Variance of Load Estimates Derived by Piecewise Linear Interpolation

Shih, George B.; Wang, Xiaosong; Grimshaw, H. J.; VanArman, Joel

doi:10.1061/(asce)0733-9372(1998)124:11(1114)

Cited by 11 publications

(6 citation statements)

References 7 publications

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“…To calculate pesticide loss from the paddy field and fish pond, the volume of respective surface discharge in hourly resolution was multiplied by the corresponding pesticide concentration in the outflow. The hourly pesticide concentrations were estimated by a piecewise linear interpolation as described in Potter et al (2003) and Shih et al (1998). In a few cases, outflow concentration data were not available and field water concentrations were taken as a surrogate for field outlet concentrations, assuming homogeneous spatial distribution of pesticide concentrations.…”

Section: Methodsmentioning

confidence: 99%

Fate of Pesticides in Combined Paddy Rice-Fish Pond Farming Systems in Northern Vietnam

Anyusheva

Lamers

et al. 2012

J. Environ. Qual.

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During the last decades, high population growth and exportoriented economics in Vietnam have led to a tremendous intensifi cation of rice production, which in turn has signifi cantly increased the amount of pesticides applied in rice cropping systems. Since pesticides are toxic by design, there is a natural concern on the impact of their presence in the environment on human health and environmental quality. Th e present study was designed to examine the water regime and fate of pesticides (fenitrothion, dimethoate) during two consecutive rice crop seasons in combined paddy rice-fi sh pond farming systems in northern Vietnam. Major results revealed that 5 and 41% (dimethoate), and 1 and 17% (fenitrothion) of the applied mass of pesticides were lost from the paddy fi eld to the adjacent fi sh pond during spring and summer crop seasons, respectively. Th e decrease of pesticide concentration in paddy surface water was very rapid with dissipation half-life values of 0.3 to 0.8 and 0.2 d for dimethoate and fenitrothion, respectively. Key factors controlling the transport of pesticides were water solubility and paddy water management parameters, such as hydraulic residence time and water holding period. Risk assessment indicates that the exposure to toxic levels of pesticides for aquaculture (Cyprinus carpio, Daphnia magna) is signifi cant, at least shortly after pesticide application.

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Section: Methodsmentioning

confidence: 99%

Fate of Pesticides in Combined Paddy Rice-Fish Pond Farming Systems in Northern Vietnam

Anyusheva

Lamers

et al. 2012

J. Environ. Qual.

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“…Estimating uncertainty in load estimates for these three load methods can be complex, but is important for selecting the best method for a particular data set. For a period-weighted approach, the variance of a load estimate can be derived from a semivariogram calibrated to the data using a cross-validation technique (Shih et al 1998). For regression-model methods, the uncertainty in the regression is easy to calculate, but this can underestimate errors if the model calibration data set is not representative of all hydrologic conditions or model residuals are autocorrelated (Aulenbach 2013).…”

Section: Introductionmentioning

confidence: 99%

Approaches to stream solute load estimation for solutes with varying dynamics from five diverse small watersheds

et al. 2016

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. 2016. Approaches to stream solute load estimation for solutes with varying dynamics from five diverse small watersheds. Ecosphere 7(6):e01298. 10. 1002/ecs2.1298 Abstract. Estimating streamwater solute loads is a central objective of many water-quality monitoring and research studies, as loads are used to compare with atmospheric inputs, to infer biogeochemical processes, and to assess whether water quality is improving or degrading. In this study, we evaluate loads and associated errors to determine the best load estimation technique among three methods (a period-weighted approach, the regression-model method, and the composite method) based on a solute's concentration dynamics and sampling frequency. We evaluated a broad range of varying concentration dynamics with stream flow and season using four dissolved solutes (sulfate, silica, nitrate, and dissolved organic carbon) at five diverse small watersheds (Sleepers River Research Watershed, VT; Hubbard Brook Experimental Forest, NH; Biscuit Brook Watershed, NY; Panola Mountain Research Watershed, GA; and Río Mameyes Watershed, PR) with fairly high-frequency sampling during a 10-to 11-yr period. Data sets with three different sampling frequencies were derived from the full data set at each site (weekly plus storm/snowmelt events, weekly, and monthly) and errors in loads were assessed for the study period, annually, and monthly. For solutes that had a moderate to strong concentration-discharge relation, the composite method performed best, unless the autocorrelation of the model residuals was <0.2, in which case the regression-model method was most appropriate. For solutes that had a nonexistent or weak concentration-discharge relation (model R 2 < about 0.3), the period-weighted approach was most appropriate. The lowest errors in loads were achieved for solutes with the strongest concentration-discharge relations. Sample and regression model diagnostics could be used to approximate overall accuracies and annual precisions. For the period-weighed approach, errors were lower when the variance in concentrations was lower, the degree of autocorrelation in the concentrations was higher, and sampling frequency was higher. The period-weighted approach was most sensitive to sampling frequency. For the regression-model and composite methods, errors were lower when the variance in model residuals was lower. For the composite method, errors were lower when the autocorrelation in the residuals was higher. Guidelines to determine the best load estimation method based on solute concentration-discharge dynamics and diagnostics are presented, and should be applicable to other studies.

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“…Surface‐water samples typically are collected only once every k = 7 or 14 d. In practice, the predictions are often obtained by linearly imputing the gap days on the original scale (Shih et al, 1998; Stone et al, 2008; Richter et al, 2009), a method that corresponds to fitting a piecewise linear spline to the data, with knots at the sample data points. Several predictive watershed regression models based on historical pesticide monitoring data have been published (Larson and Gilliom, 2001; Chen et al, 2002; Guo et al, 2004; Chen, 2005; Vecchia et al, 2008; Stone et al, 2014).…”

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confidence: 99%

Kriging Models Predicting Atrazine Concentrations in Surface Water Draining Agricultural Watersheds

2016

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The performance of kriging methods in predicting maximum m-day (m = 1, 7, 14, or 30) rolling averages of atrazine concentrations in 42 site-years of Midwest Corn Belt watersheds under two systematic sampling designs (sampling every 7 or 14 d) was examined. Daily atrazine monitoring data obtained from the Atrazine Ecological Monitoring Program in the Corn Belt region (2009-2014) were used in the evaluation. Both ordinary and universal kriging methods were considered, with the covariate for universal kriging derived from the deterministic Pesticide Root Zone Model (PRZM). For the maximum 1-d rolling averages, prediction did not differ among methods. For rolling averages of longer duration (m > 1), predictions obtained by linear interpolation on a logarithmic scale were better (up to 15% lower for 7-d sampling and 22% lower for 14-d sampling in terms of the relative root mean squared prediction error) than those obtained by linear interpolation on the original linear scale and also less variable. For kriging methods, empirical semivariograms of daily atrazine time series suggest a negligible noise process, supported by replicate analysis of selected field samples; piecewise linear semivariogram models were found to perform best for predicting sampled data. We demonstrate that kriging prediction intervals offer close to nominal coverage for unsampled values.

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Variance of Load Estimates Derived by Piecewise Linear Interpolation

Cited by 11 publications

References 7 publications

Fate of Pesticides in Combined Paddy Rice-Fish Pond Farming Systems in Northern Vietnam

Fate of Pesticides in Combined Paddy Rice-Fish Pond Farming Systems in Northern Vietnam

Approaches to stream solute load estimation for solutes with varying dynamics from five diverse small watersheds

Kriging Models Predicting Atrazine Concentrations in Surface Water Draining Agricultural Watersheds

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