1.1 Background

The pollution of water and sediments with heavy metals increases due to the increase in pollution activities such as industrial, agricultural and surface runoff (^{Bhagat et al., 2020}). The accumulation of heavy metals is one of the most important factors and reasons to study water quality (^{Elzwayie et al., 2017}). Sediment is the highest pool of heavy metals (HMs) in water (^{Xu et al., 2018}). HMs, due to toxicity, persistence and bioaccumulation problems in the natural environment, are major pollutants (^{Seshan et al., 2010}). The level of HMs is calculated under three situations in the marine ecosystem: water, sediment, and organisms (^{Andreas et al., 2019}). Water, the food chain, and sediment can collect large amounts of (HMS), which can have fatal consequences on aquatic species (^{Benson et al., 2017}; ^{Iqbal & Shah, 2014}; ^{Mehrgan et al., 2019}). Trace elements in marine ecosystems can be affected by the column of water, sediments, and biota by chemical and biological processes (^{Mohiuddin et al., 2010}; ^{Nowrouzi & Pourkhabbaz, 2014}). Sediments consist of clay, sand, and some organic materials at different rates; the concentrations of HMs in sediment are greater than in the water (^{Habeeb et al., 2015}). Toxic elements accumulate in rivers, sediments, plants, and animals, due to agricultural, human, industrial activity, and sewage. All contribute to pollution (^{Ilie et al., 2014}; ^{Mohd et al., 2014}; ^{Shanbehzadeh et al., 2014}; ^{Yi et al., 2020}). Urban, agriculture, industries, and commercial operations add to the input into the aquatic ecosystem of substantial quantities of substances of pollutant (in particular heavy elements) and damage the often deposited environmental systems (^{Jiang & Sun, 2014}; ^{Zourarah et al., 2009}). Anthropogenic activities and natural processes, particularly rock weather and volcanic activity, play an important influence in the build-up of HMs in sediments (^{Devanesan et al., 2020}; ^{Maanan et al., 2015}; ^{Saeed & Shaker, 2008}). discharge of wastewater contain hm without any treatment and its apply for agricultural purpose are possible ways of heavy metals accumulation in plants food chain (^{Basra et al., 2014}).

Sediments due to its toxicity, persistence, and bioaccumulation of heavy metals is considered a critical issue for the aquatic ecosystem (^{Harikumar et al., 2010}; ^{Salah et al., 2012}). Sediments as environmental markers have been widely used and they also reported their ability to track sources of pollution (^{Alaoui et al. 2010}).

Several studies have shown that aquatic systems in various areas of the world are polluted with HMs (^{Habeeb et al., 2015}). (^{Ghalib & Ramal, 2021}) study some of (HMs) (Zn, Cr, Cd, Ni, Cu, Co, Fe, Pb and Fe) in water of Habbaniyah lake (HL), Results showed that (HL) was polluted with HMs, Based on international and national guides, (contamination degree), (heavy metal pollution index) and (heavy metal evaluation index) indices were calculated and compared with limitations, which show that water quality of (HL) was bad.

Total sediment concentrations of HMs are useful for detecting any net changes, but there is no indication of the chemical form of sediment metals (^{Yunus et al., 2020}). Depending on sediment type and characteristics of adsorbed molecules, various physical and chemical absorption mechanisms of HMs accumulate in sediments (^{Rabee et al., 2011}). The scientific community has become increasingly aware of lake sediment pollution, as it is an important cause of ecosystem-based health stress and various research showed that in sediments, HMs may have a direct effect on aquatic ecosystem quality (^{Devanesan et al., 2017}). The correct evaluation and biological and ecological importance of sediment pollution in lake are therefore critical. Can rotate the sediment in the water because of the biological perturbation and change the pH and temperature, although the sediment is a sink of HMs analysis pollution of HMs in sediments helps to find these sources of pollutants in the water ecosystem (^{Maina et al. 2019}; ^{Balasim et al., 2013}). Toxic pollutant discharges including wastewater treatment, fossil fuel burning, and air deposition, can penetrate marine environments from anthropogenic sources (^{Singovszka et al., 2017}).

The environmental quality indexes and indices are a valuable instrument in which decision-makers, administrators, technicians or the public can process, analyze and provide raw environmental knowledge (^{Habeeb et al., 2015}). HMs, that are both essential and inessential ions, are highly crucial in ecotoxicology so they are highly persistent and can seriously impact living organisms. (^{Öztürk et al., 2009}). Although trace metals, like chromium (Cr), zinc (Zn), copper (Cu), arsenic (As), manganese (Mn) and vanadium (V) are important components of biological activities at low concentrations, but at high concentrations will becomes a global issue due to potential harm impacts on human health and aquatic ecosystems (^{Andreas et al., 2019}). HMs such as copper, zinc and nickel play an integral role in biological processes and are important metals, while others, such as cadmium and lead, are not essential elements (^{Benzer et al., 2013}). Pb and Cd are rare elements, do not have basic biological roles, and are extremely poisonous to plants and animals (^{Nowrouzi & Pourkhabbaz, 2014}). In addition, sediment research can help to clarify pollutant origins in marine environments (^{Salah et al., 2012}).

