Modelling agro-environmental variables under data availability limitations and scenario managements in an alluvial region of the North China Plain. (January 2019)

• Record Type: Journal Article
• Authors: Manevski, Kiril; Børgesen, Christen D.; Li, Xiaoxin; Andersen, Mathias N.; Zhang, Xiying; Shen, Yanjun; Hu, Chunsheng
• Is Part Of: Environmental modelling & software. Volume 111(2019)
• Page Start: 94
• Page End: 107
• Publication Date: 2019-01
• Subjects: Crop yields -- Drainage -- Environmental geology -- Mathematical model -- Nitrogen leaching -- Soil classification; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2018.10.001
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Single or multiple weather station data were combined with soil textural data ranging from low to high detail, i.e., point data from a field station, the FAO Digital Soil Map of the World and a comprehensive data from national soil survey, as input to the Daisy model to simulate and upscale crop yields, drainage and nitrogen leaching for an agroecosystem in the North China Plain. Increasing the detail of the weather data increased the spatial variation of all simulated variables and decreased their regional median. Regional crop yields were simulated well with high-detail input data, though at a weak response to data detail. Simulated regional drainage and nitrogen leaching, and their spatial variability, however, responded well and increased two-to threefold, but their regional medians were similar for medium- and high-detail soil data. This work demonstrates the importance of explicit consideration of weather and soil variability for agro-environmental simulation studies at regional scale. Graphical abstract: Image 1 Highlights: Crop yield, drainage and nitrogen leaching were modelled for North China Plain region. Pedotransfer functions are good support for regional application of field-scale model. Increased input data detail decreased the median of simulated regional variables. Increased input data detail increased variability/spatialisation of simulated regional variables. Careful choice of model input data is needed for regions with low data quality/quantity.