidence of the anthropogenic impacts on ecosystems and help in assessing the risks associated with discharged human waste quality (Romano et al. 2017 ; J. Wang et al. 2016 ; Gulf et al. 2023 ; Vald et al. 2023 ). Core sediments are frequently used in geochemistry and paleo-pollution research; it can serve as historical records of contamination in recent decades (Sarı et al., 2013 ; Gulf et al. 2023 ; Vald et al. 2023 ). The use of sediment quality index can also reveal the impact of human activity has on coastal ecosystems. Numerous studies have been done in recent years show that the use of multivariate pollution index (contamination factor (CF), pollution load index (PLI), potential ecological risk index (PER) and mean probable effect concentration quotient (m-ERM-Q) was a good tool to assess the potential risk posed by trace elements exposure in sediment (Mas et al., 2004; Vald et al., 2023 ; El barjy et al. 2018 ; Sea, Liu, Sheng, Liu, & Li, 2023; Effendi, Kawaroe, & Fauzia, 2016). Some scientific investigations have been reported in the literature on the surface and core sediments in Tahaddart estuary (Massik et al. 2003 ; El Mrini 2004; Nachite et al. 2008 ; Rifai N. et al, 2018 ; Elbarjy et al. 2018 ). However, this is the first study to evaluate and discuss the contamination trend and eco-toxicology risk assessment in core sediments from the Tahaddart estuary. The purpose of this study is to investigate the historical variation of contamination status of TEs using sediment pollution indices, to evaluate ecological risks of TEs using ecological risk indices and guidelines for sediment quality in 210 Pb/ 137 Cs dated sediment cores. This study also aims to reconstruct the spatial and temporal land covers changes covering a time span of the last 32 years. 2. Materials and Methods 2.1. Study area The present study has been carried out on Tahaddart estuary located between the 35°30′ − 35°40′ latitudes North and 5°55′-6°01′ longitudes West in the north of Moroccan (Fig. 1 ). It is 3.5 km long with a surface area of 140 km 2 , which is occupied by temporary salted lakes, alluvial plains, and sandy coastal zones (Tahiri et al. 2014 ). It is one of the Moroccan sites that were considered by the RAMSAR Convention for the conservation of wetlands of international interest, and in 2005 as a RAMSAR zone under the name of “Complexe du bas Tahaddart” (Nachite et al. 2008 ). The anthropogenic land cover in the Tahaddart estuary is primarily dominated by agricultural areas. The rest of the study area was occupied by artificial land which used for urban areas, roads, railways, and infrastructure industry. The few villages in the area have a total population of about 45,339 inhabitants in 2014 (Barjy et al. 2018 ). 2.2. Land cover changes: The analyses of land cover changes are performed using three sets of remote sensing Landsat satellite images in 1984, 2006 and 2016 obtained from the USGS official website http://glovis.usgs.gov/ . All images were acquired during the dry season, with the multispectral scanner sensor (MSS), the thematic mapper sensor (TM) and the enhanced thematic mapper plus sensor (ETM+). For land cover monitoring, we have used Erdas imagine software to reproject and subset the study area. Visual interpretation is used to identify different land cover types in the satellite images. The study area in all images is classified into seven different land cover types: artificial surface, agriculture areas, forest, water bodies, beaches and sands, wetland. Each land use type is delineated using on-screen digitization of ArcGIS 10.1. The area of each land cover type is extracted by Geographic Information System (GIS) techniques. The area change occurred in each land cover type is then calculated according to the following landscape dynamic model (Lo and Gunasiri 2016): K = (So – St)/ So × 100%, where, K = area change of each land use type; So = area of initial time; St = area of end time. 2.3. Sampling and analytical methods: 2.3.1. Sample collection Two sediment cores of 1.9 m in length and 8 cm in diameter (TC1; TC2) were collected from the Tahaddart estuary in June 2016 with the following geographical coordinates: 35°35'13.06"N, 5°58'55.32"W for CT1 and 35°36'3.03"N, 5°57'48.36"W for CT2 (Fig. 1 ). The coring operation was conducted using a hund-held PVC corer. Once in the LETG laboratory (UMR 6554), the cores were split lengthwise, photographed, logged, and then subsampled for further analysis. 2.3.2. Geochronology analyzes Radio-chronological data for the last century was obtained using 137 Cs and 210 Pb exces measurements with a gamma spectrometer (LETG Laboratory de Nantes, Géolittomer-UMR 6554-CNRS, France). Samples were collected in the first 50 cm. The CFCS (Constant Flux, Constant Sedimentation rate) model was used for the 210 Pb exces to calculate the sedimentation rate in Tahaddart estuary (Golberg 1963). 2.3.3. Sediment contamination and risk assessment indices The geochemical data (Trace metal concentration and local geochemical background) obtained in our previous study (Barjy et al. 2018 ) was used in this study. The sediment concentrations were compared with sediment quality guidelines (SQGs) proposed by Long et al. ( 1995 ) for marine ecosystems to evaluate the ecotoxicological risk. The effect range low (ERL), the effect range median (ERM), the threshold effect level (TEL), and Probable Effect Level (PEL) were used to evaluate the level of toxicity of metals in the sediment cores. This study used the Contamination Factor (CF) and Pollution Load index (PLI) to evaluate the level of metal pollution degree of and possible anthropogenic impact on core sediments from Tahaddart estuary. The contamination factor of the studied metals was calculated by the following equation (Hakanson, 1980 ): CF = C i /C BV , Where C i is the mean concentration of an individual metal examined and C BV is the background value of the individual metal. The pollution load index (PLI) is a site-specific index which provides a simple comparative mean for assessing the level of metal contamination (Tomlinson et al, 1980 ): \(\text{P}\text{L}\text{I}=\sqrt[\text{n}]{({\text{C}\text{F}}_{1}\times {\text{C}\text{F}}_{2}\times {\text{C}\text{F}}_{3}\dots {\text{C}\text{F}}_{\text{n}})}\) , where n is the number of heavy metals taken into consideration and CF is the contamination factor. The potential ecological risk E i r was used to assess the potential risk of each metal in the sediment (Hakanson, 1980 ): $$\text{E}\text{i}\text{r}=Tri\times CFi ; RI=\sum \text{E}\text{i}\text{r}$$ Where E r i is the potential ecological risk index of an individual metal, T r i is the metal toxic response factor: Zn = 1, Pb = Cu = Ni = 5, Cd = 30, ‘‘RI’’ refers to the total of all risk factors for trace metals in sediments (Hankson L. et al. 1980). Mean sediment quality guidelines-quotient (SQG-Q) is an index that used to evaluate the possible biological effects of the coupled toxicity of trace elements in the surface sediments (Long et al. 1998 ). The SQG-Q was calculated for each sampling site, using the following equations: $$\text{m}\text{E}\text{R}\text{M}-\text{Q} =\frac{{\sum }_{\text{i}}^{\text{n}}\text{C}/\text{E}\text{R}\text{M}}{\text{n}}$$ Where: C metal concentration at each sampling site, ERM is effect range median and n is the number of metals used. 3. Results and discussion 3.1. Spatial-temporal LULC changes The data obtained through the analysis of multi-temporal satellite imageries from 1984 to 2016 are illustrated in figure and Table. The land cover maps (Fig. 2 ) demonstrate some important spatial-temporal patterns. The artificial area experienced an increasing trend from 1984 to 2016, with a decreasing in agricultural land, forests, wetlands, and beaches/dunes. The table 1 shows that the artificial area increased from 513.3 ha in 1984 and 1284 ha in 2006, to 1762.1 ha in 2016, with a rate change of 60% during 1984–2006 and 27.1% during 2006–2016. On other hand, the forest land decreased from 2046.7 ha in 1984 to 1419.3 ha in 2016. They are lost 336.2 ha during 1984–2006 and − 291.2 ha during 2006–2016, representing a rate of change of -19.7% and − 20.5%. The wetland had a lost 396.2 ha during 1984–2006 and 80.5 ha during 2006–2016. The beaches /dunes had a lost − 174.4 ha of its area during 1984–2006 and − 68.7 ha during 2006–2016. The Scrub/ herb vegetation and the agricultural land remained relatively stable in first period (1984–2006). During 2006–2016, The Scrub/ herb vegetation increased from 1291.6 ha to of 1727.3 ha. The agricultural land had lost 450.8 ha of its area, with a rate of variation of -8.9%. Furthermore, the beaches and dunes land recorded a decreasing area during the period 1984–2016 with a rate change between − 4.5 and − 20.7%. This regression can be explained by the sediment imbalance resulting from extraction of sand for construction needs and retention of sediment by “Ibn Battuta” and “April 9, 1947” Dam at upstream site. A detailed analysis of the intra and inter-transition of land cover classes (Table 2) reveals that 77.4% of the study area remained stable with 22.6% of change between 1984 and 2016. The most interesting change was manifested by artificial expansion at the expense of disappearance of other land-use types. For example, 1.4% of forests land was converted to artificial land and 3.1% transformed mainly into Scrub/ herb vegetation. Moreover, 5.3% agricultural land was converted also to artificial land. Another class of land cover that has undergone significant transformations was wetlands. Assessed at 28.6% in 1984, only 23.7% remained intact and 2.1% is converted into agricultural land, 1.2% into artificial land. This unconventional land cover transition is mainly linked to the construction of the thermal power station and the radio station in 1949; the TGV construction and the Rabat-Tangier highway in 2005, induced predominantly by Tangier’s urban development (Barjy et al. 2018 ). 3.2. Radionuclide profiles and sediment chronology The plot of 210 Pb xs and 137 Cs activities against depth for the Tahaddart sediment core is displayed in Fig. 3 . The surface 210 Pb xs activities was around to 34.1 Bq / kg (Fig. 5 A), relatively lower compared to activities found in other coastal ecosystems (Bellucci et al. 2007 ; Alonso-hernandez and Ruiz-fernández 2011). A detailed analysis of the 210 Pb xs distribution with depth suggests that the recording can be divided into two distinct segments. At the top of sediment core (0 to 20 cm), the 210 Pb xs activities decreased exponentially with depth, indicating regular sedimentation. However, the 210 Pb xs activities were relatively constant throughout the 20–50 cm segment of the core. A flattening of 210 Pb xs indicates either a dilution of the atmospheric flux of 210Pbxs by mixing of sediments, acceleration of sedimentation and / or the occurrence of slumps due to, for example, heavy rains (Alonso-hernandez et al, 2011). The 137 Cs activities range from 0.3 to 1.3 Bq / kg which are below the detection limit (2Bq / kg), which means that dating using this radionuclide is difficult (Fig. 3 ). This has also been observed in other coastal ecosystems such as: Yucatan Peninsula in Mexico (Ruiz-fernández, 2016 ) and Havana Bay in Cuba (Alonso-hernandez et al, 2011). The application of CFCS model (constant flux, constant supply), gave a sedimentation rate of 0.53 cm / year, which is comparable to that found by Khalfaoui et al. ( 2020 ) for the Tahaddart estuary. The slight difference between the two sedimentation rates is a maybe a result of the limited number of samples analyzed or located in the area (Khalfaoui et al. 2020 ). On the other hand, the sedimentation rate is higher than that recorded at Loukous estuary (Morocco) and Venice lagoon, but lower than the maximum rate recorded at Oum Errabia estuary and the Moulay Bousselham lagoon, Morocco (Kalloul et al, 2012 ; Maanan M. et al 2009; Mhammdi et al, 2010 Bellucci et al. 2007 )(Table 3). 3.3. Sediment quality The concentration of the studied metals in the dated sediment cores derived from Tahaddart estuary exhibited increasing trends, with the highest concentrations observed at the upper parts of sediment cores as obtained from our previous study (Barjy et al. 2018 ). To investigate the historical metals contamination, a comparative study was performed using the sediment quality guidelines (Fig. 4 ). The results showed that all concentrations in trace elements are below the values of ERM; thus, the concentrations of all trace elements in sediment cores do not represent any ecological risk. As indicated in figure, Zn and Cu levels in both cores were lower than TEL. Ni level in sediment exceeded the TEL values indicated in the SQG but still below the PEL values, while Pb, Cd and Cr concentrations were higher than the TEL values at upper parts of the cores. Based on the previous results, contamination factor (CF) and pollution load index (PLI) have been calculated for each core, the results are given in Fig. 5 below. The CF varied within a range of 0.53–2.13 for Zn; 0.75–2.01 for Pb; 0.64–2.60 for Cu; 0.57–1.69 for Ni; 0.66–2.22 for As; 0.23–19.11 for Cd and 0.65–3.33 for Cr in TC1’s core ; and 0.79 and 2.11 for Ni; 0.39 and 2.10 for Cu; 0.97 and 2.10 for Zn; 0.61 and 2.95 for Cr; 0.77 and 2.13 for Pb; 0.21 and 16.09 for Cd; 0.95 and 2.63 for As in TC2’s core (Table 4). The minimum values ​​are generally found at the base of the cores, while the maximum values ​​are observed at the upper part. For Cd, the vertical distribution of CF reveals a strong contamination (FC ≥ 6). For As, Pb, Ni, Zn and Cr, the calculated FCs indicate moderate contamination at the top, while the base of the core is marked by low contamination. According to table 4, the values ​​of pollution load index (PLI) for the two cores (TC1 and CT2) are between 0.64 and 2.72 with an average of order 1.62 for the CT1 core and between 0.63 and 2.86 with an average of 1.67 for CT2 core. The results ​​indicate that almost of the two cores have values ​​higher than 1, which suggests the existence of anthropogenic pollution. The vertical distribution of PLI highlighted strong values ​​at the top of the cores (Fig. 6 ). As shown in Fig. 7 , the ERM quotients (ERM-Q) of individual TEs indicated that Ni present a ‘‘High-medium Priority Site’ between 5–30 cm (CT1) et 0–5/15- 70cm (CT2). The others TEs (Cd, Cu and Pb) which classified them as "Medium-low priority side", except Zn and Cr have presented a "Low Priority Site". All the core sediment exhibited M-ERM-Q values > 0.1 confirming them as “medium-low priority sites”. The M-ERM-Q varied within a range of 0.06–0.18 for CT1, and 0.07–0.2 for CT2 which mean that the combination of six TEs (Cd, Cr, Cu, Ni, Pb, and Zn) might have a 21% probability of toxicity posing potential risk to the aquatic organisms (Table 5). The vertical distribution of the potential ecological risk index (Eir) for single TES at CT1 and CT2 cores indicated decreasing pollution intensity in the following order (Fig. 6 ): Cd > Cu > Pb > Ni > Cr > Zn, with individual mean values of 205.1; 8.3; 6.3; 5.7; 3.3 and 1.1; respectively for CT1 core and 209.8; 6.5; 5.9; 5.7; 2.4 and 1.5 for the CT2 core. It is worth noting that the E ir max values of all TEs were less than 40, and they posed a "low potential ecological risk", except for Cd where the risk was " high potential ecological risk" at the surface. The results highlighted the risk that Cd pose to the human body and the ecosystem. The Håkanson potential ecological risk index range for all sampling sites is from 24.4 and 608.1, indicating moderate to high potential ecological risk at surface (Table 5). 