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Liu, An, Duodu, Godfred, Goonetilleke, Ashantha, & Ayoko, Godwin(2017)Influence of land use configurations on river sediment pollution.Environmental Pollution, 229, pp. 639-646.

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https://doi.org/10.1016/j.envpol.2017.06.076

1

Influence of land use configurations on river sediment pollution

An Liu1,2,3, Godfred O. Duodu3, Ashantha Goonetilleke3*, Godwin A. Ayoko3 1 College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen 518060, People’s Republic of China 2 Shenzhen Key Laboratory of Environmental Chemistry and Ecological Remediation, Shenzhen 518060, People’s Republic of China 3 Science and Engineering Faculty, Queensland University of Technology (QUT), P.O. Box 2434, Brisbane, Qld 4001, Australia

Graphical Abstract

Highlights

• Land use configuration plays an important role in river sediment pollution • High density and more diverse land use development results in high pollutant loads • Knowledge created for robust land use planning to minimise waterway pollution

*Corresponding author:

E-mail: [email protected]; Tel: +61 7 3138 1539; Fax: +61 7 3138 1170

mailto:[email protected]

2

Abstract: Land use is an influential factor in river sediment pollution. However, land use type alone is found to be inadequate to explain pollutant contributions to the aquatic environment since configurations within the same land use type such as land cover and development layout could also exert an important influence. Consequently, this paper discusses a research study, which consisted of an in-depth investigation into the relationship between land use type and river sediment pollution by introducing robust parameters that represent configurations within the primary land use types. Urban water pollutants, namely, nutrients, total carbon, polycyclic aromatic hydrocarbons and metals were investigated in the study. The outcomes show that higher patch density and more diverse land use development forms contribute relatively greater pollutant loads to receiving waters and consequently leading to higher sediment pollution. The study outcomes are expected to contribute essential knowledge for creating robust management strategies to minimise waterway pollution and thereby protect the health of aquatic ecosystems.

Capsule: Presents a robust approach for understanding the role of land use configurations in river sediment pollution and thereby contribute to protecting the health of aquatic ecosystems.

Keywords: River sediment pollution; Land use type; Polycyclic aromatic hydrocarbons; Metals; Nutrients

1 Introduction

Understanding river sediment pollution is important because it acts a reliable indicator of the ecological health of the water body (Duodu et al., 2016b; Liao et al., 2017). The sediment bed provides habitat for flora and fauna and is also a sink for pollutants. These pollutants can interchange between water and sediments (Sarria-Villa et al., 2016). Therefore, pollutants associated with sediments could have adverse impacts on the aquatic ecosystem when released back to the water body due to flooding or anthropogenic activities such as dredging (Kapsimalis et al., 2014). This can be particularly serious when toxic pollutants such as heavy metals and polycyclic aromatic hydrocarbons (PAHs) enter the water column, and pose high risks to the water environment. Consequently, an in-depth understanding of sediment pollution can help in the development of management strategies for safeguarding the water environment and improving its ecological health.

Current research into river sediment pollution focuses on the investigation of temporal and spatial distribution of pollutant loads and associated health risk assessment. These are generally undertaken by collecting sediment samples along a river during different seasons and sampling locations, which are characterised by different land use types (for example Dudhagara et al., 2016; Giuliani et al., 2016; Goswami et al., 2016). The health risk assessment is then undertaken by incorporating pollutant loads into a range of risk assessment equations (for example Dudhagara et al., 2016; Sarria-Villa et al., 2016; Tejeda-Benitez et al., 2016; Zhang et al., 2016).

As a number of researchers have noted, the surrounding land use type is a critical factor influencing river sediment pollution (Karstens et al., 2016; Liu et al., 2017; Zhao et al., 2017). This is due to the fact that land use is strongly associated with anthropogenic activities which can influence the pollutant loads entering waterways. However, recent research outcomes have shown that land use type alone is inadequate to explain pollutant inputs to the natural environment such as water bodies and the associated sediment bed (Ding et al., 2016; Lee et al., 2009; Shi et al., 2017). This is due to the fact that even within the same land use type, configurations such as land cover and land development layout could be significantly different. For example, in urban areas, the primary land use type includes a number of development types such as residential development, recreational areas and roads. These sub-

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classes of land use types would have different pollutant generation characteristics due to their different attributes even though these are all urban land use types. This can also be supported by a previous study undertaken by Liu et al. (2012). They found that, land use type as a lumped parameter cannot adequately explain pollutant export from different urban forms even within the same urban land use type. Urban form refers to urban planning forms including road layout, housing development forms and the configuration of the different uses. In this context, parameters which can represent the configurations within the same land use type are essential in order to undertake a more technically robust investigation into the relationships between land use and pollutant loads in river sediments.

Although numerous studies have focused on the relationship between land use type and pollutants in river sediments, only a limited number of studies have investigated how configurations within the same land use type influence river sediment pollution (Liu et al., 2017; Zhao et al., 2017). Therefore, this knowledge gap constrains effective land use planning for protecting the ecological health of waterways. It is in this context that this paper presents the outcomes of a research study which investigated the relationship between land use type and river sediment pollution by introducing robust parameters that represent land use configurations within a primary land use type. The study outcomes are expected to contribute essential knowledge for creating robust management strategies to minimise waterway pollution and thereby protect the health of aquatic ecosystems.

2 Methods and materials

2.1 Study sites

The study site selected was the Brisbane River, an urbanised river system, which is located in Southeast Queensland, Australia. The length of this river is 344 km and drains a catchment area of 1,356,000 ha. A 75 km section of the river, from the mouth where it drains into Moreton Bay up to the confluence of the Bremer River, ranges from a salt wedge estuary for short periods immediately following floods, to a well-mixed estuary intruding 60 km landwards for most of the year with the remaining 15 km being a tidal freshwater river. Many rivers and creeks drain into this river, including the Bremer River at the upper reach, Oxley, Breakfast, and Bulimba creeks at the lower reaches as it runs downstream into Moreton Bay with a mean annual discharge of about 1.4×109 m3. The existing climatic condition is sub-tropical with distinct wet summer and dry winter seasons. The annual average temperature and rainfall ranges from 15–25 °C and 940 mm, respectively (Duodu et al., 2017; Yu, 2011).

The river catchment can be categorized into four primary land use types. These are, natural environment (NAE), intensive uses (INU, primarily urban uses), agricultural areas (AGR) and water surfaces (WAS). Each primary land use type includes a number of sub-classes. For example, AGR can be further divided into irrigated cropping and grazing areas, while WAS includes rivers and reservoirs (Duodu et al., 2017 and Table S1 in the Supplementary information (DSITIA, 2014)). There were 22 sampling points selected along the river, including upstream (SP1-SP3), middle (SP4-SP11) and downstream (SP12-SP22) sections. This permitted the detailed investigation of the influence of surrounding land use on river sediment pollution as the different river sections generally relate to different land use types. Figure 1 shows these sampling points while detailed information regarding land use types (primary types and sub-classes) along the river are provided as Table S1 in the Supplementary Information.

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Figure 1 Sampling points along the Brisbane River

2.2 Sample collection and laboratory testing

The catchment has dry winters and wet summers. The sediment sampling was undertaken in the months of June (winter), September (spring), December (summer), 2014, and May (autumn), 2015. The sampling scheme was designed to enable the analysis of seasonal variation in sediment pollution. About 0-3 cm depth of sediment sample was scooped from the selected sampling points using a ponar stainless-steel grab sampler with a stainless-steel spoon to control the depth. The sampling and handling were in accordance with Australian- New Zealand standard (AS/NZS 5667.12: 1999). The sediment samples collected were stored in pre-cleaned 250mL glass jars and transported on ice to the laboratory and stored at -20ᴼC until further analysis.

Each sample collected was tested for nutrients (total nitrogen, TN and total phosphorus, TP), total carbon (TC), 16 polycyclic aromatic hydrocarbons (PAHs) classified by the US EPA as priority toxic pollutants and 20 metal species. The PAHs included naphthalene (NAP) acenaphthylene (ACY), acenaphthene (ACE), fluorene (FLU), phenanthrene (PHE), anthracene (ANT), fluoranthene (FLT), pyrene (PYR), benz(a)anthracene (BAA), chrysene (CHR), benzo(b+k)fluoranthene (BKF), benzo(a)pyrene (BAP), indeno(1.2.3.cd)pyrene (IND), dibenzo(a.h)anthracene (DBA), benzo(g.h.i)perylene (BGP) and alkylated PAH 2-bromonapthalene (BNAP) as reported earlier (Duodu et al., 2017). Metals investigated were Cr, Si, V, U, Sn, Sb, As, Al, Fe, Mn, Co, Ti, Se, Mi, Cu, Zn, Ag, Cd, Hg and Pb (Duodu et al., 2016a). However, due to equipment failure, sediment samples collected only in June (winter) and September (spring) in 2014 were tested for TP while the other pollutants were tested for all four seasons. TN, TP and TC can be generated by both inherent sources such as microorganisms in river sediments (Mu et al., 2017) as well as external sources such as anthropogenic activities (Miguntanna et al., 2013). PAHs and metals are primarily generated from external sources such as traffic emissions, but can also be products of sediment digenesis (Liu et al., 2017; Liu et al., 2016; Mejia et al., 2013). Therefore, these pollutant types can be differently influenced by surrounding land uses.

