Towards a long-term integrated monitoring programme in Europe: network design in theory and practice

Long-term integrated monitoring is an important approach forinvestigating, detecting and predicing the effects ofenvironmental changes. Currently, European freshwaters,glaciers, forests and other narural and semi-natural ecosystemsand habitats are monitored by a number of networks establishedby different organisations. However, many monitoring programmeshave a narrow focus (e.g. targeting individual ecosystems) andmost have different measurement protocols and sampling design.This has resulted in poor integration of ecosystem monitoring ata European level, leading to some overlapping of efforts and alack of harmonised data to inform policy decisions. The need fora consistent pan-European long-term integrated monitoring ofterrestrial systems programme is recognised in the scientificcommunity. However, the design of such a system can be problematic, not least because of the constraints imposed bythe need to make maximum use of existing sites and networks.Based on the outcomes of the NoLIMITS project (Networking ofLong-term Integrated Monitoring in Terrestrial Systems), thisarticle reviews issues that should be addressed in designing aprogramme based on existing monitoring sites and networks. Fourmajor design issues are considered: (i) users' requirements,(ii) the need to address multiple objectives, (iii) role ofexisting sites and (iv) operational aspects.     

A water quality monitoring network design methodology for the selection of critical sampling points: Part II

In order to resolve the spatial component of the design of a water quality monitoring network, a methodology has been developed to identify the critical sampling locations within a watershed. This methodology, called Critical Sampling Points (CSP), focuses on the contaminant total phosphorus (TP), and is applicable to small, predominantly agricultural-forested watersheds. The CSP methodology was translated into a model, called Water Quality Monitoring Station Analysis (WQMSA). It incorporates a geographic information system (GIS) for spatial analysis and data manipulation purposes, a hydrologic/water quality simulation model for estimating TP loads, and an artificial intelligence technology for improved input data representation. The model input data include a number of hydrologic, topographic, soils, vegetative, and land use factors. The model also includes an economic and logistics component. The validity of the CSP methodology was tested on a small experimental Pennsylvanian watershed, for which TP data from a number of single storm events were available for various sampling points within the watershed. A comparison of the ratios of observed to predicted TP loads between sampling points revealed that the model's results were promising.