3.4. historical anthropogenic impacts on Tahaddart estuary The results presented in this study provide important information about the historical contamination of the Tahaddart estuary in the last 150 years. Anthropogenic activities around the estuary have left their fingerprint on the geochemical records (Barjy et al. 2018 ). The results obtained so far confirm that the study area has experienced several changes patterns induced by urbanization and industrialization process during the past 32 years. Overall, land cover in the study area is primarily agricultural and has remained constant, while the estuary was a subject to rapid artificial intensification since the 1984s, which is reflected in reduction of agricultural land, forests, wetlands, and beaches/dunes. This degradation in the natural environment is resulting from many factors like the construction of the thermal power station and the radio station in 1949; the TGV construction and the Rabat-Tangier highway in 2005, induced predominantly by Tangier’s urban development (Barjy et al. 2018 ; Tahiri et al., 2014 ). Several authors (Cesar & al., 2002; Mas, 2004 ; Al-tahir, 2015; Gupta and Sprawl, 2019) have blamed population growth and some kind of exploitation as being responsible for land cover change. This situation of lands degradation in the Tahaddart estuary is also observed in other Moroccan ecosystems like Oualidia and Moulay Boussalham lagoons (Maanan et al, 2014 ). Although the benefit of urbanization and agriculture development, some previous studies have suggested that the inappropriate land cover has been discussed as a factor that can affect environment quality of coastal ecosystem (M.C, 2019; Tang et al., 2022 ; ). Several authors argue that the data extracted from sediment cores provide important information of the contamination history over the past decades (Maanan et al., 2014 ; Irabien and al., 2008; Mahu et al., 2016 ; Hasan et al., 2023 ; Yang et al. 2020 ). However, in Tahaddart estuary, the highest values of contamination factor, pollution load index, ERM quotients (ERM-Q) and ecological risk index for all the metals studied were found at the upper portion of sediment cores confirming that there has been some anthropogenic influence on this estuary in recent times (since 1984), which receive a significant among of trace elements due to direct discharge from anthropogenic activities (Rabat-Tangier highway, thermal power station…) and the extensive use of fertilizers on farmlands around the estuary. The data obtained confirm gradually upward increasing trends in trace metal; spatially from 1984 when anthropogenic activities increased according to the evolution of land cover analyses. Recent case studies prove that some trace elements are mainly human-induced in coastal ecosystems (Zourarah B.. et al 2009 ; Zhuang et al. 2022 ; Sea et al. 2023 ). The result also revealed a gradual deterioration in the environment quality of Tahaddart estuary according to the sediment quality index, the studied zone was moderately impacted, with a 21% risk of biotoxic impacts. This sediment that may act in the future as a potential long term source of pollutants that could directly affect the water quality of estuary (Veerasingam et al. 2015 ). However, additional efforts should be made to avoid the spreading of contaminants in the lagoon and the preindustrial values obtained from the historical reconstruction provided could be used as the reference levels for environmental restoration purposes. 4. Conclusion In this study, the coastal zone of Tahaddart estuary is taken as the research area. The changes of estuary zone over the years are analyzed, and its ecological and environmental status is scientifically evaluated, the comprehensive management and protection measures are proposed. The main conclusions are as follows: Based on the land cover data in the study area, it is found that artificial land area is gradually increasing, and the area of forests, wetlands, agricultural areas, beaches, and dunes during the period 1984–2016. This degradation is essentially linked to the development of socio-economic activities (sand extraction, urban expansion, etc., industrial development). The isotope analysis of sediment core indicates that sedimentation rate is 0.53 cm/year indicated by 210 Pb, which means that one meter of sediment covers a period of 189 years. The temporal evolution of contamination and ecological index is characterized by increasing trends over the past last 150 years. Sediment quality analyses based on contamination index and sediment quality guidelines indicated a generally moderate quality sedimentary environment in Tahaddart estuary with 21% probability of acute toxicity. This work reveals important information about historical contamination in Tahaddart estuary that can be used to protect and improve the quality of this ecosystem. Declarations Funding The authors received no financial support for the research, authorship, and/or publication of this article. Competing Interests The authors have no relevant financial or non-financial interests to disclose. Authors’ Contributions All authors contributed to the study conception. MEB, HB, NH, BH, and MeM were responsible for preparation of materials, data collection and analysis. MEB, HB, MM and MeM verified the analytical methods. MEB and MeM wrote the first draft of the manuscript and all authors commented on previous versions of it. All authors discussed the results and approved the final manuscript. Data Availability The datasets generated and analysed during this study and its supplementary information files are available from the corresponding author on reasonable request. Ethics Approval Not applicable. Consent for Publication Not applicable. Consent for Publication Not applicable. References Alonso-hernandez, Carlos M, and Ana Carolina Ruiz-fernández. 2011. “Reconstruction of Sedimentation and Pollution in Havana Bay, Cuba,” no. https://doi.org/10.1016/j.jhazmat.2011.09.037. Barjy, Meryem El et al. 2018. “Human and Ecological Risk Assessment : An International Contamination and Environmental Risk Assessment of Heavy Metals in Marine Sediments from Tahaddart Estuary ( NW of Morocco ).” Human and Ecological Risk Assessment 0(0): 1–16. https://doi.org/10.1080/10807039.2018.1495056. Beach, West Palm, Cesar A Berlanga-robles, and Arturo Ruiz-lunar. 2002. “Land Use Mapping and Change Detection in the Coastal Zone of Northwest Mexico Using Remote Sensing Techniques.” Bellucci, L G, M Frignani, J K Cochran, and S Albertazzi. 2007. “Pb and 137 Cs as Chronometers for Salt Marsh Accretion in the Venice Lagoon e Links to Flooding Frequency and Climate Change” 97. https://doi.org/10.1016/j.jenvrad.2007.03.005. Bellucci, L G, M Frignani, J K Cochran, and S Albertazzi. 2007. “Pb and 137 Cs as Chronometers for Salt Marsh Accretion in the Venice Lagoon e Links to Flooding Frequency and Climate Change” 97. https://doi.org/10.1016/j.jenvrad.2007.03.005. C, Mohammed Firoz. 2019. “Impact of Land Use and Land Cover Change on the Environmental Quality of a Region : A Case of Ernakulam District in Kerala , India.” 11(2): 102–35. Dadson, Ishmael Yaw. 2016. “Land Use and Land Cover Change Analysis along the Coastal Regions of Cape Coast and Sekondi” 8 (2): 108–26. Effendi, Hefni, Mujizat Kawaroe, and Dea Fauzia. 2016. “Ecological Risk Assessment of Heavy Metal Pollution in Surface Sediment of Mahakam Delta , East Kalimantan.” 33: 574–82. EL MRINI A. (2004) : L’estuaire de Tahaddart (Province de Tanger – Maroc nord occidental) : Etudes préliminaires. Mém. DESA, Univ. Abdelmalik Essaadi, FS. Tétouan , p. 52. Goldberg, E. (1963).Geochronology with lead-210, International Atomic Energy Agency, pp. 121–131. Gulf, İzmit et al. 2023. “Assessment of Eco-Toxicological and Health Risks of Core Sediment From.” Regional Studies in Marine Science 64: 103059. https://doi.org/10.1016/j.rsma.2023.103059. Gupta, R D, and Urban Sprawl. 2019. “Change Assessment of Spatio-Temporal Dynamics of Land Use / Land Cover Using Remote Sensing and GIS : A Case Study of Lucknow City ( 1993-2019 ),” no. December. Hakanson, L., 1980. An ecological risk index for aquatic pollution control. A sedimentological approach. Water Res. 14, 975–1001. Hasan, Rakibul et al. 2023. “Vertical Distribution , Contamination Status and Ecological Risk Assessment of Heavy Metals in Core Sediments from a Mangrove-Dominated Tropical River.” Marine Pollution Bulletin 189(November 2022): 114804. https://doi.org/10.1016/j.marpolbul.2023.114804. Irabien, M. J. et al. 2008. “A 130 Year Record of Pollution in the Suances Estuary (Southern Bay of Biscay): Implications for Environmental Management.” Marine Pollution Bulletin 56(10): 1719–27. Kaliraj, S, N Chandrasekar, K K Ramachandran, Y Srinivas, and S Saravanan. 2017. “The Egyptian Journal of Remote Sensing and Space Sciences Coastal Landuse and Land Cover Change and Transformations of Kanyakumari Coast , India Using Remote Sensing and GIS.” The Egyptian Journal of Remote Sensing and Space Sciences 20 (2): 169–85. https://doi.org/10.1016/j.ejrs.2017.04.003. Kalloul S, Hamid W, Maanan M, Robin M, Sayouty EH, Zourarah B (2012).Source contributions to heavy metal fluxes into the Loukous Estuary (Moroccan Atlantic Coast). J Coast Res 28:174–183 Khalfaoui, Otmane, Laurent Dezileau, Jean-philippe Degeai, and Maria Snoussi. 2020. “A Late Holocene Record of Marine High- Energy Events along the Atlantic Coast of Morocco : New Evidences from the Tahaddart Estuary.” 5. Lo, Kwong Fai A, and Chethika W D Gunasiri. 2016. “Impact of Coastal Land Use Change on Shoreline Dynamics in Yunlin County, Taiwan,” no. October 2014. https://doi.org/10.3390/environments1020124 Lo, Kwong Fai A, and Chethika W D Gunasiri. 2016. “Impact of Coastal Land Use Change on Shoreline Dynamics in Yunlin County, Taiwan.” (October 2014). Long, E. R.; Field, L. J.; MacDonald, D. D. (1998).Predicting toxicity in marine sediments with numerical sediment quality guidelines.Environ. Toxicol.Chem. 17 (4), 714-727. Long, E.R., MacDonald, D.D., Smith, S.L., Calder, F.D., 1995. Incidence of adverse biological effects within ranges of chemical concentrations in marine and estuarine sediments. Environ. Manage. 19, 81–97. Maanan M, Landesman C, Maanan M, Zourarah B, Fattal P, Sahabi M (2013). Evaluation of the anthropogenic influx of metal and metalloid contaminants into the Moulay Bousselham lagoon, Morocco, using chemometric methods coupled to geographical information systems. Environmental Sciences and Pollution Research 20: 4729–474. Maanan, Mohamed, Mohammed Saddik, Mehdi Maanan, and Mohamed Chaibi. 2014. “Environmental and Ecological Risk Assessment of Heavy Metals in Sediments of Nador Lagoon , Morocco.” Ecological Indicators 48: 616–26. http://dx.doi.org/10.1016/j.ecolind.2014.09.034. Maanan. 2014a. “Evaluation of the Anthropogenic Influx of Metal and Metalloid Contaminants into the Moulay Bousselham ... Evaluation of the Anthropogenic Influx of Metal and Metalloid Contaminants into the Moulay Bousselham Lagoon , Morocco , Using Chemometric Methods Co,” no. January 2013. https://doi.org/10.1007/s11356-012-1399-6. Mahu, Edem et al. 2016. “Geochronology and Historical Deposition of Trace Metals in Three Tropical Estuaries in the Gulf of Guinea.” Estuarine, Coastal and Shelf Science 177: 31–40. http://dx.doi.org/10.1016/j.ecss.2016.05.007. Mas, J F. 2004. “Mapping Land Use / Cover in a Tropical Coastal Area Using Satellite Sensor Data , GIS and Artificial Neural Networks” 59: 219–30. https://doi.org/10.1016/j.ecss.2003.08.011. Mas, J F. 2004. “Mapping Land Use / Cover in a Tropical Coastal Area Using Satellite Sensor Data , GIS and Artificial Neural Networks.” 59: 219–30. Massik Z., Lakhdar I. & Zizah S., 2003. Impact d’une activité de dragage de sables sur la faune et la flore de l’estuaire de Tahaddart (Cas de l’estuaire de Tahaddart). Colloque International sur les sables et Environnement (Solution Alternatives). Casablanca, Maroc, 1-21 p. Mhamdi Alaoui A., Choura M., Maanan M., Zourarah B., Robin M., FreitasConceição M., Andrade C., Khalid M., Carruesco C. (2010).Metal fluxes to the sediments of the Moulay Bousselham lagoon, Morocco. Environmental Earth Sciences, Vol. 61, No. 2, pp. 275-286. Nachite D., Bekkali R., Macias A. & Anfuso G., 2008. El estuario de Tahaddart: las bases para una gestión integrada de un espacio en plena transformación. Service de Publication de l’Université de Cadix (Espagne), 33 p Rifai N. et al. 2018. “ÉVALUATION DE LA DYNAMIQUE DE L’OCCUPATION DU SOL DANS LA ZONE HUMIDE RAMSAR DE TAHADDART (NORD-OUEST DU MAROC) Nabil R.” 73(2): 142–52. Romano, Elena, Giovanni De Giudici, Luisa Bergamin, Stefano Andreucci, Chiara Maggi, Giancarlo Pierfranceschi, Maria Celia Magno, and Antonella Ausili. 2017. “The Marine Sedimentary Record of Natural and Anthropogenic Contribution from the Sulcis- Iglesiente Mining District (Sardinia, Italy).” Marine Pollution Bulletin 122 (1–2): 331– 43. https://doi.org/10.1016/j.marpolbul.2017.06.070 Ruiz-fernández, Ana Carolina. 2016. “Sedimentary Records of Recent Sea Level Rise and Acceleration in the Yucatan Peninsula Article in Science of The Total Environment · September 2016.” Science of the Total Environment 573 (September): 1063–69. https://doi.org/10.1016/j.scitotenv.2016.08.142. Sarı, E., Ünlü, S., Balcı, N., Apak, R., Kurt, M.A., Koldemir, B., 2013. Evaluation of contamination by selected elements in a Turkish port. Pol. J. Environ. Stud. 22, 841–847 Sea, South Yellow et al. 2023. “Ecological and Environmental Risks of Heavy Metals in Sediments in Dingzi.” Marine Pollution Bulletin 188(December 2022): 114683. https://doi.org/10.1016/j.marpolbul.2023.114683. Shi, Cui et al. 2022. “Science of the Total Environment Heavy Metals and Pb Isotopes in a Marine Sediment Core Record Environmental Changes and Anthropogenic Activities in the Pearl River Delta over a Century.” Science of the Total Environment 814(188): 151934. https://doi.org/10.1016/j.scitotenv.2021.151934. Şimşek, A., Özkoç, H.B., Bakan, G., 2022. Environmental, ecological and human health risk assessment of heavy metals in sediments at Samsun-Tekkeköy, North of Turkey. Environ. Sci. Pollut. Res. 29, 2009–2023. Tahiri. M, Achab M., Emran A., Tahiri A., Hakdaoui M., El Hadi H., (2014). Lithology data conctribution in hydrographic network distribution using remote sensing and GIS: case of Tahaddart basin, northwestern Rif, Morocco. International Journal of Advanced Research (2014), Volume 2, Issue 5, 380-391. Tahiri. M, Achab M., Emran A., Tahiri A., Hakdaoui M., El Hadi H., (2014). Lithology data conctribution in hydrographic network distribution using remote sensing and GIS: case of Tahaddart basin, northwestern Rif, Morocco. International Journal of Advanced Research (2014), Volume 2, Issue 5, 380-391. Tang, Huan et al. 2022. “Impact of Land Cover Change on a Typical Mining Region and Its Ecological Environment Quality Evaluation Using Remote Sensing Based Ecological Index ( RSEI ).” Tomlinson, D., Wilson, J., Harris, C., Jeffrey, D., 1980. Problems in the assessment of heavy-metal levels in estuaries and the formation of a pollution index. Helgoländer Meeresuntersuchungen 33, 566–575. Town, Bo, Musa Tarawally, Wenbo Xu, Weiming Hou, and Terence Darlington Mushore. 