Abstract

The valuation of ecosystem services of pollution regulation in basins with partial monitoring does not have only one consolidated methodology which can be applied in all countries, biomes and across spatio-temporal scales. While different metrics can incorporate elements of uncertainty for decision makers, changes in land use, climate and sectoral demands in basins increase the need for the efficiency and complexity of valuation methods. Here, based on adapting a pre-existing method, we present a new ecosystem service valuation applied to river basins under different characteristics in the biomes of the Atlantic Forest and Brazilian savannah. Our assumptions of ecosystem service valuation concern an analogy based on willingness-to-pay for not marketable services, but adapted by data from the river basins' ecohydrological monitoring. First, the method depicts river ecosystem valuation with probabilistic criteria of both the water yield, as supply, and the grey Water Footprint (greyWF), as demand. Second, we introduced the comparison between water supply and demand carried out on the continuous flow regime and monitored loads in rivers with different land uses, sizes and biomes. Third, this new ecosystem service valuation method enabled us to quickly visualize the possible stages of sustainability concerning the Brazilian legal framework among different basins. The methodology was applied in 12 Brazilian river basins, with drainage areas between 17 and 26,500 km2, and changes in land use with variable percentages of urban (62–92%), forest (51–84%) and agriculture (51–89%) areas. The most polluted basins, with greyWF values far above those allowed, have the most significant, almost asymptotic valuation curves. Results range from a minimum reference value of 61 US$/ha/year for conservation, adapted from the Brazilian Water Producer, to US$ 330 for restoring high polluted basins. The results show the viability of this method and discuss further opportunities for water security, especially for climate change and non-stationary sectorial demands.

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