An integrated soil-crop system model for water and nitrogen management in North China

Abstract

An integrated model WHCNS (soil Water Heat Carbon Nitrogen Simulator) was developed to assess water and nitrogen (N) management in North China. It included five main modules: soil water, soil temperature, soil carbon (C), soil N, and crop growth. The model integrated some features of several widely used crop and soil models, and some modifications were made in order to apply the WHCNS model under the complex conditions of intensive cropping systems in North China. The WHCNS model was evaluated using an open access dataset from the European International Conference on Modeling Soil Water and N Dynamics. WHCNS gave better estimations of soil water and N dynamics, dry matter accumulation and N uptake than 14 other models. The model was tested against data from four experimental sites in North China under various soil, crop, climate, and management practices. Simulated soil water content, soil nitrate concentrations, crop dry matter, leaf area index and grain yields all agreed well with measured values. This study indicates that the WHCNS model can be used to analyze and evaluate the effects of various field management practices on crop yield, fate of N, and water and N use efficiencies in North China.

Figure 1. The conception framework of the WHCNS model.

Figure 2

Sensitivity analysis of each parameters of WHCNS model for soil water content (a), NO₃⁻-N (b), NH₄⁺-N (c), LAI (d), dry matter (e) and yield (f). K_s, saturated hydraulic conductivity; θ_s, saturated water content; θ_r, residual water content; α, the inverse of the air-entry value; n, pore size distribution index; V_n^*, maximum nitrification rate; K_n, half saturation constant; K_d, an empirical proportionality factor; α_d^*, empirical coefficient; K_v, first order kinetic constant of volatilization; T_sum, accumulated available temperature; K_ini, K_mid, K_end donote crop coefficients at initial, middle and end stages, respectively; SLA_maxand SLA_min, denote maximum and minimum specific leaf area,respectively; AMAX, the maximum assimilation rate; R_max, maximum root depth.

Figure 3. Comparison of simulated (solid lines) and measured (cycles) volumetric soil water content (cm³ cm⁻³) at different depths for T1 at Müncheberg site.

Figure 4. Comparison of simulated (solid lines) and measured (cycles ) soil nitrate N concentration (mg kg⁻¹) at different depths for T1 at Müncheberg site.

Figure 5. Comparison of simulated (solid lines) and measured (cycles) soil ammonium N concentration (mg kg⁻¹) at different depths for T1 at Müncheberg.

Figure 6. Comparison of simulated (solid lines) and measured (cycles) total dry matter for the three treatments at Müncheberg.

Figure 7. Comparison of simulated (solid lines) and measured (cycles) N-uptake by plant for three treatments at Müncheberg.

Figure 8. Simulated and measured gravimetric soil water contents in 0–90 cm for T1 for different models at Müncheberg (ExN.xxx = Expert-N + crop model).

Figure 9. Simulated and measured soil mineral nitrogen in 0–90 cm for T1 for different models at Müncheberg (ExN.xxx = Expert-N + crop model).

Figure 10. Simulated and measured N uptake by crops for T1 for different models at Müncheberg (ExN.xxx = Expert-N + crop model).

Figure 11

The relationship between simulated and measured soil volumetric water content (SWC, ‘’,cm3 cm⁻³), soil nitrate concentration (SNC, ‘’, kg ha^-1), crop dry mass (DM,‘’, kg ha⁻¹) and leaf area index (LAI, ‘’) for WHCNS model in North China.

Figure 12. The relationship between simulated and measured crop yield in four sites for the WHCNS model in North China.

Figure 13. Distribution of simulated and measured yields for different crops for the WHCNS model in North China (Obs, Observed; Sim, Simulated; WW, Winter Wheat; SM, Summer Maize; SPM, Spring Maize).