2018. “Comparative Analysis of Responses of Land Surface Temperature to Long-Term Land Use / Cover Changes between a Coastal and Inland City: A Case Of,” 1–18. https://doi.org/10.3390/rs10010112 Vald, J, Luc Ortlieb, A Sifeddine, and A Castillo. 2023. “Human-Induced Metals Accumulation in Sediments of an Industrialized Bay of Northern Chile . An Enrichment and Ecological Risk Assessment Based on Preindustrial Values.” 189(November 2022). Veerasingam, S, P Vethamony, R Mani Murali, and B Fernandes. 2015. “Depositional Record of Trace Metals and Degree of Contamination in Core Sediments from the Mandovi Estuarine Mangrove Ecosystem , West Coast of India.” Marine Pollution Bulletin 91(1): 362–67. http://dx.doi.org/10.1016/j.marpolbul.2014.11.045. Wang, Jie, Guijian Liu, Jiamei Zhang, Houqi Liu, and Paul K.S. Lam. 2016. “A 59-Year Sedimentary Record of Metal Pollution in the Sediment Core from the Huaihe River, Huainan, Anhui, China.” Environmental Science and Pollution Research 23 (23): 23533–45. https://doi.org/10.1007/s11356-016-7587-z. Yang, Guohuan et al. 2020. “Heavy Metals of Sediment Cores in Dachan Bay and Their Responses to Human Activities.” Marine Pollution Bulletin 150(July 2019): 110764. https://doi.org/10.1016/j.marpolbul.2019.110764. Zhuang, Haihai et al. 2022. “Assessment of the Vertical Characteristics and Contamination Levels of Toxic Metals in Sediment Cores from Typical Chinese Intertidal Zones.” Marine Pollution Bulletin 185(PA): 114307. https://doi.org/10.1016/j.marpolbul.2022.114307. Zourarah B.. et al. 2009. “Sedimentary Records of Anthropogenic Contribution to Heavy Metal Content in Oum Er Bia Estuary ( Morocco ).” (February). Tables Tableau 1 : Area and amount of change in different land cover categories in the Tahaddart estuary during 1984-2016. 1984 2006 2016 1984-2006 2006-2016 ha % Km % Km % Km % Km % Artificial area 513.3 3.5 1284 8.7 1762.1 11.9 770.7 60.0 478.1 27.1 Agricultural land 5434.9 36.7 5543.7 37.5 5092.9 34.5 108.8 2.0 -450.8 -8.9 Forest land 2046.7 13.8 1710.5 11.6 1419.3 9.6 -336.2 -19.7 -291.2 -20.5 Scrub and herb Vegetation 1264.7 8.5 1291.6 8.7 1727.3 11.7 26.9 2.1 435.7 25.2 Beaches, dunes 841.2 5.7 666.8 4.5 598.1 4 -174.4 -26.2 -68.7 -11.5 Wetland 4300.3 29 3904.1 26.4 3823.7 25.9 -396.2 -10.1 -80.5 -2.1 Water body 402.1 2.7 368.4 2.5 345.7 2.3 -33.7 -9.1 -22.6 -6.5 Tableau 2: The land cover transition matrix. 2016 forest land Scrub/ herb vegetation beaches /dunes Water body agricultural land artificial area wetland Total 1984 forest land 8,7 3,1 0,0 0,0 0,4 1,4 0,3 13,8 Scrub/ herb vegetation 0,5 6,0 0,0 0,1 0,4 1,2 0,5 8,7 beaches /dunes 0,1 0,2 4,4 0,1 0,2 0,0 0,0 5,1 Water body 0,0 0,0 0,0 1,4 0,4 0,0 0,7 2,7 agricultural land 0,1 1,0 0,1 0,2 30,5 5,3 0,5 37,7 artificial area 0,1 0,3 0,0 0,0 0,3 2,7 0,1 3,5 wetland 0,2 1,0 0,5 2,1 1,2 23,7 28,6 Total 9,6 11,6 4,6 2,3 34,3 11,9 25,7 100,0 Tableau 3: Sedimentation rate in Tahaddart estuary and the related values reported in other coastal areas. Coastal sediment Sedimentation rate (cm/year) Reference Tahaddart estuary (Morocco) 0,53 Present study Tahaddart estuary (Morocco) 0.46 Khalfaoui et al. 2020 Loukous estuary (Morocco) 0.27-0.37 Kalloul et al, 2012 Oum Er bia estuary (Morocco) 0,38 à 0,68 Maanan M. et al 2009 Moulay Bousselham logoon 0,6 – 0,70 Mhammdi et al, 2010 Venise logoon 0.25 cm y-1 Bellucci et al. 2007 Tableau 4: The ranges and averages of contamination factor (CF), Pollution Load Index (PLI) in sediment cores from Tahaddart estuary. Contamination factor (CF) PLI Ni Cu Zn Cr Pb Cd As CT1 MOY SD 1.14 0.25 1.66 0.44 1.11 0.43 1.67 0.79 1.26 0.29 6.84 4.69 1.27 0.41 1.62 0.52 MIN- MAX 0.57-1.69 0.67-2.60 0.53-2.13 0.65-3.33 0.75-2.01 0.23-19.11 0.66-2.22 0.64-2.72 CT2 MOY SD 1.29 0.35 1.48 0.51 1.46 0.24 1.21 0.45 1.23 0.32 6.99 4.84 1.64 0.47 1.67 0.55 MIN- MAX 0.79-2.11 0.39-2.42 0.97-2.10 0.61-2.95 0.77-2.13 0.21-16.09 0.95-2.63 0.63-2.86 Cf <1 indicates low contamination; 1<Cf <3 is moderate contamination; 3<Cf 6 is very high contamination. PLI >1 means that pollution exists; otherwise, if it is <1, there is no metal pollution Tableau 5: The ranges and averages of individual ecological risk Index (Er i ), total ecological risk (RI) and Mean ERM quotients (m-ERM-Q) in sediment cores from Tahaddart estuary. Ecological risk Index (Er i ) RI m-ERM-Q Ni Cu Zn Cr Pb Cd CT1 MOY SD 5.62±1.24 8.02±2.31 1.09±0.42 3.23±1.54 6.35±1.41 187.30±145.19 211.61±149.24 0.12 0.03 MIN- MAX 2.83-8.45 3.35-13.01 0.42-2.13 1.30-6.66 3.77-10.07 6.53-573.42 24.39-608.07 0.06-0.18 CT2 MOY SD 6.46±1.77 7.39±2.55 1.46±0.24 2.43±0.90 6.15±1.59 209.79±145.12 233.67±150.85 0.13 0.03 MIN- MAX 3.94-10.54 1.93-12.11 0.97-2.10 1.22-5.90 3.87-10.66 6.23-482.64 19.27-520.69 0.07-0.20 E i r < 40 indicates a low potential ecological risk; 40 <E i f < 80 is a moderate ecological risk; 80 <E i r < 160 is a considerable ecological risk; 160 <E i r 320 is a very high ecological risk. R I < 95 indicates a low potential ecological risk; 95 <R I < 190 is a moderate ecological risk; 190 <R I 380 is a very high ecological risk. M-ERM-Q was defined: 9% probability of toxicity (M-ERM-Q <0.1), 21% probability of toxicity (0.11 ≤ M-ERM-Q <0.5), 49% probability of toxicity (0.51 ≤ M-ERM-Q 1.5). 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Maanan","email":"","orcid":"","institution":"Nantes University: Nantes Universite","correspondingAuthor":false,"prefix":"","firstName":"Mohamed","middleName":"","lastName":"Maanan","suffix":""},{"id":330229973,"identity":"1d8068a7-ad49-4081-897b-cb462ffb7c25","order_by":2,"name":"Hassna Boukaid","email":"","orcid":"","institution":"University Hassan II Casablanca: Universite Hassan II Casablanca","correspondingAuthor":false,"prefix":"","firstName":"Hassna","middleName":"","lastName":"Boukaid","suffix":""},{"id":330229974,"identity":"100eaa8b-ec4d-44fc-b300-3d46f93c739a","order_by":3,"name":"Najwa Hassou","email":"","orcid":"","institution":"higher institute of nursing professions and technical healt of Rabat","correspondingAuthor":false,"prefix":"","firstName":"Najwa","middleName":"","lastName":"Hassou","suffix":""},{"id":330229975,"identity":"995ca8ed-731c-4002-ac37-63c7133dd00e","order_by":4,"name":"Bazairi Hocein","email":"","orcid":"","institution":"Université Mohammed V de Rabat: Universite Mohammed V de Rabat","correspondingAuthor":false,"prefix":"","firstName":"Bazairi","middleName":"","lastName":"Hocein","suffix":""},{"id":330229976,"identity":"67ae451c-46a7-4ed0-9c82-1a8af0bea347","order_by":5,"name":"Mehdi Maanan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6UlEQVRIiWNgGAWjYFACHgaJBBj7AxCzsZOihXEGSAszMVpgTGYeMElAg25778EbDxi2yfPPbn722ObXNnk+ZgbGDx9zcGsxO3Mu2SKB4bbhjDvHzI1z+24btjEzMEvO3IZHy40cM6BfbjM23Egwk87tuc0I1MLGzItPy/03YC3282+kf5O27LltT1jLDR6wlsQNQOukGX7cTiSs5UyOsUWCwe3kjTdyyiR7G24ntzEzNuP3y/Ezhjd/VNy2nXcjfZvEjz+3bee3Nx/88BGPFggwgNKMbWCygZB6ZPCHFMWjYBSMglEwUgAA/7tRaozfk90AAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0003-3019-6860","institution":"University of Hassan II","correspondingAuthor":true,"prefix":"","firstName":"Mehdi","middleName":"","lastName":"Maanan","suffix":""}],"badges":[],"createdAt":"2024-05-22 10:13:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4460113/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4460113/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62616464,"identity":"512b9c50-758b-4637-a326-4ec7c2a44548","added_by":"auto","created_at":"2024-08-16 13:15:57","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":360995,"visible":true,"origin":"","legend":"\u003cp\u003elocalization of sampling stations in Tahaddart estuary (North-West of Morocco).\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4460113/v1/c7000e5f2bcdfc815a23bd58.jpg"},{"id":62617635,"identity":"5ae3ab2e-d736-4a40-8c68-b697b44ac322","added_by":"auto","created_at":"2024-08-16 13:31:57","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":683758,"visible":true,"origin":"","legend":"\u003cp\u003eland cover change in Tahaddart estuary during 1984-2016.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4460113/v1/d6f9332a7cc51aca9d00d056.jpg"},{"id":62616465,"identity":"cc31a44b-42ad-4cb9-bbde-b6d9e41e1e34","added_by":"auto","created_at":"2024-08-16 13:15:57","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":68570,"visible":true,"origin":"","legend":"\u003cp\u003eDepth profile of \u003csup\u003e137\u003c/sup\u003eCs and \u003csup\u003e210\u003c/sup\u003ePb \u003csub\u003eexces\u003c/sub\u003e Activities for sediment core in Tahaddart estuary.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4460113/v1/1cc3cefb2388babeeae591fe.jpg"},{"id":62616470,"identity":"dc3ab49d-a553-411e-9db3-db5e8b30e2bc","added_by":"auto","created_at":"2024-08-16 13:15:58","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":271320,"visible":true,"origin":"","legend":"\u003cp\u003eComparison between sediment quality guideline and trace element concentrations in sediment cores (CT1; CT2) from Tahaddart estuary.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4460113/v1/7c07985e6af455df392c4f67.jpg"},{"id":62616466,"identity":"226980e6-08f3-4add-8b56-4081b6091bfc","added_by":"auto","created_at":"2024-08-16 13:15:57","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":266455,"visible":true,"origin":"","legend":"\u003cp\u003eVertical profiles of Contamination Factor (CF) and Pollution Load Index (PLI) in the sediment cores CT1 and CT2 from Tahaddart estuary.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4460113/v1/f2d1f30d03ae915d0bee0017.jpg"},{"id":62616469,"identity":"31b23fe4-2c0a-4f91-b712-292c08fa7ddf","added_by":"auto","created_at":"2024-08-16 13:15:57","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":222757,"visible":true,"origin":"","legend":"\u003cp\u003eVertical profiles of individual ecological risk Index (E\u003csub\u003er\u003c/sub\u003e i ) and total ecological risk (RI) in sediment cores (CT1; CT2) from Tahaddart estuary.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4460113/v1/c7770da3f0ef0847c4e35e0d.jpg"},{"id":62616933,"identity":"ef7c6d74-edad-48a8-908f-b20d2e0aa040","added_by":"auto","created_at":"2024-08-16 13:23:57","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":366996,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eThe ERM quotients (ERM-Q) and the Mean ERM quotients (m-ERM-Q) profiles over time in sediment cores (CT1; CT2) from Tahaddart estuary.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4460113/v1/a73c473326d590927c1901f8.jpg"},{"id":66279405,"identity":"8ff14c2d-a4a8-430c-aafa-e48d1ad1697f","added_by":"auto","created_at":"2024-10-09 14:49:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3072166,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4460113/v1/672f65b4-8c68-4c21-b263-4bfbe9532e29.pdf"}],"financialInterests":"","formattedTitle":"Effect of land-cover changes on heavy metals concentration and ecological risk in sediments of Tahaddart estuary, Morocco","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eRecently, the Morocco\u0026rsquo;s Atlantic coast is already exposing to diverse human pressures, including urban sprawl, industrial development, and over-exploitation of coastal resources, which lead to rapid changes in land cover. The decrease in natural lands and the rise in built-up and agricultural areas are some of visual evidence of modifications in land cover patterns (Dadson, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Kaliraj et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Mas, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Such dynamic can contribute to the input of trace elements (TEs) in coastal areas, thus resulting in serious environmental pollution (Sarı et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Maanan et al, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Lo and Gunasiri, 2016). Trace elements emission into the environment is harmful not only to the ecosystems, but also may have long-term consequences on human health because of refractory characteristics of bioaccumulation (Şimşek et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The information of land cover is important to overcome problems of uncontrolled pollution and environmental risk for sustainable environment.\u003c/p\u003e \u003cp\u003eTo confirm this assumption, many studies have reported that built-up and agricultural land in coastal areas has been increased, while area under other natural land categories has decreased (Town et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Lo and Gunasiri, 2016; Dadson, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). According to other studies, the improper use of land by human activities was a primary factor causing the degradation of coastal water quality (Romano et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; J. Wang et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The rapid urbanization contributed to the input of significant amounts of TEs into the marine environment and directly affects the coastal systems in which they are often deposited and absorbed by sediments (Shi et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Gulf et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Vald et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). As a consequence of the land use practices, the metallic pollution has been dramatically increasing. But, the absence of long term records for TEs makes difficult to trace their behavior in coastal areas, which is the first step to prepare proactive adaptation strategies for proper marine management.\u003c/p\u003e \u003cp\u003eThe temporal distribution of the trace elements in coastal sediments cores adjacent to populated areas can provide the evidence of the anthropogenic impacts on ecosystems and help in assessing the risks associated with discharged human waste quality (Romano et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; J. Wang et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Gulf et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Vald et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Core sediments are frequently used in geochemistry and paleo-pollution research; it can serve as historical records of contamination in recent decades (Sarı et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Gulf et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Vald et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The use of sediment quality index can also reveal the impact of human activity has on coastal ecosystems. Numerous studies have been done in recent years show that the use of multivariate pollution index (contamination factor (CF), pollution load index (PLI), potential ecological risk index (PER) and mean probable effect concentration quotient (m-ERM-Q) was a good tool to assess the potential risk posed by trace elements exposure in sediment (Mas et al., 2004; Vald et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; El barjy et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sea, Liu, Sheng, Liu, \u0026amp; Li, 2023; Effendi, Kawaroe, \u0026amp; Fauzia, 2016).