1.2 Research objectives

Habbaniyah Lake (HL) has environmental, recreational, drinking and agricultural importance due to the fact that many activities were surrounded (HL). This research aims at (i) Examine the spatial and temporal of HMs in sediments (ii) assessing the metal toxicity in sediments using environmental pollution indexes (iii) Combining operations and technology of geographical information systems (GIS) to form a framework that provides the ability to capture and analyze spatial and non-spatial geographic data from different sources and merge in one form for analysis to evaluate contamination in sediments of HL.

2.1. Study area

Figure 1. Shows the study area of Habbaniyah lake HL, HL is a crucial strategic location in Iraq where it is far from Baghdad 68km, far away from Fallujah 20km, and far away from the south of Ramadi 25km. A neighborhood of the HL is 426 square kilometer, 35km length, 25km width, and therefore the depth of the HL between 9-13m with a complete capacity of this size is attributed to 3.3billion m3 (^{Salah et al., 2014}). HL is found between the latitudes (33°18'21" N and longitudes 43°26'14" E) at elevation (51m) above water level (^{AL-Fahdawi et al., 2015}). HL is fed by the Euphrates through Warrar Canal and has two outlets: the Mijarrah Canal and Dhiban Canal (^{Salah et al., 2014}).

Figure 1 Study area. 

2.2. Sampling

Thirty-three stations were selected within HL monthly during (October 2020 - April 2021), sediments samples taken from HL bed to measure HMs. Stations were located using (Garmin, GPS map pro 60 CSx).

Stations were selected regularly by interpolation method to cover the lake fully. Sediment samples were collected in clean polyethylene bags (1kg) by employing an Ekman bottom grab sampler at a depth of 10-13m. A sensitive balance was used to weigh one gram of sediment samples after they had been dried at 120°C for 3 hours. (37 percent of HCl acid) and (65% of HNO3 acid) were added to sediment samples in a flask of (100 ml), using Whatman paper (No. 42) to eliminate undesirable particulates (e.g., wood pieces, plants, and other particles), and storing the samples at (4 °C) further investigation. The samples were heated around 20 minutes to get (1ml) samples size, the one ml samples were mixed with (24 ml) of double water in (25 ml) flask size. Finally, the samples were ready for analysis.

2.3. Instruments

United States (US) Phoenix 986 atomic absorption spectrophotometers (AAS) (GBC- company) have been employed in the analysis of (HMS), sensitive balance (Mettler-Toledo- company), nitric and hydro-chloric acids (BDH - company) were used. Standard solutions of Ni, Cd, Cr, Fe, Co, Zn, Pb, and Cu solutions with the purity of (99.99%) (BDH -company), (ARC GIS.V 10.33) was applied to show maps.

2.4. Evaluation of heavy metal pollution

The lake sediments metals contamination is evaluated with (I-geo), (CF), (CD) and (PLI).

Geo-accumulation index (I-geo)

The next Müller equation computed the index of geo-accumulation (^{Rabee et al., 2011}).

Factor 1.5 is applied to potentially modify the background values because of lithological variances in seven classes; I-geo was classified as shown in Table 1. by Kassim et al. (1991).

2.5. Contamination factor (CF)

The Contamination level by heavy metals of sediment is calculated by contamination factor (CF) (^{Salah et al., 2012}):

Table 2. shows CF values to describe the degree of pollution (^{Salah et al., 2012}). Table 3. presents CD values to describe the degree of pollution.

2.6. The Pollution load index (PLI)

The PLI of the location is determined from the n-root of CFs for all the toxic metals collected. The PLI from any location is obtained (^{Öztürk et al., 2009}). General equation proposed by ^{Salem et al. (2014)} pollution load index follows: (PLI) as

Were,

CF = factor of pollution, n = elements number The PLI of > 1 is contaminated, while <1 does not indicate any contamination.

3.1. Concentration of heavy metal

Table 4. Shows the results of the (HMs) concentrations of sediments collected from the HL. (HMs) quantities found in the research area of (HL) are shown in Table 4. The mean concentrations of (HMs) were followed the order: Fe> Pb> Cr> Ni> Co> Zn> Cu> Cd. Figures (2, 3, 4, 5, 6, 7, 8 and 9) show the mean spatial concentration of (Pb), (Fe), (Cr), (Co), (Ni), (Zn), (Cu) and (Cd) respectively. Table 5. shows the results of heavy metals analytical value (mg/kg) compared with the guide.

