Use of a Bayesian isotope mixing model to estimate proportional contributions of multiple nitrate sources in surface water.
To identify different NO(3)(-) sources in surface water and to estimate their proportional contribution to the nitrate mixture in surface water, a dual isotope and a Bayesian isotope mixing model have been applied for six different surface waters affected by agriculture, greenhouses in an agricultural area, and households. Annual mean δ(15)N-NO(3)(-) were between 8.0 and 19.4‰, while annual mean δ(18)O-NO(3)(-) were given by 4.5-30.7‰. SIAR was used to estimate the proportional contribution of five potential NO(3)(-) sources (NO(3)(-) in precipitation, NO(3)(-) fertilizer, NH(4)(+) in fertilizer and rain, soil N, and manure and sewage). SIAR showed that "manure and sewage" contributed highest, "soil N", "NO(3)(-) fertilizer" and "NH(4)(+) in fertilizer and rain" contributed middle, and "NO(3)(-) in precipitation" contributed least. The SIAR output can be considered as a "fingerprint" for the NO(3)(-) source contributions. However, the wide range of isotope values observed in surface water and of the NO(3)(-) sources limit its applicability.
Laboratory of Applied Physical Chemistry - ISOFYS, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000 Ghent, Belgium. dongmei.xue@ugent.be
Dongmei
D
Xue
Bernard
B
De Baets
Oswald
O
Van Cleemput
Carmel
C
Hennessy
Michael
M
Berglund
Pascal
P
Boeckx
D001499:Bayes Theorem; D004784:Environmental Monitoring / Q000379:methods*; D005618:Fresh Water / Q000737:chemistry*; D008956:Models, Chemical; D009566:Nitrates / Q000032:analysis* / Q000737:chemistry; D014874:Water Pollutants, Chemical / Q000032:analysis* / Q000737:chemistry
D009566:Nitrates; D014874:Water Pollutants, Chemical