Group-based estimation of missing hydrological data: I. Approach and general methodology

Elshorbagy, Amin; Panu, U. S.; Simonović́, Slobodan P.

doi:10.1080/02626660009492388

Cited by 56 publications

(24 citation statements)

References 45 publications

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“…As primeiras técnicas de imputação foram desenvolvidas através da substituição dos dados Silva Júnior, R. O., Queiroz, J. C. B., Ferreira, D. B. S., Tavares, A. L., Souza Filho, P. W. M., Guimarães, J. T. F., Edson José Rocha, P. faltantes pela média, pela mediana, por interpolação ou até por regressão linear (Elshorbagy et al, 2000). Nesses casos, a técnica é conhecida como imputação única, uma vez que o valor faltante é preenchido uma única vez.…”

Section: Coleta E Análise De Dados Fluviométricosunclassified

Estimativa de precipitação e vazões médias para a bacia hidrográfica do rio Itacaiúnas (BHRI), Amazônia Oriental, Brasil (Estimation of Precipitation and average Flows for the Itacaiúnas River Watershed (IRW) - Eastern Amazonia, Brazil)

Júnior

Queiroz

Ferreira

et al. 2017

Rev. Bras. Geog. Fis.

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Este artigo discute a relação entre dados observados de precipitação de sete estações meteorológicas e os dados resultantes de interpolação realizadas pelo Climate Prediction Center (CPC) para a área da bacia hidrográfica do rio Itacaiúnas (BHRI), Amazônia Oriental, no período de 1986-2005. O trabalho avalia também a aplicação de metodologias expeditas para estimar vazões médias mensais nas sub bacias, a partir de uma única estação de referência situada em seu exutório. As vazões foram estimadas pelos métodos de correção pela área de drenagem e de padronização de vazões médias comparadas com vazões medidas (1985-1995) em uma de suas sub bacias. Os resultados obtidos para a precipitação mostraram-se compatíveis com o comportamento sazonal definido para a região, cuja correlação entre os dados observados e os interpolados pelo CPC demonstram que estes representam bem a variabilidade espaço-temporal da precipitação na BHRI. A análise dos resultados das estações meteorológicas mostrou uma tendência de incremento na precipitação de leste para oeste, cujo comportamento pode estar associado a densa cobertura florestal que compõe o mosaico de Unidades de Conservação (UC’s), combinado com altitudes elevadas (600-800 m) da Serra de Carajás. A avaliação do comportamento das vazões da única estação (Fazenda Alegria) com série de dados fluviométricos disponíveis apresentou resultados consistentes com o comportamento sazonal das curvas de vazão dentro do ano hidrológico. Os métodos utilizados para a estimativa de vazões mostraram resultados diferenciados em termos absolutos, porém, as curvas de vazões estimadas acompanham o comportamento da curva de vazões medidas na estação Fazenda Rio Branco. A B S T R A C TThis paper discusses the relationship between observed precipitation data from seven meteorological stations and the resulting interpolation data from the Climate Prediction Center (CPC) for the area of the Itacaiúnas river basin (BHRI), Eastern Amazonia, in the period 1986-2005. The work also evaluates the application of expeditious methodologies to estimate monthly average flows in the sub basins, from a single reference station located in its exutorio. The flow rates were estimated by the methods of correction by the drainage area and standardization of average flows compared to measured flows (1985-1995) in one of its sub basins. The results obtained for the precipitation were compatible with the seasonal behavior defined for the region, whose correlation between the data observed and those interpolated by the CPC show that they represent well the spatio-temporal variability of the precipitation in the BHRI. The analysis of the results of the meteorological stations showed a tendency of increase in the precipitation from east to west, whose behavior may be associated with dense forest cover that composes the mosaic of Conservation Units (UC's), combined with high altitudes (600-800 m) of the Serra de Carajás. The evaluation of the flow behavior of the single station (Fazenda Alegria) with a series of available fluviometric data presented results consistent with the seasonal behavior of the flow curves within the hydrological year. The methods used for the estimation of flow rates showed different results in absolute terms, however, the estimated flow curves follow the behavior of the measured flow curve in Fazenda Rio Branco station. Keywords: Estimation, precipitation, flow, sub basin, Eastern Amazon

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Section: Coleta E Análise De Dados Fluviométricosunclassified

Estimativa de precipitação e vazões médias para a bacia hidrográfica do rio Itacaiúnas (BHRI), Amazônia Oriental, Brasil (Estimation of Precipitation and average Flows for the Itacaiúnas River Watershed (IRW) - Eastern Amazonia, Brazil)

Júnior

Queiroz

Ferreira

et al. 2017

Rev. Bras. Geog. Fis.

