Application of geostatistics to evaluate partial weather station networks

Ashraf, Muhammad; Loftis, Jim C.; Hubbard, K. G.

doi:10.1016/s0168-1923(96)02358-1

Cited by 132 publications

(70 citation statements)

References 5 publications

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“…In this study, daily precipitation data were measured at 19 raingauged stations covering the whole studied area, and the other meteorological data were observed at 4 meteorological stations around the catchment. All meteorological data were interpolated over the whole study area using the inverse distance square method (Ashraf et al, 1997). Based on DEM, such meteorological variables as air temperature, air vapor pressure and wind velocity were topographically corrected with the empirical relationships during interpolation:…”

Section: Meteorological Datamentioning

confidence: 99%

Quantifying the effect of land use and land cover changes on green water and blue water in northern part of China

Liu

Ren

Yuan

et al. 2009

Hydrol. Earth Syst. Sci.

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Abstract. Changes in land use and land cover (LULC) have been occurring at an accelerated pace in northern parts of China. These changes are significantly impacting the hydrology of these parts, such as Laohahe Catchment. The hydrological effects of these changes occurring in this catchment were investigated using a semi-distributed hydrological model. The semi-distributed hydrological model was coupled with a two-source potential evaportranspiration (PET) model for simulating daily runoff. Model parameters were calibrated using hydrometeorological and LULC data for the same period. The LULC data were available for 1980, 1989, 1996 and 1999. Daily streamflow measurements were available from 1964 to 2005 and were divided into 4 periods: 1964-1979, 1980-1989, 1990-1999 and 2000-2005. These periods represented four different LULC scenarios. Streamflow simulation was conducted for each period under these four LULC scenarios. The results showed that the change in LULC influenced evapotranspiration (ET) and runoff. The LULC data showed that from 1980 to 1996 grass land and water body had decreased and forest land and crop land had increased. This change caused the evaporation from vegetation interception and vegetation transpiration to increase, whereas the soil evaporation tended to decrease. Thus during the period of 1964-1979 the green water or ET increased by 0.95%, but the blue water or runoff decreased by 8.71% in the Laohahe Catchment.

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Section: Meteorological Datamentioning

confidence: 99%

Quantifying the effect of land use and land cover changes on green water and blue water in northern part of China

Liu

Ren

Yuan

et al. 2009

Hydrol. Earth Syst. Sci.

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“…Therefore, the hourly rainfall data collected from these three stations between 1970 and 2009 were used to estimate the regional average rainfall p for the watershed by using the reciprocal-distance-squared method (Chow et al, 1988). Since this method is simple and can directly reflect the weighting of distance, it has been widely used not only in determining ungauged or regional average rainfalls but also in determining unmeasured or regional average physical quantities in other fields, such as hydrology and earth science (Ashraf et al, 1997;Cheng, 1998;Teegavarapu and Chandramouli, 2005;Chen, 2011). The regional average rainfall estimated by the reciprocal-distance-squared method can be expressed as follows:…”

Section: Regional Average Rainfall In the Chenyulan Stream Watershedmentioning

confidence: 99%

Recent changes in the number of rainfall events related to debris-flow occurrence in the Chenyulan Stream Watershed, Taiwan

Chen

Huang

Jan

et al. 2012

Nat. Hazards Earth Syst. Sci.

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Abstract. This study analyzed the variability in the number of rainfall events related to debris-flow occurrence in the Chenyulan stream watershed located in central Taiwan. Rainfall data between 1970 and 2009 measured at three meteorological stations nearby/in the watershed were collected and used to determine the corresponding regional average rainfall for the watershed. Data on debris-flow events between 1985 and 2009 were collected and used to study their dependence on regional average rainfall. The maximum 24-h regional rainfall R d was used to analyze the number of rainfall events N r , the number of rainfall events that triggered debris flows N d , and the probability of debris-flows occurrences P . The variation trends in N r , N d and P over recent decades under three rainfall conditions (R d > 20,230, and 580 mm) related to debris-flow occurrence were analyzed. In addition, the influences of the Chi-Chi earthquake on N d and P were presented. The results showed that the rainfall events with R d > 20 mm during the earthquakeaffected period (2000)(2001)(2002)(2003)(2004) strongly responded to the increases in the average number of rainfall events that triggered debris flows and the average probability of debris-flows occurrences. The number of rainfall events with R d > 230 mm (the lower boundary for the rainfall ever triggering debris flow before the Chi-Chi earthquake), and R d > 580 mm (the lower boundary for extreme rainfall ever triggering numerous debris flows) in the Chenyulan stream watershed increased after 2000. The increase in the number of extreme rainfall events with R d > 580 mm augmented the number of rainfall events ever triggering numerous debris flows in the last decade. The increase in both the number of rainfall events that ever triggered debris flows and the probability of debrisflow occurrences was greater in the last decade