Figure 2 Average spatial concentration of (Pb). 

Figure 3 Average spatial concentration of (Fe). 

Figure 4 Average spatial concentration of (Cr). 

Figure 5 Average spatial concentration of (Co). 

Figure 6 Average spatial concentration of (Ni). 

Figure 7 Average spatial concentration of (Zn). 

Figure 8 Average spatial concentration of (Cu). 

Figure 9 Average spatial concentration of (Cd). 

3.2. Pollution loaf index (PLI)

Table 4. Presents the values of (PLI) and (I-geo) of (HMs) in sediments. (Fig 10) Shows the PLI values by heavy metals in all sities of HL sediments.

Figure 10 (PLI) of the sediments. 

3.2. Pollution load index (PLI)

Table 4. Presents the values of (PLI) and (I-geo) of (HMs) in sediments. (Fig 10) Shows the PLI values by heavy metals in all sites of HL sediments.

3.3. Geo-accumulation index (I-geo)

The sediments contamination level was estimated by use the geo-accumulation index (I-geo). I-geo values presented (Fig 11) and in (Table 4).

Figure 11 (I-geo) of the sediments. 

3.4. Contamination factor (CF) and contamination degree (CD)

The predicted contamination factors (CF_s) and CD for different heavy metals in HL sediments displayed in (Fig. 12 and 13) and listed Table 6.

Figure 12 Contamination factor (CF). 

Figure 13 Contamination degree (CD). 

4.1. Heavy metals concentration

Table 4. shows the results of (HMs) concentration in bed sediments of the HL. The mean concentrations of the (HMs) measured in the sediment were followed the order: Fe> Pb> Cr> Ni> Co> Zn> Cu> Cd. Figures (2, 3, 4, 5, 6, 7, 8 and 9) show the average Spatial concentration of (Pb), (Fe), (Cr), (Co), (Ni), (Zn), (Cu) and (Cd) respectively.

Table 5. shows the results of heavy metals analytical value (mg/kg) Compared with the guidelines.

Results showed that Pb ranged from 35.988 mg/kg to 59.116 mg/kg with a mean of 47.354 mg/kg above (USEPA) and (CCME) recommendation on sediments quality for marine life (Table 4). The high level of Pb was recorded at S5 (59.116 mg/kg), S1 (54.816 mg/kg), and S19 (55.659 mg/kg) might be due to agriculture waste and mud, high levels of fuel combustion lead in vehicles, also caused by the spillover of leaded petrol from fishing vessels and this may be related to increasing human activity. Higher amounts of Pb are typically seen in water bodies near highways and major towns due to significant gasoline consumption (^{Saeed & Shaker, 2008}). Cd was varied from (0.241 mg/kg) at S3 to (4.627 mg/kg) at W1 with a mean of (3,539 mg/kg) above (USEPA) and (CCME) recommendation and with the limit of WHO (Table 4). Human activities like urban development, industrialization, and agricultural rushing can be ascribed to these elevated levels. Zn levels varied from 4.555 mg/kg to 13.258 mg/kg with mean (9.577 mg/kg) under the WHO, USEPA, and CCME standards. Cu levels ranged from (2.838 mg/kg) at S3 to (5.582 mg/kg) at S5 with mean (4.531 mg/kg) did not exceed the criteria of WHO, CCME, and USEPA. Cu concentrations were found to be high at locations in and around population centers. The result in Ni was 13.725 mg/kg to 20.044 mg/kg with the mean levels 18.002 mg/kg above the USEPA limit, attributable to agricultural and human activity. Co levels vary from (7.470 mg/kg) in W2 to (14.443 mg/kg) at S2 with an average of 10.608 mg/kg. The level of Cr was varied from (10.087 mg/kg) at S3 to (35.035 mg/kg) at S7 with mean value of 25.188 mg/kg with the limits of USEPA, WHO, and CCME guidelines of (USEPA), drinking and aquatic life limitations respectively (Table 4).

The highest value of Co can be due to the quantities of sewage, farm, and municipal wastewater pumped into the HL. The level of Fe varied from (1180.993 mg/kg) at S3 to (2713.491 mg/kg) at S19 with mean value (2152.971 mg/kg) above the limit of guidelines.

The average concentration of (Pb and Cd) was greater than the geochemical background level (Table 4). Based on USEPA guidelines, sediments from HL have been contaminated with (Cd, Ni, Pb and Fe) (Table 5).

Concentrations of (HMs) were varied spatially, The major significant spatial factors affecting the HMs distribution include, population, lake bank densities, beds hydrological conditions, landfilling by factories, and wastewater discharge. (^{Balasim et al., 2013}).

4.2. Pollution indices