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1.
Artigo em Inglês | MEDLINE | ID: mdl-33447973

RESUMO

A significant contributor to water pollution is increased nutrient concentration that results in eutrophication. Modeling approaches are crucial to understanding the dynamics of nutrients in river basins. This study integrates empirical models into Geographic Information Systems to quantify total nitrogen and phosphorus (TN and TP) load and concentration in watercourses of Brazil's Lobo Stream Hydrographic Basin (LSHB). Land use, topographic, demographic, and hydrological data were used to simulate the load and concentration of nutrients generated by point and nonpoint pollution sources. The results indicate that the simulated TN and TP load is primarily generated by nonpoint sources, 81% and 76%, respectively. The Itaqueri River subbasin is the most critical, yielding more than half of the basin's TN and TP load. About 90% of annual LSHB point pollution load is generated in the Itaqueri River subbasin, principally from the Água Branca Stream. The linear regression between simulated and observed concentration indicates significant relationships (TN, r2 = 0.73 (p < 0.05), TP, r2 = 0.78 (p < 0.05)). The method used was able to simulate TN and TP concentration in watercourses, but was inconsistent for point pollution, indicating it represents the dynamics of nutrients in rural basins more effectively than in urban ones. The study shows that its methodology, despite limitations, enables scientists and managers to understand and predict spatial distribution of nutrient concentration in LSHB watercourses.

2.
Environ Monit Assess ; 192(11): 707, 2020 Oct 17.
Artigo em Inglês | MEDLINE | ID: mdl-33068183

RESUMO

Among the problems related to water security, the effects of climate change on water availability stand out. Researchers have used hydrological models integrated with climate models in order to predict the streamflow behaviour in different hydrographic basins. This work aimed to analyse future climate scenarios for the Ribeirão do Lobo River Basin, located in the state of São Paulo, Brazil. The stochastic generator PGECLIMA_R was used in the simulation of climate data, which were used as input data in the hydrological model SMAP, after it was calibrated and validated for the study site. In all, five future scenarios were generated, with scenarios A, B, C and D projected based on the 5th report of the IPCC and scenario E based on the trend of climate data in the region. Among the scenarios generated, scenario D, which considers an increase of 4.8 °C in air temperature and a reduction of 10% in rainfall, is responsible for the worst water condition in the basin and can reduce up to 72.41% of the average flow and up to 55.50%, 54.18% and 38.17% of the low flow parameters Q90%, Q95% and Q7,10, respectively, until the end of the twenty-first century. However, the E scenario also becomes a matter of concern, since it was responsible for greater increases in temperature and greater reductions in rainfall and, consequently, more drastic monthly reductions in streamflow, which may negatively impact water resources and affect the various uses of water in the Ribeirão do Lobo River Basin.


Assuntos
Mudança Climática , Modelos Teóricos , Brasil , Monitoramento Ambiental , Hidrologia
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