The Impact of Metal Mining on Global Water Stress and Regional Carrying Capacities—A GIS-Based Water Impact Assessment
2. Materials and Methods
2.1. Water Footprint Assessment
2.2. Water Stress and Water Scarcity Determination
- 0–1: ‘low’ water stress (<10%). The overall water consumption within a given area is lower than 10% of natural runoff. If taking into account EWR, runoff is defined as WA minus EWR, which is not or is slightly affected by water consumption.
- 1–2: ‘low–medium’ water stress (10–20%). Total water consumption is rated between 10 and 20% of natural runoff minus EWR, which is affected moderately.
- 2–3: ‘medium–high’ water stress (20–40%). Total water consumption is rated between 20 and 40% of natural runoff minus EWR, which is expected to be modified significantly.
- 3–4: ‘high’ water stress (40–80%). Total water consumption is rated between 40 and 80% of natural runoff minus EWR, which is seriously affected and modified.
- 4–5: ‘extremely high’ water stress (>80%). The basin’s overall water consumption exceeds 80% of natural runoff minus EWR, violating the environmental water needs in case of exceeding water availability by 100% (= EWR-related threshold). As many mining operations are located in remote areas which are arid but simultaneously characterized by low water use, thus having less competition amongst water users, these areas are not comparable to the regular definition of WSI. Nevertheless, mining operations have to be aware of localized impacts, particularly with respect to environmental water needs . As a consequence, this category includes ‘arid and low water use’, differing from the established water stress definition but assuming that environmental water needs are violated regardless of the amount of water used.
2.3. Mining Data and System Boundaries Applied for a Water Impact Assessment
- Geographic coordinates and individual mine-site production data of a time period between 2010 and 2018 for 2783 mining operations producing preprocessed ores or concentrates of bauxite, cobalt, copper, iron ore, lead, manganese, molybdenum, silver, U3O8 (uranium concentrate or yellow cake) and zinc as well as the refined metals gold, nickel, palladium and platinum. In addition, 13,817 exploration projects and 11,500 development projects of all 14 commodities were also considered.
- Specific water consumption volumes per t mining commodity based on a comprehensive review of LCA databases as well as recent studies on water footprints in the mining sector (shown in Table 2 and Table 3) and annual water consumption volumes of each individual mining operation according to LCA calculations and mine-site production volumes.
- Water stress index (WSI) at the sub-basin level according to Gassert et al. , obtained from the Aqueduct Project, and WSI at the major river basin level as defined by the Global Runoff Data Centre (GRDC) . In total, water stress of approximately 25,000 basin units, representing ~15,000 sub-basins and 405 major river basins according to the GRDC, was implemented.
- Based on calculations by Luck et al. , estimated changes in water stress by 2030 and 2040 and projected water stress in 2030 and 2040 at the sub-basin level were implemented in the GIS considering three IPCC climate change scenarios (RCP4.5/SSP2, RCP8.5/SSP2 and RCP8.5/SSP3) to derive estimations of the water stress that mining operations may be confronted with in the next two decades.
2.4. Water Consumption in Mining and Refining of Metal Raw Materials
|Processing Stage of the Mining Commodity||Minimum Range|
|Averaged Water Consumption|
(in m3/t Metal Commodity)
|Global Water Consumption|
|Reviewed Data Sources Providing LCA-Based Inventory Data on Specific Water Consumption Values per t Metal Commodity|
|Ore and Metal Concentrate|
|Preprocessed ore||0.320–0.395 ||0.447–0.578 [23,86,87]||0.447||88.9 1|
|International Aluminium Institute ;|
Frischknecht et al. (Ecoinvent, bauxite, at mine, GLO #1063) ;
Buxmann et al. 
Dai et al. ;
Shahjadi et al. ;
40.000 –42.403 
Northey et al. ;
Frischknecht et al. (copper concentrate at beneficiation) ;
Shahjadi et al. ;
Pena and Huijbregts (incl. SX-EW) 
|Fines||0.210–0.874 [26,27,92,93]||1.519 –|
|Ferreira et al. ;|
Frischknecht et al. (Fe at beneficiation, GLO #1100) ;
Haque and Norgate ;
Tost et al. 
Frischknecht et al. (lead concentrate at beneficiation, GLO #1104) ;
Shahjadi et al. ;
|Concentrate||1.390 ||1.418 ||1.404||62.7 1|
|Frischknecht et al. (manganese concentrate at beneficiation, GLO #1110) ;|
Fritsche (2005) (manganese concentrate, GLO 2003–2004) 
|Concentrate||52.2–209.6 ||382.0 –|
Frischknecht et al. (molybdenum concentrate, GLO #1117, RER #5858, RAS #5859) 
|Ore and Metal Concentrate|
|Concentrate||1621–1805 [27,89,90]||3128 ||1713||41.1 1|
Shahjadi et al. ;
Fritsche (Xtra-silver concentrate) 
|Concentrate (U3O8)||46.20–100.00 [11,86,94];|
|6000–8207 [11,86,94]||2746||17.1 1|
Frischknecht et al. (uranium oxide RNA #5988, RNA #5989) ;
Fritsche (uranium oxide) ;
Mudd et al. 
|24.65 ||11.93||114.2 1|
Frischknecht et al. (zinc concentrate at beneficiation, GLO #1157, SE #10099) ;
Shahjadi et al. 
