Clean drinking water is a precious resource. It is the basis of our daily life and decides like no other substance about our health and well-being. It is therefore important to ensure that the water for everyday use meets the highest quality criteria. But what is meant by the term water quality and how can water quality be measured and compared? This question will be addressed and explained in more detail in the following sections.

While water is a molecule consisting of two hydrogen and one oxygen atom (H2O), the term "quality" is much broader: In philosophy, quality is equated with the attributes of an object (Honderich 2005)⁠, whereas in engineering, quality is seen as a property that makes a particular object suitable for a particular purpose (Phadke 1995)⁠. Pragmatically speaking, water quality can be defined on the one hand by its physical and chemical properties and on the other hand by the suitability of a water resource as a drinking water resource. Thus, water quality clearly describes the properties of water which, if adverse impacts on human health can be excluded, characterise the water as drinkable (WHO 1993)⁠. This results in the need to make water quality measurable, for example to determine the drinkability of water and the ecological status of water bodies. As water quality consequently comprises many different aspects, indicators are needed to capture these. In the course of assessing water quality, the chemical, biological, radiological and physical properties of water are compared with standards and guidelines (Bartram and Ballance 1996)⁠. These standards also specify how the measurements are to be carried out to ensure comparability and uniform measurement conditions (see also…).

Water Quality Policies

For example, in the "Directive on environmental quality standards in the field of water policy" (DIRECTIVE 2008/105/EC), the European Union defines a number of chemical substances that are considered priority pollutants and potential threats to “good water quality”. In general, the directive requires that the annual average concentration of certain substances in water bodies must not exceed legally prescribed limits and also regulates an upper limit for the maximum concentration of these substances. The regulation mainly concerns metals such as cadmium or mercury, residues of certain pesticides and a number of aromatic hydrocarbons. Similar regulations exist in the USA, where the United States Environmental Protection Agency (EPA) defines standards and test procedures for ninety different substances. These also include biological contaminants such as E-coli and salmonella. Against this background, the United Nations has also developed a number of strategies - e.g. the WHO Water Quality and Health Strategy 2013-2020 - and launched programmes - e.g. the UNESCO World Water Assessment Programme.

Water Quality Indicators

Water quality indicators thus cover aspects of the physical, chemical and biological (Liu, Islam, and Gao 2003)⁠ properties of water as Figure 1 shows:

Figure 1: Overview of water quality indicators
Figure 1: Overview of water quality indicators

The physical properties (Figure 1, upper left corner) refer to the water molecules themselves (temperature) and the chemical substances dissolved in the water (e.g. electric conductivity, viscosity). Since the reactivity of most chemical substances and their solubility depends on temperature, temperature is an important indicator. For example, the oxygen concentration decreases with rising temperatures, whereas the reaction rate of chemical reactions can accelerate, which has an impact on the ecological status of water bodies. In addition, sediments and other turbidity substances (such as organic material) change the optical properties of water and make it appear turbid and opaque at high concentrations (McCoy and Olson 1986)⁠.

The chemical properties (Figure 1, upper right corner) mainly refer to the substances dissolved in water (Benchea, Cretescu, and Macoveanu 2011)⁠. Important here is the pH value, which indicates how acidic or alkaline water is and also influences the chemical reactions and the ecological status. In addition, dissolved metals, salts and nitrogen-based compounds could have significant impacts on water quality. Pesticides and fertilizers can also be leached from the soil in agricultural areas and fed into watercourses, thus affecting water quality.

Biological indicators (Figure 1, lower left corner) refer in particular to the presence of certain micro-organisms such as bacteria, viruses and other microbes such as parasites (Yoder and Rankin 1998)⁠. At the same time, the presence or absence of certain animal and plant species may indicate the ecological status of a water body which is closely linked to water quality. For example, if water bodies are contaminated with toxic substances, or if the oxygen content is significantly reduced by algae blooms as a result of nutrient over-saturation, this can lead to a lasting disturbance of the ecological status and deterioration of water quality.

Last but not least, radioactive elements (Figure 1, lower right corner) such as uranium can be included in the radiological water quality indicators. Such elements can come from natural sources (weathering of rocks) as well as from anthropogenic processes (such as the usage of nuclear energy).

This -by far not complete overview – reveals the multi-dimensionality of water quality and the need to measure a broad range of different indicators. Some of them relate directly to a certain property of water (e.g. temperature) while other indicators only allow for indirect estimates of certain properties: For example, electric conductivity, that is a property of any material describing how well it conducts electric currents, refers to the amount of ions (i.e. atoms with a positive or negative electric charge) dissolved in the water. Moreover, the indicators have to be measured separately but have to be interpreted in a combined manner since they all relate to the overall quality of water. Ultimately, this means that there are many ways to measure and interpret water quality. It is essential that the selected indicators capture the dimensionality of the relevant aspect (e.g. heavy metal concentration), provide reliable results, allow a conclusive interpretation, are applicable and precisely defined.

Space Technologies for Assessing Water Quality

Space technologies can make important contributions to the identification of various water quality indicators on different temporal and spatial scales (Hadjimitsis et al. 2010)⁠, but not all indicators can be collected with the necessary accuracy. The advantage of space technologies is that they can cover larger areas in repeated time intervals and offer great potential for automation, which can reduce costs compared to laboratory analyses (Mumby et al. 1999)⁠. Especially optical remote sensing (see also provides valuable data that can be used for a number of water quality indicators. Optical remote sensing includes any kind of imaging systems that use visible light and near infra-red wavelength ranges to collect spectral information about the earth's surface. One example is the title image of the article, which shows an image of the environmental satellite Sentinel-2 (see also of Lake Mondsee in Austria as a so-called false-colour image. The water surface of the lake appears blue, whereas the surrounding land areas are coloured red, since vegetation in the infra-red reflects sunlight particularly strongly.