\u003c/p\u003e \u003cp\u003eSome scientific investigations have been reported in the literature on the surface and core sediments in Tahaddart estuary (Massik et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2003\u003c/span\u003e ; El Mrini 2004; Nachite et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Rifai N. et al, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Elbarjy et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e ). However, this is the first study to evaluate and discuss the contamination trend and eco-toxicology risk assessment in core sediments from the Tahaddart estuary. The purpose of this study is to investigate the historical variation of contamination status of TEs using sediment pollution indices, to evaluate ecological risks of TEs using ecological risk indices and guidelines for sediment quality in \u003csup\u003e210\u003c/sup\u003ePb/\u003csup\u003e137\u003c/sup\u003eCs dated sediment cores. This study also aims to reconstruct the spatial and temporal land covers changes covering a time span of the last 32 years.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study area\u003c/h2\u003e \u003cp\u003eThe present study has been carried out on Tahaddart estuary located between the 35\u0026deg;30\u0026prime; \u0026minus;\u0026thinsp;35\u0026deg;40\u0026prime; latitudes North and 5\u0026deg;55\u0026prime;-6\u0026deg;01\u0026prime; longitudes West in the north of Moroccan (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). It is 3.5 km long with a surface area of 140 km\u003csup\u003e2\u003c/sup\u003e, which is occupied by temporary salted lakes, alluvial plains, and sandy coastal zones (Tahiri et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). It is one of the Moroccan sites that were considered by the RAMSAR Convention for the conservation of wetlands of international interest, and in 2005 as a RAMSAR zone under the name of \u0026ldquo;Complexe du bas Tahaddart\u0026rdquo; (Nachite et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The anthropogenic land cover in the Tahaddart estuary is primarily dominated by agricultural areas. The rest of the study area was occupied by artificial land which used for urban areas, roads, railways, and infrastructure industry. The few villages in the area have a total population of about 45,339 inhabitants in 2014 (Barjy et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Land cover changes:\u003c/h2\u003e \u003cp\u003eThe analyses of land cover changes are performed using three sets of remote sensing Landsat satellite images in 1984, 2006 and 2016 obtained from the USGS official website \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://glovis.usgs.gov/\u003c/span\u003e\u003cspan address=\"http://glovis.usgs.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. All images were acquired during the dry season, with the multispectral scanner sensor (MSS), the thematic mapper sensor (TM) and the enhanced thematic mapper plus sensor (ETM+). For land cover monitoring, we have used Erdas imagine software to reproject and subset the study area. Visual interpretation is used to identify different land cover types in the satellite images. The study area in all images is classified into seven different land cover types: artificial surface, agriculture areas, forest, water bodies, beaches and sands, wetland. Each land use type is delineated using on-screen digitization of ArcGIS 10.1. The area of each land cover type is extracted by Geographic Information System (GIS) techniques. The area change occurred in each land cover type is then calculated according to the following landscape dynamic model (Lo and Gunasiri 2016): K = (So \u0026ndash; St)/ So \u0026times; 100%, where, K\u0026thinsp;=\u0026thinsp;area change of each land use type; So =\u0026thinsp;area of initial time; St\u0026thinsp;=\u0026thinsp;area of end time.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Sampling and analytical methods:\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1. Sample collection\u003c/h2\u003e \u003cp\u003eTwo sediment cores of 1.9 m in length and 8 cm in diameter (TC1; TC2) were collected from the Tahaddart estuary in June 2016 with the following geographical coordinates: 35\u0026deg;35'13.06\"N, 5\u0026deg;58'55.32\"W for CT1 and 35\u0026deg;36'3.03\"N, 5\u0026deg;57'48.36\"W for CT2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The coring operation was conducted using a hund-held PVC corer. Once in the LETG laboratory (UMR 6554), the cores were split lengthwise, photographed, logged, and then subsampled for further analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2. Geochronology analyzes\u003c/h2\u003e \u003cp\u003eRadio-chronological data for the last century was obtained using \u003csup\u003e137\u003c/sup\u003eCs and \u003csup\u003e210\u003c/sup\u003ePb\u003csub\u003eexces\u003c/sub\u003e measurements with a gamma spectrometer (LETG Laboratory de Nantes, G\u0026eacute;olittomer-UMR 6554-CNRS, France). Samples were collected in the first 50 cm. The CFCS (Constant Flux, Constant Sedimentation rate) model was used for the \u003csup\u003e210\u003c/sup\u003ePb\u003csub\u003eexces\u003c/sub\u003e to calculate the sedimentation rate in Tahaddart estuary (Golberg 1963).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.3.3. Sediment contamination and risk assessment indices\u003c/h2\u003e \u003cp\u003eThe geochemical data (Trace metal concentration and local geochemical background) obtained in our previous study (Barjy et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) was used in this study. The sediment concentrations were compared with sediment quality guidelines (SQGs) proposed by Long et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1995\u003c/span\u003e) for marine ecosystems to evaluate the ecotoxicological risk. The effect range low (ERL), the effect range median (ERM), the threshold effect level (TEL), and Probable Effect Level (PEL) were used to evaluate the level of toxicity of metals in the sediment cores.\u003c/p\u003e \u003cp\u003eThis study used the Contamination Factor (CF) and Pollution Load index (PLI) to evaluate the level of metal pollution degree of and possible anthropogenic impact on core sediments from Tahaddart estuary. The contamination factor of the studied metals was calculated by the following equation (Hakanson, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1980\u003c/span\u003e): CF\u0026thinsp;=\u0026thinsp;C\u003csub\u003ei\u003c/sub\u003e/C\u003csub\u003eBV\u003c/sub\u003e, Where C\u003csub\u003ei\u003c/sub\u003e is the mean concentration of an individual metal examined and C\u003csub\u003eBV\u003c/sub\u003e is the background value of the individual metal. The pollution load index (PLI) is a site-specific index which provides a simple comparative mean for assessing the level of metal contamination (Tomlinson et al, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1980\u003c/span\u003e): \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{P}\\text{L}\\text{I}=\\sqrt[\\text{n}]{({\\text{C}\\text{F}}_{1}\\times {\\text{C}\\text{F}}_{2}\\times {\\text{C}\\text{F}}_{3}\\dots {\\text{C}\\text{F}}_{\\text{n}})}\\)\u003c/span\u003e\u003c/span\u003e, where n is the number of heavy metals taken into consideration and CF is the contamination factor.\u003c/p\u003e \u003cp\u003eThe potential ecological risk E\u003csup\u003ei\u003c/sup\u003e\u003csub\u003er\u003c/sub\u003e was used to assess the potential risk of each metal in the sediment (Hakanson, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1980\u003c/span\u003e):\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\text{E}\\text{i}\\text{r}=Tri\\times CFi ; RI=\\sum \\text{E}\\text{i}\\text{r}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere E\u003csub\u003er\u003c/sub\u003e\u003csup\u003ei\u003c/sup\u003e is the potential ecological risk index of an individual metal, T\u003csub\u003er\u003c/sub\u003e\u003csup\u003ei\u003c/sup\u003e is the metal toxic response factor: Zn\u0026thinsp;=\u0026thinsp;1, Pb\u0026thinsp;=\u0026thinsp;Cu\u0026thinsp;=\u0026thinsp;Ni\u0026thinsp;=\u0026thinsp;5, Cd\u0026thinsp;=\u0026thinsp;30, \u0026lsquo;\u0026lsquo;RI\u0026rsquo;\u0026rsquo; refers to the total of all risk factors for trace metals in sediments (Hankson L. et al. 1980).\u003c/p\u003e \u003cp\u003eMean sediment quality guidelines-quotient (SQG-Q) is an index that used to evaluate the possible biological effects of the coupled toxicity of trace elements in the surface sediments (Long et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). The SQG-Q was calculated for each sampling site, using the following equations:\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\text{m}\\text{E}\\text{R}\\text{M}-\\text{Q} =\\frac{{\\sum }_{\\text{i}}^{\\text{n}}\\text{C}/\\text{E}\\text{R}\\text{M}}{\\text{n}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere: C metal concentration at each sampling site, ERM is effect range median and n is the number of metals used.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Results and discussion","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Spatial-temporal LULC changes\u003c/h2\u003e \u003cp\u003eThe data obtained through the analysis of multi-temporal satellite imageries from 1984 to 2016 are illustrated in figure and Table. The land cover maps (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) demonstrate some important spatial-temporal patterns. The artificial area experienced an increasing trend from 1984 to 2016, with a decreasing in agricultural land, forests, wetlands, and beaches/dunes. The table 1 shows that the artificial area increased from 513.3 ha in 1984 and 1284 ha in 2006, to 1762.1 ha in 2016, with a rate change of 60% during 1984\u0026ndash;2006 and 27.1% during 2006\u0026ndash;2016. On other hand, the forest land decreased from 2046.7 ha in 1984 to 1419.3 ha in 2016. They are lost 336.2 ha during 1984\u0026ndash;2006 and \u0026minus;\u0026thinsp;291.2 ha during 2006\u0026ndash;2016, representing a rate of change of -19.7% and \u0026minus;\u0026thinsp;20.5%. The wetland had a lost 396.2 ha during 1984\u0026ndash;2006 and 80.5 ha during 2006\u0026ndash;2016. The beaches /dunes had a lost \u0026minus;\u0026thinsp;174.4 ha of its area during 1984\u0026ndash;2006 and \u0026minus;\u0026thinsp;68.7 ha during 2006\u0026ndash;2016. The Scrub/ herb vegetation and the agricultural land remained relatively stable in first period (1984\u0026ndash;2006). During 2006\u0026ndash;2016, The Scrub/ herb vegetation increased from 1291.6 ha to of 1727.3 ha. The agricultural land had lost 450.8 ha of its area, with a rate of variation of -8.9%. Furthermore, the beaches and dunes land recorded a decreasing area during the period 1984\u0026ndash;2016 with a rate change between \u0026minus;\u0026thinsp;4.5 and \u0026minus;\u0026thinsp;20.7%. This regression can be explained by the sediment imbalance resulting from extraction of sand for construction needs and retention of sediment by \u0026ldquo;Ibn Battuta\u0026rdquo; and \u0026ldquo;April 9, 1947\u0026rdquo; Dam at upstream site.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA detailed analysis of the intra and inter-transition of land cover classes (Table\u0026nbsp;2) reveals that 77.4% of the study area remained stable with 22.6% of change between 1984 and 2016. The most interesting change was manifested by artificial expansion at the expense of disappearance of other land-use types. For example, 1.4% of forests land was converted to artificial land and 3.1% transformed mainly into Scrub/ herb vegetation. Moreover, 5.3% agricultural land was converted also to artificial land. Another class of land cover that has undergone significant transformations was wetlands. Assessed at 28.6% in 1984, only 23.7% remained intact and 2.1% is converted into agricultural land, 1.2% into artificial land. This unconventional land cover transition is mainly linked to the construction of the thermal power station and the radio station in 1949; the TGV construction and the Rabat-Tangier highway in 2005, induced predominantly by Tangier\u0026rsquo;s urban development (Barjy et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Radionuclide profiles and sediment chronology\u003c/h2\u003e \u003cp\u003eThe plot of \u003csup\u003e210\u003c/sup\u003ePb\u003csub\u003exs\u003c/sub\u003e and \u003csup\u003e137\u003c/sup\u003eCs activities against depth for the Tahaddart sediment core is displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The surface \u003csup\u003e210\u003c/sup\u003ePb\u003csub\u003exs\u003c/sub\u003e activities was around to 34.1 Bq / kg (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA), relatively lower compared to activities found in other coastal ecosystems (Bellucci et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Alonso-hernandez and Ruiz-fern\u0026aacute;ndez 2011). A detailed analysis of the \u003csup\u003e210\u003c/sup\u003ePb\u003csub\u003exs\u003c/sub\u003e distribution with depth suggests that the recording can be divided into two distinct segments. At the top of sediment core (0 to 20 cm), the \u003csup\u003e210\u003c/sup\u003ePb\u003csub\u003exs\u003c/sub\u003e activities decreased exponentially with depth, indicating regular sedimentation. However, the \u003csup\u003e210\u003c/sup\u003ePb\u003csub\u003exs\u003c/sub\u003e activities were relatively constant throughout the 20\u0026ndash;50 cm segment of the core. A flattening of \u003csup\u003e210\u003c/sup\u003ePb\u003csub\u003exs\u003c/sub\u003e indicates either a dilution of the atmospheric flux of 210Pbxs by mixing of sediments, acceleration of sedimentation and / or the occurrence of slumps due to, for example, heavy rains (Alonso-hernandez et al, 2011).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe \u003csup\u003e137\u003c/sup\u003eCs activities range from 0.3 to 1.3 Bq / kg which are below the detection limit (2Bq / kg), which means that dating using this radionuclide is difficult (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This has also been observed in other coastal ecosystems such as: Yucatan Peninsula in Mexico (Ruiz-fern\u0026aacute;ndez, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and Havana Bay in Cuba (Alonso-hernandez et al, 2011). The application of CFCS model (constant flux, constant supply), gave a sedimentation rate of 0.53 cm / year, which is comparable to that found by Khalfaoui et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) for the Tahaddart estuary. The slight difference between the two sedimentation rates is a maybe a result of the limited number of samples analyzed or located in the area (Khalfaoui et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). On the other hand, the sedimentation rate is higher than that recorded at Loukous estuary (Morocco) and Venice lagoon, but lower than the maximum rate recorded at Oum Errabia estuary and the Moulay Bousselham lagoon, Morocco (Kalloul et al, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Maanan M. et al 2009; Mhammdi et al, 2010 Bellucci et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2007\u003c/span\u003e)(Table\u0026nbsp;3).