Agricultural soils provide ecosystem services, but the removal of natural vegetation reduces water infiltration capacity, increasing surface runoff. Thus, monitoring erosion is critical for sustainable agricultural management. Sediment losses and surface runoff were evaluated using a simulated rainfall of 75 mm/h in areas with crops and pastures in both the Caiabi River and Renato River sub-basins of the Teles Pires River watershed in Mato Grosso State, Brazil. In both the Caiabi and Renato sub-basins, data were collected from 156 observations in the upper, middle, and lower regions where (1) soybeans, (2) maize, and (3) pasture were grown alone, with another crop, or with soil that was scarified. Erosion occurred independent of soil texture and was closely related to the management and use of systems involving fewer crops and more soil scarification, regardless of sub-basin location. In uncovered, scarified soil, the soil losses from erosion were greater compared to covered soil, regardless of sub-basin and sub-basin region. In the Renato River sub-basin, soil losses in cultivated areas not planted with crops but with scarification were 66.01, 90.79, and 60.02 g/square meter in the upper, middle, and lower regions, respectively. Agricultural producers need to increase the planting of crops throughout the year and minimize soil disturbance, which will reduce soil erosion and improve sustainability.
KEYWORDS Water availabilityWater use grant Water resources management Hydrological data Hydrographic basin RESUMO: A regionalização de vazões mínima e média fornece subsídios para a gestão de recursos hídricos, sobretudo em aspectos relacionados a outorgas de uso de água e regularização de vazões. Nesse contexto, o objetivo do trabalho foi regionalizar a vazão mínima associada à permanência de 95% (Q 95 ) e a vazão média de longa duração (Q ml ) para o médio e alto Rio Teles Pires, em Mato Grosso. Para regionalização das vazões foram utilizadas séries históricas de nove estações fluviométricas e as seguintes características físicas da bacia hidrográfica: área de drenagem (A D ); perímetro (P); comprimento axial (L); e comprimento total dos cursos de água (L Total ). Foram ajustados modelos de regressão linear, potencial, exponencial e logarítmico. Foi possível identificar uma única região hidrologicamente homogênea para Q 95 e Q ml no médio e alto Rio Teles Pires. Na regionalização da Q 95 , as variáveis explicativas que possibilitaram os melhores ajustes dos modelos de regressão foram A D e L Total , enquanto que para a regionalização da Q ml foram A D e L. As equações de regionalização apresentaram bons resultados e podem ser utilizadas no processo de gestão de recursos hídricos da área em estudo. ABSTRACT: The regionalization of minimum and medium flows provides subsidies for the management of water resources, especially in aspects related to water use grants and flow regulation. In this context, the objective of this work was to regionalize the minimum flow associated with the permanency of 95% (Q 95 ), and the long-term medium flow (Q ml ) for the medium and upper Teles Pires river in Mato Grosso. For regionalization of flows, we used historical series of nine fluviometric stations, and the following physical characteristics of the hydrographic basin: drainage area (DA); perimeter (P); axial length (L); and total length of water courses (LTotal
Recebido em 15/07/2013; Aceito em 16/10/2013. RESUMO:Diante das preocupações com o ambiente de trabalho e consequentemente com o bem-estar dos trabalhadores, objetivou-se com o presente trabalho avaliar a utilização da modelagem matemática fuzzy, na avaliação da salubridade de trabalhadores agrícolas, relacionada ao ambiente térmico e acústico. Para tanto, foram consideradas como variáveis de entrada do sistema, o índice de bulbo úmido e termômetro de globo (IBUTG, °C) e o nível de ruído (dB(A)), tendo como variável de saída o índice de bem-estar humano (IBEH). O método de inferência utilizado foi o de Mandani e na defuzificação, utilizou-se o método do centro de gravidade. Foram utilizadas 25 regras para representar estes dados, sendo que para cada regra foi atribuído peso igual a 1. Os resultados indicam que o modelo matemático teve uma metodologia satisfatória, podendo auxiliar na tomada de decisões e análises cotidianas. Palavra-chave: salubridade, ambiente de trabalho, sistemas inteligentes. FUZZY MODELING IN HUMAN WELL-BEINGPARAMETERS ABSTRACT: Given the concerns about the work environment and consequently the well-being of workers, this study aimed to evaluate the use of fuzzy mathematical modeling in assessing of the farm workers health, related to thermal and acoustic environment. So, were considered as input variables of the system, the wet bulb globe temperature index (WBGT, °C) and noise level (dB (A)), and the output variable was the human well-being index (HWBI). The inference method used was the
The objective of this work was to evaluate the heat dissipated in broiler chickens during the first two weeks of life and to estimate with infrared thermography the loss of sensible heat from birds. The environmental conditions were pre-established in wind tunnels using the automatic monitoring and control system, where only air temperature values were varied during each experimental week. Thus, the heat exchanges through convection and radiation of each animal were calculated by means of equations for the first and second week of life, and the temperature of the broilers was obtained by means of thermographic images. Based on the results, it has been found that the surface temperatures of the birds are correlated with air temperature and that they suffer greater heat dissipation when subjected to temperatures below their thermal comfort zone and also as growth develops.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.