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Influence of sampling frequency and load calculation methods on quantification of annual river nutrient and suspended solids loads

  • Ahmed Elwan
  • Ranvir Singh
  • Maree Patterson
  • Jon Roygard
  • Dave Horne
  • Brent Clothier
  • Geoffrey Jones
Article
  • 695 Downloads

Abstract

Better management of water quality in streams, rivers and lakes requires precise and accurate estimates of different contaminant loads. We assessed four sampling frequencies (2 days, weekly, fortnightly and monthly) and five load calculation methods (global mean (GM), rating curve (RC), ratio estimator (RE), flow-stratified (FS) and flow-weighted (FW)) to quantify loads of nitrate-nitrogen (NO3–N), soluble inorganic nitrogen (SIN), total nitrogen (TN), dissolved reactive phosphorus (DRP), total phosphorus (TP) and total suspended solids (TSS), in the Manawatu River, New Zealand. The estimated annual river loads were compared to the reference ‘true’ loads, calculated using daily measurements of flow and water quality from May 2010 to April 2011, to quantify bias (i.e. accuracy) and root mean square error ‘RMSE’ (i.e. accuracy and precision). The GM method resulted into relatively higher RMSE values and a consistent negative bias (i.e. underestimation) in estimates of annual river loads across all sampling frequencies. The RC method resulted in the lowest RMSE for TN, TP and TSS at monthly sampling frequency. Yet, RC highly overestimated the loads for parameters that showed dilution effect such as NO3-N and SIN. The FW and RE methods gave similar results, and there was no essential improvement in using RE over FW. In general, FW and RE performed better than FS in terms of bias, but FS performed slightly better than FW and RE in terms of RMSE for most of the water quality parameters (DRP, TP, TN and TSS) using a monthly sampling frequency. We found no significant decrease in RMSE values for estimates of NO3N, SIN, TN and DRP loads when the sampling frequency was increased from monthly to fortnightly. The bias and RMSE values in estimates of TP and TSS loads (estimated by FW, RE and FS), however, showed a significant decrease in the case of weekly or 2-day sampling. This suggests potential for a higher sampling frequency during flow peaks for more precise and accurate estimates of annual river loads for TP and TSS, in the study river and other similar conditions.

Keywords

Uncertainty Load estimation methods Nutrients Suspended solids Water quality Water resources management 

Notes

Acknowledgments

We are grateful to the reviewer for the constructive feedback and suggestions that improved the manuscript. This study is part of a collaborative project between Institute of Agriculture and Environment, Fertiliser and Lime Research Centre (FLRC), Massey University, and Horizons Regional Council (HRC). This project is partially funded by HRC. The authors thank HRC for the financial support and providing the flow and water quality datasets used in this study.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute of Agriculture and Environment (IAE)Massey UniversityPalmerston NorthNew Zealand
  2. 2.Horizons Regional CouncilPalmerston NorthNew Zealand
  3. 3.Plant and Food ResearchPalmerston NorthNew Zealand
  4. 4.Institute of Fundamental SciencesMassey UniversityPalmerston NorthNew Zealand

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