*2.4. Model Parameterisation*

The process of parameterisation is illustrated in Figure 3. The vegetative stage of lettuce refers to the growing period of lettuce growth after germination until harvest. A growing period during the vegetative stage of 59 days after transplanting was simulated in this study.

**Figure 3.** Flow chart of parameterisation of AquaCrop in this study (adjusted from [76]). T is temperature, ETo is potential evapotranspiration, gs is stomatal conductance, WP is water productivity coefficient, Ks is stress coefficient, Es is soil temperature, Tr is crop transpiration.

As lettuce is a crop which is not yet parameterised in AquaCrop, calibration of the model involved adjusting the model parameters to make them match the observed data [54,77].

The primary variables of lettuce growth, e.g., canopy cover and aboveground biomass were parameterised. For the calibration of the curves, the measured data in two experimental fields at the Chearov site (S1) (having sand soil) and Ourong site (S2) (with loam soil) were used, during the growing season in 2017. The AquaCrop model does not allow the use of observed data to build the canopy cover and biomass curves, but allows the data to be used to calibrate the canopy cover and biomass curves [78].

Canopy cover curves are a plot of the development of leaf expansion response to growing time per day, based on Equation (1). Biomass curves are a relationship plot of the growth of lettuce biomass response to growing time per day, based on Equation (4). The calibration of simulated canopy and biomass curves is based on one-at-a-time (OAT) methods (i.e., changing one parameter at a time while holding others constant) [79] and adjusting the parameters by trial and error, by comparing simulated and observed field data, and minimising the function of root mean square error.

We parameterised the canopy cover curve, which is important to the model for transpiration and evaporation [78]. The main parameters of Equation (1), e.g., CCo and CGC for canopy cover curve determination, were adjusted to match the observed canopy cover data. In addition, adjusting the maximum canopy cover (CCx), time to reach maximum canopy cover, and time to recover, is crucial in order to obtain correct simulations of canopy cover growth. Subsequently, the focus was on adjusting the biomass curve of Equation (4). WP\* and KcTr,x (coefficient for maximum crop transpiration) are the main parameters for regulating biomass curves in AquaCrop [74]. As lettuce is a C3 crop type [80], the recommended values for WP\* lie between 15 and 20 g m−2. All calibrated crop parameters are shown in Table 3.



The model performance for canopy cover and biomass simulation was evaluated using statistic indicators, including root mean square error (RMSE), Nash–Sutcliffe coefficient (N), and coefficient of determination (*R*2), defined as below.

$$\text{RMSE} = \sqrt{\frac{\sum\_{i=1}^{n} \left(\mathbf{O\_i} - \mathbf{S\_i}\right)^2}{n}} \tag{5}$$

$$\text{IN} = 1 - \frac{\sum\_{i=1}^{n} \left(\text{O}\_{\text{i}} - \text{S}\_{\text{i}}\right)^{2}}{\sum\_{i=1}^{n} \left(\text{O}\_{\text{i}} - \text{D}\right)^{2}} \tag{6}$$

$$\mathcal{R}^2 = \left(\frac{\sum\_{i=1}^n \left(\mathbf{O\_i} - \overline{\mathbf{O}}\right) \left(\mathbf{O\_i} - \overline{\mathbf{S}}\right)}{\sqrt{\sum\_{i=1}^n \left(\mathbf{O\_i} - \overline{\mathbf{O}}\right)^2 \sum\_{i=1}^n \left(\mathbf{O\_i} - \overline{\mathbf{S}}\right)^2}}\right)^2\tag{7}$$

where O and S are the observed and simulated values at time i, respectively, and n is the total amount of the data. When N and R2 are close to 1, it is considered to be satisfactory [81]. RMSE should be close to 0. *Water* **2018**, *10*, 666

AquaCrop requires the selection of inputs related to the irrigation method, such as sprinkler, drip, or surface. These methods determine the fraction of the soil surface made wet by irrigation [82] and the impact on irrigation efficiency [83].

Default AquaCrop settings for field management include mulching, and use an adjusted factor for the effect of mulches on soil evaporation. It varied between 0.5 for mulches derived from plant material, and 1.0 for plastic mulch [75].

The drip irrigation method with plastic mulch was applied as the input for field management in the model during the parameterisation, as this is the actual practice of the experiment in this study.

The soil water balance calculation, including soil moisture simulation in AquaCrop, is based on the storage capacity of the soil layers, described in Raes et al. [84], and previously in the BUDGET model [85].

During the experimental period, water ponding at 15 cm and 20 cm below the bed soil at site S1 and S2 respectively, which was observed during the experiment, was taken into account as a boundary condition during the parameterisation of the model. This water ponding resulted in wet soil during the growing period. The values of physical soil available data in the Section 2.2.2 were adopted to simulate soil moisture in this study.

It was noted that the plantation experiment was during the rainy season when irrigation was not needed. The crop parameters obtained after parameterisation are important for the investigation of the irrigation scenarios for water saving when irrigation is necessary, especially during the dry season.