288,140 ; 309,110 –
347,910 ; 392,686 –
427,696 ; 453,305 –
Frischknecht et al. (gold at refinery #10110-14) ;
Tost et al. ;
Norgate and Haque ;
Frischknecht et al. (primary nickel, GLO #35, GLO #1121, ZA #1124, RU #1125) 
|273,523–327,874 [86,90]||210,713||45.8 1|
Frischknecht et al. (primary at refinery, ZA #1128, RU #1129) ;
Fritsche (primary at refinery, ZA, RU) 
|Metal||169,968–200,000 [27,86,90]||406,998–487,876 [27,86,90]||313,496||67.3 1|
Frischknecht et al. (primary at refinery, ZA #1134, RU #1135) ;
Fritsche (primary at refinery, ZA, RU) 
3.1. Mining-Related Water Stress and Global Water Scarcity Impact
|Mining Commodity||Global Production in 2018 (in t)|
(Except Bauxite in 2016)
|Global Production Share|
(in Percent) (According to USGS )
|Number of Mining Sites Considered|
|Averaged Water Consumption Factor|
|Global Water Consumption in 2018|
(=Water Consumption Multiplied with Regional WSI)
(=Global WSFP Divided by Number of Mining Properties)
3.2. Mining’s Influence on Regional Water Stress and Carrying Capacities
- Loa Basin (Figure 4a, basin no. 319), located in the northern part of the Antofagasta region in Chile, is one of the world’s leading copper-mining areas, hosting 7.9% of global copper and 8.2% of global molybdenum production (according to production in 2018). Mining alone is the main driving factor causing the ‘extremely high’ water stress due to exceeding the available water limits during the entire year as a result of hyper-arid conditions simultaneously paired with the highest rates of water consumption in the mining sector. Owing to the fact that copper mining is ranked as one of the largest water-consuming sectors in the global mining industry, many large-scale production capacities are primarily located in Chile, therefore resulting in intense water scarcity impacts in the Chilean Loa Basin. As a consequence, the total annual water scarcity impact caused by mining operations in Loa Basin accounts for 368.17 Mm3, of which 338.3 Mm3 is associated with copper mining, which represents 14.5% of the global copper-related water scarcity effect. Another large water scarcity impact of 22.5 Mm3 results from molybdenum mining, which is often jointly performed with copper production.
- Similar to Loa Basin, the Pilbara region in northwestern Australia is also characterized by high water scarcity impacts due to large-scale mining under arid conditions. Pilbara comprises three river basins, namely De Grey River (Figure 4a, basin no. 321), Fortescue (basin no. 323) and Ashburton (basin no. 327), altogether providing 53.3% of the global iron ore fine supply—i.e., the overall results in Pilbara are significantly influenced by iron ore mining. However, the percentage of water consumption for mining in Pilbara varies significantly between the basins. For instance, while mining’s influence on the basin’s water stress in De Grey River is basically low (usually below 10% of the basin’s total water consumption per month), its contribution to the overall water stress in Ashburton is slightly above 10% in the period from January to March but exceeds the EWR limits significantly from September to October, thus causing a range of ‘low–medium’ to ‘extremely high’ water stress throughout the year. By contrast, in Fortescue River Basin, mining alone is responsible for the ‘extremely high’ water stress during most of the year, particularly surpassing EWR thresholds from April to December. Overall, as the production of iron ore fines is responsible for the largest global water consumption amongst all mining commodities observed in this study, Pilbara is, after Loa Basin, the most prominent area affected by high mining-related water stress as well as a water scarcity impact accounting for 1039.91 Mm3 in total. This represents roughly 55% of the global water scarcity effect resulting from iron ore mining, particularly regarding iron ore fines.
