Can the agricultural AquaCrop model simulate water use and yield of a poplar short-rotation coppice?

Abstract

We calibrated and evaluated the agricultural model AquaCrop for the simulation of water use and yield of a short-rotation coppice (SRC) plantation with poplar (Populus) in East Flanders (Belgium) during the second and the third rotation (first 2 years only). Differences in crop development and growth during the course of the rotations were taken into account during the model calibration. Overall, the AquaCrop model showed good performance for the daily simulation of soil water content (R² of 0.57-0.85), of green canopy cover (R² > 0.87), of evapotranspiration (ET; R² > 0.76), and of potential yield. The simulated, total yearly water use of the SRC ranged between 55% and 85% of the water use of a reference grass ecosystem calculated under the same environmental conditions. Crop transpiration was between 67% and 93% of total ET, with lower percentages in the first than in the second year of each rotation. The observed (dry mass) yield ranged from 6.61 to 14.76 Mg ha^-1 yr^-1. A yield gap of around 30% was observed between the second and the third rotation, as well as between simulated and observed yield during the third rotation. This could possibly be explained by the expansion of the understory (weed) layer; the relative cover of understory weeds was 22% in the third year of the third rotation. The agricultural AquaCrop model simulated total water use and potential yield of the operational SRC in a reliable way. As the plantation was extensively managed, potential effects of irrigation and/or fertilization on ET and on yield were not considered in this study.

Keywords: POPFULL; Populus; bioenergy; harvestable biomass prediction; soil water content; yield gap.

Figure 1

Schematic representation of the crop structure during the three rotations of the short‐rotation poplar plantation in East Flanders (Belgium). A short description of each year of the first rotation (2010–2011; R1.1–R1.2) and of the second rotation (2012–2013; R2.1–R2.2) and the first 2 years of the third rotation (2014–2015; R3.1–R3.2), in terms of habitus, start of the growing season and observed yield, is also presented.

Figure 2

Observed (obs) precipitation (Pr) and calculated reference evapotranspiration of a well‐watered grassland (ET₀) (top panel row); calculated (from leaf area index (LAI) measurements) and simulated (sim) canopy cover (CC) (second panel row); observed and simulated soil water content (SWC) in the upper 0.3 m of the soil and observed soil water table depth (SWT) (third panel row); and observed and simulated evapotranspiration (ET), and simulated transpiration (Tr) (bottom panel row) for R2 and the first 2 years of R3 of the short‐rotation coppice plantation. For explanations of R2.1, R2.2, R3.1, and R3.2, see Fig. 1.

Figure 3

Simulated values of the daily soil water content (SWC) and evapotranspiration (ET) against observed values for all years. For explanations of R2.1, R2.2, R3.1, and R3.2, see Fig. 1. Grey, dotted lines show the 1 : 1 line.

Figure 4

Smoothed spline curves of observed (obs) daily evapotranspiration (ET) values with the (unsmoothed) daily random measurement error (RME), and the smoothed simulated (sim) daily ET values for the 2 years of R2 and the first 2 years of R3. For explanations of R2.1, R2.2, R3.1 and R3.2, see Fig. 1.

Figure 5

Energy balance closure for the 4 years of the study. Red lines are the linear regression lines. The regression equation between measured energy fluxes and available energy is also presented. For explanations of R2.1, R2.2, R3.1, and R3.2, see Fig. 1.