Spatial optimization of the water quality monitoring network in São Paulo State (Brazil) to improve sampling efficiency and reduce bias in a developing sub-tropical region.

Water quality monitoring networks (WQMNs) are essential to provide good data for management decisions. Nevertheless, some WQMNs may not appropriately reflect the conditions of the water bodies and their temporal/spatial dimensions, more particularly in developing countries. Also, some WQMNs may use more resources to attain management goals than necessary and can be improved. Here we analyzed the São Paulo State (Brazil) WQMN design in order to evaluate and increase its spatial representativeness based on cluster analysis and stratified sampling strategy focused on clear monitoring goals. We selected water resources management units (UGRHIs) representative of contrasting land uses in the state, with bimonthly data from 2004 to 2018 in 160 river/stream sites. Cluster analysis indicated monitoring site redundancy above 20% in most of the UGRHIs. We identified heterogeneous spatial strata based on land use, hydrological, and geological features through a stratified sampling strategy. We identified that monitoring sites overrepresented more impacted areas. Thus, the network is biased against determination of baseline conditions and towards highly modified aquatic systems. Our proposed spatial strategy suggested the reduction of the number of sites up to 12% in the UGRHIs with the highest population densities, while others would need expansions based on their environmental heterogeneity. The final densities ranged from 1.6 to 13.4 sites/1,000km. Our results illustrate a successful approach to be considered in the São Paulo WQMN strategy, as well as providing a methodology that can be broadly applied in other developing countries.