Evaluation of various meteorological datasets in estimation yield and actual evapotranspiration of wheat and maize (case study: Qazvin plain)

Precipitation (P) and temperature (T) are important factors in agricultural studies, water resources, and ecosystems. Therefore, their accurate measurement and estimation are very important. In this study, GLDAS-AgMERRA, GLDAS-CRU, GLDAS-AgCFSR networked meteorological datasets were evaluated in estimating the yield and actual evapotranspiration (ETa) of wheat and maize plants and comparing them with Qazvin Synoptic Station information. For this purpose, the Qazvin Synoptic Station information from 1980 to 2010 and the climatic information of the mentioned sets was extracted for six scenarios (S1: P and potential evapotranspiration (ETp) of GLDAS-T of CRU,S2: P and ETP of GLDAS-T of AgMERRA, S3: P of GLDAS- T and ETP of CRU, S4: P of GLDAS- T and ETP of AgMERRA, S5: P and ETP of GLDAS- T of AgCFSR, S6: P of GLDAS- T and ETp of AgCFSR). These dataset’s data quality was evaluated using R2, NRMSE, and ME statistical parameters with Aqua Crop model outputs. The calculated statistical parameters showed that in estimating the yield of the simulated wheat plant using Scenario 2 and 4, for maize, scenarios 1 and 3 were better correlated with other scenarios. In terms of ETa, Scenario 3 for maize and Scenario 6 for wheat were better correlated. The results show that accurately networked meteorological datasets can be used to estimate crop yields.