Spatial Distribution and Mapping of Heavy Metals in Agricultural Soils of the Sfafaa Region (Gharb, Morocco)

Available online at www.sciencedirect.com ScienceDirect www.materialstoday.com/proceedings Materials Today: Proceedings 13 (2019) 832–840 ICMES2018 Spatial Distribution and Mapping of Heavy Metals in Agricultural Soils of the Sfafaa region (Gharb, Morocco) N. El Khodrania,d*, S. Omraniab, A. Zouahric, A. Douaikc , H. Iaaichc, A. Yahyaouia, M. Fekhaouid aLaboratory of Zoology and General Biology, Faculty of Sciences, Mohammed V University, Rabat, Morocco. bLaboratory CERNE2D, Faculty of Sciences, Mohammed V University, Rabat, Morocco. cResearch Unit on Environment and Conservation of Natural Resources, Regional Center of Rabat, National Institute of Agricultural Research (INRA),Rabat, Morocco. dScientific Institute, Mohammed V University, Rabat,Morocco. Abstract Our study has the purpose of mapping the vulnerability of the soils of the Sfafaa region by the contamination of heavy metals through their monitoring. A campaign of soil sampling and analyzes in the laboratory has been realised. The approach followed is the spatial analysis using Geographic Information System (GIS). The data have been spatialized through the GIS in order to establish the relationship between the levels of contamination observed for each species and their spatial distribution. The total concentrations of heavy metals were assessed for samples from seventeen sites representative of the agricultural lands, selected along the Beht River, over a period from March to June of 2013 and 2014. Concentrations of eight elements were determined: Mn, Cd, Cr, Cu, Ni, Pb, Zn and Fe. The results show that Ni, Cr, and Cd present high concentrations in plots irrigated by groundwater. Cr concentration is the most important (319.7 ppm), exceeding the standard for a normal soil (100 ppm) while the average content of Zn is 89.8 ppm, below the standards for a normal soil (200 ppm). In general, the results showed a metal contamination that exceeds the standards for Ni (62.7 mg/kg in average and values ranging from 21.6 to 102.4 mg/kg), Cd (1.9 mg/kg in average and values ranging from 1.3 to 3.2 mg/kg), and Cr (274.8 mg/kg in average and values ranging from 200.7 to 327.4 mg/kg), due to the overuse of fertilizers. These results confirm the impact of the agriculture intensification on the quality of the soils in the Gharb region. © 2019 Elsevier Ltd. All rights reserved. Peer-review under responsibility of the scientific committee of the International Conference on Materials and Environmental Science, ICMES 2018. Keywords: Agricultural pollution, Heavy metals, PCA, Soil quality, Sfafaa, Sidi Slimane. * Corresponding author. Tel.: +212663008685. E-mail address: [email protected] 2214-7853 © 2019 Elsevier Ltd. All rights reserved. Peer-review under responsibility of the scientific committee of the International Conference on Materials and Environmental Science, ICMES 2018. El Khodrani et al / Materials Today: Proceedings 13 (2019) 832–840 833 1. Introduction In the arid and semi-arid regions of Morocco, where precipitations are scarce and irregular, there is a yearly growing water deficit. Consequently, irrigation becomes necessary to ensure agricultural production up to meet the food needs of the growing population. The agricultural development in these regions thus depends on irrigation using groundwater [1].These ground waters are rich in organic matter and nutrients [2]. However, they contain high rates of unneeded chemical elements, particularly heavy metals [3-5], which are source of risk for farmers, soils, plants, consumers, and the and the environment. The heavy metals are naturally present in the soil. Some heavy metals are essential and beneficial to living organisms such as manganese (Mn), zinc (Zn), boron (B), and copper (Cu) for which concentrations in the soil and cattle feed must be maintained at a certain level to allow normal growth, development, and reproduction. However, if levels are too high, toxicity mechanisms can be developed [6].Some heavy metals such as copper (Cu) and zinc (Zn) become toxic for plants at lesser concentrations than for humans [7-10]. Plants are also an obstacle that mitigates the potential risks for health [11, 12]. During the last decades, the problems associated with the increase in the levels of heavy metals and their constant presence in the environment interested researchers [13, 14]. Due to their persistence, toxicity and non-biodegradable nature, heavy metals are regarded as a serious concern in relation to human health [15, 16]. Considering the rising level of heavy metals in soils spatial studies are conducted to assess heavy metal contents in soils throughout the world. Spatial distribution of heavy metals in agricultural soils is correlated with their natural sources and anthropogenic inputs [17]. A combination of multivariate statistics (such as Principal component analysis) and spatial analysis using mapping techniques is an important tool for identifying pollution characteristics of heavy metals in soils and distinguishing their natural sources and anthropogenic inputs [18]. The objective of this study is to map the vulnerability of the soils of the Sfafaa region to contamination of heavy metals through their monitoring. 