Abstract
The loss of nitrogen from fertilised soils in the form of nitrous oxide (N2O) is a side effect of modern
agriculture and the focus of many model-based studies. Due to the spatial and temporal heterogeneity of
soil N2O emissions, the measured data can introduce limitations to the use of those statistical methods
that are most commonly employed in the evaluation of model performance. In this paper, we describe
these limitations and present an algorithm developed to address them. We implement the algorithm
using simulated and measured N2O data from two UK arable sites. We show that possible time lags
between the measured and simulated data can affect model evaluation and that their consideration in
the evaluation process can reduce measures such as the Mean Squared Error (MSE) by 30%. We also
analyse the algorithm's results to identify patterns in the estimated lags and to narrow down their
possible causes.
Original language | English |
---|---|
Pages (from-to) | 251 - 262 |
Number of pages | 12 |
Journal | Environmental Modelling and Software |
Volume | 84 |
Early online date | 15 Jul 2016 |
DOIs | |
Publication status | First published - 15 Jul 2016 |
Bibliographical note
1030795Keywords
- Agro-ecosystems
- Model evaluation
- Nitrous oxide
- Soil modelling
- Time lag