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Sediment quality\u003c/h2\u003e \u003cp\u003eThe concentration of the studied metals in the dated sediment cores derived from Tahaddart estuary exhibited increasing trends, with the highest concentrations observed at the upper parts of sediment cores as obtained from our previous study (Barjy et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). To investigate the historical metals contamination, a comparative study was performed using the sediment quality guidelines (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The results showed that all concentrations in trace elements are below the values of ERM; thus, the concentrations of all trace elements in sediment cores do not represent any ecological risk. As indicated in figure, Zn and Cu levels in both cores were lower than TEL. Ni level in sediment exceeded the TEL values indicated in the SQG but still below the PEL values, while Pb, Cd and Cr concentrations were higher than the TEL values at upper parts of the cores.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBased on the previous results, contamination factor (CF) and pollution load index (PLI) have been calculated for each core, the results are given in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e below. The CF varied within a range of 0.53\u0026ndash;2.13 for Zn; 0.75\u0026ndash;2.01 for Pb; 0.64\u0026ndash;2.60 for Cu; 0.57\u0026ndash;1.69 for Ni; 0.66\u0026ndash;2.22 for As; 0.23\u0026ndash;19.11 for Cd and 0.65\u0026ndash;3.33 for Cr in TC1\u0026rsquo;s core ; and 0.79 and 2.11 for Ni; 0.39 and 2.10 for Cu; 0.97 and 2.10 for Zn; 0.61 and 2.95 for Cr; 0.77 and 2.13 for Pb; 0.21 and 16.09 for Cd; 0.95 and 2.63 for As in TC2\u0026rsquo;s core (Table\u0026nbsp;4). The minimum values ​​are generally found at the base of the cores, while the maximum values ​​are observed at the upper part. For Cd, the vertical distribution of CF reveals a strong contamination (FC\u0026thinsp;\u0026ge;\u0026thinsp;6). For As, Pb, Ni, Zn and Cr, the calculated FCs indicate moderate contamination at the top, while the base of the core is marked by low contamination.\u003c/p\u003e \u003cp\u003eAccording to table 4, the values ​​of pollution load index (PLI) for the two cores (TC1 and CT2) are between 0.64 and 2.72 with an average of order 1.62 for the CT1 core and between 0.63 and 2.86 with an average of 1.67 for CT2 core. The results ​​indicate that almost of the two cores have values ​​higher than 1, which suggests the existence of anthropogenic pollution. The vertical distribution of PLI highlighted strong values ​​at the top of the cores (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, the ERM quotients (ERM-Q) of individual TEs indicated that Ni present a \u0026lsquo;\u0026lsquo;High-medium Priority Site\u0026rsquo; between 5\u0026ndash;30 cm (CT1) et 0\u0026ndash;5/15- 70cm (CT2). The others TEs (Cd, Cu and Pb) which classified them as \"Medium-low priority side\", except Zn and Cr have presented a \"Low Priority Site\". All the core sediment exhibited M-ERM-Q values\u0026thinsp;\u0026gt;\u0026thinsp;0.1 confirming them as \u0026ldquo;medium-low priority sites\u0026rdquo;. The M-ERM-Q varied within a range of 0.06\u0026ndash;0.18 for CT1, and 0.07\u0026ndash;0.2 for CT2 which mean that the combination of six TEs (Cd, Cr, Cu, Ni, Pb, and Zn) might have a 21% probability of toxicity posing potential risk to the aquatic organisms (Table\u0026nbsp;5).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe vertical distribution of the potential ecological risk index (Eir) for single TES at CT1 and CT2 cores indicated decreasing pollution intensity in the following order (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e): Cd\u0026thinsp;\u0026gt;\u0026thinsp;Cu\u0026thinsp;\u0026gt;\u0026thinsp;Pb\u0026thinsp;\u0026gt;\u0026thinsp;Ni\u0026thinsp;\u0026gt;\u0026thinsp;Cr\u0026thinsp;\u0026gt;\u0026thinsp;Zn, with individual mean values of 205.1; 8.3; 6.3; 5.7; 3.3 and 1.1; respectively for CT1 core and 209.8; 6.5; 5.9; 5.7; 2.4 and 1.5 for the CT2 core. It is worth noting that the E\u003csub\u003eir\u003c/sub\u003e max values of all TEs were less than 40, and they posed a \"low potential ecological risk\", except for Cd where the risk was \" high potential ecological risk\" at the surface. The results highlighted the risk that Cd pose to the human body and the ecosystem. The H\u0026aring;kanson potential ecological risk index range for all sampling sites is from 24.4 and 608.1, indicating moderate to high potential ecological risk at surface (Table\u0026nbsp;5).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4. historical anthropogenic impacts on Tahaddart estuary\u003c/h2\u003e \u003cp\u003eThe results presented in this study provide important information about the historical contamination of the Tahaddart estuary in the last 150 years. Anthropogenic activities around the estuary have left their fingerprint on the geochemical records (Barjy et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The results obtained so far confirm that the study area has experienced several changes patterns induced by urbanization and industrialization process during the past 32 years. Overall, land cover in the study area is primarily agricultural and has remained constant, while the estuary was a subject to rapid artificial intensification since the 1984s, which is reflected in reduction of agricultural land, forests, wetlands, and beaches/dunes. This degradation in the natural environment is resulting from many factors like the construction of the thermal power station and the radio station in 1949; the TGV construction and the Rabat-Tangier highway in 2005, induced predominantly by Tangier\u0026rsquo;s urban development (Barjy et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Tahiri et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Several authors (Cesar \u0026amp; al., 2002; Mas, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Al-tahir, 2015; Gupta and Sprawl, 2019) have blamed population growth and some kind of exploitation as being responsible for land cover change. This situation of lands degradation in the Tahaddart estuary is also observed in other Moroccan ecosystems like Oualidia and Moulay Boussalham lagoons (Maanan et al, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough the benefit of urbanization and agriculture development, some previous studies have suggested that the inappropriate land cover has been discussed as a factor that can affect environment quality of coastal ecosystem (M.C, 2019; Tang et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; ). Several authors argue that the data extracted from sediment cores provide important information of the contamination history over the past decades (Maanan et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Irabien and al., 2008; Mahu et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Hasan et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Yang et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, in Tahaddart estuary, the highest values of contamination factor, pollution load index, ERM quotients (ERM-Q) and ecological risk index for all the metals studied were found at the upper portion of sediment cores confirming that there has been some anthropogenic influence on this estuary in recent times (since 1984), which receive a significant among of trace elements due to direct discharge from anthropogenic activities (Rabat-Tangier highway, thermal power station\u0026hellip;) and the extensive use of fertilizers on farmlands around the estuary. The data obtained confirm gradually upward increasing trends in trace metal; spatially from 1984 when anthropogenic activities increased according to the evolution of land cover analyses. Recent case studies prove that some trace elements are mainly human-induced in coastal ecosystems (Zourarah B.. et al \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Zhuang et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Sea et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The result also revealed a gradual deterioration in the environment quality of Tahaddart estuary according to the sediment quality index, the studied zone was moderately impacted, with a 21% risk of biotoxic impacts. This sediment that may act in the future as a potential long term source of pollutants that could directly affect the water quality of estuary (Veerasingam et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). However, additional efforts should be made to avoid the spreading of contaminants in the lagoon and the preindustrial values obtained from the historical reconstruction provided could be used as the reference levels for environmental restoration purposes.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eIn this study, the coastal zone of Tahaddart estuary is taken as the research area. The changes of estuary zone over the years are analyzed, and its ecological and environmental status is scientifically evaluated, the comprehensive management and protection measures are proposed.\u003c/p\u003e \u003cp\u003eThe main conclusions are as follows:\u003c/p\u003e \u003cp\u003e \u003col style=\"list-style-type:lower-alpha;\"\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eBased on the land cover data in the study area, it is found that artificial land area is gradually increasing, and the area of forests, wetlands, agricultural areas, beaches, and dunes during the period 1984\u0026ndash;2016. This degradation is essentially linked to the development of socio-economic activities (sand extraction, urban expansion, etc., industrial development).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe isotope analysis of sediment core indicates that sedimentation rate is 0.53 cm/year indicated by 210 Pb, which means that one meter of sediment covers a period of 189 years.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe temporal evolution of contamination and ecological index is characterized by increasing trends over the past last 150 years. Sediment quality analyses based on contamination index and sediment quality guidelines indicated a generally moderate quality sedimentary environment in Tahaddart estuary with 21% probability of acute toxicity.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThis work reveals important information about historical contamination in Tahaddart estuary that can be used to protect and improve the quality of this ecosystem.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding \u0026nbsp;\u003c/strong\u003eThe authors received no financial support for the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u0026nbsp; The authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions\u003c/strong\u003e All authors contributed to the study conception. MEB, HB, NH, BH, and MeM were responsible for preparation of materials, data collection and analysis. MEB, HB, MM and MeM verified the analytical methods. MEB and MeM wrote the first draft of the manuscript and all authors commented on previous versions of it. All authors discussed the results and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e The datasets generated and analysed during this study and its supplementary information files are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval\u003c/strong\u003e\u0026nbsp; Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u0026nbsp; Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u0026nbsp; Not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlonso-hernandez, Carlos M, and Ana Carolina Ruiz-fern\u0026aacute;ndez. 2011. \u0026ldquo;Reconstruction of Sedimentation and Pollution in Havana Bay, Cuba,\u0026rdquo; no. https://doi.org/10.1016/j.jhazmat.2011.09.037.\u003c/li\u003e\n\u003cli\u003eBarjy, Meryem El et al. 2018. \u0026ldquo;Human and Ecological Risk Assessment : An International Contamination and Environmental Risk Assessment of Heavy Metals in Marine Sediments from Tahaddart Estuary ( NW of Morocco ).\u0026rdquo; \u003cem\u003eHuman and Ecological Risk Assessment\u003c/em\u003e 0(0): 1\u0026ndash;16. https://doi.org/10.1080/10807039.2018.1495056.\u003c/li\u003e\n\u003cli\u003eBeach, West Palm, Cesar A Berlanga-robles, and Arturo Ruiz-lunar. 2002. \u0026ldquo;Land Use Mapping and Change Detection in the Coastal Zone of Northwest Mexico Using Remote Sensing Techniques.\u0026rdquo;\u003c/li\u003e\n\u003cli\u003eBellucci, L G, M Frignani, J K Cochran, and S Albertazzi. 2007. \u0026ldquo;Pb and 137 Cs as Chronometers for Salt Marsh Accretion in the Venice Lagoon e Links to Flooding Frequency and Climate Change\u0026rdquo; 97. https://doi.org/10.1016/j.jenvrad.2007.03.005.\u003c/li\u003e\n\u003cli\u003eBellucci, L G, M Frignani, J K Cochran, and S Albertazzi. 2007. \u0026ldquo;Pb and 137 Cs as Chronometers for Salt Marsh Accretion in the Venice Lagoon e Links to Flooding Frequency and Climate Change\u0026rdquo; 97. https://doi.org/10.1016/j.jenvrad.2007.03.005.\u003c/li\u003e\n\u003cli\u003eC, Mohammed Firoz. 2019. \u0026ldquo;Impact of Land Use and Land Cover Change on the Environmental Quality of a Region : A Case of Ernakulam District in Kerala , India.\u0026rdquo; 11(2): 102\u0026ndash;35.\u003c/li\u003e\n\u003cli\u003eDadson, Ishmael Yaw. 2016. \u0026ldquo;Land Use and Land Cover Change Analysis along the Coastal Regions of Cape Coast and Sekondi\u0026rdquo; 8 (2): 108\u0026ndash;26. \u003c/li\u003e\n\u003cli\u003eEffendi, Hefni, Mujizat Kawaroe, and Dea Fauzia. 2016. \u0026ldquo;Ecological Risk Assessment of Heavy Metal Pollution in Surface Sediment of Mahakam Delta , East Kalimantan.\u0026rdquo; 33: 574\u0026ndash;82.\u003c/li\u003e\n\u003cli\u003eEL MRINI A. (2004) : L\u0026rsquo;estuaire de Tahaddart (Province de Tanger \u0026ndash; Maroc nord occidental) : Etudes pr\u0026eacute;liminaires. \u003cem\u003eM\u0026eacute;m. DESA, Univ. Abdelmalik Essaadi, FS. T\u0026eacute;touan\u003c/em\u003e, p. 52.\u003c/li\u003e\n\u003cli\u003eGoldberg, E. (1963).Geochronology with lead-210, International Atomic Energy Agency, pp. 121\u0026ndash;131.\u003c/li\u003e\n\u003cli\u003eGulf, İzmit et al. 2023. \u0026ldquo;Assessment of Eco-Toxicological and Health Risks of Core Sediment From.\u0026rdquo; \u003cem\u003eRegional Studies in Marine Science\u003c/em\u003e 64: 103059. https://doi.org/10.1016/j.rsma.2023.103059.\u003c/li\u003e\n\u003cli\u003eGupta, R D, and Urban Sprawl. 2019. \u0026ldquo;Change Assessment of Spatio-Temporal Dynamics of Land Use / Land Cover Using Remote Sensing and GIS : A Case Study of Lucknow City ( 1993-2019 ),\u0026rdquo; no. December.\u003c/li\u003e\n\u003cli\u003eHakanson, L., 1980. An ecological risk index for aquatic pollution control. A sedimentological approach. Water Res. 14, 975\u0026ndash;1001.\u003c/li\u003e\n\u003cli\u003eHasan, Rakibul et al. 2023. \u0026ldquo;Vertical Distribution , Contamination Status and Ecological Risk Assessment of Heavy Metals in Core Sediments from a Mangrove-Dominated Tropical River.\u0026rdquo; \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e 189(November 2022): 114804. https://doi.org/10.1016/j.marpolbul.2023.114804.\u003c/li\u003e\n\u003cli\u003eIrabien, M. J. et al. 2008. \u0026ldquo;A 130 Year Record of Pollution in the Suances Estuary (Southern Bay of Biscay): Implications for Environmental Management.\u0026rdquo; \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e 56(10): 1719\u0026ndash;27.\u003c/li\u003e\n\u003cli\u003eKaliraj, S, N Chandrasekar, K K Ramachandran, Y Srinivas, and S Saravanan. 2017. \u0026ldquo;The Egyptian Journal of Remote Sensing and Space Sciences Coastal Landuse and Land Cover Change and Transformations of Kanyakumari Coast , India Using Remote Sensing and GIS.