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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/68
Title: 
Transfer function-noise modeling and spatial interpolation to evaluate the risk of extreme (shallow) water-table levels in the Brazilian Cerrados
Author(s): 
Institution: 
  • Universidade Estadual Paulista (UNESP)
  • Alterra Soil Sci Ctr
  • Delft Univ Technol
  • Instituto Nacional de Pesquisas Espaciais (INPE)
ISSN: 
1431-2174
Sponsorship: 
  • Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
  • WIMEK (Wageningen Institute for Environment and Climate Research)
Abstract: 
Water regimes in the Brazilian Cerrados are sensitive to climatological disturbances and human intervention. The risk that critical water-table levels are exceeded over long periods of time can be estimated by applying stochastic methods in modeling the dynamic relationship between water levels and driving forces such as precipitation and evapotranspiration. In this study, a transfer function-noise model, the so called PIRFICT-model, is applied to estimate the dynamic relationship between water-table depth and precipitation surplus/deficit in a watershed with a groundwater monitoring scheme in the Brazilian Cerrados. Critical limits were defined for a period in the Cerrados agricultural calendar, the end of the rainy season, when extremely shallow levels (< 0.5-m depth) can pose a risk to plant health and machinery before harvesting. By simulating time-series models, the risk of exceeding critical thresholds during a continuous period of time (e.g. 10 days) is described by probability levels. These simulated probabilities were interpolated spatially using universal kriging, incorporating information related to the drainage basin from a digital elevation model. The resulting map reduced model uncertainty. Three areas were defined as presenting potential risk at the end of the rainy season. These areas deserve attention with respect to water-management and land-use planning.
Issue Date: 
1-Dec-2010
Citation: 
Hydrogeology Journal. New York: Springer, v. 18, n. 8, p. 1927-1937, 2010.
Time Duration: 
1927-1937
Publisher: 
Springer
Keywords: 
  • Agriculture
  • Statistical modeling
  • Geostatistics
  • Groundwater management
  • Brazil
Source: 
http://dx.doi.org/10.1007/s10040-010-0654-5
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/68
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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