Abstract

Abstract. Pollution emissions into the drainage basin have direct impact on surface water quality. These emissions result from human activities that turn into pollution loads when they reach the water bodies, as point or diffuse sources. Their pollution potential depends on the characteristics and quantity of the transported materials. The estimation of pollution loads can assist decision-making in basin management. Knowledge about the potential pollution sources allows for a prioritization of pollution control policies to achieve the desired water quality. Consequently, it helps avoiding problems such as eutrophication of water bodies. The focus of the research described in this study is related to phosphorus emissions into river basins. The study area is the upper Iguazu basin that lies in the northeast region of the State of Paraná, Brazil, covering about 2,965 km2 and around 4 million inhabitants live concentrated on just 16% of its area. The MoRE (Modeling of Regionalized Emissions) model was used to estimate phosphorus emissions. MoRE is a model that uses empirical approaches to model processes in analytical units, capable of using spatially distributed parameters, covering both, emissions from point sources as well as non-point sources. In order to model the processes, the basin was divided into 152 analytical units with an average size of 20 km2. Available data was organized in a GIS environment. Using e.g. layers of precipitation, the Digital Terrain Model from a 1:10000 scale map as well as soils and land cover, which were derived from remote sensing imagery. Further data is used, such as point pollution discharges and statistical socio-economic data. The model shows that one of the main pollution sources in the upper Iguazu basin is the domestic sewage that enters the river as point source (effluents of treatment stations) and/or as diffuse pollution, caused by failures of sanitary sewer systems or clandestine sewer discharges, accounting for about 56% of the emissions. Second significant shares of emissions come from direct runoff or groundwater, being responsible for 32% of the total emissions. Finally, agricultural erosion and industry pathways represent 12% of emissions. This study shows that MoRE is capable of producing valid emission calculation on a relatively reduced input data basis.

Highlights

  • Sources and causes of waterbody impairments and threats should be addressed basin-wide to target the priority measures for the protection and restoration of water bodies to ensure a long-term good ecological status

  • The MoRE system comprises approaches for the estimation of emission pathways of 14 pollutants related to point and diffuse sources on a basin scale (Fuchs et al 2010), (Fuchs et al 2012) The MoRE model originated as part of the German Environment Agencys demand, to develop a database and modeling application covering all German river basins aiming on an appropriate description of rivers status

  • The MoRE system allows for the estimation of emission pathways related to point sources and related to diffuse sources

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Summary

INTRODUCTION

Sources and causes of waterbody impairments and threats should be addressed basin-wide to target the priority measures for the protection and restoration of water bodies to ensure a long-term good ecological status. Phosphor is normally the limiting nutrient in the aquatic environment (Von Sperling 1996) in that case, its increased input will lead to unwanted proliferation of algae and macrophytes, resulting in potential ecological degradation. It is necessary to control the causes and sources of phosphor in order to reduce inputs into water bodies. MoRE (Modeling of Regionalized Emissions) was used to calculate the current input situation of phosphorous loads in the catchment of upper Iguazu River. It has the potential to examine limits from guidelines in order to achieve good ecological status of surface water bodies

STUDY AREA
Model construction and data
Point source estimation
Diffuse source estimation
Verification
Estimation of phosphorus emissions
Verification of MoRE model with observed values
CONCLUSIONS

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