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Uncertainty in simulated nitrate leaching due to uncertainty in input data. A case study
Author(s) -
Hansen S.,
Thorsen M.,
Pebesma E.J.,
Kleeschulte S.,
Svendsen H.
Publication year - 1999
Publication title -
soil use and management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.709
H-Index - 81
eISSN - 1475-2743
pISSN - 0266-0032
DOI - 10.1111/j.1475-2743.1999.tb00083.x
Subject(s) - latin hypercube sampling , arable land , leaching (pedology) , environmental science , uncertainty analysis , monte carlo method , soil science , agriculture , sampling (signal processing) , nitrate , statistics , agricultural land , mathematics , econometrics , hydrology (agriculture) , computer science , soil water , geography , engineering , ecology , geotechnical engineering , archaeology , filter (signal processing) , biology , computer vision
. Deterministic leaching models are used to estimate regional losses of nitrate from agricultural land to the environment. The estimated leaching losses are associated with uncertainty arising from uncertainty in the input data used. In the present case study we have assessed this uncertainty by use of Monte Carlo analysis, using the Latin hypercube sampling technique. Input data have preferably been adopted from publicly available data. Data which could not be retrieved from the databases was assessed by guided estimates or based on local data. The estimated annual leaching loss from the study region was around 106 kg N ha −1 , which is in agreement with previous findings. The uncertainty in the leaching expressed in terms of coefficients of variation (CV) depended on the agricultural practices. CV's for arable farm rotations, cattle farm rotations, and pig farm rotations were around 20, 30 and 40%, respectively. Breakdown of the total uncertainty into contributions of different error sources did not isolate one single all important source.