Co-Kriging Estimation of Nitrate-Nitrogen Loads in an Agricultural River

Xiuyu Liang, Keith Schilling, You-Kuan Zhang () and Christopher Jones
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Xiuyu Liang: Nanjing University
Keith Schilling: University of Iowa
You-Kuan Zhang: Nanjing University
Christopher Jones: Iowa Soybean Association

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2016, vol. 30, issue 5, No 12, 1784 pages

Abstract: Abstract Daily nitrate-nitrogen (NO3-N) loads in the Raccoon River, Iowa, were estimated using Ordinary kriging (OK), Cokriging (CK), and a standard rating curve method (LOADEST) based on a dataset of 3451 measurements of NO3-N concentration collected over 19 years. The CK estimation utilizes the temporal correlation of NO3-N load with daily discharge and honors the measured points to improve estimation relative to regression based models. Loads were estimated using the observed concentrations and three subsets of the measured data that correspond to three frequencies (weekly, biweekly, and monthly). Results indicated that daily NO3-N loads were best estimated by CK using measured loads with daily discharge. Daily load estimates produced by OK using weekly data matched well with measured values, but discrepancies emerged when samples were collected less frequently, e.g., biweekly and monthly. For the entire 19-year dataset, compared to measured loads, the estimated total NO3-N load decreased using OK when samples were collected monthly, but increased using CK. Load estimation using the seven-parameter LOADEST model did not perform well for the Raccoon River because the correlation of NO3-N concentration to river discharge was poor. For the site studied, weekly and biweekly sampling may be sufficient to estimate daily NO3-N loads with CK when daily discharge data is available.

Keywords: Daily nitrate-nitrogen (NO3-N) load; Cokriging; Sampling frequency (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s11269-016-1250-9

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