SP5

SP4

SP3

SP8

SP13

SP16

SP15

SP1

SP6

SP7

SP9

SP10

SP11

SP17

SP18

SP22

SP21

SP20

SP19

SP14

SP12

SP2

5

TN, TP and TC testing was undertaken according to test methods specified in Standard Methods for the Examination of Water and Wastewater (APHA, 2005). PAHs testing was undertaken using a Shimadzu Gas Chromatograph and Mass Spectrometer (GC-MS) while metals were tested using an Agilent 8800 Triple Quad ICP-MS. Field blanks and method blanks also underwent the same procedures as the samples. Detailed information regarding PAHs and metals testing can be found in Duodu et al. (2017) and Duodu et al. (2015), respectively. Data in relation to pollutant loads (Table S2) and detailed testing methods for these pollutants are provided in the Supplementary Information. In addition to pollutant concentrations, the mineralogy of the sediment samples was investigated by X-ray diffraction using PANalytical X’Pert PRO Multi-purpose diffractometer. The measurements were undertaken as mineralogy influences the adsorption of pollutants to solids (Gunawardana et al., 2012). A 10% weight of corundum (Al2O3) was used as the internal standard in the quantitative analysis of the mineralogical components. Data obtained relating to the mineral components are provided in Table S3 in the Supplementary Information.

2.3 Extraction of land use related parameters

As noted, a lumped land use parameter (such as percentage of a primary land use type) is not adequate to interpret pollutant generation processes. Configurations within the same land use type can also exert an important influence. This requires the introduction of additional information about land development such as their diversity and density. Accordingly, other than the percentages of the four primary land use types (NAE, INU, AGR and WAS), three new parameters relating to configurations within each primary land use type were also extracted. These were Shannon’s diversity index (SHDI), patch density (PD) and largest patch index (LPI). These data were extracted from a spatial database using ArcGIS software (see Table S4 in the Supplementary Information). For parameters related to land use configurations, the three parameters (SHDI, PD and LPI) were calculated for each primary land use type. For example, SHDI for intensive use (INU) indicates the diversity of land patches in intensively used land while PD for agricultural areas (AGR) represents the density of land patches in agricultural areas. These parameters and their explanations are given in Table 1 while the detailed calculation process is given in the Supplementary Information. In addition, the resident population in the catchment area draining to each sampling point was also included in the data analysis as a variable (see Table S1 in the Supplementary Information).

3 Results and discussion

3.1 Mineralogical analysis

Figure 2 shows the mineral types in the river sediments. It can be noted that quartz (21.4%) is the most dominant mineral type, followed by kaolinite (8.92%) and muscovite (6.41%). However, albite (2.08%) and kaolinite (1.54%) have much lower percentages. Albite, microcline and muscovite belong to clay minerals, which accounted for a total of 10.0% of mineral composition. This means that sediments have the capacity of adsorbing pollutants due to the fact that minerals, particularly clay, have relatively smaller grain size and hence, larger specific surface area and surface charge sites to which higher loads of pollutants could be attached (Gunawardana et al., 2014).

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Table 1 Land use related parameters

Variables Abbreviation Explanations

Parameters related to

primary land use

Natural environment NAE

Natural environment land use percentage accounting for the total area in the

contributing catchment to each sampling point

Intensive use INU

Intensive use land percentage accounting for the total area in the contributing catchment to

each sampling point

Agricultural areas AGR

Agricultural area percentage accounting for the total area in the contributing catchment to

each sampling point

Water surfaces WAS

Water surface percentage accounting for the total area in the contributing catchment to

each sampling point

Parameters related to

configurations within the

primary land use

Shannon’s Diversity

Index SHDI

Describes the land use patch diversity within a primary land use type. The calculation

equation is 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 = −∑ (𝑝𝑝𝑖𝑖𝐿𝐿𝐿𝐿𝑝𝑝𝑖𝑖)𝑚𝑚𝑖𝑖=1 * (Lee et

al., 2009)

Patch density PD

Number of patches per unit area (number per 100 ha). The equation used for the calculation

𝑃𝑃𝑆𝑆 = 𝑁𝑁𝐴𝐴/100

**

Largest patch index LPI

The area of the largest patch divided by total land use area. The equation used for the

calculation 𝐿𝐿𝑃𝑃𝑆𝑆 = 𝐴𝐴𝑚𝑚𝑚𝑚𝑚𝑚

𝐴𝐴***

* pi=proportion of the land patch area accounting for the total area of a primary land use type; m=number of land patches within the primary land use type ** N=total number of land patches in a primary land use type; A=total area of the primary land use type (ha) *** Amax=the area of the largest land patch in a primary land use type (ha)

Quartz Albite Microcline Kaolinite Muscovite Amorphous

Perc

enta

ge (%

)

0

10

20

30

Figure 2 Mineral compositions of the river sediments

Mean value

Standard deviation

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It is also noteworthy that amorphous materials accounted for 8.25%, which is the third most dominant mineral type. As Gunawardana et al. (2014) have pointed out, these amorphous material primarily originate from anthropogenic activities such as vehicular and land use related sources. Solids deposited on road surfaces could significantly contribute to the amorphous materials in the river sediments as noted by Gunawardana et al. (2014). This confirms the role of anthropogenic activities in sediment pollution.

A further analysis was undertaken using principal component analysis (PCA) to investigate the relationship between mineral components and land use types. A matrix (22×18) was submitted to PCA. The objects were the 22 sampling points while the variables included the six mineral types and the three land use configuration parameters (SHDI, PD and LPI) for the four primary land use types (NAE, INU, ARG and WAS). Figure 3 gives the resulting PCA biplot. It can be noted that most vectors forming acute angles with mineral vectors are SHDI and PD while LPI vector is relatively far from the mineral types. This observation is independent of the primary land use types. This implies that land use diversity and their density play an important role in influencing mineral components in river sediments. Land use development with more diverse and higher density could lead to higher mineral component amounts, which would adsorb higher loads of pollutants, increasing river sediment pollution.

Figure 3 PCA biplot for mineral components and land use configuration parameters

3.2 Analysis of pollutant loads in river sediments

Figure 4 compares nutrients, total carbon, total PAH loads (sum of the 16 PAH loads) and total metal loads (sum of the 20 metal loads) for the different seasons. One-way ANOVA analysis confirmed that there is no significant difference in the mean values of TN, TOC, total PAH loads and total metal loads except TP for the four seasons. The one-way ANOVA results

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for TN, TP, TC, total PAHs and total metals were 0.72, 0.01, 0.78, 0.10 and 0.57, respectively, which are larger than 0.05 significant level, except for TP. These outcomes imply that the climatic seasons play a less important role than anthropogenic sources in influencing pollutant loads in the river sediments.

Additionally, as evident in Figure 4, data ranges such as TN load in autumn, TP load in spring, TC load in autumn, total PAH load in winter, spring and summer and total metal loads in winter and spring are relatively wide. Since these sediment samples were collected from different sampling points along the river, the relatively wide data ranges can be attributed to differences in land use types in the contributing catchments at the sampling points.