This means that optical remote sensing can detect those aspects of water quality that change the visual appearance of water bodies (Ritchie, Zimba, and Everitt 2003)⁠. A good example is turbidity, which indicates how clear water appears due to sediments and suspended solids: If turbidity is low, the water appears clear and is transparent when it is filled into glass containers. If the turbidity is high, however, the water no longer appears transparent and often takes on a grey to brownish colour, depending on the dissolved substances. Such a change is clearly visible to the human eye and can also be detected with an optical remote sensing sensor. However, in order to be able to convert the optical change in the appearance of the water into an actual quantity (e.g. suspended matter concentration per litre of water), it must be known how a change in the suspended matter content by a certain amount affects the spectral properties. For this reason, laboratory analyses and on-site measurements are also necessary when using space technologies in order to establish the relationship between water quality and optical properties. Such a relationship can be statistical, e.g. by simple regression calculation or by using physical laws. This is also called model generation and calibration. Of course, it must also be determined how accurately such a model can measure the respective water quality indicator (Nechad, Ruddick, and Park 2010; Dogliotti et al. 2015)⁠⁠. This is the process of model validation, which determines e.g. whether a particular model can replace laboratory measurements or whether the accuracy is too low to ensure a reliable determination of water quality.

On the other hand, the aforementioned conditions stipulate that not all of the listed indicators can be recorded by optical remote sensing. Therefore, optical remote sensing cannot provide estimates for all of the indicators listed in Figure 1. For example, a change in the oxygen content initially has no further effect on the optical properties of water and is therefore more complex to detect in optical imagery (Evrendilek and Karakaya 2015)⁠. The same applies to heavy metals and the pH value. Furthermore, water quality determination with optical remote sensing only works if the water is deep enough and the bottom is no longer visible. If the bottom is visible, it is not possible to separate which spectral information can actually be attributed to the water and which to the sediment and aquatic vegetation on the bottom.


In summary, water quality and its identification is an essential component for securing livelihoods and is therefore highlighted by legislation at national and multi-lateral level. In order to capture the different dimensions of water quality, indicators are indispensable, which in the best case are subject to a uniform measurement procedure laid down in standards and guidelines. It was shown that space technologies, and in particular optical remote sensing, are suitable for the acquisition of some water quality indicators, provided that calibration and validation data are available. This article gave a brief insight into these aspects, but does not claim to be exhaustive. For further information on the individual indicators and their measurements, please refer to the relevant (inter-) national standards and scientific publications (see Further Reading).

Further Reading


Bartram, Jamie, and Richard Ballance. 1996. Water Quality Monitoring. Taylor & Francis.

Benchea, Roxana Elena, Igor Cretescu, and Matei Macoveanu. 2011. “Monitoring of Water Quality Indicators for Improving Water Resources Management of Bahlui River.” Environmental Engineering & Management Journal (EEMJ) 10 (3).

Dogliotti, A I, K G Ruddick, B Nechad, D Doxaran, and E Knaeps. 2015. “A Single Algorithm to Retrieve Turbidity from Remotely-Sensed Data in All Coastal and Estuarine Waters.” Remote Sensing of Environment 156: 157–68.

Evrendilek, Fatih, and Nusret Karakaya. 2015. “Spatiotemporal Modeling of Saturated Dissolved Oxygen through Regressions after Wavelet Denoising of Remotely and Proximally Sensed Data.” Earth Science Informatics 8 (1): 247–54.

Hadjimitsis, Diofantos Glafkou, Marinos Glafkou Hadjimitsis, Leonidas Toulios, and Chris Clayton. 2010. “Use of Space Technology for Assisting Water Quality Assessment and Monitoring of Inland Water Bodies.” Physics and Chemistry of the Earth, Parts A/B/C 35 (1–2): 115–20.

Honderich, Ted. 2005. The Oxford Companion to Philosophy. OUP Oxford.

Liu, Yansui, Md Anisul Islam, and Jay Gao. 2003. “Quantification of Shallow Water Quality Parameters by Means of Remote Sensing.” Progress in Physical Geography 27 (1): 24–43.

McCoy, William F, and Betty H Olson. 1986. “Relationship among Turbidity, Particle Counts and Bacteriological Quality within Water Distribution Lines.” Water Research 20 (8): 1023–29.

Mumby, P J, E P Green, A J Edwards, and C D Clark. 1999. “The Cost-Effectiveness of Remote Sensing for Tropical Coastal Resources Assessment and Management.” Journal of Environmental Management 55 (3): 157–66.

Nechad, B, K G Ruddick, and Y Park. 2010. “Calibration and Validation of a Generic Multisensor Algorithm for Mapping of Total Suspended Matter in Turbid Waters.” Remote Sensing of Environment 114 (4): 854–66.

Phadke, Madhan Shridhar. 1995. Quality Engineering Using Robust Design. Prentice Hall PTR.

Ritchie, Jerry C, Paul V Zimba, and James H Everitt. 2003. “Remote Sensing Techniques to Assess Water Quality.” Photogrammetric Engineering & Remote Sensing 69 (6): 695–704.

WHO, World Health Organization. 1993. Guidelines for Drinking-Water Quality. World Health Organization.

Yoder, Chris O, and Edward T Rankin. 1998. “The Role of Biological Indicators in a State Water Quality Management Process.” Environmental Monitoring and Assessment 51 (1–2): 61–88.