Sampling frequency optimization of the water quality monitoring network in São Paulo State (Brazil) towards adaptive monitoring in a developing country

Water quality monitoring networks (WQMNs) that capture both the temporal and spatial dimensions are essential to provide reliable data for assessing water quality trends in surface waters, as well as for supporting initiatives to control anthropogenic activities. Meeting these monitoring goals as efficiently as possible is crucial, especially in developing countries where the financial resources are limited and the water quality degradation is accelerating. Here, we asked if sampling frequency could be reduced while maintaining the same degree of information as with bimonthly sampling in the São Paulo State (Brazil) WQMN. For this purpose, we considered data from 2004 to 2018 for 56 monitoring sites distributed into four out of 22 of the state's water resources management units (UGRHIs, "Unidades de Gerenciamento de Recursos Hídricos"). We ran statistical tests for identifying data redundancy among two-month periods in the dry and wet seasons, followed by objective criteria to develop a sampling frequency recommendation. Our results showed that the reduction would be feasible in three UGRHIs, with the number of annual samplings ranging from two to four (instead of the original six). In both seasons, dissolved oxygen and Escherichia coli required more frequent sampling than the other analyzed parameters to adequately capture variability. The recommendation was compatible with flexible monitoring strategies observed in well-structured WQMNs worldwide, since the suggested sampling frequencies were not the same for all UGRHIs. Our approach can contribute to establishing a methodology to reevaluate WQMNs, potentially resulting in less costly and more adaptive strategies in São Paulo State and other developing areas with similar challenges.

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/1,000km². 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.

Native forest cover safeguards stream water quality under a changing climate

Ensuring a sufficient and adequate supply of water for humans and ecosystems is a pressing environmental challenge. The expansion of agricultural and urban lands has jeopardized watershed ecosystem services and a changing climate poses additional risks for regional water supply. We used stream water quality data collected between 2000 and 2014, coupled with detailed precipitation and land cover information, to investigate the effects of landscape composition and short-term precipitation variability on the quality of water resources in the state of São Paulo, Brazil. The state is home to over 45 million people and has a long history of human landscape modification. A severe drought in 2014-2015 led to a major water crisis and highlighted the fragility of the regional water supply system. We found that human-dominated watersheds had lower overall water quality when compared to forested watersheds, with urban cover showing the most detrimental impacts on water quality. Forest cover was associated with a better overall water quality across the studied watersheds, with forested watersheds having low turbidity and high dissolved oxygen. High precipitation led to increased turbidity and fecal coliforms levels and lower dissolved oxygen in streams but these effects depended on watershed land cover. High precipitation diluted concentrations of nitrogen and dissolved solids in highly urbanized watersheds but exacerbated turbidity in pasture-dominated watersheds. Given the high costs of water treatment in densely populated regions, there is a pressing need to plan and manage landscapes in order to ensure adequate water resources. In tropical regions, maintaining or restoring native vegetation cover is a promising intervention to sustain adequate water quality.

Anaerobic treatment of blended sugar industry and ethanol distillery wastewater through biphasic high rate reactor

This study aimed to investigate the physicochemical properties of sugar industry and ethanol distillery wastewater and the treatment of the blended wastewater through a two-stage anaerobic reactor. For this treatment, different initial chemical oxygen demand (COD) concentrations (5-20 g/L) and hydraulic retention times (HRTs) (2-10 days) were applied. The sugar industry effluent characteristics obtained in terms of organic matter (mg/L) were as follows: 5 days biochemical oxygen demand (BOD₅): 654.5-1,968; COD: 1,100-2,148.9; total solids (TS): 2,467-4,012 mg/L; and pH: 6.93-8.43. The ethanol distillery spent wash strengths obtained were: BOD₅: 27,600-42,921 mg/L; COD: 126,000-167,534 mg/L; TS: 140,160-170,000 mg/L; and pH: 3.9-4.2. Maximum COD removal of 65% was obtained at optimum condition (initial COD concentration of 10 g/L and HRT of 10 days), and maximum color removal of 79% was recorded under similar treatment conditions. Hence, the performance of the two-stage anaerobic reactor for simultaneous removal of COD and color from high-strength blended wastewater is promising for scaling up in order to mitigate environmental problems of untreated effluent discharge.