Winter Spring Summer Autumn

TN (g

/kg)

0.0

0.5

1.0

1.5

2.0

2.5

Winter Spring

TP (g

/kg)

0

1

2

3

4

5

6

7


TC (g

/kg)

0

10

20

30

40

50

60


Tota

l PA

Hs

(ug/

g)

0

2

4

6

8

10


Tota

l met

als

(mg/

g)

0

200

400

600

800

1000

1200

1400

1600

Figure 4 Comparison of pollutant loads for different climatic seasons

(Note: TP was tested for two seasons only due to equipment failure)

Mean value

Median value

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Anthropogenic activities contribute to river sediment pollution and different land use types lead to differences in pollutant loads in terms of their spatial distribution along the river. Therefore, it was essential to investigate the influence of anthropogenic activities on pollutant loads in river sediments. For this purpose, cluster analysis (CA) was performed using OrignPro 2016 software and the nearest neighbor method was applied. The factors investigated were the four primary land use types (NAE, INU, AGR and WAS) and population (POP), while pollutant loads were the mean values of the pollutants obtained during the different seasons. For detailed analysis, the PAHs data were further divided into three groups: 2-3-ringed, 4-ringed and 5-6-ringed PAHs since PAHs with different ring numbers might be generated from different sources, where 2-3-ringed PAHs could be from light-duty vehicles and PAHs with more than 4 rings are primarily from heavy-duty vehicles (Liu et al., 2016). Additionally, according to a previous research study undertaken in the Brisbane River (Duodu et al., 2016a), metals in the sediments were found to be primarily sourced from marine (including Cr, Si, V, U, Sn, Sb and As), soil (including Al, Fe, Mn, Co, Ti and Se) and anthropogenic activities (including Ni, Cu, Zn, Ag, Cd, Hg and Pb). Therefore, the metals data was divided into three types, namely, marine (Marine-M), soil (Soil-M) and anthropogenic source (Human-M). For each type, the loads of metal species were firstly summed. Taking marine sourced metals as an example, the total loads of Cr, Si, V, U, Sn, Sb and As (summation of these metals) were calculated for the four seasons. Then, the mean value of the total loads of marine sourced metals in the four seasons was used for CA. The same method was applied for soil and anthropogenic sourced metals.

Accordingly, a 22×14 data matrix was created for the CA, where the objects were the 22 sampling points and the 14 variables included TN, TP, TC, 2-3-ringed, 4-ringed and 5-6-ringed PAHs, marine sourced, soil sourced and anthropogenic sourced metals, the four land use related factors (NAE, INU, AGR and WAS) and population (POP). Figure 5 shows the outcomes of the cluster analysis.

It can be noted in Figure 5 that INU has the closest relationship with pollutants, particularly with PAHs and anthropogenic sourced metals, followed by TN, TC and TP. Marine and soil sourced metals are close to AGR, NAE, WAS and POP. This means that PAH and anthropogenic activities related metal loads are more influenced by intensively developed lands than nutrients and total carbon, while marine and soil sourced metals are more related to the relatively natural environment. This is attributed to the fact that intensive urban uses have more complex and diverse development forms than the other three primary land use types (see Table S1, intensive uses generally have much more sub-classes than the other primary land use types), which in turn would lead to the generation of higher pollutant loads. This implies that the configurations within the primary land use types rather than difference between primary land use types play a more important role in influencing pollutant generation.

3.3 Relationship between land use type and pollutant loads in river sediments

As discussed above, configurations within the primary land use type influence pollutant loads in river sediments. To investigate their correlations with sediment pollution, PCA was employed for each primary land use type. Four data matrices were created with each matrix size being 22×12. The objects were the 22 sampling points and the variables included TN, TP, TC, 2-3-ringed PAHs, 4-ringed PAHs, 5-6-ringed PAHs, Marine-M, Soil-M, Human-M metal loads and three parameters related to land use configurations (SHDI, PD and LPI, see Table 1). Figure 6 shows the resulting PCA biplots.

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Figure 5 Cluster analysis results

As evident in Figure 6, SHDI, PD and LPI generally have different relationships with pollutants since vectors representing the three parameters point to different directions, particularly in NAE, AGR and WAS land use types (see Figure 5a, 5c and 5d). PD shows a relatively closer correlation with pollutants than SHDI and LPI, as the angles between PD and pollutant vectors are more acute compared to SHDI and LPI. This suggests that land use patch density play a more important role in influencing pollutant generation and pollutant loads in river sediments. In other words, more aggregated and compact forms of land use development would produce higher pollutant loads even though these land use patches may belong to the same land use type. This is particularly applicable to the natural environment (NAE), agricultural land (AGR) and water surfaces (WAS). High density of land use patches means that a land is divided into a number of patches, which can be used for different purposes. This could generate higher pollutant loads than the case where the land is used as a whole for a single use only.

For intensive urban use (INU, Figure 6b), SHDI, PD and LPI are strongly correlated with pollutants (except for Marine-M and Soil-M) as the vectors representing these three parameters form acute angles with the pollutant vectors. This implies that within the intensive urban use lands, both patch density and land development diversity exert a significant influence on producing pollutant loads. This can be attributed to the fact that denser and more

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diverse urban land use planning generally leads to complex urban forms and patch shapes, which are well connected by roads. This would increase impervious surface areas and consequently lead to high traffic volumes, thereby generating high pollutant loads. Furthermore, a complex urban development form requires equally complex drainage systems which could result in the collection of greater drainage flows and higher pollutant loads, leading to increased pollution contributions to receiving waters. Additionally, the higher percentage of the largest patch (LPI) also contributes a relatively higher pollutant load to the receiving waters. These results mean that complex urban form and urban development layout would contribute relatively higher pollutant loads to the receiving waters and consequently to the river sediments.

Figure 6 PCA biplots (a): NAE; (b): INU; (c): AGR; (d): WAS

In addition, it is evident that as marine (Marine-M) and soil (Soil-M) metal vectors form obtuse angles with the other pollutants and hence, do not have a close relationship with land use related parameters for all four PCA biplots. This is despite the fact that Marine-M and Soil-M vectors form acute angles with LPI and SHDI vectors in the AGR biplot. This confirms that metals primarily sourced by marine and soil are not significantly influenced by land use.

Furthermore, TN, TP and TC vectors are far from PAH vectors and anthropogenic activities sourced metals (Human-M) vector in all of the four primary land use PCA biplots. The vectors representing land use related parameters (PD vectors in NAE, AGR and WAS biplots

a

b

c

d

12

and SHDI, PD and LPI vectors in INU biplots) form acute angles with PAH vectors and Human-M vector. This suggests that land use type has a more significant influence on Ni, Cu, Zn, Ag, Cd, Hg, Pb (anthropogenic sourced metals, see Section 3.2) and PAH loads in river sediments than nutrients and carbon. This is attributed to the fact that nutrients and carbon can be contributed by inherent sources within the river systems such as microorganisms in the sediments as well as external sources such as land use type as discussed in Section 2.2. However, Ni, Cu, Zn, Ag, Cd, Hg, Pb and PAHs are primarily sourced from anthropogenic activities such as traffic emissions, which are external sources. In this context, the influence of land use type could be more discernible in the case of PAHs and anthropogenic sourced metals when compared to nutrients and carbon in the river sediments.

4 Conclusions

This paper investigated nutrients, carbon, PAH and metal loads in the sediments of Brisbane River. It was found that anthropogenic activities significantly contribute pollutants to the river sediments. How land is developed plays a significant role in the contribution of pollutants to receiving waters and thereby to the sediments. This is not only related to primary land use types, but also the configurations within the same land use type including patch density, diversity and largest-patch proportion. Therefore, controlling land use development and planning practices can minimise sediment pollution and enhance water environment health. The study results provide essential knowledge to safeguard the aquatic environment from anthropogenic pollution.

Supplementary Information

Supplementary Information provides approach to extracting land use configuration data, laboratory testing, land use related parameters, pollutant loads in river sediments and data for mineralogy.

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Liu, A., Duodu, G.O., Mummullage, S., Ayoko, G.A., Goonetilleke, A., 2017. Hierarchy of factors which influence polycyclic aromatic hydrocarbons (PAHs) distribution in river sediments. Envrionmental Pollution.

Liu, A., Goonetilleke, A., Egodawatta, P., 2012. Inherent errors in pollutant build-up estimation in considering urban land use as a lumped parameter. Journal of Environmental Quality 41, 1690-1694.

Liu, L., Liu, A., Li, Y., Zhang, L.X., Zhang, G.J., Guan, Y.T., 2016. Polycyclic aromatic hydrocarbons associated with road deposited solid and their ecological risk: Implications for road stormwater reuse. Science of The Total Environment 563-564, 190-198.

Mejia, C.A.Z., Pinzon, E.C.L., Gonzalez, J.T., 2013. Influence of traffic in the heavy metals accumulation on urban roads: Torrelavega (Spain)-Soacha (Colombia). Revista Facultad de Ingenieria-Universidad de Antioquia, 146-160.

Miguntanna, N., Liu, A., Egodawatta, P., Goonetilleke, A., 2013. Characterising nutrients wash-off for effective urban stormwater treatment design. Journal of Environmental Management 120, 61-67.

Mu, D., Yuan, D., Feng, H., Xing, F., Li, S., 2017. Nutrient fluxes across sediment-water interface in Bohai Bay Coastal Zone, China. Marine Pollution Bulletin 114, 705-714.

Sarria-Villa, R., Ocampo-Duque, W., Paez, M., Schuhmacher, M., 2016. Presence of PAHs in water and sediments of the Colombian Cauca River during heavy rain episodes, and implications for risk assessment. Science of The Total Environment 540, 455-465.

