Comparison of two regression-based approaches for determining nutrient and sediment fluxes and trends in the Chesapeake Bay watershed

Moyer, Douglas; Hirsch, Robert M.; Hyer, Kenneth

doi:10.3133/sir20125244

Cited by 36 publications

(75 citation statements)

References 9 publications

(16 reference statements)

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“…And although our case study data set does not contain any censored values-i.e., concentrations reported as less than detection limit (typically 0.5 mg/L for SS)-there are published approaches for handling such data [e.g., Tobin, 1958], and others have shown how WRTDS can be implemented in such cases [Chanat et al, 2016;Moyer et al, 2012;Zhang et al, 2015]. In fact, WRTDS has already been adopted by many investigators to estimate concentration and flux for a variety of constituents, including nitrogen, phosphorus, chloride, and dissolved organic carbon.…”

Section: Methods Application: Case Study and Broader Relevancementioning

confidence: 99%

An improved method for interpretation of riverine concentration‐discharge relationships indicates long‐term shifts in reservoir sediment trapping

Zhang

Harman

Ball

2016

Geophysical Research Letters

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Derived from river monitoring data, concentration‐discharge (C‐Q) relationships are powerful indicators of export dynamics. Proper interpretation of such relationships can be made complex, however, if the ln(C)‐ln(Q) relationships are nonlinear or if the relationships change over time, season, or discharge. Methods of addressing these issues by “binning” data can introduce artifacts that obscure underlying interactions among time, discharge, and season. Here we illustrate these issues and propose an alternative method that uses the regression coefficients of the recently developed “Weighted Regressions on Time, Discharge, and Season” model for examining C‐Q relationships in long‐term, discretely sampled data for various water‐quality constituents, including their uncertainties. The method is applied to sediment concentration data from Susquehanna River at Conowingo Dam, Maryland, to illustrate how the coefficients can be accessed and presented in ways that provide additional insights toward the interpretation of river water‐quality data, which reaffirms the recently documented decadal‐scale decline in reservoir trapping performance.

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Section: Methods Application: Case Study and Broader Relevancementioning

confidence: 99%

An improved method for interpretation of riverine concentration‐discharge relationships indicates long‐term shifts in reservoir sediment trapping

Zhang

Harman

Ball

2016

Geophysical Research Letters

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“…We used the flux bias statistic here as a dimensionless representation of the difference between the sum of the estimated fluxes on all sampled days and the sum of the true fluxes on all sampled days. Overall, WRTDS is substantially less susceptible to serious flux bias; however, it is not immune to the problem (Moyer et al 2012;Hirsch 2014). Because WBT only works with FNF and FNC series, trend identifications of the non-normalized and flow series were examined using BFAST (Table 2).…”

Section: Wrtds Bootstrap Test (Wbt)mentioning

confidence: 99%

Change in nutrient loading pattern due to coupled effect of change in concentration and hydroclimatic forces

Shafiei

McLoughlin

2017

Journal of Freshwater Ecology

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Increase in nutrient loading into large riverine systems is of interest because of long-lasting negative effects on downstream water bodies. We know little of this phenomenon with respect to long-term relationships between water quality metrics and trends in river flow. Here we present a multi-decadal examination of nutrient transport patterns of the South Saskatchewan and Red Deer Rivers, Canada. Using a multimethod approach, we show a slightly increasing trend in annual volume of water reaching a mid-watershed reservoir (Lake Diefenbaker) concomitant with a change in seasonal variability of flow events from the 1970s. Both total nitrogen (TN) and total phosphorus (TP) flux increased during the period of record. TN concentration increased, while TP concentration decreased. On average, the high-flow season transported 95% of annual TP flux, 75% of annual TN flux, and 65% of annual flow. Inter-annually, high-flow season contributions decreased with respect to water volume, but increased with respect to both TN and TP flux. We believe that changes in variability but also timing of hydroclimatic forces are responsible for observed patterns. Higher flows and more precipitation during the high-flow season are most likely responsible for increasing nutrient load regardless of overall decreases in nutrient concentration.

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“…Accessed November, 2015, http://cbrim.er.usgs.gov/). A comparison to an alternative regression‐based model for evaluating nutrient flux, ESTIMATOR, suggested that WRTDS can produce more accurate trend estimates (Moyer et al ., ). As opposed to WRTDS, GAMs were initially developed in a more general context as a modification to generalized linear models to model a response variable as the sum of smoothing functions of different predictors (Hastie and Tibshirani, ; Wood, ).…”

Section: Introductionmentioning

confidence: 99%

Numerical and Qualitative Contrasts of Two Statistical Models for Water Quality Change in Tidal Waters

Beck

Murphy

2016

J American Water Resour Assoc

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Two statistical approaches, weighted regression on time, discharge, and season and generalized additive models, have recently been used to evaluate water quality trends in estuaries. Both models have been used in similar contexts despite differences in statistical foundations and products. This study provided an empirical and qualitative comparison of both models using 29 years of data for two discrete time series of chlorophyll‐a (chl‐a) in the Patuxent River estuary. Empirical descriptions of each model were based on predictive performance against the observed data, ability to reproduce flow‐normalized trends with simulated data, and comparisons of performance with validation datasets. Between‐model differences were apparent but minor and both models had comparable abilities to remove flow effects from simulated time series. Both models similarly predicted observations for missing data with different characteristics. Trends from each model revealed distinct mainstem influences of the Chesapeake Bay with both models predicting a roughly 65% increase in chl‐a over time in the lower estuary, whereas flow‐normalized predictions for the upper estuary showed a more dynamic pattern, with a nearly 100% increase in chl‐a in the last 10 years. Qualitative comparisons highlighted important differences in the statistical structure, available products, and characteristics of the data and desired analysis.

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Comparison of two regression-based approaches for determining nutrient and sediment fluxes and trends in the Chesapeake Bay watershed

Cited by 36 publications

References 9 publications

An improved method for interpretation of riverine concentration‐discharge relationships indicates long‐term shifts in reservoir sediment trapping

An improved method for interpretation of riverine concentration‐discharge relationships indicates long‐term shifts in reservoir sediment trapping

Change in nutrient loading pattern due to coupled effect of change in concentration and hydroclimatic forces

Numerical and Qualitative Contrasts of Two Statistical Models for Water Quality Change in Tidal Waters

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