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    Predicting EC for Drainage Water Management

    Source: Journal of Irrigation and Drainage Engineering:;1986:;Volume ( 112 ):;issue: 003
    Author:
    P.‐S. Tsui
    ,
    J. C. Guitjens
    DOI: 10.1061/(ASCE)0733-9437(1986)112:3(274)
    Publisher: American Society of Civil Engineers
    Abstract: In 1982, 405 measurements of the subsurface drainage water quality parameter electrical conductivity (EC) in dS/m were collected. The data were obtained from 15 subsurface drains on 9.3 ha (23 acres) of irrigated agricultural land at Fallon, Nevada. The temporal and spatial variabilities of EC were studied using time series concepts. Autocorrelation functions (ACF) were used to evaluate the magnitude of temporal and spatial variations of EC. Results suggest that an 11‐week period is the maximum time interval for sampling and that the sampling spatial interval of 36.6 m (120 ft) is too large. Autoregressive integrated moving average (ARIMA) models for both temporal and spatial structures were established through the Box‐Jenkins time‐domain modeling process. The degree of uncertainty of the forecasts were tested using after‐thefact forecast procedures. These models can be used for various purposes such as forecasting future values and determining the transfer function, which provides a way to relate water management plans to water quality control.
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      Predicting EC for Drainage Water Management

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    http://yetl.yabesh.ir/yetl1/handle/yetl/26859
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    contributor authorP.‐S. Tsui
    contributor authorJ. C. Guitjens
    date accessioned2017-05-08T20:46:44Z
    date available2017-05-08T20:46:44Z
    date copyrightAugust 1986
    date issued1986
    identifier other%28asce%290733-9437%281986%29112%3A3%28274%29.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/26859
    description abstractIn 1982, 405 measurements of the subsurface drainage water quality parameter electrical conductivity (EC) in dS/m were collected. The data were obtained from 15 subsurface drains on 9.3 ha (23 acres) of irrigated agricultural land at Fallon, Nevada. The temporal and spatial variabilities of EC were studied using time series concepts. Autocorrelation functions (ACF) were used to evaluate the magnitude of temporal and spatial variations of EC. Results suggest that an 11‐week period is the maximum time interval for sampling and that the sampling spatial interval of 36.6 m (120 ft) is too large. Autoregressive integrated moving average (ARIMA) models for both temporal and spatial structures were established through the Box‐Jenkins time‐domain modeling process. The degree of uncertainty of the forecasts were tested using after‐thefact forecast procedures. These models can be used for various purposes such as forecasting future values and determining the transfer function, which provides a way to relate water management plans to water quality control.
    publisherAmerican Society of Civil Engineers
    titlePredicting EC for Drainage Water Management
    typeJournal Paper
    journal volume112
    journal issue3
    journal titleJournal of Irrigation and Drainage Engineering
    identifier doi10.1061/(ASCE)0733-9437(1986)112:3(274)
    treeJournal of Irrigation and Drainage Engineering:;1986:;Volume ( 112 ):;issue: 003
    contenttypeFulltext
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