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“…Finally, in addition to the above-discussed methods for imputation of missing precipitation values, data-driven approaches based on neural network algorithms should also be remembered (Gupta and Lam, 1996;Elshorbagy et al, 2000aElshorbagy et al, , 2000bKhalil et al, 2001), i.e. on learning relationships between data from target and surrounding stations.…”

Section: Introductionmentioning

confidence: 99%

Improving estimation of missing values in daily precipitation series by a probability density function‐preserving approach

Simolo

Brunetti

Maugeri

et al. 2010

Intl Journal of Climatology

102

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This work presents a novel method for estimating missing values in daily precipitation series. It is aimed at identifying the event time location with good accuracy and reconstructing the correct amount of daily rainfall. In addition, the statistical properties of the time series, i.e. both probability distribution and long-term statistics, are preserved. The completion method is based on a two-step algorithm that uses information from a cluster of neighboring stations. First, wet and dry days are tagged, and subsequently, the full precipitation amount for wet-classified days is estimated by a modified multi-linear regression approach. This method avoids overestimation of the number of wet days and underestimation of intense precipitation events, which are typical side effects of common regression-based approaches.

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“…In various references, the importance and concepts of hydrologic clustering have been studied (Panu and Unny, 1980;Elshorbagy et al, 2000;Srinivas, 2006, 2008;Abedini et al, 2008). It has also been argued 733 that as a prerequisite to modelling hydrologic data using stochastic interpolation techniques, the original dataset has to be clustered if the data points are not uniformly distributed (Shi, 2002).…”

Section: Introductionmentioning

confidence: 99%

Application of simple clustering on space‐time mapping of mean monthly rainfall pattern

Nasseri

Zahraie

2011

Intl Journal of Climatology

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Rain gauges in many watersheds are not enough to represent the spatial and temporal variations of precipitation. Many agricultural activities can be highly sensitive to these variations and therefore different monthly or annual precipitation statistics have been widely used in the literature for agricultural planning and management. For example, mean monthly rainfall has been used as one of the main criteria for classifying suitable regions for dryland farming. In this paper, a method for space-time estimation of cumulative mean monthly rainfall (CMMR) is presented. The proposed method for estimating CMMR pattern is based on developing time-varying variogram coupled with ordinary Kriging (OK). OK is selected as a spatial exploration method and all of its parameters are optimised using weighted least square method. K-means clustering has also been applied to increase the model efficiency. Space-time estimation of CMMRs in each cluster has been carried out based on the observed CMMRs of the rain gauges in each specific cluster. The proposed method is tested using 25 years of monthly rainfall records of 14 rain gauges in the Maroon watershed in south of Iran. The results of the case study have shown that both methods (estimation with and without clustering) are proper choices for space-time modelling of rainfall pattern; however, the method in which the rain gauges are classified to different clusters has shown a better statistical performance in terms of normalised mean square error.

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Group-based estimation of missing hydrological data: I. Approach and general methodology

Cited by 56 publications

References 45 publications

Estimativa de precipitação e vazões médias para a bacia hidrográfica do rio Itacaiúnas (BHRI), Amazônia Oriental, Brasil (Estimation of Precipitation and average Flows for the Itacaiúnas River Watershed (IRW) - Eastern Amazonia, Brazil)

Estimativa de precipitação e vazões médias para a bacia hidrográfica do rio Itacaiúnas (BHRI), Amazônia Oriental, Brasil (Estimation of Precipitation and average Flows for the Itacaiúnas River Watershed (IRW) - Eastern Amazonia, Brazil)

Improving estimation of missing values in daily precipitation series by a probability density function‐preserving approach

Application of simple clustering on space‐time mapping of mean monthly rainfall pattern

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