\u0026rdquo; The Egyptian Journal of Remote Sensing and Space Sciences 20 (2): 169\u0026ndash;85. https://doi.org/10.1016/j.ejrs.2017.04.003.\u003c/li\u003e\n\u003cli\u003eKalloul S, Hamid W, Maanan M, Robin M, Sayouty EH, Zourarah B (2012).Source contributions to heavy metal fluxes into the Loukous Estuary (Moroccan Atlantic Coast). J Coast Res 28:174\u0026ndash;183\u003c/li\u003e\n\u003cli\u003eKhalfaoui, Otmane, Laurent Dezileau, Jean-philippe Degeai, and Maria Snoussi. 2020. \u0026ldquo;A Late Holocene Record of Marine High- Energy Events along the Atlantic Coast of Morocco : New Evidences from the Tahaddart Estuary.\u0026rdquo; 5.\u003c/li\u003e\n\u003cli\u003eLo, Kwong Fai A, and Chethika W D Gunasiri. 2016. \u0026ldquo;Impact of Coastal Land Use Change on Shoreline Dynamics in Yunlin County, Taiwan,\u0026rdquo; no. October 2014. https://doi.org/10.3390/environments1020124\u003c/li\u003e\n\u003cli\u003eLo, Kwong Fai A, and Chethika W D Gunasiri. 2016. \u0026ldquo;Impact of Coastal Land Use Change on Shoreline Dynamics in Yunlin County, Taiwan.\u0026rdquo; (October 2014).\u003c/li\u003e\n\u003cli\u003eLong, E. R.; Field, L. J.; MacDonald, D. D. (1998).Predicting toxicity in marine sediments with numerical sediment quality guidelines.Environ. Toxicol.Chem. 17 (4), 714-727.\u003c/li\u003e\n\u003cli\u003eLong, E.R., MacDonald, D.D., Smith, S.L., Calder, F.D., 1995. Incidence of adverse biological effects within ranges of chemical concentrations in marine and estuarine sediments. Environ. Manage. 19, 81\u0026ndash;97.\u003c/li\u003e\n\u003cli\u003eMaanan M, Landesman C, Maanan M, Zourarah B, Fattal P, Sahabi M (2013). Evaluation of the anthropogenic influx of metal and metalloid contaminants into the Moulay Bousselham lagoon, Morocco, using chemometric methods coupled to geographical information systems. Environmental Sciences and Pollution Research 20: 4729\u0026ndash;474.\u003c/li\u003e\n\u003cli\u003eMaanan, Mohamed, Mohammed Saddik, Mehdi Maanan, and Mohamed Chaibi. 2014. \u0026ldquo;Environmental and Ecological Risk Assessment of Heavy Metals in Sediments of Nador Lagoon , Morocco.\u0026rdquo; \u003cem\u003eEcological Indicators\u003c/em\u003e 48: 616\u0026ndash;26. http://dx.doi.org/10.1016/j.ecolind.2014.09.034.\u003c/li\u003e\n\u003cli\u003eMaanan. 2014a. \u0026ldquo;Evaluation of the Anthropogenic Influx of Metal and Metalloid Contaminants into the Moulay Bousselham ... Evaluation of the Anthropogenic Influx of Metal and Metalloid Contaminants into the Moulay Bousselham Lagoon , Morocco , Using Chemometric Methods Co,\u0026rdquo; no. January 2013. https://doi.org/10.1007/s11356-012-1399-6.\u003c/li\u003e\n\u003cli\u003eMahu, Edem et al. 2016. \u0026ldquo;Geochronology and Historical Deposition of Trace Metals in Three Tropical Estuaries in the Gulf of Guinea.\u0026rdquo; \u003cem\u003eEstuarine, Coastal and Shelf Science\u003c/em\u003e 177: 31\u0026ndash;40. http://dx.doi.org/10.1016/j.ecss.2016.05.007.\u003c/li\u003e\n\u003cli\u003eMas, J F. 2004. \u0026ldquo;Mapping Land Use / Cover in a Tropical Coastal Area Using Satellite Sensor Data , GIS and Artificial Neural Networks\u0026rdquo; 59: 219\u0026ndash;30. https://doi.org/10.1016/j.ecss.2003.08.011.\u003c/li\u003e\n\u003cli\u003eMas, J F. 2004. \u0026ldquo;Mapping Land Use / Cover in a Tropical Coastal Area Using Satellite Sensor Data , GIS and Artificial Neural Networks.\u0026rdquo; 59: 219\u0026ndash;30.\u003c/li\u003e\n\u003cli\u003eMassik Z., Lakhdar I. \u0026amp; Zizah S., 2003. Impact d\u0026rsquo;une activit\u0026eacute; de dragage de sables sur la faune et la flore de l\u0026rsquo;estuaire de Tahaddart (Cas de l\u0026rsquo;estuaire de Tahaddart). Colloque International sur les sables et Environnement (Solution Alternatives). Casablanca, Maroc, 1-21 p.\u003c/li\u003e\n\u003cli\u003eMhamdi Alaoui A., Choura M., Maanan M., Zourarah B., Robin M., FreitasConcei\u0026ccedil;\u0026atilde;o M., Andrade C., Khalid M., Carruesco C. (2010).Metal fluxes to the sediments of the Moulay Bousselham lagoon, Morocco. Environmental Earth Sciences, Vol. 61, No. 2, pp. 275-286.\u003c/li\u003e\n\u003cli\u003eNachite D., Bekkali R., Macias A. \u0026amp; Anfuso G., 2008. El estuario de Tahaddart: las bases para una gesti\u0026oacute;n integrada de un espacio en plena transformaci\u0026oacute;n. Service de Publication de l\u0026rsquo;Universit\u0026eacute; de Cadix (Espagne), 33 p\u003c/li\u003e\n\u003cli\u003eRifai N. et al. 2018. \u0026ldquo;\u0026Eacute;VALUATION DE LA DYNAMIQUE DE L\u0026rsquo;OCCUPATION DU SOL DANS LA ZONE HUMIDE RAMSAR DE TAHADDART (NORD-OUEST DU MAROC) Nabil R.\u0026rdquo; 73(2): 142\u0026ndash;52.\u003c/li\u003e\n\u003cli\u003eRomano, Elena, Giovanni De Giudici, Luisa Bergamin, Stefano Andreucci, Chiara Maggi, Giancarlo Pierfranceschi, Maria Celia Magno, and Antonella Ausili. 2017. \u0026ldquo;The Marine Sedimentary Record of Natural and Anthropogenic Contribution from the Sulcis- Iglesiente Mining District (Sardinia, Italy).\u0026rdquo; Marine Pollution Bulletin 122 (1\u0026ndash;2): 331\u0026ndash; 43. https://doi.org/10.1016/j.marpolbul.2017.06.070\u003c/li\u003e\n\u003cli\u003eRuiz-fern\u0026aacute;ndez, Ana Carolina. 2016. \u0026ldquo;Sedimentary Records of Recent Sea Level Rise and Acceleration in the Yucatan Peninsula Article in Science of The Total Environment \u0026middot; September 2016.\u0026rdquo; Science of the Total Environment 573 (September): 1063\u0026ndash;69. https://doi.org/10.1016/j.scitotenv.2016.08.142.\u003c/li\u003e\n\u003cli\u003eSarı, E., \u0026Uuml;nl\u0026uuml;, S., Balcı, N., Apak, R., Kurt, M.A., Koldemir, B., 2013. Evaluation of contamination by selected elements in a Turkish port. Pol. J. Environ. Stud. 22, 841\u0026ndash;847\u003c/li\u003e\n\u003cli\u003eSea, South Yellow et al. 2023. \u0026ldquo;Ecological and Environmental Risks of Heavy Metals in Sediments in Dingzi.\u0026rdquo; \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e 188(December 2022): 114683. https://doi.org/10.1016/j.marpolbul.2023.114683.\u003c/li\u003e\n\u003cli\u003eShi, Cui et al. 2022. \u0026ldquo;Science of the Total Environment Heavy Metals and Pb Isotopes in a Marine Sediment Core Record Environmental Changes and Anthropogenic Activities in the Pearl River Delta over a Century.\u0026rdquo; \u003cem\u003eScience of the Total Environment\u003c/em\u003e 814(188): 151934. https://doi.org/10.1016/j.scitotenv.2021.151934.\u003c/li\u003e\n\u003cli\u003eŞimşek, A., \u0026Ouml;zko\u0026ccedil;, H.B., Bakan, G., 2022. Environmental, ecological and human health risk assessment of heavy metals in sediments at Samsun-Tekkek\u0026ouml;y, North of Turkey. Environ. Sci. Pollut. Res. 29, 2009\u0026ndash;2023.\u003c/li\u003e\n\u003cli\u003eTahiri. M, Achab M., Emran A., Tahiri A., Hakdaoui M., El Hadi H., (2014). Lithology data conctribution in hydrographic network distribution using remote sensing and GIS: case of Tahaddart basin, northwestern Rif, Morocco. International Journal of Advanced Research (2014), Volume 2, Issue 5, 380-391.\u003c/li\u003e\n\u003cli\u003eTahiri. M, Achab M., Emran A., Tahiri A., Hakdaoui M., El Hadi H., (2014). Lithology data conctribution in hydrographic network distribution using remote sensing and GIS: case of Tahaddart basin, northwestern Rif, Morocco. International Journal of Advanced Research (2014), Volume 2, Issue 5, 380-391.\u003c/li\u003e\n\u003cli\u003eTang, Huan et al. 2022. \u0026ldquo;Impact of Land Cover Change on a Typical Mining Region and Its Ecological Environment Quality Evaluation Using Remote Sensing Based Ecological Index ( RSEI ).\u0026rdquo;\u003c/li\u003e\n\u003cli\u003eTomlinson, D., Wilson, J., Harris, C., Jeffrey, D., 1980. Problems in the assessment of heavy-metal levels in estuaries and the formation of a pollution index. Helgol\u0026auml;nder Meeresuntersuchungen 33, 566\u0026ndash;575.\u003c/li\u003e\n\u003cli\u003eTown, Bo, Musa Tarawally, Wenbo Xu, Weiming Hou, and Terence Darlington Mushore. 2018. \u0026ldquo;Comparative Analysis of Responses of Land Surface Temperature to Long-Term Land Use / Cover Changes between a Coastal and Inland City: A Case Of,\u0026rdquo; 1\u0026ndash;18. https://doi.org/10.3390/rs10010112\u003c/li\u003e\n\u003cli\u003eVald, J, Luc Ortlieb, A Sifeddine, and A Castillo. 2023. \u0026ldquo;Human-Induced Metals Accumulation in Sediments of an Industrialized Bay of Northern Chile . An Enrichment and Ecological Risk Assessment Based on Preindustrial Values.\u0026rdquo; 189(November 2022).\u003c/li\u003e\n\u003cli\u003eVeerasingam, S, P Vethamony, R Mani Murali, and B Fernandes. 2015. \u0026ldquo;Depositional Record of Trace Metals and Degree of Contamination in Core Sediments from the Mandovi Estuarine Mangrove Ecosystem , West Coast of India.\u0026rdquo; \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e 91(1): 362\u0026ndash;67. http://dx.doi.org/10.1016/j.marpolbul.2014.11.045.\u003c/li\u003e\n\u003cli\u003eWang, Jie, Guijian Liu, Jiamei Zhang, Houqi Liu, and Paul K.S. Lam. 2016. \u0026ldquo;A 59-Year Sedimentary Record of Metal Pollution in the Sediment Core from the Huaihe River, Huainan, Anhui, China.\u0026rdquo; Environmental Science and Pollution Research 23 (23): 23533\u0026ndash;45. https://doi.org/10.1007/s11356-016-7587-z.\u003c/li\u003e\n\u003cli\u003eYang, Guohuan et al. 2020. \u0026ldquo;Heavy Metals of Sediment Cores in Dachan Bay and Their Responses to Human Activities.\u0026rdquo; \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e 150(July 2019): 110764. https://doi.org/10.1016/j.marpolbul.2019.110764.\u003c/li\u003e\n\u003cli\u003eZhuang, Haihai et al. 2022. \u0026ldquo;Assessment of the Vertical Characteristics and Contamination Levels of Toxic Metals in Sediment Cores from Typical Chinese Intertidal Zones.\u0026rdquo; \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e 185(PA): 114307. https://doi.org/10.1016/j.marpolbul.2022.114307.\u003c/li\u003e\n\u003cli\u003eZourarah B.. et al. 2009. \u0026ldquo;Sedimentary Records of Anthropogenic Contribution to Heavy Metal Content in Oum Er Bia Estuary ( Morocco ).\u0026rdquo; (February).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTableau 1 : \u0026nbsp;Area and amount of change in different land cover categories in the Tahaddart estuary during 1984-2016.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"897\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.456375838926174%\" style=\"width: 19.1489%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.982102908277405%\" colspan=\"2\" style=\"width: 14.772%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1984\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.982102908277405%\" colspan=\"2\" style=\"width: 14.3617%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.982102908277405%\" colspan=\"2\" style=\"width: 14.3617%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.982102908277405%\" colspan=\"2\" style=\"width: 15.0456%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1984-2006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.982102908277405%\" colspan=\"2\" style=\"width: 14.2249%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2006-2016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.39464882943144%\" style=\"width: 19.1489%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eha\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 6.155%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 5.7447%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 5.7447%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.243032329988852%\" style=\"width: 6.4286%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\" style=\"width: 7.9331%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.243032329988852%\" style=\"width: 6.2918%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.39464882943144%\" style=\"width: 19.1489%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eArtificial area\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e513.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 6.155%;\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e1284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 5.7447%;\"\u003e\n \u003cp\u003e8.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e1762.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 5.7447%;\"\u003e\n \u003cp\u003e11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e770.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.243032329988852%\" style=\"width: 6.4286%;\"\u003e\n \u003cp\u003e60.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\" style=\"width: 7.9331%;\"\u003e\n \u003cp\u003e478.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.243032329988852%\" style=\"width: 6.2918%;\"\u003e\n \u003cp\u003e27.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.39464882943144%\" style=\"width: 19.1489%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAgricultural land\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e5434.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 6.155%;\"\u003e\n \u003cp\u003e36.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e5543.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 5.7447%;\"\u003e\n \u003cp\u003e37.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e5092.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 5.7447%;\"\u003e\n \u003cp\u003e34.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e108.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.243032329988852%\" style=\"width: 6.4286%;\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\" style=\"width: 7.9331%;\"\u003e\n \u003cp\u003e-450.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.243032329988852%\" style=\"width: 6.2918%;\"\u003e\n \u003cp\u003e-8.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.39464882943144%\" style=\"width: 19.1489%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eForest land\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e2046.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 6.155%;\"\u003e\n \u003cp\u003e13.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e1710.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 5.7447%;\"\u003e\n \u003cp\u003e11.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e1419.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 5.7447%;\"\u003e\n \u003cp\u003e9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e-336.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.243032329988852%\" style=\"width: 6.4286%;\"\u003e\n \u003cp\u003e-19.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\" style=\"width: 7.9331%;\"\u003e\n \u003cp\u003e-291.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.243032329988852%\" style=\"width: 6.2918%;\"\u003e\n \u003cp\u003e-20.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.39464882943144%\" style=\"width: 19.1489%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eScrub and herb Vegetation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e1264.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 6.155%;\"\u003e\n \u003cp\u003e8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e1291.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 5.7447%;\"\u003e\n \u003cp\u003e8.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e1727.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 5.7447%;\"\u003e\n \u003cp\u003e11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e26.