2. Material and Methods 2.1. Study area The study area is a part of the Sidi Slimane Province ( Rabat-Sale-Kenitra region).The geographic coordinates are 34°15′0'' N for latitude and 6° 9′36'' W for longitude. It is limited to the North by the Province of Sidi Kacem (Rabat-Sale-Kenitra region), in the South-East by the rural commune of Boumaiz (Province of Sidi Slimane), and to the West by the rural commune of Kecybia (Province of Sidi Slimane). The rural commune of Sfafaa extends over approximately 197km2. With fertile soils, a temperate and humid climate and abundant water resources, the Sfafaa region is an important agricultural zone. It is a natural collector of surface waters. Its flat morphology (a plain of altitude lower than 12 m) does not favor the evacuation of the river flood waters to the sea. There are two irrigated sub-zones: Those irrigated by the Beht River water and those by the Sebou River water [19]. The meteorological station of Sidi Slimane [19] records minimum precipitation compared to the other stations in the Rabat-Sale-Kenitra region, because of the altitude and continentality effects. The most rainy months are November, December, and January and the driest are June, July, and August. July and August are the hottest months while the coolest are December, January, and February. The dry period lasts from May to September. 2.2. Methodology Soil sampling was done during the period of March to June during two years (2013 and 2014). The sampling is based on a grid developed using a topographic map of the study area. The samples were taken from 6 different zones: A, B, C, D, E, and F (Fig. 1). The GPS coordinates of each sample taken have been recorded for the development of the maps. The system of cartographic projection used is the conical Lambert consistent Zone 1 of Morocco. Soil samples are of 300 to 500g, collected from the 0 to 20cm horizon. They were dried in the open air for a week then grinded and sieved to 2mm and 0.2mm before undertaking chemical analysis at the National Institute of Agronomic Research laboratories in Rabat. The analysis of heavy metals (Cd, Cu, Cr, Mn, Pb, Ni, Fe and Zn) contents were done using an Atomic Absorption Spectrophotometer (AAS) [20].The dried sample is extracted with a hydrochloric/nitric acid mixture by standing for 16h at room temperature, followed by boiling under reflux for 2h.The extract is then clarified and made up to volume with nitric acid. The trace metal content of the extract can be determined in accordance with [21]. 834 El Khodrani et al / Materials Today: Proceedings 13 (2019) 832–840 Fig. 1. Study area and prospected soils and wells. 2.3. Statistical analysis First of all, a matrix of Pearson correlation coefficients between any two variables was computed and the coefficients were tested for their statistical significance. We then used Principal Component Analysis [22], a multivariate analysis technique that provides an excellent means for gaining useful information from data sets with many variables [23]. In particular, PCA can aid in the compression and classifcation of data. The purpose is to reduce the dimensionality of a data set by finding a new set of variables, smaller than the original set of variables, which nonetheless retains most of the sample’s variance. Success relies on the presence of correlations among at least some of the original variables; otherwise the number of new variables will be almost the same as the number of original variables. The new variables, called principal components, are uncorrelated, and are ordered by the fraction of the total variance each retains. The PCA was performed in this study using SPSS 20. Based on the results of analyzes and on the basis of the GPS coordinates, the maps of spatial variability of different elements were developed using the Inverse Distance Weighting (IDW) spatial interpolation approach . For this, we used the ArcGIS © version 10 software geographic information system (GIS) and its extension Geostatistical Analyst. The IDW method allows giving a value to a space not known from points to known values, and this on the basis of reverse weight to the distances [24]. 3. Results and discussion 3.1. Heavy metals analysis The results of the measurement of the different heavy metals in the soils are presented in Table 1. The concentration and average for the heavy metals determined in the soil are given in Table 1. The percentage of exceeding has been calculated for all of the heavy metals as the ratio between the number of samples which exceed the limits to the total number of samples. a. Cadmium The levels of soil cadmium content show that the F zone, which contains the sites S15, S16,and S17, had Cd concentrations ranging between 2 and 3.19 mg/kg, with an average of 2.47mg/kg (Table 1) .It is followed by the E zone (sites S12,S13 ,and S14) with concentrations ranging between 2.06 and 2.42 mg/kg, and an average of 2.28mg/kg.

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