14

Shi, P., Zhang, Y., Li, Z., Li, P., Xu, G., 2017. Influence of land use and land cover patterns on seasonal water quality at multi-spatial scales. CATENA 151, 182-190.

Standards Australia & Standards New Zealand, 1999. Water quality sampling-Part 12: Guidance on sampling of bottom sediments, AS/NZS 5667.12

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Yu, Y., 2011. Numerical Study of the Brisbane River Plume in Morton Bay: Masters thesis, Griffith University, Brisbane, Australia

Zhang, D.L., Liu, J.Q., Jiang, X.J., Cao, K., Yin, P., Zhang, X.H., 2016. Distribution, sources and ecological risk assessment of PAHs in surface sediments from the Luan River Estuary, China. Marine Pollution Bulletin 102, 223-229.

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15

SUPPLEMENTARY INFORMATION

Influence of land use configurations on river sediment pollution

An Liu1,2,3, Godfred O. Duodu3, Ashantha Goonetilleke3*, Godwin A. Ayoko3 1 College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen 518060, People’s Republic of China 2 Shenzhen Key Laboratory of Environmental Chemistry and Ecological Remediation, Shenzhen 518060, People’s Republic of China 3 Science and Engineering Faculty, Queensland University of Technology (QUT), P.O. Box 2434, Brisbane, Qld 4001, Australia

*Corresponding author:

E-mail: [email protected]; Tel: +61 7 3138 1539; Fax: +61 7 3138 1170

mailto:[email protected]

16

Table S1 Population and catchment characteristics along the Brisbane River-SP1 (adapted from DSITIA, 2014)

Population (thousand) 22.17

Primary land use Secondary land use Tertiary land use Area (ha) Percentage (%)

Natural environment

Managed resource protection Managed resource protection 96.18 1.09

Nature conservation Natural feature protection 489.17 5.52

Nature conservation Other conserved area 219.12 2.47

Other minimal use Other minimal use 3.96 0.04

Other minimal use Residual native cover 1350.07 15.24

Intensive uses1

Intensive animal production Poultry farms 2.47 0.03

Residential Rural living 4195.39 47.35

Residential Rural residential 0.00 0.00

Residential Urban residential 369.33 4.17

Services Public services 17.42 0.20

Services Recreation and culture 191.33 2.16

Services Research facilities 284.28 3.21

Utilities Electricity substations & transmission 10.28 0.12

Waste treatment and disposal Waste treatment and disposal 52.26 0.59

Agricultural areas

Cropping Cropping 12.24 0.14

Land in transition Land in transition 74.58 0.84

Irrigated modified pastures Irrigated modified pastures 24.38 0.28

Irrigated perennial horticulture Irrigated perennial horticulture 0.92 0.01

Grazing native vegetation Grazing native vegetation 1264.76 14.27

Water surfaces Reservoir/dam Reservoir/dam 5.69 0.06

River River 196.63 2.22 1 referred to as intensive urban uses in the manuscript since most of the tertiary land use types were urban development. The same applies to other sampling points

17

Table S1 continued-SP2

Population (thousand) 0


Natural environment

Nature conservation National park 7429.41 3.66 Nature conservation Natural feature protection 308.81 0.15 Nature conservation Habitat/species management area 10.21 0.01 Nature conservation Other conserved area 1501.74 0.74

Managed resource protection Managed resource protection 3000.07 1.48 Other minimal use Other minimal use 824.60 0.41 Other minimal use Defence 2372.16 1.17 Other minimal use Residual native cover 9030.86 4.45

Agricultural areas

Grazing native vegetation Grazing native vegetation 140267.37 69.09 Production forestry Production forestry 141.16 0.07 Plantation forestry Plantation forestry 2264.85 1.12 Plantation forestry Hardwood plantation 22.80 0.01

Grazing modified pastures Grazing modified pastures 2201.11 1.08 Cropping Hay & silage 141.07 0.07

Perennial horticulture Perennial horticulture 19.15 0.01 Perennial horticulture Perennial tree fruits 3.16 0.00

Land in transition Land in transition 165.76 0.08 Land in transition Land under rehabilitation 181.12 0.09

Irrigated modified pastures Irrigated modified pastures 3359.78 1.65 Irrigated cropping Irrigated cropping 8040.43 3.96 Irrigated cropping Irrigated hay & silage 87.97 0.04

Irrigated perennial horticulture Irrigated perennial horticulture 28.22 0.01 Irrigated perennial horticulture Irrigated tree fruits 20.68 0.01 Irrigated perennial horticulture Irrigated oleaginous fruits 4.53 0.00 Irrigated perennial horticulture Irrigated vine fruits 58.26 0.03

18

Irrigated perennial horticulture Irrigated flowers & bulbs 5.00 0.00 Irrigated seasonal horticulture Irrigated seasonal horticulture 8.31 0.00 Irrigated seasonal horticulture Irrigated seasonal vegetables & herbs 2309.32 1.14

Intensive uses

Intensive horticulture Abandoned intensive horticulture 9.48 0.00 Intensive animal production Dairy sheds & yards 5.82 0.00 Intensive animal production Poultry farms 54.50 0.03 Intensive animal production Aquaculture 70.83 0.03 Intensive animal production Horse studs 257.88 0.13 Intensive animal production Stockyards/saleyards 106.29 0.05 Manufacturing and industrial Manufacturing and industrial 323.20 0.16 Manufacturing and industrial Food processing factory 3.74 0.00 Manufacturing and industrial Abbatoirs 163.14 0.08 Manufacturing and industrial Sawmill 2.45 0.00

Residential Residential 58.30 0.03 Residential Urban residential 5674.86 2.80 Residential Rural residential 241.18 0.12 Residential Rural living 5099.43 2.51

Services Commercial services 364.89 0.18 Services Public services 652.35 0.32 Services Recreation and culture 1629.23 0.80 Services Defence facilities - urban 1.71 0.00 Utilities Utilities 18.72 0.01 Utilities Fuel powered electricity generation 56.05 0.03 Utilities Electricity substations & transmission 23.44 0.01 Utilities Water extraction & transmission 20.28 0.01

Transport and communication Airports/aerodromes 23.73 0.01 Transport and communication Roads 338.41 0.17 Transport and communication Railways 57.51 0.03

Mining Mining 688.82 0.34

19

Mining Mines 594.21 0.29 Mining Quarries 167.47 0.08 Mining Extractive industry not in use 200.07 0.10

Waste treatment and disposal Waste treatment and disposal 4.70 0.00 Waste treatment and disposal Landfill 4.89 0.00 Waste treatment and disposal Sewage 41.90 0.02

Water surfaces

Reservoir/dam Reservoir/dam 1595.24 0.79 Reservoir/dam Water storage - intensive use/farm dams 7.38 0.00

River River 120.22 0.06 Marsh/wetland Marsh/wetland 542.98 0.27

Table S1 continued-SP3 Population (thousand) 25.19


Natural environment

Nature conservation Natural feature protection 197.74 3.74 Nature conservation Other conserved area 1794.80 33.94 Other minimal use Other minimal use 32.17 0.61 Other minimal use Residual native cover 464.72 8.79

Intensive uses

Intensive animal production Intensive animal production 4.34 0.08 Manufacturing and industrial Manufacturing and industrial 5.41 0.10

Mining Mines 185.40 3.51 Mining Mining 2.66 0.05 Mining Quarries 79.17 1.50

Residential Rural living 171.81 3.25 Residential Rural residential 0.23 0.00 Residential Urban residential 653.81 12.36

Services Commercial services 9.61 0.18 Services Public services 52.09 0.99

20

Services Recreation and culture 115.80 2.19 Transport and communication Navigation and communication 0.67 0.01 Transport and communication Roads 69.09 1.31

Utilities Electricity substations & transmission 61.64 1.17 Waste treatment and disposal Waste treatment and disposal 10.66 0.20

Agricultural areas



Water surfaces

Reservoir/dam Reservoir/dam 35.78 0.68 River River 19.75 0.37


Population (thousand) 34.24 Primary land use Secondary land use Tertiary land use Area (ha) Percentage (%)

Natural environment

Nature conservation Natural feature protection 197.74 2.90 Nature conservation Other conserved area 1937.39 28.39 Other minimal use Other minimal use 77.21 1.13 Other minimal use Residual native cover 753.83 11.05

Intensive uses

Intensive animal production Intensive animal production 4.34 0.06 Manufacturing and industrial Major industrial complex 81.83 1.20 Manufacturing and industrial Manufacturing and industrial 23.00 0.34

Mining Mines 185.40 2.72 Mining Mining 2.66 0.04 Mining Quarries 79.17 1.16


Services Commercial services 22.24 0.33

21

Services Public services 63.00 0.92 Services Recreation and culture 193.67 2.84 Services Services 5.03 0.07

