TY - JOUR
T1 - Development of statistical models for estimating daily nitrate load in Iowa
AU - Ayers, Jessica R.
AU - Villarini, Gabriele
AU - Schilling, Keith
AU - Jones, Christopher
N1 - Funding Information:
This study was supported in part by the National Science Foundation under grant number DGE 1633098 , and by Iowa State University under Iowa Development Authority Award No. 13-NDRP-016 through funding from the U.S. Department of Housing and Urban Development. The suggestions by seven anonymous reviewers are gratefully acknowledged.
Publisher Copyright:
© 2021
PY - 2021/8/15
Y1 - 2021/8/15
N2 - There is an ongoing need to increase our understanding of the sources and timing of stream nitrate loads across agricultural watersheds in Iowa as water quality improvement strategies are implemented. The goal of this study was to model the relationship between nitrate load and the two components of streamflow (i.e., baseflow and stormflow) to quantify in-stream nitrate patterns and develop a new method for estimating loads on days when monitoring data are not available. We analyzed eight watersheds in Iowa that had long-term water quality data where grab samples have been collected from 1987 to 2019. Four regression models were developed that related daily nitrate load to daily baseflow, stormflow, and streamflow discharge. The first model considered baseflow as a predictor, the second model used stormflow, the third model included both baseflow and stormflow as two different covariates, and the final model used total streamflow (unseparated). For all eight watersheds, the baseflowstormflow models had the highest correlation coefficients, which indicates that both components are necessary and together improve nitrate load estimates. While baseflow models estimated lower nitrate loads better, stormflow models captured the variability associated with larger loads. In addition, streamflow models tended to overestimate large nitrate loads. This simple modeling framework can be used to calculate daily, monthly and annual nitrate loads. Delineating nitrate loads between stormflow and baseflow can help identify differences in nitrate sources for nutrient reduction and remediation.
AB - There is an ongoing need to increase our understanding of the sources and timing of stream nitrate loads across agricultural watersheds in Iowa as water quality improvement strategies are implemented. The goal of this study was to model the relationship between nitrate load and the two components of streamflow (i.e., baseflow and stormflow) to quantify in-stream nitrate patterns and develop a new method for estimating loads on days when monitoring data are not available. We analyzed eight watersheds in Iowa that had long-term water quality data where grab samples have been collected from 1987 to 2019. Four regression models were developed that related daily nitrate load to daily baseflow, stormflow, and streamflow discharge. The first model considered baseflow as a predictor, the second model used stormflow, the third model included both baseflow and stormflow as two different covariates, and the final model used total streamflow (unseparated). For all eight watersheds, the baseflowstormflow models had the highest correlation coefficients, which indicates that both components are necessary and together improve nitrate load estimates. While baseflow models estimated lower nitrate loads better, stormflow models captured the variability associated with larger loads. In addition, streamflow models tended to overestimate large nitrate loads. This simple modeling framework can be used to calculate daily, monthly and annual nitrate loads. Delineating nitrate loads between stormflow and baseflow can help identify differences in nitrate sources for nutrient reduction and remediation.
KW - Baseflow
KW - Discharge
KW - Nitrate load
KW - Statistical modeling
KW - Stormflow
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U2 - 10.1016/j.scitotenv.2021.146643
DO - 10.1016/j.scitotenv.2021.146643
M3 - Article
C2 - 33838365
AN - SCOPUS:85103967323
SN - 0048-9697
VL - 782
JO - Science of the Total Environment
JF - Science of the Total Environment
M1 - 146643
ER -