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

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.

Monitoring nitrogen nutrition in cotton

Both N excess and deficiency may affect cotton yield and quality. It would therefore be useful to base the N management fertilization on the monitoring of the nutritional status. This study investigated the correlations among the following determination methods of the N nutritional status of cotton (Gossypium hirsutum L., var. Latifolia): chlorophyll readings (SPAD-502®, Minolta), specific-ion nitrate meter (Nitrate Meter C-141, Horiba-Cardy®), and laboratory analysis (conventional foliar diagnosis). Samples were taken weekly from two weeks before flowering to the fifth week after the first flower. The experiment was conducted on the Fazenda Santa Tereza, Itapeva, State of São Paulo, Brazil. The crop was fertilized with 40 kg ha-1 N at planting and 0, 30, 60, 90, and 120 kg ha-1 of side-dressed N. The range of leaf N contents reported as adequate for samples taken 80-90 days after plant emergence (traditional foliar diagnosis) may be used as reference from the beginning of flowering when the plant is not stressed. Specific-ion nitrate meter readings can be used as a nutritional indicator of cotton nutrition from one week after pinhead until the third week of flowering. In this case, plants are well-nourished when readings exceed 8,000 mg L-1 NO3-. The chlorophyll meter can also be used to estimate the nutritional status of cotton from the third week of flowering. In this case the readings should be above 48 in well-nourished plants.

Quality of surface water related to land use: a case study in a catchment with small farms and intensive vegetable crop production in southern Brazil

Water degradation is strongly related to agricultural activity. The aim of this study was to evaluate the influence of land use and some environmental components on surface water quality in the Campestre catchment, located in Colombo, state of Parana, Brazil. Physical and chemical attributes were analyzed (total nitrogen, ammonium, nitrate, total phosphorus, electrical conductivity, pH, temperature, turbidity, total solids, biological oxygen demand, chemical oxygen demand and dissolved oxygen). Monthly samples of the river water were taken over one year at eight monitoring sites, distributed over three sub-basins. Overall, water quality was worse in the sub-basin with a higher percentage of agriculture, and was also affected by a lower percentage of native forest and permanent preservation area, and a larger drainage area. Water quality was also negatively affected by the presence of agriculture in the riparian zone. In the summer season, probably due to higher rainfall and intensive soil use, a higher concentration of total nitrogen and particulate nitrogen was observed, as well as higher electrical conductivity, pH and turbidity. All attributes, except for total phosphorus, were in compliance with Brazilian Conama Resolution Nº 357/2005 for freshwater class 1. However, it should be noted that these results referred to the base flow and did not represent a discharge condition since most of the water samples were not collected at or near the rainfall event.

A low-cost trap for Cerambycidae monitoring in forest plantations in Brazil

The objective of this work was to evaluate the use of a low-cost trap to capture Cerambycidae in different seasons in planted forests in Brazil. Thirty polyethylene-terephthalate trap bottles per hectare were used, disposed at every 50 m. The traps were red painted and contained glass flasks with a mixture of ethanol, methanol and benzaldehyde. There were soap and water at the trap bottom. The traps were checked biweekly for beetle presence. Sampling time required one minute per sample, and traps were easy to use. Total sampling cost, including materials and labor, was US$ 13.46 per sample. Six Cerambycidae species were captured along the dry and rainy seasons.