Transport and communication Navigation and communication 0.67 0.01 Transport and communication Roads 89.81 1.32 Transport and communication Transport and communication 0.97 0.01

Utilities Electricity substations & transmission 75.54 1.11 Waste treatment and disposal Waste treatment and disposal 10.66 0.16

Agricultural areas



Water surfaces Reservoir/dam Reservoir/dam 35.78 0.52

River River 22.83 0.33



Natural environment

Nature conservation Natural feature protection 199.93 1.04 Nature conservation Other conserved area 2623.96 13.64 Other minimal use Defence 707.35 3.68 Other minimal use Other minimal use 271.14 1.41 Other minimal use Residual native cover 2803.81 14.57

Intensive uses

Intensive animal production Horse studs 3.97 0.02 Intensive horticulture Shadehouses 33.32 0.17

Manufacturing and industrial Manufacturing and industrial 353.43 1.84 Mining Mines 22.21 0.12

Residential Rural living 3451.24 17.94 Residential Rural residential 20.08 0.10

22

Residential Urban residential 1693.81 8.80 Services Commercial services 83.44 0.43 Services Defence facilities - urban 4.07 0.02 Services Public services 309.51 1.61 Services Recreation and culture 566.57 2.94 Services Research facilities 18.32 0.10 Services Services 7.24 0.04

Transport and communication Navigation and communication 21.31 0.11 Transport and communication Railways 0.68 0.00 Transport and communication Roads 260.18 1.35

Utilities Electricity substations & transmission 193.31 1.00 Utilities Water extraction & transmission 9.54 0.05

Waste treatment and disposal Waste treatment and disposal 37.35 0.19

Agricultural areas


Perennial horticulture Perennial horticulture 9.69 0.05 Plantation forestry Plantation forestry 151.81 0.79

Irrigated perennial horticulture Irrigated perennial horticulture 6.56 0.03 Irrigated seasonal horticulture Irrigated seasonal horticulture 6.58 0.03 Irrigated seasonal horticulture Irrigated turf farming 56.22 0.29


Water surfaces

Channel/aqueduct Drainage channel/aqueduct 17.01 0.09 Lake Lake 20.10 0.10

Marsh/wetland Marsh/wetland 40.69 0.21 Reservoir/dam Reservoir/dam 20.71 0.11


23



Natural environment

Nature conservation Natural feature protection 2.84 0.01 Nature conservation Other conserved area 1360.83 5.55 Other minimal use Defence 4649.92 18.96 Other minimal use Other minimal use 306.69 1.25 Other minimal use Residual native cover 1689.93 6.89

Intensive uses

Intensive animal production Horse studs 3.97 0.02 Intensive horticulture Intensive horticulture 18.57 0.08 Intensive horticulture Shadehouses 54.20 0.22

Manufacturing and industrial Major industrial complex 47.01 0.19 Manufacturing and industrial Manufacturing and industrial 1254.35 5.12

Mining Quarries 79.49 0.32 Residential Rural living 4828.03 19.69 Residential Rural residential 236.75 0.97 Residential Urban residential 2828.94 11.54

Services Commercial services 86.27 0.35 Services Defence facilities - urban 107.00 0.44 Services Public services 308.90 1.26 Services Recreation and culture 674.92 2.75 Services Research facilities 18.32 0.07 Services Services 19.51 0.08

Transport and communication Airports/aerodromes 0.02 0.00 Transport and communication Railways 16.81 0.07 Transport and communication Roads 464.68 1.89 Transport and communication Transport and communication 6.01 0.02

Utilities Electricity substations & transmission 119.68 0.49

24

Utilities Water extraction & transmission 3.17 0.01 Waste treatment and disposal Waste treatment and disposal 210.51 0.86

Agricultural areas

Land in transition Degraded land 32.12 0.13 Land in transition Land in transition 114.14 0.47 Land in transition Land under rehabilitation 129.53 0.53

Perennial horticulture Perennial horticulture 12.35 0.05 Plantation forestry Plantation forestry 151.81 0.62

Irrigated perennial horticulture Irrigated perennial horticulture 9.17 0.04 Irrigated seasonal horticulture Irrigated seasonal horticulture 48.54 0.20 Irrigated seasonal horticulture Irrigated turf farming 56.22 0.23


Water surfaces

Channel/aqueduct Drainage channel/aqueduct 17.01 0.07 Marsh/wetland Marsh/wetland 71.22 0.29 Reservoir/dam Reservoir/dam 169.47 0.69 Reservoir/dam Water storage - intensive use/farm dams 2.16 0.01




Natural environment

Managed resource protection Managed resource protection 8.25 0.07 Nature conservation National park 284.56 2.25 Nature conservation Natural feature protection 489.17 3.86 Nature conservation Other conserved area 2701.46 21.34 Other minimal use Other minimal use 3.53 0.03 Other minimal use Residual native cover 1079.23 8.52

Intensive uses

Intensive animal production Horse studs 5.73 0.05 Intensive animal production Poultry farms 2.47 0.02

25

Intensive horticulture Shadehouses 5.92 0.05 Mining Quarries 15.10 0.12


Services Commercial services 29.47 0.23 Services Public services 46.12 0.36 Services Recreation and culture 186.63 1.47 Services Research facilities 284.44 2.25

Transport and communication Navigation and communication 10.48 0.08 Transport and communication Roads 11.53 0.09

Utilities Water extraction & transmission 1.61 0.01

Agricultural areas

Land in transition Land in transition 4.30 0.03 Perennial horticulture Perennial horticulture 41.38 0.33 Seasonal horticulture Seasonal horticulture 22.26 0.18

Irrigated perennial horticulture Irrigated perennial horticulture 0.92 0.01 Irrigated perennial horticulture Irrigated tree fruits 3.17 0.03


Water surfaces

Marsh/wetland Marsh/wetland 2.65 0.02 Reservoir/dam Reservoir 0.14 0.00 Reservoir/dam Reservoir/dam 21.55 0.17

River River 10.87 0.09 River River - intensive use 1.02 0.01



Natural environment

Nature conservation Other conserved area 22.32 2.98 Other minimal use Residual native cover 0.07 0.01

26

Intensive uses

Residential Urban residential 534.66 71.47 Services Commercial services 27.34 3.65 Services Public services 35.96 4.81 Services Recreation and culture 111.19 14.86

Transport and communication Roads 13.56 1.81 Utilities Water extraction & transmission 1.87 0.25

Water surfaces River River 1.17 0.16



Natural environment

Nature conservation Natural feature protection 489.17 11.21 Nature conservation Other conserved area 91.48 2.10 Other minimal use Residual native cover 412.44 9.45

Intensive uses

Intensive animal production Poultry farms 2.47 0.06 Residential Rural living 2809.07 64.38 Residential Urban residential 124.87 2.86

Services Public services 9.40 0.22 Services Recreation and culture 22.88 0.52 Services Research facilities 284.28 6.51

Agricultural areas

Irrigated perennial horticulture Irrigated perennial horticulture 0.92 0.02 Grazing native vegetation Grazing native vegetation 102.93 2.36

Water surfaces

Reservoir/dam Reservoir/dam 5.69 0.13 River River 7.87 0.18

27



Natural environment

Nature conservation Other conserved area 29.23 1.12 Other minimal use Defence 26.13 1.00 Other minimal use Other minimal use 37.12 1.42 Other minimal use Residual native cover 16.36 0.63

Intensive uses

Manufacturing and industrial Manufacturing and industrial 318.97 12.23 Mining Quarries 31.62 1.21


Services Commercial services 49.14 1.88 Services Defence facilities - urban 1.33 0.05 Services Public services 76.87 2.95 Services Recreation and culture 350.66 13.44 Services Research facilities 0.16 0.01

Transport and communication Railways 16.11 0.62 Transport and communication Roads 122.86 4.71 Transport and communication Transport and communication 0.84 0.03


Agricultural areas

Land in transition Degraded land 32.12 1.23 Land in transition Land in transition 3.71 0.14

Water surfaces River River 4.44 0.17

28



Natural environment

Managed resource protection Managed resource protection 8.25 0.06 Nature conservation National park 3142.90 23.46 Nature conservation Other conserved area 2925.19 21.84 Other minimal use Other minimal use 7.63 0.06 Other minimal use Residual native cover 701.31 5.23

Intensive uses





Transport and communication Navigation and communication 10.50 0.08 Transport and communication Railways 2.30 0.02 Transport and communication Roads 18.39 0.14 Transport and communication Transport and communication 5.55 0.04


Agricultural areas


29

Irrigated perennial horticulture Irrigated tree fruits 3.17 0.02

Water surfaces





Natural environment

Nature conservation National park 25.77 0.22 Nature conservation Other conserved area 851.69 7.39 Other minimal use Other minimal use 417.55 3.62 Other minimal use Residual native cover 834.33 7.24