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“…Programas de análise de consistência de dados são utilizados normalmente por redes de estações meteorológicas convencionais para controle de qualidade, para identificação de dados com problemas ou perdidos, e fornecer estimativas consistentes com base em dados de outras estações próximas. Os sistemas de controle de qualidade de rede de estações meteorológicas automáticas requerem, porém, um maior conhecimento da variabilidade espacial e temporal dos dados meteorológicos diários regionais, para serem utilizados nos sistemas matemáticos de interpolação de dados necessários para a identificação de dados suspeitos ou na estimativa de dados perdidos (DECKER, 1994;HUBBARD et al, 1996;ASHRAF et al, 1997).…”

Section: Introductionunclassified

Variabilidade espacial e temporal de dados termopluviométricos diários da rede de estações agrometeorológicas do Instituto Agronômico (IAC)

et al. 2005

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RESUMOProgramas de análise de consistência de dados são utilizados, normalmente, por redes de estações agrometeorológicas para controle de qualidade, para identificar dados com problemas e fornecer estimativas consistentes, com base em dados de outras estações próximas. Os sistemas modernos de controle de qualidade de rede de estações meteorológicas requerem porém maior conhecimento da variabilidade espacial e temporal dos dados meteorológicos diários regionais, para serem utilizados nos sistemas matemáticos de interpolação de dados necessários a fim de identificar dados suspeitos ou na estimativa de dados perdidos. O objetivo deste trabalho foi quantificar a variabilidade espacial e temporal de dados diários de temperatura do ar máxima, média e mínima e de precipitação pluvial no Estado de São Paulo, para servir de subsídio ao desenvolvimento de sistema de controle de qualidade e de limites de intervalos de confiança. Foram utilizados dados de 19 estações agrometeorológicas do IAC, em um período total de 20 anos (1981/2000), sendo Campinas considerada a estação central. Análises de regressão mensais foram realizadas com base nos dados diários da estação central e cada uma das demais estações, considerando as respectivas distâncias lineares, que variaram de 0 a 436 km, nas quais foram obtidos valores de coeficientes de determinação (R 2 ) e de erro-padrão de estimativa (SEE) para os elementos considerados. Pelos resultados, à medida que as distâncias aumentam, menores são os valores de R 2 e maiores os valores de SEE, seguindo diferentes funções, que variaram segundo o elemento meteorológico e a época do ano. Quanto à variabilidade temporal, os meses com maiores valores de SEE para temperaturas máximas e mínimas (TMAX e TMIN) foram os de primavera e inverno respectivamente. Considerando 150 km de distância, a TMAX indicou valores de SEE até de 3,0 °C e TMIN de até 2,3 °C. Para precipitação pluvial, observaram-se valores menores de SEE durante o inverno, de até 4 mm, e valores mais elevados, de até 15 mm, durante o verão. Pelas análises, os limites máximos de distâncias admitidos para explicar mais de 90% das variações dos elementos termopluviométricos entre locais foram para TMAX, 80 km (primavera-verão) e 90 km (outono-inverno); para TMIN são necessários 55 km para os meses de verão, 75 km para inverno-primavera e 90 km durante o outono. Para dados pluviométricos, as distâncias de até 12 km explicam 90% da variação para os meses de verão, até 20 km para os de primavera e outono e de até 27 km para os de inverno.Palavras-chave: temperatura máxima e mínima do ar, variabilidade temporal e espacial, controle de qualidade, estimativa de erros, rede de estações, caracterização climática.

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Application of geostatistics to evaluate partial weather station networks

Cited by 132 publications

References 5 publications

Quantifying the effect of land use and land cover changes on green water and blue water in northern part of China

Quantifying the effect of land use and land cover changes on green water and blue water in northern part of China

Recent changes in the number of rainfall events related to debris-flow occurrence in the Chenyulan Stream Watershed, Taiwan

Variabilidade espacial e temporal de dados termopluviométricos diários da rede de estações agrometeorológicas do Instituto Agronômico (IAC)

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