- Tytuł:
- Field validation of DNDC and SWAP models for temperature and water content of loamy and sandy loam Spodosols
- Autorzy:
-
Balashov, E.
Buchkina, N.
Rizhiya, E.
Farkas, C. - Powiązania:
- https://bibliotekanauki.pl/articles/972349.pdf
- Data publikacji:
- 2014
- Wydawca:
- Polska Akademia Nauk. Instytut Agrofizyki PAN
- Tematy:
-
field validation
agroecosystem
modelling
soil water content
soil temperature
DNDC model
SWAP model
temperature
water content
loamy sand
sandy loam
Spodosol - Opis:
- The objectives of the research were to: fulfil the preliminary assessment of the sensitivity of the soil, water, atmosphere, and plant and denitrification and decomposition models to variations of climate variables based on the existing soil database; validate the soil, water, atmosphere, and plant and denitrification and decomposition modelled outcomes against measured records for soil temperature and water content. The statistical analyses were conducted by the sensitivity analysis, Nash-Sutcliffe efficiency coefficients and root mean square error using measured and modelled variables during three growing seasons. Results of sensitivity analysis demonstrated that: soil temperatures predicted by the soil, water, atmosphere, and plant model showed a more reliable sensitivity to the variations of input air temperatures; soil water content predicted by the denitrification and decomposition model had a better reliability in the sensitivity to daily precipitation changes. The root mean square errors and Nash-Sutcliffe efficiency coefficients demonstrated that: the soil, water, atmosphere, and plant model had a better efficiency in predicting seasonal dynamics of soil temperatures than the denitrification and decomposition model; and among two studied models, the denitrification and decomposition model showed a better capability in predicting the seasonal dynamics of soil water content.
- Źródło:
-
International Agrophysics; 2014, 28, 2
0236-8722 - Pojawia się w:
- International Agrophysics
- Dostawca treści:
- Biblioteka Nauki