Intensive uses

Intensive horticulture Intensive horticulture 11.39 0.10 Intensive horticulture Shadehouses 17.46 0.15

Manufacturing and industrial General purpose factory 4.09 0.04 Manufacturing and industrial Major industrial complex 938.89 8.14 Manufacturing and industrial Manufacturing and industrial 389.54 3.38

Mining Mining 34.55 0.30 Mining Quarries 48.21 0.42



30

Services Services 27.65 0.24 Transport and communication Airports/aerodromes 253.26 2.20 Transport and communication Navigation and communication 8.39 0.07 Transport and communication Railways 119.45 1.04 Transport and communication Roads 296.50 2.57 Transport and communication Transport and communication 5.17 0.04


Waste treatment and disposal Sewage 13.11 0.11 Waste treatment and disposal Waste treatment and disposal 205.83 1.79

Agricultural areas


Perennial horticulture Perennial horticulture 2.66 0.02 Irrigated perennial horticulture Irrigated perennial horticulture 3.51 0.03 Irrigated seasonal horticulture Irrigated seasonal horticulture 29.96 0.26


Water surfaces

Channel/aqueduct Drainage channel/aqueduct 26.26 0.23 Marsh/wetland Marsh/wetland 95.63 0.83 Reservoir/dam Reservoir/dam 146.35 1.27 Reservoir/dam Water storage - intensive use/farm dams 2.16 0.02


Table S1 continued-SP13 Population (thousand) 181.01


Natural environment

Managed resource protection Managed resource protection 8.25 0.05 Nature conservation National park 3168.67 17.41 Nature conservation Natural feature protection 8.16 0.04 Nature conservation Other conserved area 3307.14 18.17

31

Other minimal use Other minimal use 74.71 0.41 Other minimal use Residual native cover 776.35 4.27

Intensive uses

Intensive animal production Horse studs 5.73 0.03 Intensive horticulture Intensive horticulture 2.06 0.01 Intensive horticulture Shadehouses 5.92 0.03

Manufacturing and industrial Major industrial complex 176.40 0.97 Manufacturing and industrial Manufacturing and industrial 50.62 0.28





Waste treatment and disposal Sewage 2.03 0.01

Agricultural areas


Irrigated perennial horticulture Irrigated tree fruits 3.17 0.02 Irrigated seasonal horticulture Irrigated seasonal horticulture 28.48 0.16

Water surfaces

Marsh/wetland Marsh/wetland 45.82 0.25 Reservoir/dam Reservoir 0.14 0.00

32

Reservoir/dam Reservoir/dam 78.57 0.43 River River 5.57 0.03 River River - intensive use 1.02 0.01



Natural environment

Managed resource protection Managed resource protection 8.25 0.07 Nature conservation National park 3142.90 27.60 Nature conservation Other conserved area 2875.14 25.24 Other minimal use Residual native cover 665.06 5.84

Intensive uses



Services Commercial services 104.31 0.92 Services Public services 81.12 0.71 Services Recreation and culture 164.67 1.45



Agricultural areas


Irrigated perennial horticulture Irrigated tree fruits 3.17 0.03

33

Water surfaces





Natural environment

Nature conservation Other conserved area 48.65 3.01 Other minimal use Other minimal use 2.52 0.16 Other minimal use Residual native cover 12.94 0.80

Intensive uses

Manufacturing and industrial Manufacturing and industrial 24.23 1.50 Residential Rural living 20.48 1.27 Residential Urban residential 844.00 52.26

Services Commercial services 334.98 20.74 Services Defence facilities - urban 2.75 0.17 Services Public services 120.65 7.47 Services Recreation and culture 146.90 9.10


Utilities Utilities 0.17 0.01 Agricultural areas Land in transition Land in transition 4.64 0.29

Water surfaces

Marsh/wetland Marsh/wetland 0.11 0.01 River River 1.39 0.09

34



Natural environment

Nature conservation National park 0.00 0.00 Nature conservation Other conserved area 170.84 3.96 Other minimal use Other minimal use 12.97 0.30 Other minimal use Residual native cover 50.93 1.18

Intensive uses

Manufacturing and industrial Manufacturing and industrial 17.31 0.40 Residential Rural living 431.61 10.01 Residential Urban residential 2452.37 56.85



Utilities Electricity substations & transmission 1.51 0.03 Agricultural areas Land in transition Land in transition 24.63 0.57

Water surfaces




Natural environment Nature conservation Other conserved area 56.03 2.34

35

Other minimal use Other minimal use 3.11 0.13 Other minimal use Residual native cover 15.55 0.65

Intensive uses

Manufacturing and industrial Manufacturing and industrial 5.46 0.23 Residential Urban residential 1738.23 72.62

Services Commercial services 172.85 7.22 Services Public services 117.00 4.89 Services Recreation and culture 218.63 9.13



Water surfaces




Natural environment

Nature conservation National park 2858.34 32.84 Nature conservation Other conserved area 1846.39 21.21 Other minimal use Defence 10.42 0.12 Other minimal use Other minimal use 14.41 0.17 Other minimal use Residual native cover 57.90 0.67

Intensive uses


Residential Rural living 450.03 5.17 Residential Urban residential 2063.54 23.71

Services Commercial services 242.07 2.78

36

Services Defence facilities - urban 249.51 2.87 Services Public services 160.74 1.85 Services Recreation and culture 474.50 5.45



Agricultural areas Land in transition Land in transition 25.19 0.29

Water surfaces

Marsh/wetland Marsh/wetland 33.76 0.39 Reservoir/dam Reservoir/dam 61.34 0.70




Natural environment


Intensive uses


Intensive horticulture Intensive horticulture 21.66 0.19 Manufacturing and industrial Abattoirs 19.87 0.17 Manufacturing and industrial Major industrial complex 36.56 0.31 Manufacturing and industrial Manufacturing and industrial 956.67 8.19


37


Services Commercial services 308.09 2.64 Services Defence facilities - urban 23.64 0.20 Services Public services 313.10 2.68 Services Recreation and culture 1575.17 13.49 Services Services 0.52 0.00


Utilities Electricity substations & transmission 55.64 0.48 Utilities Utilities 0.79 0.01 Utilities Water extraction & transmission 1.82 0.02

Waste treatment and disposal Sewage 13.88 0.12 Waste treatment and disposal Waste treatment and disposal 62.38 0.53

Agricultural areas

Land in transition Land in transition 134.79 1.15 Plantation forestry Plantation forestry 2.61 0.02 Irrigated cropping Irrigated cropping 2.61 0.02

Irrigated land in transition Degraded irrigated land 8.09 0.07 Irrigated perennial horticulture Irrigated perennial horticulture 4.72 0.04 Irrigated perennial horticulture Irrigated tree fruits 9.81 0.08 Irrigated seasonal horticulture Irrigated seasonal horticulture 28.48 0.24 Irrigated seasonal horticulture Irrigated seasonal vegetables & herbs 195.09 1.67

Water surfaces

Channel/aqueduct Drainage channel/aqueduct 20.17 0.17 Marsh/wetland Marsh/wetland 182.66 1.56 Reservoir/dam Reservoir/dam 19.14 0.16


38



Natural environment


Intensive uses


Intensive horticulture Intensive horticulture 21.66 0.23 Manufacturing and industrial Major industrial complex 36.56 0.40 Manufacturing and industrial Manufacturing and industrial 340.01 3.68



Services Commercial services 181.53 1.97 Services Public services 300.78 3.26 Services Recreation and culture 1194.82 12.94 Services Services 0.52 0.01


Utilities Electricity substations & transmission 30.47 0.33 Utilities Utilities 0.79 0.01 Utilities Water extraction & transmission 1.76 0.02

Waste treatment and disposal Waste treatment and disposal 62.38 0.68 Agricultural areas Land in transition Land in transition 84.02 0.91

39

Irrigated cropping Irrigated cropping 2.61 0.03 Irrigated land in transition Degraded irrigated land 8.09 0.09

Irrigated perennial horticulture Irrigated perennial horticulture 4.72 0.05 Irrigated perennial horticulture Irrigated tree fruits 9.81 0.11 Irrigated seasonal horticulture Irrigated seasonal horticulture 28.48 0.31 Irrigated seasonal horticulture Irrigated seasonal vegetables & herbs 195.09 2.11


Water surfaces

Channel/aqueduct Drainage channel/aqueduct 8.21 0.09 Marsh/wetland Marsh/wetland 158.02 1.71 Reservoir/dam Reservoir/dam 12.49 0.14




Natural environment

Nature conservation National park 12.84 0.38 Other minimal use Other minimal use 196.42 5.81

