TY - JOUR
T1 - Soil-climate contribution to DNDC model uncertainty in simulating biomass accumulation under urban vegetable production on a Petroplinthic Cambisol in Tamale, Ghana
AU - Budiman, Budiman
AU - Christoph, Steiner
AU - Topp, CFE
AU - Andreas, Buerkert
PY - 2020/6/1
Y1 - 2020/6/1
N2 - Crop yield simulation using the Denitrification–Decomposition (DNDC) model can help to understand key bottlenecks for improved nitrogen (N) use efficiency and estimate greenhouse gas (GHG) emissions in West African urban vegetable production. The DNDC model was successfully calibrated using high-resolution weather records, information on management practices and soils, and measured biomass accumulation and N uptake by amaranth (Amaranthus L.), jute mallow (Corchorus olitorius L.), lettuce (Lactuca sativa L.), and roselle (Hibiscus sabdariffa L.) for different input intensities (May 2014–November 2015) in urban vegetable production of Tamale (N-Ghana, West Africa). The root mean square error (RMSE) and relative error (E) values fell within the confidence interval (α 5%) of the measurements, and there was a high correlation (0.91 to 0.98) between measurements and predictions. However, the analysis of uncertainty and factor importance indicated that soil properties (pH, SOC, and clay content) and weather (precipitation) variability contributed highly to yield uncertainty of vegetable biomass.
AB - Crop yield simulation using the Denitrification–Decomposition (DNDC) model can help to understand key bottlenecks for improved nitrogen (N) use efficiency and estimate greenhouse gas (GHG) emissions in West African urban vegetable production. The DNDC model was successfully calibrated using high-resolution weather records, information on management practices and soils, and measured biomass accumulation and N uptake by amaranth (Amaranthus L.), jute mallow (Corchorus olitorius L.), lettuce (Lactuca sativa L.), and roselle (Hibiscus sabdariffa L.) for different input intensities (May 2014–November 2015) in urban vegetable production of Tamale (N-Ghana, West Africa). The root mean square error (RMSE) and relative error (E) values fell within the confidence interval (α 5%) of the measurements, and there was a high correlation (0.91 to 0.98) between measurements and predictions. However, the analysis of uncertainty and factor importance indicated that soil properties (pH, SOC, and clay content) and weather (precipitation) variability contributed highly to yield uncertainty of vegetable biomass.
KW - West Africa
KW - carbon–nitrogen modelling
KW - factor importance
KW - horticulture
KW - urban agriculture
UR - http://www.scopus.com/inward/record.url?scp=85082181123&partnerID=8YFLogxK
U2 - 10.1002/jpln.201900514
DO - 10.1002/jpln.201900514
M3 - Article
SN - 1436-8730
VL - 183
SP - 306
EP - 315
JO - Journal of Plant Nutrition and Soil Science
JF - Journal of Plant Nutrition and Soil Science
IS - 3
ER -