- Orange Basin (Figure 4a, basin no. 326) and Limpopo Basin (basin no. 320) are further prominent examples of river catchments affected by high water stress and water scarcity effects caused by the mining industry. Both basins are located in South Africa, covering areas of the Republic of South Africa, Lesotho, Namibia, Botswana, Zimbabwe and Mozambique. While Limpopo Basin supplied 68.3% (146.7 t) of global platinum and 36.9% (80.3 t) of palladium production in 2018, mining operations situated in Orange Basin contributed to 4.3% (114.4 t) of global gold production, which is the largest gold production capacity in the basins observed. However, even relatively low quantities of metal production for gold or platinum group metals, for example, may cause high water stress and water scarcity impacts, particularly due to the relatively high specific water demand per t refined metal. Consequently, both basins are highly influenced by water consumption for the precious metals mining and refining industry. Overall, this mining sector is mostly responsible for ‘low’ water stress in both basins, primarily averaging between 5 and 9% from June and December and peaking at 13.5% in November, which is classified as ‘low–medium’ water stress. Besides gold and PGM production, mining of copper, iron ore and manganese also has a significant influence on the hydrological system of both basins. Manganese production in Orange Basin represents 35.6% of global manganese production, resulting in a global water scarcity footprint (WSFP) of 74.4% for manganese mining. While the total WSFP of mining in Orange Basin is 270 Mm3, the annual mining-related WSFP in Limpopo Basin is estimated to be 256 Mm3, mainly caused by the mining and refining of platinum group metals. For instance, palladium production in Limpopo accounts for 72.6% of the global palladium WSFP and platinum production accounts for approximately 81% of the global platinum WSFP.
4. Discussion and Conclusions
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
|BWS||Baseline water stress|
|EFR||Environmental flow requirement|
|EWR||Environmental water requirement|
|GIS||Geographic information system|
|GRDC||Global Runoff Data Centre|
|ISO||International Organization for Standardization|
|LCA||Life cycle assessment|
|MAR||Mean annual runoff|
|RCP||Representative concentration pathway|
|SDG||Sustainable development goal|
|SSP||Shared socioeconomic pathway|
|WSFP||Water scarcity footprint|
|WSI||Water stress index|
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|Annual Flow (km3a−1) and|
Percentage of Natural Flow (%)
to Be Preserved as EWR
|Sustainable Groundwater Abstraction (km3a−1) and Percentage of Natural Recharge (%)|
|Asia||10,178.2 (57.0)||110.3 (3.4)|
|North America||3656.3 (55.2)||30.3 (1.9)|
|Europe||1489.7 (52.8)||20.0 (1.7)|
|Africa||5032.1 (70.2)||14.3 (0.7)|
|South America||11,242.9 (73.4)||24.0 (0.6)|
|Oceania||240.4 (35.1)||2.6 (1.0)|
|Australia||251.0 (48.4)||1.9 (1.3)|
|Global||32,090.6 (63.0)||203.3 (1.6)|
|Water Scarcity Impact|
|Water Consumption/Water Scarcity Ratio||Most Relevant Mining|
(in Terms of Production Volumes)
|Fortescue River (Australia)||No. 323||522.7||<1.0 1||>500:1||Iron ore|
|Tocantins (Brazil)||No. 273||259.9||<1.0||~260:1||Iron ore|
|Ashburton River (Australia)||No. 327||208.0||1040.0||~1:5||Iron ore|
|Sao Francisco (Brazil)||No. 290||166.0||63.2||2.6:1||Iron ore|
|Orange (South Africa)||No. 326||87.5||270.6||1:3.1||Gold, iron ore, manganese|
|Amazonas (Brazil)||No. 259||85.6||71.2||1:0.8||Copper, gold, bauxite, zinc, silver|
|Limpopo (South Africa)||No. 320||76.8||256.0||1:3.3||Platinum, palladium, nickel, gold, copper|
|Loa (Chile)||No. 319||73.6||270.6||1:3.7||Copper, molybdenum, silver|
|Congo (Central Africa)||No. 243||69.1||<1.0||~70:1||Copper, cobalt, gold|
|St. Lawrence (USA, Canada)||No. 117||62.5||<1.0||~100:1||Nickel, cobalt, copper, gold|
|Zambezi (Central Africa)||No. 293||57.5||1.4||~40:1||Copper, nickel|
(Ukraine, Belarus, Russia)
|No. 96||55.3||114.8||1:2.1||Iron ore|
|Ob (Russia)||No. 25||46.2||132.0||1:2.9||Gold, copper, zinc, iron ore, bauxite, lead, silver, uranium|
|Colorado River (USA, Mexico)||No. 138||43.9||192.5||1:4.4||Copper, molybdenum, gold|
|Huang He (Yellow River) (China)||No. 149||43.1||200.8||1:4.7||Nickel, molybdenum, gold, copper, zinc|
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Meißner, S. The Impact of Metal Mining on Global Water Stress and Regional Carrying Capacities—A GIS-Based Water Impact Assessment. Resources 2021, 10, 120. https://doi.org/10.3390/resources10120120
Meißner S. The Impact of Metal Mining on Global Water Stress and Regional Carrying Capacities—A GIS-Based Water Impact Assessment. Resources. 2021; 10(12):120. https://doi.org/10.3390/resources10120120Chicago/Turabian Style
Meißner, Simon. 2021. "The Impact of Metal Mining on Global Water Stress and Regional Carrying Capacities—A GIS-Based Water Impact Assessment" Resources 10, no. 12: 120. https://doi.org/10.3390/resources10120120