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.243032329988852%\" style=\"width: 6.4286%;\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\" style=\"width: 7.9331%;\"\u003e\n \u003cp\u003e435.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.243032329988852%\" style=\"width: 6.2918%;\"\u003e\n \u003cp\u003e25.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.39464882943144%\" style=\"width: 19.1489%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBeaches, dunes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e841.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 6.155%;\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e666.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 5.7447%;\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e598.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 5.7447%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e-174.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.243032329988852%\" style=\"width: 6.4286%;\"\u003e\n \u003cp\u003e-26.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\" style=\"width: 7.9331%;\"\u003e\n \u003cp\u003e-68.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.243032329988852%\" style=\"width: 6.2918%;\"\u003e\n \u003cp\u003e-11.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.39464882943144%\" style=\"width: 19.1489%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWetland\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e4300.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 6.155%;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e3904.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 5.7447%;\"\u003e\n \u003cp\u003e26.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e3823.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 5.7447%;\"\u003e\n \u003cp\u003e25.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e-396.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.243032329988852%\" style=\"width: 6.4286%;\"\u003e\n \u003cp\u003e-10.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\" style=\"width: 7.9331%;\"\u003e\n \u003cp\u003e-80.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.243032329988852%\" style=\"width: 6.2918%;\"\u003e\n \u003cp\u003e-2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.39464882943144%\" style=\"width: 19.1489%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWater body\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e402.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 6.155%;\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e368.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 5.7447%;\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.4726867335563%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e345.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.574136008918618%\" style=\"width: 5.7447%;\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\" style=\"width: 8.617%;\"\u003e\n \u003cp\u003e-33.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.243032329988852%\" style=\"width: 6.4286%;\"\u003e\n \u003cp\u003e-9.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\" style=\"width: 7.9331%;\"\u003e\n \u003cp\u003e-22.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.243032329988852%\" style=\"width: 6.2918%;\"\u003e\n \u003cp\u003e-6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTableau 2: The land cover transition matrix.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"740\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.152496626180837%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.869095816464238%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"75.97840755735493%\" colspan=\"8\"\u003e\n \u003cp\u003e\u003cstrong\u003e2016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.152496626180837%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.869095816464238%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.581646423751687%\"\u003e\n \u003cp\u003e\u003cstrong\u003eforest land\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.256410256410257%\"\u003e\n \u003cp\u003e\u003cstrong\u003eScrub/ herb vegetation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.906882591093117%\"\u003e\n \u003cp\u003e\u003cstrong\u003ebeaches /dunes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.906882591093117%\"\u003e\n \u003cp\u003e\u003cstrong\u003eWater body\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.256410256410257%\"\u003e\n \u003cp\u003e\u003cstrong\u003eagricultural land\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.470985155195681%\"\u003e\n \u003cp\u003e\u003cstrong\u003eartificial area\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e\u003cstrong\u003ewetland\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.906882591093117%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.152496626180837%\" rowspan=\"8\"\u003e\n \u003cp\u003e\u003cstrong\u003e1984\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.869095816464238%\"\u003e\n \u003cp\u003e\u003cstrong\u003eforest land\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.581646423751687%\"\u003e\n \u003cp\u003e8,7\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.256410256410257%\"\u003e\n \u003cp\u003e3,1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.906882591093117%\"\u003e\n \u003cp\u003e0,0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.906882591093117%\"\u003e\n \u003cp\u003e0,0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.256410256410257%\"\u003e\n \u003cp\u003e0,4\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.470985155195681%\"\u003e\n \u003cp\u003e1,4\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e0,3\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.906882591093117%\"\u003e\n \u003cp\u003e\u003cstrong\u003e13,8\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.16860465116279%\"\u003e\n \u003cp\u003e\u003cstrong\u003eScrub/ herb vegetation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.319767441860465%\"\u003e\n \u003cp\u003e0,5\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.046511627906977%\"\u003e\n \u003cp\u003e6,0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e0,0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e0,1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.046511627906977%\"\u003e\n \u003cp\u003e0,4\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.354651162790697%\"\u003e\n \u003cp\u003e1,2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.284883720930232%\"\u003e\n \u003cp\u003e0,5\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e\u003cstrong\u003e8,7\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.16860465116279%\"\u003e\n \u003cp\u003e\u003cstrong\u003ebeaches /dunes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.319767441860465%\"\u003e\n \u003cp\u003e0,1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.046511627906977%\"\u003e\n \u003cp\u003e0,2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e4,4\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e0,1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.046511627906977%\"\u003e\n \u003cp\u003e0,2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.354651162790697%\"\u003e\n \u003cp\u003e0,0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.284883720930232%\"\u003e\n \u003cp\u003e0,0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e\u003cstrong\u003e5,1\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.16860465116279%\"\u003e\n \u003cp\u003e\u003cstrong\u003eWater body\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.319767441860465%\"\u003e\n \u003cp\u003e0,0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.046511627906977%\"\u003e\n \u003cp\u003e0,0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e0,0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e1,4\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.046511627906977%\"\u003e\n \u003cp\u003e0,4\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.354651162790697%\"\u003e\n \u003cp\u003e0,0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.284883720930232%\"\u003e\n \u003cp\u003e0,7\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2,7\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.16860465116279%\"\u003e\n \u003cp\u003e\u003cstrong\u003eagricultural land\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.319767441860465%\"\u003e\n \u003cp\u003e0,1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.046511627906977%\"\u003e\n \u003cp\u003e1,0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e0,1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e0,2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.046511627906977%\"\u003e\n \u003cp\u003e30,5\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.354651162790697%\"\u003e\n \u003cp\u003e5,3\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.284883720930232%\"\u003e\n \u003cp\u003e0,5\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e\u003cstrong\u003e37,7\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.16860465116279%\"\u003e\n \u003cp\u003e\u003cstrong\u003eartificial area\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.319767441860465%\"\u003e\n \u003cp\u003e0,1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.046511627906977%\"\u003e\n \u003cp\u003e0,3\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e0,0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e0,0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.046511627906977%\"\u003e\n \u003cp\u003e0,3\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.354651162790697%\"\u003e\n \u003cp\u003e2,7\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.284883720930232%\"\u003e\n \u003cp\u003e0,1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e\u003cstrong\u003e3,5\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.16860465116279%\"\u003e\n \u003cp\u003e\u003cstrong\u003ewetland\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.319767441860465%\"\u003e\n \u003cp\u003e0,2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.046511627906977%\"\u003e\n \u003cp\u003e1,0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e0,5\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.046511627906977%\"\u003e\n \u003cp\u003e2,1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.354651162790697%\"\u003e\n \u003cp\u003e1,2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.284883720930232%\"\u003e\n \u003cp\u003e23,7\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e\u003cstrong\u003e28,6\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.16860465116279%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.319767441860465%\"\u003e\n \u003cp\u003e\u003cstrong\u003e9,6\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.046511627906977%\"\u003e\n \u003cp\u003e\u003cstrong\u003e11,6\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e\u003cstrong\u003e4,6\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2,3\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.046511627906977%\"\u003e\n \u003cp\u003e\u003cstrong\u003e34,3\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.354651162790697%\"\u003e\n \u003cp\u003e\u003cstrong\u003e11,9\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.284883720930232%\"\u003e\n \u003cp\u003e\u003cstrong\u003e25,7\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.593023255813954%\"\u003e\n \u003cp\u003e\u003cstrong\u003e100,0\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTableau 3: Sedimentation rate in Tahaddart estuary and the related values reported in other coastal areas.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.53073463268366%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoastal sediment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.18290854572714%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSedimentation rate (cm/year)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.286356821589205%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.53073463268366%\"\u003e\n \u003cp\u003eTahaddart estuary (Morocco)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.73463268365817%\"\u003e\n \u003cp\u003e0,53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.73463268365817%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ePresent study\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.53073463268366%\"\u003e\n \u003cp\u003eTahaddart estuary (Morocco)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.73463268365817%\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.73463268365817%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eKhalfaoui et al. 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.53073463268366%\"\u003e\n \u003cp\u003eLoukous estuary (Morocco)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.73463268365817%\"\u003e\n \u003cp\u003e0.27-0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.73463268365817%\" colspan=\"2\"\u003e\n \u003cp\u003eKalloul et al, 2012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.53073463268366%\"\u003e\n \u003cp\u003eOum Er bia estuary (Morocco)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.73463268365817%\"\u003e\n \u003cp\u003e0,38 \u0026agrave; 0,68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.73463268365817%\" colspan=\"2\"\u003e\n \u003cp\u003eMaanan M. et al 2009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.53073463268366%\"\u003e\n \u003cp\u003eMoulay Bousselham logoon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.73463268365817%\"\u003e\n \u003cp\u003e0,6 \u0026ndash; 0,70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.73463268365817%\" colspan=\"2\"\u003e\n \u003cp\u003eMhammdi et al, 2010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.53073463268366%\"\u003e\n \u003cp\u003eVenise logoon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.73463268365817%\"\u003e\n \u003cp\u003e0.25 cm y-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.73463268365817%\" colspan=\"2\"\u003e\n \u003cp\u003eBellucci et al. 2007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTableau 4: The ranges and averages of contamination factor (CF), Pollution Load Index (PLI) in sediment cores from Tahaddart estuary.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.371601208459214%\" colspan=\"2\" rowspan=\"2\" valign=\"top\" style=\"width: 7.3657%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"67.97583081570997%\" colspan=\"7\" valign=\"top\" style=\"width: 45.4073%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eContamination factor (CF)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.969788519637461%\" rowspan=\"2\" valign=\"top\" style=\"width: 6.0659%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePLI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\" style=\"width: 8.4055%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCu\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eZn\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCr\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePb\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\" style=\"width: 6.0659%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCd\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\" style=\"width: 6.0659%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.199066874027994%\" rowspan=\"2\" valign=\"top\" style=\"width: 3.1196%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\" style=\"width: 4.3328%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMOY\u003c/strong\u003e \u003cstrong\u003e\u0026nbsp;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.953343701399689%\" style=\"width: 8.4055%;\"\u003e\n \u003cp\u003e1.14 \u0026nbsp;0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.953343701399689%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e1.66\u0026nbsp;0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.953343701399689%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e1.11\u0026nbsp;0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.953343701399689%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e1.67\u0026nbsp;0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.953343701399689%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e1.26\u0026nbsp;0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.953343701399689%\" style=\"width: 6.0659%;\"\u003e\n \u003cp\u003e6.84\u0026nbsp;4.