Applicability of a distributed watershed pollution model in a data-poor environment in Santa Catarina State, Brazil

Ivan Luiz Zilli Bacic,Christiaan Mathias Mannaerts,David G Rossiter

doi:10.1590/s0100-06832008000400035

Ivan Luiz Zilli Bacic, Christiaan Mathias Mannaerts + Show 1 more

Open Access

https://doi.org/10.1590/s0100-06832008000400035

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Abstract

Intensification of agricultural production without a sound management and regulations can lead to severe environmental problems, as in Western Santa Catarina State, Brazil, where intensive swine production has caused large accumulations of manure and consequently water pollution. Natural resource scientists are asked by decision-makers for advice on management and regulatory decisions. Distributed environmental models are useful tools, since they can be used to explore consequences of various management practices. However, in many areas of the world, quantitative data for model calibration and validation are lacking. The data-intensive distributed environmental model AgNPS was applied in a data-poor environment, the upper catchment (2,520 ha) of the Ariranhazinho River, near the city of Seara, in Santa Catarina State. Steps included data preparation, cell size selection, sensitivity analysis, model calibration and application to different management scenarios. The model was calibrated based on a best guess for model parameters and on a pragmatic sensitivity analysis. The parameters were adjusted to match model outputs (runoff volume, peak runoff rate and sediment concentration) closely with the sparse observed data. A modelling grid cell resolution of 150 m adduced appropriate and computer-fit results. The rainfall runoff response of the AgNPS model was calibrated using three separate rainfall ranges (< 25, 25-60, > 60 mm). Predicted sediment concentrations were consistently six to ten times higher than observed, probably due to sediment trapping along vegetated channel banks. Predicted N and P concentrations in stream water ranged from just below to well above regulatory norms. Expert knowledge of the area, in addition to experience reported in the literature, was able to compensate in part for limited calibration data. Several scenarios (actual, recommended and excessive manure applications, and point source pollution from swine operations) could be compared by the model, using a relative ranking rather than quantitative predictions.

Highlights

Intensification of agricultural production may lead to higher living standards of the producers and more wealth in a country
If not coupled with sound environmental management, severe environmental problems may arise, both at the farm level and off-site. This is especially true in transitional economies such as Santa Catarina State, Southern Brazil, with a well-developed market system, but languid environmental legislation or enforcement
Past applications included the assessment of soil erosion (Prato & Shi, 1990; Engel et al, 1993; Mitchell et al, 1993; Rainis et al, 2002; Walling et al, 2003), prediction of surface runoff (Engel et al, 1993; Mitchell et al, 1993; Grunwald & Norton, 2000), assessment of allowable nutrient loads (Pekarova et al, 1999; Rode & Lindenschmidt, 2001), prediction of effects of different land use management practices (Prato & Shi, 1990; Mostaghimi et al, 1997) and simulation of the effect of expanded swine production on P transport and water quality (Sauer et al, 2003)

Summary

SUMMARY

Source pollution from swine operations) could be compared by the model, using a relative ranking rather than quantitative predictions. RESUMO: APLICABILIDADE DE UM MODELO DE POLUIÇÃO PARA BACIAS HIDROGRÁFICAS EM UM AMBIENTE POBRE EM DADOS NO ESTADO DE SANTA CATARINA, BRASIL. Foram descritos os passos necessários para que o modelo pudesse ser aplicado nesse ambiente, incluindo: preparação dos dados, seleção do tamanho de células, análise de sensibilidade, calibração e aplicação em diferentes cenários. As previsões de concentração de sedimentos em água foram consistentemente de seis a dez vezes maiores do que os valores observados, possivelmente devido à captura de sedimentos pela vegetação próxima dos rios e drenos – situação não considerada pelo modelo. Foi então possível aplicar o modelo para uma classificação relativa dos diferentes cenários em estudos comparativos, mas não para previsões quantitativas precisas. Termos de indexação: poluição do solo e da água, AgNPS, dejetos de suínos, simulação, calibração de modelo, análise de cenários, conhecimento especializado local

INTRODUCTION

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