Intensive uses

Manufacturing and industrial Manufacturing and industrial 1300.39 38.44 Manufacturing and industrial Oil refinery 368.83 10.90

Residential Rural living 8.79 0.26 Residential Urban residential 98.62 2.92


Transport and communication Airports/aerodromes 1.47 0.04

40

Transport and communication Ports and water transport 1.67 0.05 Transport and communication Railways 28.37 0.84 Transport and communication Roads 77.52 2.29 Transport and communication Transport and communication 21.08 0.62

Utilities Electricity substations & transmission 2.90 0.09 Waste treatment and disposal Sewage 30.56 0.90

Agricultural areas

Land in transition Land in transition 234.93 6.95 Plantation forestry Plantation forestry 3.12 0.09

Water surfaces

Channel/aqueduct Channel/aqueduct 0.58 0.02 Channel/aqueduct Drainage channel/aqueduct 21.10 0.62

Marsh/wetland Marsh/wetland 658.10 19.46 Marsh/wetland Marsh/wetland - conservation 0.10 0.00


41

Table S2 Pollutant loads in river sediments (mean values for the four seasons)

Sampling points TN (g/kg) TP

(g/kg)* TC (g/kg) 2-3-ringed

PAHs (µg/g)

4-ringed PAHs (µg/g)

5-6-ringed PAHs (µg/g)

Marine metals (mg/g)

Soil metals (mg/g)

Anthropogenic activities metals

(µg/g)

SP1 0.74±0.41 3.33±0.67 10.68±7.25 0.34±0.10 0.10±0.03 0.15±0.10 373.60±79.53 166.13±6.35 365.89±108.34 SP2 1.30±0.17 3.80±0.70 18.71±3.01 0.37±0.10 0.31±0.13 0.46±0.18 410.52±118.32 194.90±81.36 384.89±78.62 SP3 1.35±0.50 3.54±0.46 18.71±6.33 0.36±0.11 0.34±0.21 0.92±1.07 316.06±54.70 154.65±17.91 261.31±29.77 SP4 1.01±0.53 3.91±0.41 13.64±6.03 0.36±0.15 0.25±0.19 0.40±0.32 476.37±189.05 190.05±71.45 306.03±128.76 SP5 1.09±0.64 3.95±0.35 13.25±7.61 0.37±0.11 0.26±0.10 0.40±0.08 403.28±167.18 186.89±50.92 281.78±41.24 SP6 0.98±0.64 2.42±2.42 12.61±6.99 0.31±0.17 0.45±0.32 0.62±0.42 502.11±263.00 183.97±55.33 400.02±46.37 SP7 1.64±0.17 4.26±0.85 21.64±1.41 0.47±0.20 0.34±0.18 0.69±0.10 281.64±29.59 157.93±7.33 305.23±78.39 SP8 1.67±0.16 4.68±0.93 20.48±1.40 0.55±0.20 0.54±0.23 0.94±0.41 299.99±29.36 193.02±20.35 359.33±47.57 SP9 1.37±0.19 2.93±2.93 17.15±2.25 0.35±0.19 0.33±0.27 0.50±0.30 263.95±26.98 152.96±10.72 262.98±1.23 SP10 1.38±0.33 4.81±0.69 19.30±4.82 0.59±0.24 0.67±0.49 1.18±0.66 284.58±44.84 159.22±11.64 295.31±49.62 SP11 1.60±0.24 4.13±0.80 22.13±1.76 0.52±0.19 0.79±0.36 1.42±0.82 270.81±28.48 145.95±11.38 296.58±42.51 SP12 1.38±0.14 4.06±0.95 19.10±1.83 0.27±0.14 0.51±0.23 1.67±1.30 285.13±26.73 146.67±19.87 303.41±87.58 SP13 1.56±0.26 3.39±0.29 19.60±2.32 0.39±0.25 0.62±0.25 0.71±0.33 244.83±14.97 137.13±6.83 370.88±69.76 SP14 1.60±0.21 2.66±0.06 26.66±6.99 0.47±0.42 1.28±1.17 1.23±1.26 258.88±8.46 129.63±9.37 277.39±49.54 SP15 1.00±0.06 2.52±0.07 22.89±5.92 0.99±0.30 2.67±0.92 1.87±0.92 338.83±22.72 153.49±12.59 433.84±166.26 SP16 0.99±0.56 2.45±0.25 16.92±9.37 0.75±0.37 1.91±0.98 1.11±0.61 284.81±95.42 132.75±17.06 459.54±239.94

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SP17 1.56±0.08 3.45±0.18 21.93±3.41 0.67±0.22 1.17±0.50 1.13±0.33 263.38±45.97 149.29±19.20 343.64±66.96 SP18 1.58±0.08 2.97±0.01 21.53±1.03 0.57±0.34 1.19±0.63 1.06±0.57 244.61±5.10 130.55±7.83 316.64±25.06 SP19 1.24±0.07 2.50±0.17 18.01±1.68 0.49±0.30 0.66±0.32 0.53±0.21 245.82±58.73 133.43±14.48 253.02±14.08 SP20 1.43±0.33 2.16±0.38 34.06±11.97 0.42±0.13 1.13±0.54 0.54±0.26 323.04±25.34 154.88±25.98 331.98±49.47 SP21 1.35±0.22 3.69±0.66 16.74±2.56 0.39±0.15 0.32±0.11 0.39±0.13 268.62±13.92 154.09±26.65 242.01±44.27 SP22 0.44±0.26 1.88±0.61 6.04±5.45 0.32±0.17 0.25±0.30 0.27±0.37 686.17±376.95 165.84±44.38 215.12±36.84

*Data for TP are the mean values of winter and spring only due to equipment failure

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Table S3 Mineralogy data (%)

Sampling points Quartz Albite Microcline Kaolinite Muscovite Amorphous SP1 41.61 3.18 0.94 4.02 4.38 8.76 SP2 25.77 2.25 1.4 9.09 6.63 7.1 SP3 25.69 2.42 1.31 8.29 5.89 8.4 SP4 29.98 1.93 1.65 8.63 6.8 12.46 SP5 26.6 1.33 1.46 8.68 5.72 14.89 SP6 22.73 1.38 0.18 6.76 5.51 9.32 SP7 16.01 2.02 1.77 11.34 7.29 6.42 SP8 11.84 1.29 1.58 12.15 7.57 5.85 SP9 8.96 1.12 1.2 9.8 6.06 2.8 SP10 17.17 1.86 1.73 11 7.3 3.45 SP11 14.53 2.03 1.46 11.93 7.3 9.62 SP12 15.42 2.09 1.6 11.61 7.39 8.28 SP13 13.62 1.98 1.59 11.99 7.35 5.24 SP14 19.76 2.52 2.11 8.75 6.78 9.95 SP15 27.46 2.53 2.65 5.44 4.76 9.07 SP16 29.13 2.24 2.01 6.46 5.24 7.95 SP17 14.48 2.29 1.34 10.28 7.13 4.91 SP18 13.52 1.72 0.97 11.16 7.23 6.88 SP19 18.18 2.24 1.69 9.5 7.61 5.58 SP20 20.21 2.47 1.64 7.58 6.16 14.51 SP21 18.54 1.49 1.1 9.4 7.67 10.1 SP22 40.18 3.28 2.51 2.44 3.32 10.05

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Table S4 Data on configurations within the primary land use types

Sampling points

Natural environment (NAE) Intensive urban use (INU) Agricultural land (AGR) Water surfaces (WAS) SHDI PD LPI SHDI PD LPI SHDI PD LPI SHDI PD LPI

