A spatially referenced water and nitrogen management model (WNMM) for (irrigated) intensive cropping systems in the North China Plain

Abstract

A spatially referenced biophysical model, the water and nitrogen management model (WNMM), was developed and shown to simulate dynamic soil water movement and soil–crop carbon (C) and nitrogen (N) cycling under a given agricultural management, for the purpose of identifying optimal strategies for managing water and fertiliser N under intensive cropping systems (mainly wheat–maize) in the North China Plain and other regions in the world. A uniform data structure, ARC GRID ASCII format, was used both in GIS and WNMM for achieving a close Model-GIS coupling. A significant part of WNMM adopts and modifies concepts and components from widely used models, with a focus on soil N transformations. WNMM simulates the key processes of water dynamics in the surface and subsurface of soils: including evapotranspiration, canopy interception, water movement and groundwater fluctuations; heat transfer and solute transport; crop growth; C and N cycling in the soil–crop system; and agricultural management practices (crop rotation, irrigation, fertiliser application, harvest and tillage). The model runs on a daily time step at any desired scale and is driven by lumped variables (meteorological and crop biological data) in text data format, and spatial variables (soil and agricultural management) in ARC GRID ASCII format. In particular, WNMM simulates all key N transformations in agricultural fields, including mineralisation of fresh crop residue N and soil organic N, formation of soil organic N, immobilisation in biomass, nitrification, ammonia (NH 3) volatilisation, denitrification and nitrous oxide (N 2O) emissions. WNMM has been successfully applied in Fengqiu County, Henan Province and Luancheng County, Hebei Province, China at site and regional scales. The key WNMM components were intensively calibrated and verified against comprehensive field measurements of soil water content, evapotranspiration, crop leaf area index and yield, NH 3 volatilisation, denitrification and N 2O emissions as well as nitrate (NO 3 −)–N concentrations in the soil solution. A sensitivity analysis showed that WNMM was sensitive to changes in meteorological variables, soil hydraulic properties, land use and agricultural management. At the site scale, WNMM simulated well soil water content, crop growth and yield, NH 3 volatilisation and soil NO 3 −–N concentration. There was uncertainty in simulating soil denitrification and N 2O emissions, when the predicted peaks of denitrification and N 2O emissions at very wet conditions could not be confirmed because of limitations in the acetylene-inhibition method for measuring denitrification. At county scale, WNMM simulation of crop yield in Fengqiu County explained 22% of the variation in observed crop yields, and 31% of crop yield variation in Luancheng County where soil variation was less. These results are considered acceptable because factors such as soil salinity and other nutrient deficiencies, which have not been considered in this version of WNMM, may play a role. The source code for the WNMM is available on request.