Monitoring is paramount in environmental sciences since it provides necessary information on system behavior of environmental variables over time and space related to specified management objectives. Monitoring is also practiced to gain a deeper understanding of natural and anthropogenic processes within the environment.

However, monitoring can be a time and financial costly activity which needs to be carefully designed to attain already selected objectives to avoid what Ward et al. (1986) calls the "data rich- information poor" syndrome.

In the context of river basin management, environmental monitoring includes the measurement of all related variables such as climate (e.g. precipitation, temperature, humidity, solar radiation), hydrology (e.g. streamflow, snow cover, groundwater level), water quality (e.g. pH, temperature, nutrients), human activities (e.g. water abstractions, WWTP effluents). Moreover, socio-economic factors such as population, GDP, among others, also are relevant while observing a basin as a system. 

According to UNEP/WHO (1996) the general definition of monitoring can be differentiated into three types of activities that distinguish between long-term, short-term and continuous monitoring programs:

  • Monitoring is the long-term, standardized measurement and observation of the aquatic environment in order to define status and trends.  
  • Surveys have finite duration, intensive programs to measure and observe the quality of the aquatic environment for a specific purpose.  
  • Surveillance is continuous, specific measurement and observation for the purpose of water quality management and operational activities.

Monitoring should aim at representing the spatial and temporal variability of the parameters being analyzed while minimizing the costs. Especially in developing countries, financial constraints are a limiting factor which needs to be taken into consideration while designing a monitoring network.

The design of sound monitoring concept is not only necessary to understand the current status of water resources but, in the context of integrated water resources management (IWRM), a primordial tool to assess the impacts of measures or interventions to improve the environment. Therefore, paradigmatic water-related policies such as the Water Framework Directive (WFD, 2000) or the Clean Water Act (CWA, 1972) created legal frameworks to protect and improve the quality of water resources where monitoring programs played a central role in the decision making process.

As mentioned before, monitoring networks can be cost-intensive and difficult to maintain. Therefore, environmental time series often contain gaps which must be filled out using statistical tools (e.g. correlation, regression). Due to the financial and financial constraints, many regions in the world do not have enough data for the proper management of the environment. Therefore, methods have been developed to work in data-scarce regions but it still remains a challenge. Initiatives such as the Decade on Prediction in Ungauged Basins (PUB) launched by the International Association of Hydrological Sciences (IAHS) aimed at achieving major advances in the capacity to make predictions in ungauged basins underlying the importance of data and information stemming from monitoring programs. Nowadays, remote sensing is arising as an important tool to collect data worldwide in a cost-effective manner which can foster the sustainable management of water resources. 


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