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.953343701399689%\" style=\"width: 6.0659%;\"\u003e\n \u003cp\u003e1.27\u0026nbsp;0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.26438569206843%\" style=\"width: 6.0659%;\"\u003e\n \u003cp\u003e1.62\u0026nbsp;0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.475873544093178%\" style=\"width: 4.3328%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMIN- MAX\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\" style=\"width: 8.4055%;\"\u003e\n \u003cp\u003e0.57-1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e0.67-2.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e0.53-2.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e0.65-3.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e0.75-2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\" style=\"width: 6.0659%;\"\u003e\n \u003cp\u003e0.23-19.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\" style=\"width: 6.0659%;\"\u003e\n \u003cp\u003e0.66-2.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.98169717138103%\" style=\"width: 6.0659%;\"\u003e\n \u003cp\u003e0.64-2.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.2993630573248405%\" valign=\"top\" style=\"width: 3.1196%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.853503184713375%\" style=\"width: 4.3328%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.19108280254777%\" style=\"width: 8.4055%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.19108280254777%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.19108280254777%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.19108280254777%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.19108280254777%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.19108280254777%\" style=\"width: 6.0659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.19108280254777%\" style=\"width: 6.0659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.509554140127388%\" style=\"width: 6.0659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.2993630573248405%\" rowspan=\"2\" valign=\"top\" style=\"width: 3.1196%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.853503184713375%\" style=\"width: 4.3328%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMOY\u003c/strong\u003e\u0026nbsp; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.19108280254777%\" style=\"width: 8.4055%;\"\u003e\n \u003cp\u003e1.29\u0026nbsp;0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.19108280254777%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e1.48\u0026nbsp;0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.19108280254777%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e1.46\u0026nbsp;0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.19108280254777%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e1.21\u0026nbsp;0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.19108280254777%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e1.23\u0026nbsp;0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.19108280254777%\" style=\"width: 6.0659%;\"\u003e\n \u003cp\u003e6.99\u0026nbsp;4.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.19108280254777%\" style=\"width: 6.0659%;\"\u003e\n \u003cp\u003e1.64\u0026nbsp;0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.509554140127388%\" style=\"width: 6.0659%;\"\u003e\n \u003cp\u003e1.67\u0026nbsp;0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.475873544093178%\" style=\"width: 4.3328%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMIN- MAX\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\" style=\"width: 8.4055%;\"\u003e\n \u003cp\u003e0.79-2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e0.39-2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e0.97-2.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e0.61-2.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\" style=\"width: 6.2392%;\"\u003e\n \u003cp\u003e0.77-2.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\" style=\"width: 6.0659%;\"\u003e\n \u003cp\u003e0.21-16.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\" style=\"width: 6.0659%;\"\u003e\n \u003cp\u003e0.95-2.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.98169717138103%\" style=\"width: 6.0659%;\"\u003e\n \u003cp\u003e0.63-2.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003col style=\"list-style-type:lower-alpha;\" start=\"1\"\u003e\n \u003cli\u003eCf \u0026lt;1 indicates low contamination; 1\u0026lt;Cf \u0026lt;3 is moderate contamination; 3\u0026lt;Cf \u0026lt;6 is considerable contamination; and Cf \u0026gt;6 is very high contamination.\u003c/li\u003e\n \u003cli\u003ePLI \u0026gt;1 means that pollution exists; otherwise, if it is \u0026lt;1, there is no metal pollution\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTableau 5: The ranges and averages of\u0026nbsp;individual ecological risk Index (Er i ), total ecological risk (RI) and Mean ERM quotients (m-ERM-Q)\u0026nbsp;in sediment cores from Tahaddart estuary.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.251989389920425%\" colspan=\"2\" rowspan=\"2\" valign=\"top\" style=\"width: 7.2508%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.681697612732094%\" colspan=\"6\" valign=\"top\" style=\"width: 43.505%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEcological risk Index (Er i )\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.59946949602122%\" rowspan=\"2\" style=\"width: 9.9944%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.355437665782494%\" rowspan=\"2\" style=\"width: 6.271%;\"\u003e\n \u003cp\u003e\u003cstrong\u003em-ERM-Q\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.25389755011136%\" valign=\"top\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.25389755011136%\" valign=\"top\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCu\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.25389755011136%\" valign=\"top\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eZn\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.25389755011136%\" valign=\"top\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCr\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.25389755011136%\" valign=\"top\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePb\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.262806236080177%\" valign=\"top\" style=\"width: 9.9944%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCd\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"3.6684782608695654%\" rowspan=\"2\" valign=\"top\" style=\"width: 3.1355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.820652173913043%\" style=\"width: 4.1153%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMOY\u003c/strong\u003e \u003cstrong\u003e\u0026nbsp;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e5.62\u0026plusmn;1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e8.02\u0026plusmn;2.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e1.09\u0026plusmn;0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e3.23\u0026plusmn;1.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e6.35\u0026plusmn;1.41\u003c/p\u003e\n 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\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.876560332871012%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.876560332871012%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.876560332871012%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.876560332871012%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.876560332871012%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.373092926490985%\" style=\"width: 9.9944%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.176144244105409%\" style=\"width: 9.9944%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.737864077669903%\" valign=\"top\" style=\"width: 6.271%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"3.7447988904299585%\" rowspan=\"2\" valign=\"top\" style=\"width: 3.1355%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.066574202496533%\" style=\"width: 4.1153%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMOY\u003c/strong\u003e\u0026nbsp; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.876560332871012%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e6.46\u0026plusmn;1.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.876560332871012%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e7.39\u0026plusmn;2.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.876560332871012%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e1.46\u0026plusmn;0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.876560332871012%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e2.43\u0026plusmn;0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.876560332871012%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e6.15\u0026plusmn;1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.373092926490985%\" style=\"width: 9.9944%;\"\u003e\n \u003cp\u003e209.79\u0026plusmn;145.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.176144244105409%\" style=\"width: 9.9944%;\"\u003e\n \u003cp\u003e233.67\u0026plusmn;150.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.737864077669903%\" valign=\"top\" style=\"width: 6.271%;\"\u003e\n \u003cp\u003e0.13\u0026nbsp;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.536023054755043%\" style=\"width: 4.1153%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMIN- MAX\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.221902017291066%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e3.94-10.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.221902017291066%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e1.93-12.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.221902017291066%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e0.97-2.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.221902017291066%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e1.22-5.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.221902017291066%\" style=\"width: 6.6629%;\"\u003e\n \u003cp\u003e3.87-10.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.815561959654179%\" style=\"width: 9.9944%;\"\u003e\n \u003cp\u003e6.23-482.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.688760806916427%\" style=\"width: 9.9944%;\"\u003e\n \u003cp\u003e19.27-520.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.077809798270893%\" valign=\"top\" style=\"width: 6.271%;\"\u003e\n \u003cp\u003e0.07-0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003col style=\"list-style-type:lower-alpha;\" start=\"3\"\u003e\n \u003cli\u003eE\u003csup\u003ei\u003c/sup\u003e\u003csub\u003er\u003c/sub\u003e\u0026lt; 40\u0026nbsp;indicates a low potential ecological risk; 40 \u0026lt;E\u003csup\u003ei\u003c/sup\u003e\u003csub\u003ef\u003c/sub\u003e\u0026lt; 80 is a moderate ecological risk;\u0026nbsp;80 \u0026lt;E\u003csup\u003ei\u003c/sup\u003e\u003csub\u003er\u003c/sub\u003e\u0026lt; 160 is a considerable ecological risk; 160 \u0026lt;E\u003csup\u003ei\u003c/sup\u003e\u003csub\u003er\u003c/sub\u003e\u0026lt; 320 is a high ecological risk and\u0026nbsp;E\u003csup\u003ei\u003c/sup\u003e\u003csub\u003er\u003c/sub\u003e\u0026gt; 320 is a very high ecological risk.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eR\u003csub\u003eI\u0026nbsp;\u003c/sub\u003e\u0026lt; 95\u0026nbsp;indicates a low potential ecological risk; 95 \u0026lt;R\u003csub\u003eI\u0026nbsp;\u003c/sub\u003e\u0026lt; 190 is a moderate ecological risk;\u0026nbsp;190 \u0026lt;R\u003csub\u003eI\u0026nbsp;\u003c/sub\u003e\u0026lt; 380 is a considerable ecological risk and R\u003csub\u003eI\u003c/sub\u003e\u0026gt; 380 is a very high ecological risk.\u003c/li\u003e\n \u003cli\u003eM-ERM-Q was defined: 9% probability of toxicity (M-ERM-Q \u0026lt;0.1), 21% probability of toxicity (0.11 \u0026le; M-ERM-Q \u0026lt;0.5), 49% probability of toxicity (0.51 \u0026le; M-ERM-Q \u0026lt;1.5) and 76% probability of toxicity (M-ERM-Q \u0026gt;1.5).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Coastal land cover change, Spatial mapping, Eco-toxicological risk, Sediment quality guideline, 210Pb/137Cs dating","lastPublishedDoi":"10.21203/rs.3.rs-4460113/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4460113/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLong-term trends of trace element contamination in coastal ecosystems are important for assessing the impact of land cover changes on the environment quality. In this study, the assessment of historical land cover changes and contamination status trends of Tahaddart estuary (N-W, Morocco) was investigated. Two sediment cores were selected, analyzed for trace elements (TEs), compared with sediment quality guidelines, and assessed by using environmental and ecological indices. Radiometric dating was performed on sediment core by using \u003csup\u003e210\u003c/sup\u003ePb and \u003csup\u003e137\u003c/sup\u003eCs isotope. Identification and description of the land cover patterns from 1984 to 2016 was analyzed using GIS methods. The geomatic results showed significant decline in agricultural land, forests, wetlands, and beaches/dunes between1984 and 2016, which are increasingly replaced by artificial land. The radio-dating of sediment core indicate that the mean sedimentation rates are 0.53 cm/years based on \u003csup\u003e210\u003c/sup\u003ePb activities. The ecotoxicological risk and contamination indexes revealed a gradual deterioration in the environment quality of Tahaddart with moderate contamination level and 21% risk of toxicity. This research provides a reference database for costal area development.\u003c/p\u003e","manuscriptTitle":"Effect of land-cover changes on heavy metals concentration and ecological risk in sediments of Tahaddart estuary, Morocco","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-16 13:15:53","doi":"10.21203/rs.3.rs-4460113/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"053726bb-db19-4d9b-a600-f8d6ae1f7751","owner":[],"postedDate":"August 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-09T14:41:38+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-16 13:15:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4460113","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4460113","identity":"rs-4460113","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}