SP1 0.59 0.23 15.24 0.73 0.18 47.35 0.34 0.36 14.27 0.09 0.99 2.22

SP2 0.44 0.03 4.45 0.37 0.19 2.80 0.63 0.01 69.09 0.06 0.18 0.79

SP3 0.73 0.16 33.94 0.83 1.05 12.36 0.41 0.23 23.44 0.05 3.60 0.68

SP4 0.75 0.13 28.39 0.80 0.89 14.14 0.45 0.17 23.53 0.05 3.41 0.52

SP5 0.78 0.08 14.57 0.96 0.27 17.94 0.48 0.15 25.54 0.04 4.71 0.21

SP6 0.72 0.06 18.96 1.18 0.19 19.69 0.43 0.19 17.55 0.06 1.87 0.69

SP7 0.76 0.13 21.34 0.78 0.18 48.91 0.08 3.43 0.81 0.02 13.80 0.17

SP8 0.11 8.93 2.98 0.88 0.83 71.47 0.00 0.00 0.00 0.01 85.47 0.16

SP9 0.55 0.30 11.21 0.61 0.18 64.38 0.09 1.93 2.36 0.02 14.75 0.18

SP10 0.19 3.68 1.42 1.37 0.53 54.40 0.06 5.58 1.23 0.01 22.52 0.17

SP11 0.84 0.07 23.46 0.84 0.27 29.38 0.04 4.52 0.31 0.05 4.32 0.60

SP12 0.52 0.23 7.39 1.75 0.27 32.95 0.13 1.92 1.12 0.11 1.83 1.27

SP13 0.78 0.08 18.17 1.18 0.19 25.66 0.04 4.33 0.23 0.04 3.81 0.43

SP14 0.87 0.06 27.60 0.74 0.31 28.76 0.04 5.51 0.36 0.05 4.67 0.68

SP15 0.15 4.68 3.01 1.34 0.71 52.26 0.02 21.55 0.29 0.01 133.33 0.09

SP16 0.20 1.70 3.96 1.29 0.30 56.85 0.03 4.06 0.57 0.01 26.35 0.09

SP17 0.13 4.02 2.34 0.89 0.44 72.62 0.00 0.00 0.00 0.05 9.39 0.64

SP18 0.75 0.10 32.84 1.02 0.37 23.71 0.02 3.97 0.29 0.07 2.48 0.70

SP19 0.39 0.21 4.87 1.61 0.25 39.57 0.15 2.07 1.67 0.10 1.60 1.56

45

SP20 0.40 0.25 6.11 1.64 0.28 37.42 0.17 2.30 2.11 0.10 1.93 1.71

SP21 0.19 0.96 5.81 1.14 0.71 38.44 0.19 0.84 6.95 0.48 0.62 19.46

SP22 0.52 1.24 13.72 1.05 0.41 37.67 0.18 3.01 9.13 0.07 16.27 1.57

46

Approach to extracting land use configuration data The approach for extracting the three land use configuration data is shown for Natural Environment land use (NAE) in SP1 (see Table S1) as an example, while the same approach was applied for other land use types. It is noted that NAE in SP1 includes five tertiary land use types (managed resource protection, natural feature protection, other conserved area, other minimal use and residual native cover), which were seen as the five land patches. In addition, the area of each land patch is given in Table S1 as well. These were used for calculating the three land use configuration parameters.

Shannon’s Diversity Index (SHDI)

The SHDI parameter was calculated using Eq. S1. As shown in Table S1, NAE in SP1 includes five land patches and their areas are given as well. Therefore, the proportion of each land patch area accounting for the total area of the primary land use (NAE in the case) can be calculated (Pi in Eq. S1). Then, SHDI for NAE in SP1 was calculated using Eq. S1. Since there were five land patches, m in Eq. S1 equals five.

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 = −∑ (𝑝𝑝𝑖𝑖𝐿𝐿𝐿𝐿𝑝𝑝𝑖𝑖)𝑚𝑚𝑖𝑖=1 Eq. S1

Where

pi =proportion of the land patch accounting for the total area of the primary land use type;

m=number of land patches within the primary land use type

Patch density (PD)

PD indicates the number of patches per unit area (number per 100 ha). The calculation method is given in Eq. S2. As evident in Table S1, there are five land patches included in NAE of SP1. This means that N in Eq.S2 equals five. Then, the total area of NAE (A in Eq. S2) in SP1 was calculated. Finally, PD for NAE in SP1 was obtained using Eq. S2.

𝑃𝑃𝑆𝑆 = 𝑁𝑁𝐴𝐴/100

Eq. S2

Where

N=total number of land patches in a primary land use type

A=total area of the primary land use type (ha)

Largest patch index (LPI)

LPI was obtained by the area of the largest patch divided by total land use area. The calculation method is given in Eq. S3. The largest land patch in NAE of SP1 was the residual native cover, which occupies 1350.07 ha. Therefore, the LPI for NAE of SP1 was obtained using the total area of NAE (A in Eq. S3) dividing by the area of residual native cover (Amax in Eq. S3).

𝐿𝐿𝑃𝑃𝑆𝑆 = 𝐴𝐴𝑚𝑚𝑚𝑚𝑚𝑚𝐴𝐴

Eq. S3

Where:

47

Amax=the area of the largest land patch in a primary land use type (ha)

A= total area of the primary land use type (ha)

Laboratory testing

Nutrients and carbon Nutrients (TN and TP) were tested using SmartChem 140 discrete analyser, which is a colorimetric instrument. Matrix blank and matrix spiked samples together with a standard solution (for quality control) were analysed as samples to check for accuracy, precision and recovery. The test methods for TN and TP were Method 4500 in the Standards Methods for Water and Waste Water (APHA 2005).

Total carbon (TC) was tested using the Shimadzu TOC-5000A total organic carbon analyser. All sample were analysed along with matrix blank and matrix spiked samples to check for accuracy. TC was tested using Method 3510B in the Standards Methods for Water and Wastewater (APHA 2005).

Metals Details of sample preparation and analysis as well as the analytical performance of the method has been published elsewhere (Duodu et al., 2015). A minor change was the use of 10 Hz laser pulse frequency instead of 8 Hz to enhance count rates and precision. In brief, about 40 mg of germanium (IV) oxide was added to a known mass of sediment samples such that the mass of Ge ~ 1%. The mixture was milled and homogenized using a vibratory McCrone Micronizing mill after the addition of ethanol. The resulting slurry was completely dried in a sealed oven at 40 °C in a petri dish for about 5 h and 1 g of the dried homogenized sediment pressed into a pellet of about 12 mm diameter and 2 mm thickness using SPECAC Manual Hydraulic Press (Duodu et al., 2016; Duodu et al., 2015).

A 193 nm ArF excimer laser ablation system (Electro Scientific Industries, New Wave Research Division, Tokyo, Japan) coupled to an Agilent 8800 Triple Quad ICP-MS (Agilent Technologies Australia Pty Ltd) were used for the measurements. All instrument parameters are summarized in Duodu et al. (2015). The data acquired were subsequently processed with Igor Pro version 6.34 coupled to Iolite 2.5 software using external calibration with GBW07312, MESS-3 and STSD-1, and Ge as internal standard. Before measurements, the ICP-MS was calibrated to low oxide production rates (ThO+/Th+ < 0.5%, using NIST 610, and 612), and was monitored throughout batch acquisition. All data were background corrected and four replicate measurements were taken for each sample. For quality control, randomly selected duplicate samples, field blanks and CRM PACS-2 were analysed along with the samples during the analysis procedure (Duodu et al., 2016; Duodu et al., 2015).

PAHs A combined single extraction and clean-up step was employed for the extraction of PAHs from freeze dried samples using a Dionex accelerated solvent extractor (ASE 300) system (Thermo Fisher Scientific Australia Pty Ltd). Each sample was spiked with surrogate standard before extraction to check extraction efficiency. For recovery, sea sand (solid

48

blank) was spiked with PAH Mix standard and treated as a sample. The method was validated by extracting the PAH content of organics in marine sediments certified reference material, SRM 1941b. Similarly, accuracy and precision were evaluated by matrix spikes. Matrix blanks were prepared in a similar manner (with sea sand), but without spiking. The method detection limit (MDL) of the PAHs were determined as 3.1 times the standard deviation of fortified sea sand with QTM PAH Mix standard solution each, with a 2 g (dry weight) sample. Details of the method and analytical performance of the method has been published in Duodu et al. (2017). References

American Public Health, A., Eaton, A. D., American Water Works, A., & Water Environment, F. (2005). Standard methods for the examination of water and wastewater. Washington, D.C.: APHA-AWWA-WEF.

DSITIA, 2014. Land Use Summary 1999-2013: Brisbane River Sub-Catchment.Department of Science, Information Technology, Innovation and the Arts,Queensland Government (Retrieved 28 September 2016) https://publications.qld.gov.au/storage/f/2014-07 14T07%3A51%3A33.011Z/brisbane-land-use-web.pdf.

Duodu, G.O., Goonetilleke, A., Allen, C., Ayoko, G.A., 2015. Determination of refractive and volatile elements in sediment using laser ablation inductively coupled plasma mass spectrometry. Analytica Chimica Acta 898, 19-27.

Duodu, G.O., Goonetilleke, A., Ayoko, G.A., 2016. Comparison of pollution indices for the assessment of heavy metal in Brisbane River sediment. Environmental Pollution 219, 1077-1091.

Duodu, G.O., Ogogo, K.N., Mummullage, S., Harden, F., Goonetilleke, A., Ayoko, G.A., 2017. Source apportionment and risk assessment of PAHs in Brisbane River sediment, Australia. Ecological Indicators 73, 784-799.

Gunawardana, C., Goonetilleke, A., Egodawatta, P., Dawes, L.A., Kokot, S., 2012. Source characterisation of road dust based on chemical and mineralogical composition. Chemosphere 87, 163-170.

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