Performance Study of SPAW Model with Temperature-Derived ${\mathrm{ET}}_0$ as Input in Place of Pan Evaporation under Wheat Crop in a Semiarid Subtropical Climate

In this study, we have attempted to enhance the utility of soil–plant–atmosphere–water (SPAW) model that has been used successfully by various workers in different countries for soil moisture prediction under different cropping conditions. One of the major climatic inputs for SPAW model is pan evaporation, which in many places is not readily available. To address the above, and to get the benefit of this model in regions characterized by limited weather data availability, this study was undertaken using computed ${\mathrm{ET}}_0$ from air temperature by the 1985 Hargreaves equation, as one of the inputs in place of pan evaporation. For the purpose, actual air temperature collected from experimental farm area, as well as forecast air temperature collected from National Centre for Medium Range Weather Forecasting, Government of India, were used. First, the SPAW model was calibrated and its performance was evaluated under wheat, taking layerwise and profile soil moisture as the variables for comparison between the predicted and observed values. The results showed that the root-mean-square error (RMSE) varied from $0.30\text{to}0.58\mathrm{cm}$ for measured values ranging between 2.24 and $4.25\mathrm{cm}$ . The index of agreement $\left(d\right)$ varied from 0.81 to 0.92 and coefficient of determination $\left(r^2\right)$ from 0.46 to 0.73 for 0–15, 15–30, 30–45, and $45–60\mathrm{cm}$ soil depths. For the whole $60\mathrm{cm}$ profile, the RMSE was $1.07\mathrm{cm}$ with $d$ and $r^2$ values of 0.94 and 0.85 respectively. The RMSE and $d$ varied from $0.36\text{to}0.63\mathrm{cm}$ and 0.77 to 0.89 respectively when ${\mathrm{ET}}_0$ computed from actual air temperature was used in place of pan evaporation, where as when ${\mathrm{ET}}_0$ computed from forecast air temperature data was used, the corresponding values were $0.35–0.64\mathrm{cm}$ and 0.68–0.85 respectively for the four soil layers. There was a tendency of the models to underestimate when the computed ${\mathrm{ET}}_0$ was used as input in place of pan evaporation. In general, performance of the models were better at lower depths.